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ICUS Report 71

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����������������ICUS 東日本大震災関連記録集
（２）
目次
発表論文等

1.

中尾悠士, 沢田治雄：高分解能衛星データを用いた津波浸水域把握手法の開発（生産研究 64 巻 4 号（2012）） ············· 1

2.

越智士郎, 古関潤一, 宮下千花, 沢田治雄：高分解能衛星画像を利用した液状化噴砂地の抽出（生産研究 64 巻 4 号（2012）） ························ 63.

石川達也, 沢田治雄：
高解像度衛星画像を用いた液状化地帯判別の有効性（広域の環境・災害リスク情報の収集と利用フォーラム論文集，22,

4.

pp.21-28） ······················· 10

越智士郎, 石川達也, 宮下千花, 古関潤一, 沢田治雄, 李雲慶：
RapidEye 画像による液状化噴砂の検出手法の検討（広域の環境・災害リスク情報の収集と利用フォーラム論文集，22,

5.

pp.29-30） ······················· 18

Haruo SAWADA：
Review of activities on remote sensing for the Great Earthquake and tsunami in Japan（12p, 2012） ····· 20

6.

腰原幹雄：
東日本大震災における木造校舎の被害（生産研究 64 巻 4 号（2012）） ·········································· 32

7.

近藤伸也, 目黒公郎：
東日本大震災における関連学会の活動成果の評価（生産研究 64 巻 4 号（2012）） ······················ 38

8.

近藤伸也・目黒公郎：
東日本大震災から一年間における関連学会の活動動向分析（安全工学シンポジウム 2012 講演予稿集） ······················································································ 43

9.

澤田義人, 遠藤貴宏, 沼田宗純, 目黒公郎, 沢田治雄：
災害に関連したテキストデータの可視化手法の開発（生産研究 64 巻 4 号（2012））－東日本大震災関連報道記事の解析－ ································································································ 47

10. 沼田宗純, 目黒公郎：
Investigation on Fukushima Minpo Newspaper articles by running spectrum analysis（生産研究 64 巻 6 号（2012））············································································································ 55

11. 川崎昭如, ヘンリー マイケル, 目黒公郎：
東日本大震災後の外国人の災害情報収集過程

その１：日本人と外国人の情報収集比較分析（生産研究 64 巻 4 号（2012））············································································································ 63

12. 川崎昭如, ヘンリー マイケル, 目黒公郎：
東日本大震災後の外国人の災害情報収集過程

その２：退避行動の違いによる分析（生産研究 64 巻 4 号（2012））············································································································ 71

13. マイケル ヘンリー, 川崎昭如, 目黒公郎：
Foreigners' disaster information gathering behavior after the 2011 Tohoku Earthquake
part 3: analysis of foreign students considering their post-disaster action（生産研究 64 巻 4 号（2012））············································································································ 76

14. 川崎昭如，Henry, M., 目黒公郎：
言語能力の違いに着目した東日本大震災後の外国人の災害情報収集分析（地域安全学会論文集 No.18, 2012） ·································································································· 83

15. Henry, M., 川崎昭如, 目黒公郎：
東日本大震災後の外国人退避の意思決定と災害情報収集過程の関係（地域安全学会論文集 No.18, 2012） ·································································································· 93

16. 色田彩恵・加藤孝明・Maria Bernadet Karina DEWI, 松尾一郎, 度会清治, 関谷直也：
東日本大震災における被災住民の生活再建に関する潜在的な選択肢の調査（地域安全学会論文集 No.31, 2012） ································································································ 101

17. 塩崎由人, 加藤孝明：
自然災害と関連分野におけるレジリエンス，脆弱性の定義について（生産研究 64 巻 4 号（2012））·········································································································· 105

18. 山本了平, 大原美保, 目黒公郎：
東日本大震災における企業の緊急地震速報の利用状況に関する調査報告（生産研究 64 巻 6 号（2012））·········································································································· 109

19. 大原美保, 目黒公郎, 田中 淳：
全国で発表された緊急地震速報（警報）の地域傾向に関する分析（生産研究 64 巻 6 号（2012））·········································································································· 114

20. 大原美保, 牧之段浩平, 佐原孝紀：
津波避難場所および津波避難ビルの減災効果に関する一考察－宮城県南三陸町におけるケーススタディー－（生産研究 64 巻 6 号（2012）） ························ 119

21. 大原美保：
震災時の駅周辺における帰宅困難者対応の課題－東京都内の駅周辺地区帰宅困難者対策地域協力会の活動に基づく考察－（生産研究 64 巻 6 号（2012））·········································································································· 123

22. 藤生 慎, 沼田宗純, 大原美保, 目黒公郎：
東日本大震災における自治体の建物被害認定調査の実施状況に関する考察（生産研究 64 巻 4 号（2012））·········································································································· 127

23. 松下朋子・沼田宗純・目黒公郎：
被災者への住宅供給システムについての考察 東日本大震災の事例より（土木学会第 32 回地震工学研究発表会講演論文集（2012）） ······················································· 132

24. 高野 佑, 沼田宗純, 目黒公郎：
応急仮設住宅供給業務へのプロジェクトマネジメント手法適用の検討（生産研究 64 巻 6 号（2012））·········································································································· 137

25. 大原美保：
ジェンダーの視点から見た災害応急対応の課題（生産研究 64 巻 4 号（2012）） ························ 141

26. 陳 勲・沼田宗純・目黒公郎：
東日本大震災における電力復旧優先順位に向けた検討（土木学会第 32 回地震工学研究発表会講演論文集（2012）） ······················································· 146

27. 沼田宗純・目黒公郎：
災害対策フェーズを用いた災害対策状況の可視化手法の提案～災害報道を利用したモニタリングを事例として～（土木学会第 32 回地震工学研究発表会講演論文集（2012）） ······················································· 150

28. 野田哲司・藤生 慎・沼田宗純・目黒公郎：
東日本大震災における自治体間の職員派遣の実態分析（土木学会第 32 回地震工学研究発表会講演論文集（2012）） ······················································· 153

29. Muneyoshi Numada and Kimoro Meguro:
News coverage concentration on specific municipalities: Analysis of TV report contents
at 2011 Tohoku Earthquake (USMCA2012) ··························································································· 158

30. Akiyuki Kawasaki, Michael Henry and Kimiro Meguro:
Analysis of disaster information gathering behavior and language ability
after the 2011 Tohoku earthquake (USMCA2012) ··················································································· 166

31. Sae Shikita, Maria Bernadet karina Dewi and Takaaki Kato:
Reconstruction of Kamaishi City after the 2011 Tohoku earthquake and tsunami (USMCA2012) ··········· 175

32. Yuto Shiozaki and Takaaki Kato:
Review on the definitions of vulnerability, resilience, and adaptation (USMCA2012) ····························· 180

33. Takaaki Kato:
Relation between urbanization and natural disaster risk in mega cities-lessons from Tokyo- (USMCA2012) ······································································································· 190

34. Shinya Kondo and Kimiro MEGURO:
Development of a web-based trend analysis system of earthquake disaster researches presented
at the past world conferences on earthquake engineering (15 WCEE LISBOA 2012) ······························ 198

35. Akiyuki Kawasaki, Michael Henry and Kimiro Meguro:
Comparing the disaster information gathering behavior and post-disaster actions of Japaneseand foreigners in the Kanto area after the 2011 Tohoku Earthquake (15 WCEE LISBOA 2012)·············· 208

36. Muneyoshi Numada, Kimiro Meguro:
Analysis of the concentration of TV news coverage to the specific municipalities
on the 2011 off the Pacific coast of Tohoku Earthquake (15 WCEE LISBOA 2012)································ 217

37. Miho Ohara, Kimiro Meguro and Atsushi Tanaka:
A study on people's awareness of earthquake early warning before and after
the 2011 off the Pacific Coast of Tohoku Earthquake, Japan (15 WCEE LISBOA 2012) ························· 227

38. 加藤孝明：
都市における防災の基本と今後の防災対策の方向性（機関誌『経済人』，18-19，関西経済連合，2013） ······································································· 234

39. 加藤孝明：
首都直下地震における火災リスクと広域避難の課題（火災誌 322 号（VOL.63, No.1），2013） ························································································ 236

40. 加藤孝明：
メガシティ東京の災害リスクと防災都市づくり（建築雑誌，vol.127，No.1638，日本建築学会，2012） ································································· 240

41. 加藤孝明：
東日本大震災の復興を俯瞰して，これからの防災・減災まちづくりを考える（都市計画，vol.299，p32-36，日本都市計画学会，2012）···························································· 244

42. 加藤孝明：
震災から２年目，今こそ落ち着いて考えるべき（Planners, No.70，p2-3，日本都市計画家協会，2012.6） ······························································· 249

43. 「現場知」共有座談会（Planners, No.70，p8-12，日本都市計画家協会，2012.6） ······················ 251
44. 加藤孝明：
季刊まちづくり 35 号：『特別企画／次の広域・巨大災害に備えて これからの津波減災まちづくりの論点』（p102-105,（株）学芸出版社，2012.4） ········································································· 256

45. 加藤孝明：「防災まちづくり」パネルディスカッション（市政

vol.61，p25-30，発行所：公益財団法人 全国市長会館，2012.5）································ 258

46. 加藤孝明：大規模水害メガ・ハザードに地域社会が挑む－東京・新小岩－（「しぶとい都市」のつくり方 脆弱性と強靱性の都市システム p319-322，発行：東京大学・都市
持続再生研究センター，2012）·········································································································· 264

47. 加藤孝明：
時代変化と木造密集市街地－東京－（「しぶとい都市」のつくり方 脆弱性と強靱性の都市システム p309-311，発行：東京大学・都市
持続再生研究センター，2012）·········································································································· 268

48. 加藤孝明：
自然災害リスクと脆弱性の構造－今後の都市のリスクマネジメントの方向性－（「しぶとい都市」のつくり方 脆弱性と強靱性の都市システム p055-056，発行：東京大学・都市
持続再生研究センター，2012）·········································································································· 271

ICUS オープンレクチャーの記録
OL1：第 22 回 ICUS オープンレクチャー「復興を俯瞰して考える」 ··········································· 273
OL2：【経験の共有】震災復興・連続シンポジウム
第 1 回「被災地からみた復興の現状」 ·················································································· 275
OL3：【経験の共有】震災復興・連続シンポジウム
第 2 回「復興の全体像を考える」 ·························································································· 276
OL4：【経験の共有】震災復興・連続シンポジウム
第 3 回「福島の現状：復興課題を共有する」 ······································································· 278
OL5：【経験の共有】震災復興・連続シンポジウム
第 4 回「神戸から東北，そして東南海に備える」 ······························································· 279
OL6：【経験の共有】震災復興・連続シンポジウム
第 5 回「南三陸町の現状と課題：市民目線から」 ······························································· 280

６４巻４号（２０１２）

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対応する予測結果を即座に検索することで，沿岸に対するに

津波警報・注意報の迅速な発表を実現している．出力され津波による被害は時として国境を超える広範囲に及び，る結果は津波の沿岸での高さや到着時間で，気象庁では津災害発生直後の被災状況を把握することが重要でありなが波の高さとして０.
５,
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２００３］ ．現在津波被害把握の的な数字での発表をしている．

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・リモートセンシング

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航空機や人工衛星から地上を撮影したデータを使う．広７）８）［中央防災会議 ,，２０１１］．以下にそれぞれの特徴を
２０１０］

範囲を素早く，また比較的安価に取得可能という特徴があまとめた．いずれの場合も浸水ラインを最も基本的な情報

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２０１１］
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２００４］

のひとつとしてとらえている．

マトラ沖の巨大地震では，インド洋全域にわたって津波被・被害想定

害が発生し，被害の甚大さから国際チャーターによる衛星

あらかじめ過去の記録などから起こりうる地震を想定し，これらの内津波を発生させる可能性のある断層について津

の集中観測も行われた．このため比較的多くの活用事例が５）．
残されている［I
CUS,
２００９］

波の数値シミュレーションを行うもの．沿岸に到達する津被災直後においては航空機による測量で被災地の状況を波の高さや到達までの時間といった結果が得られる．この把握することが，天候や回帰周期に左右されないために有結果を利用した浸水域等の具体的な被害の算定などが行わ効である．一方で航空機による撮影では，広範囲にわたる

れ，ハザードマップとして公表されることもある．

津波被害に対し，国境を越えた撮影などが難しい場合もあ

しかし被害想定に用いる地震は数百年間の記録などを基る．
得られた画像を利用できる情報にするには加工が必要で，にしたもので，想定やシナリオには限界がある．このため，
実際の被災地域が想定浸水域を大きく上回ることもある．

津波被害の把握としては，画像を技術者が目視で判読，解例えば２００５年に政府中央防災会議の下に設置された専門析するために時間がかかる．また，この方法では被害を受調査会が日本海溝・千島海溝周辺海溝型地震について，物けた範囲が倍になればその分時間も倍かかる．東日本大震

的・人的・ライフライン・交通および経済の被害について災の場合，被災地ほぼ全域の津波浸水ラインが報道発表さ定量的に算定していた．一方で東日本大震災では実際の地

４）．
れたのは３月１８日のことである［GSI,２０１１］

震動の範囲，津波高，津波の範囲，浸水域，人的・物的被・現地踏査

害等において想定をはるかに超える結果となり，ハザード

もっとも精度が高いものの，広範囲を網羅するには大勢

マップ上で津波が来ないとされていた地域にも大きな被害の人手が必要でコストも高い．被災直後の混乱の中，すべが生じた．

ての地域において素早く被災地域を一括して把握すること

・シミュレーション

は非常に困難である．また，被害が大きい地域ほど現地踏

震度計からの震度情報や GPS波浪計からの情報などを査が難しい．例えば，本研究の対象地として取り上げた宮
城県山元町は以前から出入りのあった測量会社に依頼をし利用し，沿岸に到達する津波を予報する．
ただし，現在日本ではこの観測結果から直接津波を計算するのではなく，上記事前予測の計算結果を津波予報デーて数日のうちに結果を入手できたが，近隣市町村では同様の期間内には現地踏査を実現できていない．

タベースに保存・蓄積したものを利用する．地震発生時はつまり津波被害の影響を受けた可能性がある世帯等の把

このデータベースから，発生した地震の位置や規模などに握に必要な津波浸水域情報は，事前の想定やシミュレーシ
ョンから求めたものは津波発生直後に入手できるものの精

山九株式会社
東京大学生産技術研究所

度が低く，精度が高い航空写真の目視判読や現地踏査の成＊＊＊都市基盤安全工学国際研究センター

果は初期段階には提供されない状況である．つまり，比較

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的精度が高く，素早く広範囲の被害を把握する仕組みが不究では画像をオブジェクトに分割する細かさを３０/
１００，そ

２）
．以上を踏まえ，本研究は人工足している［CAO,２００１］の後結合する度合いを９０/
１００とすることで適切な結果が衛星から撮影された画像を用いて津波浸水域を半自動で把得られた．

握する手法を開発し，被害把握の迅速化に資することを目的とした．

瓦礫オブジェクトは実際には複数の木材などの集合である．このため輝度で分ける今回の手法を用いると木材の色

２ 手の違いや含まれる車両などからオブジェクト内部に複数の法

別オブジェクトが生成される．こういった空間的な情報も本研究では航空写真での津波浸水域目視判読時に主な判

土地被覆分類に利用できるのがオブジェクトベースの分類

断材料として利用した瓦礫を用いた浸水域の自動判読を行手法の特徴である．瓦礫に特徴的な「オブジェクト内の穴

う．すなわち，瓦礫が分布している範囲を津波による浸水の数」の割合が図２のように得られた．

域とする．

また，各オブジェクトの特徴を示す数値として正規化植生指数（NDVI）に着目した．正規化植生指数とは以下の数

敢 瓦礫の識別式で計算され，−１から１の値をとる．数字が大きければ瓦礫を抽出する際，本研究では利用する衛星画像の解像大きいほど緑色の植生が濃いことを表わす．

度が０.
５mと高いことからオブジェクトベースの土地被覆分類を行う．これは高解像度の画像をピクセルごとに分類

NDVI
=（NI
R− R）／（NI
R+R）

する方法では多数のノイズが発生するためである．ピクセ
ルベースとオブジェクトベースの土地被覆分類の特徴を以

ここで NIR:
近赤外スペクトルデータ，R:
赤色スペクトル
データ下にまとめる．適切にオブジェクト化を行うことで，より正確な土地被覆分類が可能になる．

各オブジェクトの正規化植生指数の出現パターンに特徴

・ピクセルベースがあることが分かった（図３）．以上から，瓦礫の識別にピクセル単体で土地被覆を分類する．各ピクセルの持つスペクトル情報（特に NDVI）とオブジェクト内の異質オ

スペクトル情報のみを基に分類を行う．空間解像度の比較

ブジェクトの数が有効と予想された．そこで，本研究では的低い画像を利用して土地被覆分類を行うのに適している．

NDVI値，バンド１（青），バンド２（緑），オブジェクト・オブジェクトベース

内の異質オブジェクト数の４つの属性によってオブジェク

隣り合うピクセルの輝度差などを用いることで複数の隣

トを瓦礫と瓦礫以外にわけることとした．実際に衛星画像接するピクセルから構成されるオブジェクトを生成し，オを確認すると，瓦礫の各スペクトル値等は撮影条件やそのブジェクトの属性を用いて土地被覆分類を行う．スペクト

地域における瓦礫の種類によって多少左右されていること

ル情報の他，面積や形といった空間情報も分類に利用でき，が分かった．そこで画像の対象範囲を細かく区切ることで，高解像度の画像を分類するのに適している．

その地域に応じた瓦礫とそれ以外を分けるための各種属性

今回使用した ENVI画像処理ソフトでは，細かさというのしきい値を決定することとした．

１つの変数のみを用いてオブジェクトの生成を行う．また，

上記のような画像の特徴と対象とした山元町の地形状況

一度エッジ検出と細かさの指定により分割したオブジェク

から南北方向に１分（約１.
８km）ごとに分割して解析する

トに対し，再度隣り合うオブジェクト同士を結合することことが妥当と判断した．そこで，次のような処理手順で瓦が可能になっている．図１に画像のオブジェクト化の実例

礫を識別する処理を施した．

を示す．道路や家屋といった特徴が適切に捉えられている

１）分割した被災後の画像（Strip）ごとにオブジェクト分のがわかる．また，瓦礫に関してもそれ以外と明確に区別されてオブジェクト化されていることが見て取れる．本研

図１

画像のオブジェクト化

図２

30

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６４巻４号（２０１２）

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外のオブジェクトも含まれている．そこで，瓦礫として分類されたオブジェクトが津波によるものであるかどうかの識別に標高データを利用することとした．ある標高より不連続的に高い位置にある「瓦礫」は津波による瓦礫ではな
いと考え，その標高以下の「瓦礫」のみ津波による瓦礫として扱う判定法を加えた．
まず，抽出した瓦礫オブジェクトの標高を，２００８年に国
土地理院より提供開始された全国１０mメッシュ標高モデ
ルを利用して求める．なお，一部の都市計画区域について
はより高精度な５ mメッシュ標高モデルも整備されている．図５はある St
rip内の瓦礫とされたオブジェクトについて横軸に標高，縦軸に０から４０mの０.
１m間隔の各標高
における瓦礫オブジェクトの出現頻度を表わしたグラフで
図３ある．標高３ m以下の低地にたくさんの瓦礫が広がって

各オブジェクトの NDVI値出現頻度

いる様子と標高５ m付近に瓦礫が集中する様子がグラフからわかる．標高５ m付近については，津波が最終的に到達した部分に堆積した瓦礫を表わしている．従って，このStrip内においては，標高５ mより高い位置にある瓦礫とされるオブジェクトについて津波による瓦礫ではない可能性が高い．
続いてしきい値となる標高の求めかたについて検討した．
前記のように，しきい値としたい標高は St
rip毎，すなわち
地形によって変化する．そこでしきい値とする標高を上げていった際，その標高より下に瓦礫オブジェクトの全体の何パーセントが含まれているか，という累積含有率に注目した．図５の赤い線の傾きが緩やかになる標高を津波が到達した標高とすることが妥当であることが確認された．図６にこの仕組みを示す．この模式図では累積含有率が１０%
ᅇ   

図４

瓦礫オブジェクト抽出の結果類を行い，瓦礫に相当するオブジェクトを１０個選ぶ．
２）これらの瓦礫オブジェクトの NDVI
・バンド１・バンド２の最小値以上，最大値以下およびオブジェクト内異質
オブジェクト数３個以上という条件で瓦礫を抽出する．
図４に得られた瓦礫の分類結果を示す．分類が適切に行われている例を青色の丸，瓦礫以外のオブジェクトが瓦礫

P 

図５

標高に対する瓦礫オブジェクトの出現頻度と累積含有率の例

として分類されている例を緑色の丸，瓦礫が瓦礫として分類されていない例を赤色の丸でそれぞれ示す．

㻥㻜㻑

柑 浸水域の判定瓦礫とされるオブジェクトの抽出に続き，津波による浸㻤㻜㻑

水域の決定を行う．浸水域には瓦礫が散在するため，瓦礫㻣㻜㻑の存在する範囲を浸水域として扱うことは得られた画像ではおおむね妥当である．ところが前項図４に示されるとおり，瓦礫として分類されたものの中には津波による瓦礫以

㻢㻜㻑

図６

瓦礫の標高に対する分布の断面模式図

31

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増えることになる標高差が，津波の到達した境界を機に大きくなっている．

(m)

(m)

1000

15

800

本研究においては累積含有率４０%から１ %毎に増やし

10

600

ていき，１%の増加が標高差１ m以上に対応するときの標

400

5

200

高をしきい値とすると，おおむね妥当であることが判読か0

ら確認できた．そこで，この処理を各 Stripに対して実施し

-200

←໭

༡→

-5

-400

た．図７にしきい値とした標高より上にある瓦礫オブジェ-600

クトを除いた津波到達域の画像を示す．

0

-10

-800

しきい値とした標高をつなぐことで，図８に示すように
自動判別による津波浸水域が生成される．このときの自動

-1000

-15

図９

実地踏査浸水域線に対する自動判読浸水域線の水平方向の差（紫）と垂直方向の差（橙）判別による浸水域の誤差を図９に示す．標高をしきい値に用いているため，丘などの標高が大きく上昇する箇所で津波による浸水がとまった場所は自動判読と実地踏査の浸水

線がおおむね一致している．一方，標高がなだらかに変わる地形では自動判読による浸水域線が浸水域を正確に捉えきれていない．
４ 本研究の成果
本研究ではリモートセンシングを利用して津波浸水域を自動で判読する手法を開発した．これにより広域にわたる

図７抽出された瓦礫（黄色）と破棄された「瓦礫オブジェクト」（赤）の例

津波災害発生後の初期段階で被害把握の精度向上が見込まれる．以下に本研究より得られた成果を示す．
・リモートセンシングによって得られた高解像度の画像を目視判読することで津波の浸水域を把握できることが示された．この際，地面の色彩変化とともに，特に津波の到達線付近では瓦礫の有無が重要な判断材料となる．
・リモートセンシングによって得られた高解像度の光学衛星画像を自動処理することで津波の浸水域の概況を把握できることが示された．ごく初期のシミュレーションと後日の実地踏査との間を精度および処理時間の観点から埋める
ことで，現場からの情報がなくとも津波被害の全体像把握
が災害発生後初期段階で可能となる．
・国際災害チャーターなどの枠組みを利用することにより自前で処理能力を持たない地域や，複数の国や地域にまたがる災害発生時にも有効に機能する可能性が示された．
５ 今 後 の 課 題
本研究より得られた成果を踏まえ，今後の課題について
以下に列挙する．
・瓦礫と標高以外に複数の指標や被災前の画像を効果的に使うといった手法を組み合わせることによる精度向上を目指すことが必要．
・本研究では宮城県山元町の東日本大震災による津波被害９）について解析を行った．今後別の地域や［山元町 ,
２０１１］

異なる津波災害についても研究を進める必要がある．
・抽出された瓦礫を有効に使い，道路等の情報を組み込む
図８

実地踏査（青）と自動判読（緑）によって得られた津波浸水域線ことで寸断された道路ネットワークの検出などが考えられる．復旧計画や物資の輸送計画に役立てられる．
（２０１２年５月２１日受理）

32

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参

考

文

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資料９p

33

―5―

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― 14 ―

OSM

2

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(

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)

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ISODATAISODATAOSM
6ISODATA

2

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― 15 ―

5-1
5
5
(

5-1

ISODATA

5-2

5

NDVI

5-2)

ISODATA
5-3
5-3

80

― 16 ―

NDVI

6.1(GeoEye-1)(2006)
77

OpenStreetMap

pp.83-95.

No.546(2001)

1995(2010)

ALOS/AVNIR-2

SAR

pp.55-61.
2008

3

10

pp.12-24.
(2007)

78

pp23-34.
(2007)
2004

6.2

Vol.7

No.5

pp.1-14.
(2001)(1~3
GeoEye-1)

No.668/-54

pp.177-185.
(2000)
Vol.2 pp.119-128.

OpenStreetMap(2002)
1995
11
pp.2323-2328.

MSS(2012)
Vol.64No.4(1991)― 17 ―

pp.455-459.

1995

RapidEye

3.11

1 RapdiEye
RapidEye

(

2008

29

8

)

5.5
(

(440-510nm)

2012)(520-590nm((630-680nm))(630-680nm)(760-850nm)
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2011

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GeoEyeRapidEye
GeoEye5,,(25-28,2012― 19 ―),VOL.64,No.4,

Review of activities on remote sensing for the Great Earthquake and tsunami in Japan
Haruo Sawada
Institute of Industrial Science, the University of Tokyo, Tokyo, Japan

Abstract
Thousands of digital aerial photos were taken by private survey companies after the Tohoku
Earthquake, conducted under the special agreement in case of disaster between GSI (Geospatial
Information Authority of Japan) and the air-survey group of Japan. While these pictures were
exceedingly useful in identifying damage levels of the tsunami by visual interpretation, the processof interpreting the whole damaged area required plenty of time and manpower. Meanwhile, withregards to satellite remote sensing data, International Disaster Charter (IDC), together with Sentinel
Asia, made contributions, offering few thousand or more satellite images. JAXA continuously
produced PALSAR images of inundation caused by tsunami until the satellite stopped its operationin April 2011. High-resolution satellite images were used in identifying the damages, with thecomparison of pre- and post- quake images enabling us to identify the reality of the destruction. In
such ways, remote sensing data hold potential in the field of large earthquake disaster management.
However, their products were seldom used in tsunami damaged sites. These real situations haveshown us the importance of appropriate preparation for making remote sensing data useful to a large
tsunami disaster.
Keywords: the Tohoku Earthquake; aerial photography; satellite remote sensing; tsunami
1. Introduction
The Great M9.0 Tohoku Earthquake,

destructive

power

of

the

tsunamicharacterizes

the

event

of

the

and

Tohokuoccurred on 11 March 2011, was the biggest

Earthquake. The number of fully, half andearthquake known ever to have hit Japan. It

partially collapsed residential houses weredirectly devastated buildings, houses, dams,

129,291, 264,004 and 725,918, respectively. In

railways, roads and other vital infrastructure, as

addition, 63,574 non-residential houses wereit triggered the huge tsunami that reachedalso damaged. Serious destruction of roads,

heights of up to 40 meters. The disaster gave

bridges, railways and levees were reported

direct and serious damage to eleven prefectural

4,200, 116, 29 and 45 places, respectively. Out

governments. According to the report by theof 300km of coastal levees, approximately

National Police Agency on 5 September 2012,

190km was damaged. Various remote sensing

the number of the dead, missing and injured

data have been introduced for the purpose of

totalled 15,870, 2,846 and 6,110, respectively.

gathering information for damage assessment

The number of those missing indicates the(H. Sawada 2012, Tonooka 2011). The data

― 20 ―

was also applied in rehabilitation plans. This

GSI owns an aircraft called KUNIKAZE forreport summarizes how remote sensing data

aerial photographing use, but the plane

were used for the Tohoku Earthquake andhappened to be under periodic inspection until

presents lessons learned and recommendations

the end of March 2011. Therefore, it was notfor improvement in operational use of remote

until April 1st that GSI could start flying

sensing technology.

KUNIKAZE.
Aerial photos were taken by digital and

2. Aerial photography

conventional cameras, depending on their

2.1 Aerial photogrammetry

availability suitable for 1/10,000 scale images.

In 2005, GSI (Geospatial Information Authority

The geocoded photos (with Japanese coordinateof Japan) signed a contract with APSAT

system) were distributed via GSI website. On(Association of Precise Survey and Applied

the next day of shooting, these aerial photos

Technology)

aerialwere converted to orthophotos and opened tophotographs. Forty-four minutes after the

public via website in digital format with 50cm

earthquake hit Tohoku, GSI called APSAT,

resolution. Printed images were applied for

unofficially asking them to stand ready forgovernmental

shooting. Then, ten minutes later, GSI officiallyresolution digital images were available uponrequested for emergency aerial photographs

request.

on takingemergency

use.

Furthermore,higher-(Tanioka et al. 2011). Following this call,
APSAT

immediately

contacted

the22

2.3 Products and other activities by GSI

contracting survey companies to fly over to

Our staffs and students interpreted the tsunami

Tohoku. However, because both GSI andlines on the orthophotos immediately after GSI

APSAT offices were located in the damaged

opened them on the web and started offering

areas, the telephone line between the two was

the “tsunami aerial photo map” with 1/10,000

unstable, with only one-way communication

scale. The major key for interpretation wasfrom GSI to APSAT available. The survey

debris (Kishi et al. 2012). Few weeks later, GSI

airplane had to fly for a longer distance, aboutpublished a tsunami affected area map with

250km to 550km, from the base airport because

1/25,000 scale (Masaharu and Nagayama 2011).
The

Sendai Airport, the main airport in the Tohoku

groundlevel

isimportantarea, had also been destroyed by tsunami. The

information for rehabilitation of the area. Seven

next day, six survey companies immediately

survey companies used LiDAR to create DEM

started taking aerial photos according to thewith 5m spatial resolution conformed to theagreement with GSI, and within two days

contract with GSI in emergency. The total

covered majority of the damaged area of about

mapping area of the seven flights was about

2

4,820 km . Unfortunately, due to weather

10,980km2

conditions, the crew had to wait until on March

earthquake were found in numerous coastal

19 to cover 100% of the tsunami damaged area.

areas, further worsening the tsunami aftermath.

Ground sinks caused by the

Therefore the new control point survey was
2.2 Distribution of aerial photos

required for making new geographic maps inthis region.

― 21 ―

Mukouyama et al. (2011) mentioned

used in 1.3% of news and, in contrast, the wordthat a tsunami simulation was useful in quickly“aerial photo” was used in only 0.04% of news

and accurately identifying the damaged areas(Y. Sawada et al. 2012; 2012b).

on remote sensing images. However, lack of

Flood water brought by tsunami

machines and electric power made their work

remained in a wide area of rice fields and otherdifficult because their office was also damaged

agricultural lands for a long period of time.

by the earthquake and electricity was limited

Satellite images made large contributions inunder governmental control. The lesson to bemapping these inundated areas. Even MODIS

learned is that we must think of ways to

was useful to detect tsunami debris (Aoyama

continue operations under crisis, particularly in2012).

the rescue phase of a disaster.

High-resolution satellite images were

Aerial photo survey was conductedparticularly useful in identifying damages. Theagain through May to November 2011. These

GeoEye image with 50cm resolution detectedaerial photos have often been used by the local

debris caused by the tsunami. Its object-typegovernments and residents as an importantclassification, combined with elevation data,

information source for damage assessment andenabled us to semi-automatically delineate therehabilitation plans. GSI provided base maps

tsunami affected areas (Nakao and Sawada

with the scales of 1/25,000, 1/50,000 and2012; 2012b).
The effective comparison of pre- and1/200,000. The digital web mapping system on

post- quake images helped us to easily identify

the web was also introduced for further uses.
GSI dispatched a team to the Cabinet

damage situations (Ishidate et al. 2011).

Office to serve at the “Emergency Mapping

Therefore, we strongly suggest that the image

Center” for six weeks. Another team (TEC-

dataset of the usual, non-emergency conditions

FORCE), equipped with large printing systems,

be developed and stored as database nationwide.

was sent to Sendai City in Tohoku, to help the

While remote sensing data have much potential

disaster management center by distributing

for large earthquake disaster management, theaerial photos and their products (Furuya et al.

Tohoku Earthquake has clearly shown us that2012).

appropriate preparation for remote sensing data
is a crucial matter.

3. Satellite data
3.1 Capability of satellite data

3.2 Private survey companies

Satellite images were extremely helpful in

In response to the tsunami disaster, theover-viewing the whole picture of tsunami

industry-government-academic

damages along the coastal lines of 600km

formed as Emergency Mapping Team and the(Nakajima 2011), even over Fukushima where

Emergency Mapping

the troubles of atomic power plants caused

established at Cabinet Office in order tomuch severe conditions and only the UAV

standardize the situational awareness at the

could take aerial photos (Yamazaki 2011). The

national level (Furuya et al. 2012).

(EMC)

was
was

Beside this activity, private survey

text analysis of the news reports for two weeks
showed that the word “satellite image” wasCentergroup

companies― 22 ―

conducted

theircontribution

activities.

The

Corporation

Technological Disaster”. IDC aims at providing

reported that the pan-sharpen AVNIR-2 image

unified system of space data acquisition andwas highly useful in identifying large buildingsdelivering them to those affected by natural or

washedneverthelessman-made disasters through Authorized Users.

identifying the damage levels of the remaining

Each member agency has committed its

buildings was not an easy task. The Hitachi

resources to support the provisions of the

Solutions Corporation offered both the Cabinet

Charter and thus helping to mitigate the disaster

Office and local governments GeoPDF files

effects on human life and property. Establishedwhich

in 1999, IDC started its activities in 2000.

away

were

WorldView1

Asia

by

Surveytsunami;mapped

from

and

The

2.

QuickBird,
Image

One

JAXA,

as

the

Japanese

representative,

Corporation used Radarsat-2 to show the landparticipated in 2005, and the number ofcover changes and damages to fisheries caused

participating institutions has now reached 21

byorganizations in 2012. There are tens oftsunami.

The

Japan

Corporation

started

the

Space

Imagingofrequests every year from various regions.

emergency structure, successfully obtaining

Looking back at 2011, thirty-one actions weresatellite images: e.g. COSMO SkyMed on 12

taken,March, GeoEye-1 on 13 March and IKONOS

Earthquake.

formulation

including

that

for

the

Tohokuon 12 March (Li et al. 2011). While the state of
emergency continued until the end of April

4.2 IDC Activity for Tohoku Earthquake

2011, the KKG (Kokusai Kogyo Group)

JAXA requested IDC to activate emergency

presented aerial and satellite images, other data

observation on 11 March 2011. Few days later,

and tsunami simulation CG videos. PASCO

the following IDC products appeared on the

Corporation

photos,web: WorldView (33 products), RapidEye (32inundation map derived from TanDEM-X,

products), SPOT (17 products), Landsat (9TerraSAR-X, EROS-B images, topographic

products), TerraSAR-X (9 products), GeoEyechange maps and other information related to(8 products), IKONOS (7 products), QuickBird

nuclear power plant problems.

(4 products), Radarsat (4 products), FormosatSome

showedpanoramic

surveyprivatecompanies(1 product).

offered their remote sensing data and products

The images were observed from on 12

through internet. For example, the Asia Survey

March to 14 April 2011. In total, 94 satellite

Corporation used the LVSquare for providing

image maps were uploaded on the website andaerial photos, airborne LiDAR data, SAR data,high-resolution images came to be frequently

geographic maps and snapshots of the groundused. The actual observation dates differed by(Ogawa et al. 2011).

each satellite system; WorldView: 6 days,
SPOT: 3 days (12 to14 March), RapidEye: 2

4. International activities

days (12 and 13 March), IKONOS: 2 days (124.1 IDC: International Disaster Charterand 14 March), and GeoEye: 2 days (13 and 19

IDC stands for: “the Charter on Cooperation to

March). Over 5,000 satellite images that wereAchieve the Coordinated Use of Spacenot uploaded on the web were also sent directly

Facilities

to JAXA. These images were the true success

in

the

Event

of

Naturalor― 23 ―

of the IDC program. Its timing is also worthy of

we felt that the duration period of IDC

note. As one of the many examples, the SPOT

activation was much too short -- most of theimage of 12 March was uploaded on theemergency observation activities were ceased

website the following day, already processed aswithin a few weeks. We particularly felt so

an image showing the tsunami damages withafter the ALOS stopped its operation in April

the scale of 1/100,000 (Charter call ID359,

2011. In case of huge disasters, government

Product No. 05). It is exceedingly quick

should have some agreement with foreigncompared with the average of 7.8 days in IDC

institutions to continue satellite observation forin last ten years.

a certain period of time. And the agreement
must be signed ahead of the disaster.

4.3 Use of IDC products
Although there was huge demand for maps

5. Actions of Japanese remote sensing

indicating damaged zones, only very few wereorganizations

actually available. Hand-drawn maps often had

5.1 Satellite observation

to be used to show damaged sites at the local

JAXA played an important role in supporting

offices. Regrettably, IDC products were hardly

the Cabinet Office disaster management center,used by local government or volunteer staff onproviding not only diverse satellite data, butsite for the following reasons:also offering satellite communication system to-The name of IDC not recognized enoughboth the Cabinet and local governments

by local government. Even ALOS was(Takahashi et al. 2011).

seldom known by local government

JAXA revised the ALOS operation(Kakuta et al. 2012)

soon after the earthquake, thereby offering-Printed images not available (Since noabout 450 scenes during 72 paths (Ishidate et al.

electric power was supplied, printing-out2011). On 12 March, JAXA brought into thewas not possible at the time.)

Cabinet Office seventy satellite geographic-Only English language shown on maps

maps that had been produced by overlaying(labels need to be transliterated into

digital maps on existing ALOS images. After

Japanese)

emergency observations by ALOS, satellite-Awkward data access: Difficult to reach

imagesthe digital images (On the other hand, GSI

information about tsunami inundation areas)

ortho-photos were available on the web)were uploaded on their website 33 times. The

andproducts(e.g.

statisticalininundation map produced from the AVNIR-2

introducing the IDC products directly to theon 12 March, along with the pre-event PRISM

local government. If only had there been

image and the inundation map that derived

volunteers to transliterate English into Japanesefrom FORMOSAT-2, were also released only

right after the publish, these products would

two days after the earthquake.

We

faced

many

challenges

have been very helpful. Otherwise, the products

The GeoGrid opened up a website

are only useful to English-speakers who arefrom on 1st April to 16 July 2011, to offer

away from the disaster site with no limitation

ASTER image data and information derived

for electricity use or Internet access. In addition,from ALOS data. ASTER images are often― 24 ―

used in Japan now because no other Japanese

COSMO-SkyMed, Terra-SARX, TanDEM-X,

satellite has such high-resolution sensors to

RADARSAT-2, and ALOS X, C and L band

observe land cover.

satellite SAR data were available when the
Tohoku Earthquake happened. Radar data were

5.2 Damage assessment

often used to delineate inundated areas caused

The total thirty-three times of uploads on theby the tsunami. The TerraSAR-X of StripMap

JAXA website included images from eachmode with 3 m ground resolution wellsatellite as follows: PRISM: 3 times, AVNIR-2:

identified the inundated area (Yoshikawa et al.

17 times, PALSAR: 17 times, TerraSAR-X:

2011). SAR data has high potential to provide

twice and RapidEye: once. Most of themthe damage information with appropriate

showed tsunami damages. JAXA also provided

timing.

pre-disaster satellite images and the comparisonof pre- and post-disaster images clearly showed

6.2 PALSAR

the tsunami damage situations. As for other

Since PALSAR is little affected by cloud andevents, liquefaction, for example, was reported

haze, it was effective in capturing the

10 days later.

inundation areas. JAXA sent these inundation

AVNIR-2, being an optical sensor, isdata to the Ministry of Agriculture, Forestry

often affected by cloud and atmosphericand Fisheries every week. SAR however, faced

conditions. Nevertheless, its images under goodsome difficulty in clearly detecting the tsunami

weather clearly demonstrated the tsunami

damaged areas. Since the quake struck in early

impact. Cyclic satellite observation, equipped

March, an off season for paddy fields, thewith high-resolution optical sensors, was usefulinundated agricultural fields were identified as

in monitoring the aftermaths.

tsunami damaged areas. But then, how can the

Coastal pine forests were very popular

damaged areas during the paddy growing

in Japan and created scenic beauty in Tohoku.

season be distinguished? Analysis of PALSAR

Sometimes, their widths were wider than 300

conducted by JAXA indicated that the flooded

meters and worked for protecting winds andarea was only a half of the damaged areas.

sands from sea side. Tsunami destroyed these

Therefore, further study is required to detect

forests as well as seawall. Forestry Agency

tsunami affected urban or residential areas.

conducted an assessment of their damages byThat improvement makes the information more

field survey and satellite image processing.

helpful for rescue purposes in cities, in addition

Comparison of Landsat images between pre-to monitoring damages in farmlands.

and post- event clearly showed the damagelevels of coastal forest caused by the tsunami

6.3 Floating objects(Ochi et al. 2012).

Huge amount of floating debris were carried tothe ocean by the tsunami. JAXA explained on

6. Synthetic Aperture Radar (SAR)

23 March that PALSAR was useful in precisely

6.1 SAR datadetecting drifting objects, applying the data of

SAR is considered a good tool to observe

13 March 2011. They explained that the image

groundhelped to navigate ships to take their routes. As

even

in

bad

weather

condition.

― 25 ―

mentioned before, one tragic feature of the4, 2011). RSSJ (2011) also published a special

tsunami disaster is the large number of missing

edition journal, featuring the usage of high-people. On hearing the news that a dog was

resolution satellite images.

found at sea after three weeks surviving on a

The FCMG (Forest Conservation andfloating object, we, as well as many others,

Management Group) observed all coastal

came up with the idea of applying latest image

forests by using satellite remote sensing data,from PALSAR or other remote sensors toand proposed rehabilitation plans according todetect floating objects for rescue purposes.

site conditions. They used Landsat and SPOT-5

Even in the case of ships, image of ten days

for the comparison of pre- and post- disaster

before is not good enough to find safe routes.

situations.

These stories showed that it would bemeaningless to determine only the potentiality

8. Discussionof remote sensing data for disasters. Data

The information requirements for the tsunami

obtained by remote sensing is extremely usefuldisaster summarized by Kakuta et al. (2012)as practical information. Therefore, we strongly

were as follows;

recommend the disaster management groups
create an operational way in processing and- Overview: within one hour after a disaster
event

delivering satellite remote sensing data for- Estimation of debris: within a weeklarge disasters.

- Traffic route: every day or every 2-3 days
depending on the road class

7. Academic societies- Remote sensing images: interpretation

Workshops and seminars were held nationwide

result is also required

as well as in Tohoku. Academic societies, such
as

AJG

(The

Associationof

It must be necessary to offer theJapanese

information according to these requirements.

Geographers), GISAJ (GIS Association of

The overview was obtained from the airplane

Japan), JASDIS (Japan Society for Disasterof the self-defence when the tsunami wasInformation Studies), JSCE (Japan Society of

attacking the coastal area. The Japanese

Civil Engineering), JSPRS (Japan Society of

information satellite, may be, collected images.

Photogrammetry and Remote Sensing), andThese information were sent to the disaster

RSSJ (The Remote Sensing Society of Japan)

management center in the Cabinet Office.

have launched various projects and opened up

However, normal citizens could not see thewebsites to present their activities. JSPRS

information.

published a journal special edition, featuring a

Hundreds of digital aerial photos werelist of remote sensing data (Tsuru 2012),

taken by private survey companies under the

including lists of vertical air photographs,

special agreement in case of disaster. Theiroblique photographs, elevation data derived

geocoded photos (with Japanese coordinate

from aerial laser, vehicle installation fieldsystem although it was not suitable formeasurement data, optical satellite data, SAR

international collaboration) were distributed

data. Activities of private companies were also

through the GSI website. Even though theysummarized in a special edition (Vol. 50 - No.

were useful in identifying the damage level by― 26 ―

visual interpretation of debris, it took time and

need

to

start

collaborative

networksormanpower to interpret the whole damaged area.

agreements among related institutions and local

The amount of debris was quite difficult togovernments ahead of the next large disasterestimate even by the LiDAR data.

because there is difficulty to build up a new

Many other survey companies alsocollaboration framework during the rescue andmade contributions by offering satellite images.

evacuation phase. If an agreement exists, we

The International Disaster Charter, as well as

can start helping quickly with appropriate aid

the Sentinel Asia, contributed, offering several

supplies. Unfortunately, aid supplies andthousands

volunteers were not proportional in the Tohoku

ofsatellite

images.

However,

because the product labels and directions were

Earthquake.

shown in English only, the people in disaster-With

regards
list

product

stricken areas had difficulty to understand its

standardization,

instructions. Furthermore, supporting actions

requirements should be prepared, as it responds

were ceased only few weeks after the quake.

to the necessity of each disaster stage andFor these reasons, it is regrettable that remotelocation. Spatial information required varysensing data made little contribution to help the

depending on disaster types and phases --victims. While international collaboration suchbefore event, during event (rescue stage), afteras the partnership with IDC continues to beevent (evacuation stage), and rehabilitation

important and useful, we firmly suggest its

stage.

operations and activities be strengthened andestablished to meet the requirement list so that

improved further.

both product manufacturers and users know

If the daily requirements

a

to
of

information

The standard products must be

were set, for example, monitoring of road

beforehand

network and/or detection of collapsed houses,

geocoding type, scale, color, language etc.

the satellite information providers could help to

These products should be used in disaster drills

produce such images and information.

to get people familiar with remote sensing

We wish to add two other proposals.

thefeatures

of

each

item:

products.

The first is to establish collaboration undernormalsituations;thesecondistheReferences

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Ooga

and

Akihiro Nakazawa, 2011, LVSquare:

Broadcast of disaster information after

Takahashi,

Masuo,

Masanobu

Miyagi,

Shimada,Tohoku region Pacific coast Earthquake

Yousuke

MasatoOhki,

via internet, Journal of the Japan

Noriyuki Kawano, Tomohiro Shiraishi

Society of Photogrammetry and Remoteand Takeshi Motohka, 2011, Disaster

Sensing, 50(4), 219-226.

monitoring for Japan Earthquake withRSSJ, 2011, High-resolution satellite remotesatellite by JAXA, Journal of the Japansensing concerning the 2011 off theSociety of Photogrammetry and remote

Pacific Coast of Tohoku Earthquake andsensing, 50(4), 198-205.

theTanioka, Seiichi, Hideaki Takenaka, Hideaki,

Remote Sensing Society of Japan, 31(3),Takashi Y Nakajima, Hiroaki Kuze,

344-367.

Tamio Takamura, 2011, An urgent air

TsunamiDisaster,

Journalof

Sawada, Haruo, 2012, Contribution of remotephotographing for the 2011 off thesensing data for the Tohoku Earthquake,

Pacific coast of Tohoku Earthquake,

Proceedings of 21st Forum on Global

JournalEnvironment

andDisaster

Risk

Photogrammetry and Remote Sensing,Information,

12-13

March.

Tokyo,

of

the

Japan

Societyof50(1), 185 -191.
Tonooka, Hideyuki, 2011, Great east Japan

Japan:IIS, 29-32.
Sawada, Yoshito, Takahiro Endo, Muneyoshi

earthquake seen in ASTER nighttime

Numada, Tetsuya Ishikawa, Kimiro

thermal infrared imagery, Journal of the

Meguro and Haruo Sawada, 2012,

Remote Sensing Society of Japan, 31(3),Development334-337.

ofvisualization

methodology of text data related to

Tsuru, Kosuke, 2012, Activity report ofdisaster, Proceedings of 21st Forum on

photogrammetric

Global Environment and Disaster Risk

Tohoku Earthquake, Journal of theInformation,

Japan Society of Photogrammetry and12-13

March.

Tokyo,

RemoteJapan:IIS, 53-60.
Sawada, Yoshito, Takahiro Endo, Muneyoshi

engineers

Sensing,51(1),

for

the

4-37,

http://www.jsprs.jp/action.html.

Numada, Tetsuya Ishikawa, Kimiro

Yamazaki, Kengo, 2011 Aerial Photographing

Meguro and Haruo Sawada, 2012b, A

activity by unmanned aerial vehiclevisualization method for text data by

against great east Japan earthquake,self-organizing maps – Analysis of

Journalnews texts which are related to the

Photogrammetry and remote sensing,Great East Japan Earthquake -, Seisan-

50(4), 216-218

of

the

Japan

SocietyofKenkyu, 64(4), 49-56.
Referenced web sites
AA: Aero Asahi Corporation (in Japanese)

AAS: Asia Air Survey Corporation

http://ec2-175-41-208-71.ap-northeast1.compute.amazonaws.com/

http://www.ajiko.co.jp/bousai/touhoku
2011/touhoku_eng.htm― 29 ―

GSI: Geospatial Information Authority of Japan,

AIST: The National Institute of Advanced

Ministry of Land, Infrastructure

Industrial Science and Technology

Transport and Tourism (in Japanese)(AIST): Global Earth Observation Grid

http://www.gsi.go.jp/BOUSAI/h23_to

ASTER data distribution through WMS,
ASTER time series data, PALSAR InSAR

hoku.html

for crustal deformation

HU: Harvard University
Japan Sendai Earthquake Data Portal

http://disaster.geogrid.org/

http://cegrp.cga.harvard.edu/japan/?q=

ATR-Promotions Inc.

content/home

Software and data set distribution for iPad

Digital archive of 2011 Tohoku Earthquake

http://eq.stroly.com/maps/support
AJG:

http://worldmap.harvard.edu/japanmap

The Association of Japanese/

Geographers
http://www.ajg.or.jp/disaster/201103_

IDC: International Disaster Charter

Tohoku-eq.html

http://www.disasterscharter.org/home

DCRC: Disaster Control Research Center,

http://www.disasterscharter.org/web/ch

Tohoku University

arter/activation_details?p_r_p_141547

Building damage map derived from the4252_assetId=ACT-359

interpretation of post- and pre-event aerial

IIS: Institute of Industrial Science, The

photos

University of TokyoPNG and KML files of GSI aerial photo,

http://www.tsunami.civil.tohoku.ac.jp/tohoku2011/mapping_damage.html

KML and SHP files of the Tsunami line

Center for Satellite Based Crisis Information,interpreted by the laboratory
http://stlab.iis.u-

DFD, Germany

tokyo.ac.jp/eq_data/index_e.html

TerraSAR-X Change Analysis of Sendai

JASDIS: Japan Society for Disaster

Area, Japan

Information Studies

http://www.zki.dlr.de/article/1893

http://www.jasdis.gr.jp/11link/index.ht

Interactive view of RapidEye satellitemlimages on ZKI GIS-Viewer
http://www.zki.dlr.de/flexviewer2.5/in

JAXA: Japan Aerospace Exploration Agency
ALOS and other satellite images

dex.html?config=config_japan201103.

/emergency

xml
FCMG: Forest Conservation and Management

http://www.eorc.jaxa.jp/imgdata/practiGroupcal/natural/earthquake/east-japanhttp://www.hozen-ken.jp/index.html

20110311.php

GISAJ: GIS Association of Japan

Image gallery 3) Disaster
http://www.eorc.jaxa.jp/ALOS/gallery/

Aerial photographs, tectonic activity,
geographic base maps, DEM, Tsunami

lib_data/j3disaster.htm
Summary of the activities for the Tohoku

affected area map, traffic information
http://rarmis.jp/dpgissig/

Earthquake
http://www.jaxa.jp/info_support_j.html― 30 ―

http://www.finds.jp/independent/tohok

JFA: Forest Conservation and Management

u/index.html

Research GroupNIED: National Research Institute for Earth

http://www.hozen-ken.jp/menu/2012-

Science and Disaster Prevention

01siryou4.pdf

Aerial photos and ALOS data distribution

JSCE: Japan Society of Civil Engineering
http://committees.jsce.or.jp/2011quake

through WMS (tentative)/

http://bosai-drip.jp/alos/wms.htm

JSI: Japan Space Imaging Corporation

Satellite images, aerial photography,

http://www.spaceimaging.co.jp/EastJa

traffic information, map of evacuation

panEarthquake/tabid/576/Default.aspx

center, other geographic maps, list of

JSPRS: Japan Society of Photogrammetry andrelated sites

Remote Sensing

http://all311.ecom-plat.jp/

http://www.jsprs.jp/action.html

NPA: National Police Agency

KKG: Kokusai Kogyo Group (in Japanese)

http://www.npa.go.jp/archive/keibi/bik

http://www.kk-

i/index.htm

grp.jp/english/csr/disaster/201103_touhoku/ind

NTNU: National Taiwan Normal University

ex.html

Web Map Service

Mapionhttp://140.122.82.87/2011_Japan_Eart

Aerial Photo and Information on Land

hquake/index.htm

marks

PASCO Corporation (in Japanese)
http://www.pasco.co.jp/disaster_info/1

http://www.mapion.co.jp/feature/eq20
11/hisaichi.html

10311/

NICT: National Institute of Information and

RSSJ: Remote Sensing Society of Japan
http://www.rssj.or.jp/sinsaihenotoriku

Communications Technology
airborne Pi-SAR2 images on 2011/03/12

mi/sinsaihenotorikumi.htm

and 2011/03/18

Tokyo University of Information Science

http://www2.nict.go.jp/pub/whatsnew/press/h22/announce110312/index.html

MODIS support of SAR and Nuclear
pollution for 3.11 quake disaster

NARO: National Agriculture and Food

http://easia2.tuis.ac.jp/browse/Sanriku/indexSanriku.

Research Organization
GSI aerial photo distribution through WMS― 31 ―

― 32 ―

400
2300

― 33 ―

― 34 ―

― 35 ―

― 36 ―

― 37 ―

― 38 ―

X

a
Pbj:

b

Pi,j:

b

(%)

j

(%)
/

Nab:
Nall:

Pai:

(%)

a

― 39 ―

i

a

b

17
16

5 24 25

1 2 3
4 13 14
18

16 24
25

15

3

5 18 1 1713

2 4 14
15
23

23
11

11

/

/

X

X

16

24 25

25

3

6 17
18

11

5 18

17

1

3 17

12

3 18

11 13

13

10 25

5 14
15 16

8

1

/
23

4

14 15

2

X

X

― 40 ―

25
17

3 17

3

3

6

18

3 4

18

13

5

10

2

1

/
1 5 9 814 15 16

11

X

X

25
25

8
3 17 6

18

10

1 5
14 15
16

13

11

/
5

5

2

X

X

― 41 ―

1 3 4

3 4

1 2
5

/

X

― 42 ―

1
48
15
ID

1

/

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

99
4
146
1
13
2

3
57
1
11

2)

20121)
48― 43 ―

7
1
21
3
4
12
36
1

(2)
(1)

2

3

È

¿
Ð¾¶æ

¾

Ð·ô¶æ

øû÷
¾

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øû÷
ñ

Ò¿¾æ

¿

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16
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16

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(5)
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b
a

X
i Y
i

b

j

j
(7)

3)

― 44 ―

6
15

3

12

1 2

14

13

6

4

9

6

7

3

13

5

5

8 10

1

/

/

X

X

6

3

12

6

5
6

9

4 13

8
2 15

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14

1

5

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10

X

3 12 1 6

1 3 13

X

2 13
14 15

4 9
10

6

8

1 3

7
5

13

/

5

/

X

X

― 45 ―

3

(5)

(13)

(3)
(5)

(13)

(12)
(6)
(3)

(1)

6

7

(12)
5
(1)
2

3

4
(3)

(1)

5
4

3, 4, 6, 9
4

1, 5, 8, 10
1)

2012
2012, http://www.csj.jp/es/anzen2012/

2)

(13)

,

, 63,

457-460, 2011.
3),
http://www.jafse.org/archives/2010/02/post-108.html

6
5

1, 3, 5, 10, 13
3

4, 9, 137

― 46 ―

― 47 ―

― 48 ―

30
25
20
15
10
5
0
-5
-10
-15
-20

― 49 ―

z-score-3― 50 ―

03

2011/3/9

2011/3/10

2011/3/11 2011/3/12

2011/3/13

2011/3/14 2011/3/15 2011/3/16 2011/3/17

2011/3/18 2011/3/19

2011/3/20

2011/3/21

2011/3/22 2011/3/23

20

3 9

3 14

13

23

26

3 14

3 15

17

(3,7)

3 18

― 51 ―

(3/13 22)

3/18

3/14

3/17

3/13

3/16

3/19

― 52 ―

3/22


1.
2.

SOM

SOM

― 53 ―

― 54 ―

― 55 ―

Analysis pointt: Available data

Time interval B

Extract

Documentt

t+1

Doc(t-1,i-1)

Doc(t,i-1)

Doc(t+1,i-1)

Doc(t-1,i)Doc(t,i)Doc(t+1,i)Doc(t-1,i+1)

Doc(t,i+1)

Doc(t+1,i+1)t

Notation convention
Doc(t,i): Document i at time t
Key(j): Keyword j
Freq(t, j): Frequency of keyword j at time tW(t, j): Weight of keyword j at time t

Number of Documents

t-1

t

t+1

Key(j-1)

Freq(t-1,j-1)

Freq(t,j-1)

Freq(t+1,j-1)

Key(j)

Freq(t-1,j)Freq(t,j)

Freq(t+1,j)

Key(j+1)

Freq(t-1,j+1) Freq(t,j+1) Freq(t+1,j+1)

Keyword

Keywordt-1ttR(t, j): Ranking of keyword j at time t
Where,
t: timei: Document number
j: Keyword number

Frequency of Keywords

t-1

t

t+1

W(t-1,j-1)

W(t,j -1)

W(t+1,j-1)

Key(j)

W(t-1,j)

W(t,j)

W(t+1,j)

Key(j+1)

W(t-1,j+1)

W(t,j+1)

W(t+1,j+1)

Keyword
Key(j-1)

Analysist

Method of analysis of document/ keyword
Data mining
Clustering/classification
TF-IDF
LSI (Latent Semantic Indexing)
Co-word/ Co-occurrence analysis

KeywordRankt

Key(j-1)

R(t-1,j-1)

R(t,j -1)

Key(j)

R(t-1,j)

R(t,j)

R(t+1,j)

Key(j+1)

R(t-1,j+1)

R(t,j+1)

R(t+1,j+1)

R(t+1,j-1)tTime history of Ranking of Key(j)Ranking

Rank

t

1
2
k-1

Key(j-1)

Key(j)

Key(j+1)

K

Key(j)

Key(j-1)

Key(j)

K+1

Key(j+1)

Key(j+1)

Key(j-1)― 56 ―

t-1 t t+1tFrequency of Keywords

W(t,j) : TF-IDF(t,j) = TF(t,j) * IDF(t,j)
F(t,j) / FN(t)

B/2

t

t
log(B / {bn | key(j)B/2{bn | key(j)Bbn} : times including key(j) during B

Number of articles

Number of letters

300000250000bn} )Number of letters

700

Number of articles

600
500

200000400

150000300

100000

200

50000

100

0

0

469 (0.69%)

10 (0.01%)

3,700(5.45%)

Range of items of keywords
1

19,680(28.99%)44,022(64.85%)

10
100
1000
10000

― 57 ―

0

RefugeResidents
Decontamination
Within the prefecture
Nuclear power plant accident
InfluenceRadioactive material
Fukushima Daiichi nuclear
Fukushima city
Response
Government
Great East Japan Earthquake
Plan
Child
Dose of radiation
Enforcement
Area
Detection
RequireObjectFutureTsunamiTemporary house
Examination
Earthquake disaster
Cities, towns and villages
Koriyama city
Schedule
UneasyReconstruction
Announcement
Toden
Iwaki City
Case

Frequency

Frequency
500 1,000 1,500 2,000
1696
1614
1473
1182
1152
1107
1087
1067
1065
1018
992
985
958
882
859
853
838
837
811
806
758
743
716
716
705
703
685
685
683
683
662
660
656
635

― 58 ―

0

SupportRadioactive cesium
Person in charge
In the city
Evacuee
Perspective
Investigation
Explanation
On the other hand
Reservation
Installation
Inspection
Nuclear power plant
Warning area
Situation
This prefecture
RestartDamage caused by rumors
House
DamageCheck
Minami-souma city
RequestResultPresent
Radiation
Fukushima
citizens in the town
Life
Subject
Specification
Work
Compensation
PurposeShelter

500 1,000 1,500 2,000
629
629
617
609
609
603
596
589
585
577
577
563
563
559
559
558
556
544
539
538
537
530
528
523
518
518
514
508
499
490
479
472
471
470
459

― 59 ―

250
200
150
100

248
131

50
0

42
B=3

B=7

B=31

0 10 20 30 40
Decontamination
SludgeToden
Rice
Temporary house
VictimInspection
Detection
Student
Specification
TsunamiCompensation
CenterPlanting
LessonGovernment
Radiation
PollenTemporary back-home
Shipment
Participaate
Interim storage facility(a) B=3

15
12
12
11
11
10
8
8
8
7
7
7
6
6
6
6
6
5
4
4
4
4

0 10 20 30 40

0 10 20 30 40
SludgeRice
Toden
Compensation
VictimPollenPlanting
Specification
Distribution
Decontamination
Interim storage facility
Mail
President Shimizu
Accounts
Clean up of channel
CompostTsushima area
Exausted cattle
Absentee voting
Forest for disaster
Government office
Free

22
19
16
15
12
11
11
11
10
9
9
7
7
7
7
7
7
7
7
7
7
7

(b) B=7― 60 ―

Planting
Detection
Rice
CompostForest for disaster mitigation
SludgeCenterCompensation
Two points
Temporary payment
Disaster victim
Specification
Evacuation
Shipment
Toden
EvacueeGovernment
Mail
Membership
Dose of radiation
Postponement
Company(c) B=31

36
35
34
31
31
30
27
21
19
18
16
15
15
13
10
10
8
7
7
6
5
5

― 61 ―

1
300
599
600

900
898
1197
1200

1500
1496
1
300

600
599
900
898
1200
1197
1500
1496
1
300
599
600

900
898
1200
1197
1500
1496

― 62 ―

― 63 ―

4%
2%

23%

36%

2%
3%

1%

4%

5%

5%

N=1,357

12%

3%

7%

41%

5%

59%

14%

3%

3%

6%

9%

3%

1%

6%
16%

14%

13%

N=1,334

N=1,357

n=2474860

n=1114

497

0%

20%

40%

60%

80%

n=1850

860

n=918

497

0%

― 64 ―

100%

20%

40%

60%

80%

100%

0%

20%

40%

60%

80%

100%

0

Internet
Internet

0%

20%

40%

60%

80%

100%

0

― 65 ―

500(website, portal)

500

1000

1500

Internet
Internet

1000

2000

(email, chat)

1500

2000

― 66 ―

n=3010n=2274n=3775n=1866n=2727n=1407

0%

20%

40%

60%

80%

100%

n=2365n=1659n=2268n=1191n=1518
n=865

0%

20%

40%

60%

80%

100%

n=860
n=497

0%

― 67 ―

50%

100%

Internet
Internet(website, portal)

Internet
Internet

58%(email, chat)

63%
0%

0

500

1000

42%

1500

n=798

81%
0%

20%

2000

58%

40%

19%
60%

80%

26%

n=497

100%

― 68 ―

20%

25%
40%

60%

80%

16%

n=798

12%

n=466

100%

― 69 ―

― 70 ―

)

(

20
10
0
-10
-20
-30
3/5-11― 71 ―

3/12-18

3/19-25

3/26-4/1

4/2-4/8

4%

1%

1%

5%

23%

6%

33%
7%
2%

60%

7%

3%

6%

4%

5%

5%

5%

13%

N=
N=860

N=860

(n)

150

n=518

100

n=268

50

n=527

0

338

175
347

0%

20%

40%

60%

39%

40%

10%

80%

100%

― 72 ―

21%

N=860

338

175

347

0%

20%

40%

60%

80%

100%

5%
10%

11%
2

n=3,0931

n=4,193

18%
22%

n=3,347

0%

20%

40%

60%

80%

100%

2

n=1,7761

n=2,561
n=2,482

0%

20%

40%

60%

80%

34%

100%

― 73 ―

N=1,790

n=951

338

n=521

175

n=1,014

347

0%

20%

40%

60%

80%

100%
n=742

338

n=407

175

n=701

347

0%

20%

40%

60%

80%

100%

― 74 ―

― 75 ―

― 76 ―

Others
22%

The Philippines
3%
Sri Lanka
3%
Nepal
3%
Indonesia
3%
Brazil
4%

China
34%

Thailand
13%
Vietnam7%

NativeS. Korea
8%

Advanced

Intermediate

Basic

None

Japanese (written)
Japanese (spoken)

Very useful
Slightly useful

English
0%

20%

40%

60%

80%

100%

Somewhat usefulNot useful

Remained
Relocated
Left
0%

Left
Japan
45%

Remainedin theKanto area
32%
Relocated toanother areaof Japan
23%

Personal decision
Job obligation
Government directive
Other

Family request
Concern for the young
Unable to leave

Remained
Relocated
Left
0%

20%

40%

60%

80%

100%

― 77 ―

20%

40%

60%

80%

100%

Television
Printed media
Traditional internet media
Social media

Overseas news source
Overseas government
Overseas research/academic institution
International organization (IAEA, Red Cross, etc.)
Family, friends, colleagues, etc.
3rd party other than family, friends, colleagues, etc.
Japanese news source
Japanese government
Japanese research/academic institution
Tokyo Electric Power Company (Tepco)
Other
Most-trusted information sources

RadioInter-personal
Direct communication tools
Crisis mapping

Remained

n=315

Relocated

n=192

Left

n=444

Remained

n=223

Relocated

n=236

Left

n=348

Remained

n=169

Relocated

n=143

Left

n=446

Remained

0%

20%

40%

60%

80%

100%

Relocated
Left
0%

20%

40%

60%

80%

100%

80%

100%

Least-trusted information sources
Remained
Relocated
Left
0%

20%

40%

60%

Safety of family, friends, etc.
Food & water supply
Electricity & other utilities
Earthquake & tsunami damage
Evacuation & shelters
Remained

n=542

Relocated

n=371

Left

n=777

Remained

n=592

Relocated

n=490

Left

n=925

Remained

n=474

Relocated

n=345

Left

n=671

0%

― 78 ―

Radiation level & risk
Transportation systems
Earthquake & tsunami char.
Government response
School & business continuity

20%

40%

60%

80%

100%

Was confused by conflicting or differing
information
Unable to access information due to mobile
congestion, power outage, etc.
Couldnt understand information due to lack oflanguage comprehension
Couldnt understand information due to difficult
or unfamiliar terminology
Unable to find the information due to difficulty insearching or locating it
Other
Remained
Relocated
Left
0%

Safety of family, friends, etc.
Food & water supply
Electricity & other utilities
Earthquake & tsunami damage
Evacuation & shelters

20%

40%

60%

80%

100%

Radiation level & risk
Transportation systems
Earthquake & tsunami char.
Government response
School & business continuity
Television
Printed media
Traditional internet media
Social media

RadioInter-personal
Direct communication tools
Crisis mapping

Remained

n=369

Relocated

n=261

Left

n=517

Remained

n=348

Remained

n=192

n=271

Relocated

n=111

Relocated
Left

n=504

Left

n=245

Remained

n=222

Remained

n=190

Relocated

n=188

Relocated

n=174

Left

n=344

0%

20%

40%

60%

80%

100%

Left

n=286

Remained

n=137

Relocated

n=109

Left

n=309

0%

― 79 ―

20%

40%

60%

80%

100%

Native

Advanced

Intermediate

Basic

None

Personal decision
Job obligation
Government directive
Other

Remained
Relocated
Left

Family request
Concern for the young
Unable to leave

Remained

Remained

Relocated

Relocated

Left

Left

Remained

Remained
Relocated

Relocated

Left

Left
0%

20%

40%

60%

80%

0%

100%

― 80 ―

20%

40%

60%

80%

100%

Personal decision
Job obligation
Government directive
Other

Remained

Relocated

Left

Family request
Concern for the young
Unable to leave

Remained

n=58

Relocated

n=50

Left

n=108

Remained

n=19

Relocated

n=15

Left

n=57

China

N=151

Thailand

N=55

S. Korea

N=37

Remained

n=9Vietnam

N=33

Relocated

n=3

0%

20%

40%

60%

80%

100%

Left

n=44

Remained

n=35

Relocated

n=6

Left

n=12

0%

― 81 ―

20%

40%

60%

80%

100%

― 82 ―

381
― 83 ―

382― 84 ―

383― 85 ―

384― 86 ―

385― 87 ―

386― 88 ―

387― 89 ―

388― 90 ―

389― 91 ―

390― 92 ―

373― 93 ―

374― 94 ―

375― 95 ―

376― 96 ―

377― 97 ―

378― 98 ―

379― 99 ―

380― 100 ―

地域安全学会梗概集
No.31,
ᆅᇦᏳ඲Ꮫ఍᱾ᴫ㞟
No.31,2012.
2012. 1111ᮾ᪥ᮏ኱㟈⅏࡟࠾ࡅࡿ⿕⅏ఫẸࡢ⏕ά෌ᘓ࡟㛵ࡍࡿ₯ᅾⓗ࡞㑅ᢥ⫥ࡢㄪᰝ
An Investigation on the potential choices of livelihood rehabilitationfrom the Great East Japan Earthquake12

1‫ ⏣Ⰽۑ‬ᙬᜨ 㸪ຍ⸨ Ꮥ᫂ 㸪Maria Bernadet Karina DEWI 㸪
345ᯇᑿ ୍㑻 㸪Ώ఍ Ύ἞ 㸪㛵㇂ ┤ஓ
1
2
3
Sae SHIKITA , Takaaki KATO , Maria Bernadet Karina DEWI ,Ichirou MATSUO4, Seiji WATARAI5 and Naoya SEKIYA6
1ᮾி኱Ꮫ⏕⏘ᢏ⾡◊✲ᡤ 㒔ᕷᇶ┙Ᏻ඲ᕤᏛᅜ㝿◊✲ࢭࣥࢱ࣮International Research Center for Urban Safety, Institute of Industrial Science, the University of Tokyo2ᮾி኱Ꮫ⏕⏘ᢏ⾡◊✲ᡤ 㒔ᕷᇶ┙Ᏻ඲ᕤᏛᅜ㝿◊✲ࢭࣥࢱ࣮ ෸ᩍᤵ
Assosiate Professer, International Research Center for Urban Safety, Institute of Industrial Science, the Universityof Tokyo3NPOἲே ⎔ቃ㜵⅏⥲ྜᨻ⟇◊✲ᶵᵓ㸦CeMI㸧 ⌮஦
Director, NPO Crisis & Environment Management Policy Institute (CeMI)
4NPOἲே ᪥ᮏ㒔ᕷィ⏬ᐙ༠఍ ๪఍㛗
Vice-chairperson, NPO Japan Society of Urban and Regional Planners
5ᮾὒ኱Ꮫ ♫఍Ꮫ㒊࣓ࢹ࢕࢔ࢥ࣑ࣗࢽࢣ࣮ࢩࣙࣥᏛ⛉ ෸ᩍᤵ
Assosiate Professer, Department of Media and Communications, Faculty of Sociology, Toyo University
Villages within the jurisdiction of Kamaishi Eastern Fishery Association, located in the north coast of Kamaishi
City, Iwate Prefecture, were damaged by the Great East Japan Earthquake. Citizen participation in the process ofreconstruction is gaining popularity among the locals. This paper analyzes information on eighteen households fromeach village through interviews on damages suffered, economic situations, relationships with their neighborhoods,
and awareness on disaster risks, and this information is necessary to discussion on regional reconstruction plan. And
information from announcement of administrative organization, newspapers and websites about the reconstruction
situation is also analyzed to find out the problems of the regional reconstruction.
Keywords : the Great East Japan Earthquake, Kamaishi City, reconstruction, rehabilitation, citizen participation,interview1.

ᑐ㇟ᆅᇦࡢᴫせ࡜㟈⅏࡛ࡢ⿕ᐖ(1)ᆅᇦࡢᴫせࠊᪧ᮶ࡢㄢ㢟ᒾᡭ┴㔩▼ᕷࡣ㠃✚441.43੎㸪2010ᖺ᫬Ⅼ࡛ࡢேཱྀࡣ
39,574ே1ࡢ㒔ᕷ࡛࠶ࡿ㸬᪥ᮏࡢ㏆௦〇㕲Ⓨ⚈ࡢᆅ࡜ࡋ࡚
ࡢṔྐࢆࡶࡕ㸪࠿ࡘ࡚ࡣࠕ㕲࡜㨶ࡢࡲࡕࠖ࡜ࡋ࡚㕲㗰ᴗ㸪
⁺ᴗࢆ୺せ⏘ᴗ࡜ࡋ࡚Ⓨᒎࡋࡓࡀ㸪1960ᖺ௦༙ࡤ௨㝆㸪㕲㗰ᴗࡢ⾶㏥ࡸ㖔ᒣࡢ㛢㙐࡟కࡗ࡚ேཱྀࡣᛴῶࡋ㸪⌧ᅾ࡛ࡣࣆ࣮ࢡ᫬92,123ேࡢ༙ศࢆୗᅇࡗ࡚࠸ࡿ㸬ᑵᴗ⪅ᩘࡢῶᑡࡶ⥆࠸࡚࠾ࡾ㸪≉࡟➨1ḟ⏘ᴗ࡛㢧ⴭ࡛࠶ࡿ㸬࡞࠾㸪
2010ᖺ࡟ࡣ⥲ົ┬࡟ࡼࡾ㐣␯ᆅᇦ࡟ᣦᐃࡉࢀ࡚࠸ࡿ㸬2௒ᅇㄪᰝศᯒࡢᑐ㇟࡜ࡋࡓ㸪㔩▼ᮾ㒊⁺ᴗ༠ྠ⤌ྜ㸦௨ୗ㸪ᮾ㒊⁺༠㸧⟶ෆࡢᆅᇦࡣ㸪㔩▼ᕷࡢ㒔ᚰ㒊ࡼࡾࡶ໭ഃࡢἢᓊ࡟఩⨨ࡍࡿ⟽ᓮ༙ᓥࢆ୰ᚰ࡟㸪ᐊ὾㸪∦ᓊ㸪᰿὾㸪⟽ᓮ㸪ⓑ὾㸪௬ᐟ㸪᱓ࡢ὾㸪୧▼ࡢ8ࡘࡢ㞟ⴠ࡛ᵓᡂࡉࢀ࡚࠸ࡿ㸦ᅗ1ཧ↷㸧㸬ࡑࡢ࠺ࡕ7ࡘࡣࡑࢀࡒࢀ⁺ࢆࡶࡕ㸬ఫẸࡢ኱༙ࡀ⁺ᴗࢆ୺࡞⫋ᴗ㸪࠶ࡿ࠸ࡣ๪ᴗ࡜
ࡋ࡚࠸ࡿ㸬⁺ᴗ࡟࠾࠸࡚ࡣ65ṓࢆ㉸࠼࡚ࡶ᧯ᴗࢆ⥆ࡅࡿࡇ࡜ࡀ୍⯡ⓗ࡛㸪௚ࡢᴗ✀࡟ẚ࡭ࡿ࡜㧗㱋⪅ࡢᑵᴗ⋡ࡣ㧗࠸࡜⪃࠼ࡽࢀࡿ㸬୍᪉࡛㸪ᑡᏊ㧗㱋໬ࡣᕷᇦ඲యࡢᖹ

ᆒ࡟ẚ࡭ࡿ࡜῝้࡛࠶ࡿ㸬⌧ᆅ࡛ࡢ⪺ࡁྲྀࡾㄪᰝ࡟ࡼࡿ࡜㸪㞟ⴠࡢⱝ࠸ୡ௦ࡣ㸪ከࡃࡀ௙஦ࢆồࡵ࡚ᕷ୰ᚰ㒊࠶ࡿ࠸ࡣᕷእ࡬ὶฟࡋ࡚࠸
ࡿᶍᵝ࡛࠶ࡿ㸬⁺ᴗࢆ⥅ࡄ࡜࠸࠺㑅ᢥ⫥ࡣ㸪⁺ᴗࡣከ኱࡞ປຊࢆせࡍࡿ௙஦࡛࠶ࡾ㸪㏆ᖺ㨶౯ࡢప㏞࡟ࡼࡾ⤒῭ⓗ࡞≧ἣࡶᝏ໬ࡋ࡚࠸ࡿࡇ࡜࠿ࡽ㸪ᩗ㐲ࡉࢀࡓࡾぶୡ௦ࡶᏊ౪ࡀ⁺ᴗ࡟ᑵࡃࡇ࡜ࢆᮃࡲ࡞࠿ࡗࡓࡾ࡜࠸࠺≧ἣࡀ࠶ࡿ㸬ࡲࡓ㸪ⓑ὾࡞࡝༙ᓥୖ࡟࠶ࡿ୍㒊ࡢ㞟ⴠ࡛ࡣ㸪㟈⅏௨๓࠿ࡽ㐨㊰஦᝟ࡢᝏࡉࡀఫẸࡢ㛫࡛୙‶ࡢ✀࡜࡞ࡗ࡚࠸
ࡓ㸬ࡍ࡞ࢃࡕ㸪ෆ㝣㒊࡬࢔ࢡࢭࢫࡍࡿࡓࡵࡢ㐨㊰ࡀ㸪ᾏᓊ⥺ࡂࡾࡂࡾࢆ㏻ࡾ㸪࡜ࡁ࡟ࡣἼࢆ⿕ࡿࡼ࠺࡞⣽࠸㐨㊰ࡋ࠿࡞ࡃ㸪⾤ⅉࡶ୙༑ศ࡛༴㝤࡛࠶ࡿ࡜࠸࠺ࡇ࡜࡛࠶ࡿ㸬୍᪉࡛㸪༙ᓥ༡ഃࡢ௜ࡅ᰿࡟఩⨨ࡍࡿ୧▼ᆅ༊࡛ࡣ㸪㟈⅏┤๓ࡢ2011ᖺ3᭶5᪥࡟୕㝣⦪㈏㐨ࡀ㛤㏻ࡋ࡚࠾ࡾ㸪㟈⅏᫬࡟ࡣ㑊㞴㊰࡜ࡋ࡚ᙺ❧ࡗࡓ࡜࠸࠺⤒⦋ࡀ࠶ࡿ㸬3(2)ᮾ᪥ᮏ኱㟈⅏࡛ࡢ⿕⅏≧ἣ㔩▼ᕷ࡛ࡣ㸪ἢᓊࡢ඲ᇦࡀὠἼ࡟ࡼࡾ⏒኱࡞⿕ᐖࢆཷࡅ࡚࠸ࡿ㸬㔩▼ ࡛ࡣ㸪ὠἼࡢ᭱኱Ἴࡢ㧗ࡉࡣ9.3m࡜᥎

－ 29 －― 101 ―

ᐃࡉࢀ࡚࠸ࡿ㸬Ṛ⪅࣭⾜᪉୙᫂⪅ࡣᕷෆ඲ᇦ࡛931ே࡟ୖࡾ㸪ࡇࡢ࠺ࡕ6๭௨ୖࡀ65ṓ௨ୖࡢ㧗㱋⪅࡛࠶ࡿ㸬࡞࠿࡛ࡶ㸪ᮾ㒊⁺༠⟶ෆ࢚ࣜ࢔ࡢྵࡲࢀࡿ㬼ఫᒃᆅ༊ࡢṚ⪅࣭⾜᪉୙᫂⪅ࡣ㸪ᕷ඲యࡢ62.6%࡟┦ᙜࡍࡿ583ே࡜࡞ࡗ࡚
࠸ࡿ㸬ࡲࡓ㸪ᘓ≀⿕ᐖ࡟ࡘ࠸࡚ࡶ㸪඲ቯ࣭኱つᶍ༙ቯࡋࡓᘓ≀ࡀᕷ඲య࡛ࡣ3,343Ჷ࡛࠶ࡿࡢ࡟ᑐࡋ㸪㬼ఫᒃᆅ༊࡛ࡣࡑࡢ48.3%ࢆ༨ࡵࡿ1,614Ჷ࡜࡞ࡗ࡚࠾ࡾ㸪ᕷࡢ୰࡛ࡶ≉࡟኱ࡁ࡞⿕ᐖࢆཷࡅ࡚࠸ࡿࡇ࡜ࡀࢃ࠿ࡿ㸬4࡞࠾㸪ᕷ
ෆ࡛Ⓨ⏕ࡋࡓ㟈⅏ᗫᲠ≀ࡢ㔞ࡣ820,000t࡜᥎ᐃࡉࢀ࡚࠸
ࡿ㸬5⁺ᮧᆅᇦ࡛ࡣ㸪⁺⯪ࡸຍᕤ᪋タ㸪෭ⶶ᪋タ࡞࡝ࡢ⁺ᴗ᪋タࡶ኱ࡁ࡞⿕ᐖࢆཷࡅ㸪⁺ᴗࡣ୰᩿ࡍࡿࡇ࡜࡜࡞ࡗࡓ㸬ᮾ㒊⁺༠⟶ෆࡢ㞟ⴠ࡛ࡣ㸪ⓑ὾ࡢࡼ࠺࡟༙ᩘ㏆ࡃࡢᐙᒇࡀὶࡉࢀࡎ࡟ṧࡗࡓ㞟ⴠࡶ࠶ࡿࡀ㸪୧▼ࡢࡼ࠺࡟2-3㌺ࢆṧࡋ࡚ᐙᒇࡢ࡯࡜ࢇ࡝ࡀὶኻࡋࡓ㞟ⴠࡶ࠶ࡾ㸪ࡑࡢ⿕ᐖࡣ῝้࡛࠶ࡿ㸬ᅗ 1 㔩▼ᕷ࡜ᮾ㒊⁺༠⟶ෆ (ฟ඾㸸Google Map)2.

᚟ᪧ࣭᚟⯆ࡢ⤒㐣(1)ᛂᛴᑐᛂ࣭᚟ᪧࡢ≧ἣࣛ࢖ࣇࣛ࢖ࣥࡢ᚟ᪧࡣ㸪㟁Ẽࡣ5᭶ୖ᪪㸪Ỉ㐨ࡣ7᭶୰᪪㸪㒔ᕷ࢞ࢫ࣭ᅛᐃ㟁ヰࡣ4᭶୰᪪ࡲ࡛࡟㸪࡯࡜ࢇ࡝ࡢᆅ
ᇦ࡛᚟ᪧࡋ࡚࠸ࡿ㸬4 ୍᪉࡛㕲㐨ࡣ㸪ᕷࡢἢᓊ㒊ࢆ༡໭࡟㉮ࡿJRᒣ⏣⥺࡜୕㝣㕲㐨༡ࣜ࢔ࢫ⥺࡟ࡘ࠸࡚ࡣ㸪2012ᖺ
9᭶⌧ᅾࡶ㐠ఇࡀ⥆࠸࡚࠸ࡿ㸬㑊㞴⪅ࡣᕷෆ㑊㞴ᡤ࡛᭱኱9,883ேࢆᩘ࠼ࡓࡀ㸦2011ᖺ
3᭶17᪥᫬Ⅼ㸧1㸪2011ᖺ8᭶࡟ࡣ㑊㞴ᡤࡣࡍ࡭࡚㛢タࡉࢀࡓ㸬ࡲࡓྠᖺ11᭶ึ᪪ࡲ࡛࡟ࡣ㸪ᛂᛴ௬タఫᏯࡀ3,164ᡞࡢ௬タఫᏯࡀᘓタࡉࢀ㸪࠺ࡕධᒃᡞᩘࡣ3,102ᡞ࡛࠶ࡿ㸬ࡇࡢ࡯࠿㸪⿕⅏⪅ࡢ௬ఫࡲ࠸࡜ࡋ࡚ࡣᕷႠ࣭┴ႠఫᏯ㸪Ẹ㛫㈤㈚ఫᏯࡀ฼⏝ࡉࢀ࡚࠸ࡿ㸬4㟈⅏௨๓ࡶẖᖺ600-700ேࡢேཱྀῶᑡࡀぢࡽࢀ࡚࠸ࡓ㔩▼ᕷ࡛࠶ࡿࡀ㸪㟈⅏ᚋ8࠿᭶࡛2052ேࡢῶᑡࡀぢࡽࢀ࡚࠸ࡿ㸬ࡇࡇ࠿ࡽṚஸ⪅ᩘࢆ㝖ࡃ࡜658ே࡜࡞ࡾ㸪≉࡟㌿ฟ⪅ᩘࡣ๓ᖺࡢྠ᫬ᮇ࡜ẚ㍑ࡍࡿ࡜790ேቑຍࡋ࡚࠸ࡿ㸬ࡇࡢ㛫࡟㸪ᑐ㇟ᆅᇦࡢྵࡲࢀࡿ㬼ఫᒃᆅ༊࡛ࡣ㸪Ṛ⪅࣭୙᫂⪅ᩘࢆ㝖ࡃ࡜1,229ேࡀ㌿ฟࡋ࡚࠸ࡿ㸬ࡇࢀࡣࠊ㟈⅏๓ࡢ
ேཱྀ6,630ே࡟ᑐࡋ࡚18.5%࡟┦ᙜࡋ㸪Ṛ⪅࣭୙᫂⪅ᩘࡶ

ྵࡵࡿ࡜27.3%࡜ࡶ࡞ࡿ㸬4㟈⅏ᗫᲠ≀ࡢ௬⨨ࡁሙ࡬ࡢᦙฟ≧ἣࡣ㸪2012ᖺ8᭶ᮎ࡛ᗫᲠ≀඲యࡢ88%࡜࡞ࡗ࡚࠸ࡿ୍᪉࡛㸪ฎ⌮࣭ฎศẚ⋡
ࡣ7%࡟࡜࡝ࡲࡗ࡚࠸ࡿ㸬࡞࠾┠ᶆᮇ᪥ࡣᖹᡂ26ᖺ3᭶࡜
ࡉࢀ࡚࠸ࡿ㸬5(2)᚟⯆ࡢ⤒㐣a. ⾜ᨻ୺యࡢືࡁ
ᒾᡭ┴࡛ࡣ2011ᖺ8᭶࡟᚟⯆ᇶᮏィ⏬࠾ࡼࡧ᚟⯆ᐇ᪋ィ⏬ࡀ⟇ᐃࡉࢀࡓ㸬ࡲࡓ㸪㔩▼ᕷࡣྠᖺ4᭶୰᪪࡟ࡣ᚟⯆ࡲࡕ࡙ࡃࡾᇶᮏ᪉㔪ࢆⓎ⾲ࡋ࡚࠸ࡿࡶࡢࡢ㸪᚟⯆ᇶᮏィ⏬
ࡢ⟇ᐃ࡟ࡣ᫬㛫ࢆせࡋ࡚࠾ࡾ㸪㦵Ꮚ᱌ࡢⓎ⾲ࡣ6᭶ୗ᪪㸪୰㛫᱌ࡣ10᭶ୗ᪪㸪᭱⤊ⓗ࡞ィ⏬ࡢỴᐃࡣ12᭶ୗ᪪࡜࡞
ࡗ࡚࠸ࡿ㸬ࡇࡢ㛫㸪ᕷ࡛ࡣ᚟⯆ᇶᮏィ⏬᱌ࡢ᳨ウࡢࡓࡵࡢ」ᩘࡢ༠㆟᳨࣭ウᶵ㛵ࡀタ⨨ࡉࢀ࡚࠸ࡿ㸬ࡇࡢ࠺ࡕ୰
ᚰ࡜࡞ࡗ࡚࠸ࡿࡢࡣ3ࡘࡢ఍㆟࣭ጤဨ఍࡛࠶ࡾ㸪ᕷ㛗ࡸᕷ⫋ဨ࡟ࡼࡗ࡚ᵓᡂࡉࢀࡿࠕ⅏ᐖ᚟⯆ࣉࣟࢪ࢙ࢡࢺ᥎㐍ᮏ㒊఍㆟ࠖ㸪ᕷ⥲ྜᑂ㆟఍ࡢጤဨࡸ㛵ಀᅋయ࣭⾜ᨻᶵ㛵ࡢᙺ⫋ဨ㸪᭷㆑⪅࡛ᵓᡂࡉࢀ㸪᥎㐍ᮏ㒊఍㆟ࡢ࣓ࣥࣂ࣮ࡶ
ฟᖍࡋ࡚࠸ࡿࠕ᚟⯆ࡲࡕ࡙ࡃࡾጤဨ఍ࠖ㸪ࡑࡋ࡚ᘓ⠏ᐙࡸ኱Ꮫ㛵ಀ⪅㸪㛵ಀᅋయࡢᙺ⫋ဨ࡟ࡼࡗ࡚ᵓᡂࡉࢀࡿ
ࠕ᚟⯆ࣉࣟࢪ࢙ࢡࢺ఍㆟࡛ࠖ࠶ࡿ㸬ࡑࡢ௚㸪୍⯡ࡢᕷẸࡀⓎゝࡍࡿሙ࡜ࡋ࡚㸪ࠕ㔩▼᚟⯆ࡲࡕ࡙ࡃࡾ㞟୰࣮࣡ࢡࢩࣙࢵࣉࠖ㸪ࠕ᚟⯆ࡲࡕ࡙ࡃࡾ᠓ㄯ఍ࠖ㸪ࠕ᚟⯆ᆅᇦ఍㆟ࠖ࡞࡝ࡀ㛤ദࡉࢀࡓ㸬ࡇࡢࡼ࠺࡟ᕷẸࡀពぢࡸ㉁ၥࢆ
Ⓨࡍࡿࡇ࡜ࡢ࡛ࡁࡿሙࡣ⏝ពࡉࢀ࡚࠸ࡓࡀ㸪ࡑࡢෆᐜࡀ
࡝ࡢ⛬ᗘ᚟⯆ィ⏬ࡢ⟇ᐃࣉࣟࢭࢫ࡛⏕࠿ࡉࢀࡓ࠿ࡣ୙᫂
░࡛࠶ࡿ㸬ࡓ࡜࠼ࡤ㸪࢖ࣥࢱ࣮ࢿࢵࢺୖ࡛බ㛤ࡉࢀ࡚࠸ࡿ᚟⯆ࡲࡕ࡙ࡃࡾጤဨ఍ࡢ㆟஦㘓࡟ࡼࡿ࡜㸪᚟⯆ࡲࡕ࡙ࡃࡾ᠓ㄯ఍࡛࡞ࡉࢀࡓ㆟ㄽࡢࡲ࡜ࡵࡣ᚟⯆ࡲࡕ࡙ࡃࡾጤ
ဨ఍࡛㓄ᕸࡉࢀ࡚࠸ࡿࡀ㸪ጤဨ఍࡛ࡑࢀ࡟㛵㐃ࡋࡓ㆟ㄽ
ࡣ࡯࡜ࢇ࡝⾜ࢃࢀ࡚࠸࡞࠸㸬ࡲࡓ㸪᚟⯆ᆅᇦ఍㆟ࡣ㸪㔩▼ᕷࡢ࣮࣒࣮࣍࣌ࢪ࡛ࡶάືࡢ᝟ሗࡀᥖ㍕ࡉࢀ࡚࠾ࡽࡎ㸪ࡑࡢᐇែࡣ୙࡛᫂࠶ࡿ㸬ࡲࡓ㸪୰ᚰⓗ࡟ാ࠸࡚࠸ࡓ࡜⤌⧊ࡢ୍ࡘ࡜⪃࠼ࡽࢀࡿ᚟⯆ࣉࣟࢪ࢙ࢡࢺ఍㆟࡟ࡘ࠸࡚ࡶ㸪㛤ദ᪥⛬ࡣබ㛤ࡉࢀ࡚࠸ࡿࡶࡢࡢ㸪఍㆟ࡢヲࡋ࠸ෆᐜ࠾
ࡼࡧ㆟஦㘓ࡣᕷࡢ࣮࣒࣮࣍࣌ࢪ࡛ࡣබ㛤ࡉࢀ࡚࠸࡞࠸㸬㟈⅏ᚋ㸪2011ᖺ12᭶࡟ไᐃࡉࢀࡓᅜࡢ᚟⯆஺௜㔠ไᗘࡢᑐ㇟࡜࡞ࡿ஦ᴗࡢỴᐃࡣྛ⮬἞య࡛₞ḟⓗ࡟⾜ࢃࢀ࡚࠸ࡿ㸬ᒾᡭ┴࡜㔩▼ᕷ࡛ࡣ㸪᚟⯆஺௜㔠஦ᴗィ⏬ࡀ㸪⌧ᅾࡲ࡛ࡢ࡜ࡇࢁ2012ᖺ3᭶㸪7᭶㸪9᭶࡟ࡑࢀࡒࢀỴᐃࡉࢀ࡚࠸ࡿ㸬ලయⓗ࡟ࡣ㸪㒔ᕷබᅬᩚഛ஦ᴗࡸ༊⏬ᩚ⌮஦ᴗ㸪
⁺ᴗ㞟ⴠ㜵⅏ᶵ⬟ᙉ໬஦ᴗ㸪㐨㊰஦ᴗ࡞࡝ࡢ᪤Ꮡࡢ஦ᴗ
ࡢ㐺⏝࡟ຍ࠼㸪ὠἼ᚟⯆≉༊ᩚഛ஦ᴗ࡜࠸ࡗࡓ㸪2011ᖺ
12᭶࡟ไᐃࡉࢀࡓ᚟⯆≉༊ἲ࡟ࡼࡗ࡚᪂ࡓ࡟๰タࡉࢀࡓ஦ᴗࡶᑟධࡉࢀࡓ㸬ࡇࢀࡽࡢ஦ᴗࡣ᚟⯆஺௜㔠ไᗘࡢせ⥘࡟ᚑ࠸㸪ᖹᡂ23ᖺ࠿ࡽ27ᖺࡲ࡛ࡢ5ᖺ㛫ࢆィ⏬ᮇ㛫࡜ࡋ࡚࠸ࡿ㸬b. ᮾ㒊⁺༠⟶ෆࡢఫẸ⤌⧊ᮾ㒊⁺༠⟶ෆࡢᆅᇦ࡛㸪ᆅᇦఫẸࡀ⮬ᚊⓗ࡟᚟⯆ࢆ⪃࠼ࡿືࡁࡣ㸪୧▼ࡢఫẸࡀ㑊㞴ᡤࡢయ⫱㤋࡛㸪⮬ࡽࡢ㞟ⴠࡢ᚟⯆ࡢ⤮ࢆᥥࡁ㸪ᐇ⌧ࡢࡓࡵ࡟ᆅ୺࡜஺΅ࡍࡿ࡞࡝ᐇ㝿࡟ືࡁฟࡋ࡚࠸ࡓ࡜ࡇࢁ࠿ࡽጞࡲࡗࡓ㸬ࡑࡇ࡬㸪ᮾி࡟ᮏᣐᆅࢆ⨨ࡁ⅏ᐖ㛵㐃ࡢㄪᰝࢆ⾜ࡗ࡚࠸ࡿ NPO ἲே⎔ቃ㜵⅏⥲ྜᨻ⟇◊✲ᶵᵓ㸦CeMI㸧ࡢ⫋ဨࡀ㸪2011 ᖺ 5᭶࡟㟈⅏ᙜ᫬ࡢ≧ἣ࡟ࡘ࠸࡚ࡢㄪᰝ࡟ゼࢀࡓ㸬ࡑࢀ௨㝆㸪ࡇࡢ NPO ࡢ༠ຊࡢࡶ࡜㸪ᆅᇦఫẸࡣ᚟⯆࡟ྥࡅࡓ⤌⧊໬࡬࡜ືࡁࡔࡋࡓ㸬ࡣࡌࡵࡣ୧▼ࡢࡳ࡛᚟⯆ࡲࡕ࡙ࡃࡾࡢࡓࡵࡢ࣮࣡ࢡࢩ
ࣙࢵࣉࢆ⾜ࡗ࡚࠸ࡓ㸬ࡋ࠿ࡋ㸪ḟ➨࡟㸪㐨㊰ࡸ⏕ά㛵㐃

－ 30 －― 102 ―᪋タࡢ㓄⨨࡞࡝㸪᚟⯆ࡣ༙ᓥ඲య࡛⪃࠼ࡿᚲせᛶࡀ࠶ࡿ࡜࠸࠺⪃࠼ࡀ⏕ࡌ㸪6 ᭶௨㝆㸪⟽ᓮ༙ᓥࡢ௚ࡢᆅᇦࡶᕳ
ࡁ㎸ࡴࡼ࠺࡟࡞ࡗ࡚࠸ࡗࡓ㸬ࡑࡢ⤖ᯝ㸪ࡶ࡜ࡶ࡜⟽ᓮ༙ᓥ඲యࢆྵࡴᆅᇦࢆ⟶ෆ࡜ࡋ࡚࠸ࡓᮾ㒊⁺༠ࡀ୰ᚰ࡜࡞
ࡗ࡚㸪CeMI ࡸ㒔ᕷィ⏬ࡢᑓ㛛ᐙࢆ஺࠼࡞ࡀࡽ⟶ෆࡍ࡭࡚ࡢ㞟ⴠࡢ௦⾲⪅ࢆྵࡴᆅᇦ఍㆟ࢆࡦࡽࡃࡼ࠺࡟࡞ࡗࡓ㸪⟽ᓮ༙ᓥ࿘㎶ࡢᆅᇦ࡛ࡣ㸪㟈⅏ᚋ㸪ୖグࡢືࡁ௨እ࡟
ࡶᵝࠎ࡞᚟⯆㛵㐃࡛ᅋయࡀ⤌⧊ࡉࢀࡓࡾ㸪㞟ⴠࡑࢀࡒࢀ
࡛ᑓ㛛ᐙࢆᣍ࠸࡚⊂⮬ࡢࣉࣛࣥసࡾࢆ⾜ࡗࡓࡾࡍࡿືࡁ
ࡀ⏕ࡲࢀ࡚࠸ࡓ≧ἣ࡛࠶ࡗࡓ㸬ࡇ࠺ࡋࡓ୰㸪୧▼࠿ࡽጞࡲࡗࡓᮾ㒊⁺༠⟶ෆࡢఫẸ఍㆟ࡶ㸪༢࡞ࡿ⮬୺ⓗ࡞ᆅᇦ఍㆟࡜࠸࠺❧ሙ࡛ࡣ㸪ᕷࢆࡣࡌࡵ࡜ࡍࡿ⾜ᨻ⤌⧊࡟ᑐࡋ
࡚Ⓨゝຊࡀᙅ࠸࡜࠸࠺ࡇ࡜࡛㸪NPO ἲே໬ࡍࡿࡇ࡜ࢆ┠ᣦࡍࡼ࠺࡟࡞ࡗࡓ㸬ࡑࡋ࡚㸪2012 ᖺ 3 ᭶࡟ࡣ NPO ἲே㔩▼ᮾ㒊⁺༠⟶ෆ᚟⯆ᕷẸ఍㆟㸦࠾ࡣࡇࡊࡁᕷẸ఍㆟㸧࡜ࡋ࡚ṇᘧ࡟ NPO ἲே໬ࡉࢀࡓ㸬ࡑࡢ⌮஦ࡸ஦ົᒁ㛗ࡣ㸪ᮾ㒊⁺༠㛵ಀ⪅ࡸ⏫ෆ఍㛗࡞࡝ࡀ୰ᚰ࡜࡞ࡗ࡚࠸ࡿ㸬ࡇࡢఫẸ఍㆟ࡢ 2011 ᖺෆࡢືࡁࢆぢࡿ㝈ࡾ࡛ࡣ㸪NPO
࡜ࡋ࡚ࡢ┠ⓗࡣ᫂☜࡟࡞ࡗ࡚࠸࡞࠿ࡗࡓ㸬ࡋ࠿ࡋ㟈⅏࠿
ࡽ 1 ᖺ௨ୖࡀ⤒ࡗࡓ᭱㏆࡛ࡣ㸪4 ࡘࡢ࣮࣡࢟ࣥࢢࢢ࣮ࣝ
ࣉ࡟ศ࠿ࢀ᳨࡚ウసᴗࢆࡍࡿ࡜࠸࠺᪉㔪ࡀ⤒ࡗ࡚࠾ࡾ㸪
NPO ࡜ࡋ࡚ࡢᮏ᱁ⓗ࡞άື࡟ධࢁ࠺࡜ࡋ࡚࠸ࡿ㸬4 ࡘࡢ࣮࣡࢟ࣥࢢࢢ࣮ࣝࣉ࡜ࡣ㸪㞟ⴠࡈ࡜ࡢ᚟⯆ࡲࡕ࡙ࡃࡾᨭ
᥼ࡸῶ⅏ᑐ⟇࡞࡝ࡢࣉࣛࣥࢆ⪃࠼ࡿࠕ᚟⯆࣭ῶ⅏ࡲࡕ࡙ࡃࡾ࣭ࡦ࡜࡙ࡃࡾ஦ᴗ᳨ウ WGࠖ㸪ࠕ᪂⏘ᴗ࡜㞠⏝ࡢ๰ฟ ஦ ᴗ ᳨ ウ WGࠖ 㸪 ࠕ 㜵 ⅏ ᩍ ⫱ ࡜ グ 㘓 ఏ ᢎ ஦ ᴗ ᳨ ウ
WGࠖ㸪ࠕ࠾ࡣࡇࡊࡁほගࠊ≉⏘ရࡢ㛤Ⓨ࡜㈍኎ಁ㐍஦ᴗ᳨ウ WG࡛ࠖ࠶ࡿ㸬

3.

࢖ࣥࢱࣅ࣮ࣗㄪᰝ

(1) ㄪᰝࡢ┠ⓗ᚟⯆ࣉࣛࣥࡢ⟇ᐃ࡟࠾࠸࡚ࡣ㸪㛗ᮇⓗ࣭ᆅ༊඲ᇦⓗ࡞
どⅬࡀඃඛࡉࢀࡿഴྥ࡟࠶ࡿ㸬ࡇࢀࡣ⾜ᨻ୺ᑟࡢ༠㆟⤌⧊㸪࠾ࡣࡇࡊࡁᕷẸ఍㆟࡞࡝ࡢᕷẸ⤌⧊࠸ࡎࢀ࡟࠾ࡅࡿ᳨ウ࡟ࡶ࠶࡚ࡣࡲࡿ࡜ゝ࠼ࡿ㸬ࡋ࠿ࡋ㸪▷ᮇⓗ࣭ᒁᡤⓗ࡞どⅬ࡛⏕ά෌ᘓࢆ⪃࠼ࢀࡤ㸪ே࡟ࡼࡗ࡚ࡣ㑅ᢥྍ⬟࡞㑅ᢥ⫥ࡀ㝈ࡽࢀ࡚࠸ࡿሙྜࡀ࠶
ࡿ㸬ࡇࢀࡣ㸪⤒῭ⓗ࡞⌮⏤ࡸࣔࣅࣜࢸ࢕㸪㒔ᕷᶵ⬟࡬ࡢ࢔ࢡࢭࢩࣅࣜࢸ࢕࡞࡝࡟ࡼࡗ࡚Ỵࡲࡗ࡚ࡃࡿࡶࡢ࡛࠶ࡿ㸬ࡑࡢࡼ࠺࡞ไ㝈ࡢ࠿࠿ࡾࡸࡍ࠸࡜⪃࠼ࡽࢀࡿ㧗㱋⪅ࡀࡇࡢᆅᇦ࡛ࡣ㧗࠸๭ྜࢆ༨ࡵ࡚࠸ࡓࡾ㸪᚟⯆ࣉࣛࣥࢆ⪃࠼ࡿືࡁ࡟㸪ᑠࡉ࡞Ꮚ౪ࢆ㣴⫱ࡋ࡚࠸ࡿࡼ࠺࡞ⱝ࠸ᒙࡀධ
ࡾ࡙ࡽ࠿ࡗࡓࡾࡍࡿ≧ἣ࡛ࡣ㸪ฟ᮶ୖࡀࡗࡓ᚟⯆ࣉࣛࣥ࡟ࡘ࠸࡚࠸ࡅࡎ㸪㞟ⴠ࡟ᡠࡽ࡞࠸㸪ᡠࢀ࡞࠸ேࡀከࡃฟ
ࡿ࡜࠸࠺ྍ⬟ᛶࡀ࠶ࡿ㸬ࡲࡓ㸪୰࡟ࡣࡍ࡛࡟㞟ⴠ࡟ࡣᡠࡽ࡞࠸ࡇ࡜ࢆ⪃࠼࡚࠸ࡿேࡓࡕࡶ࠸ࡿྍ⬟ᛶࡣ࠶ࡿ㸬≉࡟㸪௚ࡢᆅᇦ࡛ࡢᬽࡽ
ࡋ࡟㐺ᛂࡋࡸࡍ࠸ⱝᖺᒙ࡟㸪ࡇ࠺࠸ࡗࡓ⪃࠼᪉ࡀᏑᅾࡍ
ࡿ࡜ண᝿ࡉࢀࡿ㸬ࡇࡢࡓࡵ㸪ከࡃࡢேࡀ㞟ⴠ࡟ᡠࡿ࡜࠸
࠺๓ᥦ࡟❧ࡗ࡚సࡗࡓ᚟⯆ࣉࣛࣥࡀ㸪ᐇ㝿࡟ࡣᡂࡾ❧ࡓ࡞ࡃ࡞ࡿ࡜࠸࠺ࡇ࡜ࡶ࠶ࡾᚓ࡞࠸࡜ࡣゝ࠼࡞࠸㸬ࡉࡽ࡟ࡣ㸪⮬ศࡓࡕࡢពᛮࡸᕼᮃ࡜ࡋ࡚ᣢࡗ࡚࠸ࡓࡾ
⾲᫂ࡋࡓࡾࡋ࡚࠸ࡿ⏕ά෌ᘓࡢ㑅ᢥ⫥ࡀ㸪ࡑࡢୡᖏࡸᆅ
ᇦࡢ≧ἣࢆᐈほⓗ࡟⪃࠼ࢀࡤ㑅ᢥ୙ྍ⬟࡛࠶ࡗࡓࡾ㸪㏫࡟㑅ᢥྍ⬟࡞㑅ᢥ⫥ࢆ⪃៖࡟࠸ࢀ࡚࠸࡞࠿ࡗࡓࡾࡍࡿሙ
ྜࡶ࠶ࡿ㸬ࡇࡢࡼ࠺࡞≧ἣୗ࡛㸪⾲㠃ⓗ࡞ᕼᮃㄪᰝ࢔ࣥ
ࢣ࣮ࢺࢆ⾜ࡗࡓ࡜ࡇࢁ࡛㸪ᆅᇦࡢᑗ᮶ീࢆᥥࡃࡓࡵࡢᇶ
♏࡜࡞ࡿ᝟ሗ࡜ࡋ࡚ⓗ☜࡞ࡶࡢࡣᚓ㞴࠸࡜⪃࠼ࡽࢀࡿ㸬௨ୖࡢࡼ࠺࡞⌮⏤࠿ࡽ㸪ᆅᇦ࡟㐺ษ࡞᚟⯆ࣉࣛࣥࢆ⪃࠼ࡿᅵྎࡢ୍㒊࡜࡞ࡿ㈨ᩱ࡜ࡍࡿࡓࡵ㸪᚟⯆ࡢྲྀࡾ⤌ࡳ࡟ࡣ✚ᴟⓗ࡟ཧຍࡋ࡚࠸࡞࠸ఫẸࡢ⌧≧ࡸᛮᝨࢆㄪᰝࡋ㸪ࡑ࠺ࡋࡓேࡓࡕࡀ௒ᚋ࡜ࡿࡇ࡜ࡢ࡛ࡁࡿ㑅ᢥ⫥ࡢ⠊ᅖࢆᐈほⓗ࡟ศᯒࡍࡿࡇ࡜ࡀㄪᰝࡢ┠ⓗ࡛࠶ࡿ㸬ࡇࢀ࡟ࡼࡾ㸪ᆅᇦࡢ᚟⯆ࡢᒎᮃࡢᰂ㌾ᛶࢆ☜ಖࡋ㸪᳨ウࡢ㐣⛬࡟⥲ྜⓗ࡞どⅬࢆ⤌ࡳ㎸ࡴࡇ࡜ࢆ᭱⤊ⓗ࡞ࡡࡽ࠸࡜ࡍࡿ㸬(2) ㄪᰝ࣭ศᯒࡢ᪉ἲ
௒ᅇࡢㄪᰝ࡛ࡣ㸪୧▼࡜ⓑ὾ 2 ࡘࡢ㞟ⴠ࡟ࡘ࠸࡚㸪௬タఫᏯ࡟ධᒃࡋ࡚࠸ࡿ㞟ⴠࡈ࡜ࡢ⿕⅏⪅࡟㸪ᑐ㠃࡛࢖ࣥࢱࣅ࣮ࣗࢆ⾜ࡗࡓ㸬ྛᡞ࡛ࡣ㸪࢔ࣥࢣ࣮ࢺ⚊ࢆㄪᰝ⪅ࡀᣢࡗࡓ≧ែ࡛㉁ၥࡋ㸪⪺ࡁྲྀࡗࡓෆᐜࢆㄪᰝ⪅ࡀ᭩ࡁྲྀࡿ࡜࠸࠺ᙧᘧ࡛ㄪᰝࢆ⾜ࡗࡓ㸬ྛᡞ࡬ࡢ࢖ࣥࢱࣅ࣮࡛ࣗࡢ㉁ၥࡣ㸪࢔ࣥࢣ࣮ࢺ⚊࡟グ㍕ࡋࡓ㉁ၥ㡯┠࡟ἢࡗ࡚⾜ࡗࡓ㸬ࡓࡔࡋࠊⓑ὾࡛ࡢ࢖ࣥ
ࢱࣅ࣮ࣗᐇ᪋ᚋ㸪ᐇ᪋ࡢ⤒㦂ࢆ㋃ࡲ࠼࡚࢔ࣥࢣ࣮ࢺࡢෆ
ᐜࡢᨵⰋࢆ⾜ࡗࡓࡓࡵ㸪ⓑ὾࡜୧▼࡛ࡣ㉁ၥࡢෆᐜࡀ␗
࡞ࡿ㒊ศࡀ࠶ࡿ㸬ࡲࡓ㸪㉁ၥࡢ㡰␒ࡸෆᐜࡣࡑࢀࡒࢀࡢ
ୡᖏ࡛ࡢ఍ヰࡢ㐍ࡳ᪉࡟ᛂࡌ࡚ኚ࠼࡚࠾ࡾ㸪ᚲࡎࡋࡶࣇ
࢛࣮࣐ࢵࢺ㏻ࡾ࡟ࡣ⾜ࢃ࡞࠿ࡗࡓ㸬ⓑ὾࡟ࡘ࠸࡚ࡣ㸪2011 ᖺ 10 ᭶ 9 ᪥࠿ࡽ 10 ᪥࡟࠿ࡅ࡚
ㄪᰝࢆ⾜ࡗࡓ㸬ゼၥࡋࡓ௬タఫᏯࡣⓑ὾ࡢ㞟ⴠෆ࡟఩⨨ࡋ㸪ධᒃࡋ࡚࠸ࡓⓑ὾ࡢఫẸ⣙ 20 ୡᖏࡢ࠺ࡕ㸪8 ୡᖏ࡟ᑐࡋ࡚࢖ࣥࢱࣅ࣮ࣗࢆ⾜ࡗࡓ㸬ୡᖏ୺ࡢᖺ㱋ศᕸࡣ㸪40
௦ࡀ 1 ே㸪60 ௦࣭70 ௦ࡀࡑࢀࡒࢀ 3 ே㸪80 ௦ࡀ 1 ே࡛࠶ࡗࡓ㸬୧▼࡟ࡘ࠸࡚ࡣ㸪ྠᖺ 12 ᭶ 1 ᪥࠿ࡽ 2 ᪥࡟࠿ࡅ࡚㸪㞟ⴠ࠿ࡽࡣᑡࡋ㞳ࢀࡓ⏥Ꮚᆅ༊࠾ࡼࡧ㬼ఫᒃᆅ༊㸦᪥ྥᆅ༊㸧ࡢ 2 ⟠ᡤࡢ௬タఫᏯ࡟ධᒃࡋ࡚࠸ࡓ୧▼ࡢఫẸྜィ
10 ୡᖏ࡟ᑐࡋ࡚࢖ࣥࢱࣅ࣮ࣗࢆ⾜ࡗࡓ㸬ୡᖏ୺ࡢᖺ㱋ศᕸࡣ㸪30 ௦࣭50 ௦ࡀࡑࢀࡒࢀ 1 ே㸪60 ௦ࡀ 3 ே㸪70 ௦
ࡀ 5 ே࡛࠶ࡗࡓ㸬㉁ၥ㡯┠ࡣ㸪ᖺ㱋ࡸᛶู㸪ୡᖏᵓᡂ࡞࡝ࡢୡᖏᒓᛶ㸪
཰ධࡸ㈓⵳㸪೉ධ㔠࡞࡝⤒῭ⓗ࡞㡯┠㸪㞟ⴠ࡜ࡢ㛵ࢃࡾࡸᒃఫ⥅⥆ពᛮ㸪ᜏஂఫᏯࡢᕼᮃᙧែ࡞࡝ఫᏯ෌ᘓ࡟㛵ࡍࡿ㡯┠㸪⅏ᐖࣜࢫࢡ࡟ᑐࡍࡿチᐜᗘ㸪ồࡵࡿ㜵⅏ᑐ⟇ࡢ⛬ᗘ࡞࡝㜵⅏࡟㛵ࡍࡿ㡯┠㸪ࡑࡢ௚᚟⯆ࡲࡕ࡙ࡃࡾ࡟
ᮃࡴࡇ࡜࡞࡝࡛࠶ࡿ㸬࢖ࣥࢱࣅ࣮ࣗ⤖ᯝࡢศᯒ᪉ἲ࡜ࡋ࡚ࡣ㸪ࡲࡎୡᖏࡈ࡜
ࡢ᝟ሗ࠿ࡽ㸪ࡑࡢୡᖏࡢ≧ἣࡸ⪃࠼᪉ࢆ㚷ࡳࡓୖ࡛㸪⏕ά෌ᘓ࡟㛵ࡋ࡚࠶ࡾᚓࡿࢩࢼࣜ࢜ࢆᐈほⓗ㸪⥙⨶ⓗ࡟ண᝿ࡋ㸪࠶ࡿ⛬ᗘࡢ᮲௳ࡀࡑࢁ࠼ࡤ⏕ά෌ᘓࡢ㑅ᢥ⫥࡜ࡍࡿࡇ࡜ࡀ࡛ࡁࡿࡶࡢ㸪࠾ࡼࡧࡑࡢ᮲௳ࢆิᣲࡋࡓ㸬ḟ࡟㸪࢖ࣥࢱࣅ࣮࡛ࣗᚓࡽࢀࡓ᝟ሗࡸ㸪ୡᖏࡈ࡜ࡢศᯒ࡟ࡼࡗ
࡚ฟࡉࢀࡓ㑅ᢥ⫥㞟ྜࢆ㸪㞟ⴠࡈ࡜࡟㞟ィࡋ㸪㞟ⴠࡢ⨨࠿ࢀࡓ≧ἣ㸪ㄢ㢟ࢆ⪃ᐹࡋࡓ㸬(3) ศᯒ⤖ᯝa. ⓑ὾
8ୡᖏࡢ࠺ࡕ1ୡᖏࢆ㝖࠸࡚㸪ᕼᮃ࡜ࡋ࡚ࡣᡞᘓ࡚ఫᏯ
ࡢ෌ᘓࢆ⪃࠼࡚࠸ࡓ㸬ࡋ࠿ࡋ㸪ࡇࡢ࠺ࡕ3ୡᖏࡣ㸪㞟ⴠ࡟᚟⯆බႠఫᏯࡀᘓࡘ࡞࡝ࡋ࡞࠸㝈ࡾ㸪⮬ຊ࡛ࡣ㞟ⴠ࡛ᬽࡽࡋ⥆ࡅࡿࡇ࡜ࡀฟ᮶࡞࠸࡜⪃࠼ࡽࢀࡓ㸬ࡇࡢ⌮⏤࡜ࡋ࡚ࡣ㸪ࡇࡢ3ୡᖏࡣࡍ࡭࡚㧗㱋ୡᖏ࡛࠶ࡾ㸪㈓㔠ࡸ཰ධࡀᑡ࡞࠿ࡗࡓࡾ㸪⏕ᴗ࡛࠶ࡿ㣴Ṫᴗࡢ᚟ᪧ࡟㈝⏝ࡀ᥃࠿ࡾࡍࡂࡿ࡜࠸࠺⤒῭ⓗ࡞ࡇ࡜ࡀᣲࡆࡽࢀࡿ㸬ࡲࡓ㸪ࡑࢀ௨
እࡢ5ୡᖏ࡟ࡘ࠸࡚ࡶ⮬ຊ෌ᘓ࡟ࡣ᮲௳ࡀ࠶ࡿ࡜⪃࠼ࡽࢀ㸪
⁺ᴗ᚟ᪧࡸᏯᆅྲྀᚓ࡬ࡢ⿵ຓࡀ୙༑ศ࡞࡝㸪᮲௳ࡀࡑࢁ
ࢃ࡞ࡅࢀࡤ㸪ࡉࡽ࡟3ୡᖏࡀ㞟ⴠ࡛ࡢ༢⊂෌ᘓࡣ㞴ࡋࡃ࡞－ 31 －― 103 ―

ࡿ㸬࠸ࡎࢀࡶ60௦௨ୖࡢୡᖏ࡛࠶ࡿ㸬ࡼࡃ⪺࠿ࢀࡓᅇ⟅ෆᐜ࡜ࡋ࡚㸪࢖ࣥࢱࣅ࣮ࣗࢆ⾜ࡗࡓ඲࡚ࡢୡᖏ࠿ࡽ㸪㐨㊰࡟㛵ࡍࡿᢤᮏⓗ࡞ᩚഛࡢせᮃࡸ୙Ᏻ㸪୙‶ࡀ⪺࠿ࢀࡓ㸬㟈⅏๓࠿ࡽࡢ㐨㊰஦᝟࡬ࡢ୙‶࡜㸪㟈⅏᫬࡟㐨㊰ࡢᑍ᩿࡟ࡼࡗ࡚Ꮩ❧ࡋࡓ࡜࠸࠺⤒㦂࠿ࡽ㸪ࡇࡢࡼ࠺࡞ᅇ⟅࡟࡞ࡗࡓ࡜⪃࠼ࡽࢀࡿ㸬ࡲࡓ㸪ὠἼ࡟ᑐࡍࡿᏳ඲ᛶࢆồࡵࡿኌࡶ඲࡚ࡢୡᖏ࠿ࡽ⪺࠿ࢀࡓ㸬ࡋ࠿ࡋࡇࢀࡽࡣ㸪௒ᅇㄪᰝᑐ㇟࡜࡞ࡗࡓ㧗㱋⪅࡟㛵ࡋ࡚ࡣ㸪ᚲࡎࡋࡶ㞟ⴠ࡟ᡠࡿ࡜࠸࠺㑅ᢥ⫥ࢆ࡜ࡿࡓࡵࡢᚲせ᮲௳࡛ࡣ࡞࠸ࡇ࡜ࡀศ࠿ࡗࡓ㸬㐨㊰࡟㛵ࡋ࡚ࡣ㸪㧗㱋⪅ࡣ⮬ศࡓࡕࡀᡠࡿࡓࡵ࡟ᚲせ㸪࡜࠸࠺ࡼࡾࡣ㸪ⱝ࠸ேࡓࡕࡀ
ఫࡳࡘࡃࡓࡵ࡟ࡣ୙ྍḞ㸪࡜࠸࠺ࡼ࠺࡟⪃࠼࡚࠸ࡿࡓࡵ
࡛࠶ࡿ㸬ࡲࡓ㸪㞟ⴠࡢὠἼ㜵⅏ᑐ⟇࡟ࡘ࠸࡚ࡣ㸪ࡍ࡛࡟㞟ⴠࡢ㧗ྎ࡟ᅵᆅࢆࡶࡗ࡚࠸ࡿࡓࡵ㸪㏣ຍⓗ࡟ᚲせ࡞᮲௳࡟࡞ࡽ࡞࠸ሙྜࡀ࠶ࡗࡓ㸬ࡉࡽ࡟㸪࡝ࡕࡽ࠿࡜࠸࠼ࡤ
Ᏻ඲ᛶࡼࡾࡶ཰ධࡢᏳᐃࢆ㔜どࡍࡿୡᖏࡀ3ୡᖏ࠶ࡿ㸬௨ୖࡢ⤖ᯝ࠿ࡽ㸪ⓑ὾࡟ࡘ࠸࡚ࡣ㸪㟈⅏๓ࡼࡾ㧗つ᱁ࡢ㐨㊰ࡸ㸪ሀᅛ࡞ὠἼᑐ⟇ࡔࡅ࡟ຊⅬࢆ⨨ࡃࡢ࡛ࡣ࡞ࡃ㸪ಶࠎࡢୡᖏ࡟ᑐࡍࡿ⏕ά෌ᘓࡢ⿵ຓࡀ㸪௒ᚋ⮬ຊ෌ᘓ࡛ࡁࡎ࡟㞟ⴠࢆཤࡽࡊࡿࢆᚓ࡞࠸ୡᖏࢆῶࡽࡍୖ࡛ࡣ㔜せ࡟࡞ࡿ࡜⪃࠼ࡽࢀࡿ㸬b. ୧▼᮲௳࡟ࡼࡗ࡚ࡣᡞᘓ࡚ఫᏯࢆ㑅ᢥ⫥࡟࠸ࢀࡿࡇ࡜ࡀ࡛
ࡁࡿୡᖏࡀ7ୡᖏ࠶ࡗࡓ㸬ࡑࡢ᮲௳ࡣ㸪㞳ࢀ࡚ఫࡴᐙ᪘ࡢ
ᨭ᥼ࡸ㸪ᅵᆅྲྀᚓ࡞࡝෌ᘓ࡟࠿࠿ࡿ㈝⏝࡬ࡢ⿵ຓ࡛࠶ࡿ㸬ࡲࡓ㸪࢖ࣥࢱࣅ࣮ࣗ࡟ࡼࡗ࡚ᐹࡍࡿࡇ࡜ࡢ࡛ࡁࡓ୧▼ࡢఫẸࡓࡕࡢ⪃࠼᪉࡟ᇶ࡙ࡃ࡜㸪༙ᩘࡢୡᖏ࡟ࡣ㸪㞟ⴠ࡟ᡠࡿࡓࡵ࡟ࡣᏳᚰ࡛ࡁࡿࡔࡅࡢὠἼ㜵⅏ᑐ⟇ࡀᚲせ᮲௳࡟࡞ࡿ࡜⪃࠼ࡽࢀࡿ㸬ࡇࡢ㞟ⴠࡣ㟈⅏᫬㸪247㌺୰᥎ᐃ
220㌺ࡀὶኻࡋ࡚࠾ࡾ㸪ⓑ὾࡜㐪ࡗ࡚㧗ྎ࡟Ꮿᆅ࡜ࡋ࡚฼
⏝࡛ࡁࡿᖹᆅࡀᑡ࡞࠸㸬ࡇࢀࡽࡢࡇ࡜ࡀ㸪Ᏻ඲ᛶ࡟ᑐࡍࡿせồࢆࡼࡾษᐇ࡞ࡶࡢ࡜ࡋ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿ㸬ࠕ᝿ᐃእࡣ෌ࡧ㉳ࡇࡾᚓࡿࠖ࡜࠸࠺ㄆ㆑ࢆᣢࡗ࡚࠸ࡿୡᖏࡶ
࠶ࡾ㸪ࡑࡢ⤖ᯝ㸪ࠕࡶ࠺㞟ⴠ࡟ࡣఫࡳࡓࡃ࡞࠸ࠖ࡜⪃࠼ࡿே࡜㸪ࠕ⅏ᐖࣜࢫࢡࢆཷࡅධࢀ࡚ࡶఫࡳࡓ࠸ࠖ࡜⪃࠼ࡿேࡢ཮᪉ࡀ࠸ࡓ㸬ࡲࡓ㸪᚟⯆࡟᫬㛫ࡀ࠿࠿ࡿ࡞ࡽ㞟ⴠ௨እࡢሙᡤ࡛ࡢ෌
ᘓࡶ⪃࠼ࡿ࡜࠸࠺ୡᖏࡶ」ᩘ࠶ࡗࡓ㸬ࡇࡢ⌮⏤࡜ࡋ࡚ࡣ㸪࡯࡜ࢇ࡝ࡢୡᖏ࠿ࡽ⪺࠿ࢀࡓ᚟⯆࣭෌ᘓࡢ┠㏵ࡀ❧ࡓ࡞࠸ࡇ࡜࡟ᑐࡍࡿ୙Ᏻࡸ㸪㞟ⴠࡀ࠸ࡎࢀ᚟⯆ࡋ࡚ࡶ㸪ࡶ࡜ఫࢇ࡛࠸ࡓேࡢከࡃࡀฟ࡚⾜ࡗ࡚ࡋࡲ࠺ࡢ࡛ࡣᡠࡗ࡚ࡶ
௙᪉࡞࠸࡜࠸࠺⪃࠼᪉࡟ࡼࡿࡶࡢ࡛࠶ࡗࡓ㸬ࡇࡢⅬ࡟ࡘ࠸࡚ࡣ㸪㟈⅏࠿ࡽࡢ⤒㐣᫬㛫࡟ࡼࡗ࡚ࡶᅇ⟅ࡀኚࢃࡿ࡜
ண᝿ࡉࢀ᩿ᐃࡣ࡛ࡁ࡞࠸㸬ࡋ࠿ࡋ㸪᚟⯆ࡢ┠㏵ࡀ❧ࡘࡲ࡛࡟࠶ࡲࡾ࡟᫬㛫ࡀ⤒࡚ࡤ㸪ேཱྀὶฟࡀቑ኱ࡍࡿྍ⬟ᛶࡣ࠶ࡿ㸬ᐇ㝿࡟௒ᅇࡢㄪᰝ࡛ࡣ㸪༙ᩘࡢୡᖏࡀ㸪᪩ᮇ࡟᚟⯆ࡢ┠㏵ࡀ❧ࡓ࡞࠸㸪࠶ࡿ࠸ࡣఫࡳጞࡵࡽࢀࡿ᮲௳ࡀ
ᩚࢃ࡞࠸ሙྜ㸪㞟ⴠእ࡬ฟ࡚࠸ࡃ࡜⪃࠼ࡽࢀࡓ㸬௨ୖࡢࡇ࡜࠿ࡽ㸪୧▼࡛ࡣ⏕άࡢᏳ඲ᛶ࡜᪩ᮇࡢᏳᐃ
࡜࠸࠺2ࡘࡢ᮲௳ࢆ‶ࡓࡍࡓࡵ㸪㞟ⴠࢆ㞳ࢀࡿ㑅ᢥࢆࡍࡿୡᖏࡀᑡ࡞ࡃ࡞࠸ྍ⬟ᛶࡀ࠶ࡿ࡜⪃࠼ࡽࢀࡿ㸬4.

᚟⯆࡬ྥࡅ࡚ࡢㄢ㢟ᮾ㒊⁺༠⟶ෆࡢᆅᇦ࡟࠾࠸࡚㸪㆟ㄽࢆࡍࡿࡓࡵࡢᅵྎ
ࡣฟ᮶ୖࡀࡗ࡚ࡁࡓ㸬ࡋ࠿ࡋ㸪᚟⯆ࣉ࡙ࣛࣥࡃࡾ࡟ྥࡅ
࡚ࡣ౫↛࡜ࡋ࡚ㄢ㢟ࡀ࠶ࡿ㸬࠾ࡣࡇࡊࡁᕷẸ఍㆟ࡢ࣓ࣥࣂ࣮ࡣ㸪CeMIࡸᑓ㛛ᐙࢆ㝖࠸࡚ࡣ㸪⥲ྜⓗ࣭ᗈᇦⓗ࡞どⅬࡀᚲせ࡜࡞ࡿࡲࡕ࡙ࡃࡾࡢ㆟ㄽࡢ⤒㦂ࡀ࡞࠸㸬ࡇࡢࡓࡵ㸪㆟ㄽࡀ࣓ࣥࣂ࣮ಶࠎࡢฟ㌟ࡢ㞟ⴠ࡟㛵ࡍࡿせᮃࡸ㸪ὠἼ࡟ᑐࡍࡿ᏶඲࡞㜵ᚚ㸪ࡲࡓᚑ๓࠿ࡽ୙‶ࡢ࠶ࡗࡓ㐨㊰ᨵၿࡢ㝞᝟࡜࠸ࡗࡓಶࠎࡢ஦᱌࡟೫ࡾࡀࡕ࡛࠶ࡿ㸬௒ᚋ㸪㟈⅏௨๓࠿ࡽᆅᇦ࡟ᏑᅾࡋࡓᑡᏊ㧗㱋໬ࡸ㞠⏝
ࡢ୙㊊࡞࡝ࡢၥ㢟࡟ᑐᛂࡋ㸪ᣢ⥆ྍ⬟࡞ᆅᇦࢆᐇ⌧ࡍࡿᙧ࡛ࡢ᚟⯆ࢆ┠ᣦࡍࡓࡵ࡟ࡣ㸪ண⟬ࡢ᭷㝈ᛶࡸ㸪ᆅᇦࡢ⨨࠿ࢀࡓ⌧≧ࢆ㋃ࡲ࠼ࡓୖ࡛㸪⥲ྜⓗ࡞どⅬ࡜ᰂ㌾࡞Ⓨ᝿ࢆࡶࡕ㸪ᆅᇦ࡟࡜ࡗ࡚ᮏᙜ࡟ᚲせ࡞᪋⟇ࢆᥦ᱌ࡋ࡚࠸
ࡃࡇ࡜ࡀ࡛ࡁࡿ࠿ࡀ㔜せ࡛࠶ࡿ㸬ࡑࡢ⌧≧ࡢ୍㒊࡜ࡋ࡚㸪ᮏ◊✲࡛ᢅࡗࡓࡼ࠺࡞ㄪᰝ⤖ᯝࢆ㸪ᇶ♏ⓗ࡞㈨ᩱ࡜ࡋ࡚ᢕᥱࡍࡿࡇ࡜ࡀᚲせ࡛࠶ࡿ㸬⌧ᅾ࠾ࡣࡇࡊࡁᕷẸ఍㆟࡛ࡣ㸪ሀᅛ࡞㜵Ἴሐ࡞࡝ࡢὠἼ
㜵⅏ᑐ⟇ࡸ㧗つ᱁ࡢ㐨㊰࡞࡝ࡢᚲせᛶࡀ㆟ㄽࡉࢀ࡚࠸ࡿ㸬ࡋ࠿ࡋ㸪ఫẸಶࠎ࡟↔Ⅼࢆ࠶࡚ࡿ࡜㸪㜵⅏ᑐ⟇࡬ࡢせồ࡟ࡣୡᖏᕪࡀ࠶ࡿ㸬ࡲࡓ㸪ඖࡢ㞟ⴠ࡟ᡠࡿ࡜࠸࠺㑅ᢥ⫥ࢆྲྀࡽ࡞࠸㸪࠶ࡿ࠸ࡣྲྀࡿࡇ࡜ࡀ࡛ࡁ࡞࠸࡜⪃࠼ࡽࢀࡿୡᖏࡶከࡃᏑᅾࡍࡿ㸬ࡑ࠺ࡋࡓ୰࡛㸪ண᝿ࡉࢀࡿᑗ᮶ࡢ
㞟ⴠࡢேཱྀつᶍ࡜㸪࢖ࣥࣇࣛᩚഛࡢつᶍ࡜ࡢࣂࣛࣥࢫࢆ
⪃៖ࡋ㸪ࡉࡲࡊࡲ࡞᪉⟇ࢆ᳨ウࡋࡓ࠺࠼࡛㸪ᆅᇦ࡟࡜ࡗ
࡚㐺ษ࡞㑅ᢥ⫥ࢆ࡜ࡿࡇ࡜ࢆ⪃࠼ࡿᚲせࡀ࠶ࡿ㸬ࡉࡽ࡟㸪⌧ᅾ୙㊊ࡋ࡚࠸ࡿ࢖ࣥࣇࣛࢆ⿵࠺࡜࠸࠺どⅬࡔࡅ࡛࡞ࡃ㸪ࡼࡾ㛗ᮇⓗ࡟ᆅᇦࡢᑗ᮶ീࢆண᝿ࡋ㸪ᣢ⥆ྍ⬟ᛶࡢᐇ⌧ࡢࡓࡵ࡟ᚲせ࡞ྲྀࡾ⤌ࡳࢆᶍ⣴ࡋ࡚࠸ࡃࡇ
࡜ࡶồࡵࡽࢀࡿ㸬ࡲࡓ㸪⌧ᅾࡢ࡜ࡇࢁ㸪NPO࠾ࡣࡇࡊࡁᕷẸ఍㆟ࡢάືࡢ㸪᚟⯆ࣉࣟࢭࢫࡢୖ࡛ࡢ఩⨨࡙ࡅࡀ᫂☜࡟࡞ࡗ࡚࠸࡞
࠸㸬ఫẸᅋయࡀ⾜ᨻ࡟ᑐࡋ࡚せᮃࢆ㝞᝟ࡍࡿ࡜࠸࠺ᵓᅗ
࠿ࡽᢤࡅฟࡋ࡚㸪ᕷẸ఍㆟ࡀᢸ࠺ᙺ๭ࢆ᫂☜໬ࡋ㸪୍ࡘࡢ୺య࡜࡞ࡗ࡚ࡲࡕ࡙ࡃࡾࢆ⾜࠺࡜࠸࠺ឤぬࢆࡶࡘࡇ࡜
ࡀồࡵࡽࢀࡿ㸬5.

ࡲ࡜ࡵ௒ᅇ◊✲ࡢᑐ㇟࡜ࡋࡓᆅᇦࡣ㸪㐣ཤࡢ୕㝣ὠἼ࡛ࡶ⿕ᐖࢆཷࡅ㸪ࡑࡇ࠿ࡽ᚟⯆ࡋ࡚ࡁࡓሙᡤ࡛࠶ࡿ㸬ࡋ࠿ࡋ㸪㐣ཤ࡟౑ࢃࢀࡓ᚟⯆ᡭἲࡣ⌧ᅾ࡛ࡣ㏻⏝ࡋ࡞࠸㸬ᆅ᪉ศᶒ࡜ఫẸཧຍ㸪⦰ᑠ♫఍࡜࠸࠺㸪⌧௦ࡢ᪥ᮏࡢከࡃࡢᆅ
᪉㒔ᕷࡀ┤㠃ࡍࡿࡇࢀࡲ࡛࡟࡞࠸ㄢ㢟ࢆᢪ࠼ࡘࡘ㸪኱⅏ᐖ࠿ࡽࡢ᚟⯆ࢆᯝࡓࡉ࡞ࡅࢀࡤ࡞ࡽ࡞࠸㸬ࡋ࠿ࡋ㸪ࡇ࠺ࡋࡓ≧ἣࡔ࠿ࡽࡇࡑ㸪௚ࡢᆅ᪉㒔ᕷࡢࣔࢹࣝ࡜࡞ࡿࡼ࠺࡞㸪ᣢ⥆ྍ⬟࡞ᆅᇦࡢ⫱ᡂࣉࣟࢭࢫࢆస
ࡾୖࡆࡿዲᶵ࡛ࡶ࠶ࡿ㸬࡜ࡃ࡟ఫẸ⤌⧊ࡢࡲࡕ࡙ࡃࡾ࡟
࠾ࡅࡿ୺యⓗ࡞ࡣࡓࡽࡁࡀ㸪ᆅᇦࡢ෌⏕ࡢୖ࡛࡝ࡢࡼ࠺
࡞ᙺ๭ࢆࡣࡓࡍࡇ࡜ࡀ࡛ࡁࡿࡢ࠿㸪ࡑࡢྍ⬟ᛶࡣᗈ࠸࡜
⪃࠼ࡽࢀࡿ㸬௒ᚋࡢάືࢆ⥅⥆ⓗ࡟ほᐹࡋ㸪ᑗ᮶ࡢ⅏ᐖ࡛⏕࠿ࡍࡇ࡜ࡢ࡛ࡁࡿࣔࢹࣝࢣ࣮ࢫ࡜ࡍࡿ࡭ࡃ㸪◊✲ࢆ⥅⥆ࡋࡓ࠸㸬ཧ⪃ᩥ⊩1) ෆ㛶ᗓ⤫ィᒁ㸸ᖹᡂ22ᖺᅜໃㄪᰝ
2) 㔩▼ᕷ㸸㔩▼ᕷࡢᴫせ, p1-2, 17, 20113) බ ᫂ ඪ 㸸 http://www.komei.or.jp/news/detail/20110413_4972,
2012/2/44) 㔩▼ᕷ㸸㔩▼ᕷ᚟⯆ࡲࡕ࡙ࡃࡾᇶᮏィ⏬ ࢫࢡ࣒ࣛ࠿ࡲ࠸ࡋ᚟
⯆ࣉࣛࣥ, p6-7, 14-17, 20115) ⎔ቃ┬㸸 ⅏ᐖᗫᲠ≀ฎ⌮ࡢ㐍ᤖ≧ἣ, 2012

－ 32 －― 104 ―

― 105 ―― 106 ―― 107 ―― 108 ―― 109 ―

1
2
1
19
21
9
71
9
18

0

20

40

60

80

0
0

9.6

(N=12)

3.8(N=52)

0
1.9
0
9.6
0
3.8

PC

0
0

33.3

15.4
8.3
3.8
9.6
25

41.7

3.8
8.3
11.5
76.9

0

8.2
11.5
8.2
14.8
21.3
75.4
0

20

40

60

80

6.6
TV

47.5
34.4
6.6
27.9
3.3
36.1
29.5
93.4
0

20

40

60

80

100

― 110 ―

20

40

60

80

100

100

25

4.9

31.7
25

41.7

31.7

25
26.8
0
0
0

7.3

(N=12)(N=41)

2.4
10

20

30

40

50 %

0

34.5
75

0.0
6.9

25
100

24.1
25
20.7
79.3
0
(N=4)

N=12)
N= 22)
N=26)

8.3

25

31.8

66.7
45.5
56.5

22.7
0 13

0% 20% 40% 60% 80% 100%

― 111 ―

20

40

60

100

80 100 %(N=29)

(N=36)(N=24)

33.3
19.0

52.8

58.3
62.4
61.7

13.9

49.4
51.7
47.1
46.7
43.5

31.7
40.0

76.2

18.3
25.9

4.8
0%

22.4
13.3
18.8
8.3
9.4
11.7
7.1
5.0
5.9
3.3
3.5
6.7
2.4
6.7
3.5
1.7
2.4

20% 40% 60% 80% 100%0

― 112 ―

10

20

30

43.3

(N=60 )
(N=85)
40

50

60

70

(N=25)

0.0

60.0

28.0

4.0
(N=24)
8.3 4.2
0%

75.0

0.0

20% 40% 60% 80% 100%

― 113 ―

― 114 ―

50

45

40
26

30
20
10

1 1

0

5 5 5 3 41 2 1 2 3 3

4 2
1 1 2 1 1 1 1 1 1

-1
70
60

60

54 52

50

44
35

40
30
20
10
0

23

18

24 25

24

28

13

18 20

21

16

18

14

38
29 30
19

23 22

2011

3

10

2011

3

11

35

34 33
26
18

17

23 25 21
14

12
11
10
10 8 12
9
9
8
7 5 5
7
7 7 5 5 5
7 5
7
5 7
44 4
4 3 2 5 2 4 5 5 4 4 3 2 2 2 2 2 3
4 33
1 1 2 11 3 2 0 0 03 00 00 00 00 3 3 2
1 1 2 0 1 3 2 2 1 1 1 13 1

60
47

50
30
10
0

2011 3 102011 3 11

40
20

52

30

26
20

19

21 23

28
23 20

13
13
10
7 6
65 6
6
5
5
4
4
4
3
2 2 2 3 1
2 0 0 01 1 1 04 1 01 00 01 00 00 00 00 01 00 01 00 01 00 00 00 00 00 00 00 00 00 00 00 10 10
11 1― 115 ―

90
80
70
60
50
40
30
20
10
0

100
90
80
70
60
50
40
30
20
10
0

2011

3

11

100
90
80
70
60
50
40
30
20
10
0

― 116 ―

100
2010

80

2011

60
40
20
0

― 117 ―

100
90
80
70
60
50
40
30
20
10
0
0

10

20

30

40

50

60

― 118 ―

― 119 ―― 120 ―

92

129

121
17 21 83

400-600m

271 24
383

20%

40%

127

60%

68

113

63

69

0

166

234

14

32 130 20 60
1011

35 29 51 24― 121 ―

20%40%

1.0-3.3m
3.3-6.6m
6.6-10m

38

10-15m
15m

232
60%

1.0m

252
175

112 47 85 67
0%

0

165

4

800-1000m
1000m

80% 100%

12
1

4 23

600-800m

46 30

192

200

395
30

200-400m

96

226

89 37

3151

64 94

218
731

85

200m

161

202

298

8
20

150

92

29

0%

8

89

233

6

80%

51
100%

1800
1600
1400
1200
1000
800
600
400
200
0

1.0m
1.0-3.3m
3.3-6.6m
6.6-10m
10-15m15m
0

200 400 600 800 1000 1200 1400 1600 1800

1800
1600
1400
1200
1000
800
600
400
200
0

1.0m
1.0-3.3m
3.3-6.6m
6.6-10m
10-15m15m
0

200 400 600 800 1000 1200 1400 1600 1800

― 122 ―

― 123 ―― 124 ―― 125 ―― 126 ―― 127 ―

34

0%

20%
1

― 128 ―

27

40%
2

60%
1

80%
2

100%

15000

1

2

1

2

12000
9000
6000
3000

0
0

50000

100000150000200000250000

Ln(

1000000
100000

10000
1000
100
10
1
0

10

20

30

40

3

20%

6

― 129 ―

60

70

80

90

100

58

0%

0%

50

40%

60%

39

20%

40%

80%

100%

14

60%

80%

3

100%

17

0%

23

20%

40%

6

60%

10

80%

2

100%

― 130 ―

― 131 ―土木学会 第 32 回地震工学研究発表会講演論文集（2012 年 10 月）



被災者への住宅供給システムについての考察
東日本大震災の事例より



松下


朋子・沼田宗純・目黒公郎

1博士課程1年

東京大学大学院工学系研究科（〒153-8505 東京都目黒区駒場4-6-1）

正会員 准教授 東京大学生産技術研究所（〒153-8505 東京都目黒区駒場4-6-1）

正会員 教授 東京大学生産技術研究所（〒153-8505 東京都目黒区駒場4-6-1）




東日本大震災という大規模災害を機に、被災者への応急仮設住宅供給の新しい在り方が提示された．ひとつは、民間賃貸住宅を仮設住宅とみなす「みなし仮設」の活用であり、もうひとつは地域を支える地元の建設業者による木造応急仮設住宅の建設である．この 2 つの取り組みの共通点でもある特徴は既存ストックやシステムを利用しているところにある．人口減少、少子高齢化の進む日本における災害対策の在り方として、新しいものを作るだけではなく、限りあるものを賢く使っていく、それを防災対策としていかに実践していくかということが今後重要になってくると思われる。本稿ではこの２つの新しい取り組みを
しっかり評価することで、これからの防災対策に活かすことを目的とし、特に地元業者による仮設住宅建設に重点を置き、そのプロセス、結果、今後の課題を整理した．

 はじめに既にあるものを有効利用している部分で共通している．



人口減少、少子高齢化の進む日本における災害後の応防災対策の根幹となる法制度は、大規模災害の直後に急的住宅対策の在り方として、新しいものを作るだけで制定されてきたという歴史的事実が示すように、災害ははなく、限りあるものを賢く使っていくことが必要とさ

防災に関する新たな法制度を制定する契機にもなる ．

れており、それを防災対策としていかに実践していくか

災害時の応急仮設住宅の供給においては、昭和 22 年ということが今後重要になってくると思われる．現代日（1946 年）におきた南海地震を契機として翌年の昭和本がおかれた状況の下でのこれらの取り組みは、今後の23 年(1947 年）に制定された災害救助法に基づいて、そ

応急仮設住宅供給に関する制度の抜本的な見直しにつなの基本的方針が定められている．平成 7 年（1995 年）

がる可能性を示し、冒頭で述べたような、制度改正の契の阪神・淡路大震災においては、同法律に基づき、住宅機になるのではないかと考える．

を失った被災者に対して約５万戸の応急仮設住宅が供給

阪神・淡路大震災以来特に仮設住宅に関しては多くのされた．東日本大震災では被害の甚大さから、主流であ研究がなされてきたが、本稿では２つの新しい取り組み

ったプレハブ建築協会によるプレハブ仮設住宅の一括供に着目し、評価することで、これからの防災対策に活か給だけでは被災直後の需要の高さに応えることが困難ですことを目的としている．また地元業者による仮設住宅あった．したがって従前の枠を超えた対応が必要とされ、 建設参画に重点を置き、そのプロセスと結果を整理し、それらから導かれる今後の課題を考察した．

発災後まもなく、被災者のための応急仮設住宅供給における新たな 2 つのアプローチが取られた．
ひとつは、民間賃貸住宅を仮設住宅とみなす「みなし 東日本大震災以前から指摘されてきた問題

仮設」の活用であり、もうひとつは地域を支える地元の建設業者による木造応急仮設住宅の建設である．これらの取り組みは空き家・空き室等既存ストックの利用、地

なぜ東日本大震災における新たな試みが注目に値する

元で活動してきた地域工務店の参画を促したという点で、 のか．それは既に多くの専門家等によって指摘されてき― 132 ―


た応急仮設住宅供給に関する問題に対する解決の糸口を

阪神・
阪神・淡路
大震災

示しているからであると考える．その中でも特に筆者ら

139

0 49 ,681

1995年

が問題視するのは、応急仮設住宅の建設にかかっている

東日本

多大な財政負担と、それにもかかわらず建設されたもの

大震災

は原則として 2 年 3 ヶ月の使用期限が定められストック

2011年

として残らないという点である．
国土交通省によると東日本大震災で建設された応急仮9 ,0 1 7 4 2 ,9 5 1

67,877

地域工務店等

プレハブ協会
プレハブ 協会

みなし仮設
みなし仮設

による供給
による供給

による供給
による供給

( 民間賃貸借上げ
借上げ)

設住宅の平均コストは１戸あたり 602 万円と報告されて
おり、建設された約 5 万 3 千戸を単純計算すると約

図-1



3180 億円かかっている ．それらの建設された膨大な量

阪神・淡路大震災と東日本大震災における応急
仮設住宅供給の内訳

の「仮住まい」については、被災者が退去した後の利用についての定めはない．また、退去した被災者についてはプレハブ建築協会のみによるプレハブ仮設住宅の供給

は、もとの場所で生活を希望する場合は、国が準備する

では需要に追いつかないということが判明し、借り上げ

公営住宅へ入居するか、被災者生活再建支援法に基づき仮設住宅の弾力的運用と、公募による地元建設業者によ

最大で 300 万円の国からの支援金と自己資金を足し合わる仮設住宅建設への参画という２つの新しい取り組みがせて自力で自宅を再建をする、という選択肢がある．ど遂行された．結果として、東北3県を中心に合計約12万ちらにしても「応急的」な仮設住宅の供給と、「恒久戸の応急仮設住宅が供給された．

的」な住宅再建の間に連続性はない．仮設住宅の供給と、

図－1は1995年の阪神・淡路大震災と東日本大震災に供給後の管理・運営にかかる行政負担、加えて被災者生

おける応急仮設住宅供給体制を比較したグラフである．

活再建支援法による住宅再建に支給される分を合計する

1995年の阪神・淡路大震災では約５万戸の応急仮設住宅と、被災者への住宅供給に費やされる財政負担は多大でが供給されたが、そのうち既存アパートの仮設住宅としある．

ての利用はたったの139戸であった．しかし16年後に起また、それだけの財政負担を課す一方で、そもそもこった東日本大震災では全供給数約12万戸中、半数以上「応急的な住居」という概念自体が、豊かになった現代の57％（約68,000戸）が、みなし仮設住宅であった．この日本の実情にあっていない．戦後間もなく制定されたの劇的な増加の要因として考えられるのは、少数ながら

災害救助法は、原則として「現地にて、現物（現金でなも阪神・淡路大震災で実現された経験を踏まえ、みなしく）を支給する」という考えに基づいているが、現在そ仮設住宅の可能性が多くの専門家らの研究によって検証れらが厳密に守られているわけではない．しかしそれらされてきたことに一因があるのではないかと考える．

を見直すような抜本的な制度改正まで至っていない、と

一方、地域工務店等による応急仮設住宅建設についいうのが現状である．

てはどうだろうか．阪神・淡路大震災での前例はなく、
東日本大震災において初めて実現し、その割合は全体の7％と１割にも満たないが、実に多種多様な応急仮設住 東日本大震災における新しい取組みの概要

宅が建設され、今後その積極的活用がおおいに期待されるところである．阪神・淡路大震災後におけるみなし仮2011 年 3 月 11 日 14 時 46 分、我が国の観測史上最大設がそうであったように、地域工務店による参画が今後規模であるモーメントマグニチュード 9.0 の海溝型地震の応急仮設住宅供給のあり方において、さらに大きな役が三陸沖を襲い、宮城県北部で最大の震度 7.0、東京都割を担っていく可能性があるのではないかと考える．

や神奈川県においても震度 5 強を記録した ．人的被害
は、死者・行方不明者合計約 1 万 8000 人、建物被害は
全壊約 13 万戸、半壊約 26 万戸と報告されており 、 全

 地域工務店の参画による応急仮設住宅の供給

国の避難者総数は約  万人を超え、約  万戸の応急仮設住宅が供給された ．前章で述べたように東日本大震災以前は応急仮設住宅

地震発災の15分後、事前に取り決めされていた通り国の供給において地域建設業者が携わることはなかった．

土交通省住宅生産課はプレハブ建築協会に対して協力をその理由として考えられるのは、①全４７都道府県と要請し、3月14日には国土交通大臣からの社団法住宅生（社）プレハブ建築協会との間で「災害時における応急産団体連合会に対して「概ね2カ月で3万戸程度の供給が仮設住宅の建設に関する協定」が締結していたこと、まできるようお願いしたい」という要請が出された．壊滅

た、②「応急的」と定義される仮設住宅に対して、プレ的な被害を受けた岩手・宮城・福島の東北3県においてハブ小屋以上の恒久性のあるものを建設するということ― 133 ―


自体、災害救助法の「原則」に沿わないがゆえに、プレまとめる．

ハブ以外の事前対策をとらなかったとも考えられる．

(1) 公募方針の違い

東日本大震災で建設された応急仮設住宅は、その大部分は従来同様、プレハブ建築協会の規格建築部会によ岩手県と福島県においては概ね方針が似ており、どちる軽量鉄骨製の現場小屋タイプであったが，その他ハウらも県が主体となって公募を行い、その選定評価項目とスメーカーによるアパートタイプ、地元業者による木造

しては、施工能力、品質などの条件以外に、県産材の利（在来工法、枠組壁工法、ログハウス、伝統工法（板倉用、県内事業者等の雇用、居住性・環境・再利用性など造り））、輸送コンテナを改造し、積み上げてできた３の「質」を高く評価していた．そしてそれらの評価項目

階建てアパート、トレーラーハウス、介護機能付きタイに基づいて事業者を選定し、公表し、実際仮設住宅の発プ、などと実に多様な「応急仮設住宅」が供給された．

注をしている．

これらの新しいタイプの仮設住宅建設の試みは、従来型

一方宮城県では様相が異なり、公募業務そのものを一のプレハブ仮設住宅にはなかった、①居住性の向上、②般社団法人すまいづくりまちづくりセンター連合会に外再利用の可能性、そして③地元貢献という新しい価値観

部委託し、県は選定等について主体的に関わっていない．

を仮設住宅供給システムにもたらした．

岩手県や福島県に比べて公募条件は簡易で、前述のよう

この地域工務店の参画によってもたらされたポジテな「評価項目」は公表されておらず、選定結果についてィブな側面について、それに至ったプロセスと，その結も非公開であった．また、宮城県の場合は業者が選定さ果を評価することで今後の対策に活かすことができればれても直接受注につながるわけではなく、公募によってと考える．

選定された事業者のリストが市町村に提供された．結果
として地元事業者による応急仮設住宅の建設を行ったのは南三陸町と山元町だけであった．それ以外については

 業者選定のプロセス：公募の概要

県がプレハブ建築協会へ発注をした．
なぜこのような方針の違いがあるのか？宮城県の被害

東日本大震災では応急仮設住宅の建設において初めは他県に比べて大きく、応急仮設住宅業務にかかる作業て「公募」という形式がとられ、岩手、宮城、福島の３量が膨大になることが予測され、それにかかる手間を削

県から県内建設業者に対して協力要請がなされた．結果減するためにもプレハブ建築協会に一括発注したというとして、全体供給量に対して岩手県では 17.8％、宮城

ことは理由のひとつとして考えられる．これに関しては

県では 2.4％、福島県では 25.3％（2 次募集分は含んで

地元建設業者による応急仮設住宅供給における規模によいない）が、公募によって選ばれた地域建設業者によっる対策を検証する必要がある．

て建設されることになった．
(2) 事業者選定における評価基準

これまで仮設住宅に関しては、QCD(Quality, Cost and岩手県と福島県においては前述のとおり公募の際に詳Delivery）のうち、Delivery－つまり供給のスピードが最も重視されてきた．そのためにプレハブ建築協会との細にわたる評価基準が提示された．

協定が締結され、災害時には被災していない全国のプレa) 応募者要件（適合・不適合判定のため）

ハブ建築協会の会員会社らが被災地において応急仮設住応募団体の適合・不適合を決める条件には、応急仮設宅の供給を担い、一括で行うことによって諸手続きの省

住宅の供給能力（供給可能戸数、施工期間）、過去の実

略など時間の短縮を図ってきた．

績などの施工能力問うと共に、申請事業者が県内事業者

しかし今回の公募においては、プレハブ建築協会によであることも含まれた．これにより、被災地外からの参る均一な仮設住宅供給のかわりに、県産材の利用、地元

加を難しくしたが、地元の建設業者の参加を促進するの職人の雇用、木材の再利用性や環境への配慮など、これに効果があったと思われる．

までの応急仮設住宅の建設においてほとんど重視されて

b) 評価項目(適合者の中から最適な業者を選定するための指標)

こなかった「質」が求められた．このことが結果として要件を満たした適合者の中からさらに選定するために様々なアイディアや取り組みを生み出したと同時に、被災地の建設業者による応急仮設住宅供給が可能であると評価指標が提示された．中でも地元雇用・県産材の利用いうことを示した点で画期的かつ意義深い活動であったなど地元経済活性への配慮、再利用性・居住性・計画性といえる．

など環境および質への配慮が配点において大きな割合を占めていた．

岩手、宮城、福島の３県において公募が行われたが、実際のところ各県によって公募の行い方や対応は異なり、

例えば福島県においては次の８つの評価項目が挙げ結果にもその違いが顕著であった．以下各県での状況をられた：①確実な住宅供給能力と体制、②適正な販売契― 134 ―


2000

21

岩手県

岩手県

89

11406
13984

宮城県

6000

5
156

27

福島県

福島県

63

29846

選定された地域建設業者数

17872

応募した地域建設業者数

図-3 公募結果：応募数と選定された業者数

県からの公募量（戸）（プレ協供給不足分として）
地域建設業者による応募量（戸）（供給可能戸数）
実際に供給された量（戸）（プレ協供給分含める）

地域建設業者による供給

図-2 岩手県と福島県における応急仮設住宅建設に

岩手県

2485

（社）プレハブ協会による供給（戸）11499

関する公募数と応募数および全体供給量の比較



宮城県 523

約価格、③供給住宅の性能及び品質、④県内企業の活用

福島県

21572

5496

12376

計画、⑤震災被災者の雇用計画、⑥県産材の活用計画、⑦住宅の解体及び移築方法、⑧仮設住宅計画案・モデル

図-4 3 県における応急仮設住宅の全供給戸数に占める



団地提案書における配慮事項 ．このうち④～⑧は地元地域事業者とプレハブ協会の割合

雇用、再利用性、居住性の向上と関わるものであり、100点満点中75点の配点を占めており、これらの新しいた災害時の資材、職人等の手配についての準備および土価値に置かれた比重が大きいことがわかる．軽量鉄骨の地不足に対する解決策の検討が必要である．

プレハブにはDeliveryの側面（工期）では劣るが、(4) 各県の結果

Quality（質）の評価をしっかりと行うことで木造によるメリットが大いに活かされる評価項目となっている．

以上、公募による結果を図-3、図-4 に示す．図-3 かまた福島県では福島第一原子力発電所の事故の影響にらは各県において多くの地域建設業者が応募しているこ

より、建設場所や必要戸数が不確定な状態が続いたこととがわかる．特に宮城県は 156 者の応募に対して、実際もあり、2 回にわけて公募が行われた．そのおかげで 2に発注に至ったのは 5 者のみであった．図-4 からプレ次募集では 1 次募集での経験を踏まえて、県側の事業者

ハブ建築協会が供給している割合はいずれの 3 県においに対する評価内容が若干修正されている．また同じく応ても高いことがわかる．これについては岩手県と福島県募する事業者側も、１次での建設経験の教訓を踏まえて、 においては、プレハブ建築協会が供給できない戸数のみ
プランや工法においてさらに工夫することで改善改良がを公募したために、応募数にかかわらず実際建設された可能となった．実際、1 次と 2 次両方で応募し選定されのは公募数を若干上回る程度であった．宮城県においてた事業者で、1 次の教訓を活かして 2 次では工期を１週は、もともと公募数が公表されなかったためにプレハブ間短縮できたり、再利用のために金物を使用したりなど、 建築協会による不足分がどれほどであったのかはわからないが、発注された 5 者により供給された量は約 500 戸

実際改善されたことが調査からわかった．

にとどまった．
岩手県の活動記録報告書によると、事業者選定時に価(3) 公募数をはるかに超えた応募数
図－2 に岩手県と福島県における、県による公募数に対格面だけでなく技術面等の質的な側面も評価するようにして応募した建設業者の数および実際供給された全戸数

評価項目を設けたが、実際は技術面での差がつきにくく、をグラフで示した．この結果から、各県が提示した公募

結果として価格により選定された業者が多かったという．

者数をはるかに上回る建設業者が応募したことが分かる． 「価格がやや高かったことにより、技術評価が高かった両県において公募数の約 5～6 倍の応募数があり、そのものの残念ながら落選となった事業者もあった．競争率

応募数だけみれば必要な戸数を全て地域の工務店によっが時間的な制約から評価基準等を簡素化せざるをえず、て建設できたのではないか、と思われる．しかし実際のやむをえない面もあったが、工夫の余地があるのではな

建設に参画した建設業者への聞き取り調査や報告書等にいかと考えられる」とある ．

よると、適切な土地がない、資材や職人が不足している

独創性や質的な評価項目について福島県と岩手県を比など、担い手がいても実際に作業する大工や建設に必要較すると、福島県の方がより応募者による創意工夫を促

な部品、または土地そのものがないという深刻な問題がす内容であったといえる．

あることがわかった．したがって今後の課題はそういっ

ま た 岩 手 県 で は 福 島 県 と 比 較 し て 団 体 （ Joint― 135 ―


Venture）による応募が少なかった．理由として考えら

居住性の向上、②再利用の可能性、そして③地元貢献とれるのは、福島県は「県内に本社」がある業者を公募のいう新しい価値観を仮設住宅供給システムにもたらした．

条件としていた為に本社がない業者は他の業者と組まな

またその公募条件および評価項目の設定により供給内容

くてはならなかったが、岩手県は「県内に営業所」があに差があったことがわかった．

ればよく、県外から参加する業者がＪＶを組む必要性が(2) 地域の担い手による参画可能性と今後の課題
地域建設業者の応募数の多さからも決して現地での供低かったからといえる．
さらには福島県で建設された木造仮設住宅と比較した給が不可能ではないことを示したが、同時に適切な土地、時に、岩手県で建設された仮設住宅の多くは外観上はプ

資材や職人の不足は深刻であったことがわかり、今後のレハブ建築協会によって作られた建物とあまり変わらな

課題として災害時の資材、職人等の手配および土地不足

いものが多かった．これについても事前に県より提示さに対する解決策の検討が必要である．

れた条件設定によるものが大きいと思われる．
宮城県においては、スピードを重視してプレハブ協会

謝辞：本稿を執筆する上で貴重な経験を共有させて下さへの一括発注を貫いたという解釈ができるが、公募の実った福島県の佐久間建設工業様、株式会社ナイス様、綿用性について疑問が残った．福島県については、当初よ密に行われた現地調査データを共有させて下さった森林り原子力発電所の事故の影響で、居住地の選定、また期総合研究所様、東京大学藤田松村研究室様、御礼申し上間について不確かな部分が多いため、単純な比較はでき

げます．

ない．


 参考文献 内閣府政府統括官：わが国の災害対策
 国土交通省：応急仮設住宅建設必携中間とりまとめ
 結論と今後の課題
 復興庁：復興の現状と取組
東日本大震災では、被災者のための住宅供給として２ 警察庁：警察庁緊急災害警備本部広報資料

復興庁：全国の避難者等の数
つの新たな取り組みが試みられた．みなし仮設の活用は、

国土交通省：応急仮設住宅着工・完成状況, 
法制度の弾力的運用によって、被災者の半数以上が利用
するに至り、今後のさらなる有効利用が可能であると思 福島県応急仮設住宅建設事業候補者（２次募集）選考委
われるが、今後の課題としては、みなし仮設入居者に対員会: 福島県応急仮設住宅建設事業候補者の公募（２次募集）に関する審査結果について, 2012
する行政サポートを徹底する必要があるといえる．

岩手県岩手県東日本大震災津波対応の活動記録（永久保被災地の地域建設業者による木造応急仮設住宅建設へ
存版）
の参画に関しては、これまで公募のプロセスと結果について述べてきたことを次に結論としてまとめる．
受付(1) 新しい価値の創造
公募という客観性のあるプロセスを経た、応急仮設住宅の建設は、従来型のプレハブ仮設住宅にはなかった①



                              
                
         









― 136 ―

― 137 ―― 138 ―― 139 ―― 140 ―― 141 ―

120000

350

100000

300

80000
60000
40000

250
200
150
100

20000

50

0

0

― 142 ―

350
300
250
200
150
100
50
0

3/16

3/23

3/30

4/6

4/13

4/20

4/27

― 143 ―

100
90
80
70
60
50
40
30
20
10
0
3 14
3 11

― 144 ―

13

100
80
60
40
20
0
3 14
3 11

― 145 ―

13

土木学会 第 32 回地震工学研究発表会講演論文集（2012 年 10 月）

東日本大震災における	
 
電力復旧優先順位に向けた検討	 	 陳	
  勲１・沼田	  宗純２・目黒	  公郎３	
 1

学生会員	  中央大学	  理工学部土木工学科（〒112-8551	
 東京都文京区春日 1-13-27）	
 E-mail:chen@risk-mg.iis.u-tokyo.ac.jp	
 
2

正会員	
  東京大学	  生産技術研究所(〒153-8505	
 東京都目黒区駒場 4-6-1)	
 E-mail: numa@iis.u-tokyo.ac.jp	
 

３

正会員	
  東京大学	  生産技術研究所(〒153-8505	
 東京都目黒区駒場 4-6-1)	
 E-mail: meguro@iis.u-tokyo.ac.jp	
 
	
 
	
 

電力は，我々が日常生活を効率的・生産的に安定して営むために，必要不可欠なものである。その一方で、ひとたび停電が発生すると、都市生活に与える影響は極めて大きい。特に、災害時に配送電施設が被害を受けると、一部の地域では数日間も電力が使えない状態になる可能性もある。本研究では、配送電施設の被害が生じた場合、より効果的な電力復旧の優先順位を検討する。
	 Key words:	
 Earthquake, Electric power, Restoration, Priority

1. はじめに重要な報道機関、避難場所等の施設について優先的

	
 に復旧計画をたてる。本稿では、電力の供給停止の2011 年（平成 23 年）3 月 11 日 14 時 46 分、太平影響を最小限にすることを目的とし、上記に加え、洋の三陸沖を震源とする地震「東北地方太平洋沖地

災害の状況、施設.	
 復旧の難易度も考慮し、電力供震」が発生した。この地震により、東北から関東に給上復旧効果の大きいものから先に復旧するためのかけての東日本一帯に甚大な被害をもたらした。そ方策を検討する。	
 の中で、電力設備被害や原発事故に伴う電力供給力	
 の低下により、東北電力や東京電力管内で輪番停電

	 の実施を伴う電力危機が発生した。長時間に亘る停2. 評価エリア

電により、公的機関や一般市民など、さまざまな社

	
 会的な機能に影響を与えた。一方、電力会社は復旧

本研究では、評価エリアの単位として、配電用変資源が有限であるため、電力設備をすべて同時に復電所供給エリア（以下では配電エリアという）を用旧することは困難である。従って、復旧作業に優先いる。電力は発電所から需要家に供給するまで、送順位を付け復旧戦略を立案することが重要である。	
 電電圧に応じていくつかの変電所を経由するが、配原則として復旧の順位は、人命にかかわる施設、

電用変電所は変電所としては末端にあたり、一般需対策の中枢である官公署、県民生活の安定のために要家を対象として電力供給を行っている。(図-１)	
 1― 146 ―

鍋田変
長町変
花京院変
吉岡変
松島変

電力供給量（ｋｗｈ）	
 

14
12
10

ＬＴ１
ＬＴ１
ＬＴ１
ＬＴ１
ＬＴ１

	
 
	
 
	
 
	
 
	
 

8
6
4
2
0

1

3

5

7

9 11 13 15 17 19 21 23
時刻	
 

	
 

図-2	
  3 月 11 日の電力供給量の変化	
 

	
 

	
 

図-1 電力設備の系統	
 	
 電力供給量（ｋｗｈ）	
 3. 震災直後の電力供給量変化
	
 発災直後の東北電力管内配電用変電所の電力供給量の変化を図-2 に示す。発災直後から一部の電力供給量が落ちて、16 時にゼロになったことが分かる。
ここで、16 時までゼロにならない理由は送電設備自体の被害が小さいことと考えられる。そして、地震

8

柳町通変

	
 

6
4
2
0

発生翌日の午前 6 時に柳町通変を始めに東北電力の

1

3

5

7

復旧作業が開始された（図-3）。	
 
	
 

ＬＴ１

9 11 13 15 17 19 21 23
時間（ｈ）



図-3	
  柳町通変の 3 月 12 日の電力供給量の変化	
 

	
 

	
 

4. 電力の復旧状況

100
80
復
旧
率 60
�
％ 40
�	
 

「流通・配電対策班」と「業務機能対策班」を設置した。その中で、復旧作業は、主に「発電対策班」と「流通・配電対策班」が行った。	
 

青森県	
 
岩手県	
 
宮城県	
 
福島県	
 
秋田県	
 
山形県	
 

日時	
 

に復旧するまでには少し時間がかかり、特に、宮城県の復旧活動が遅いことが分かった。	
 図-4	
  停電復旧率	
 

	
 

	
 

	
 

	
 
	
 

2
― 147 ―

20日18時	 

19日18時	 18日18時	 

17日18時	 

16日18時	 

15日18時	 

14日18時	 分かった。一方、岩手県、福島県と宮城県は、完全

13日18時	 に、青森県は 50 時間以内に 100%復旧できたことが12日18時	 0と山形県は系統切替等により地震から 30 時間以内

11日18時	 20

	  図-4 に停電復旧率を示す。これによると、秋田県

23日18時	 本部」、「原子力地点対策班」、「発電対策班」、

22日18時	 	  震災直後に、東北電力は「東日本大震災総合対策

21日18時	
 

	
 

	
 

	
 

5. 復旧優先順位に向けた検討

Ⅰに関しては、宮城県に電力を提供している発電	
 所から一次変電所までの復旧作業が 12 日にすべて	  ここでは、震災地の中で最も復旧が遅れていた宮完了したため、安定的な供給を提供できたと考えら

城県に着目して、電力の復旧優先順位について検討れる。	
 
Ⅱに関しては、図-6 に示すように、宮城県の 3 月

する。	
 
	
  3 月 12 日に 35 カ所、3 月 13 日に 33 カ所、14 日

12 日と 13 日の避難人数はいずれも約 228,200 人でに 48 カ所、15 日に 34 カ所の配電用変電所が復旧をあった。また、大町変の復旧図（図-7）から、復旧開始した。その中で、13 日午前 1 時に復旧し始めた開始直後に電力需要が一気に上がることは大町変の大町変電所の電力需要は直ぐに回復する傾向を見せ

供給エリア内の建物被害が少ないと考えられ、電力た。一方で、例えば、12 日 24 時に復旧し始めた古供給ができれば、すぐに電力を使用できる状況であ川変電所は、電力需要量は増えていったが、その増ったと考えられる。	
 

加量は直ぐにではなく、徐々に増えていく傾向を示	  また、図−8 のように、大町変は変電所 3 として、した（図-5）。	
 古川変は変電所 2 だとしたら、ⅠとⅡの条件が同時

ここで、大町変電所と古川変電所の復旧優先順位に満たす場合、大町変と古川変がお互いに復旧優先を入れ替えると、より電力供給の復旧効果が大きい

順位を入れ替えることができると考えられる。そしと考えられる。ただし、大町変電所に関して、早くて、同じ手法を繰り返して、次のステップは大町変

復旧しても、同じような復旧効果が得られるとは限は変電所 1 と比較して、変電所 4 は古川変と比較すらない。そこで、復旧優先順位を変更する上で考慮

ることになる。	
 
図-9 は、配電用変電所の復旧の順番を入れ替えた

すべき視点とその効果を次に述べる。	
 場合の復旧状況を比較したものである。3 月 13 日頃	
 8から電力需要が大きく改善されていることが分かる。

電⼒力力需要(kwh)

今後は、この検討を踏まえ、どの変電所を優先的に76復旧するのかのインプット要素を明らかにする必要

5

がある。	
 

4

	
 

3
2

	
 

1

7. まとめと今後の課題

0	
 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
⽇日付（3⽉月）

本稿では、配送電施設の被害に対しより損失が少	 なくなる電力復旧優先順位を検討した。その結果、

図-5	
  古川変電所の 3 月 11 日以降の電力需要量の変化（15大町変を事例に述べたように、復旧優先順位を入れ

時時点の電力需要量をプロット）	
 	
 替えると、より早く、より多くの人々が電力を使え

6. 復旧優先順位の調整と効果るようになることが分かった。	
 	 本稿では、実際の復旧状況を把握した上で、分析	  復旧期日を変更するに伴い、同じ復旧効果を得るを行った。今後は、電力需要が事前に把握し、それためには、下記の二つの条件が必要である。	
 に応じて、復旧の優先順位を考慮した電力復旧モデ	 ルを構築する。	
 I.

	 送電側が同じ供給ができること	 II. 配電側が同じ需要家であること	 	 3― 148 ―

500
電力需要(kwh)	
 避難者数（⼈人）

300,000
避難者数（人）

250,000
200,000
150,000

100,000
50,000

300
200
100
0

２９⽇日

２８⽇日

２７⽇日

２６⽇日

２５⽇日

２４⽇日

２３⽇日

２２⽇日

２１⽇日

２０⽇日

１９⽇日

１８⽇日

１７⽇日

１６⽇日

１５⽇日

１４⽇日

１３⽇日

１２⽇日

0

期⽇日

修正前	
 
修正後	
 

400

1201
1204
1207
1210
1213
1216
1219
1222
1301
1304
1307
1310
1313
1316
1319
1322
1401
1404
1407
1410
1413
1416
1419
1422

350,000

	
 

日期	
 
図-9	
  宮城県の電力復旧優先順位の修正比較	 図-6	
  2011 年 3 月における宮城県の避難者数の推移	
 

電力需要(kwh)	
 

15

	
 

謝辞

10

	
 本稿で使用したデータは、東北電力株式会社	
 電力
流通本部	
 電力システム部からご提供頂きました。	
 

5
0

参考文献
１）	
 目黒公郎，副島紀代，山崎文雄，片山恒雄：電1112141618202224262830 1 3 4 6 8 10日期

力需要特性から見た都市の地域分類，土木学会

����	
 

論文集，No.507/I-30，pp.255-263，1995.	
 

	
 

２）	
 飯田亮一，秦康範，目黒公郎：被災度に応じた

図-7	
 大町変復旧推移図	
 地震後の地域別電力需要予測モデルの構築，第	
 61 回土木学会年次学術講演概要集，4-176	
 (CD-ROM)，2006	 ３）	
 山口紀行，秦康範，目黒公郎：電力供給量の変動を利用した被害把握手法における停電エリ
アの補間，第 60 回土木学会年次学術講演概要
集，I-651(CD-ROM)，2005	
 

	
 

４）	
 東北電力：CSR レポート，2012	
 図−8	
  分析手法フロー図	
 ５）	
 東北電力：東日本大震災後の当社の状況報告書，
2012	
 
	
 

The Priority of Electric Power Restoration in the East Japan Earthquake	 Xun	
 CHEN	 ,	 Muneyoshi	
 NUMADA	 and	 kimiro	
 MEGURO	 	 Power is essential for operating our production is stable and efficient day-to-day life. On the other hand,once a power outage occurs, the impact on urban life is extremely large. In particular, the electric delivery
facilities are damaged in the event of a disaster, there is a possibility that the state can not use the powerin some areas for several days . If there is damage of electric delivery facilities, in this paper, we examine
the priority of power restoration more effective.
	
 4― 149 ―

土木学会 第 32 回地震工学研究発表会講演論文集（2012 年 10 月）

災害対策フェーズを用いた災害対策状況の可視化手法の提案～災害報道を利用したモニタリングを事例として～
沼田

宗純1・目黒公郎2

1東京大学生産技術研究所助教(〒153-8505 東京都目黒区駒場4-6-1）
E-mail: numa@iis.u-tokyo.ac.jp
2東京大学大学院情報学環／生産技術研究所教授 (〒153-8505 東京都目黒区駒場4-6-1）
E-mail: meguro@iis.u-tokyo.ac.jp

本研究では，効果的な災害対策を実現することを目的に，「被害抑止，被害軽減，災害予知と早期警報，
被害評価，災害対応，復旧，そして復興」の合計7つの災害対策のフェーズに対し，現状のフェーズがどの段階なのかを可視化する手法を提案する．これにより，災害対策の担い手が，現状の対策がどの段階なのかを認識することができ，総合的に災害対策をマネジメントすることが可能となる．
本稿では，その基礎的な検討として，東日本大震災後の災害報道を利用し，災害対策の各フェーズをモ
ニタリングし，時系列に各フェーズの変化を示す．

Key Words : disaster management, disaster cycle, visualization system

1.

はじめに

2011年東日本大震災は，広範囲かつ多様な被害であったため，災害の全容を掴むことは容易ではなかった．そして，発災後の応急対応，復旧，そして復興へとその対応や対策は長期間に及んでいる．
災害対策は，大きくは事前対策と事後対策に分けられる．事前についてはリスク・マネジメント，事後についてはクライシス・マネジメントによって，対策の立案・進捗管理などが行われる．これらの事
前及び事後の対策は，発災時点を境に事前に，被害抑止，被害軽減，そして災害予知と早期警報の3つ，事後に，被害評価，災害対応，復旧，そして復興の4つ，合計7つのフェーズに分けることができる．そして，復旧や復興は次の発災に対する被害抑止へと繋がるので，発災以前の現況に戻すだけの復旧を行うことは適切でなく，被害再発を防ぐ観点から改良
復旧や復興によってスパイラル的に災害に強い国土や社会構造へと変えていく必要がある1)．
効果的な災害対策を実現するためには，災害対策の従事者が，これら7つのフェーズの視点に立ち，自分たちが今どのフェーズに置かれているのか，対策が不十分なフェーズはどこか，今後優先的に行うべき対策はどのフェーズなのか等，現状の災害対策の状況を把握し，総合的に災害対策をマネジメント
することが必要である．
そこで，本研究では，効果的な災害対策に結びつけることを目的に，上述の7つのフェーズに対し，
現状のフェーズがどの段階なのかを可視化する手法を提案する．これにより，災害対策の担い手が，現状の対策がどの段階なのかを認識することができ，総合的に災害対策をマネジメントすることが可能となる．
その基礎的な検討として，本稿では，東日本大震
災後の災害報道を利用し，災害対策の各フェーズを
モニタリングし，時系列に各フェーズの変化を示す．

2.

7つの災害対策を表すキーワードの設定

災害対策の7つのフェーズを分類するために，各フェーズを表すキーワードを設定した（表-1）．また，各フェーズには，大区分としてハードとソフト，中区分として構造物や土地利用等の内容を分類した．
なお，本稿では，マクロ的な視点で災害対策の各フェーズをモニタリングすることを考え，災害報道を用いることが有効であると考えた．ここで用いた
災害報道データは，JCC株式会社の「ドキュメン
ト・アナライザー」である．これは，1日24時間365
日，番組の内容をテキストデータ化したものである．

1― 150 ―

表-1 各フェーズを表すキーワード（一部）
フェーズ
被害抑止力
被害抑止力
被害抑止力
被害抑止力
被害抑止力
被害抑止力
被害抑止力
被害抑止力
被害抑止力
被害抑止力

3.

大区分

中区分

キーワード

ハード
ハード
ハード
ハード
ハード
ハード
ハード
ハード
ハード
ソフト

構造物
構造物
構造物
構造物
構造物
構造物
構造物
構造物
構造物
土地利用

住宅耐震補強L型擁壁
グラウンドアンカー
バイブロハンマー
防潮堤
安全率
安定材
安定処理
液状化対策
街づくり条例

被害抑止

key2

50.0%
40.0%

復興

10.0%
0.0%

復旧

災害予知・警報

緊急対応

ここでは，NHK総合で放送された東日本大震災関連の報道内容を用いた分析結果を示す．これは，日別に報道された内容を各フェーズに分類し，一日の災害報道時間全体の中で，各フェーズが占める割合を示したものである．
これによると，2011年3月12日（図-1）は，発災直後であり，人命救助，消火活動，二次災害の抑止などの初動対応の段階であることが示されている．
発災から時間が経過すると，緊急対応から復旧段階に入り，図-2に示すようにインフラ施設やライフラ
インの早期復旧等の復旧に関するステージに入ってくることが分かる．さらに時間が経過すると，復興に関する対応が加わってくる（図-3）．
そして，さらに時間が経過すると，被害抑止，被害軽減といったフェーズに入ると考えられる．「被害抑止」は，建物や各種構造物の耐震補強，粘り強い構造への補強，液状化対策，宅地耐震化等，「被害軽減」は，津波避難ビル等の避難施設，停電に対するバックアップシステムの整備等である．
各フェーズの可視化により，被害抑止や被害軽減が相対的に低ければ，7つの災害対策の中で，これらを強化するようにマネジメントし，次の災害へ備えるように誘導することが可能となる．

被害評価

図-2 2011年3月19日の各フェーズの放送割合
被害抑止
50.0%
40.0%

復興

30.0%

被害軽減

20.0%
10.0%
0.0%

復旧

災害予知・警報

緊急対応

被害評価

図-3 2011年4月19日の各フェーズの放送割合

4.

おわりに

本研究は，災害報道を利用し災害対策のフェーズをモニタリングし，7つの災害対策の視点から総合的に災害対策を実現するためのマネジメント手法を紹介した．
今後は，各フェーズを分類するキーワードの設定
精度を向上させ，また，地域別に災害対策フェーズをモニタリングするシステムを開発する．

被害抑止
50.0%
40.0%
30.0%

被害軽減

20.0%

災害対策の可視化

復興

30.0%

被害軽減

20.0%
10.0%

参考文献
１) 土木学会東日本大震災特別委員会 地域防災
計画特定テーマ委員会：地域防災計画特定テーマ(委)中間とりまとめ(案)20111219 版.pdf，
2011 年 12 月

0.0%

復旧

災害予知・警報

緊急対応

被害評価

図-1 2011年3月12日の各フェーズの放送割合

2― 151 ―

PROPOSAL OF THE VISUALIZATION OF DISASTER-COUNTERMEASURESITUATIONS BY USING DISATER MNAGEMENT CYCLE- CASE STUDY OF DISASTER MEDIA REPORT Muneyoshi NUMADA and Kimiro MEGURO
This research proposes the visualization system of the stage/phase of disaster countermeasures condition by using seven index of “Mitigation, Preparedness, Prediction & Early Warning, Assessment, Response, Recovery and Reconstruction” for the purpose of effective coutermeasreus against the disaster.
As the basic analysis, in this paper, the change of each phase is visualized in a time series. The reports reported by tmass media during Tohoku earthquake in 2011 are used for that analysis.
Professionals, Specialists and Goverments etc. who are engaged in the disaster measurements can understand the stage/phase of their current measreument’s condition, and it is possible to manage effective
or necessary countermeasures in the point of the seven stages/phases.

3― 152 ―

土木学会 第 32 回地震工学研究発表会講演論文集（2012 年 10 月）-*+L4 >2J
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Analysis of the dispatch of local government staff conducted in the Great East Japan
Earthquake
Satoshi NODA, Makoto FUJIU, Muneyoshi NUMADA and Kimiro MEGURO
In the Great East japan Earthquake, many local governments along the Pacific Ocean in the East Japanare heavily damaged and result in a dysfunction. Local governments damaged heavily need support fromgovernments all over Japan.
Many local staff go to the damaged areas and deal with to support damaged local governments to
support local governments damaged heavily. Governmental staff sent from all over Japan helped local
governments damaged heavily to deal with a lot of task. However, there are many cases that government
staff dispatch t isn’t conducted based on the disaster mitigation principale.
In this research, we analyze staff dispatch by local governments in the 2011 Great East Japan
Earthquake. Based on this analisys, we clarify the tendency of the staff dispatch and examine theproblems concerning support to the local governments damaged heavily.
According to this analisys, many local governments dispatch governmental staff to one local
government. On the other hand, one local government dispatch staff to many local governments. Futureissues are clarification and verification of the problems concerning the dispatch of staff.

5― 157 ―

Muneyoshi NUMADA1 and Kimiro MEGURO2
1

Research Associate, ICUS, IIS, The University of Tokyo, Japannuma@iis.u-tokyo.ac.jp
2
Professor, ICUS, IIS, The University of Tokyo, Japan

ABSTRACT
Following the 2011 Tohoku Earthquake in Japan, we have noticed that TV
coverage highly emphasized certain municipalities, repeatedly reporting its
damage and disaster response activities. Nuclear power plant accident was also
extensively highlighted. The news coverage focusing on specific regions induced
aid and support e.g. distribution of relief supplies and donations -- to certain
areas only. This problem of unbalanced press coverage has also been witnessedin the past disasters -- Hokkaido Nansei Oki Earthquake in 1993, Hokkaido Toho
oki Earthquake in 1994, and the Southern Hyogo prefecture earthquake in 1995.
While the same issue arose again in the 2011 Tohoku Earthquake, lopsided media
coverage again failed to offer disaster overview or enhance understanding thetotal damage, both of which are crucial in times of such massive earthquake. We
believe that TV media bears heavy responsibility and should therefore play theleading role in providing information that helps people to make appropriate
decisions and judgments.
The purpose of this research is to conduct a quantitative analysis of themunicipalities that were repeatedly featured in TV news reports. Media coveragerate by municipalities was analyzed to find out the relationship between media
coverage amount and damage level.
The result showed that even if the damage levels were equal, the amount of TV
news coverage among the municipalities differed -- a common and distinctive
feature among all TV stations. One of the reasons can be explained by the factthat TV crew was unable to reach certain cities and towns due to damaged roads
and traffic. However, another reason and perhaps the essential problem lie in the
longtime tendency of Japanese TV stations: to follow and conform to successful
reports which has given impact and sensation. The unbalance occurs because
each TV station is driven by the fear of missing out on a scoop. The results of thisstudy, based on quantitative analysis, are an indication of these alarming
phenomena.
Keywords: TV news coverage, TV media, disaster information, Tohoku
earthquake― 158 ―

October 2012, Ulaanbaatar, Mongolia

1. INTRODUCTION
1.1 Overview of the 2011 Tohoku Earthquake
At 14:46 JST (5:46 UTC) on March 11th, 2011, an earthquake of a moment
magnitude 9.0, the largest earthquake ever recorded in Japan, struck off the shore
followed, deeplyof the Sanriku area in the Tohoku Region. The
hitting indented coastal areas and bringing enormous and devastating damage tomany cities and villages in the area. Damage bymega tsunami was not only
limited to buildings, but the resulting fires destroyed many communities, taking
lives of thousands. Moreover, nuclear power plant (NPP) facilities sufferedcomplicated and serious damage. This earthquake was later officially namedby the Japan Meteorological
Agency (JMA).
1.2 Importance of TV programs
In this earthquake, people faced difficulty in grasping the full scope of thedisaster since the damage was extremely widespread and diverse. To obtain
information on damage conditions, safety confirmation, news and announcementsfrom municipalities, all kinds of media were used. In addition to the conventional
television, radio and the Internet, new types of information-sharing tools such as
Twitter and Facebook were utilized. The Internet TV news sites, such as
USTREAM and NICO-NICO DOUGA, were also capable of broadcasting NHK(Japan Broadcasting Corporation) programs and commercial TV stations at nocharge. Furthermore, people could watch TV programs in the open air byreceiving one-segment broadcasting services.
According to a survey (Nomura Research Institute, Ltd. 2011) on trends inmedia contact associated with the 2011 off the Pacific coast of Tohoku
earthquake , TV was ranked no.1 and no.2 as the important information source.
On acquiring earthquake information, about 80.5% considered
TV andNand56.9% consideredboth ranked below TV.
Likewise, another survey (My Voice Communications, Inc. 2011) shows "howpeople gathered information on the 2011 Tohoku earthquake". Here again, TV
was ranked top at 93.5%, followed by newspapers at 44.9%, Internet news sites at
44.8%, Internet portal sites (e.g. Yahoo) at 42.8% and radio at 31.1%. These
results evidently show that the majority relied on TV as the main tool to get
information.
According to the Article 108 of the Broadcasting Act and Disaster
Countermeasure Basic Act (Tanaka 2008), broadcasting organizations are obliged
to provide useful services in order to prevent and minimizing disasters. Also, theMinistry of Internal Affairs and Communications has requested NHK and the
National Association of Commercial Broadcasters in Japan to provide accurate
and detailed information to the public as quickly as possible (Ministry of Internal
Affairs and Communications 2011).
Considering the above, we can say that the expected role of TV news is not justreports on damages but also to provide useful information that prevent further
damage. TV news is indeed

New Technologies for Urban Safety of Mega Cities in Asia
― 159 ―

to make appropriate contributions in disaster management.
1.3 Problems of TV programs
Immediately after the 2011 Tohoku Earthquake, certain affected areas, where
TV reporters could easily reach, were repeatedly exposed from an early stage,leaving strong impact on the viewers. Obviously, specific municipalities wereintensively covered by TV news than others. High emphasis was also placed on
the nuclear power plant accident. We can say that the news coverage was prettymuch unbalanced, especially when considering the vast extent of the affectedareas. This unfairness eventually led to the uneven allocation of aid activities,
with distribution of relief supplies and donations concentrated to limited
municipalities while other areas were left neglected.
Although this problem of media coverage concentration has been repeatedly
pointed out in the past earthquakes (Nakamori 1995) such as Hokkaido Nansei
Oki Earthquake in 1993, Hokkaido Toho oki Earthquake in 1994, and theSouthern Hyogo prefecture earthquake in 1995, the same issue arose again in the2011 Tohoku Earthquake (Nakamori 2011). Unbalanced media coverage on
certain topics and areas does not offer the audience comprehensive views orunderstanding of total damage, both of which are crucial especially at the time ofsuch massive disaster. TV media is heavily responsible for providing information
to the public so that they can make correct decisions and take appropriate actions.
Previous studies on TV news coverage and contents after the Tohoku
earthquake include: chronological analysis of TV news contents (NHK 2011),
verification of early media coverage, confused and disordered reports of thenuclear power plant accident, and analysis of foreign media reports (Generalincorporated association of Tokyo-sya 2011). But never before had there been any
quantitative analysis of TV news coverage unbalance conducted.
1.4 Purpose of this research
The purpose of this study is to conduct a quantitative verification of theunbalance in media coverage by municipalities during the emergency period after
the Tohoku earthquake. The correlation between media coverage and damagelevel during the first ten days after the disaster was analyzed.
2. TV news data
In this study, we selected six major TV stations, namely NHK, NTV, TBS, Fuji
TV, TV Asahi, and TV Tokyo. TV content analysis generally requires text datafrom each program section. Especially for this study, we adopted a database called"Document-Analyser" by JCC Corporation, which allowed us to obtain text dataof all six TV stations for 365 days a year, 24 hours a day and by the unit ofseconds. The database enabled us to comprehend the full details of when, what,
where, and how each TV stations reported. Table 1 shows an example of the text
data of NHK on March 12th.
The target period of this research covers the ten days from March 11th to 20th,
considering the importance of TV news reports at an early stage immediately after
the disaster. We paid attention to how the damage situation became apparent
Your paper title― 160 ―

October 2012, Ulaanbaatar, Mongolia

along with how much influence the news reports gave on supply of relief goods.
Table 1: Example of the text data of the TV program (259 characters)
In Miyagi Prefecture, by the earthquake, 53 people were killed. The details is 17 people in the
Higashimatsushima city, 12 people in the Kesennuma city, 8 people in the Shichigahama
town and 5 people in the Sendai city. In the coastal town of Minamisanriku where was
attacked by the tsunami, many buildings and houses were washed away by the tsunami
except the hospital building constructed by concrete, and many people were missing. In thearea along with the port of Kesennuma in Kesennuma city, the large-scale fire occurredcaused by the outflowing oil from the tank at the port. The video of Kesennuma city. (March
12, NHK)
3. Concentration of TV PROGRAMS
Contents of news programs broadcasted by each TV station were more or lesssimilar; no big difference or distinctive feature was observed from the reports
produced during the ten days after the disaster.
3.1 Index C Definition: Concentration-ratio of municipality news coverage
This chapter analyses by text data the way each TV station focused its reports
on specific municipalities. Concentration-Ratio of the News Coverage on
e C is indicated by the ratio of "theMunicipality is defined as Index
total number of all municipalities each TV station has picked up" and "the numberof each municipality each TV station has picked up." Here, the definition of "pickimplies the appearance of municipality name in text data as underlined inTable 1. For example, Higashimatsushima CC
Shichigahama T
C
i-Sanriku T
respectively in the text given in Table 1.
If the Index C scores high, it indicates that the TV station has made intensive
reports focusing on a particular municipality. If the Index C is low, it suggests thatno specific municipality has received unusual attention. If the Index C is zero,then municipalities got no coverage at all.
3.2 Correlation between C value and damage level
In this section, we discuss the relationship between the C value and damagelevel. Although previous studies have conducted a quantitative analysis ofcorrelation between newspaper coverage and damage level (Matsumura 1998), therelationship between the TV report coverage and damage level has not yet beenstudied.
The definition of "earthquake coverage rate" is indicated by the ratio of quakerelated reports in all newspaper articles excluding advertisements. The result
suggests a high correlation between eand the numberof casualties, but not much correlation with the number of totally collapsedbuildings.

New Technologies for Urban Safety of Mega Cities in Asia
― 161 ―

Number of casualties

10000

Number of casualties

10000

Higashimatsusima city
Otsuchi town

1000

1000

Kesennuma city
Yamamoto town

Kamaishi city

Kamaishi city

100

10

10

0%
5%
10%
%
Concentration-ratio of the municipality
C

1

15%

0%
5%
10%
%
Concentration-ratio of the municipality
C(a) NHK(d) Fuji-TV
10000

Higashimatsusima city
Otsuchi town
Kamaishi city

1000

Higashimatsusima city
Otsuchi town

1000

Kesennuma city

Kamaishi city

Yamamoto town

100

10

10

0%
5%
10%
%
Concentration-ratio of the municipality
C

1

15%

0%
5%
10%
%
Concentration-ratio of the municipality
C(b) NTV(e) TV-Asahi

100

10000

Higashimatsusima city
Otsuchi town

1000

Kamaishi city

15%

Number of casualties

Number of casualties

10000

Kesennuma city

Yamamoto town

100

1

15%

Number of casualties

Number of casualties

10000

Kesennuma city

Yamamoto town

100

1

Higashimatsusima city
Otsuchi town

1000

Kesennuma city

100

Yamamoto town

Otsuchi town

Higashimatsusima city
Kesennuma city

Kamaishi city
Yamamoto town

10

10
1

1
0%
5%
10%
Concentration-ratio of the municipality
C
%

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20%
%
Concentration-ratio of the municipalityC30%(c) TBS(f) TV-Tokyo
Figure 1: Relationship between the number of casualties and the concentration
ratio of the municipality

Your paper title― 162 ―

October 2012, Ulaanbaatar, Mongolia

Number of casualties

Number of casualties

1000

50

Otsuchi ctown

40
30
20
10
0

Kesennuma city

100
Yamamoto town
Higashimatsusima city

Higashimatsusima city

Kesennuma city

10

Kamaishi city
Ofunato city
Natori city

Sendai city

1

0%
5%
10%
15%
20%
%
Concentration-ratio of the municipality
C

25%

0%
5%
10%
15%
%
Concentration-ratio of the municipality
C20%(a) the day of the earthquake,(b) three days after the earthquake,2011.3.11
2011.3.13
Figure 2: Relationship between the number of casualties and the concentration
ratio of the municipality of NHK
Using the above result as reference, this paper analyses the relationship between
casualties and the Index C of TV news coverage. The number of total casualties
used here represents the sum of the missing and the dead.
Figure 1 shows the relationship between casualties and the Index C on March
11th. In calculating the Index C here, the total number of news coverage onmunicipalities from March 11th to 20th is used, and the number of casualties
referred to those confirmed by March 20th.
Focusing on the municipalities with over 1,000 casualties, NHK showed thehighest Index C score for Kesennuma City, followed by Kamaishi City, Otuchi
Town, Higashimatsushim City and Yamamoto Town. This result shows that eventhough the number of casualties is similar, significant difference is seen in theamount of TV news coverage on municipalities.
Similarly, when looking at Nihon-TV s reports on municipalities with over1000 casualties, the Index C of Kesennuma shows high value, while Yamamotoand Higashimatsushima show relatively low value. The same tendency isobserved in other TV stations. This tendency can also be observed from thechronological analysis as given in Table 2 (a) and (b). On March 14th, in
Higashimatsushima City, 152 dead and 400 missing people were found, likewiseon March 15th in Yamamoto, 111 dead and 638 missing people were found.
Despite these findings of high number of casualties, no obvious reaction wasobserved in the Index C.
Figure 2 shows the relationship between casualties and the Index C of NHK on
the day the earthquake hit, the third and the tenth day after disaster. The C iscalculated by the number of coverage on March 11th, the day of the earthquake,the sum of the coverage of the third and the tenth days respectively. The numberof casualties used is the sum of dead and missing people on the day of theearthquake, by the third and tenth days since March 11th respectively.
The Index C of the Sendai and Natori cities on the day of the earthquake is high,subsequently followed by Ofunato City, Kamaishi City, Kesennuma City,
Higashimatsushima City and Yamamoto Town. At this stage, Otsuchi Town is notcovered as seen in Figure 2 (a). Now, we will discuss by comparing two
municipalities of Kesennuma City and Otsuchi Town.
On the third day (Figure 2 (b)), both Kesennuma and Otsuchi showed increase
New Technologies for Urban Safety of Mega Cities in Asia
― 163 ―

in the number of casualties. Nevertheless, the Index C of Kesennuma rose whilethat of Otsuchi remained unchanged. By the tenth day, the number of casualties ofboth reached almost the same level, yet a large gap in Index C is observed.
These results have proved quantitatively that difference exists in Index C, despite
the fact that the casualty level is the same. Therefore, the figures indicates that thenews report coverage is unbalanced, and this tendency is common among all TV
stations. Of course, one of the reasons may be explained by the accessibility tocertain municipalities due to road conditions. However, another reason may bethat TV stations tend to conform with reports by major successful TV stations
which have managed to deliver news with strong impact because they are driven
by the fear of missing out on a scoop. The results of this study, based on
quantitative analysis, are an indication of these alarming phenomena.

4. CONCLUSIONSThe concentrated news coverage induced the unfair allocation of relief supplies
and donations to some specific areas. This problem has repeatedly happened in
the past disasters. This research has proved quantitatively that difference exists in
Index C, regardless whether the casualty level is the same or not. This fact has
shown the fact that news report coverage is unbalanced among all TV stations.
One of the reasons may be the accessibility to certain municipalities due to theroad conditions. However, another reason may be that the TV stations have thetendency to conform with reports by major successful TV stations which managed
to deliver news with strong impact, and they are driven by the fear of missing out
on a scoop. The results of this study, based on quantitative analysis, are an
indication of these alarming phenomena.
Led by these results, we propose the following strategy to improve the standardof fairness in TV news reporting ahead of the next disaster. Considering thelimited time and human resources at TV stations, we strongly advise them to: (1)grasp the overall damage conditions and perspective accurately, (2) provide
information that corresponds to the direct needs of the audience, and (3) promote
cooperation among TV stations, pay respect to press freedom, avoid unbalanced
news coverage focusing on specific municipalities only, and lastly, improveaccess to obtain necessary information.
With regards to the role of the press, TV stations are expected to provide useful
information, thereby contributing to appropriate disaster response, both frominside and outside the disaster-affected areas (Cabinet Office of Japan 2008). The
above-mentioned strategy will serve as the guideline for improvement in this
aspect.
In the next phase of this study, we will develop similar analysis using theamount of reporting time, then verifying the difference from text data. Moreover,
we will carry out further study to find out what kinds of subject matters werereported intensively.

Your paper title― 164 ―

October 2012, Ulaanbaatar, Mongolia

AKCNOWLEDGEMENT
This research has been supported by Mr. Takatoshi Ishii of JCC Corporation.

REFERENCE
General incorporated association of Tokyo-sya (2011). Journalism of
unprecedented disaster and tribulation, Journal of general journalism research,
No.217, pp.9-18, 26-51
Japan Cabinet Office of Japan (2008). Basic Disaster Management Plan, pp.48-49.
Kazuo Matsumura (1998). Reaction of society against the earthquake disaster
reported by the newspaper, Journal of Architectural Institute of Japan. 511,
pp.61-67.
Ministry of Internal Affairs and Communications (2011). The request for Japan
Broadcasting Corporation and National Association of Commercial
Broadcasters in Japan about the information providing of the 2011 Off the
Pacific Coast of Tohoku Earthquake, http://www.soumu.go.jp/menu_news/snews /01ryutsu07_01000018. html. [Accessed at 2011.4.1]
My Voice Communications, Inc. (2011). Questionnaire survey on "How to gather
information about the 2011 Off the Pacific Coast of Tohoku Earthquake ",http://www.myvoice.co.jp/biz/surveys/15417/index. html. [Accessed at
2011.5.30]
Nakamori H., (1995). Problems about initial and regional-detail information
focused on the city of Hanshin region, Journal of the Institute of Social Safety
Science (5), pp.21-28.
Nakamori H., (2011). Problems of news and mass media in the 2011 Off the
Pacific Coast of Tohoku Earthquake. Journal of Urban problems, Vol.102,
pp.4-9.
NHK (2011). What kinds of contents did TV stations provide in the 2011 Off the
Pacific Coast of Tohoku Earthquake, NHK broadcasting studies, Vol. 61, No.5,
pp.2-7.
NHK (2011). What kinds of contents did TV stations provide in the 2011 Off the
Pacific Coast of Tohoku Earthquake (2), NHK broadcasting studies, Vol. 61,
No.6, pp.2-9.
Nomura Research Institute, Ltd. (2011). Research on trends in media contact
associated with the earthquake, http://www.nri.co.jp/news/2011/110329.html.
[Accessed at 2011.3.29.]
Tanaka H., and Yoshii A., (2008). Introduction to Disaster Information Theory,
Koubundou, pp.164-165, 218-227.

New Technologies for Urban Safety of Mega Cities in Asia
― 165 ―

Akiyuki KAWASAKI1, Michael HENRY2, and Kimiro MEGURO3
1
Project associate professor, International Center for Urban Safety Engineering,
Institute of Industrial Science, the University of Tokyo, Japanakiyuki@iis.u-tokyo.ac.jp
2
Assistant professor, Division of Field Engineering for the Environment,
Faculty of Engineering, Hokkaido University, Japan
3
Professor and Director, International Center for Urban Safety Engineering,
Institute of Industrial Science, the University of Tokyo, Japan

ABSTRACT
After the March 11 Tohoku Earthquake, people living in Japan were faced with
confusing and conflicting messages from differing information sources which
created an atmosphere of uncertainty and led many people, particularly
foreigners, to relocate to western Japan or leave the country entirely. In order toimprove the dissemination of information after future disasters, a survey was
conducted to understand how people in the Kanto region the most populous
area of Japan and border the Tohoku region received their disaster information,
what difficulties they encountered related to disaster information and how these
may have affected their post-disaster decisions. This paper presents analyses anddiscussions on the relationship between language ability and disaster information
gathering behavior, information difficulties, and demographic characteristics.
Keywords: 2011 Tohoku Earthquake, disaster information, language ability

1. INTRODUCTION
At 14:46 on March 11th, 2011, a magnitude of 9.0 earthquake with a hypocenterin the Pacific Ocean off the Sanriku area of Tohoku struck, causing enormous
damage mainly in the eastern area of Japan. This earthquake (which shall berecorded in Japan and resulted in a massive tsunami which hit the Tohoku andKanto regions, but also triggered a nuclear power plant crisis which included core
meltdown and the release of radioactive material.
The news of this earthquake was immediately delivered all over the world, butdifferences in the reported urgency level of the crisis and disagreements andcontradictions between the contents of overseas and domestic media after theearthquake soon emerged. Under these circumstances, a large number offoreigners residing in Japan hurriedly evacuated for short- or long-term periods
either inside the country or outside Japan. This evacuation had broad implications― 166 ―

October 2012, Ulaanbaatar, Mongolia

on socio-economic activities. These effects include the withdrawal of foreign
government functions in Japan due to the relocation or closure of embassies,functions, relocation of supply chain or human resources outside of Japan, and soforth. The educational field was particularly hard-hit, as up to 80% of foreign
students in the Tohoku region returned to their country, and many did not returnto Japan; this effect was also felt in the Kanto region and other areas of Japan, andthe withdrawal of large numbers of foreign student had a large impact on someuniversities economic situation. The tourism industry was also affected by thecancellation of trips, tours, conferences, and so forth.
After the Tohoku Earthquake, many important questions about disaster
information dissemination particularly as it relates to foreigners were raised.
How did foreigners residing in Japan collect disaster information? Which sources
did they trust when faced with a wide variety of information released from both
domestic and overseas sources? Did differences in their Japanese and English
language ability affect their information collection behavior or which information
sources they trusted the most or least? What aspects of disaster information may
have contributed to the widespread flight of foreigners? What should be done toimprove disaster information dissemination to foreigners after future disasters?
To contribute to solving these issues, we conducted a questionnaire survey
targeted at Japanese and foreigners residing in the Kanto region at the time of theearthquake. Previous analyses have introduced general results focusing on the
differences between Japanese and foreigners (Kawasaki et al., 2011; Henry et al.,2011). In this paper, we examine the disaster information gathering behavior andrelated difficulties considering the language ability in order to better understand
how we may improve disaster information dissemination in the future.

2. SURVEY METHODOLOGY & SAMPLE CATEGORIZATION
2.1 Survey design & distribution
We carried out an online questionnaire survey focusing on people in the Kanto
region, which is the most populous area in Japan and includes Tokyo and sevensurrounding prefectures. In order to collect samples from the major foreign
nationalities, we prepared the survey in nine different languages. A detailed
overview of the survey contents is provided in Kawasaki et al. (2011) and Henryet al. (2011). The survey was distributed via two methods: first, through social andprofessional contacts; and second, through direct requests for cooperation withentities such as business communities, universities, embassies, and so forth.
Responses were gathered for two weeks beginning roughly 10 weeks after theearthquake occurred.
2.2 Categorization by language ability
A total of 1,357 responses were collected in this survey, of which 497 were fromJapanese and 860 were from foreign nationals representing 73 countries. We first

New Technologies for Urban Safety of Mega Cities in Asia
― 167 ―

categorized the respondents into groups according to their self-assessed Japanese
speaking and listening and English proficiency levels, as summarized in Table 1.
The purpose of this analysis is to investigate
how the difference in language ability levels affected disaster informationcollection behavior, so the respondents who chose the upper or lower two levels
They were then divided
into three categories based on langu
high proficiency in only English or only Japanese. This resulted in the extractionof 767 respondents, who were then divided into five groups depending on theirlanguage ability category and nationality (Japanese or foreigner).
Table 1: Categorization of respondents according to language ability
English proficiency
NativeNativeAdvanced

Intermediate

Basic

None

Advanced

JPN+ENG
F:198 J:76

F:74
J:135

JPN only
F:42 J:236

Intermediate

F:152

F:57 J:1

F:30 J:1

Basic

ENG only
F:215

F:56

F:9 J:1

None

3. ANALYSIS BY LANGUAGE ABILITY
3.1 Disaster information sources
The most-trusted disaster information sources are shown in Figure 1 bynationality and language ability. For foreigners [JPN+ENG] and [ENG only], themost-trusted sources were International Organization, Japanese news source, andJapanese government. For foreigners [JPN only], however, the most-trusted
source was Japanese news source, followed distantly by Japanese government andinternational organization. For Japanese respondents, the most-trusted source wasJapanese news sources, followed by the Japanese government and Japanese
research/academic institutions.
Overseas news source

25 Overseas news

Overseas government

28

32
Overseas news
31

Overseas

19 Overseas news
10

Overseas

Overseas

Overseas research/academic

Overseas
research/
31

27
Overseas
research/

17
Overseas research/

International organization

41International

43International

38 International

16

Overseas news

17

Overseas15
517Overseas research/
28

11International

10

Family, friends, etc.

Family, friends, etc.
1724
Family,friends, etc.

24
Family,friends, etc.

18
Family, friends, etc.

Third party other than family,

8Third party other than

10
Third party other thanThird party other than3 Third party other than

6

7

5

7

4

5

TEPCO

TEPCO

TEPCO

TEPCO

TEPCO

Japanese news source

37
Japanesenews

40Japanesenews

64 news
JapaneseJapanese
59 news

Japanese government

42 Japanese

40

38

39

34
Japanese
research/

31
Japanese
research/Japanese research/academic
0

25

50

75

100

Japanese

0

25

50

75

100

Japanese

33
Japanese
research/
0

25

50

75

100

20

66

Japanese

46

Japanese
39 research/
0

25

50

75

100

36
0

25

Figure 1: Most-trusted disaster information sources

Disaster information collection by Thai and foreigners during the 2011 Thai flood― 168 ―

50

75

100

October 2012, Ulaanbaatar, Mongolia

Figure 2 shows the least-trusted disaster information sources. A similar trend canbe seen for foreigners [JPN+ENG], [ENG only], [JPN only] and Japanese[JPN+ENG], with the top least-trusted information source being the Tokyo
Electric Power Company (TEPCO), followed by the Japanese government andoverseas news sources. For Japanese [JPN only], TEPCO is still the top leasttrusted source, followed by the Japanese government and Japanese news sources.
43
Overseasnews

Overseasnews
44Overseas news source

14

Overseas

17

Overseas government

7 Overseas research/

Overseas research/academic

International

6

International organization

31Overseas news
17

Overseas32
Overseas news
12

Overseas3

5 Overseas research/

5 Overseas research/

3

Overseas research/

1

2

0

1

International

2

International

International

Family, friends, etc.

Family, friends, etc.
18

13Family, friends, etc.

12Family, friends, etc.

13Family, friends, etc.

Third party other than family,Third
15 party other than

16 party other than
Third

Third party other thanThird
24 party other than

TEPCO

57 TEPCO

52 TEPCO

57 TEPCO

59 TEPCO

Japanese news source

23 Japanese news

18 Japanese news

19 Japanese news

22 Japanese news

Japanese government

49 Japanese

50 JapaneseJapanese research/academic

4 Japanese research/

4 Japanese research/

0

25

50

75

100

0

19

Overseas

25

50

75

100

36
2
0

Japanese

45 JapaneseJapanese research/

4 Japanese research/

25

50

75

100

0

25

50

75

100

10
19
55
25
43
7
0

25

50

75

100

Figure 2: Least-trusted disaster information sources
In order to evaluate the net trust-worthiness of information sources, the percentageof respondents who found a source to be un-trustworthy was subtracted from thepercentage who found a source to be trust-worthy. These results are summarized
in Figure 3. For foreigners [JPN+ENG] and [ENG only], the source with thehighest net trust-worthiness was international organization, and for foreigners[JPN only] and Japanese [JPN+ENG] and [JPN only], the source with the highest
net trust-worthiness was Japanese news source. The source with the lowest net
trust-worthiness for all groups was TEPCO. Large differences by language ability
could be seen for international organization and Japanese news sources: in thecase of the former, the net trust-worthiness was much lower for Japanese [JPN
only] than for the other groups; conversely, for Japanese news source, the net
trust-worthiness was much lower for foreigner [JPN+ENG] and [ENG only] thanfor the other groups.
F:JPN+ENG

F:ENG only

F:JPN only

J:JPN+ENG

J:JPN only

60

2422

16
11

20

5

0
-20

45
41
37

40
36 38

40

-5
-11-12-16-20-7121410

1

26
1112

8
-1

5

36
283031 29

22
15

11

3

2
-8 -6
-14 -14
-21

-8 -9

-5

-40
-50-47-50 -50
-55

-60

Figure 3: Net trust-worthiness of disaster information sources
3.2 Media & language for disaster information acquisition
The media and language utilized for acquiring disaster information is shown in
Figure 4. Foreigners [JPN+ENG] used Japanese TV the most, followed bytraditional internet in both English and Japanese. These respondents also tended to

New Technologies for Urban Safety of Mega Cities in Asia
― 169 ―

use Japanese more for non-internet media modes and English more for internet
media modes. For foreigner [ENG only], however, English was overwhelming
used for all media modes, with traditional internet and TV being the most-used.
Conversely, foreigners [JPN only] showed the opposite trend, with Japanese being
the most-utilized language for nearly all media modes. In this case, Japanese
television was the most-used mode, followed by Japanese traditional internet andtraditional internet in other languages. The media and language usage pattern forJapanese [JPN+ENG] and [JPN only] was fairly similar, with Japanese television,
traditional internet, and printed media as the most-used media modes. Japanese[JPN+ENG] did, however, tend to use English in addition to Japanese much morethan Japanese [JPN only].
Japanese
EnglishOther
Television

18

87

41

Television

19
5
4

Radio

Radio

Printed media

35
34
16

Interpersonal

37
33
27

Printed media
InterpersonalInternet:traditional

7070Internet:traditional

33

Internet: directcomm. tools

26
31
22

Internet: directcomm. tools

Internet: social
media

32
45
17

Internet: social
media

Internet: crisis
mapping17
21
5Internet: crisis
mapping

0

25

50

75

100 0

28
64
9
3
10
3
5
27
10
5
41
21
13
81
23
3
43
16
4
45
10
4
20
1
25

50

83

Television

12
26
2
36
10
36
36

Radio
Printed media
InterpersonalInternet:traditional

7

Internet: crisis
mapping
75

100

Radio

Interpersonal
79

Internet:traditional

45

0

25

Internet: directcomm. tools

Internet: crisis
mapping75

100

0Television
Radio

59

41
5
16
13
1
43
24
1
14
5

Internet: social
media

50

95

14
1
33
11
3

Printed media

26
12
33
19
24
14

Internet: directcomm. tools
Internet: social
media

18
1
36
3
1

Television

Printed media
Interpersonal
88

25

50

97

1
31
48

1
29

Internet:traditional

1411Internet: directcomm. tools

1

Internet: social
media

35
3

Internet: crisis
mapping

1

75

100 0

86

10
25

50

75

100

Figure 4: Utilized media and language for acquiring disaster information
3.3 Problems related to disaster information acquisition
Figure 5 shows the reasons why respondents encountered difficulties related to
information acquisition. Confused by conflicting or differing information was thereason cited by the highest percentage of respondents for all groups except forforeigners [ENG only], for whom language comprehension was the largest
problem, and Japanese [JPN+ENG], for whom inability to access information wasjust as highly rated as conflicting or differing information. The differences basedon nationality and language ability were relatively small for most reasons except
for inability to access information and language comprehension. For the former,
Japanese respondents appeared to have more trouble with accessing information
due to mobile congestion, power outage, and so forth than foreigners did. For thelater, foreigners [ENG only] the only group not skilled in Japanese cited
language comprehension difficulties much more than the other groups.

Disaster information collection by Thai and foreigners during the 2011 Thai flood― 170 ―

October 2012, Ulaanbaatar, Mongolia

F:JPN+ENG

F:ENG only

F:JPN only

J:JPN+ENG

J:JPN only

100
80
60
40

78

71
55
40

48

70

74 71 70

20
0

73

58

11
Unable to access
Confused by conflicting or
information (mobile
differing information
congestion, power outage,etc.)

18 21 21
2

1

28 27

25 23

1

Couldn't understand(language ability)

Couldn't understand(terminology)

24
10

15

Unable to find information(difficulty in searching or
locating)

Figure 5: Reasons for problems related to disaster information acquisition

4. DISCUSSION
4.1 Dissemination of disaster information to foreigners in English
After the Tohoku Earthquake, to what extent did information originating fromdomestic (Japanese) sources get disseminated to foreigners residing in the Kanto
region? Were foreigners who can understand Japanese the only ones able to utilize
information from domestic sources, whereas those less skilled in Japanese wereunable to receive domestic information? We propose the hypothesis that major
Japanese information provided by domestic information sources was somehowtransmitted to many foreigners in English. If so, then even Foreigner [ENG only]
was able to obtain the same Japanese-language information delivered fromdomestic information sources as Foreigner [JPN+ENG], and this fact led to bothgroups having a similar pattern for most- and least-trusted information sources.
However, Foreigner [JPN+ENG] tended to collected information from both
Japanese and English media, whereas Foreigner [ENG only] collected information
mainly in English with a very low percentage of information collection in
Japanes
Earthquake provided by domestic information sources was disseminated to
we found that there were primarily three means by which the information fromdomestic information sources was disseminated to foreigners in English.

broadcaster. For regular NHK General TV programs, two news programs aretranslated in English simultaneously using alternative audio, however, after the
Tohoku Earthquake two additional news programs were also translated in English
simultaneously with extended airtime. In addition, NHK also broadcast the news
briefings of TEPCO and press conferences of the Prime Minister with-hour English news program which normally can only be viewed
overseas, was delivered after the earthquake via the Internet and via cable TV in
Japan through special arrangements with domestic cable TV companies. Throughthese supporting activities led primarily by NHK, there were a variety of Japanese
news programs choices which could be viewed in English for a period after the
Tohoku Earthquake. Although the utilization of television in both Japanese and

New Technologies for Urban Safety of Mega Cities in Asia
― 171 ―

English by Foreigner [ENG only] was not as high as other media modes (asshown in Fig. 2), we believe that TV played an important role as one of the usefuldomestic information sources in English.
The second means was through the use of social media such as Facebook tocollect or find domestic information translated into English by a third party.
pful and
important information source after the earthquake in their open responsecomments. The Fukushima Reactor Feed was a Facebook page launched at noonon March 12th by a foreigner residing in Japan, with the intention of sharing
information on the nuclear power plant crisis by translating news broadcasts andarticles related to situation in Fukushima. Some of this information included
URLs referring back to the original information source, whereas somen of domestic TV broadcasts
and news articles. As a result, information translated with a wide range ofaccuracy was available to many foreign audiences. Similarly, some individuals
and groups provided Japanese information by translating it into English on their
blogs and websites.
The third means was automatic translation of Japanese text into English usingtranslation software or translation applications via a web browser. In this case, it
is difficult to obtain an exact translation of a Japanese sentence into a English one,but some people may believe consider it is possible to understand the approximate
meaning by identifying keywords from the translation result.
As described here, an environment was built on the Internet which allowed
foreigners to understand the circumstances by collecting secondary English
translations of Japanese information or by translated broadcast contents. Thus,
Foreigner [ENG only] was able to obtain similar information as Foreigner[JPN+ENG], which may explain why their reliability on domestic information
sources was similar.
4.2 Reliance of foreigners skilled in English on overseas information sources
Why did Foreigner [JPN+ENG], who collected domestic information in both
Japanese and English, and Foreigner [ENG only], who collected domestic
information mainly in English, both tend to place higher reliability on overseas
information sources, and why did they both tend to distrust domestic information
sources? Through analysis of the open responses provided by foreigners thefollowing reasons were derived.
Both groups (Foreigner [JPN+ENG] and Foreigner [ENG only]) may have felt
discomfort or anxiety due to a gap between the actual situation in Japan and theoverly urgent and sensationalist reports coming from overseas. In addition, as anuclear power plant along with a distinct lack of active publishing of specificinformation. Furthermore, these feelings of anxiety and so forth may have been

Disaster information collection by Thai and foreigners during the 2011 Thai flood― 172 ―

October 2012, Ulaanbaatar, Mongolia

exacerbated by the shortage of reliable English information from public
institutions. These reasons may have produced higher distrust of domestic
information sources (albeit the difference was small) and greater trust in overseas
information sources.
The major opinions of foreigners provided in the open response section as related
to information from domestic sources are summarized below.
a) Passive attitude of information disclosure to the public- A lack of proactive information provision based on the precautionary principle.
of smored radiation level ismillisievert
without any
analysis, evaluation, verification, or prediction, which forced people to makedecisions or take action based on less useful information- No information about the worst-case scenario and risks which might occur overthe medium- to long-term time period, such as response to radioactive
contamination, nor information about the expected radiation levels such as theprediction of short- to long-term dispersion considering weather conditions suchas wind direction- Analysis results should have been open and transparentb) Repetitious, meaningless and ambiguous information- Difficult to understand the actual meaning due to the high frequency ofambiguous expressions used by many Japanese to avoid being assertive, such as
we can t exclude the fact that
did not occur- No consistency in information or large amounts of contradictory information- Repeated broadcasting of the same images and information seen and given after
earthquake
plant crisis
management, but many opinions were received in the open response section of
hard to understand why the Japanese government entrusted the resolution of thenuclear problem to TEPCO, which is just a public company

safe without showing any scientific evidence about the radioactive contamination
impression to many foreigners that the Japanese government lacked theprecautionary principle, and that the government underestimated the situation due
to poor crisis management ability. In addition, foreigners were very concerned
whether the Japanese government and TEPCO were hiding information.

4.3 Reliance of foreigners skilled in Japanese on domestic Japanese
information sources
Contrary to other groups of foreigners based on language ability, Foreigner [JPN
only] mainly used Japanese media or, in some cases, their native language (except

New Technologies for Urban Safety of Mega Cities in Asia
― 173 ―

English) for collecting information, but they rarely used English (Fig. 3). There isa large(57%) versus overseas information sources (32%).
A similar level of reliance (based on percentage) could also be observed forJapanese [JPN+ENG]. The majority of Japanese [JPN+ENG] collected
information in Japanese, although there was some limited use of English. Even
when the amount of information collected from overseas information sources was
small, even if they were able to collect using both English and Japanese language,
it resulted in low trust in overseas information sources; this tendency was evengreater for Japanese [JPN only].
Foreigner [JPN only] appeared to collect some information in their native
language (excluding English), in which the urgency of crisis may have beendifferent from domestic broadcasts. Japanese [JPN+ENG] also collected overseas
information in limited manner. As both of these groups collected information in asimilar manner in Japanese, both Foreigner [JPN only] and Japanese [JPN+ENG]
also tended to trust similar information sources. However, Japanese [JPN only]
only collected domestic information, and as such their evaluation oftrustworthiness was biased towards domestic information sources.

REFERENCES
Kawasaki, A., Henry, M., Meguro, K., 2011. Disaster information gathering
behavior after the Tohoku Earthquake Part 1: Results of Japanese respondents.
2011 New Technologies for Urban Safety of Mega Cities in Asia (ICUS Report
2011-02), Chiang Mai, Thailand, 45-56.
Henry, M., Kawasaki, A., Meguro, K., 2011. Disaster information gathering
behavior after the Tohoku Earthquake Part 2: Results of foreign respondents. 2011
New Technologies for Urban Safety of Mega Cities in Asia (ICUS Report 201102), Chiang Mai, Thailand, 149-161.

Disaster information collection by Thai and foreigners during the 2011 Thai flood― 174 ―

Maria Bernadet Karina DEWI1, Sae SHIKITA2, Takaaki KATO3
1
Graduate Student, ICUS, IIS, The University of Tokyo, Japandewi@iis.u-tokyo.ac.jp
2
Undergraduate Student, ICUS, IIS, The University of Tokyo, Japansae.shikita@gmail.com
3
Associate Professor, ICUS, IIS, The University of Tokyo, Japankato-t@iis.u-tokyo.ac.jp
ABSTRACT
Hakozaki Peninsula, Kamaishi city, consists of eight villages, located alongside
the coastal area of Iwate Prefecture. During the 2011 Tohoku earthquake andtsunami, the casualties were 1,061 dead and missing, 2,954 completely destroyedhouses, and 687 partially destroyed houses. Currently, the population lives in
temporary houses in scattered locations. As other cities in the Tohoku affected
area, this city faces the very significant problem of a declining society, as well asother problems.
Kamaishi city
economic and governance systems areresources that should be considered with regard to reconstruction. Since the 2011
Tohoku earthquake the process of reconstruction with the involved stakeholders
the national government, municipalities, communities, NPOs, and others has beenongoing. This paper analyzes the current situation of the recovery, community
activities for reconstruction, and relation between these activities, then finding
problem between the process and involved stakeholders.
Keywords: reconstruction, Kamaishi city, Hakozaki Peninsula, community
participation, problems, solution.
1. BACKGROUNDKAMAISHI CITY BEFORE THE DISASTER

Kamaishi city is located in the southeastern part of Iwate Prefecture, along thecoastal line towards the Pacific Ocean, with total area of 441.43 square kilometers.
Kamaishi city was well known for its fishery and iron industry. In 1857, Nambu
Domain constructed the Ohashi blast furnace at Kamaishi as the first westernstyle blast furnace in Japan. In 1934, the Meiji Government established Nippon
Steel, the city population at that time reached 40,388. At the same time, roads
and railways were developed, and the role of Kamaishi Port became significant.

― 175 ―

0ctober 2010, Kobe, Japan

Figure 1: Changes in population and the number ofhouseholds in Kamaishi (Source: National Census)

Figure 2: Population pyramid ofKamaishi City in 2010
(Source: National Census)

Figure 1 shows the population trend in Kamaishi City, the densely inhabited
district (DID) population, and the number of households, with the data obtained
from the National Census. The population is estimated from 2010 until 2040.
From this graph, it can be assumed that population will greatly reduce in the
future. The decrease can be seen in the general population, as well as in theurbanized area. On the other hand, the declining household rate is smaller
compared to rate of population decline. Figure 2 explains how the population has
been subject to a declining birth rate with the majority of the population between
age of 55 and 79.
The situation of industry in Kamaishi City in 2007 was decreasing, with primaryindustry becoming 3.8%, secondary industry 33.3%, and tertiary industry 67.6%.
The number of employees had been declining about 30% from 1990 until 2010. In
particular, the decline of the primary industry was significant, having halved in 20
years. Agriculture has decreased about 65% among others. Though the number offish caught has not decreased much, the revenue of the fishery industry has been
declining, especially from 2000 until 2009.

2. CASUALTIES AND DAMAGE CAUSED BY THE GREAT EAST
JAPAN EARTHQUAKE AND TSUNAMI
Kamaishi City suffered great tsunamis in 1896, 1933, 1960 and most recently in
2011. With the highest tsunami wave reaching 10.1 m at Kamaishi harbor during
the Great East Japan Earthquake and Tsunami on March 11, 2011, Kamaishi City
suffered 885 fatalities, with 176 missing, 9,883 evacuees to other areas, and 633
evacuees inside the city (Kamaishi, 2011). The number of dead and missing in
Kamaishi City was the third largest in Iwate Prefecture, after Rikuzentakata andOtsuchi Town. The number of totally collapsed buildings is 2,954, with 396
highly destroyed, 291 partially destroyed, and 907 damaged.

3. CURRENT SITUATION

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Refugee location was completed by October 8th, 2011, and temporary housing wascompleted by August 5, 2011 with 3,164 relocated to 50 sites. An estimated 50%
of debris from the total amount of 762,000 tons was removed by April 2012 witha process of 3% (23,000t). Currently, the population is living in temporary
housing in scattered locations.

4. RECONSTRUCTION
4.1. AUTHORIZED RECONSTRUCTION PLAN BY THE GOVERNMENTIn September 2011, the Basic Policy for Reconstruction was enacted, which
initially consisted of a policy and Reconstruction Plan timetable. Then in
December 2011, the Basic Reconstruction Plan (Figure 3) was enacted. However,the detailed landscape plan and land use will be decided after consultation with
communities (Figure 4).

Figure 3: The ideal image of the city
as per the Basic Reconstruction Plan
(Source: Kamaishi, 2011)

Figure 4: Draft of land use plan for thecentral area
(Source: Kamaishi, 2012)

4.2. COMMUNITY PARTICIPATION
Sets of interviews were conducted regarding the settlement of Ryoishi and
Shirahama by the Crisis & Environmental Management Policy Institute (CeMI)
and Kato Takaaki Laboratory of ICUS, the University of Tokyo in order tounderstand the conditions and expectations of the communities in terms of thereconstruction process. The interviews were conducted with people who had
moved to temporary housing, in the reconstruction target area, especially those
who left the town right after the earthquake. To reverse the stem the decline is as
important as ensuring citizens to live in it. The basic reconstruction of Kamaishi
City was organized and meets the needs of stakeholders. However it was not
sufficiently transparent in assuring the opinion of representative organizations andcitizens, regarding the details of the residential area plan and disaster prevention
measures. Therefore, it should be a matter of policy
Reconstruction of Kamaishi City after the2011 Tohoku Earthquake and Tsunami― 177 ―

0ctober 2010, Kobe, Japan

plays a role in achieving stakeholders satisfaction.
Community participation across Hakozaki Peninsula is becoming more effective,
and the community bond between districts is becoming stronger. This movement
began in June 2011 with the combined involvement of four villages, mainly heldby finshermen in Ryoishi Village with support from Non-Profit Organization(NPO) CeMI. Community members and NPOs had been working together for thereconstruction process, including discussing the reconstruction plan. Then in
October 2011, events were held mainly by residence of Katagishi Village to raise. In March 2012, a new NPO wasestablished, named O-Hakozaki Shimin Kaigi (Community Association ofHakozaki Peninsula) consisting of community members and professionals. The
involved community is located across the following villages: Ryouishi,
Kuwanohama, Kariyado, Shirahama, Hakozaki, Nebama, Katagishi, andMurohama.
Starting in August 2012, O-Hako
are conducted via
four working groups. Working Group 1 manages community recovery for the
future, including physical, social, and human factors; Working Group 2 addresses
economic issues, creating job opportunities and new industries related to fishery;
Working Group 3 focuses on human capacity building such as disaster mitigation
and response; and Working Group 4 focuses on economic development, based on
the resources of this area, and product marketing and value addition.

5. DISCUSSION
Challenges and problems
During the reconstruction process, there have been several challenges for all
stakeholders. One positive note is that the community has been quite adaptable tothe scattered location of temporary housing and has formed a new community intheir new location.
Top-down planning strategies have been applied in this area from the very
beginning. Citizens trust the government to develop and implement thereconstruction plan. However, differentiation in the reconstruction division has
posed a challenge, since there is no sufficient cohesion between all of thedivisions. For example, reconstruction is mainly focused on the physical aspects
with some considering the other aspects such as social and economic. However,such interlinked functioning is needed to have a comprehensive approach to thereconstruction process, and to bridge the involved stakeholders. Possible solutions
are achievable through citizen participation.
The second challenge is that there has not been much chance for the community toparticipate and share their aspirations. The reconstruction plan management
planned to have consensus building with community, and a public hearing for theplan was held. The other difficulty is the community has a short-term view
regarding their economic, social, and built-environment situation, while the local

New Technologies for Urban Safety of Mega Cities in Asia
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government has a long-term view. In the area, fishermen and fisheries dominate
with local fishermen participating in a cooperative union aimed for their working
purpose. The profile of community in the area is fishermen and fisheries industry,
with their fishermen cooperative union which aimed for their working purpose.
Japan, now a developed , needs to adopt a different approach for reconstruction
than those that were implemented after prior disasters during the developing
period. The next challenge is overcoming the issue of the ageing population of
Kamaishi City, as well as the deteriorating economic condition. The majority ofcommunity leaders and most of the people are aged 70 years old. However, ayoung generation does exist in Shirahama to support the reconstruction process. In
addition, the community members who are elderly tend to stay in their previous
place and/or city, and do not want to move to other cities. The interviews resultthat the community has a strong attachment to the area. The future of the cities
lies in ensuring that safety and sustainability issues are addressed incomprehensive ways; how to attract the people to stay in this area also needs to betaken into account. Considering the formation of a compact, smaller town, is also
important to maintain the population and sustainability in the future.

6. CONCLUSION
Currently Kamaishi City and the other affected area in Japan are in the early phaseof reconstruction. Considering the past of Kamaishi City, and the present situationof the ageing society, Kamaishi City has several challenges to face during thereconstruction process, especially related to the developed state of Japan and thecurrently applied planning system, as well as in the character of the community toadapt to the new situation.
Further study is necessary to analyze the challenge of the reconstruction process,including finding influencing factors, considering the needs of citizens, andnsuring citizen involvement, and consensus between all stakeholders. Then,
analysis can be aimed to find possible suggestions to achieve a comprehensive
reconstruction process.

REFERENCES
Kamaishi City. 2011. Reconstruction Plan Kamaishi. Basic Town Plan. Iwate
Prefecture, Japan: Kamaishi City. Data obtained on December 22nd, 2011.
Kamaishi City. http://www.city.kamaishi.iwate.jp/index.cfm/8,0,76,425, html
Iwate Prefecture. 2012. Iwate Prefecture NPO activities.
http://www.pref.iwate.jp/~hp0301/npo-info/ninsho/sinseininshodantaiichiran/ichiran-10(451-500).htm. Data obtained on June 2012.
Website of Reconstruction from the Central Government
http://reconstruction.go.jp. Data obtained on June 2012.
Japan Non-Profit Organization . 2012.
nonprofitjapan.home.jgc.org/npo/mpojp.html. Data obtained on June 2012.

Reconstruction of Kamaishi City after the2011 Tohoku Earthquake and Tsunami― 179 ―

Yuto SHIOZAKI1 and Takaaki KATO2
PhD candidate, Department of Urban Engineering,
The University of Tokyo, Japanyuto@iis.u-tokyo.ac.jp
2
Associate Professor, ICUS, IIS, The University of Tokyo, Japan
1

ABSTRACTThe concepts of resilience, vulnerability, and adaptation are increasingly used in
the fields of global climate change, natural disasters, and ecological and social
systems. However, each of the concepts has different definitions. This paper
reviews the definitions of vulnerability, resilience, and adaptability, and showsthat the concepts can be categorized based on some attributes. First, there are
two major definitions for the concept of vulnerability: the exposure to hazards andthe degree of coping capacity. Most vulnerability concepts involve exposure,sensitivity, and adaptability. Criticality is also an important concept invulnerability. Second, the concept of resilience is classified into engineeringresilience, ecological resilience, and social resilience. Regime shift is also an
important concept in ecological resilience. Social resilience includes the aspectsof learning and adaptation in addition to engineering resilience and ecologicalresilience. Third, the concept of adaptation/adaptability is classified into thecontext of the target to be operated, the degree of system modification, as well as
the timing and duration. As a result, the concept is grouped into coping capacity,
adjustment capacity, and transformability. Finally, the linkages between the three
concepts are demonstrated using a scenario of a city exposed to a natural disaster.
Keywords: vulnerability, resilience, adaptation, catastrophic regime shift,
criticality, natural disaster

1. INTRODUCTION
In the recent years, the concepts of resilience, vulnerability, and adaptation
have been increasingly used in the context of global climate change, natural
disasters, and ecological and social systems. The perspectives of the three
concepts are used as approaches for understanding how and why a system
responds to hazards. These concepts have been applied to ecological systems,social systems, and socio-ecological systems (coupled human-environmental
systems). These concepts can form an interdisciplinary and comprehensive
framework. However, since no unified definition exists for these concepts, and theexisting definitions are different, the use of these terms may lead to confusion. In
Japan, especially after the Great East Japan Earthquake in 2011, these terms haveoften been used when discussing natural disaster management and reconstruction,― 180 ―

October 2012, Ulaanbaatar, Mongolia

but without clear definitions. As a result, the discussions in this field are subject toconfusion.
To prevent such confusion, this work first highlights the fundamental
definitions and components of the three concepts by reviewing relevant articles
and reports in the fields of global climate change, natural disasters, and ecologicaland social systems. These components represent the aspects of abehavior in response to hazards. Therefore, understanding them is considered to
be useful for establishing a framework for analyzing and managing a system.
Second, this article uses a scenario of a city responding to a rapid natural disasterto demonstrate the components. This example clarifies the linkage between thethree concepts and facilitates a discussion on the focal points of urban analysis
and management in preparation for natural disasters.
2. SYSTEM AND HAZARD
The concepts of resilience, vulnerability, and adaptation are used to represent
the manner in which a system responds to hazards. Hence, it is necessary to
clarify the definitions of system and hazard before the definitions and componentsof vulnerability, resilience, and adaptation are explained.
2.1 SystemAs, 2009). Systems focused upon in this work are
generally ecological systems, social systems, and socio-ecological systems. The
definitions of a system are listed in Table 1. For example, a lake or forest is an
ecological system, in which many animal and plant species interact with eachother. A community, city, or country are types of social systems. Examples ofsocial-ecological systems are a fishing village or an agricultural community, inwhich people are both dependent on and influence their surrounding ecologicalsystems. Any system is generally associated with subsystems and higher-ordersystems (e.g. a tree-patch-forest system or a household-community-city system).
2.2 Hazard
According to Turner et al. (2003),
comprising perturbation, stress (and stressors), and the consequences they produce.
A perturbation is a major spike in pressure beyond the normal range of variability
in which the system operates. Perturbations commonly originate beyond thesystem or location in question. Stress is a continuous or slowly increasingpressure, commonly within the range of normal variability. Stress often originates
In other words, there are two types of hazards: perturbation and stress. The
former is a rapid environmental change that occurs in the short term (e.g., a tidal
wave or hurricane), and the latter is a chronic environmental change that
influences a system over the long term (e.g., sea level rise, soil degradation). As aresult, hazards might cause damage to the system. In social systems, in addition toenvironmental change, political or social changes may also act as hazards, such aspolitical upheaval, war, and aging of the society.

New Technologies for Urban Safety of Mega Cities in Asia
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Table 1: Definitions of Systems
SystemEcologicalsystem(Ecosystem)

Definition
All the animals and plants in a particular area, and the way
in which they are related to each other and to theirenvironment (Longman, 2009).
The people in a society are considered as a system organizedSocial system
by a characteristic pattern of relationships (Miller, 1995).
A social-ecological system consists of a bio-geo-physicalSocialunit and its associated social actors and institutions. Socialecologicalecological systems are complex, adaptive, and delimited bysystemspatial or functional boundaries surrounding particular
ecosystems and their problem context (Glaser et al., 2008).
3. VULNERABILITY
3.1 Background of Vulnerability
ulnerability has been derived from the,sin the study of natural disasters (Janssen et al., 2006). It is considered to focus on
the relationship between a social system and its surrounding natural environment.
From the 1990s, research on natural disasters started to focus on the vulnerabilityof social systems to environmental change, and particularly, to climate change.
3.2 Definitions of Vulnerability
There are many different definitions of vulnerability, but Dow (1992) has
pointed out that there are two major definitions. In the first definition,
vulnerability is defined as exposure to the hazards of natural disasters andenvironmental changes. In the second definition, vulnerability is defined as thelack of coping capacity to hazards.
In the first definition, the vulnerability of a system can be measured by the
degree of potential or actual hazards that the system is exposed to. For example,
exposure is the degree of estimated or actual damage to humans, infrastructure,buildings, and other properties in the case of a natural disaster.
In the second definition, the exposure of a social system is a given condition,and the coping capacity, depending on the components or the condition of thesocial system, is assumed to affect the degree of damage caused to the system by ahazard. Coping capacity is considered to be composed of two types of social
system abilities. One is the ability to absorb the impact of hazards and continue tofunction, and the other is the ability to recover losses. Dow (1992) defines theformer ability as resistance, and the latter, as resilience.
Additionally, there is a combined definition that encompasses those describedabove, in which a social system with low coping capacity and high hazard
exposure is assumed to be the most vulnerable (Cutter, 1996).
According to Adger (2006), the concept of vulnerability is most often
conceptualized by three components: exposure, sensitivity, and adaptive capacity.

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October 2012, Ulaanbaatar, Mongolia

or socio-political stress.
which a system is modified
or affected by perturbations.
evolve in order to accommodate environmental hazards or policy change and to
expand the range of variability with which it can cope.
Gallopin (2006) defines the three components of vulnerability in a similarmanner: exposure, sensitivity, and capacity of response. His definitions of
exposure and sensitivity are the same as those of Adger (2006), and he defines theability to adjust to a disturbance, moderatecapacity of response as
potential damage, take advantage of opportunities, and cope with theconsequences of a transformation that occurs.
Turner et al. (2003) also defined exposure and sensitivity in a similar manner,
although they distinguish the capacity to cope/respond from the capacity ofadaptation, in their framework of vulnerability analysis. Capacity to cope/respondis the ability of a system to moderate potential damage immediately after anenvironmental change, and to influence the recovery situation of system. On theother hand, capacity of adaptation is the ability of a system to restructure itself
after the coping/response action is taken.
Finally, the concept of criticality is introduced, which is related to the conceptof vulnerability. Even if a system is exposed to a hazard, the system can cope to acertain degree because of its adaptability or capacity to cope/respond. However,the system is considered to be deteriorated in the case of the occurrence of ahazard whose magnitude is beyond the adaptability or the capacity of the system
to cope/respond. Kasperson et al. (1996) defined such a situation as criticality,
which refers to a situation in which the extent or rate of environmental
degradation precludes the continuation of the current system or levels of humanwell-being, given feasible adaptations and societal capabilities to respond.
4. RESILIENCE
4.1 Background of Resilience
The term resilience was originally used in the field of material science, where it
meant., 2007). It was
introduced by Holling (1973) as a concept for representing an
responses to environmental change. At first, resilience was used in the field of
population ecology and in the study of ecosystem management, and it wasmathematically based and model oriented. Since the late 1980s, the concept has
been used increasingly in the analysis of social-ecological interactions and applied
to human systems under the umbrella of social-ecological system studies. At
present, there are studies in which the concept is applied to only social systems,
focusing more on human society or communities than on ecological systems(Janssen et al., 2006; Wilson, 2011).
4.2 Definitions of Resilience
There are also many definitions of resilience; however, they can be grouped
under three general categories: (1) engineering resilience, (2) ecologicalresilience, and (3) social/community resilience (Holling, 1996; Adger 2000;

New Technologies for Urban Safety of Mega Cities in Asia
― 183 ―

Wilson, 2011). In this section, we first explain how a system responds to an
environmental change and then present the definition for each category.
Assuming that a system is in an equilibrium condition, the system may respondto environmental change in any of the following manners (De Bruijn, 2004):i) The system does not react at all.
ii) The system reacts but soon returns to the equilibrium condition.
iii) The system reacts and switches to another stable condition.
iv) The system enters an oscillating unstable condition.
In the first case, the system completely absorbs the impact of environmental
change. In the second case, assuming that a system is always dynamicallychanging, the system is not expected to completely return to the same condition,
but the system is expected to change within the domain, wherein its fundamental
structure of variables and processes that control system behavior are maintained,
and to return to an equilibrium condition. Such a domain is called the domain of
attraction of equilibrium. In the third and fourth cases, the system changes to sucha great extent that it cannot maintain its fundamental structure. In the third case, asa result, the system switches to another domain of attraction where thefundamental structure of the system is different. In the fourth case, the systemdoes not settle in any domain of attraction.
Engineering resilience is an important attribute in the second case, when asystem can return close to the initial equilibrium point after an environmental
change. Engineering resilience is defined as the ability of a system to return to theequilibrium situation after an environmental change (Holling, 1973). It can bemeasured by the time required for a system to return to the equilibrium situation.
Ecological resilience is defined as the ability of a system to persist despiteabsorbing changes in state variables, driving variables, and parameters (Holling,1973). In other words, it is the ability of a system to maintain its fundamental
structure while undergoing environmental change. Ecological resilience can bemeasured by the magnitude of environmental change that can be absorbed before
the system changes to another domain of attraction. In ecological systems, if asystem changes to another domain of attraction by environmental change, thesystem will restructure by changing the variables and processes that control its
behavior. This phenomenon is called regime shift (Scheffer & Carpenter, 2003).
For example, the abrupt change from a clear-water lake to an algae-dominatedlake occurs when the ratio of a nutrient reaches the threshold in the process ofeutrophication. Once a regime shift occurs in a system, it is difficult for thesystem to return to the previous domain of attraction. Understanding theconditions and processes of regime shift is required in order to maintain a system
in a desired state, and hence, the concept of ecological resilience is important forthe management of a system.
The concept of ecological resilience has been applied to the field of socialecological systems. The concept is expanded in this field, and it is described as (1)the amount of environmental change a system can absorb and still remain within
the same state, (2) the degree to which the system is capable of self-organization(versus lack of organization, or organization forced by external factors), and (3)the degree to which the system can build and increase the capacity for learningand adaption (Folke, 2006).

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October 2012, Ulaanbaatar, Mongolia

In the field of social systems, Adger (2000) focuses on the resilience of humansociety and communities, terming it social resilience. Cutter et al. (2008) definessocial resilience as the ability of a social system to respond and recover fromdisasters and includes those inherent conditions that allow the system to absorb
impacts and cope with an event, as well as post-event, adaptive processes thatfacilitate the ability of the social system to re-organize, change, and learn inthe attributes of engineering resilienceand ecological resilience. Additionally, the aspects of learning and adaptation ofsocial systems are more emphasized in social resilience.
5. ADAPTATION
5.1 Background of Adaptation
According to Smit and Wandel (2006), the term adaptation has its roots innatural science, and specifically, in evolutionary biology. The definition ofcharacteristics, which enable organisms or systems to cope with environmental
changes in order to survive and reproduce. The term adaptation is used in thecontext of anthropology, in which cultures or societies that can cope withenvironmental change quickly and easily are considered to have high adaptability.
Since the late 1990s, the concept of adaptation has been used in the study ofclimate change. The concept of adaptation/adaptability is usually included in theconcept of vulnerability and resilience.
5.2 Definition of Adaptation

system to adjust to climate change, to moderate potential damages, to take
Adaptation is defined by the Intergovernmental Panel on Climate Change (IPCC)
as follows: (it is the) adjustment in ecological, social, or economic systems in
response to actual or expected stimuli and their effects or impacts. This term
refers to changes in processes, practices, or structures to moderate or offset
potential damages or to take advantage of opportunities associated with changes
in climate. It involves adjustments to reduce the vulnerability of communities,., 2001).
Adaptability is synonymous with some terms such as adaptive capacity, coping
capacity (capacity to cope), and response capacity (capacity to respond).
Adaptation also has some synonyms: mitigation and adjustment. These
synonymous terms are used with the same definitions as adaptability or adaptation
in some cases, but they use different definitions in other cases. In the case ofdifferent definitions, the synonymous terms are often used to distinguish
adaptability or adaptation in the context of the target to be operated, the degree ofsystem modification, as well as the timing and duration.
In the context of the target to operate on, IPCC differentiates between
adaptation, by defining it as actions that operate upon the system itself,
mitigation, by defining it as actions that operate upon the origin and attributes ofthe environmental change (e.g., greenhouse gases reduction) (Gallopin, 2006).

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In the context of the degree of system modification, adjustment can be
distinguished from adaptation. Adjustment is the action of a system in response toenvironmental change that does not essentially alter the system itself, and it tends
to result in a short-term and minor system modification. On the other hand,
adaptation is the action of a system in response to environmental change that
fundamentally alters the system itself, and it shifts the system to a new state(Gallopin, 2006). The definition of adaptability and transformability by Walker etal. (2004) is considered to be related to this viewpoint. For them, adaptability is
the collective capacity of the human actors in the system to manage the sensitivity
and ecological resilience of system, given that the fundamental characteristics offundamentally
system are maintained. Transformability is
new system when ecological, economic, or social (including political) conditions
make the existing system untenable.
In the context of timing and duration, coping capacity can be distinguishedfrom adaptive capacity. Coping capacity is the relatively short-term ability of asystem to survive crises, whereas adaptive capacity is the ability of a system toachieve more sustainable and relatively long-term adjustment (Smit & Wandel,2006). Gallopin (2006) indicates that there are generally two types of components
in the concept of adaptive capawith environmental contingencies (to be able to maintain or even improve its
condition in the face of changes in its environment(s)). This is assumed to be a
relatively short-time ability and to be manifested immediately after ancapacity to extend the range ofenvironmental change.
environments to which it can adapt. This is assumed to be a long-term ability andis expected to manifest before an environmental change or after the first one
occurs.
As described above, this article classifies the concepts of adaptation into threegroups: (1) coping capacity, (2) adjustment, and (3) transformability. (1) Coping
capacity is the relatively short-time ability of a system to survive a crisis and copewith contingencies during or immediately after environmental change. This is theability of a system to prevent the existing fundamental structure from collapsingin an emergency situation. It is also related to resistance and resilience, which
Dow (1992) defined, and to engineering resilience. (2) Adjustment is therelatively long-term ability to modify a system, while its fundamental structure ismaintained, in preparation for expected environmental changes or after an actual
environmental change. The adjustment after an actual environmental change canbe also called learning. Adjustment includes the ability to extend coping capacity,
described as (1). (3) Transformability is the ability to create a fundamentally new
system when the existing system is untenable (in the case of a regime shift or
criticality).
6. LINKAGE OF THE THREE CONCEPTS
The definitions and components of vulnerability, resilience, and adaptation
have been explained. Now, the linkages between the concepts and components are
discussed for a city exposed to a rapidly occurring natural disaster.

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October 2012, Ulaanbaatar, Mongolia

Figure 1: Relationship between the magnitude of a hazard and the degree ofdamageFigure 2: Engineering resilience and ecological resilience
Figure 1 conceptually represents the relationship between the magnitude of ahazard and the degree of damage to a system. The horizontal axis indicates themagnitude of a hazard to which the system is potentially exposed (exposure). The
magnitude of the hazard gradually increases towards the right, although it isgenerally thought that a larger magnitude hazard tends to occur with lower
probability. The vertical axis indicates the degree of damage that the system
undergoes because of the hazard. The function of figure 1 is to indicate the extent
to which a system may be damaged if it is subjected to hazards of various
magnitudes (Mens et al., 2011).
As the figure shows, the system undergoes no damage up to a certain degree of
hazard. For example, assuming that a city is protected against floods by dikes, thecity would suffer no damage from small-scale flooding as the dikes can cope withfloods to a certain degree. The system starts to undergo damage at a certain
magnitude of hazard. In figure 1, the trajectory of the function shown can be
discontinuous, and the gradient of the trajectory may not constant, although it is acontinually increasing function. This function corresponds to sensitivity, which is
a component of vulnerability. The higher the resistance of a system is, the more
gradual the trajectory of the function becomes. In this context, sensitivity is related
to resistance.
Assuming that there is a threshold point of regime shift/criticality, the system
can maintain the existing fundamental structure, provided the degree of damage
does not reach the threshold. In this case, the system can recover or regenerate

New Technologies for Urban Safety of Mega Cities in Asia
― 187 ―

from the damage without losing its structure. The time taken for recovery is theengineering resilience or resilience, which Dow (1992) has defined (see figure2.a). After the process of recovery, adjustment may be used in preparation for the
next hazard. Adjustment can also be used before an anticipated hazard. This abilityof a system is assumed to improve sensitivity, engineering resilience, andecological resilience.
Conversely, a system cannot continue and recover if the degree of damage isbeyond the threshold. In this case, the system loses its structure and cannot
continue to persist. The maximum degree of damage that the system canwithstand without resulting in a regime shift or criticality is ecological resilience(see figure 2.b). The system enters an untenable situation if a regime shift or
criticality occur. In such a case, the system requires to fundamentally modify itself
to create a new system. This ability corresponds to transformability.
7. CONCLUSION
The concepts of vulnerability, resilience, and adaptability have originated indifferent fields. However, these concepts have been applied to ecological systems,social-ecological systems, and social systems, and linked with each other. All
these concepts are used as approaches for understanding how and why a system
responds to environmental change and for managing the system in an appropriate
and efficient manner.
Each of the concepts can be divided into some components. There are two
major definitions of the concept of vulnerability, while the concept is generallycomposed of exposure, sensitivity, and adaptability. A system can collapse if themagnitude of a hazard exceeds the adaptability of the system. This situation iscalled criticality. Further, the concept of resilience is classified into engineeringresilience, ecological resilience, and social/community resilience. Engineeringresilience is the speed of system recovery when the system returns to equilibrium
conditions. Ecological resilience is the ability of a system to maintain its existing
fundamental structure while undergoing environmental change. Regime shift isalso an important concept in ecological resilience, and it is similar to criticality.
Social resilience includes the aspects of learning and adaptation in addition toengineering resilience and ecological resilience. Finally, the concept ofadaptation/adaptability is classified based on the target to operate on, the degreeof system modification, and the timing and duration. As a result, the concept isdivided into three groups: coping capacity, adjustment capacity, andtransformability. Finally, the linkages between the three concepts are discussed in
the case of a city exposed to a rapid natural disaster.
REFERENCES
Adger, N., 2006. Vulnerability. Global Environmental Change, vol. 16, pp. 268281.
Adger, N., 2000. Social and ecological resilience: are they related? Progress in
Human Geography, 24[3], pp. 347-364.
Cutter, S. et al., 2008. A place-based model for understanding community
resilience to natural disasters. Global Environmental Change, vol. 18, pp. 598-606.

Review on the Definitions of Vulnerability, Resilience and Adaptation― 188 ―

October 2012, Ulaanbaatar, Mongolia

Cutter, S. L., 1996. Vulnerability to environmental hazards. Progress in Human
Geography, 20[4], pp. 529-539.
de Bruijn, K. M., 2004. Resilience and flood risk management. Water Policy, vol.
6, pp. 53-66.
de Bruijn, K. M., Green, C., Johnson, C. McFadden, L., 2007. Evolving Concepts
in Flood Risk Management: Searching for a Common Language. In: S. Begum, M.
J. Stive J. W. Hall (Eds.), Flood Risk Management in Europe. Dordrecht: Springer,
pp. 61 75.
Dow, K., 1992. Exploring differences in our common future(s): The meaning ofvulnerability to global environmental change. Geoforum, 23[3], pp. 417-436.
Folke, C., 2006. Resilience: the emergence of a perspective for social-ecologicalsystem analyses. Global Environmental Change, 16[3], pp. 253-267.
Gallopín, G., 2006. Linkages between vulnerability, resilience, and adaptive
capacity. Global Environmental Change, vol. 16, pp. 293-303.
Glaser, M. et al., 2008. Human/nature interaction in the Anthropocene: Potentialof social system analysis. GAIA, 17[1], pp. 77-80.
Holling, C. S., 1973. Resilience and stability of ecological system. Annu. Rev.
Ecol. Syst., vol. 4, pp. 1-23.
Holling, C. S., 1996. Engineering Resilience versus Ecological Resilience. In: P.
C. Schulze (Eds.), Engineering Within Ecological Constraints. Washington DC:
The National Academy of Sciences, pp. 31-43.
Janssen, M., Schoon, M., Ke, W. Börner, K., 2006. Scholarly networks onresilience, vulnerability and adaptation within the human dimensions of global
environmental change. Global Environmental Change, vol. 16, pp. 240-252.
Kasperson, J. X., Kasperson, R. E., Turner II, B. L., 1996. Regions at risk:
Exploring environmental criticality. Environment, 38[10], pp. 4-15, 26-29.
Longman, P., 2009. Longman Dictionary of Contemporary English. 5th edition.
Harlow: Longman ESL.
McCarthy, J. J. et al. (Eds.), 2001. Climate Change 2001: Impacts, Adaptation,
Vulnerability. Cambridge University Press, Cambridge, UK.
Mens, M. J., Klijn, F., de Bruijn, K. M. van Beek, E., 2011. The meaning ofsystem robustness for flood risk management. Environmental Science & Policy,
vol. 14, pp. 1121-1131.
Miller, G. A., 1995. WordNet: A lexical database for English. Communications of
the ACM, 38[11], pp. 39-41.
Smit, B., Wandel, J., 2006. Adaptation, adaptive capacity and vulnerability.
Global Environmental Change, 16[3], pp. 282-292.
Scheffer, M., Carpenter, S. R., 2003. Catastrophic regime shifts in ecosystems:
linking theory to observation. TRENDS in Ecology and Evolution, 18[12], pp.
648-656.
Turner II, B. L. et al., 2003. A framework for vulnerability analysis insustainability science. Proceedings of the National Academy of Sciences of theUnited States of America, 100[14], pp. 8074-8079.
Walker, B. et al., 2004. Resilience, adaptability and transformability in socialecological systems. Ecology and Society, 9[2], art. 5 [online], URL:
http://www.ecologyandsociety.org/vol9/iss2/art5/
Wilson, G., 2011. Community Resilience and Environmental Transitions. 1stedition. New York: Routledge.

New Technologies for Urban Safety of Mega Cities in Asia
― 189 ―Î»´¿¬·±² ¾»¬©»»² «®¾¿²·¦¿¬·±² ¿²¼ ²¿¬«®¿´¼·­¿­¬»® ®·­µ ·² ³»¹¿ ½·¬·»­ó Ô»­­±²­ º®±³ Ì±µ§± ó
Takaaki KATO
Associate Professor, ICUS, IIS, the University of Tokyo, Japankato-t@iis.u-tokyo.ac.jp

ABSTRACTAt present, the Tokyo metropolitan region has two kinds of natural mega hazards:
M.7 class inner-plate earthquakes and large-scale floods. The Central Disaster
Prevention Council, which is the supreme organization of disaster affairs inJapan, has warned about both in published reports. It stated that Tokyo hasenormous exposed risks, and tremendous amounts of damage were estimated in
the disasters. The present natural hazard risk in Tokyo is closely related to theprocess of urbanization in the city. As for earthquake disasters, Tokyo has broadwooden crowded areas that are vulnerable to the spread of post-disaster urban
fires. The risk has accumulated in two periods of rapid urbanization. The reason
primarily lies with urban planning, which does not include the concept of natural
hazard risk management—that is to say, urban planning yields to the highpressure of urbanization. This problem has been the main issue with urban
earthquake disaster planning in Tokyo for the last four decades. On the other
hand, the risk of large-scale floods is not apparent at present. Tokyo has notexperienced a large-scale flood for the last century thanks to river management;
however, the risk will surely grow in response to climate change. Tokyo has what
is called a “below-sea-level city,” which is hugely vulnerable. I can point to two
failures that account for why it has been generated: urban planning and hazard
control. These cases show that urban planning is significant in natural hazard
risk management. In this study, I show the structure of natural hazard risk inmega cities and discuss the role of urban planning in risk management, as well as
present necessary countermeasures to consider in urban planning.
Keywords: urbanization, natural disasters, urban vulnerability

1. MEGA-HAZARD IN TOKYOTokyo has two kinds of mega hazards: earthquakes and large-scale floods
corresponding to climate change. The earthquake probability in the next thirty
years is estimated at 70% by the government. On the other hand, large-scale
floods present only a small risk at present, thanks to flood control by rivermanagement, but the risk will surely increase in response to forthcoming climatechange. A few decades from now, it will be a serious problem.

― 190 ―

October 2012, Ulaanbaatar, Mongolia

1.1. Earthquake Hazard
In Japan, earthquake damage estimation is a common feature of amunicipality’s disaster prevention plan and includes the latest damage estimationby the Tokyo metropolitan government. In this estimation, four earthquakes are
assumed as an earthquake scenario. The damage situation is influenced by time
and weather conditions; for example, they may be assumed as occurring at 18:00
in winter under a wind velocity of 8m/s. Figure 1 shows the results of groundshaking for a Northern Tokyo Bay earthquake scenario, which creates maximum
damage. Maximum intensity will be JMA Seismic Intensity upper 6, which is thelevel at which tremendous damage occurs. The area of intensity upper 6, coloredorange in the figure, covers 70% of the entire ward districts where urban stock isconcentrated. Most of the area covers the eastern region of Tokyo, in which thepossibility of liquefaction is also greater. We understand that the cause for this isthat the ground structure in the east area of Tokyo is relatively weak.
Ground shaking and liquefaction cause buildings to collapse. The spatial
distribution of building damage is shown in figure 2 and is concentrated in east
Tokyo. Two reasons for this are the high seismic intensity and the possibility ofliquefaction. Another reason is the unplanned accumulation of many crowded oldwooden houses in the highly dense area. Vulnerability to building damage is seen
in structures in which the buildings were constructed on weak ground.
Moreover, post-earthquake urban fire spread might occur in a mega-city.
The firefighting power in Tokyo is adequate; however, the number of fires thatbreak out after an earthquake is estimated to be much greater than the available
firefighting power, resulting in an enormous amount of fire damage. Burnt areasin Tokyo are estimated to total approximately 100 square kilometers. For
reference, the 1995 Hanshin-Awaji earthquake disaster resulted in some amountof damage being caused by post-earthquake urban fire spreading; however, it wasapproximately 65 ha, which was much less than the estimated amount of damagein Tokyo. Figure 3 shows pictures of the current situation of the typical vulnerable
districts to post-earthquake urban fire. Large numbers of flammable houses werebuilt and spread with narrow roads across wide-ranging areas. The spatial
distribution of fire damage is different from collapsed buildings. It distributes in adoughnut-shaped pattern, centering on CBD of Tokyo.
The history of urbanization in Tokyo shows that it has had two periods ofrapid urbanization. The first is a recovery period that occurred after the Kanto
earthquake disaster in 1923. Many fires broke out after the earthquake, and due tostrong winds, the fires spread, burning down most of the urbanized areas in Tokyoand Yokohama. A lot of people lost their houses, and an absolute shortage ofhouses occurred. To supply temporary residences for the large number of
evacuees became a priority issue. At the same time, the government had toreconstruct the central district of Tokyo and therefore could not afford to plan andconstruct urban infrastructure. As a result, the fringe of the central district, which
had been farmland, had been urbanized by huge numbers of poor-quality houses.
The second period was a high economic growth period that began in theearly 1960s, after World War II. In the war, Tokyo was burned down again bybomb attacks. The situation was similar to the 1923 Kanto earthquake disaster.
Tokyo had suffered from a lack of housing. Furthermore, Japan entered into ahigh economic growth period after the Korean War in the early 1950’s Tokyo’s
economic growth promoted immigrants from across the country to flock to Tokyo.
New Technologies for Urban Safety of Mega Cities in Asia
― 191 ―

The situation caused the housing shortage to worsen. Tokyo had to continue toprovide temporary housing for residents for a long time. In the same manner as
the 1923 Kanto earthquake disaster, numerous poor-quality houses began
accumulating in the absence of urban planning.
The areas formed in these periods are nearly equal to the current
vulnerable areas, as shown in Figure 4; therefore, we can say that Tokyo failed tocontrol vulnerability in the periods of rapid urbanization. There are two reasonsfor this failure. The first is that, at the time, urban planning commissions had little
knowledge about how to control for disaster risks because economic growth hadtaken priority.
The second is that the speed of urbanization was so high that there was notime or ability to make urban plans and construct urban infrastructures. As a result,urban planning for disaster mitigation adopted a style that assumed it would
always be able to keep pace with problems as they occurred. Up until now, as I
mentioned, the problems have not yet been solved. It takes a long time to solve
past urban problems.
A lesson learned from Tokyo is that it is important to prevent problems before
they occur or to mitigate problems when they occur. Japan should have had longrange plans and should have incorporated the concept of risk management into
urban planning in a period of rapid urbanization.

Figure 1 Spatial distribution of ground shaking and the possibility of liquefactionin Tokyo in an earthquake scenario (TMG, 2012)

Relation between urbanization and natural hazard in mega cities –Lessons from Tokyo― 192 ―October 2012, Ulaanbaatar, Mongolia

Figure 2 Spatial distribution of collapsed buildings in Tokyo (TMG, 2012)

Figure 2 Spatial distribution of post-earthquake urban fire spreading in Tokyo(TMG, 2012) and in urbanization areas in two rapid urbanization periods.

1.2. Large-Scale Floods
Tokyo has below-sea-level areas in the eastern area, as shown in Figure 4.
The pink area in the figure is under sea level. The deep pink shows the area under
the low tidal level. This area has an accumulation of low-rise buildings andapproximately two million people live in the area. Tokyo is obviously very
vulnerable to flooding. Figure 5 is a zoom shot of the area. It has many black or
red buildings, which are estimated to be under water in case of flooding. In the
picture on the right, the red arrows show the water level in the event of a flood. It
can be understood that the water level will reach very high levels if a flood occurs.

New Technologies for Urban Safety of Mega Cities in Asia
― 193 ―

Figure 4 Ground level in Tokyo and a picture of a typical area in Tokyo

Figure 5 Inundation of below-sea-level city in case of flood, focusing on buildings
At present, the municipality has a legal obligation to publish a hazard map.
A hazard map of Katsushika city, which is located in the east area of the Tokyo
metropolitan area, shows that there is no evacuation space in the neighborhood
because the entire city area will be inundated in the event of a flood.
Approximately 300,000 people should evacuate to another city located more than
10km from their hometowns. Mass transit such as buses and railways is theplanned means of transportation. It is nearly impossible for huge numbers ofcitizens to evacuate because of the capacity limitation of transportation. Moreover,even if evacuation is successful, they will have to remain in the evacuation area
for a long period of time; estimations suggest they will remain in the evacuation
area for more than 20 days after the bank is repaired. The current situation meansthat the city fundamentally has no acceptable solution for a below-sea-level city.
Failure to control large-scale flooding is the result of two past failures
related to industrialization and urbanization. One is ground subsidence
corresponding to industrialization. The graph in Figure 6 shows a history ofground subsidence. Subsidence continued until thirty years ago, when regulations
were established to forbid ground water pumping. Regulations came too late,however. The maximum length of subsidence is about 5 meters on the report, but
it may actually be longer. The second reason for failure is urbanization. Figure 7

Relation between urbanization and natural hazard in mega cities –Lessons from Tokyo― 194 ―October 2012, Ulaanbaatar, Mongolia

shows maps from 100 years ago to the present. The current urbanized area was arural zone until only sixty years ago. It is already a recognized ground subsidence
in this region. In spite of this situation, urbanization in the form of low-rise houses
had expanded into the area under sea level for these sixty years. If urban planningin those days had included the concept of risk management for flooding, or if
urban planning had prevented urbanization in the areas, or if urban planning had
built up the area with high-rise buildings, the present risk would likely bedramatically smaller. We can say that failures of hazard control and urban
planning created a “below-sea-level city.” The reasons for a large-scale flood risk
are basically the same as for an earthquake.

Figure 6 Historical record of ground subsidence in Tokyo (TMG)

Figure 7 Urbanization in a typical area of Katsushika city over the past 100 years

2. STRUCTURE OF DISASTER RISK
It is understood that the current risk in Tokyo is related to past urbanization. I
consider the structure of disaster risk in a mega city. Natural disaster risk can
primarily be explained by four factors, as shown in Figure 8: hazard control, acity’s location, accumulation, and vulnerability.
Hazard existence is the fundamental factor. Japan must consider earthquakes
and floods as hazards.

New Technologies for Urban Safety of Mega Cities in Asia
― 195 ―

The first risk factor is hazard control, such as construction of a river dike inthe event of flooding, but it obviously has limitations. Hazard control forearthquake hazards is inherently impossible, although control for large-scale
floods has proved valid. In fact, large-scale floods have occurred for over the past
fifty years; however, climate change will wreak limitations. The amount of riskthat hazard control cannot cover is pushed to urbanized areas.
Risk in urbanized areas can be explained by three factors: location,
accumulation, and vulnerability. The second risk factor is the location of theurbanized area. If an urbanized area overlaps the spatial distribution of the hazard,
it produces a risk. The typical cases involve urbanized areas that are located inflood-prone areas and in weak ground that produces earthquake shaking, aspreviously mentioned. Expansion of urbanization should be controlled by urban
planning.
The third risk factor is accumulation of urban stock, such as building facilities
and lifelines. If accumulation is small, the entire amount of damage will
necessarily be small. If the entire amount of damage is small, it is easy to rescue
the afflicted area and support its recovery. However, accumulation is one of thefundamental and unique characteristics of mega cities; therefore, it is appropriate
to consider that it is uncontrollable. In addition, the functions of urban planninginclude density control of urbanized areas; therefore, controlling accumulation
would be possible.
The term, “exposure risk,” which is generally used to explain the process, isconsidered to be equivalent to location multiplied by accumulation.
The forth and most important risk factor is vulnerability—in other words, thequality of the urbanized area from the viewpoint of disaster risk. Vulnerability canbe explained by balancing two factors: physical fragility, such as building fragility
and lifeline fragility; and the resilience and response abilities of society, such as
the firefighting and evacuation abilities of local communities. For example, an old
town is generally fragile, but if young people work and live there, their resilienceand response abilities are high; therefore, we can say that the town may be notvulnerable. In contrast, if old people, who are vulnerable in terms of physicalstrength, live in modern buildings, such as high-rise apartments, they will sufferfrom even slight outages of lifelines. Moreover, the resilience and response
abilities of society are supported by two factors: physical factors, such as
evacuation areas, roads, and firefighting facilities; and social systems, such as
evacuation planning and community-based education. Recent urban planningincludes community-based improvements, management, and activities for the
future, which are called achidukuri in Japanese. It deals with all of theabovementioned sub-factors. Urban planning can control vulnerability.
I consider these four factors basically as explanatory parameters of mega risk
in a mega city. All of the factors, except hazard control, are parameters that can becontrolled by urban planning; therefore, I can say that the present actual disastermega risk is capable of being solved in theory by urban planning. Therefore, weshould consider future urban planning by focusing on this viewpoint over the next
decades. At the same time, we should pay attention to the current balance of thesefactors and the monitoring system of disaster risk that will be needed in planning.

Relation between urbanization and natural hazard in mega cities –Lessons from Tokyo― 196 ―October 2012, Ulaanbaatar, Mongolia

Figure 8 Structure of Natural Disaster Risks

3. CONCLUSION AND DISCUSSION
The important lessons learned from Tokyo are that rapid urbanization without
urban planning would itself result in disaster risk, which means that disaster risk isclosely related to urbanization. More attention should be paid to the rapid
urbanization period. Whether urban planning includes the concept of risk
management or not at this time will determine future disaster risks. In the case ofa city having no concept of risk management, the city will have a huge amount of
risk. Long-range plans are needed to consider this fact.
The structure of natural disaster risk can be constructed with four main
keywords: hazard control, a city’s location, accumulation, and vulnerabilities,
including physical fragility and the resilience and response activities of local
communities. All keywords, except hazard control, can be controlled by urban
planning. The role of urban planning is significant in disaster risk management.
Developing cities, including Ulaanbaatar, are presently facing rapid
urbanization. Present urban planning may be readjusted if based on the above
context. However, urban planning should inherently be comprehensive; disasterrisk management is also an important issue that urban planning should consider.
Better direction should be pursued in balance with other urban planning issues.

REFERENCES
Tokyo Metropolitan government. 2012. Report on earthquake damage estimation.
Tokyo Metropolitan government, Japan.
Cabinet Office. 2005. Report on Tokyo inner-plate earthquake damage estimation,
Japan.

New Technologies for Urban Safety of Mega Cities in Asia
― 197 ―

Development of a Web-based Trend Analysis System
of Earthquake Disaster Researches Presented at the Past
World Conferences on Earthquake Engineering
Shinya Kondo

Project Researcher, International Center for Urban Safety Engineering,
Institute of Industrial Science, The University of Tokyo, Japan

Kimiro Meguro

Professor, Director of International Center for Urban Safety Engineering,
Institute of Industrial Science, The University of Tokyo, JapanSUMMARY:
In this study, the authors propose a web-based system aiming to analyse trends of past disaster researches. In
particular, the authors plan to build “research paper database” and a “collection of keywords.” The research
paper database will consist of contents of research papers published in the Proceedings of the past World
Conferences on Earthquake Engineering (WCEEs) with information regarding the authors. Each keyword in thecollection of keywords will describe the research field on disaster and has set indexes such as “type of disaster,”“type of countermeasures,” and “type of object of damage.” The disaster list will consist of disaster happened in
the past and in the future. Furthermore, the proposed system has three functions and a full-text search of a
research paper database: “trend analysis of disaster research,” “impact analysis of disaster,” and “search for
related research.”
Keywords: trend analysis, web-based system, the World Conference on Earthquake Engineering

1. INTRODUCTION
In our world, many disasters (earthquake, volcanic disaster, flood, etc.) occurred and cause extensive
damage. Till date, many researchers from various academic fields have studied disaster and disastercountermeasures, aiming to decrease negative impact due to disasters.
Disaster research has wide fields from pure to practical sciences, and structural and non-structural
measures. Researchers tend to make presentations on their research results at the conferences andmeetings that their primary academic societies hold. Therefore, even if there are many useful researchoutcomes for disaster management, it is very difficult to overlook them from bird-eye as the number ofsocieties is many and they are divided into many small fields. There is a need to establish anenvironment to overlook all related researches from bird-eye and share them.
In recent years, the service for research result searching and sharing has been developed in various
fields and it becomes possible to check and get necessary information from libraries by remote.
Google has opened a service of Google Scholar and it provides a simple way to broadly search foracademic literature. From the Google Scholar, users can search across many sources in different fields:
articles, papers and reports, books, abstracts and opinions, from academic publishers, professionalsocieties, online repositories, universities and other web sites. Thomson Reuters is offering Web of
Science. This service, which provides users with a search function with high speed citations and caneasily identify author information can be easily identified, has been utilized researchers, administrators,
university faculty, and students. And this service can be subject to important publications andinfluential journals more than 11,600 around the world dating back to 1900, to analyze the citation
pattern to perform a search across the fields.
As above mentioned, general environment that can share the results of individual studies has been
established. However, in order to use efficiently disaster research results for disaster management― 198 ―

around the world, we should grasp an overall picture and characteristic of disaster related researches.
In this study, as the first step of the research, the authors propose a web-based system aiming tounderstand an overall picture of earthquake disaster researches. This system has a function to analysetrends of past researches from the various viewpoints of disaster management. Furthermore, users cangrasp the impact on the study of disasters, and it becomes possible to search related researches. In thispaper, the authors try to build a prototype of proposed system using the research papers published in
the proceedings of all the past World Conferences on Earthquake Engineering (WCEEs), and someresults of analysis are introduced.
2. BUILDING DATABASE FOR PROPOSED SYSTEM
2.1. Research Paper Database
In order to make full-text search and mining of research papers and reports possible, we haveestablished a research paper database using research papers published in the proceedings of all the past
WCEEs. These papers are obtained from the website which National Information Centre ofEarthquake Engineering (2009) has opened. Table 2.1 shows the number of research papers publishedin the proceedings of each conference. Each research paper is saved as a PDF file, and text data wereextracted using “Adobe Acrobat 9.0” as OCR software.
Table 2.1. The Number of Research Papers Published in the Proceedings of the Past WCEEs
Conference
1st, United States, 1956
2nd, Japan, 1960
3rd, NewZealand, 1965
4th, Chile, 1969
5th, Italy, 1974
6th, India, 1977
7th, Turkey, 1980
8th, United States, 1984
9th, Japan, 1988
10th, Spain, 1992
11th, Mexico, 1996
12th, New Zealand, 2000
13th, Canada, 2004
14th, China, 2008

Number of papers
42
134
165
167
452
669
743
845
1004
1191
1437
1519
2341
3008

2.2. Collection of Keywords
In this section, the collection of appropriate keywords from disaster management viewpoints set inadvance is described. Keywords are selected based on disaster prevention glossary in Japan and addedfrom the proceedings of the disaster-related academic societies in Japan. Furthermore, the opinions ofresearchers in disaster fields are reflected to the collection of keywords. Keyword that is difficult torecognize the meaning in terms of disaster management in a single word, such as "rock", "water","stress", etc. are removed. And keyword such as "disaster management" that has a broad concept andis difficult to classify research fields are excluded. Finally, the total number of keywords is 1,392.
To each keyword, indexes, such as "type of disaster," "type of countermeasures," and "type of objectof damage" are set as shown in Table 2.2. "Type of disaster" means a kind of hazards, such as
earthquake, volcano, flood, etc. that may become cause of damage and disaster (Table 2.3). "Type ofmeasures" is a classification based on the concept of disaster life cycle (Meguro and Murao, 2008) asshown in Table 2.4. "Type of object of damage" means the target of disaster countermeasures andobject of damage (Table 2.5).
― 199 ―

Table 2.2. Example of indexes setting
Keywords

DisasterCountermeasures

Tsunami warning

Earthquake(Tsunami)

Disaster prediction
and warning

Disaster prevention
learning

Preparation

Dangerous area ofslope failure

Mitigation

Disaster effects

Natural slope (Landslide)

Table 2.3. The number of keywords set with the indexes “Type of Disaster”
Number of keywords
Index nameVolcanic disasters
Storm and flood
Earthquake
Large scale fire
Man-made disaster
International disaster relief
Others

58
167
307
126
10
10
8

Table 2.4. The number of keywords set with the indexes “Type of Countermeasures”
Index name
Number of Keywords

Hazard mechanism
Damage mechanism
Mitigation
Preparedness
Prediction and early warning

288
313
153
105
27

Damage assessment
Emergency disaster response

49
72

RecoveryReconstruction

36
48

Information and communication

26

Table 2.5. The number of keywords set with the indexes “Type of object of damage”
Number of keywords
Index nameNatural slope (Landslide)
33
Earth structure （Embankment）
16
Ground deformation (Liquefaction)
10
Debris flow
13
Structure damage (Civil infrastructure)
55
Structure damage (Building)
53
Structure damage (Others)
3
Fire spread
12Lifeline and system
21
Transportation (road, railway, harbor)
12
Human loss
13
Affected people (refugees)
24
Industrial damage (Business interruption)
11― 200 ―

3. DISTRIBUTION OF FIELD OF RESEARCH PAPERS
In this chapter, the distribution of research papers is calculated. The full-text search of the research
paper database extracts keywords which consist of the collections of keywords. In this study, MeCab(Kyoto University and NTT communications) is used for full-text search. MeCab is the software formorphological analysis of Japanese text.
One research paper has been allocated to the research field based on the number of appearance of the
keyword. In this study, this value is defined as the hitting ratio (Eqn. 3.1). Research fields arecomposed by items in two indexes. Two indexes (index “a” and index “b”) are selected from “type ofdisaster,” “type of countermeasures,” and “type of object of damage.”

 m
i

j

i , j ,l

 1ゎ

(3.1)

(mi , j ,l : Hitting ratio in item " i" (index " a" ) and item " j" (index " b" ) of paper " l" )Hitting ratio of the research paper is expressed as a product of the value of item "i" of index "a" anditem "j" of index "b". This value is the number of appearance of the keyword divided by the total
number of keywords (Eqn. 3.2).

mi , j ,l 

xi ,l

x

i ,l



y j ,l

y

j ,l

(3.2)

The number of appearance of keywords (index " a" , item " i" )xi The total number of keywords (index " a" , item " i" )The number of occurrences of keywords (index " b" , item " j" )yj The total number of keywords (index " b" , item " j" )The sum of hitting ratio of the research paper in a proceedings is the number of research papers
considering hitting ratio in a proceedings (Eqn. 3.3).
N ab

M i , j   mi , j ,l ゎ

(3.3)

l 1

( M i , j : The number of research papers considering hitting ratio in a proceedings in item " i" (index " a" )and item " j" (index " b" ))( N ab : The number of research papers having keywords(index " a" and index " b" ))The number of research papers considering hitting ratio in a proceedings divided by the number of
research papers with keywords (index "a" and index "b") is the hitting ratio of a proceedings (Eqn.
3.4).

Pi , j  M i , j / N ab ゎ
( Pi , j : Hitting ratio of a proceedings in item " i" (index " a" ) and item " j" (index " b" ))(3.4)

4. OUTLINE OF FUNCTIONS
The proposed system has three functions to analyse trends of past researches from the viewpoint ofdisaster management: “trend analysis of disaster research,” “impact analysis of disaster,” and “search
for related research.”― 201 ―

4.1. Trend Analysis of Disaster Research
Using the function “trend analysis of disaster research,” users can see the hitting ratio of researches
published in a proceedings. Figure 4.1 shows a distribution diagram of the hitting ratio of aproceedings. X-axis is set index "a", and Y-axis is set index "b". In this figure, the hitting ratio (%) ofa proceedings in item "i" (index "a") and item "j" (index "b") is described at the respective area
composed of item "i" and item "j". Area of the circle in respective area is proportional to the hitting
ratio. In this study, three indexes are set. Therefore, users can analyse the trend of disaster researchfrom the following three viewpoints.


Analysis A: “type of disaster” and “type of countermeasures”
Analysis B: “type of countermeasures” and “type of object of damage”
Analysis C: “type of disaster” and “type of object of damage”
X-axis: index “a”
Volcanic disaster

Pbj: Hitting ratio of a proceedings (%)

item“j” (index “b”)
Storminandflood
Earthquake

Y-axis:index “b”

Large scale fire

Pi,j: Hitting ratio of a proceedings (%)
in item “i” (index “a”) and item “j” (index “b”)

Man‐made disaster
International disaster relief
Others
Total
Nab: The number of research papers

having keywords (index “a” and index“b”)
Nall: Total number of research papers
Pai: Hitting ratio of a proceedings (%) in item “i” (index “a”)

Figure 4.1. A distribution diagram of the hitting ratio of a proceedings

4.2. Impact Analysis of DisasterIn order to prepare for future disasters, it is necessary to organize problems and research results aboutpast disasters. “Impact analysis of disaster” is intended to analyse how long one disaster keeps impact
on disaster research. Using this function, users can see the time series variation of the number of
research papers related to past disasters. Specifically, a "disasters list" which is the summary of thename of past disasters is built, and research papers with the name of disaster are extracted by thefull-text search of research paper database. In this paper, earthquake disasters occurred since 1900
killing more than a thousand people (United States Geological Survey: USGS) are used to a "disasters
list". The number of disasters extracted is 125.
4.3. Search for Related Research
In order to take advantage of a research paper on disaster countermeasures, it is necessary to extract
also research papers related to its contents. The function “search for related research” is intended tosearch related research papers which have keywords or the name of past disasters. When users view
the page of a certain research paper, they can see the list of research papers related to its contents.

― 202 ―

5. APPLICATION (WCEE)In this paper, two results are described. The first is the result of trend analysis of disaster research
papers published in the proceedings of the all past WCEEs using the function "trend analysis ofdisaster research". The second is the extraction result of research papers related to the past earthquake
disaster using the function “impact analysis of disaster.”
5.1. Trend Analysis of Disaster Research
Figure 5.1 shows distribution diagrams of the hitting ratio from the 1st to the 14th WCEE proceedings.
The X-axis shows "type of countermeasures" and the Y-axis shows "type of disaster effect." Contents
observed from these distribution figures are as below.
In all conferences, the main research fields are composed of "Structure damage (building)" andfour types of countermeasures such as "Hazard mechanism", "Damage mechanism", "Mitigation",and "Damage assessment."
Research field of WCEE is getting wider comparing to before.
The most popular research field consists of "Structure damage (building)" and "Damage
mechanism" until 2000, since 2004, it has become "Structure damage (building)" and"Mitigation."
1st, United States, 1956

2nd, Japan, 1960
Natural slope

Natural slope

Earth structure

Earth structure

Ground deformation

Ground deformation

Debris flow
Structure damage(civil infrastructure)
Structure damage (building)

Debris flow
Structure damage(civil infrastructure)
Structure damage (building)

Structure damage (others)

Structure damage (others)

Fire spread

Fire spread

Lifeline and system

Lifeline and system

Transportation

Transportation

Human loss

Human loss

Affected people (refugees)
Industrial damage(Business interruption)

Affected people (refugees)
Industrial damage(Business interruption)
Total

Total

Y‐axis:object of damage
X‐axis: countermeasures

Y‐axis:object of damage
X‐axis: countermeasures

3rd, New Zealand, 1965

4th, Chile, 1969
Natural slope

Natural slope

Earth structure

Earth structure

Ground deformation

Ground deformation

Debris flow
Structure damage(civil infrastructure)
Structure damage (building)

Debris flow
Structure damage(civil infrastructure)
Structure damage (building)

Structure damage (others)

Structure damage (others)

Fire spread

Fire spread

Lifeline and system

Lifeline and system

Transportation

Transportation

Human loss

Human loss

Affected people (refugees)
Industrial damage(Business interruption)

Affected people (refugees)
Industrial damage(Business interruption)

Total

Total

Y‐axis:object of damage
X‐axis: countermeasures

Y‐axis:object of damage
X‐axis: countermeasures

Figure 5.1 (a). Distribution diagrams of the hitting ratio of all the past WCEE proceedings― 203 ―

5th, Italy, 1974

6th, India, 1977
Natural slope

Natural slope

Earth structure

Earth structure

Ground deformation

Ground deformation

Debris flow
Structure damage(civil infrastructure)
Structure damage (building)

Debris flow
Structure damage(civil infrastructure)
Structure damage (building)

Structure damage (others)

Structure damage (others)

Fire spread

Fire spread

Lifeline and system

Lifeline and system

Transportation

Transportation

Human loss

Human loss

Affected people (refugees)
Industrial damage(Business interruption)

Affected people (refugees)
Industrial damage(Business interruption)

Total

Total

Y‐axis:object of damage
X‐axis: countermeasures

Y‐axis:object of damage
X‐axis: countermeasures

7th, Turkey, 1980

8th, United States, 1984
Natural slope

Natural slope

Earth structure

Earth structure

Ground deformation

Ground deformation

Debris flow
Structure damage(civil infrastructure)
Structure damage (building)

Debris flow
Structure damage(civil infrastructure)
Structure damage (building)

Structure damage (others)

Structure damage (others)

Fire spread

Fire spread

Lifeline and system

Lifeline and system

Transportation

Transportation

Human loss

Human loss

Affected people (refugees)
Industrial damage(Business interruption)

Affected people (refugees)
Industrial damage(Business interruption)

Total

Total

Y‐axis:object of damage
X‐axis: countermeasures

Y‐axis:object of damage
X‐axis: countermeasures

9th, Japan, 1988

10th, Spain, 1992
Natural slope

Natural slope

Earth structure

Earth structure

Ground deformation

Ground deformation

Debris flow
Structure damage(civil infrastructure)
Structure damage (building)

Debris flow
Structure damage(civil infrastructure)
Structure damage (building)

Structure damage (others)

Structure damage (others)

Fire spread

Fire spread

Lifeline and system

Lifeline and system

Transportation

Transportation

Human loss

Human loss

Affected people (refugees)
Industrial damage(Business interruption)

Affected people (refugees)
Industrial damage(Business interruption)

Total

Total

Y‐axis:object of damage
X‐axis: countermeasures

Y‐axis:object of damage
X‐axis: countermeasures

11th, Mexico, 1996

12th, New Zealand, 2000
Natural slope

Natural slope

Earth structure

Earth structure

Ground deformation

Ground deformation

Debris flow
Structure damage(civil infrastructure)
Structure damage (building)

Debris flow
Structure damage(civil infrastructure)
Structure damage (building)

Structure damage (others)

Structure damage (others)

Fire spread

Fire spread

Lifeline and system

Lifeline and system

Transportation

Transportation

Human loss

Human loss

Affected people (refugees)
Industrial damage(Business interruption)

Affected people (refugees)
Industrial damage(Business interruption)

Total

Total

Y‐axis:object of damage
X‐axis: countermeasures

Y‐axis:object of damage
X‐axis: countermeasures

Figure 5.1 (b). Distribution diagrams of the hitting ratio of all the past WCEE proceedings― 204 ―

13th, Canada, 2004

14th, China, 2008
Natural slope

Natural slope

Earth structure

Earth structure

Ground deformation

Ground deformation

Debris flow
Structure damage(civil infrastructure)
Structure damage (building)

Debris flow
Structure damage(civil infrastructure)
Structure damage (building)

Structure damage (others)

Structure damage (others)

Fire spread

Fire spread

Lifeline and system

Lifeline and system

Transportation

Transportation

Human loss

Human loss

Affected people (refugees)
Industrial damage(Business interruption)

Affected people (refugees)
Industrial damage(Business interruption)

Total

Total

Y‐axis:object of damage
X‐axis: countermeasures

Y‐axis:object of damage
X‐axis: countermeasures

Figure 5.1 (c). Distribution diagrams of the hitting ratio of all the past WCEE proceedings

5.2. Impact Analysis of DisasterFigure 5.2 shows the number of research papers related to the past earthquake disaster in descendingorder using the function "impact analysis of disaster." This is intended for disaster with 5 papers or
more. The number of research papers related to the 1995 Kobe Earthquake in Japan is the largest. And
other earthquakes in Japan such as the 1923 Kanto Earthquake and the 1948 Fukui Earthquake are
well-researched.
Figure 5.3 shows the process of the number of research papers which are presented at each conference.
The target earthquake disasters have related research papers more than 20. Study of the 1995 Kobe
Earthquake has been an increase in the number of research papers from 1996. Research about
earthquake that occurred before the 1st conference tends to be continuously until 14th conference.
Many researchers presented research papers related to the 1976 Tangshan Earthquake at the 14th
China conference.
0

50

100

150

200

250

300

1995 Kobe

345

1985 Mexico

831906 San Francisco

801923 Kanto

78

1976 Tangshan

54

1948 Fukui
2004 Sumatra

350

25
10

1975 Haicheng

101988 Spitak

91999 Turkey

91990 Luzon

91980 El Asnam

7

1999 Taiwan

7

1963 Skopje

72001 Gujarat

6

1970 Tonghai

62005 Pakistan

5

1976 Guatemala

5

Figure 5.2. The number of research papers related past earthquake disaster― 205 ―

1995 Kobe Earthquake

1985 Mexico Earthquake

1906 San Francisco Earthquake

1923 Kanto Earthquake

1976 Tangshan Earthquake

1948 Fukui Earthquake

Figure 5.3. The process of the number of research papers which are published in each proceedings

6. CONCLUSIONSIn this study, the authors proposed a web-based system aiming to understand and grasp overall pictureof disaster researches from bird-eye. Using this system, users can analyse the trend of disaster researchand grasp the changes of the number of research papers related to past earthquakes. In this paper, theauthors tried to apply the proposed system to analyse all research papers published in the proceedingsof all past WCEEs. As a result, the trend of disaster research field and research on past disasters fromthe 1st to the 14th conferences become clear. In the future, the proposed system will be improved toassist implementation of proper disaster countermeasures using disaster research database.
REFERENCES
Google (2004). Google Scholar, http://scholar.google.co.jp/schhp?hl=en
Thomson Reuters. Web of Science,
http://apps.webofknowledge.com/WOS_GeneralSearch_input.do?locale=en_US&last_prod=WOS&SID=Y
1p%40DG%40EoaPf863f8gk&product=WOS&highlighted_tab=WOS&search_mode=GeneralSearch
National Information Centre of Earthquake Engineering (2009). WCEE ONLINE PROCEEDINGS,
http://www.nicee.org/wcee/― 206 ―

Kimiro Meguro and Osamu Murao (2008). Urban city and disaster prevention, The Open Univeristy of Japan,
Japan.
Kyoto University and NTT Communications. MeCab: Yet Another Part-of-Speech and Morphological Analyzer,
http://mecab.googlecode.com/svn/trunk/mecab/doc/index.html
United States Geological Survey (2012). Earthquakes with 1,000 or More Deaths since 1900,
http://earthquake.usgs.gov/earthquakes/world/world_deaths.php― 207 ―

Comparing the disaster information gathering behavior
and post-disaster actions of Japanese and foreigners
in the Kanto area after the 2011 Tohoku Earthquake
A. Kawasaki & K. Meguro

International Center for Urban Safety Engineering (ICUS),
Institute of Industrial Science, The University of Tokyo, Japan

M. Henry

Division of Field Engineering for the Environment,
Faculty of Engineering, Hokkaido University, JapanSUMMARY:
After the March 11 Tohoku earthquake, people living in Japan were faced with confusing and conflicting
messages from differing information sources which created an atmosphere of uncertainty and led many people,
particularly foreigners, to relocate to western Japan or leave the country entirely. In order to improve thedissemination of information after future disasters, a survey was conducted to understand how people in the
Kanto region – the most populous area of Japan and bordering the Tohoku region – received theirdisaster-related information and how it affected their decisions in the aftermath of the disaster. This paper
compares the results of Japanese and foreigners and discusses some initial impressions of the disaster
information gathering behavior and post-disaster actions. It was found that the role of domestic information
sources versus overseas information sources could have contributed to the confusion foreign respondents
experienced and led to their relocate or evacuation from Japan.
Keywords: Tohoku Earthquake, disaster information, media, foreigners, Japan

1. INTRODUCTION
At 14:46 Japan Standard Time (05:46 UTC) on March 11, 2011, a magnitude 9.0 earthquake occurred
off the Pacific coast of the Tohoku region of Japan. This earthquake not only caused strong groundmotion but also triggered a massive tsunami which inundated the eastern seaboard of Japan and caused
widespread destruction. The earthquake and tsunami also knocked out the cooling systems at the
Fukushima Daiichi nuclear power plant in Fukushima Prefecture, sparking a nuclear-related crisis
which culminated with the confirmation of nuclear meltdown in three of the reactors.
In the wake of this triple disaster, people living in Japan began to seek disaster-related information inorder to keep pace with the evolving situation and to make decisions regarding their post-disasteractions. As previous research shows, the primary source of information after environmental or
man-made disasters is generally the mass media (Greenberg et al., 2002), and although thisinformation was traditionally accessed via television, radio, or printed media, internet-based media arebecoming the predominant means for people to access and communicate disaster-related information(Boyle et al., 2004; Lu et al., 2007), with social media in particular emerging as an important
communication tool (Palen, 2008; Qu et al., 2009; Yates and Paquette, 2010; Kawasaki et al., 2012).
After the Tohoku Earthquake and during the unfolding of the nuclear crisis, there emerged a growing
disparity between the information given by domestic Japanese sources and overseas sources(Sanchanta, 2011), which may have contributed to the wide gap in perception of the situation between
Japanese and foreigners residing in Japan. While Japanese people in general continued life as usual,foreign communities reacted much differently, with many foreigners relocating within the country or
leaving Japan altogether (Associated Press, 2011). The difference in post-disaster actions between
Japanese and foreigners supports previous evidence which suggests that increased attention must be
given to populations which have specific needs during times of disaster (Spence, 2007). Therefore, inorder to improve disaster response and recovery, it is necessary to understand disaster information
gathering behavior considering different needs and perspectives.
― 208 ―

The objective of this paper is to examine and clarify the information gathering behavior andpost-disaster actions after the Tohoku Earthquake considering the difference between Japanese andforeigners. This study focused on people living in the Kanto region of Japan, which lies to the south of
the Tohoku region, and includes Tokyo along with seven surrounding prefectures (Fig. 1).

Figure 1. Map of Tohoku and Kanto regions of Japan

2. METHODOLOGY
2.1. Survey design & distribution
Data on disaster information gathering behavior were collected using an online survey. This survey
was provided in nine different languages (Japanese, English, Chinese, Korean, Portuguese, Nepalese,
French, Thai, Vietnamese), and the contents were designed to clarify respondents’ information
gathering activities, their information-related difficulties and their post-disaster actions. A summary of
the survey questions is given in Table 1. The survey was distributed via two methods: first, throughsocial and professional contacts of the authors; and second, through direct requests for cooperation
with various entities such as business communities, universities, embassies, and so forth. Responses
were gathered for two weeks beginning roughly 10 weeks after the earthquake occurred.
Table 1. Survey questions
Theme

Questions
What information sources did you trust the most / the least during the two weeks following the earthquake?
Information
During the two weeks following the earthquake, which media did you use to acquire information and ingathering
what language?
activities
What types of information were most important for you during the first day, first week, and second week
after the earthquake?
What types of information were unavailable, unclear, or difficult for you to understand during the first day,first week, and second week after the earthquake?
Information
In general, what were the reasons why the above information was unclear or difficult to understand?
difficulties
When faced with unclear or difficult to understand information, what media did you utilize in order toclarify or better understand that information?
Within the first two weeks after the earthquake, did you choose to remain in the Kanto area, relocate toanother area of Japan, or leave Japan?*
Post-disaster
What was the reason for your choice?
actionAt that time when you made your choice, how useful, if at all, was disaster-related information in making
that choice?** Questions were restricted to a single response; other questions allowed multiple responses― 209 ―

2.2. Sample characteristics
The survey received 1357 responses representing 74 countries. Japanese respondents alone made up
36% (N=497), and the distribution of foreign respondents (N=860) by country is shown in Fig. 2.
Questions asking for gender, age and occupation were voluntary, with overall response rates of 94.8%,
94.9%, and 93.9%, respectively. For gender, 67.8% of Japanese respondents were male and 32.1%
female, whereas 57.5% of foreign respondents were male and 42.5% female. The distributions for age
and occupation are given in Fig. 3 and Fig. 4, respectively.

100%

China
23%

Others33%

Thailand
7%

Nepal
2%

France4%Vietnam
5%

UK
5%

70-79

South Korea
Brazil
6%
5%

50-59

40%

40-49

20%

20-29

0%

Figure 2. Distribution of foreign respondents by country
Japanese company
Overseas company
Freelance/self-owned
No occupation

60-69

60%

USA
7%

Indonesia
3%

80

80%

30-39
10-19
Japanese

Foreigners

Figure 3. Distribution of respondents by age

Japanese government
Overseas government
Student
Other

Japanese educational inst.
Overseas military
House makerJapanese

N=456

Foreigners

N=818
0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Figure 4. Distribution respondents by occupation

3. RESULTS
3.1. Information sources
The distributions of most- and least-trusted disaster information sources for Japanese and foreign
respondents are shown in Fig. 5. For Japanese respondents, the most-trusted sources were based inJapan, such as Japanese news sources, the Japanese government, and Japanese research and academic
institutions. Foreign respondents tended to trust overseas sources more than Japanese respondents,
particularly international organizations such as the IAEA or Red Cross. Distrust of Japan-basedsources was similar between Japanese and foreign respondents, with both groups showing the greatest
distrust of information from the Tokyo Electric Power Company (TEPCO). However, foreign
respondents tended to distrust overseas sources more than Japanese respondents.
Furthermore, some sources that were highly trusted were also highly distrusted for both groups. For
example, for Japanese respondents the Japanese government was the second most-trusted source,
behind Japanese news sources. However, the Japanese government was also the second least-trusted
source for Japanese respondents, ranking only behind TEPCO. A similar result could be observed forforeign respondents.

― 210 ―

Overseas news source
Overseas research/academic institution
Family, friends, colleagues, etc.
Japanese news source
Japanese research/academic institution
Other

Overseas government
International organization (IAEA, Red Cross, etc.)
3rd party other than family, friends, colleagues, etc.
Japanese government
Tokyo Electric Power Company (Tepco)Ó±­¬ó¬®«­¬»¼ ·²º±®³¿¬·±² ­±«®½»­
Japanese

N=1114Foreigners

N=2474
0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Ô»¿­¬ó¬®«­¬»¼ ·²º±®³¿¬·±² ­±«®½»­
Japanese

N=918

Foreigners

N=1850
0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Figure 5. Most- and least-trusted information sources

3.2. Media & language for information acquisition
The distributions of media and language utilized for disaster information acquisition for Japanese andforeign respondents are shown in Fig. 6. Understandably, Japanese respondents overwhelming used
Japanese-language media, with nearly half being “traditional” forms of media such as television, radio,
and printed media such as magazines, newspapers, and so forth. The usage pattern ofJapanese-language media by foreign respondents was relatively similar to Japanese respondents;
however, foreign respondents turned more to internet-based forms of media when using English orother languages. In particular, inter-personal communication such as face-to-face, telephone, and soforth was more highly utilized in other languages than in Japanese or English for foreign respondents.
Television

Radio

Printed media

Inter-personal

Traditional internet media

Direct communication tools

Social media

Crisis mapping

Japanese
Foreigners
Japanese
Foreigners
Japanese
Foreigners
0

400

800

1200

1600

2000

2400

Figure 6. Media and language for information acquisition

3.3. Importance of information
The importance of information over time is shown in Fig. 7. Overall, there was little difference
between Japanese and foreign respondents for all three time periods. On the first day, information on
the safety of family, friends, etc. was the most important type of information, followed by information
on earthquake and tsunami damage and on transportation systems. By the first week, however, theimportance of information on radiation level and risk and on food and water supply, along with― 211 ―

information on transportation systems, became the most important types of information; by the second
week, these were joined by information on government response. For both Japanese and foreign
respondents, the relative importance of information on radiation level and risk increased consistently
from the first day to the first and second weeks, along with the importance of information on thegovernment’s response and on school and business continuity. Conversely, the relative importance of
information on the safety of family, friends, etc. and on the earthquake and tsunami damage tended todecrease over time.
Safety of family, friends, etc.

Radiation level & risk

Food & water supply

Transportation systems

Electricity & other utilities

Earthquake & tsunami char.

Earthquake & tsunami damage

Government response

Evacuation & shelters

School & business continuity
Japanese

N=1982Foreigners

N=3302

Japanese

N=1603Foreigners

N=4038Japanese

N=1206

Foreigners

N=2928
0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Figure 7. Importance of information over time

3.4. Difficulties related to information
Fig. 8 shows what information was unavailable, unclear, or hard to understand over time. Again, thedistribution for Japanese and foreign respondents was mostly similar, although Japanese respondents
tended to have more difficulties with earthquake and tsunami damage and on government responsethan foreign respondents. Conversely, foreign respondents tended to have more difficulties withinformation on food and water supply. For both groups, the most difficulty on the first day was withinformation on safety of family and friends, on radiation level and risk, and on transportation systems.
By the first and second weeks, radiation level and risk had become the information with mostdifficulties, along with government response. Over time, information difficulties increased forradiation level and risk, food and water supply, and government response, and decreased for safety offamily and friends, earthquake and tsunami damage, and evacuation and shelters.
Safety of family, friends, etc.

Radiation level & risk

Food & water supply

Transportation systems

Electricity & other utilities

Earthquake & tsunami char.

Earthquake & tsunami damage

Government response

Evacuation & shelters

School & business continuity
Japanese

N=1542Foreigners

N=2482

Japanese

N=1053Foreigners

N=2406

Japanese

N=772

Foreigners

N=1611
0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Figure 8. Unavailable, unclear, or hard to understand information over time

― 212 ―

The reasons why this information was unavailable, unclear, or hard to understand are shown in Fig. 9.
For both Japanese and foreign respondents, the primary reason for information difficulties was due to
confusion caused by conflicting or differing information, followed by inability to access information
due to mobile congestion or power outages. However, for foreign respondents, lack of language
comprehension was another source of information difficulties, whereas very few Japanese respondents
cited this as a problem.
Was confused by conflicting or differing information
Unable to access information due to mobile congestion, power outage, etc.
Couldnt understand information due to lack of language comprehension
Couldnt understand information due to difficult or unfamiliar terminology
Unable to find the information due to difficulty in searching or locating it
Other
Japanese

N=853

Foreigners

N=1790
0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Figure 9. Reasons why information was unavailable, unclear, or hard to understandFig. 10 shows the media and language utilized when clarifying information difficulties. Japanese
respondents again utilized primarily Japanese-language media, with traditional internet media such as
information portals being the most-utilized media. Foreign respondents’ usage of Japanese-language
media was again similar, although they used television, inter-personal communication, and crisis
mapping slightly more than Japanese respondents. Their utilized media in English and other languages,
however, differed in that foreign respondents tended to use direct communication tools such as email
and chat and social media such as social networking sites and blogs much more in English and otherlanguages than in Japanese. Furthermore, inter-personal communication in other languages was used
relatively more than in English or Japanese.
Television

Radio

Printed media

Inter-personal

Traditional internet media

Direct communication tools

Social media

Crisis mapping

Japanese
Foreigners
Japanese
Foreigners
Japanese
Foreigners
0

300

600

900

1200

1500

1800

Figure 10. Media and language for clarifying information difficulties

3.5. Post-disaster actions
The respondents’ post-disaster actions were evaluated by whether they relocated from the Kanto
region or left Japan. Within this survey’s sample, just over 90% of the Japanese respondents elected toremain in Kanto, whereas nearly 60% of the foreign respondents chose to leave Kanto. Of the foreign
respondents who chose to leave Kanto, 34% relocated to another area of Japan, while the other 66%
left Japan entirely.

― 213 ―

The distribution of reasons for choosing to remain in Kanto, relocate to another area of Japan, or leave
Japan entirely is shown in Fig. 11. For Japanese respondents, the main reason for their choice was that
it was a personal decision. However, for foreign respondents, while personal decision was also cited,
other primary reasons included family request and job obligation. Relative to Japanese respondents, alarger percentage of foreign respondents also cited concern for the young and government directive.
Personal decision
Government directive

Family request
Unable to leave

Job obligation
Other

Concern for the young

Japanese

N=583

Foreigners

N=1399
0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Figure 11. Reason for post-disaster relocation

When asked about the usefulness of disaster information for making the choice to remain, relocate orleave, more than 70% of both Japanese and foreign respondents stated that disaster information was
somewhat to very useful, with only slightly more than 10% of each group finding disaster information
to be not useful for their decision-making. The percentage of foreign respondents who found disaster
information to be very useful was about 28%, which was more than the 21% of Japanese respondents.

4. DISCUSSION
When comparing the disaster information gathering behaviour of Japanese and foreign respondents,
the largest differences could be seen in which sources were trusted and which media and language
were utilized for acquiring disaster information. In the case of the Japanese respondents, they trusted
domestic sources more than overseas sources but also distrusted domestic sources more than overseas
sources. When looking at the language used for acquiring information, however, it can be seen thatJapanese respondents turned primarily to Japanese-language forms of media; therefore, their relative
trust and distrust of domestic sources versus overseas sources may be attributed to their lack ofutilization of overseas (non-Japanese language) media. In the case of foreign respondents, Japanese,
English, and other language media were all utilized, and it could also be seen that foreign respondents
tended to trust domestic and overseas sources relatively equally, but distrusted overseas sources morethan domestic sources. The overlap between sources which were ranked highly as both trusted anddistrusted could be seen for both Japanese and foreign respondents, and indicates that there was a large
disparity between individuals regarding which sources were or were not trusted – that is, one person’s
most-trusted source may be another person’s least-trusted source. Considering the responses of bothgroups, it would appear that Japanese and overseas academic and research institutions andinternational organizations may be a good means for disseminating disaster information in the future,as they both had good trust levels and little distrust for both Japanese and foreign respondents.
For information importance and information difficulties over time, little difference between the
responses of Japanese and foreigners was observed. However, the reasons why respondents
encountered information difficulties differed; while both groups cited conflicting information as theprimary reason, foreign respondents appeared to encounter more difficulties with language, whereas
Japanese respondents focused more on inability to access information. Conflicting information andlanguage difficulties may not be completely independent, however, as Japanese respondents could beassumed to have had conflicting information in Japanese alone, whereas foreign respondents may haveencountered conflicting information more broadly and in different languages, as they utilized English
and other languages more than Japanese respondents. This reason for information disparity may lie
within the role which the mass media fulfills in disseminating disaster information. After a disaster,during the “response” and “recovery” phases, the information transmitted by the mass media is― 214 ―

generally focused on the affect areas in order to assist with recovery, but in the long-term “mitigation”
phase the mass media help provide information to raise awareness and improve preparation, often
through coverage of non-local disasters (Quarantelli, 1996). Therefore, in the aftermath of the Tohoku
Earthquake, it can be said that the domestic coverage was intended to support recovery activities but
overseas coverage was focusing on lessons for disaster mitigation in their own countries. As a result,foreigners in Japan who turned to overseas media, perhaps due to language comprehension or otherproblems, encountered disaster information for which they were not the target audience; that is, theyneeded local information but the sources they could turn to were not providing them with theinformation they needed.
By far, the largest difference between Japanese and foreign respondents could be observed in the
post-disaster action; that is, whether the respondents elected to remain in the Kanto area or relocated.
A large majority of the Japanese respondents chose to remain in the Kanto area, with “personal
decision” being the most-cited reason for this choice. For foreigner respondents, however, the reasons
were more varied but perhaps the largest differences in reasons is the “family request.” The cause ofthis large difference may also be related to the previous discussion on the target audience of domestic
versus overseas coverage of the disaster. Families of foreigners living in Japan may not have been able
to receive information about their family member’s local situation, instead only receiving information
which focused on the broader issues. As a result, they may have passed on information they werereceiving from their overseas sources to their family members in Japan, thus creating conflicting
information for those residing in Japan who were receiving domestic information. As this difference inpost-disaster response is the largest observed between Japanese and foreign respondents, and was alsoa critical issue post-disaster as reported in various news sources as mentioned earlier, the next step in
the analysis of the survey data will be to examine the characteristics and differences between foreign
respondents who remained in Japan and those who chose to relocate.

5. CONCLUSION
In this paper, disaster information gathering behaviour and post-disaster actions were investigatedthrough an online survey targeting people who were residing in the Kanto area of Japan at the time of
the 2011 Tohoku Earthquake, and specifically compares the results of Japanese and foreigners. From
the results, the largest difference could be seen in the post-disaster actions, where it was found that amuch larger percentage of foreigners than Japanese chose to relocate from the Kanto area rather thanstay and, for foreign respondents, the request of family members to relocate was more highly cited as
the reason for the post-disaster action than for Japanese respondents. In addition, foreign respondents
tended to encounter more language difficulties when trying to collect disaster information thanJapanese respondents. These factors may be affected by the roles of the domestic versus overseas
sources; for foreign respondents who could not understand local coverage due to language issues, they
were forced to turn to overseas sources, but these sources were not reporting the type of localized
recovery information which was necessary for their situation, and possibly caused confusion when thiscoverage or information conflicted with other information. It could also be seen that foreign
respondents turned to media provided in Japanese, English, and other languages, whereas Japaneseutilized primarily Japanese-language sources.
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http://www.businessweek.com/ap/financialnews/D9M681N80.htm (17 April 2012)
Boyle, M., Schierbach, M., Armstrong, C.L., Mcleod, D.M., Shah, D.V., and Pan, Z. (2004). Information
seeking and emotional reactions to the September 11 terrorist attacks. Journalism and Mass Communication
Quarterly. 181, 155-167.
Greenberg, B.S., Hofschire, L., and Lachlan, K. (2002). Diffusion, media use and interpersonal behaviors. In:
Communication and Terrorism: public and media response to 9/11, Hampton Press, Cresskill, U.K., 3-16.
Kawasaki, A., Berman, L.B., Guan, W. (2012) Emerging web and geospatial technology revolutionizes disaster― 215 ―

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Lu, H.Y., Case, D.O., Lustria, M.L.A., Kwon, N., Andrews, J.E., Cavendish, M.A., and Floyd, B.R. (2007).
Predictors of online information seeking by international students when disaster strikes their countries.
CyberPsychology and Behavior. 10:5, 709-712.
Palen, L. (2008). Online social media in crisis events. Educause Quarterly. 3, 76-78.
Qu, Y. We, P.F., and Wang, X. (2009). Online community response to major disaster: a study of Tianya Forumin the 2008 Sichuan Earthquake. 42nd Hawaii International Conference on System Sciences.
Quarantelli, E.L. (1996). The future is not the past repeated: projecting disasters in the 21st century from current
trends. Journal of Contingencies and Crisis Management. 4:4, 220-240.
Sanchanta, M. (2011). Japanese, foreign media diverge. The Wall Street Journal.
http://online.wsj.com/article/SB10001424052748703512404576209043550725356.html (17 April 2012)
Spence, P.R., Lachlan, K., Burke, J.M., and Seeger, M.W. (2007). Media use and information needs of thedisabled during a natural disaster. Journal of Health Care for the Poor and Undeserved. 18, 394-404.
Yates, D. and Paquette, S. (2010). Emergency knowledge management and social media technologies: a casestudy of the 2010 Haitian Earthquake. International Journal of Information Management. 31, 6-13.

― 216 ―

Analysis of the concentration of TV news coverageto the specific municipalities
on the 2011 off the Pacific coast of Tohoku Earthquake
Muneyoshi Numada
Research Associate, Institute of Industrial Science, The University of Tokyo, Japan

Kimiro Meguro
Professor, Institute of Industrial Science, The University of Tokyo, JapanSUMMARY
In the 2011 off the Pacific coast of Tohoku earthquake, we observed a concentration of news coverage on thedamage and disaster response activities of specific municipalities and a high emphasis on the nuclear power
plant accident. The concentrated news coverage induced the concentration of aid activities such as distribution ofrelief supplies and donations to the specific area. This problem has repeatedly happened in the past disasters. The
purpose of this research is to conduct a quantitative analysis of the municipalities that were repeatedly coveredby the TV news reports during the emergency period after the Tohoku earthquake. This research defined the
media coverage rate on municipalities in order to analyse the relationship between the amount of media coverageand the level of damage caused by the disaster. The result showed that even if the damage level is equally high,there was a difference in the amount of TV news coverage among the municipalities.
Keywords: The Pacific coast of Tohoku Earthquake, Concentration of news program, TV program,Disaster information

1. INTRODUCTION
At 14:46 JST (5:46 UTC) on March 11th, 2011, an earthquake of a moment magnitude 9.0, the largest
earthquake ever recorded in Japan, struck off the shore of the Sanriku area in the Tohoku Region. The
following “mega tsunami” hit deeply indented coastal areas and brought extensive and devastating
damage to many cities and villages in this area. Mega tsunami damage was not only limited tobuildings, but the resulting fires destroyed many communities and nuclear power plant (NPP) facilities
have suffered complicated and serious damage. This earthquake was later named “The 2011 off the
Pacific coast of Tohoku Earthquake” by the Japan Meteorological Agency (JMA).
In this earthquake, it was difficult to grasp the full scope of the disaster since the damage waswidespread and diverse. In order to obtain information about the damage condition, safety
confirmation, news and announcement from municipalities, a variety of media, not only conventional
tools such as television, radio and the Internet but also new types of information-sharing tools such as
Twitter and Facebook were used. Also the Internet TV news sites such as USTREAM and
NICO-NICO DOUGA were able to broadcast programs from NHK (Japan Broadcasting Corporation)and commercial TV stations at no charge. In addition, people could watch the TV programs in the
open air by receiving one-segment broadcasting services.
According to the survey (Nomura Research Institute, Ltd. 2011) on trends in media contact associatedwith the 2011 off the Pacific coast of Tohoku earthquake, TV was ranked no.1 and no.2 as animportant source of information, as 80.5% of the people considered “information from TV coverage(NHK)” and 56.9% considered “information from commercial TV stations” as important in acquiring
information about the earthquake. And “information from the newspaper” and “information from theportal sites on the I3nternet” ranked after TV. In addition, according to the survey (My VoiceCommunications, Inc. 2011) on "How one gathered information about the 2011 off the Pacific coast of― 217 ―

Tohoku earthquake", the TV was ranked top as 93.5% of the people chose TV, 44.9% chose
newspapers,44.8% chose internet news sites, 42.8% chose portal site (such as Yahoo) and 31.1%
chose radio. From these results, it is evident that many people used TV as a main tool for obtaining
information.
According to the article 108 of the Broadcasting Act and Disaster Countermeasure Basic Act (Tanaka
2008) broadcasting organizations are obliged to provide useful services in order to prevent and reducethe disaster. Also, the Ministry of Internal Affairs and Communications requested NHK and the
National Association of Commercial Broadcasters in Japan to provide accurate and detailed
information to the public as quickly as possible (Ministry of Internal Affairs and Communications2011).
From these results, it can be said that the TV news is not only to report damage situation but also it isexpected to provide useful information that can prevent further damage and contribute to an
appropriate disaster management as one of the “disaster prevention organizations”.
In the 2011 off the Pacific coast of Tohoku earthquake, some areas were easily accessible by the news
reporters or broadcasted heavily at an early stage which left a strong impact. As a result, somemunicipalities were intensively covered by the TV news reports than others. There was also a highemphasis on the nuclear power plant accident. It can be said that the news coverage was unbalanced
considering the scale of affected areas and as a result it induced the aid activities to be concentrated atcertain areas while other areas were neglected, causing unbalanced distribution of relief supplies anddonations
Although this problem of media concentration has been repeatedly pointed out (Nakamori 1995) in thepast earthquake such as Hokkaido Nansei Oki Earthquake in 1993, Hokkaido Toho oki Earthquake in
1994, and the Southern Hyogo prefecture earthquake in 1995, the same problem occurred again(Nakamori 2011). Unbalanced media coverage on certain topics and areas cannot provide the viewers
with comprehensive views and understanding of a total damage especially at the time of suchextensive disaster as the Tohoku earthquake. The TV media has a responsibility and an important role
to provide information to influence people’s decision-making and proper evaluation.
Previous studies regarding the TV news coverage and its contents after the Tohoku earthquake include
the chronological analysis of the contents of TV news (NHK 2011), the verification of early media
coverage, the confused reports of the nuclear power plant accident, and the analysis of the foreign
media reports (General incorporated association of Tokyo-sya 2011). However, the quantitative
analysis of the unbalanced TV news coverage has not yet been conducted.
The purpose of this study is to conduct a quantitative verification of unbalanced media coverageduring the emergency period after the Tohoku earthquake. The relationship between the media
coverage and the level of damage caused by the disaster for the first 10 days after the disaster was
analyzed.
2. TV NEWS DATAIn this study, we selected six major TV stations for the analysis, namely NHK, NTV, TBS, Fuji TV,
TV Asahi, and TV Tokyo. In order to analyse the TV contents, normally the text data from eachsection of the program is required. In this study, we have employed the database called"Document-Analyser" by JCC Corporation. This allowed us to obtain the text data of all six TV
stations for 365 days a year, 24 hours a day by the unit of seconds. Also it is possible for us tocomprehend when, what, where, and how each TV station did report. Table 1 shows an example ofthe text data of NHK on March 12th.
This paper uses the target period of 10 days from March 11th to 20th, considering the importance of
the TV news reports in the early stage immediately after the disaster, with regards to the understanding― 218 ―

of damage situation and the level of influence it has on a supply of relief goods. Figure 1 shows thenumber of characters obtained from the text data. The number of characters was recorded
approximately 100,000 from 11th to 13th of March, but from 14th to 18th, the number was more thandoubled to 200,000.
Figure 2 shows the total characters obtained during 10 days from each TV stations. From this figure,
NHK has the highest number of characters, followed by TBS and NTV.
Table 1. Example of the text data of the TV program (259 characters)
In Miyagi Prefecture, by the earthquake, 53 people were killed. The details is 17 people in the
Higashimatsushima city, 12 people in the Kesennuma city, 8 people in the Shichigahama town and 5
people in the Sendai city. In the coastal town of Minamisanriku where was attacked by the tsunami,
many buildings and houses were washed away by the tsunami except the hospital building constracted
by concrete, and many people were missing. In the area along with the port of Kesennuma in
Kesennuma city, the large-scale fire occurred caused by the outflowing oil from the tank at the port.
The video of Kesennuma city.
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3. ANALYSIS OF THE CONCENTRATION OF TV
The news programs broadcasted by each TV station were similar and there was no big difference or
distinctive characteristic observed from their reports made during 10 days after the disaster.
This chapter analyses how each TV station concentrated its reports on specific municipalities by using
the text data. This study defines “concentration-ratio of the news coverage on municipality C”. This isindicated by the ratio of "the total number of all the municipalities each TV station picked up" and "thenumber of each municipality each TV station picked up." Here the definition of the word "picked up”
is used when the name of a particular municipality is included in the text data as underlined in Table 1.
According to this definition, Higashimatsushima city marked “1”, Kesennuma city “4”, Shichigahama
town “1”, Sendai city “1”, and Minami-Sanriku town “1” as shown in Table 1.
If the index C is high, it indicates that the TV station has reported on the particular municipality
intensively. On the other hand, if the index C is low, it indicates that the particular municipality has
not been reported as much. If the index C is zero, it indicates that the municipality did not get coveredat all.
Table 2 (a) and (b) shows the transition of the index C in a chronological order. The three prefectureswith especially heavy damage - Iwate, Miyagi and Fukushima – are selected to obtain the news reports
coverage rate on daily basis. Due to space limitations in this paper, some municipalities withlow-value C are excluded and the value after the decimal point is omitted.
According to the table, the index C of Sendai city is high and it is evident that each TV station
concentrated on reporting about Sendai city. For Ishinomaki city, the index C varied during the periodof 11th to 15th of March however the value became high after the 16th of March. The index C of
Minami-sanriku town is low during the period of 11th to 12th of March, but the value became high for
all the TV stations from 13th to 16th of March. Miyako city was intensively reported from the 11th
through 14th of March except for TV Tokyo. Similarly, Ofunato city, Rikuzentakata city, Kamaishicity and Kesennuma city are the cities that were intensively reported by most TV station.
Using this method, we have succeeded to quantitatively evaluate the concentration and disparity of TV
news coverage on municipalities by TV stations.
Next, we discuss the relationship between the C value and the level of damage. In the previous studies,
there has been a quantitative analysis of the relationship between the newspaper coverage and thedamage level (Matsumura 1998), however the relationship between the TV report coverage anddamage level has not yet been studied. The definition "Earthquake coverage rate" is indicated by theratio of earthquake related reports in all the news reports in the newspaper excluding advertisement.
The result indicates that there is a high correlation to the number of casualties and the “Earthquake
coverage rate” rather than to the number of totally collapsed buildings.
Using the above result as reference, this paper analyses the relationship between casualties and theindex C of TV news coverage. The number of total casualties used here represents the sum of themissing and dead people.
Figure 3 shows the relationship between the casualties and the index C on March 11th. In calculating
the index C here, the total number of news coverage on municipalities from March 11th to 20th is used
and the number of casualties referred to those confirmed by March 20th.
Focusing on the municipalities with 1,000 casualties such as Kesennuma city, Kamaishi City, Otsuchi
town, Higashimatsushima city, and Yamamoto town, NHK showed the highest number of index C for
Kesennuma city, followed by Kamaishi city, Otuchi town, Higashimatsushima city and Yamamoto
town. This result shows that even though the number of casualties is similar, there is a difference inthe amount of TV news coverage on municipalities.

― 220 ―

Table 2 (a) Time history of “concentration-ratio of the municipality C” (2011.3/11-15)

2011/3/11
TV station
Pref.

Municipality

Morioka city
Miyako city
Ofunato city
Hanamaki city
Kuji city
Iwate
Tono city
Rikuzentakata city
Kamaishi city
Otsuchi city
Yamada town
Sendai city
Ishinomaki city
Shiogama city
Kesennuma city
Natori city
Kakuda city
Tagajo city
Iwanuma city
Miyagi Kurihara city
Higashimatsushima
Watari town
Yamamoto town
Matsushima town
Shichigahama town
Rifu town
Onagawa town
Minamisanriku town
Fukushima town
Aizuwakamatsu city
Koriyama city
Iwaki city
Shirakawa city
Sukagawa city
Kitakata city
Soma city
FukushNihonmatsu city
ima
Tamura city
Minamisoma city
Okuma city
Futaba town
Namie town
Kuzuo village
Shinchi town
Iidate village

2011/3/12
TV station

2011/3/13
TV station

2011/3/14
TV station

2011/3/15
TV station

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1

0

0

0

4

8

6

2

1

0

0

0

0

0

2

0

1

1

0

0

1

0

1

1

1

1

0

0

0

3

2

1

3

0

4

1

3

6

1

0

3

3

0

0

1

0

3

1

0

2

0

0

1

0

0

4

1

0

7

1

3

3

1

0

2

2

3

3

0

0

2

1

1

6

1

0

1

1

0

4

0

0

0

0

0

0

1

0

1

0

2

0

0

0

1

2

1

3

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

5

2

5

3

0

7

6

8

7

5

5 14

2

2

8

5

3

4

4

2

4

5

2

1

5

2

4

3

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

2

0

0

0

0

0

3

0

1

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

3

0

0

0

0

0

1

0

2

0

2

0

3

2

4

3

0

0

5

3

7

5

1 12

4

0

7

3

1

0

5

1

4

3

1

1

6

1

3

1

0

0

1

0

0

2

4

0

1

0

0

0

2

0

0

1

0

0

2

0

0

0

0

1

1

1

0

1

0

1

1

0

3

5

3

1

3

0

1

5

4

3

1

6

0

1

1

1

0

0

0

0

1

0

0

0

0

0

0

1

0

0

0

0

0

0

1

1

0

1

0

0

0

2

0

0

0

1

0

2

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

Concentration-ratioof
0 0 0 0 0 0 0 0 1 0 1
0 0 0 0 0 0 1 5 1 0 1 0 0 4 0 2 the0 2 municipality
1 2 0 1 0 9C 0(%)
0 1

0 1
30
25
3 1
20
0 0
15
0 0
10
0 0
5
01 0
20 0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

2

0

1

0

0
0
0
0
0
0

Note: The number is rounded off to the closest whole number― 221 ―

Table 2 (b) Time history of “concentration-ratio of the municipality C” (2011.3/16-20)

2011/3/16
TV station
Pref.

Municipality

Morioka city
Miyako city
Ofunato city
Hanamaki city
Kuji city
Iwate
Tono city
Rikuzentakata city
Kamaishi city
Otsuchi city
Yamada town
Sendai city
Ishinomaki city
Shiogama city
Kesennuma city
Natori city
Kakuda city
Tagajo city
Iwanuma city
Miyagi Kurihara city
Higashimatsushima
Watari town
Yamamoto town
Matsushima town
Shichigahama town
Rifu town
Onagawa town
Minamisanriku town
Fukushima town
Aizuwakamatsu city
Koriyama city
Iwaki city
Shirakawa city
Sukagawa city
Kitakata city
Soma city
FukushNihonmatsu city
ima
Tamura city
Minamisoma city
Okuma city
Futaba town
Namie town
Kuzuo village
Shinchi town
Iidate village

2011/3/17
TV station

2011/3/18
TV station

2011/3/19
TV station

2011/3/20
TV station

A T
A T
A T
A T
A T
F
F
F
F
F
s o
s o N N T
s o N N T
s o N N T
s o N N T
N N T
u
u
u
u
u
a k
a k H T B
a k H T B
a k H T B
a k H T B
H T B
j
j
j
j
j
h y
h y K V S
h y K V S
h y K V S
h y K V S
K V S
i
i
i
i
i
i o
i o
i o
i o
i o
1

1

1

1

0

0

4

1

0

2

0

6

4

3

2

2

1

0

2

3

3

2

0

0

1

1

1

3

3

0

7

1

4

8

6

0

3

1

6

8

6

0

1

4

3

5

2

0

2

3

2

8

7

0

1

2

5

3

3

0

2

3

5

2

6

0

1

3

4

7

8

0

3

7

4

7

1

0

1

9

1

9 10

7

1

2

1

6

3

0

0

2

0

1

0 11

1

2

1

0

0

0

0

0

4

1

0

0

1

0

1

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

2

0

0

0

0

0

0

0

0

3

0

0

1

0

0

0

0

0

1

0

1

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

5 12

8

5 12

0

6

4

6

7

9

0

9 13 10

5

7

0

6 14

8 11 137

6 10 12 12

6

7

5

5

2

0

5

2

7

6

2

6

5

3

7

6

1

8

6

5

8

3

0

3

6

6

9

1

0

0

1

4

5

6

6

0

3

5

2

3

2

0

2

1

2

2

1

0

2

0

5

1

3

0

4

2

5

4

3

0

2

1

2

9

1

0

2

0

3

6

2

0

4

1

2

0

3

0

5

0

2

1

3

0

2

0

0

1

0

0

11

9 13

8

7 33 10 13 21 15

8 44

8 10 16 14 17 38

8 16

7 17 15 13 10 21 10 20 12 13 17 11

6 10

5 12

5 17

7 12

7 10

4 31

9

8

2

9

8 15

4

9

5

8

3 10 13

6 18 14 17 26

0

0

0

0

1 11

1

2

1

0

2

6

1

3

1

0

2

0

0

1

2

0

3

0

0

4

0

0

3

8

7

7

9 18

0

7

9

5

4 18

0

6

7

6

9 11

0

5

8

6 12 11 14

8

1

6

4

5

0

0

3

1

1

2

0

0

3

0

1

0

0

1

1

1

1

1

0

0

1

0

1

0 10

1

1

2

0

2

5

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

4

0

2

1

0

1

4

0

2

2

0

0

0

0

0

0

0

0

0

2

0

0

3

1

0

0

1

2 11

0

1

0

0

0

0

1

3

0

0

0

0

0

0

0

1

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

1

0

2

0

1

1

0

0

3

0

0

0

4

0

0

5

2

2

1

2

1

0

2

1

1

1

2

0

1

1

0

1

2

0

0

1

0

2

0

3

1

1

0

0

3

0

0

0

0

1

0

0

0

0

0

1

0

0

0

0

0

0

0

0

1

0

0

1

0

3

1

0

0

0

0

0

0

0

2

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

2

2

1

2

2

0

2

1

1

1

2

0

1

1

1

2

2

0

0

1

0

2

0

3

1

1

0

0

3

0

0

0

0

0

1 11

0

0

0

0

0

0

0

0

1

0

3

0

0

0

0

0

0

0

0

0

1

0

0

0

1

0

0

0

0

0

0

1

0

0

0

0

2

1

0

0

0

0

1

4

0

0

0

0

0

1

0

1

0

0

3

2

0

1

0

6

2

0

0

5

2

0

1

0

0

2

2

1

4

2

0

1

2

0

0

0

0

1

0

0

0

9 12 15

8 13 11 11

8

6

3

5

0

9

7

4

2

6

0

8 11

7

0

5 10

8

6

9

0 10 11

2

2

7

4

2

0

2

4

7

6

2

0

4

3

4

2

0

0

1

0

6

2

2

0

2

1

0

1

2

0

0

1

0

0

0

0

1

0

0

0

2

0

0

0

0

0

2

0

1

0

0

0

0

0

0

0

0

0

2

0

0

5

3

2

3

0

0

0

2

1

2

0

1

2

1

2

1

8

1

0

0

1

2

0

0

0

0

0

0

0

3

2

2

0

2

0

9

2

3

5

8

0 13

5 10

6

4

8

5

0

8

3

0

0

1

2

4

7

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

2

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

1

0

0

0

0

0

9

3

3

6

0

0

3

4

7

5

4

0

5

7

4

5

9

0

7

1

3

7

7

0

3

1

1

4

0

5

1

0

2

0

3

0

1

0

0

0

0

0

0

0

1

0

0

0

1

0

1

0

0

0

0

0

4

0

0

0
0

1

1

1

0

1

0

1

0

1

0

0

0

0

0

1

0

0

0

0

0

4

0

0

0

1

0

0

0300

10

3

4

6

0

0

4

3

7

4

4

0

4

7

4

5

9

0

7

1

3

6

7

0

6

1

1

3250

0

0

0

1

1

0

0

1

1

1

1

1

0

3

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0200

0

0

0

0

0

0

0

1

1

1

1

1

0

3

0

0

0

0

0

9

2

2

1

3

0

9

4

2

3

1

0

1

0

0

0

1

0

0

0

0

6

0

0

2

0

0

0

1

0

0

0

0

0

1

6

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

Concentration-ratio
0 0 0 0 0 0 0 0 1 of
0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 the
0 0 municipality
0 0 0 0 0 0 C0(%)
0 0

15
2
10
0 0
5
01 0
00 0

0

1

1

1

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

2

3

0

0

0

1 13

0

0

0
0
0
0
0

Note: The number is rounded off to the closest whole number― 222 ―

Similarly, in Nihon-TV, for the municipalities with 1000 casualties, the index C of Kesennuma cityshows high value, while Yamamoto town and Higashimatsushima city show relatively low value. The
same tendency is observed in other TV stations. This tendency can also be observed from thechronological analysis of Table 2 (a) and (b). On March 14th in Higashimatsushima city, 152 dead and
400 missing people were found, likewise on March 15th in Yamamoto town, 111 dead and 638 missing
people were found. Despite these findings of high number of casualties, no obvious reaction isobserved in the index C.
Figure 4 shows the relationship between casualties and the index C of NHK on the day of theearthquake, the third and tenth day from the occurrence of earthquake.
The C is calculated by the number of coverage on the day of the earthquake, the sum of the coverageby the third and tenth days since March 11th respectively. The number of casualties used is the sum ofdead and missing people on the day of the earthquake, by the third and tenth days since March 11th
respectively.
The index C of Sendai and Natori city on the day of the earthquake is high, subsequently followed by
Ofunato city, Kamaishi city, Kesennuma city, Higashimatsushima city and Yamamoto town. Otsuchi
town is not covered at this stage as seen in Figure 4 (a). We will discuss by comparing two
municipalities of Kesennuma city and Otsuchi town.
On the third day (Figure 4 (b)), both Kesennuma city and Otsuchi town showed increase in thenumber of casualties, however the index C of Kesennuma city has increased while that of Otsuchi
town has not changed. By the tenth day since the earthquake, the number of casualties of both
Kesennuma city and Otsuchi town reached almost the same level, yet a big difference of index C isobserved.
These results proved quantitatively that there is a difference in the index C despite the fact that thecasualty level is the same and it indicated that the news reports coverage is unbalanced. This tendency
is common among other TV stations. One of the causes for this may be explained by the accessibility
to certain municipalities due to the road condition. However another cause may be that the TV stations
have tendency to comply with reports by successful TV stations which managed to deliver news withstrong impacts, driven by the mentality to avoid missing out on a scoop. The results of this study areimportant for it indicated these phenomena by using quantitative analysis.
4. CONCLUSION
The concentrated news coverage induced the concentration of aid activities such as distribution ofrelief supplies and donations to the specific area. This problem has repeatedly happened in the pastdisasters. This research proved quantitatively that there is a difference in the index C despite the factthat the casualty level is the same and it indicated that the news reports coverage is unbalanced. Thistendency is common among other TV stations. One of the causes for this may be explained by theaccessibility to certain municipalities due to the road condition. However another cause may be that
the TV stations have tendency to comply with reports by successful TV stations which managed todeliver news with strong impacts, driven by the mentality to avoid missing out on a scoop. The resultsof this study are important for it indicated these phenomena by using quantitative analysis.
From these results, we propose the following strategy to improve the TV news reports for the next
disaster. Under the condition of limited time and human resources of TV stations, it is advisable to (1)grasp the overall damage condition properly, (2) provide information that corresponds to the needs ofthe audience, and (3) promote the cooperation among the TV stations, with respect to freedom of thepress, in order to avoid unbalanced news coverage to specific municipalities and to make it moreaccessible to obtain necessary information.

― 223 ―

Number of casualties

Number of casualties

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市町村報道率（%）
Concentration-ratioof the municipality C(b) NTV
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(e) TV-Asahi
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市町村報道率（%）

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市町村報道率（%）
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Figure 3. Relationship between the number of casualties and the concentration–ratio of the municipality― 224 ―

��%

Number of casualties

Number of casualties

1000

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市町村報道率（%）
Concentration-ratioof the municipality C(b) three days after the earthquake, 2011.3.13

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Figure 4. Relationship between the number of casualties and the concentration–ratio of the municipality of NHK

At the time of disasters with extensive damage as seen in the 2011 off the Pacific coast of Tohoku
earthquake, it is difficult to evaluate the whole scope of the damage and consequently there was an
unbalanced TV news coverage. As a result, there were some municipalities that received more support
than others as discussed in this paper. From this study it can be said that the TV news coverage made a
big impact on the disaster response both for those who support and are supported thus it is important toconsider the above-mentioned strategy for improvement.
Regarding to the role of news organizations, the TV stations are expected to provide useful
information in order to contribute to the realization of appropriate disaster response, both from insideand outside of the disaster-affected area (Cabinet Office 2008) and it is important to consider theabove-mentioned strategy for improvement from this point of view as well.
For the next activities of this study, we will make similar analysis using the amount of reporting timeand verify the difference from the text data. Moreover, we will make further study to find out whatkinds of subject matters were reported intensively.
AKCNOWLEDGEMENT
This research is supported by Mr. Takatoshi Ishii of JCC Corporation.
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Nakamori H., (2011). Problems of news and mass media in the 2011 Off the Pacific Coast of Tohoku Earthquake.
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NHK (2011). What kinds of contents did TV stations provide in the 2011 Off the Pacific Coast of Tohoku― 225 ―

Earthquake, NHK broadcasting studies, Vol. 61, No.5, pp.2-7.
NHK (2011). What kinds of contents did TV stations provide in the 2011 Off the Pacific Coast of Tohoku
Earthquake (2), NHK broadcasting studies, Vol. 61, No.6, pp.2-9,
General incorporated association of Tokyo-sya (2011). Journalism of unprecedented disaster and tribulation.
Journal of general journalism research, No.217, pp.9-18, 26-51
Kazuo Matsumura (1998). Reaction of society against the earthquake disaster reported by the newspaper,
Journal of Architectural Institute of Japan. 511, pp.61-67.
Cabinet Office (2008). Basic Disaster Management Plan, pp.48-49.

― 226 ―

A Study on People's Awarenessof Earthquake Early Warning before and after
the 2011off the Pacific Coast of Tohoku Earthquake, Japan
Miho Ohara
Institute of Industrial Science /Interfaculty Initiative in Information Studies,The University ofTokyo, Japan

Kimiro Meguro
Institute of Industrial Science /Interfaculty Initiative in Information Studies,The University ofTokyo, Japan

Atsushi TANAKAInterfaculty Initiative in Information Studies,The University of Tokyo, JapanSUMMARY:
After the 2011 off the Pacific Coast of Tohoku Earthquake on March 11, 2011, Earthquake Early Warning(EEW) was frequently provided. However, some of the warning at aftershocks failed to estimate intensity
properly due to technical limitation. In this paper, questionnaire surveys were conducted to understand people’s
awareness of EEW before and after the 2011 off the Pacific Coast of Tohoku Earthquake and change of theirawareness was analyzed comparing both results. Their behavior after receiving the warning was also analyzed
and suggestions for enhancing their capacity to take proper actions after EEW were obtained.
Keywords: Great East Japan earthquake, early warning, awareness, capacity building, questionnaire survey

1. INTRODUCTION
The Japan Meteorological Agency (JMA) began to provide the service of earthquake early warning(EEW) to the public on October 1, 2007. This is a new system that quickly analyses seismic wave data
observed by seismographs near the epicenter and provides prompt alerts before the arrival of strong
tremors (S-waves) as shown in fig.1. For public use, EEW is provided to the regions where theintensity of shaking was expected to be greater than JMA 4 in case the maximum estimated intensity is
5 lower. This system aims to mitigate earthquake-related damage by enabling individuals to protect
themselves quickly in various environments such as houses, offices and factories. A warning is widely
broadcasted by television, radio, mobile phone and loudspeakers.
The Iwate-Miyagi Inland Earthquake occurred in the southern inland region of Iwate Prefecture, Japan
at 8:43 JST, June 14, 2008. It was the first earthquake since October 2007 for which EEW could be
successfully broadcasted before the arrival of strong tremors. The lead time between the warning andthe arrival of strong tremors was around 10-25 seconds in the area surrounding its epicenter. After this,a small earthquake occurred in Fukushima Prefecture at 16:59 JST on September 29, 2010. EEW was
broadcasted in the eastern area of Japan as the expected intensity exceeded 4. It was broadcasted also
in the Tokyo metropolitan area although observed intensity was less than 4. Recently, the percentageof the people who can get EEW by mobile phones is increasing. At this earthquake, a lot of people
received the warning by mobile phone in the Tokyo metropolitan area for the first time and it becamea good opportunity for making people familiar with EEW.
The 2011 off the Pacific Coast of Tohoku Earthquake occurred at 14:46 JST on March 11, 2011 andnumerous aftershocks continued. EEW was successfully provided in Tohoku area at the main shocks.
On the other hand, in the Tokyo metropolitan area, EEW failed at the main shock but was frequently
announced at aftershocks. Figure 2 shows the number of EEW that was provided to each prefecture in
Japan during March 2011 and April 2012. 45 warnings was provided in March. The number ofbroadcasted EEW from March 2011 to August 2011(6 months) was 87 although that number from
October 2007 to February 2011(41 months) was 17. However, some of the numerous warning ataftershocks failed to estimate intensity properly because several earthquakes occurred at the same time
― 227 ―

could not be identified separately or some seismometers were unusable due to long-time power outage
after the earthquake. These problems were due to technical limitation of EEW and some of them weresolved by program modification after March 2011.
In this paper, two questionnaire surveys were conducted to understand people’s awareness of EEW.
The first one was done after the earthquake in September 2010 for the people who received thewarning by mobile phone. The second one was done after the earthquake in Tohoku region in March
2011. The change of their awareness was analyzed comparing both results. Their behavior after
receiving the warning was also analyzed and suggestions for enhancing their capacity to take proper
actions after EEW were obtained.
Transmit observed data

S-waveP-waveS-waveInform of the coming tremors
before their arrival

Seismograph

Focus

Focus

When P-wave was observed

When S-wave arrived

Figure 1. Concept of Earthquake Early Warning
120
100
80
60
40
0

Hokkaido
Aomori
Iwate
Miyagi
Yamagata
Akita
Fukushima
Ibaragi
TochigiGun,aSaitama
Tokyo(Except Izu Islands)
Tokyo(Izu Islands)
Chiba
Kanagawa
Yamanashi
NaganoNiigata (Except Sado…
Niigata(Sado Island)
Toyama
Fukui
Aichi
Mie
Wakayama
Hiroshima
ShimaneTotal

20201204
201203
201202
201201
201112
201111
201110201109201108201107
201106
201105
201104
201103Figure 2. Number of Earthquake Early Warning Provided to Each Prefectureduring March 2011 and April 2012.

2. OUTLINE OF TWO QUESTIONNAIRE SURVEYS
The first questionnaire survey was done after the earthquake in Fukushima Prefecture on September
29, 2010. Survey period was from November 5-11, 2010. Main target of the survey was the people
with 30-60’s living in the Tokyo Metropolitan area (Tokyo, Saitama, Chiba, Kanagawa Prefectures)
who received the warning by their own mobile phone or neighbor’s mobile phones. The number of
respondents in each group was shown in table 1.
The second survey was done after the earthquake in Tohoku region in March 2011. Survey period wasfrom August 9-16, 2011. A questionnaire sheet was sent to the same respondent as the first survey.
The number of EEW that was provided to Tokyo, Saitama, Chiba Kanagawa Prefectures was shown― 228 ―

within red line in fig. 2. The total number of EEWs in Tokyo(Except Izu Islands), Saitama, Chiba
Kanagawa Prefectures from March 2011 to July 2011(5 months) were 21, 32, 31, 28, respectively.
The ratio of the respondents who answered the second survey was 76.6％(613 people among 800).
The number of the group A respondents who answered the survey in 2011 was 153. Among them, 11
people changed their mobile phones and could not receive EEW as of March 2011. The number of the
respondents in each group who answered the survey in 2011 and could receive EEW as of March 2011
was shown in table 1.
Table 1. Number of respondents for surveys in 2010 and 2011
2011 Survey
Ratio of the
Could receive EEW by mobile phone
Could notrespondents
as of March 2011
receive EEW
who answeredby mobile
total
Received at Received outside
the second
phone as ofhome after
home aftersurveyMarch 2011
march 2011 march 20112010 Survey

Received EEW by their own mobile
phones
Received EEW by their neighbors'Bmobile phones
Received EEW by their own mobile
C phones and experienced the stopof train
D Didn't receive or listen EEW
A

200

142

118

91

11

153

76.5

200

70

48

42

81

151

75.5

200

119

65

52

31

150

75

200

71

49

36

88

159

79.5

3. RESPONDENTS’ KNOWLEDGE OF EARTHQUAKE EARLY WARNING
At first, change of respondents’ knowledge of EEW was analyzed comparing the results of two
surveys. All the groups had the same tendency between 2010 and 2011. Figure 3 shows the result ofgroup A for example. After the earthquake in September 2010, 50.3% knew both the name of EEW
and that it forecast a strong tremor just before its arrival. After the experience of the main shock andaftershocks of Tohoku earthquake in 2011, the ratio increased to be 89.5%. At the survey in 2011, therespondents who knew neither its name nor its meaning were drastically decreased to be 2.0%.
Figure 4 shows the respondents’ knowledge of methods or conditions of EEW broadcasting. It is a
result of group A for example as all the groups had the same tendency between 2010 and 2011. The
ratio of the respondents who knew that EEW is broadcasted on TV or by mobile phone increased after
2010 and exceeded 90% in 2011. On TV, the name of the area where strong tremors are expected andthe warning message are shown. On the other hand, neither expected intensity nor lead time before thearrival of strong tremors is explained. The knowledge on expected intensity or lead time was low in2010 but increased especially in 2011. However, knowledge of criteria on intensity at which EEW is
broadcasted was still low. In addition, change in the knowledge of special receiving devices was verysmall although the special receiving devices are important tools for receiving expected intensity orlead time at home. Enhancing these knowledges is necessary.
100%
80%
60%

23
53

137

40%
20%

3
13

77

0%
2010

2011

I knew neither its
name nor its
meaning
I knew only thename of EEW
I knew goth thename of EEW and
its meaning

Figure 3. Respondents’ knowledge of EEW― 229 ―

EEW cannot be provied before strong tremorsin
the area where is too close to the hypocenters

92.2

73.2

Special receiving devices can show expected
intensity and lead time

34.6
30.1

Trains stop after receiving EEW

73.9
71.9

EEW is annoounced in some facilities such as
department stores

33.3

45.1

EEW can be received by mobile phones

96.7

71.2

Lead time is not shown on TV

39.2

Expected intensity is not shown on TV
On TV, the name of the dangerous and warning
messageare shown

92.8

65.4
20.9

EEW is proveded on TV in case maximum
expected intensity is 5 lower

23.5
0

10

20

30

2010

66.0

20.3

EEW is proveded on TV to the area where expected
intensity is 4

2011

81.0

33.3
39.9
40

50

60

70

80

90 100Figure 4. Respondents’ knowledge of methods or conditions of EEW broadcasting

4. RESPONDENTS’ RESPONSE TO EARTHQUAKE EARLY WARNING
Next, respondents’ response to EEW after EEW was investigated. More than 80% of each groupwatched EEW on TV at home after March 2011. The ratio of the respondents who received EEW at
home was highest in group A. 88.4% of group A watched EEW on TV and 80.3% received by mobile
phone at home. 59.4% received by mobile phone outside home. The feeling of respondents in group A
after receiving EEW at home was investigated. Figure 5 is the comparison of their feeling after
earthquakes in 2010 and 2011. The ratio of the respondents who thought that strong tremor would
come soon drastically increased from 34% to 86.7%. It shows that experience of receiving many EEW
after March 2011 led to high awareness of warning message.
Figure 6 shows what respondents in group A did immediately after receiving EEW at home at the both
earthquakes. Most frequent response after both earthquakes was to get earthquake information fromtelevision or radio. The second one was to wait. The ratio of the response for informing their children
or people near them was drastically increased from 2010 to 2011.The ratio of holding furniture orvaluables, hiding in a safe place and protecting my body, protecting children or elderly people,
opening a door or window were also increased in 2011. The aim of EEW service is to enable residents
to quickly protect themselves before the arrival of strong tremors. Considering this aim, it is said theexperiences of receiving many EEW after March 2011enhanced their capacity to take actions forprotecting themselves or family members.
100%
90%

4.6
6.5

0.7
5.6
8.4

80%
70%
60%

I thought it is a flash
news of earthquake
intensity

45.1

50%
86.7

40%

I thought it is due to thefailure of a mobile
phones

I could not understandthe meaning quickly

30%
20%

I thought strong tremor
will come soon

34.0

10%
0%
2010

2011

Figure 5. Respondents’ feeling after receiving EEW― 230 ―

I don't remember

1

I could not do anything

1

Others1
2

I went outside the house or building

1

12

2011

15

2010

7

I opend a door or window

18

I informed children or others of EEW

24
34

10

I protected children or elderly people

7

I hide in a safe place and protect my body

15
15

I held furniture or valuables

7

22

13
27
27

I put out fire49

I waited and evaluated the situation

53
66

I got information from TV or radio
0

10

20

30

40

50

60

70

83
80

90

100

Figure 6. Ratio of Respondent’s action after receiving EEW

5. RESPONDENTS’ ATTITUDE TOWARD FAILURE OF EARTHQUAKE EARLY WARNING
After the earthquake on March 11, 2011, numerous EEW was provided to the public due to continuous
aftershocks. However, some of them failed to estimate intensity properly because several earthquakes
at the same time could not be identified separately or some seismometers were unusable due tolong-time power outage after the earthquake. These problems were due to technical limitation of EEW
and were announced beforehand by Japan Meteorological Agency. Here, the knowledge of technicallimitation before the earthquake and their attitude toward the failure of EEW were analyzed. 36.5% of
the respondents among all knew the technical limitation before March 2011 that actual intensity can be
more or less than the expected intensity within the range of intensity 1. About 90% of the respondents
wished to use EEW even if it has a risk of failure regardless of whether they knew technical limitation
before the earthquake or not. 55.4% of the respondents with the knowledge of technical limitation
answered that they would like to use EEW aggressively even if they have a risk of failure. The ratio
decreased to be 35.0% without the knowledge. It was verified that familiarization with technicallimitation before the event is important in order to increase positive attitude in case that EEW fails.
100%

0.0
2.7

90%
80%

4.4
8.5

40.6

70%
51.9

60%
50%
40%
30%

55.4

20%

35.0

10%
0%
With Knowledge

I don't have an interest
on EEW
I would not like to use
EEW at all becase of arisk of failure
I would not like to use
EEW becase of a risk offailureI would like to use EEW
even if it has a risk offailureI would like to use EEW
aggressively even if it
has a risk of failure

Without Knowledge

Figure 7. Respondents’ attitude toward failure of EEW― 231 ―

6. RESPONDENTS’ OPINION ON EFFECTIVENESS OF EARTHQUAKE EARLY WARNING

Finally, their opinion on effectiveness of EEW was investigated. The ratio of the respondents who
thought EEW was very effective for mitigating seismic damage was about 40% at the both survey in2010 and 2011. Including the respondents who thought it is effective, the total ratio of positive
respondents amounted to be about 90%. When we focused on the relationship between their opinion
and the experience of receiving EEW after March 2011, the ratio of the respondents who thought to bevery effective was 38.5% as shown in fig.8. It was verified that real experience of receiving EEWenhanced the understanding of effectiveness of EEW. Figure 8 is the relationship between theiropinion and the knowledge on technical limitation before the earthquakes. In the chapter four, wefound that familiarization with technical limitation before the event increased positive attitude toward
the failure of EEW. In fig. 9, the ratio of the respondents who thought to be very effective was 54.5%
in case they had knowledge on technical limitation before the earthquake. This value was almost twiceof the ratio in case of respondents without the knowledge. It is concluded that making people familiar
with technical limitation led to their positive attitude toward EEW and it can increase high evaluationon the effectiveness of EEW.
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

0.2
7.2

5.7
5.7

54.1
68.6

Not Effective at all
Not Effective
Effective
Very Effective

38.5
20.0
I received EEW

I didn't receive
EEW

Figure 8. Relationship between understanding of effectivenessand the experience of receiving EEW
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

0.0
3.6

2.1
9.3

42.0
60.9

Not Effective at all
Not Effective
Effective

54.5
27.8
I knew technicallimitation

Very Effective

I didn't know
technical
limitation

Figure 9. Relationship between understanding of effectivenessand the knowledge on technical limitation

7. CONCLUSIONSIn this paper, two questionnaire surveys were conducted to understand people’s awareness of EEW.
The first one was done after the earthquake in September 2010 for the people who received thewarning by mobile phone. The second one was done after the earthquake in Tohoku in March 2011.

― 232 ―

The change of their awareness was analyzed comparing both results.
After the experience of the main shock and aftershocks of Tohoku earthquake in 2011, knowledge of
EEW among residents drastically increased. Some of the knowledges were low still in 2011 andrequired to be enhanced. Their behavior after receiving the warning was also analyzed. The ratio of the
respondents who thought that strong tremor would come soon drastically increased from 34% in 2010
to 86.7% in 2011. It shows that experience of receiving many EEW after March 2011 led to highawareness of warning message. In 2011, the ratio of the response for informing their children or
people near them, protect their bodies, protect their children or elderly family members increased,compared with the answers in 2010. The experiences of receiving many EEW after March
2011enhanced their capacity to take actions for protecting themselves or family members. People’s
awareness level and capacity can decrease easily as time passes after the disaster. It is very importantto keep their awareness level by education or training in the future.
After the earthquake on March 11, 2011, numerous EEW was provided to the public due to continuous
aftershocks. However, some of them failed to estimate intensity properly due to technical limitation.
From the survey, familiarization with technical limitation before the earthquakes increased positive
attitude in case that EEW failed. It also increased high evaluation of the effectiveness of EEW.
Continuous information dissemination on technical limitation is important for positive attitude fortaking action after receiving EEW.
REFERENCES
The Japan Meteorological Agency. (2011). A List of Past Earthquake Early Warning,
http://www.seisvol.kishou.go.jp/eq/EEW/kaisetsu/joho/joho.html
The Japan Meteorological Agency. (2011). Earthquake Early Warning provided after the 2011 off the Pacificcoast of Tohoku Earthquake. JMA News Release, Japan.
The Japan Meteorological Agency. (2011). Improvement of Earthquake Early Warning. JMA News Release,
Japan.

― 233 ―

― 234 ―― 235 ―― 236 ―― 237 ―― 238 ―― 239 ―― 240 ―― 241 ―― 242 ―― 243 ―― 244 ―― 245 ―― 246 ―― 247 ―― 248 ―― 249 ―― 250 ―― 251 ―― 252 ―― 253 ―― 254 ―― 255 ―― 256 ―― 257 ―― 258 ―― 259 ―― 260 ―― 261 ―― 262 ―― 263 ―― 264 ―― 265 ―― 266 ―― 267 ―― 268 ―― 269 ―― 270 ―― 271 ―― 272 ―����（都市基盤安全工学国際研究センター）

第 22 回オープンレクチャーのご案内「復興を俯瞰して考える」
日本社会は，この一年間，未曾有の超広域・壊滅的巨大災害からの復興という未経験の課題に奮闘している．未だ，取り組むべき様々な課題が山積している．被災地での寄り添った復興支援とともに，被災地域全体を俯瞰した議論も重要である．本オープレクチャーでは，被災地の現状をふまえた上で，被災地全体を俯瞰し復興のあり方について改めて考える．

■日■場

時： 平成 24 年 4 月 16 日（月）13:30～17:30 （13:00 開場）
所： 東京大学・駒場リサーチキャンパス（東京大学生産技術研究所）
An 棟２F コンベンションホール
（地図：http://icus.iis.u-tokyo.ac.jp/wwwj/announcements/ol_map.pdf）■主 催： 東京大学生産技術研究所都市基盤安全工学国際研究センター■入場無料，要申込み【定員：200 名】※終了後（17：30～）意見交換会（\1,000）を開催

プログラム【第一部】13:30-16:00■主旨説明：加藤孝明（東京大学生産技術研究所 都市基盤安全工学国際研究センター 准教授）
「復興を俯瞰して考えることの意義」■基調講演１：室崎益輝（関西学院大学教授，日本災害復興学会会長）「あるべき復興と減災の哲学」■基調講演２：鈴木浩（福島大名誉教授，福島県復興ビジョン策定委員会委員長）「福島復興の課題と展望」■基調講演３：中林一樹（明治大学特任教授）「二元復興論（仮題）」■基調講演４：川上征雄（国土交通省大臣官房審議官（国土政策局））「復興・減災と国土政策」【第二部】16:15-17:30■パネルディスカッション：
室崎益輝＋鈴木浩＋中林一樹＋川上征雄 （コーディネーター：加藤孝明）■閉会挨拶：目黒公郎（東京大学生産技術研究所 都市基盤安全工学国際研究センター長 教授）■申込み
e-mail: icus@iis.u-tokyo.ac.jp
FAX：03-5452-6476■問合わせ：担当 吉本英子
e-mail: yosimoto@iis.u-tokyo.ac.jp TEL：03-5452-6472― 273 ―

基調講演者プロフィール■室崎益輝
関西学院大学復興制度研究所所長・総合政策学部教授．神戸大学教授，総務省消防科学研究所所長，同消防科学研究センター長を経て 2008 年 4 月より現職．神戸大学名誉教授．災害復興学会長．専門は，都市防災，建築防火．
中央防災会議専門委員等を務める．1993 年日本火災学会賞，1998 年日本
建築学会賞(論文)，2007 年都市住宅学会賞(論文)■鈴木浩
福島大学名誉教授．東北大学大学院工学研究科博士課程（建築学専攻）修了
後、東北大学工学部助手、国立小山工業高等専門学校 助教授、文部省在外研究員（ロンドン大学）などを経て、1990 年 福島大学行政社会学部 教授、2006 年 福島大学共生システム理工学類 教授、2010 年に定年退職。専門は，地域計画、地域居住政策．福島県復興ビジョン検討委員会座長．福島県
総合計画審議会会長、福島県商業まちづくり審議会会長などを務める。

■中林一樹（なかばやしいつき）
明治大学大学院政治経済学研究科特任教授．首都大学東京教授を経て 2011年 4 月より現職．首都大学東京名誉教授．専門分野は，都市防災，自然災害
科学，都市計画・建築計画．中央防災会議「首都直下地震避難対策等専門調査会」座長、同専門委員，東京都防災会議地震部会委員なども務める．災害
復興学会副会長．南三陸復興計画策定委員会委員．

■川上征雄（かわかみ ゆきお）
国土交通省大臣官房審議官．北海道大学大学院環境科学研究科修了．国土庁入庁。1994 年東京都企画審議室計画担当課長。1996 年国土庁大臣秘書官。
2001 年国土交通省国土計画局計画官。2004 年国土交通省大臣官房参事官、
内閣府政策統括官付参事官(社会基盤担当)、2008 年国土交通省国土計画局
総合計画課長等を経て 2011 年より現職。博士(工学)．

■加藤孝明（かとう たかあき）
東京大学生産技術研究所都市基盤安全工学国際研究センター・准教授．東京大学工学部都市工学科卒業，東京大学大学院工学系研究科都市工学専攻助手・助教を経て 2010 年 4 月より現職．専門は，都市計画，都市防災，地域
安全システム学．市街地の防災性評価技術の開発，防災まちづくりの実践，復興準備，四川地震での復興計画支援等の研究を行う．東京都防災会議地震部会委員も務める．評価技術に関して 2001 年日本建築学会奨励賞，2007
年地域安全学会論文賞，理論と実践に関して 2009 年日本都市計画家協会楠
本洋二賞優秀賞．

― 274 ―

�経験の共有�震災復興・�続シン����第 1 回（第 23 回 ICUS �ープン�クチャ）「被災地からみた復興の現状」「右肩下がりの時代における超広域巨大災害」からの復興・再生は，世界で初めての経験である．
被災地では，復興を支える社会のしくみが依然として混沌とする中，復興へ向けての模索が続けられている．被災地の再生，復興をすすめていくためには，社会に存在する様々な経験，知を共有し，そこでの議論を通して得た知見を復興の現場へフィードバックしていくことが大切な第一歩と考える．
被災から二年目を迎え，一年目の「手探りの復興」から「��な復興」へ向けて舵を切るときである．この一年間，行政，地域住民，専門家は，それぞれの立場で様々な経験を重ねながら，復興
まちづくりに向けた努力を進めてきた．第１回は，復興まちづくりの現場からの報告をもとに，復興の現状とこれまでの復興の現場での経験を共有し，二年目のプランニングの課題について議論を深めることを目的として開催する。
※【経験の共有】震災復興・連続シンポジウムは，東京大学生産技術研究所 ICUS と日本都市計画家協会の共同主催で開催します．

‫ޝ‬㐿௅᭎ⷐ‫ޞ‬■日■会時：平成２４年５月２０日（日） 13:00～17:30 （12:30 開場）
場：東京大学・駒場リサーチキャンパス（東京大学生産技術研究所）
Ａｎ棟 コンベンションホール
（地図：http://www.iis.u-tokyo.ac.jp/access/access.html）■主 催：東京大学生産技術研究所 都市基盤安全工学国際研究センター
特定非営利活動法人 日本都市計画家協会■入場無料、要申し込み※終了後（17:30～）懇親会（会費制 2000 円）を開催‫ޞࡓ࡜ࠣࡠࡊޝ‬１．開会挨拶 目黒公郎（東京大学生産技術研究所 都市基盤安全工学国際研究センター長・教授）
２．趣旨説明 加藤孝明（東京大学生産技術研究所 都市基盤安全工学国際研究センター 准教授）
３．被災地の復興の現状※講演者等は予定。変更可能性有り
岩手県大槌町臂
徹（一社 おらが大槌夢広場）
岩手県大船渡市
佐藤隆雄（(独)防災科学技術研究所）
宮城県女川町久坂斗了（UR 都市機構 震災復興支援室宮城震災復興支援事務所）
福島県新地町
井上忠佳（NPO 日本都市計画家協会）
岩手・宮城県の漁村 高鍋剛（（株）都市環境研究所）
４．パネルディスカッション・意見交換
コーディネーター 加藤孝明
パネリスト 臂、佐藤、久坂、井上、高鍋、渡会清治（NPO 日本都市計画家協会副会長）
５．閉会挨拶 小林英嗣（NPO 日本都市計画家協会会長）‫ޝ‬໧วࠊߖ࡮↳ߒㄟߺ‫ޞ‬
申込み・問い合わせ：吉本英子（東大生研 ICUS） E-mail: yosimoto@iis.u-tokyo.ac.jp
TEL：03-5452-6472，FAX: 03-5452-647６― 275 ―

112 名の参加!"の$%&'()*+,-./0123456「)*の89像;<え>?
「右肩下がりの時代における超広域巨大災害」からの復興・再生は，世界で初めての経験である．
被災地では，復興を支える社会のしくみが依然として混沌とする中，復興へ向けての模索が続けられている．被災地の再生，復興をすすめていくためには，社会に存在する様々な経験，知を共有し，そこでの議論を通して得た知見を復興の現場へフィードバックしていくことが大切と考える．
第２回シンポジウムでは，第１回における個々の現場での課題の議論をふまえつつ，被災から１年余を経ているにもかかわらず殆ど語られていない「復興の全体像」について，かつての国土計画・
広域圏計画等の経験，阪神淡路大震災からの復興の経験を持つ先行世代の経験を後続世代に伝え，共有することを目的として開催する．
※【経験の共有】震災復興・連続シンポジウムは，日本都市計画家協会と東京大学生産技術研究所 ICUS との共同主催で開催します．

《開"#$%■日 時：平成２４年６月１６日（土） １５:３0～17:30 （1５:０0 開場）■会 場：建築家会館大ホール（東京都渋谷区神宮前 2-3-1）
アクセス：http://www.kenchikuka-kaikan.jp/index_map.html■主 催：特定非営利活動法人 日本都市計画家協会
東京大学生産技術研究所 都市基盤安全工学国際研究センター■入場無料、要申し込み※終了後（17:30～）懇親会（会費制）を開催《プ'()*%
１．開会挨拶 小林英嗣（NPO 日本都市計画家協会会長）
２．趣旨説明 渡會清治（NPO 日本都市計画家協会副会長）
３．基調講演：大村虔一：アーバンデザイナー、元東北大学教授
４．パネルディスカッション
大村虔一：アーバンデザイナー、元東北大学教授
土井幸平：都市計画家、元大阪市立大学教授
小林郁雄：日本都市計画家協会理事・関西支部長，神戸山手大学教授
加藤孝明：日本都市計画家協会理事，東京大学生産技術研究所都市基盤安全工学国際研究センター准教授
コーディネーター 姥浦道生：東北大学大学院准教授
５．閉会挨拶 石川岳男（NPO 日本都市計画家協会副会長）《問,-.・0123%
申込み・問い合わせ：（ＮＰＯ）日本都市計画家協会― 276 ―

事務局

E-mail:：info@jsurp.net

■パネリストプロフィール◆大村虔一（おおむらけんいち）
アーバンデザイナー、NPO 都市デザインワークス顧問、NPO とうほく
PPP・PFI 協会会長、元東北大学教授、元宮城大学副学長、前宮城県教育委
員会委員長、前宮城県都市計画審議会会長
193８年生まれ。東京大学大学院建築学専攻終了。
（株）都市計画設計研究
所を南條道昌氏、土井幸平氏とともに 1967 年に設立。199６年東北大学教授に就任。
宮城県復興まちづくり検討会委員、名取市新たな未来会議会長、亘理町震災復興会議会長として東日本大震災復興まちづくりに尽力◆土井幸平（どいこうへい）
都市計画家、元大阪市立大学教授、元大東文化大学環境創造学部長
東京都豊島区都市計画審議会会長
1939 年生まれ。東京大学大学院建築学専攻終了。
（株）都市計画設計研究
所を南條道昌氏、大村虔一氏とともに 1967 年に設立。1993 年、大阪市立大学工学部教授、大阪府等の都市計画審議会委員などを歴任。阪神・淡路大震災の際、兵庫県復興１０年委員会委員として復興まちづくりに尽力。
◆小林郁雄（こばやしいくお）
神戸山手大学教授、まちづくり株式会社コー・プラン アドバイザ、阪神大
震災復興市民まちづくり支援ネットワーク世話人
1944 年生まれ。神戸大学卒、大阪市大大学院了。(株) 都市･計画･設計研究所を経て、まちづくり株式会社コー・プランを設立、代表取締役を経て現職。阪神・淡路大震災の際、民間プランナーを中心とした「阪神大震災
復興市民まちづくり支援ネットワーク」を立ち上げ、復興まちづくりの支援活動に尽力。
NPO 日本都市計画家協会理事・関西支部長◆加藤孝明（かとう たかあき）
東京大学生産技術研究所都市基盤安全工学国際研究センター准教授
1967 年生まれ。東京大学工学部都市工学科卒業、東京大学大学院工学系
研究科都市工学専攻助手・助教を経て 2010 年 4 月より現職。東京都防災会議地震部会委員他、専門は、都市計画、都市防災、地域安全システム学等。復興準備（復興イメトレ）、四川地震での復興計画支援等の研究を行う。NPO 日本都市計画家協会理事、災害復興まちづくり特別委員会委員長。
◆姥浦道生（うばうらみちお）
東北大学大学院工学研究科都市・建築学専攻准教授
専門は都市計画・建築計画
1973 年生まれ、東京大学法学部第一類を経て東京大学大学院工学系研究科都市工学専攻博士課程満期退学。豊橋技術科学大学、大阪市立大学助手
を経て 2008 年より現職。
塩釜市震災復興会議委員、名取市新たな未来会議委員、宮古市国交省調査監理委員等― 277 ―

【経験の共有】�災復興・��シン�ジ��第３回（第 2４回 ICUS �ー�ン�クチャー）「福島の現状：復興課題を共有する」
原発災害からの復興は初めての経験である．被災地では，様々な悩み，思いが交錯する中，結果として復興の議論がローカルなものになっているように見受けられる．この未経験の課題に対し適
切な解決策を得るためには，社会の英知を集めて取り組む必要がある．そのためには，関心と支援のすそ野を拡げ，支援のネットワークを形成していく必要がある．
第３回は，福島の現状を理解し，復興課題を共有することを目的とし開催し，福島支援を志向する専門家のネットワークの形成を図るきっかけとしたい。
※【経験の共有】震災復興・連続シンポジウムは，東京大学生産技術研究所 ICUS と日本都市計画家協会の共同主催で開催します．

《����》■日■会

時：平成２４年７月２８日（土） 13:３0～17:30 （1３:０0 開場）
場：東京大学・駒場リサーチキャンパス（東京大学生産技術研究所）
Ａｎ棟 コンベンションホール
（地図：http://www.iis.u-tokyo.ac.jp/access/access.html）■主 催：東京大学生産技術研究所 都市基盤安全工学国際研究センター
特定非営利活動法人 日本都市計画家協会■入場無料、要申し込み※終了後（17:30～）意見交換会（会費制）を開催《�����》１．開会挨拶 目黒公郎（東京大学生産技術研究所 都市基盤安全工学国際研究センター 長 教授）
２．趣旨説明 加藤孝明（東京大学生産技術研究所 都市基盤安全工学国際研究センター 准教授）
３．福島県の復興の現状（国，県の取り組み，双葉８町村の現状）
安齋睦男（福島県企画調整部避難地域復興局次長）
４．浪江町の現状
玉川啓（浪江町復興推進課 主幹）
５．被災地の暮らしの現状
高村美春（南相馬市民）
７．NPO の役割と今後（仮）星野珙二（福島大学名誉教授、ふくしま NPO ネットワークセンター 理事長）
６．福島の復興課題と今後
鈴木浩（福島大学名誉教授，福島県復興ビジョン策定委員会委員長）

８．パネルディスカッション・意見交換
コーディネーター：加藤孝明（東京大学生産技術研究所 都市基盤安全工学国際研究センター 准教授）

９．閉会挨拶

渡会清治（NPO 日本都市計画家協会副会長）※講演者等は予定。已む無く変更の場合はご了承ください《����・����》申込み・問い合わせ：吉本英子（東大生研 ICUS） E-mail: yosimoto@iis.u-tokyo.ac.jp
TEL：03-5452-6472，FAX: 03-5452-647６― 278 ―

!"#$%&'()*+,-./0123456「89か;<北>?しA<南CD備FGH
我が国は各種の巨大災害に見舞われる国であるが、近年では、阪神淡路大震災、中越沖地震、東日本大震災を経験してきた。そして今、首都直下地震、南海トラフ巨大地震の発生が予測される状
況である。
災害にはそれぞれ特性があり、各災害復興の経験が直ちに今後発生する巨大災害の復興に適用できるわけではないが、復興にかかるこれまでの我が国の経験のストックを振り返り、今後発生する巨大災害で想定される被害、今後予測される社会トレンド、現状の政治経済状況等を勘案し、今、東南海地域が備えておくべきこととして、プランナーの役割及びそれを支える社会的仕組みは何かを討議する。
※【経験の共有】震災復興・連続シンポジウムは，日本都市計画家協会と東京大学生産技術研究所 ICUS との共同主催で開催します．

《開"#$%■日 時：平成２４年９月２９日（土） 15:45～17：55■会 場：デザイン・クリエイティブセンター神⼾（JSURP 主催「全国まちづくり会議 2012 in KOBE」開催会場内）■主 催：特定非営利活動法人 日本都市計画家協会
東京大学生産技術研究所 都市基盤安全工学国際研究センター■入場無料《プ'()*%
１．趣旨説明：加藤孝明（東京大学准教授）
２．基調講演「神戸から中越、そして東北へ～我々は何を学んだか」
鳴海邦碩（大阪大学名誉教授）
３．
「東北、陸前高田での経験から学ぶ 」中井検裕（東京工業大学教授）
４．パネルディスカッション
コーディネーター：加藤孝明
パネリスト：越山健治（関西大学），佐々木晶二（内閣府），中井検裕，鳴海邦碩
５．まとめ：加藤孝明（５分）《問,-.・0123%
申込み・問い合わせ：（ＮＰＯ）日本都市計画家協会 事務局― 279 ―

E-mail:：info@jsurp.net

!"#$%&'()*+,-./0123456
74 256 ICUS 89:/;<=>9?

「AB陸D#現FG課IJ市LM線OPQ
被災集落では，順次，防災集団移転事業等の事業決定が進み，復興・再生にむけて次のフェーズに入りつつある．復興計画策定以降，粛々と行政手続きが進む中，市民レベルでは今後の地域づくりの担い手が現れ，復興まちづくりに向けた多様な取り組みが現れている．その動きは，次の時代の地域づくりの先行モデルにつながるであろう．
第 5 回【経験の共有】震災復興・連続シンポジウムは，市民に焦点をあてる．宮城県南三陸町から 4 名の方を招き，市民目線から南三陸町の復興の現状と課題について情報提供をいただき，現状を共有した上で，今後の復興まちづくりの方向性について議論を深める．各地で進められている市民レベルの復興まちづくりにむけた議論，その中での悩み，新たな試みを被災地全体で共有することによって，新たな工夫を生み出す契機となることを期待する．
専門家のみならず，一般市民の参画を期待します．
※【経験の共有】震災復興・連続シンポジウムは，東京大学生産技術研究所 ICUS と日本都市計画家協会の共同主催で開催します．

《開"#$%■日 時：平成２５年３月２４日（日） 1０:０0～1３:０0 （９:３0 開場）■会 場：東京大学・駒場リサーチキャンパス（東京大学生産技術研究所）
Ａｎ棟 301/302 大会議室
（地図：http://www.iis.u-tokyo.ac.jp/access/access.html）■主 催：東京大学生産技術研究所 都市基盤安全工学国際研究センター
特定非営利活動法人 日本都市計画家協会■入場無料、要申し込み《プ'()*%
１．趣旨説明 加藤孝明（東京大学生産技術研究所 都市基盤安全工学国際研究センター 准教授）
２．パネルディスカッション・意見交換
コーディネーター：渡辺喜代美（広域ゼロメートル市街地研究会，ア！安全快適街づくり）
コーディネーター：高鍋剛（NPO 都市計画家協会理事）
小野寺寛：南三陸町 すばらしい歌津をつくる協議会 会長
後藤一磨：南三陸町 宮城大学「地域連携センター」復興まちづくり推進員
佐藤徳郎：南三陸町 仮設中瀬町自治会長・集落全員同行避難仮設入居実践の区長
内海明美：南三陸町 仮設田尻畑自治会長・「ガレキの中にできたカフェ」の担い手※冒頭に南三陸町の復興の現状についての説明あり．
３．閉会挨拶
渡会清治（NPO 日本都市計画家協会副会長）《問,-.・0123%
申込み・問い合わせ：吉本英子（東大生研 ICUS） E-mail: yosimoto@iis.u-tokyo.ac.jp
TEL：03-5452-6472，FAX: 03-5452-647６― 280 ―