1/ 44

Spatial Distribution Monitoringof Isolated Dwelling
Using Building Micro Geodata건물 마이크로 지오 데이터를 이용한원격 주택의 분포 파악

Yuki AKIYAMA(The Univ. Tokyo)
Chiaki M. AKIYAMA (Univ. of Tsukuba)

Today’s Contents

2/ 44

1. Background and objective
2. Data development of isolated dwelling inJapan
3. Results: distribution of isolated dwelling
4. Trial calculation on
location optimization of isolated dwelling
5. Summary and future work
Acknowledgments:
This research is supported by the Grant-in-Aid for Scientific Research-KAKENHI(15K12453: Geography) and by the collaborative research budgets of Research Center
for San-En-Nanshin Regional Collaboration, Aichi University (2018-06). In addition, theresidential map used in this presentation was received from the CSIS collaborative
research utilization system (JoRAS) in cooperation with the University of Tokyo Spatial
Information Science Research Center (CSIS) collaborative research (No. 122) under theprovision of housing maps throughout Japan.

1. Background and objective

3/ 44

1. Background and objective

4/ 44Japan is one of the TOP
aging country in the world.

Source: Cabinet Office, Japan (2017) Annual Report on the Aging Society: 2017.

1. Background and objective

5/ 44• Young generation moves to more urbanizedarea than their hometown.

• At origin of migrants, aging anddepopulation are accelerating…
• Especially at hilly and mountainous areas
and remote island areas.

1. Background and objective

6/ 44

Maruyama, Kiwa-cho, Kumano-city, Mie prefecture

Photo by C. Akiyama(May. 2017)

Isolated detached house that does not have neighboring
residents in the vicinity, is named as “isolated dwelling”

1. Background and objective

7/ 44

Isolated dwelling is
spatially isolated from other dwellings.
Future concerns:

・Decrease in the cost effectiveness of infrastructure
maintenance・Increase the risk of disaster> It is difficult to get help from others because of no neighborhoods
・Isolated dwelling would be “vacant house” ?
Vacant house is big issue in the current Japan.

It is important to grasp spatial distribution of isolated
dwelling in national scale and to address the future picturein the sense of sustainable municipality management.

1. Background and objective

8/ 44

Marginal settlement in remote island
・ Deserted village in mountainous area (Sakaguchi, 1975)
・ Geographical characteristics of non-resident settlementsof hilly mountainous regions in Japan (Sakuno, 2013)

However, these researches are case study of a settlement/
municipality…Few research works on national scale analysis↓

National-scale research・Classification of mountainvillage using existed statistics(Okahashi, 1986)

・Distribution change of settlement
using topographical maps
(Kaneki, 2003)

Resolution is relatively macro-size aggregated unit:
municipalities, or settlement

There is no study to grasp nationwide spatial
distribution of isolated dwelling by building unit!

1. Background and objective

9/ 44

Objective1) to grasp the spatial distribution of isolated
dwellings throughout Japan2) to compare the distribution of isolated
dwellings at two time points so that the spatial
distribution of increase and decrease of isolatedhouses, and
3) to estimate the economic burden of local
governments by relocation promotion for
isolated dwellings in the future, and examined
the possibility of site location optimization.

Today’s Contents

10/ 44

1. Background and objective
2. Data development of isolated dwelling inJapan
3. Results: distribution of isolated dwelling
4. Trial calculation on location optimization ofisolated dwelling
5. summary and future work10

2. Data development ofisolated dwelling in Japan

11/ 44

Flow of data development
Digital residential map(whole of Japan)
Building Micro Geodata(Appr. Num. 100 Millions)
Residential Micro Geodata（Appr. Num. 27 Millions)
Isolated dwelling point data
(Appr. Num. 15 Thousands)
112. Data development ofisolated dwelling in Japan

12/ 44

Digital residential map(whole of Japan)

Building Micro Geodata(Appr. Num. 100 Mill.)
Residential Micro Geodata（Appr. Num. 27 Mill.)
Isolated dwelling point data
(Appr. Num. 15 Thou.)

Building Polygon©OpenStreetMap cotributors / CC-BY-SA

Source data: Digital residential map
Product of12

2. Data development ofisolated dwelling in Japan

13/ 44

Digital residential map(whole of Japan)

Building Micro Geodata(Appr. Num. 100 Mill.)
Each polygon
showsbuilding shape

Residential Micro Geodata（Appr. Num. 27 Mill.)
Isolated dwelling point data
(Appr. Num. 15 Thou.)

Building Polygon©OpenStreetMap cotributors / CC-BY-SA

Source data: Digital residential map
Product of13

2. Data development ofisolated dwelling in Japan

14/ 44

Digital residential map(whole of Japan)

Building Micro Geodata(Appr. Num. 100 Mill.)
Each polygon
showsbuilding shape

Residential Micro Geodata（Appr. Num. 27 Mill.)
Isolated dwelling point data
(Appr. Num. 15 Thou.)

Building Polygon©OpenStreetMap cotributors / CC-BY-SA

Thanks to Joint Research Program
No.122 at,UTokyo to support
to use ZENRIN digital residential map.

14

2. Data development ofisolated dwelling in Japan

15/ 44

Digital residential map(whole of Japan)

Building Micro Geodata(Appr. Num. 100 Mill.)
Residential Micro Geodata（Appr. Num. 27 Mill.)
Building point data

Isolated dwelling point data
(Appr. Num. 15 Thou.)

Building Polygon©OpenStreetMap cotributors / CC-BY-SA

Convert ALL building polygons to point(Appro. Num. 100 Millions) from wholeof Japan (appr. 1800 municipalities)15

2. Data development ofisolated dwelling in Japan

16/ 44

Digital residential map(whole of Japan)

Building Micro Geodata(Appr. Num. 100 Mill.)
Residential Micro Geodata（Appr. Num. 27 Mill.)

Residential point data
Building point data

Isolated dwelling point data
(Appr. Num. 15 Thou.)

Building Polygon©OpenStreetMap cotributors / CC-BY-SA

Select RESIDENTIAL USE building
point (Appr. Num. 27 Mill.) from
Building Micro Geodata.

2. Data development ofisolated dwelling in Japan
Digital residential map(whole of Japan)

Building Micro Geodata(Appr. Num. 100 Mill.)

17/ 44Def. of Isolated dwelling
There are not residentialbuilding in walking distance.
・Walking distance is 500m inroad network distance(Nagata , 2015)

Residential Micro Geodata（Appr. Num. 27 Mill.)・Search nearest residential
point from each residential
point within 500 m. If there is
Isolated dwelling point datano point, the residential point(Appr. Num. 15 Thou.)is defined as isolated dwelling.

2. Data development ofisolated dwelling in Japan

18/ 44

Flow of data development
Digital residential map(whole of Japan)

Digital residential map(whole of Japan)

Building Micro Geodata(Appr. Num. 100 Millions)

Building Micro Geodata(Appr. Num. 100 Millions)

Residential Micro Geodata（Appr. Num. 27 Millions)

Residential Micro Geodata（Appr. Num. 27 Millions)

Isolated dwelling point data
(Appr. Num. 15 Thousands)

Isolated dwelling point data
(Appr. Num. 15 Thousands)

Year of 2009

Year of 2014

Spatial temporal changes
between 2009 and 2014 in throughout of Japan18

Today’s Contents

19/ 44

1. Background and objective
2. Data development of isolated dwelling inJapan
3. Results: distribution of isolated dwelling
4. Trial calculation on location optimization ofisolated dwelling
5. summary and future work19

3. Results:

20/ 44

Distribution of isolated dwelling
Year:2009

Year:2014

Isolateddwelling

Isolateddwelling

Num. ofisolated dwellingin Japan:
17,106 in 2009
15,052 in 2014

Total number ofisolated dwellingdecrease in Japan.

3. Results:

21/ 44

Distribution of isolated dwelling in municipality level
Number of isolated
dwelling (2009)

Number of isolated
dwelling (2014)0
1 - 10
11 - 25
25 - 50> 50

0
1 - 10
11 - 25
25 - 50> 50

Both 2009 and 2014,
Many isolated
dwellings are in- North and East of
Hokkaido,- Mountainous areasin Tohoku, Chugoku,
Shikoku, and Kyusyu
Regions.

3. Results

22/ 44

Percentage of isolated dwelling in municipality level
Percentage ofisolated dwellingin 2009 (%)

0.0
0.0 - 1.0
1.0 - 2.5
2.5 - 5.0
> 5.0Percentage ofisolated dwellingin 2014 (%)

0.0
0.0 - 1.0
1.0 - 2.5
2.5 - 5.0
> 5.0Highest % is
10.46 % at
Toyokoro-cho,
Hokkaido
Highest % (except
Hokkaido) is
6.08 % at Shiibason, Miyazaki

3. Results

23/ 44

Increase/decrease of percentage of isolated dwelling
Percentagechange (%)≦ -1.0-1.0 - 0.0
0.0 - 1.0
1.0 - 2.5
> 2.5

Top 10 municipalities in large
increase/decrease of percentage of isolated
dwelling (2009-2014)
Municipality
Horonobe, Hokkaido
Horokanai, Hokkaido
Koshimizu, Hokkaido
Shiiba, Miyazaki
Kitadaito, Okinawa
Satoma, Hokkaido
Teshio, Hokkaido
Minamidaito, Okinawa
Okawa, Kochi
Oketo, Hokkaido

Islated dwelling rate
2009
2014 Difference
0.00 8.39
8.39
0.00 7.23
7.23
5.04 8.51
3.47
3.24 6.08
2.84
0.00 2.74
2.74
3.51 5.75
2.23
6.44 8.51
2.07
1.27 2.94
1.67
1.73 3.03
1.30
3.79 4.78
0.99

3. Results

24/ 44

Scattering plot for北海道
aging ratemunicipality
level中四国
and isolated
dwellingrate
東北 in関東中部近畿
九州
沖縄
Percentage of isolated dwelling (2014) [%]

12
10
12

8
12

12

北海道 10 東北

12

北海道

10 東北

北海道

10

6
4

12

2

12

0

10

北海道

10

12

5

8

東北

10

東北

関東
8

中部

12

北海道

東北
関東
Tohoku

中部

北海道

東北

関東
Kanto 中部

近畿

10東北

関東

中部
Chubu近畿

中四

関東

中部

近畿
Kinki 中四国

九

中部

近畿

中四国
九州
Chushikoku

沖

8

関東

中部

近畿
6

中四国

九州
Kyusyu沖縄

6近畿

中四国

九州

沖縄
Okinawa

4

6

8
10

関東

8

8

4

6
15

関

20 4

25

30

2

35
40
6
2 in municipal level
8
Aging ratio(2010)
[%]
4
0
6
2
8
0
5
4
0
6 rate ≠ High percentage
High aging
of isolated dwelling
2
0
5
10
4
Regional Characteristics
0
6
2
0
5
10
15
4
0

10

0

北海道

北海道
東北
Hokkaido

45

50

10

15

15

20

20

25

3. Results

25/ 44

Relationships between “aging ratio” and “changes inpercentage of北海道
isolatedin municipallevel
東北 dwelling”
関東
中部
近畿
中四国
九州
沖縄
Increase/decrease of percentage
of isolated dwelling (2009 ~ 2014) [%]
12
10

8

10

北海道
東北 近畿
関東 中四国中部
関東中部
Hokkaido
Kinki

九

東北
関東
Tohoku
中部
近畿

中部
近畿
中四国
九州
Chushikoku

中沖

北海道 中部
東北 近畿
関東
中部
Kanto
関東
中四国

近畿 沖縄
中四国
九州
Kyusyu10東北
北海道 中部
中部
近畿
Chubu
関東
近畿関東 中四国
九州

中四国
九州
沖縄
Okinawa

北海道

8
6
4

12

12

10
12

2
0

10
0

-2 8
-4

北海道

8

5 10

68

6

12

北海道

北海道

東北
12

10
12
東北

12
東北 北海道
関東

10

8

8
10
106

8

15

8

東北

20

6

25

30

35

40

45

6
46

4

4
6
2 [%] in municipal level
24
Agingratio(2010)42
24
40between “aging ratio” and02
No significant
relationships
2
15
20
0
5
100
155
2010
25
30
0
0
“changesin percentage of isolated dwelling”.
2
2
010
515
10
15
20
25
0
5
20
25
30
35
0
0
-6

50

46

25
35
30
40

3. Results

26/ 44

Let’s see relationships bet. isolated dwelling andpopulation using pinpoint residential building data×=

Calculate“aging rate” and“single householdrate” in eachresidential point

Micro Population Census(2010）

Isolated dwelling
point data(2014)

Estimated residence/household
number for each building point
based on population census
and digital residential map（Akiyama et al., 2013）

3. Results

27/ 44Compare “aging rate” and “single household rate” forisolated dwelling and non-isolated dwelling
No. ofresidents
Isolateddwelling

31,856

No. ofSingleSingleAging rate
No. ofresidents
Household Household[%] Households
over 65
no. rate [%]10,819Non-isolated 126,249,157
24,914,140
dewlling

33.96

8,686

847

9.75

19.73 25,536,883 2,606,494

10.21

・About 34 % of residents in isolated dwellings in Japan are
High risk in natural disaster/High possibility
over 65 years old
to be vacant house in the future・Single Household rates [%] are similar values:
Many (young) single household in urban area

Today’s Contents

28/ 44

1. Background and objective
2. Data development of isolated dwelling inJapan
3. Results: distribution of isolated dwelling
4. Trial calculation on location optimization ofisolated dwelling
5. summary and future work2829/ 44
4. Trial calculation on
location optimization of isolated dwelling

Hypothesis: If the residents living in isolated dwellingmoves to city center, how much can they save
lifeline expenditure of the municipality?
“Urban Facility Location Plan” has similar concept.
・Amendment to Act on Special Measures concerning Urban Reconstruction in 2014
→Each municipality can develop "Urban Facility Location Plan".
→For reforming to compact city, the plan designs attraction district to attract
urban facilities(medical care, welfare, commercial) and to create public
transportation network.

Hub center

City center

Rail way

Ministry of Land, Infrastructure,
Transport and Tourism(MLIT)

30/ 44
4. Trial calculation on
location optimization of isolated dwelling

Hypothesis: If the residents living in isolated dwellingmoves to city center, how much can they save
lifeline expenditure of the municipality?
If isolated dwelling disappeared…

・Save lifeline expenditure(water and municipal road maintenance and management etc…)
・The cost of expected future lifeline expenditure forisolated dwelling can be assigned to relocation promotion expenses

・We Estimate-Lifeline expenditure for isolated dwellings
for the future in each municipal level-Relocation promotion expenses for each isolated dwelling30

31/ 44
4. Trial calculation on
location optimization of isolated dwelling

Estimate minimum annual public-work costfor isolated dwelling
Lifeline expenditure is cost ofminimum public-works for isolated dwelling:water service and municipal road to isolated dwellingci  d i w  r1  r 2[JPY/year]where
ci :minimum annual public-work cost for isolated dwelling (i) [JPY/year]
di :distance from isolated dwelling(i) to nearest neighborhood [m]w :annual replacement cost of water supply pipe per meter [JPY/m/year]
r1:annual maintenance cost of municipality roads(cleaning fee for road surface) per meter [JPY/m/year]
r2:maintenance cost of municipality roads(road construction expenses) per meter [JPY/m/year].

32/ 44
4. Trial calculation on
location optimization of isolated dwelling

Estimate minimum annual public-work costfor isolated dwellingci  d i w  r1  r 2Calculation method of w，r1，r2

・W: annual replacement cost of water supply pipe per meter [JPY/m/year]= replacement of water pipe (Ozeki et al. 2009) ✕replacement rate JWWA, 2016)= 32,147[JPY/m] * 0.79 % = 253.96 [JPY/m/year]
・r1: cleaning fee for municipal road surface [JPY/m]= cleaning fee for road surface (Ozeki et al. 2009) ✕mini. road width(Mlit, 1970)= 145[円/㎡] ✕ 3[m]＝435[円/m]regular updating fee convert
into annual average cost.

・r2: road construction expenses [JPY/m]={road maintenance (every 10 yr) /10+ replacement (every 20 yr)/20(Ozeki et al. 2009)} × mini. road width(Mlit, 1970)={(1,526[JPY/㎡] /10)+(3,406[JPY/㎡] /20)}✕3[m]=968.7 [円/m]33/ 44
4. Trial calculation on
location optimization of isolated dwelling

Estimate minimum annual public-work costfor isolated dwellingci  d i w  r1  r 2Cost foreach isolated dwelling= 1,657.66 [JPY/m/year]×di [m]Cj :Total minimum cost for isolated dwellings of municipality (j)
n

n

n

k 1

k 1

k 1

C j  y  ck  y  (1657.66d k )  1657.66 y  d k

Cost forEach municipality

Where:
y: number of years to maintain isolated dwellingn: the number of isolated dwelling in municipality j34/ 44
4. Trial calculation on
location optimization of isolated dwelling

Supposition of relocation promotion expenses

Mj :Total relocation promotion expense of municipality (j)𝑀𝑗 = 𝑛𝑗 ⋅ 𝑚j
Where:
nj :the number of isolated dwelling in municipality j
mj :relocation promotion expensefor each isolated dwelling household in municipality j(Set m a lump sum: 2.5, 5, 10, 25, 100 million JPY)

Compare Mj and Cj
How many years does it take ?

Mj

Cj

Mj

Cj

35/ 44
4. Trial calculation on
location optimization of isolated dwelling
Estimatedtotal cost [bln. JPY]

0.0
0.0-0.1
0.1-0.5
0.5-1.0
1.0-2.5
2.5-

Average cost[mln. JPY/ household]

0.0
0.0-1.0
1.0-2.0
2.0-3.0
3.0-5.0
5.0-

National total of
estimated
minimum
annual publicwork cost
：21.77 bln JPY

36/ 44
4. Trial calculation on
location optimization of isolated dwelling
Estimatedtotal cost [bln. JPY]

0.0
0.0-0.1
0.1-0.5
0.5-1.0
1.0-2.5
2.5-

Average cost[mln. JPY/ household]

0.0
0.0-1.0
1.0-2.0
2.0-3.0
3.0-5.0
5.0-

National total of
estimated
minimum
annual publicwork cost
：21.77 bln JPY
Most expensive cost:
5.58 Bln JPY
at Betsukai-cho, Hokkaido
No. of Isolated dwelling:300

Most expensive cost(ex.Hokkaido):1.87 Bln JPY at
Iwaki city, Fukushima
No. of Isolated dwelling: 146

37/ 44
4. Trial calculation on
location optimization of isolated dwelling
Estimatedtotal cost [bln. JPY]

0.0
0.0-0.1
0.1-0.5
0.5-1.0
1.0-2.5
2.5-

Average cost[mln. JPY/ household]

0.0
0.0-1.0
1.0-2.0
2.0-3.0
3.0-5.0
5.0-

Average estimatedminimum annual
public-work cost/isolated dwelling：1.446 mln JPY
Most expensive average
cost: 17.77 mln JPY at
Tokashiki-mura, Okinara
No. of Isolated dwelling:1
Most expensive average cost
(multiple isolated dwelling):6.23 mln JPY at

Kamikitayama-mura, Nara
No. of Isolated dwelling: 3

38/ 44
4. Trial calculation on
location optimization of isolated dwelling
Relocate promotion expenses for each isolated dwelling (JPY)
mi =

100万円
1100万円
mln.

2.5
mln.
250万円
250万円

500万円
5500万円
mln.

1000万円
10
mln.
1000万円

2500万円
25
mln.
2500万円

5000万円
50
mln.
5000万円

1億円
100
mln.
1億円

Number of municipalities which achieved
relocation promotion expenses recovery

1400
1400
1200
1200
1000
1000

800
800
600
600

Mj

400
400

Cj

200
200
0

0
0

0

5

5

10
10

15
15

20
20

25
25

30
30

35
35

40
40

Elapsed year since the promotion started [Years]

45
45

39/ 44
4. Trial calculation on
location optimization of isolated dwelling
Relocate promotion expenses for each isolated dwelling (JPY)
mi =

100万円
1100万円
mln.

2.5
mln.
250万円
250万円

500万円
5500万円
mln.

1000万円
10
mln.
1000万円

2500万円
25
mln.
2500万円

5000万円
50
mln.
5000万円

1億円
100
mln.
1億円

Number of municipalities which achieved
relocation promotion expenses recovery

1400
1400 1 mln. 2.5 mln. 5 mln.
→2yrs

→4yrs

→8yrs

25 mln.
→ 30 yrs

10 mln.
→ 13 yrs

1200
1200
1000
1000

800
800

50 mln→ 61 yrs

600
600
400
400
200
200
0

0
0

100 mln.
→ 121 yrs
0

5

5

10
10

15
15

20
20

25
25

30
30

35
35

40
40

Elapsed year since the promotion started [Years]

45
45

40/ 44
4. Trial calculation on
location optimization of isolated dwelling

0 (first year)
1-3
3-5
5 - 10> 10

Year of relocation promotion
cost recovery achieve

Year of relocation
promotion cost
recovery achieve(year)[year]
13
12
11
10
9
8
7
6
5
4
3
2
1
0
0

1

2

3

4

Estimated total expenses (Cj)*relocation promotion
expense (mi)= 10 mln. JPY

5

6

7

[0.1 bln. JPY]

If all isolated dwelling residents agree tomove to city center to get 10 mln. JPY
relocation promotion expense, manymunicipalities expect to be compact city
within 10 years.

41/ 44
4. Trial calculation on
location optimization of isolated dwelling

Isolated dwelling should be excluded?

NO WAY!!

There are good practices to sustainable life style for isolated dwellings.

Ex. Satoyama* in Japan
Hilly and Mountainous areas in Switzerland*one of Japan’s traditional agricultural landscapes
Small community has fostered cultural and traditional society,harmonious human-nature interactions, ecotourism resources…
Heidi, Girl of the Alps

Maienfeld in Switzerland

It needs to discuss from themultiple view points, not only
lifeline cost but also ecotourism,
cultural and traditional society
to keep freedom of residence.

Today’s Contents

42/ 44

1. Background and Objective
2. Data Development of Isolated Dwelling inJapan
3. Results: distribution of Isolated dwelling
4. Trial calculation on Location Optimization of
Isolated dwelling
5. Summary and future work42

５. Summary and future work

43/ 44

Summary-Developed isolated dwelling database using building
MGD for all of Japan.
-Mapped distribution of Isolated dwelling, relationships
isolated dwelling and aged rate and so on.
-Estimated both relocation promotion expenses andlife line maintenance cost for isolated dwellingfor each municipality

Future work
-Examination method for isolated dwelling from digital
residential map (such as home office, guest-house,…)-Calculation of relocation promotion expenses according
to isolated distance-Interview with municipal officers to check our estimation
result44/ 44

Thank you for your kind attention!
How about this kinds of issues in Korea?
경청해 주셔서 감사합니다!

Related papers
Akiyama, M,C., Akiyama, Y., Spatial Distribution Monitoring of Isolated Dwelling Using
Building Micro Geodata and Its Issue, International Conference on Spatial Analysis andModeling (SIM 2018), B-2-5, 2018. http://ua.t.u-tokyo.ac.jp/sam2018/abstract/B-2-5
秋山祐樹・秋山千亜紀，建物マイクロジオデータを用いた全国の孤立住宅の分布把握，日本地理44
学会発表要旨集, 93, 217, 2018.