Annual Report 2016, Volume 22࠯঺ ᵐᵖ ࠰ࡇҘᓶ‫ܖٻ‬
࿢‫ؾ‬ἼἴὊἚἍὅἉὅἂᄂᆮἍὅἑὊ
࠰‫إ‬ίᇹ ᵐᵐ ӭὸɉȲɛɅ
ā൦4ࡖ஑༃๱ɁȜɥ਱༃๱Ă৊ၕɅɢɤो67ॣĪਡ໘59ॣĂਡ੫ǔॣīɈࢼວᆀᅙॸ࢞ɬ഼൥ߔɞॸ࢞
࡙࠲ɂଌૈȱĂိ౰3:༃ǎॢɅާ੓ȯɦȹࢼວᆀᅙĆࢼວᆀᅙॸ࢞Ɉ౰‫ݪ‬ၡਠ‫ޏ‬ɁȜɥĶ൦2:‫ ޑ‬DFSfTࠞࣃ˂ʺĜʠʓˋʏˋʈʏˋʵʐɾʸķɅȤȞɀĂ27ॣɈ৏ຢཡ࿍Ă38ॣɈʵʑʗĜཡ࿍ɬ਄ȞɘȱȹăȭɦɣɈॣౘɉࢼວᆀᅙĆࢼວॸ࢞ࢪ๘ɂȱɀɈᄜߠɬ‫ݪ‬ȹȱɀȞɥȭɂɈ௠ɂ঒ȢɘȳăāDFSfT Ȧอࢷȳɥಇો࡜௣‫ܒ‬౳ĶɌɘɩɤķɈʟĜʗɉਡ໘ެɈഽȩɈॸ࢞ଞɅᆀᅙȯɦĂိ౰39༃๱ɉߔެȥɣ711჈ॣɬ‫ܛ‬Ȣɥʘɾˋ˅ĜʡౘɬࡥሃȱɘȱȹăɘȹĂ‫ܟ‬ှ༜ਗ౰ާ৏˄ĜʘĜɈާཡɉĂຎʓˋʗĜɅȤȫɥ຾૵Ɉࡳ୹๐ާɁȜɤĂိ౰39༃๱ɅȤȞɀɜ൤ሕਡ‫ۧݦ‬හʓˋʗĜɂਡ੫ି൵ૢࣞ
ɬำय़ȳɥɅ૖ɤɘȱȹăā৩ɅĂຎʓˋʗĜɈࢼວᆀᅙॸ࢞ȥɣ౺ɘɦȹ౰‫ݪ‬Ɉ‫ێ‬ȾɂȱɀĂĶိ౰39༃๱ණ࢝ࡤჹ‫ݻ‬൨ൎܾਡ੫
‫ࢾ୹ࡳߔݨ‬ᆵʯ˅ʈˁʸĪTBUSFQTīķɅĂႨʓˋʗĜɈஂ࣋ୂɬൣ࿍ଞɂȳɥʈ˃ĜʯɈอ‫ݻڨ‬൨Ķ఍ᆧ‫ڤ‬೔။௩ɬᄆૄȱȹ࡜েဿ຦ไܾ઄ɂȱɀɈ༔ࣞ။ঃɅȤȫɥഹޮ࿎‫ݟ‬଴ၭɈ৭භɂଜ‫ޏ‬ଌകķȦੜ൰ȯɦȹȭɂȦࢫȬɣɦɘȳăႨॸ࢞Ɉ੕୒ᄆ࿈ɉĂ࡜েဿ຦ຑɅ཮Ƞ༔ࣞ౺દଞɈॄ੟โഹޮɬॎঌȳɥȹɛɈ༔ࣞ။ঃ౫๱ɈߊᆏɅ৐ȫɀĂɼˋʡʥʏɺɅȤȞɀ˂ʺĜʠʓˋʏˋʈɅɢɥഹޮ࿎‫ݟ‬ʏʑʞʸɬߊᆏȳɥȭɂɅȜɤɘȳăāɜȠ‫ێ‬ȾɈ൥ȧɄ຦ȧɂȱɀĂ໲Ⴈߔ୹‫ࡼޏ‬ɬෂఘɅߤ຦ɬާ઻ȱȹਡ੫โɄᇦ़ॸ࢞ʯ˅ʈˁʸ
Gvuvsf! Fbsui ɒɈઞ‫ކ‬ȦࢫȬɣɦɘȳă਱Ă‫ބ‬ęɉණ࢝Ɉ‫ݗ‬ඤ‫ݛ‬ɞ౺ဘഽᅕ౯ɈঌவɄɃĂഁ࢖Ʌ‫ސ‬ड़ȱɄȫɦɊɄɣɄȞ‫ݻ‬൨Ʌ‫ڱ‬ɘɦɀȞɘȳă‫୹ࡳߔݨ‬ɉĂȭɦɘɁɅഽȩɈሄဦɬ౺ə୸ȱĂഽȩɈᄵᅙɄඪॽɬอࢷȱɀȧɘȱȹȦĂౘഽȩɈଜ‫ޏ‬โ‫ݻ‬൨Ȧ‫ސ‬ड़ȯɦɄȞɘɘɁરȯɦɀȞɘȳăGvuvsf!Fbsui ɉĂߔ‫ޢ‬໘Ɉᇦ़ɈəɄɣȴଜ‫ޏ‬ɂɈᇦ़ɅɢȽɀȭɦɣɈਲ໧Ʉ‫ݻ‬൨Ʌଲɤ೨ɚɂȞȠఛȹɄਡ੫ᇦ़ʯ˅ʈˁʸɁĂಫᅝ൥ߔɜ೔ߔɈᇦ़Ʌɢɤ Gvuvsf!Fbsui Ʌଲɤ೨ɚȭɂɂɄɤɘȱȹăຎʓˋʗĜȦࠎૢ࡙࠲ɂȱɀ Gvuvsf! Fbsui ໲ႨʋˋʕĜʏɺʸɅ‫ݡ‬ძȳɥȭɂɂɄɤĂߤ຦ɬާ઻ȱɀȞɘȳăိ౰3:༃4ॢɅɉĂຎʓˋʗĜȦෂఘɂɄȽɀಫᅝ൥ߔ Gvuvsf! Fbsui! ʅʛʇʂʭˇĜʇʏʿʛʯɬާ੓ȞȹȱɘȱȹăȷɈߤ຦ɉĂɘȺ஗Ʌ୊ȞȹɊȥɤɁȳȦĂDFSfT Ɉᄆૄȳ‫ێ‬ȾɈఛȱȞၫ৐ɬ૲ȳɜɈɂȞȢɘȳăāႨ༃ၡɉ DFSfT Ȧိ౰39༃๱Ʌ਄Ƚȹߤ຦ĪDFSfT ૵బɅɢɥʯ˅ʈˁʸॸ࢞Ăࢼວᆀᅙॸ࢞Ăॸ࢞౰‫ݪ‬Ăਡ੫ৄᆔĂ࣋‫ߤۋ‬຦Ăଜ‫ޏ‬ਇॷĂᅅધĂȷɈ഼īɬ교โɅࡥሃȱĂ૵জ࿎‫ݟ‬ȳɥɂɂɜɅެင࠲
बଞȥɣȮૄຩɬȞȹȺȩȹɛɈ૝ᆧɂȱɀɜ၂ୠȞȹȱɘȱȹă࠲बȳɥ‫ޣ‬ᅕၫɅȮ਒ᅿȞȹȺȧĂ਱ষɜȮૄຩȮૅ‫ܧ‬ɬ෴ȫɦɊɂૃȞɘȳăࡱȱȩȤࡄȞడȱ௫Ȭɘȳă

ိ౰3:༃Ǐॢಫᅝ൥ߔࠞࣃ˂ʺĜʠʓˋʏˋʈॸ࢞ʓˋʗĜʓˋʗĜෳāā‫ڤ‬ā݊ā೑āဦ

ᄆā૫
ɉȲɛɅ
\2^! ʯ˅ʈˁʸ်ॸ࢞ߤ຦ĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤ
āā2/2/āʯ˅ʈˁʸǍćಪ඘โ˂ʺĜʠʓˋʏˋʈʯ˅ʈˁʸāā2/3/āʯ˅ʈˁʸǎćණ࢝࿍೸௶ၡຕਗʯ˅ʈˁʸāā2/4/āʯ˅ʈˁʸǏć‫ܒ‬౳ᆀᅙ਒๱‫ݛ‬ʯ˅ʈˁʸ2\3^! ࢼວᆀᅙॸ࢞ĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤ 48
āā3/2/āࢼວᆀᅙॸ࢞‫ޱ‬ᅟ
āā3/3/āࢼວᆀᅙʯ˅ʈˁʸॸ࢞Ɉ௢੧
\4^! ॸ࢞౰‫ݪ‬Ɉ৊࿍ĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤ :6
āā4/2/āॸ࢞ሄဦɄɃ
āā4/3/āߔ‫ޏ‬Ćॸ࢞‫ޏ‬ɁɈཡ࿍\5^! ି௤ĆާཡଌಕຑĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤ21:
āā5/2/āି௤āā5/3/āާཡଌಕຑ
\6^! ਡ੫ৄᆔĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤ222!
āā6/2/āެਡఱିȫ໴ɦ
āā6/3/ā࣋ۙɈ‫ެޠ‬๧ਂ
\7^! ࣋‫ߤۋ‬຦ĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤ228
āā7/2/āਆࡹĪߔငĆ൥ߔۡī
āā7/3/āሄဦ൨ᄆ௘‫ގ‬
āā7/4/āိ౰39༃๱ߔ౺ౘ໘ᄟ
\8^! ଜ‫ߤۋ࣋ޏ‬຦Ćଜ‫ޏ‬ਇॷĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤ232\9^! ʓˋʗĜɈ਄ૢĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤ235
āā9/2/āʓˋʗĜ଱੓Ɉʏˋʵʐɾʸāā9/3/āਡ੫ʯ˅ʈˁʸĨGvuvsf!FbsuiĩɒɈଲɤ೨ə
āā9/4/ā൦27‫ ޑ‬TBS ‫ކ‬ജఒਖஐᆅĆಫᅝ൥ߔ Tvnnfs!Tdippm!po!Njdspxbwf!Sfnpuf!Tfotjoh\:^! ଱ᅟॸ࢞ಡྩĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤ238
āā:/2/ā‫ܒ‬౳ʟĜʗିఒʏʑʞʸāā:/3/ā๝༜ჟࣗଆ
āā:/4/ā൥࡜ʟĜʗଲຶˁɼʘĜക඲
āā:/5/āၪଗࠫപʥʛʠˇĜʇૈಡĪTLZOFUīāā:/6/āȷɈ഼ोപക඲Ăʕʭʠɾʀɺ
\21^ ိ౰39༃๱ोધ࡙ʟĜʗʱĜʑ଱ᅟࣞო! ĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤ241
āā21/2/ā‫ޱ‬ᅟāā21/3/āိ౰39Ī3127ī༃๱ोધ࡙ʟĜʗʱĜʑȤɢɍʟĜʗࠣᆅૅ‫ܧ‬ଆ଱ᅟࣞო
āā21/4/āိ౰39Ī3127ī༃๱ʟĜʗʘɾˋ˅Ĝʡଌಕ\22^ ိ౰39༃๱ DFSfT ʣʽĜʒ˄ʗĜʰʛʡˁɼˋȤɢɍʣʽĜʑ˂˂Ĝʑ!ĤĤĤĤĤĤĤĤĤĤĤĤĤ243\23^ ೨ఉĆ‫܄ۿ‬ĆఱૢĆᅅધ! ĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤĤ246
āā23/2/āʓˋʗĜɈ৭౰
āā23/3/āఊۙშၛāā23/4/āࢪ๘‫ޏۙڳ܄ۿ‬āā23/5/āߔ໘߂ହ‫ۙڳޏۙڳ‬ȤɢɍʓˋʗĜ໘‫ޏۙڳ‬āā23/6/āᅅધāā23/7/āެင૝ࣸ‫ێ‬ᅿ༓ⴥ኱Ꮫ⎔ቃ䝸䝰䞊䝖䝉䞁䝅䞁䜾◊✲䝉䞁䝍䞊㻯㼑㼚㼠㼑㼞㻌㼒㼛㼞㻌㻱㼚㼢㼕㼞㼛㼚㼙㼑㼚㼠㼍㼘㻌㻾㼑㼙㼛㼠㼑㻌㻿㼑㼚㼟㼕㼚㼓㻘㻯㼔㼕㼎㼍㻌㼁㼚㼢㼑㼞㼟㼕㼠㼥Ī‫ޱ‬ᅟī
āਡᆏ൥ߔၭఱಫᅝ൥ߔࠞࣃ˂ʺĜʠʓˋʏˋʈॸ࢞ʓˋʗĜĪDFSfTīɉĂ൦໩ࡖෂࡖᄆ࿈Ćෂࡖो‫ކ‬ɬཡ๐ȳɓȩĂ3127༃ǐॢȥɣɈ൦જࡖɅȤȫɥᄆ࿈Ćो‫ކ‬Ɂɉࢪ๘੔໻ฤɬିȫĂȯɣɅǏȾɈ୭๘‫ݻ‬൨ɬಡฤȱߤ຦ɬ઻ɛɘȱȹăDFSfT! ɉĂ೔ਡࢼວᆀᅙɈॸ࢞ʓˋʗĜɂȱɀ2::6༃Īိ౰Ǔ༃īǐॢɅཡഫȱĂ˂ʺĜʠʓˋʏˋʈࡳ୹ɈߊᆏɂࠞࣃɒɈܾᅙɅ࠲ȳɥॸ࢞ɬඐȽɀএ੭Ʌ૖ȽɀȞɘȳăȷɈ˃ĜʜɉĂଖణĆۗઌĆ‫ކ‬ജ৙ߔɈယᄘɁɈಫᅝ൥ߔ৙ߔငɈ๙ຕɬۜȧॅȞɁ2:97! ༃Īூሆ72༃īɅާಡȯɦȹߔ໘ࢼວॸ
࢞ૈಡĶ‫܇‬ജߒപॸ࢞ʓˋʗĜķɁȜɤĂȭɈʓˋʗĜȦ༥ોĆ๖ࠓȯɦɀ DFSfT! Ȧඞ౺ȱɘȱȹă3115༃
ǐॢɈਡᆏ൥ߔ຾ᆏၭఱ‫ݛ‬ষɉĂ൦‫ࡖێ‬Ć൦໩ࡖ߂ǒ༃࠰Ɉෂࡖᄆ࿈Ćो‫ކ‬ɅȤȞɀइൌโᄆ࿈ɬฤɛĂʓˋʗĜɂȱɀຕਗ‫ݛ‬ȯɦȹ౰‫ݪ‬Ȧ౺ɘɦɥɢȠ೔ਡࢼວᆀᅙૈಡɈ࡙༑ɬ୤ଌȯȵĂȷɈၫ৐ɬცߊɅȱɘȱȹăāɘȹĂ3128༃ǐॢɅɉᆅ৙ृ൥ߔۡ࣋‫ۋ‬೨ఉɈຕਗɈɜɂĶᅃਗᆅ৙ߔ࿬ķȦఛಡȯɦĂ˂ʺĜʠʓˋʏˋ
ʈʋĜʑȦඞ౺ȱɘȳăĪ೨ఉూīāDFSfT Ɉ೨ఉɉ‫ࡥݚ‬ɈూɈฆɤɁȳăā࣋ۙɉॸ࢞ᆴ‫ۊ‬Ʌಔɬ඲ȩɂࢼɅĂȷɦȸɦ઄ฤȯɦȹॸ࢞ʯ˅ʈˁʸɅ୦Ƚɀॸ࢞ɬమɛɀȞɘȳăᣐⅬ㐠Ⴀጤဨ఍
㻿㼠㼑㼑㼞㼕㼚㼓㻌㻯㼛㼙㼙㼕㼠㼠㼑㼑䝸䝰䞊䝖䝉䞁䝅䞁䜾ᇶ┙◊✲㡿ᇦ㻲㼡㼚㼐㼍㼙㼑㼚㼠㼍㼘㻌㻲㼕㼑㼘㼐㻌㼛㼒㻌㻾㼑㼙㼛㼠㼑㻌㻿㼑㼚㼟㼕㼚㼓䝸䝰䞊䝖䝉䞁䝅䞁䜾」ྜ◊✲㡿ᇦ㻵㼚㼠㼑㼓㼞㼍㼠㼑㼐㻌㻲㼕㼑㼘㼐㻌㼛㼒㻌㻾㼑㼙㼛㼠㼑㻌㻿㼑㼚㼟㼕㼚㼓䝉䞁䝍䞊㛗㻰㼕㼞㼑㼏㼠㼛㼞
ᩍဨ఍㆟㻿㼠㼍㼒㼒㻌㻹㼑㼑㼠㼕㼚㼓⾨ᫍ䝕䞊䝍ฎ⌮ᐊ㻿㼑㼏㼠㼕㼛㼚㻌㼒㼛㼞㻌㻿㼍㼠㼑㼘㼘㼕㼠㼑㻌㻰㼍㼠㼍㻌㻼㼞㼛㼏㼑㼟㼟㼕㼚㼓◊✲䝥䝻䜾䝷䝮㻌䠍ࠥ䠏㻾㼑㼟㼑㼍㼞㼏㼔㻌㻼㼞㼛㼓㼞㼍㼙㼟㻌㻝㻙㻟ᕤᏛ⣔஦ົ䝉䞁䝍䞊㻱㼚㼓㼕㼚㼑㼑㼞㼕㼚㼓㻌㻭㼐㼙㼕㼚㼕㼟㼠㼞㼍㼠㼕㼛㼚㻌㻯㼑㼚㼠㼑㼞Īॸ࢞ʯ˅ʈˁʸǍġǏīǍīāಪ඘โ˂ʺĜʠʓˋʏˋʈʯ˅ʈˁʸǎīā௶ၡຕਗʯ˅ʈˁʸǏīā‫ܒ‬౳ᆀᅙ਒๱‫ݛ‬ʯ˅ʈˁʸ䝉䞁䝍䞊ᨭ᥼ಀ
㻯㼑㼚㼠㼑㼞㼟㻌㻿㼡㼜㼜㼛㼞㼠ĮǍįāʯ˅ʈˁʸ်ॸ࢞ߤ຦
2/2/āʯ˅ʈˁʸǍćಪ඘โ˂ʺĜʠʓˋʏˋʈʯ˅ʈˁʸĮ‫ޱ‬ᅟį
˂ʺĜʠʓˋʏˋʈࡳ୹Ʌɢɥණ࢝ࠞࣃॸ࢞Ɉమ๐ɂɂɜɅĂࡕശɈࠫപၫၭɈঔ‫ޢ‬ȦȱɊȱɊᄎ൨ɂɄȽɀ
ȞɥăႨʯ˅ʈˁʸɁɉĂȭɦɘɁ୥ယɄࠫപȦਲ໧ɁȜȽȹʗĜʊʛʠɅȾȞɀĂఛȹɄ˂ʺĜʠʓˋʏˋʈ
ʓˋʍɂɺ˃ʌ˂ʒʸɬާཡȳɥȭɂɅɢȽɀఛࣟჶɬಓ࣡โɅಜɤ൱ȞɀȞȩăູɅĂ‫ݢ‬૗৉ȥɣʶɼʇ˅༜
Ʌ૖ɥঢ়Ȟ༜ෳ‫ۊ‬ɁɈ˂ʺĜʠʓˋʏˋʈ௶ၡɈຕਗɂߤᅙĂ૫౦ൣழळ‫ܒ‬౳ʓˋʍɅɢɥ൥࡜௶ၡɂఆ౺௶ၡ
ɬ࠸ɚʈ˅Ĝʨ˃Ʉࠞࣃ௶ၡɈଲຶɄɃɈߤᅙɬฆȲɀĂಪ඘โ˂ʺĜʠʓˋʏˋʈɈ೯౺ɂఛȹɄࠞࣃ௶ၡɈ
೯୸ɬɛȰȳă
ಪ඘โ˂ʺĜʠʓˋʏˋʈʯ˅ʈˁʸɈ൦Ǐࡖෂࡖᄆ࿈Ćෂࡖो‫࠰ࡖކ‬Īိ౰39Ľ44༃๱īɅȤȫɥॸ࢞‫ݻ‬൨Ȥɢɍൿ౰ᄆ࿈ɉ‫ݚڬ‬ɈฆɤɁȜɥă൦ǎࡖɅȤȞɀଌૈȱȹॸ࢞ʞĜʶɈູଋɅࡊȿȩʯ˅ʈˁʸॸ࢞ɬཡ๐ȯȵĂȯɣɅ୭๘‫ݻ‬൨ɬಡฤȱȹăĮෂࡖो‫࠰ࡖކ‬Ɉॸ࢞‫ݻ‬൨Ȥɢɍൿ౰ᄆ࿈įśॸ࢞‫ݻ‬൨Ć! ʀɺ˅ʖ˃Ă‫܀‬Ă‫ݗ‬ඤ‫࡜ݛ‬ൌĂȤɢɍܸಹ࡜ൌɬൎ௣ɂȱȹఛȱȞ൥࡜˂ʺĜʠʓˋʏˋʈ଴ၭɂȱɀĂ૵೓৉঍ȤɢɍഽᅕɄఱ৙৉঍ɬᅙȞȹ਒ʑʲʇʠ˃ယ‫ސ‬༑ࠫപɈ‫ݢ‬༑౯ɬცɣȥɅȳɥăĆ! ঢ়‫ࠫۊ‬പĂ਒࿡๱ࠫപĂ਒ʑʲʇʠ˃ယ‫ސ‬༑ࠫപȦ‫ݢ‬༑ɄɌɘɩɤǔਖɄɃఛȱȞ‫ܒ‬౳ʟĜʗɂණ௫ࠫപʟĜʗɈຕਗᆀᅙȳɥȭɂɅɢɤ൥࡜௶ၡɂᆌ‫௶ۊ‬ၡɈယᆋɬ࠸ɚఛȱȞࠫപၫၭɈ‫ݢ‬༑౯ɬცɣȥɅȳɥăĆ! ৉ߔʓˋʍɬᅙȞȹഽߍࠫപɅɢɥʨɼʂʶʑైฤɺ˃ʌ˂ʒʸ਒๱‫ݛ‬Ʌൎȱɀࡍᅇȳɥණ௫ॳ௠ʟĜʗେୠ଴ၭɈȠȻĂఆ౺ MJEBS ɬᅙȞɀණ௫ȤɢɍऋෂȥɣɈఝᆹୃࠁ৭ഢोപ଴ၭɬߊᆏȳɥăĆ! ණ௫˂ʺĜʠʓˋʏˋʈɬߤᅙȱȹණ࢝൥࡜ࠞࣃɈၴ‫࢞ॸވ‬ɂȱɀĂఛȹɄࠫപക඲ާཡɬ਄ȠăइൌโɅɉĂാᅣ๝දऄ຦ळɈ຾૵Ɉ൥࡜ࠞࣃࠫപക඲ɬާཡȳɥăຶɣɦȹʟĜʗɂ౰‫ݪ‬ɉ৊ާȳɥăĆ! ਒ယ‫ސ‬༑˄ĜʎĜɁଲຶȯɦɥǏ૫ইʟĜʗɬߤᅙȱȹఝᆹ˂ʺĜʠʓˋʏˋʈɂʨɼʂʶʑဿ‫ݛ‬ᆲɈ༘‫ڐ‬ăĆ! ਒ࠐ๱ฝ୸ᆵɈʷ˂༜˄ĜʘɅɢɥණ࢝ࡤჹɈ‫܀‬ယ࿫ɈࠫപȤɢɍȭɈ˄Ĝʘɬߤᅙȱȹ൥࡜ෂ࿲ᄿဘଋĪਹ්ɞ‫ݴ‬ဢīɈယ࿫ोപĂྦ਄௲ୈ၃ɁɈტɈ௢੧ोപăś୭๘‫ݻ‬൨ćಪ඘ʶɼʇ˅༜˂ʺĜʠʓˋʏˋʈ
āāāāāāĪJoopwbujwf!njdspxbwf!sfnpuf!tfotjohīĆ! ࣋‫ۋ‬ĆࠞࣃĆ੠ޮࠠ૗ᅙɈჟఱਂऋ࡙Ćྦ਄࡙຃੪Ɉʶ˃ʙʨˋʡĂழळĆॎᆲɈਗ౰ާ৏˄Ĝʘʏʑʞʸɬާཡȳɥă
Ć! ʈ˅Ĝʨ˃ණ߈ဿ຦ࠫപᅙɈழळ‫ܒ‬౳຃੪ᅙਗ౰ާ৏˄ĜʘʏʑʞʸɈʀˋʐʣɺ˂ˋʈʺʟ˃ɬާཡȳɥă
Ć! BMPT.3ɞ UfssbTBS.Y ຑɈ߂ହ TBS ‫ކ‬ജɅɢɥණరĂ෿༜Ă‫ݮ‬ટĂဇ౉ޮɄɃɈ੠ޮ༘‫ڐ‬Ʌ࠲ȳɥॸ࢞ɬైమȱĂ੠ޮ༘‫ڐ‬଴ၭɈ࿈ஈ‫ݛ‬ɬᄆૄȳăĆ! ණరএ௣ɬණ߈໘ɈܾᆵୠෂɅɢɥ༟‫ޓ‬এ௣ɂȱɀɂɣȢĂȷɈஈྩ‫ݿ‬าɅȤȞɀණ५Ă൥࡜५Ă๝ᆋ५Ɂཡ౺ȳɥ๝૱࡜এ௣ɬ౷ߊɅ༘‫ڐ‬ȱĂȷɈဘᆅ࡙৭ɬ‫ސ‬ცȳɥăණ௫Ć‫ܒ‬౳ࠫപʟĜʗɬᅙȞȹ๝૱࡜โɄ
ɺʯ˅ĜʙɅɢɥණ߈ߤ຦Ɉࠠ૗ĂȞɩɊĶණ௣๏࡜ᅅၡķɬଌএȱĂঌ੠Ʌᄜᆏɀɥȭɂɬ࢞࣡Ɉᄆโɂ
ȳɥăProgram 1: Innovation in remote sensing technology and algorithm
The limitation of existing approaches has often been recognized in the course of the Earth environment
studies using remote sensing. In this program, novel sensors and algorithms are explored in order toestablish remote sensing methodologies that enable more in-depth and comprehensive analyses of various
targets including vegetation and atmosphere. In this way this program aims at the innovation of remotesensing through such activities as construction and operation of next-generation satellite sensors, and theintegration of wide spectral-range observations using optical and microwave remote sensors.

―1―Įॸ࢞໘ᅎɂိ౰39༃๱Ɉ౰‫ݪ‬į

ş2/2/2/āʶɼʇ˅༜˂ʺĜʠʓˋʏˋʈ
ş2/2/2/2/āਗ౰ާ৏˄ĜʘĪTBSīɈާཡĪˀʍʭɹʛʠॸ࢞ଆīਗ౰ާ৏˄ĜʘĪTBSīɉഽᄆโʓˋʍɁĂ೔๏েळĂ෇ᄕɁɜࠫപɁȧɥɜɈɁȜɥă୦ᅰɈ TBS ʓˋʍɉ෸ೀှ༜ĪIIĂWWĂIWĂWIīɁĂູɅฝୈ༜ɁȜɥ M ʨˋʡȦ๝ᆋ೸ɅȤȫɥʭɹˁʟĜ‫ޑ‬๖Ɉএ௣Ɂ൥
ȧȩ‫ࣗ܆‬ȯɦɀȞɥăూ2/2/2/2/.2ɈɢȠɅĂႨॸ࢞ɁɉĂʈ˅Ĝʨ˃ණ߈ဿ຦ɬɉȲɛĂழላ౳Ăላ౳Ɉඑੈ
ຑɈȹɛɅĂ‫ܟ‬ှ༜ਗ౰ާ৏˄ĜʘĪDQ.TBSī຃੪ழळ‫ܒ‬౳ɬާཡȱɀȞɥăȭɈ DQ.TBS ʓˋʍɈණ௫ଌ௠
ଌঅɈȹɛɅĂႨॸ࢞ଆɉ຾૵Ʌ൥ळჟఱਂऋ࡙ KY.2ɬާཡȱȹĪూ2/2/2/2/.3īăూ2/2/2/2/.2ā‫ܟ‬ှ༜ਗ౰ާ৏˄Ĝʘ຃੪ழळ‫ܒ‬౳

ూ2/2/2/2/.3āਗ౰ާ৏˄Ĝʘ຃੪ჟఱਂऋ࡙ĪKY.2ī

ూ2/2/2/2/.4ɈɢȠɅĂDQ.TBS ʓˋʍȦൈ‫ܟ‬ှ༜Ī੆ಽɘȹɉ‫ۦ‬ಽīɬഗఒȱɀĂ੆ಽɂ‫ۦ‬ಽှ༜ɬວ૪Ʌ
ିఒȳɥăȭɈᆤʟĜʗɬିఒȳɥȭɂɅɢȽɀĂ૾྘‫ކ‬ജĂൈ‫ܟ‬ᆎĂʙ˃ʠߍɄɃĂᅕęɄఛ‫ކ‬ജɬෆ୸ȳɥȭɂȦɁȧɥăDQ.TBS ʓˋʍɉɺʇʞɻʮʓˋʍɁȜɤĂǨʨˋʡɈʙʻĜʯʩ˃ʑɁĂQSG Ȧ2-911ġ
3-111I{ ɁȜɥăႨॸ࢞ɁɉĂDQ.TBS ʓˋʍȦ‫ݟڤ‬ĂॎᆲĂʋˋʩʇʠɁಡोȯɦɀȞɥăȭɈఛळʓˋʍ
ȦʯˁʛʠʭʁĜʸɈઽ౬ɂ๝ᆋ೸ɅȤȫɥʭɹˁʟĜ‫ޑ‬๖Ʌɢɥ‫ࣗ܆‬ɬॎঌɁȧĂɘȹȭɈʓˋʍɅɢȽɀĂ਒౼๱ɂฝʦɼʒɈ‫ކ‬ജɬຶɥȭɂȦɁȧɥɂࡖ൒ȳɥăȭɈழळ‫ܒ‬౳Ʌ DQ.TBS ʓˋʍɬ຃੪ȳɥ೐ɅĂႨॸ࢞ଆɁɉʓˋʍɈණ௫ଌ௠ଌঅᅙɈ DQ.TBS ຃੪ჟఱਂऋ࡙ĪDQ.TBS! VBWĂూ2/2/2/2/.3ɬઞ௎īɜާཡȱȹăూ2/2/2/2/.5ɈɢȠɅĂႨॸ࢞ଆɈ൥ळჟఱਂऋ࡙ɉᅕęɄʷʛʏʿˋɈȹɛɅĂᅕęɄʓˋʍɬ຃੪ȳɥȭɂȦɁȧɥăɘȹĂჟఱਂऋ࡙Ɉ౯༑ɬࣅ‫ݛ‬ȳɥȹɛɅĂʃĜʴˋʋˋʵʐʛʠɅɢɥॎᆲ‫ݛ‬ɂࣅ‫ݛ‬ɬూɤĂ
KY.3ɬࠊ౰ȯȵȹĪూ2/2/2/2/.6īă਱ষĂࠞࣃࠫപĂర੠ࠠ૗ɄɃɈȹɛɅĂෳࢯᆋɂෳ૪࠰ɈʷʛʏʿˋȦɁȧɥɢȠɅĂᅕęɄ౯༑৐௫ɬȳɥᅅฤɁȜɥăĪǍīDQ.TBS ʷʛʏʿˋ
ȭɈ DQ.TBS ʷʛʏʿˋɈ଱Ʉᄆโɉൈ‫ܟ‬ှ༜ɈઢᅸɅ
ɢɥࡊೣॸ࢞ɂȷɈܾᅙɈާཡɁȜɥăࡊೣॸ࢞ɁɉĂණ࢝࿍೸Ʌɢɥൈ‫ܟ‬ှ༜Ī‫ܟ‬ှ༜ɂ෸ೀှ༜ɬ࠸ɚīɅɢɥᅕęɄ๝૱༜Ɉઢᅸᄎ൨Ɉ‫ސ‬಑Ăൈ‫ܟ‬ှ༜Ʌɢɥࠍொਗ౰
ާ৏˄ĜʘĪJoTBSīĂ૾྘‫ކ‬ജɈ౺౰ၫၭĂൈ‫ܟ‬ᆎĂʙ˃ʠߍɄɃɈᅕęɄ‫ކ‬ജɬ౺౰ȱ‫ސ‬಑ȳɥᅅฤɁȜɥăȭȭɁĂఆ౺Ăಥ࿉ĂᅕęɄ๲௳ହᇆɄɃɅɢɥൈ‫ܟ‬ှ༜Ɉઢᅸଌঅɂ‫ސ‬಑ɬȳɥᅅฤɁȜɥăɘȹĂȭɈൈ‫ܟ‬ှ༜ɢɤଲຶȳɥय़‫ݪ‬ɬ୦ᅰɈ෸ೀှ༜Ɉ‫ސ‬಑य़‫ݪ‬ɂ྘ߏॳບ
ȱĂȭɈ଴ၭɬൈ‫ܟ‬ှ༜ɅɢɥୃࠎɈ਒ȯĂ࿈਒ʟĜʗĪEFNīɄɃෆ୸ɅܾᅙȳɥᅅฤɁȜɥă
DQ.TBS! VBW Ɉ‫ۿ‬ᅙ‫ޱ‬༄ɬూ2/2/2/2/.4Ʌ૲ȳăȭɈూȥɣɩȥɥɢȠɅĂDQ.TBS ʓˋʍȦ SIDQ ɘȹɉ MIDQȥɣ‫ێ‬ȾɈှ༜ɈəɬഗఒȱɀĂණჶɅઢᅸȯɦĂᆤှ༜ɈܾຒĪSIDQ ɂ MIDQīɬວ૪ɅିఒȳɥăȭɈᆤఒਖɢɤĂ૾྘Ăൈ‫ܟ‬ᆎĂʙ˃ʠߍɄɃĂᅕęɄ௶ၡɬෆ୸Ɂ
ȧĂණ࿍೸ɂɈ࠲बɬ෮ੈȳɥᅅฤɁȜɥă

―2―

ూ2/2/2/2/.4āDQ.TBS!VBW Ɉ‫ޱ‬༄ూ2/2/2/2/.5āDQ.TBS!VBW Ɉʍʮʏʑʞʸూ2/2/2/2/.6āDQ.TBS ຃੪ᅙ VBW!KY.3

DQ.TBS ʓˋʍɈܾᅙާཡɁɉĂளᅰȭɈʓˋʍɬ๲ණྡဒĂ੠ޮࠠ૗Ăಥ࿉‫ۊ‬ɂ‫ޠ‬ᅖ‫ۊ‬Ɉʺʣʗ˂ˋʈɄɃ
ɅܾᅙȳɥᅅฤɁȜɥăȹɂȢɊĂ๲ණྡဒɈʶʛʬˋʈɁɉĂ‫ܟ‬ှ༜Ʌɢɥఝᆹɂྥఝᆹ‫ۊ‬ɈယᇆĂୃ਒Ăʶˋʈ˅ĜʮĂ࣡ණɅȤȫɥಥ࿉Ɉࠞࣃဿ‫ݛ‬ɄɃɈʺʣʗ˂ˋʈɅܾᅙȱĂ੠ޮࠠ૗ɁɉĂȭɈʓˋʍɬʈ˅Ĝʨ˃ණ߈ဿ຦Ă‫ݮ‬ટߤ຦ɄɃɈࠫപɅߤᅙȳɥᅅฤɁȜɥăĪǎīDQ.TBS ʏʑʞʸ
ూ2/2/2/2/.7ɉ DQ.TBS! VBW Ɉʏʑʞʸɬ૲ȳăȭɈʏʑʞʸɉྦ਄౫সʏʑʞʸĂʂˋʴĜʡʋˋʬʽĜʗĂʞ˄ʹʠ˂ĆʋʶˋʡʟĜʗʧˋʡ˂ˋʈĂઽ౬౫সĂʓˋʍɄɃȥɣ৭౰ȯɦɀȤɤĂྦ਄౫সʏʑʞʸɉ଴຦ɂ૵ᆍྦ਄ʺʐʽĜ˃ȥɣ৭౰ȯɦɀȞɥăʂˋʴĜʡʋˋʬʽĜʗɉ DQ.TBS! VBW Ɉ೔ʍʮʏʑʞʸɈ౫সɅ઴ᅙȳɥăઽ౬౫সɉࠑ౯ਂၭക඲ĪJNVīɂ HQT ɬ઴ᅙȳɥă଱ʓˋʍɂȱɀĂDQ.TBS ɬ઴ᅙȳɥȦĂȭɈʷʛʏʿˋɁɜʧɼʩĜʑʲʇʠ˃ʃʹˁĂHQT.TBS ɄɃɜ຃੪ȳɥᅅฤɁȜɥăDQ.TBS ʓˋʍȦʙʻĜʯʩ˃ʑཡ౺ࡉĂഗିఒʺʐʽĜ˃Ă‫ކ‬ജఒਖஐᆅʺʐʽĜ˃ȥɣ৭౰ȯɦɀȞɥă

ూ2/2/2/2/.7/āD ʨˋʡ DQ.TBS Ɉʏʑʞʸూూ2/2/2/2/.8ąTBS ʓˋʍɈʵɼˋʠʗĜʊʛʠ

ూ2/2/2/2/.7Ȧ VBW ɂਂऋ࡙຃੪ᅙ D ʨˋʡ TBS ʏʑʞʸɬ૲ȳăDQ.TBS ʓˋʍȦ SG ʏʑʞʸĂʙʻĜʯʩ˃ʑཡ౺ࡉĂ‫ކ‬ജఒਖஐᆅʏʑʞʸȥɣ৭౰ȯɦɀȞɥăూ2/2/2/2/.8ɉ TBS ʓˋʍɈʵɼˋʠʗĜʊʛʠɈଌঅɈᅕાɬȱɛȳăూ2/2/2/2/.9Ȧ DQ.TBS ʓˋʍɈ SG ʏʑʞʸɘȹɉഗିఒʺʐʽĜ˃Ɉ‫ޑ‬ᇭూɬ૲ȳăࡊႨโɅĂȭɈʏʑʞʸȦഗఒɂିఒɈʍʮʺʐʽĜ˃ȥɣ৭౰ȯɦɀȞɥăഗఒʍʮʺʐʽĜ˃Ɉ໴ᆵ඘ાɅĂʱĜʑʨˋʡ ED ġ261NI{ĪM ʨˋʡɈ௲ਗīɬɜȾʙʻĜʯʩ˃ʑཡ౺ࡉɈ Jo.qibtfĪǥīɂ Rvbesbuvsf
ĪǭīɈఒਖɬಞറȳɥăʙʻĜʯʩ˃ʑȦୈ༜ౘ2-381NI{ĪǨʨˋʡɈ௲ਗīɅဿ෮ȯȵĂȭɈഗିఒʏʑʞʸɈୈ༜ౘɈ຦੼ဍȦ2-381NI{ ľ261NI{ ɁȜɥăഗఒʏʑʞʸɈᆀຶʙʽĜʣˋʈ࡙༑ȦǍĂǎĂǏĂ
ǔĂ27ɘȹɉǌġĽ42eC ɅಡฤȳɥȭɂȦɁȧɥăିఒࡉɈᆀຶʙʽĜʣˋʈ࡙༑ȦǍĂǎĂǏĂǔĂ27ĿǎɘȹɉǌġĽ73eC ɁȜɥă๝ᆵഝဍࡉĪQBīȦʩ˃ʑഗఒ๝ᆵ61XĪ੕൥īĂഗఒࡖ࠰21̂tĪ੕൥īĂevuz!
djsdmf! ǎœĪ੕൥īɬ୸ᆵȳɥăഗିఒ࡙Ɉʑɼʛʙˋʈബ๱ĪSIDQ ɂ MIDQīȦࡊႨโɅǍ̂t Ɂ੕൥ǎ̂t!
ɁȜɥăɺˋʞʢငယȦʭ˃‫ܟ‬ှ༜ɬଌএȳɥȹɛɅĂMIDQ ɂ SIDQ ᅙɈ‫ܟ‬ှ༜ʶɼʇ˅ʑʠ˂ʛʯɺ˄Ĝ―3―ɺˋʞʢȥɣ৭౰ȯɦɀȞɥăూ2/2/2/2/.:Ȧຎॸ࢞ଆɁާཡȯɦȹ DQ.TBS ʏʑʞʸɈ೔ʺʐʽĜ˃ĪǨĂǟĂ
ǴʨˋʡīɂĂ຾૵ާཡȯɦȹʙʻĜʯʩ˃ʑཡ౺ࡉɬ૲ȳăూ2/2/2/2/.21Ȧჟఱਂऋ໘Ʌ຃੪ȱȹ DQ.TBS
ʏʑʞʸĪǨɂǟʨˋʡīɁȜɥăూ2/2/2/2/.22Ȧ຾૵Ʌާཡȯɦȹǟʨˋʡ TBS ᅙɈʩʛʙɺ˄ĜɺˋʞʢɂĂɺˋʞʢູ౯ɈപฤȱɀȞɥᅕાɬ૲ȳă
Ŋ
Œ
œŉńő
ōŉńő
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ŒŊœŦŤŦŪŷŦųġȪœŹȫĻġōŉńőŒ

ూ2/2/2/2/.9ąDQ.TBS ʏʑʞʸɈ‫ޑ‬ᇭూĪǝīǨʨˋʡ‫ܟ‬၂༜ਗ౰ާ৏˄ĜʘʏʑʞʸĪǞīǟʨˋʡ‫ܟ‬ှ༜ਗ౰ާ৏˄ĜʘʏʑʞʸĪǟīǴʨˋʡ‫ܟ‬ှ༜ਗ౰ާ৏˄ĜʘʏʑʞʸĪǠīಫᅝ൥ߔཡʙʻĜʯཡ౺ࡉĪǔʙʻˋʥ˃୸ᆵī

ూ2/2/2/2/.:ąTBS ɈʙʻĜʯʩ˃ʑཡ౺ࡉɂ‫ކ‬ജఒਖஐᆅɈʺʐʽĜ˃―4―ĪǝīǨʨˋʡ TBSĪǞīǟʨˋʡ TBS

ూ2/2/2/2/.21ąჟఱਂऋ࡙ɂਂऋ࡙Ʌ຃੪ȱȹ TBSĪǨɂǟʨˋʡī

ూ2/2/2/2/.22ąDQ.TBS ɈഗିఒᅙɈʶɼʇ˅ʑʠ˂ʛʯɺˋʞʢɂപฤᅙɈ๝༜ჟࣗଆ

ĪǏīDQ.TBS ຃੪ჟఱਂऋ࡙ĪDQ.TBS!VBWīʏʑʞʸႨॸ࢞Ɉ VBW! TBS ʏʑʞʸɉʲĜ˅Ĝʡ36lh ɁĂDQ.TBSĂHQT.TBS ɄɃɈ߂ହʓˋʍɬ຃੪ȳɥᅅฤɁȜɥăȭɈ VBW Ɉྦ਄‫ݢ‬༑Ʉ਒๱ɉ2-111n ġ5-111n ɁȜɥăෂఘୈ༜ౘ2-381NI{Ă‫ސ‬ജ๱Ǎn ġǏnĂʩ˃ʑɈ૪࠰ဍ5/6ġ59̂tĂʩ˃ʑɈʨˋʡဍġ261NI{Ăʂʭʢʟɻɺߍ31p ġ71pĂࠫപဍǍlnĂɺˋʞʢ
ʍɼʒ2/6n Ŀ1/5nĪǐʩʥ˃īĂɺˋʞʢၪଗৌᆎń91œĂQSG2-111I{ĂʬĜʇ๝ᆵ9/76XĪ਒๱Ǎlnīġ
:6XĪ਒๱ǐlnīɁȜɥăႨॸ࢞ɁɉĂ਒๱ǎln ‫ݚڬ‬Ɉྦ਄ଌঅɬȳɥᅅฤɁȜɤĂ੕൥๝ᆵɉ61X ɁȜɥăഗିఒɺˋʞʢɉ MIDQ ɂ SIDQ Ɉɺˋʞʢȥɣ৭౰ȯɦɀȞɥăȭɈ MIDQ ɂ SIDQ ɺˋʞʢɁିఒȯɦȹʩ˃ʑɢɤĂ෸ೀှ༜ɂ‫ܟ‬ှ༜ɬ࠸ɚൈ‫ܟ‬ှ༜Ɉઢᅸູ౯ɬ෮ੈȳɥᅅฤɁȜɥă
ూ2/2/2/2/.23ɉĂ๝༜ჟࣗଆɁപฤȯɦȹ‫ܟ‬ှ༜ĪMMĂMSĂSMĂSSīɂ෸ೀှ༜ĪIIĂIWĂWIĂWWīɈ‫ކ‬ജɬ੔এȱȹɜɈɁȜɥăǨɂǮɉȷɦȸɦ੆ಽ‫ܟ‬ှ༜ɂ‫ۦ‬ಽ‫ܟ‬ှ༜ɬ૲ȳăMS ɉ MIDQ ɈഗఒɁĂSIDQ
ɈିఒɁȜɥăȭɈూȥɣɩȥɥɢȠɅĂ‫ܟ‬ှ༜Ɉ‫ކ‬ജɉ෸ೀှ༜Ɉ‫ކ‬ജɂ྘ߏȱɀĂ‫ކ‬ജɈ೏ც౯ɂઢᅸ௻ൔ
ɄɃɈ‫ۅ‬Ȟɬ૲ȱɀȞɥă਱ষɜ‫ܟ‬ှ༜Ɉ‫ކ‬ജɈ෮ੈɬॅറȱĂᅕęɄܾᅙɒɜॳບȳɥᅅฤɁȜɥă

―5―ĪǝīMjofbs!Qpmbsj{bujpoĪǞīDjsdvmbs!Qpmbsj{bujpo
ూ2/2/2/2/.23ą෸ೀɂ‫ܟ‬ှ༜Ɉ‫ކ‬ജ

―6―ూ2/2/2/2/.24ɉĂ෸ೀှ༜ɂ‫ܟ‬ှ༜Ɉ྘ߏॳບɬȳɥȹɛɈʵɼˋʠʗĜʊʛʠɈଌঅɈᅕાɁȜɥăȭȭɁĂိჶĂǎჶĂǏჶɈཱଗჶĪʋĜʢĜ˂ʭ˄ʇʗĜīɬൎ௣ɅȱɀĂઢᅸଌঅɬ਄Ƚȹăూ2/2/2/2/.25ɅȭɈ߂ହɈय़‫ݪ‬ɬ૲ȳăȭɈय़‫ݪ‬ȥɣɩȥɥɢȠɅĂ‫ܟ‬ှ༜Ɉઢᅸ༜ɉĂɢɤʦɼʒȦவɄȞȭɂȦယȥȽȹă

ూ2/2/2/2/.24āʵɼˋʠʗĜʊʛʠɈଌঅć෸ೀှ༜ɂ‫ܟ‬ှ༜Ɉ྘ߏॳບ

(1,1) LP, Co-Pol., HH

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Cross-range (m)Cross-range (m)Cross-range (m)Cross-range (m)(2,1) LP, Cross-Pol., VH(2,2) LP, Co-Pol., VV(2,3) CP, Cross-Pol., RL(2,4) CP, Co-Pol., RR

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Cross-range (m)(a) LP imaging output

Cross-range (m)(b) CP imaging output

ూ2/2/2/2/.25āʵɼˋʠʗĜʊʛʠɈଌঅय़‫ݪ‬ć෸ೀှ༜ɂ‫ܟ‬ှ༜Ɉ྘ߏॳບɈय़‫ݪ‬―7―

ş2/2/2/3/āQT.JoTBS Ʌɢɥණྉ෺‫ݚ‬ɂ๲ੋၦɦɈࠫപ
ࣷ༃Ă๬ી‫ۊ‬ɬɉȲɛĂ਒ബັᇭĂ਒‫ڗ‬ഗ๝ೀĂ‫࠹ޠ‬ೀ‫ܨ‬ɄɃɅȤȫɥණྉ෺‫ݚ‬Ă๲ੋၦɦɄɃĂᅕęɄᄎ൨Ȧཡ౺ȱȹăూ2/2/2/3/.2ɉʐʻʃ˃ʗી໘ɅȤȫɥණྉ෺‫ݚ‬ɅɢɥྡޮɈᅕાɬ૲ȳăȭɈණྉ෺‫ݚ‬ɈঈۚɂȱɀĂ๬ીާཡĂණ‫౉ݚ‬Ɉ൥ᆲ઴ᅙɄɃɁȜɥăȭɈএ௣Ȧෳࡖ࠰ɅɩȹȽɀྫவဿ‫ݛ‬ȱɀȞɥɈɁĂႨॸ࢞Ɂɉෳࡖ࠰ॅറโɄੇယࠍொਗ౰ާ৏˄ĜʘĪEjggfsfoujbm! Joufsgfspnfujd! TBS! .! EJoTBSī଴ၭɂ‫܊‬റઢᅸൌਗ
౰ާ৏˄ĜʘࠍொၭĪQfstjtufou!Tdbuufsfst!Joufsgfspnfusjd!Tzouifujd!Bqfsuvsf!SbebsĞQT.JoTBSīɬ઴ᅙȱɀĂ଱Ʌʐʻʃ˃ʗીɅȤȫɥණྉ෺‫ݚ‬Īూ2/2/2/3/.3īĂʶ˄Ĝ཰๿Ɉຄಀ਒ബັᇭɂ਒‫ڗ‬ഗ๝ೀ‫ܨ‬ȞɅȤȫɥ๲ੋၦɦɈঢ়‫ࠫۊ‬പɬ਒౼๱Ʌ਄Ƚȹă਱ɘɁĂຎॸ࢞ଆɁɉ UfssbTBS.YĂFowjtbu!BTBSĂFST.203!TBSĂKFST.2!TBSĪ‫ސ‬ജ๱ᄝ23/6nīĂBMPT!!
QBMTBSĂBMPT.3! QBMTBS.3Ɉ߂ହʟĜʗĪ‫ސ‬ജ๱ᄝ21nīɬ઴ᅙȱɀĂຄ໤ɺʐɺɂຄɺʐɺණ‫ۊ‬ɅȤȫɥ൥๬‫ޏ‬ɅȤȫɥණ߈ဿ຦Ɉࠫപɬ਄ȽɀȤɤĂູɅĂȭȭɁ൥๬‫ޏ‬ɅȤȫɥණྉ෺‫ݚ‬Ʌ෉ᄆɬȱȹăᇉɂȱɀĂూ2/2/2/3/.3Ʌ EJoTBS Ɂ UfssbTBS.Y ʟĜʗɬ‫ސ‬಑ȱɀĂɼˋʡʥʏɺĆʐʻʃ˃ʗી໘ɅȤȫɥණྉ෺‫ݚ‬Ɉ‫ސ‬಑य़‫ݪ‬ɬ૲ȳăႨॸ࢞ɁɉĂ‫ސ‬಑य़‫ݪ‬Ɉ‫ސ‬ജ๱ȦᄝǍn ɅɄɥɈɁĂএණɅȤȫɥ௢੧Ʉ‫ސ‬಑य़‫ݪ‬Ī‫ސ‬ജ๱ᄝǍnīɬຶɥȭɂȦɁȧȹăȷɈय़‫ݪ‬Ăʐʻʃ˃ʗી໘ɅȤȫɥ3121༃ǔॢǕ໲ȥɣ3122༃ǒॢ24໲ɘɁɈྫவဿ‫ݛ‬Ɉෆ୸ȦɁȧȹăȭɈ඗ࡖ࠰ࠫപɅɢɥྫவဿ‫ݛ‬Ɉෆ୸य़‫ݪ‬ɬɜɂɅȱɀĂႨॸ࢞Ɂɉ EJoTBS ɂ
QT.JoTBS ଴ၭɁෳࡖ࠰ණ࿍ჶྫவဿ‫ݛ‬ɂൌಓဿ‫ݛ‬Ɉෆ୸ɬଌૈȱȹăĪǽīLbqvl!Ebmbn ฆɤɈ൥৯౉

ĪǾīNbohhb!evb ණ‫ۊ‬Ʌණྉ෺‫ݚ‬ĪǿīBodpm ીɅၦᅶȱȹ਒ബັᇭ

ూ2/2/2/3/.2/āএණ෮ੈଖణ

ూ2/2/2/3/.3ąBMPT ‫ކ‬ജɬߤᅙȳɥ QT.JoTBS ‫ސ‬಑ćʐʻʃ˃ʗĆಀငʐʻˇॻɅȤȫɥණྉ෺‫ݚ‬Ɉࠫപ

―8―Ⴈॸ࢞ɈᄆโɂȱɀĂBMPT ‫ܒ‬౳ɈʟĜʗɬ઴ᅙȱɀĂʐʻʃ˃ʗીɬɉȲɛĂ౦‫߂ޢ‬ਡɈଽ๬ɅȤȫɥ௢੧Ʉණྉ෺‫ݚ‬ɘȹɉණ࿍೸ဿ‫ݛ‬ɬ༘‫ڐ‬ȳɥȭɂɁȜɥăॸ࢞ၫၭɂȱɀĂɘȴ‫ࢦݿ‬Ɉණྉ෺‫ݚ‬Ɉ‫ݿ‬าɬ༘‫ڐ‬ȳɥȹɛɅĂ2::4༃ġ2::9༃Īǒ༃࠰īĂ3118༃ġ3122༃Ă3125༃‫ڬ‬ষɈණྉ෺‫ݚ‬Ɉএ௣ɬ‫ސ‬಑ȳɥྼᅟȦȜɥăȭȭɁĂǨʨˋʡɈਗ౰ާ৏˄ĜʘɁȜɥ KFST.2!TBSĂBMPT!QBMTBSĂBMPT.3!QBMTBS.3Ɂ‫ސ‬಑ɬȳɥăȷȱɀĂȭɈ๬ીɈྫழဿ຦ᆲɈ༘‫ڐ‬ɬȳɥȹɛɅĂ3125༃ġএ੭Ɉ BMPT.3‫ܒ‬౳दɈʟĜʗɬ઴ᅙȳɥăȭȭɁĂএණɈྫழဿ຦ᆲɬ༘‫ڐ‬ȳɥȹɛɅĂ਒౼๱ HQT ʟĜʗĂຕोʟĜʗĂණଋ௶ၡĂএණ෮ੈʟĜʗɄɃɂ྘ߏॳບɬȳɥăɘȹĂ‫ސ‬಑౼๱৐௫ȯȵɥȹɛɅĂʟĜʗɈߊ။௻࣍ɅɢɥȦĂྼᅟɅܾȲɀ QT.JoTBS Ɂɜ‫ސ‬಑ȱȹăȭɈॸ࢞౰‫ݪ‬Ȧ๬ીो‫ކ‬Ăర੠ൎ઄ɄɃɅߤᅙɁȧɥɂࡖ൒ȳɥă
ş2/2/2/4/ā๝ᆋ೸ࠫപᅙழळ‫ܒ‬౳ HBJB.J
ూ2/2/2/4/.2ɉĂႨߔɈழळ‫ܒ‬౳ʷʛʏʿˋɬ૲ȱĂʈ˅Ĝʨ˃ࠞࣃĆණ߈ဿ຦ࠫപᅙழळ‫ܒ‬౳ HBJB.J ɂ
HBJB.JJ ɬާཡȱɀȞɥăHBJB.J ɉ๝ᆋ೸ɬࠫപȳɥȹɛɅ‫ܦ‬ေ HQTĪHQT.SPīʓˋʍɬ຃੪ȳɥăHBJB.JJ Ɂɉණ߈ဿ຦ࠫപȳɥȹɛɅ‫ܟ‬ှ༜ਗ౰ާ৏˄ĜʘĪDQ.TBSīɬ຃੪ȱĂழळ TBS ‫ܒ‬౳ɂঘɐă

ూ2/2/2/4/.2ąʈ˅Ĝʨ˃ࠞࣃĆණ߈ဿ຦ࠫപᅙழळ‫ܒ‬౳ĪHBJB.J ɂ HBJB.JJī

3124༃๱ɢɤĂႨॸ࢞ଆɁɉ HQT ‫ܦ‬ေĪHQT.SPīʓˋʍɂ๝ાდ๱Ć‫ݗ‬๱ʯ˅ĜʮɅɢɥĂ๝ᆋ೸ɂ൥࡜
ɅȤȫɥᅕęɄএ௣ɬࠫപȳɥȹɛɅĂழळ‫ܒ‬౳ HBJB.J ɬާཡȱɀȞɥĪూ2/2/2/4/.3īăూ2/2/2/4/.3ɈɢȠɅĂȭɈழळ‫ܒ‬౳ɉʂˋʴĜʡʋˋʬʽĜʗɘȹɉʷʛʏʿˋृĪQbzmpbeīĂʋʶˋʡʟĜʗʧˋʡ˂ˋʈĪDETī
ĂฆఒृĪDNTīĂ๝ᆵृĪFQTīĂઽ౬౫সृĪBDTīȥɣ৭౰ȯɦɀȞɥă਱༃๱Ʌழळ‫ܒ‬౳຃੪ᅙɈ DET ᅙɈʂˋʴĜʡʋˋʬʽĜʗĪPCDī
Ă๝ાდ๱Ć๝ા‫ݗ‬๱ʯ˅ĜʮĪFEUQīȦࠊ౰ȱĂଌ௠ଌঅɬȱȹăᅰ༃๱Ʌɜණ௫ଌ௠ଌঅɬȳɥᅅฤɁȜɥă

―9―ూ2/2/2/4/.3/ā๝ᆋ೸ࠫപᅙழळ‫ܒ‬౳ HBJB.J ɂʮ˅ʛʈʘɼɺʈˁʸూ2/2/2/4/.4/ā!!GQHB Ʌɢɥ HBJB.J ᅙɈʂˋʴĜʡʋˋʬʽĜʗĪPCDī
ĂฆఒʏʑʞʸĪDNTīĂ๝ાდ๱Ć๝ા‫ݗ‬๱ʯ˅ĜʮĪFEUQīూ2/2/2/4/.5ɅĂຎॸ࢞ଆɈழळ TBS ‫ܒ‬౳ɬ૲ȳă਱‫ޑ‬Ă౦‫ޢ‬஑261ҹࢡਗ౰ާ৏˄Ĝʘ຃੪ழळ‫ܒ‬౳Īழळ‫ܒ‬౳ TBSīɈॸ࢞ʺʟ˃Ȧࠊ౰ȱȹă3116༃ȥɣএ੭ɅȞȹɥɘɁĂಫᅝ൥ߔɉɼˋʡʥʏɺۧහਂऋࣟ
ĪMBQBOīɂࢼວȱĂʈ˅Ĝʨ˃ණ߈ဿ຦ࠫപᅙɈǨʨˋʡĪୈ༜ౘ2/386HI{ ൑īɈۧහᅙਗ౰ާ৏˄ĜʘĪTBSīɬާཡȱɀȧȹăಫᅝ൥ߔȦާཡȱȹۧහᅙ TBS ʓˋʍɉ‫܀‬ĆტĆ‫ܬ‬Ɉ‫ࣗ܆‬ɄȱɁණ࢝࿍ჶɬ೏ცɅࠠ
૗Ɂȧɥ೔๏েळʓˋʍɁĂᄕ࠰Ɂɜࠫപ‫ݢ‬༑ɁȜɤĂ੠ޮࠠ૗ɅᄭɦȹʓˋʍɁȜɥăࡕശɈ‫ܒ‬౳ TBS ɉౘʠˋɈଋᆲɂෳȯ21n ɈɺˋʞʢɁȜɥȭɂɅൎȱĂႨߔཡɈழळ‫ܒ‬౳ TBS ɉ261ҹ‫ݚڬ‬Ʌॎᆲ‫ݛ‬ȯɦĂɺˋ

― 10 ―

ʞʢɉ෸श4/7n Ɉழळ‫ݛ‬Ʌ౰োȱȹăྡ੠ණɬ਒౼๱Īȉȉġ dn ౼๱īɅࠫപɁȧɥȭɈ‫ܒ‬౳ɉĂ3131༃Ʌ൅Ȼ௫ȬȳɥᅅฤɁȜɥăȭɦɅ຃੪ȳɥಫᅝ൥ߔ຾૵ާཡɈ‫ܟ‬ှ༜ਗ౰ާ৏˄ĜʘĪDQ.TBSīɅɢɤĂණ࢝࿍ჶɬᅕęɄ‫ܟ‬ှ༜ࠫപȦ‫ݢ‬༑ɂɄɤĂఛ౦ൣɈණ࢝ࠫപɅɄɥɂࡖ൒ȳɥă਱ষĂǑࡊ‫ڬ‬௫Ɉழळ‫ܒ‬౳ TBSɈʋˋʑʞ˄ĜʏʿˋɅɢɤĂණ࢝௫ɅȤȫɥວ௲ஒɬႴ໲ࠫപ‫ݢ‬༑ɂɄɥȹɛĂ੠ޮɈᅅപĪ๲ੋၦɦĂණྉ෺‫ݚ‬īĂɼˋʭˁɈࠠ૗Ă‫ޠ‬ᅖࠫപĂਡࣃࠠ૗ɄɃᅕęɄယᄘɁߤᅙɁȧɥăႨॸ࢞Ɂࠊ౰ȱȹழळ‫ܒ‬౳ TBS ɈۧහᅙࣸʹʛʅʹʛʏʽʩˁʴˁɺˋʞʢĪ෸श4/7nīɬూ2/2/2/4/.6Ʌ૲ȳă

ూ2/2/2/4/.5ąDQ.TBS ຃੪ழळ‫ܒ‬౳

ూ2/2/2/4/.6ąࣸʹʛʅʹʛʏʽʩˁʴˁɺˋʞʢ

― 11 ―

ş2/2/2/5/āఱ৙‫ܒ‬౳ࠣ౫ᅙණ௫ࣟ
ຎʓˋʗĜȦ‫ۿ‬ᅙȳɥఱ৙‫ܒ‬౳ࠣ౫ᅙණ௫ࣟĪʋʶˋʡĆʞ˄ʹʠ˂ᅙ T ʨˋʡɂʷʛʏʿˋʟĜʗʘɾˋ˂
ˋʈᅙ Y ʨˋʡīɂȱɀĂ෸श4/7n Ɉɺˋʞʢɂ଱‫ܒ‬౳ࠣ౫ଆȦ৙ߔ഍ਗງǕިɂǔިɅĂဋ‫ܒ‬౳ࠣ౫ଆȦࠞࣃ˂ʺĜʠʓˋʏˋʈॸ࢞ʓˋʗĜॸ࢞ງǎިɅ3125༃23ॢ32໲Ʌಡ඲ȯɦĪూ2/2/2/5/īĂ3126༃๱Ʌ‫ܒ‬౳തɂɈฆఒȦɁȧɥɢȠɅĂT ɂ Y ʨˋʡɈᅕęɄɺˋʞʢɈާཡɬ਄Ƚȹă‫ݚڬ‬ɉȷɈ઱ᅕɁȜɥă
Ĳɺˋʞʢငć৙ߔृ഍ਗॸ࢞ງ‫ݎ‬௫ĪǕިīĳā
Ć! ɺˋʞʢćʩˁʴˁɺˋʞʢ
Ć! ɺˋʞʢ෸शć4/7n
Ć! ှ༜ಜࠓć‫ۦ‬ಽ‫ܟ‬ှ༜ĪSIDQīɂ੆ಽ‫ܟ‬ှ༜ĪMIDQīɅಜࠓ‫ݢ‬༑! ൏ဇć71n0 ࿓
Ć! ൏రćర๱ǒ
Ć! ɺˋʞʢɈʫĜʸဍćǯʨˋʡāʋʶˋʡᅙ3/5ŋĪʬĜʇȥɣĽǏeC ɅɄɥཱྀ‫ڱ‬ī! āāāāāāāāāāǯʨˋʡāʞ˄ʹʠ˂ᅙ3/4ŋĪʬĜʇȥɣĽǏeC ɅɄɥཱྀ‫ڱ‬ī! āāāāāāāāāāǴʨˋʡāʟĜʗʘɾˋ˂ˋʈᅙ1/7ŋĪʬĜʇȥɣĽǏeC ɅɄɥཱྀ‫ڱ‬īĆ! ᆀຶ࢒ɍʍɼʡ˅Ĝʮćʍɼʡ˅ĜʮāĽ29ġĽ31eC! āāāāāāāāāāāǯʨˋʡāāāā46ġ47eCjd! āāāāāāāāāāāǴʨˋʡāāāā58ġ59eCjd
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26ŋ0tfdBD ʍĜʴʺĜʗऄ຦FMĽǎġ:3ŋ

26ŋ0tfdBD ʍĜʴʺĜʗऄ຦

Ĳɺˋʞʢ౫সृĳɺˋʞʢ౫সृɉಮᅙʋˋʠ˅ĜˁĪGQHBĂʶɼʋˋຑīɬ઴ᅙȱĂ‫ࡥݚ‬Ɉ࡙༑ɬ૩ȾăĆ! ऄ຦ૄᇇɉ B[ĂFM ࢼɅʩ˃ʑᇙ୸ᆵ
Ć! B[ĂFM Ɉ˂ʷʛʠʑɼʛʙ௻ൔຑɈʑʞĜʗʑ௶ၡɬࠣ౫ᅙ QD ɒഗ୸‫ݢ‬༑
ĲʋʶˋʡृĪǯʨˋʡīĳʋʶˋʡृĪǯʨˋʡīɉ‫ࡥݚ‬ɈʺʐʽĜ˃ɂ࡙༑Ć઱ᅕɬ૩ȾăĆ! ʺʐʽĜ˃āāāʋʶˋʡཡ౺ࡉĆဿ෮࡙āāāഗఒ࡙
āāāVQ ʋˋʨĜʗāāāʩˇĜɺˋʯĆ! ࡙༑Ć઱ᅕāāāഗఒ๝ᆵć੕൥211X
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āāāဌ෮࡙

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Ć! ࡙༑Ć઱ᅕāāāୈ༜ౘć3-311ġ3-411NI{
āāāှ༜ć੆ಽ‫ܟ‬ှ༜ĪMIDQīāāāဿ෮ၫૺćQDN-!CQTL-!QN-!GTLāāāʫʛʠ˄Ĝʠć3/159lcqtĂ5/1:7lcqtĂ239lcqt!AQDN0CQTL0QN
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āāāဌ෮࡙
Ć! ࡙༑Ć઱ᅕāāāୈ༜ౘć9-136ġ9-511NI{
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Ć! ࡙༑Ć઱ᅕ! āāā଱ࠣ౫ଆᅙ QD ࢒ɍࠣ౫ʕʭʠɾɿɺ
! āāā଱ࠣ౫ଆᅙ QDć‫ࡥݚ‬Ɉ઱ᅕɈ GB.QDĪ35૪࠰ᇦറ‫ۿ‬๖ൎܾ QDī! āāāāĆPTćXjoepxt!8Ī75ʫʛʠīɘȹɉ Xjoepxt!9Ī75ʫʛʠī! āāāāĆDQVćɼˋʞ˃ Dpsf!j8ʯ˅ʓʛʍĜ!ǐʋɺ! āāāāĆʹʺ˂ćǔHC า๱! āāāāĆIEEć611HC า๱! āāāāĆʺʣʗć2:ɼˋʙˇɼʡʺʣʗɘȹɉ2:ɼˋʙʺʣʗĪǎ൤īĆ! ʕʭʠɾɿɺć‫ࡥݚ‬Ɉ࡙༑ɬɜȾ
! āāāUMF ૵຦৩ఛ࡙༑ć! āāāāĆಡฤȯɦȹ૪ਟɅ૵຦ɁĂOpsbe ɄɃɈ Xfc ʍɼʠȥɣ UMF ௶ၡɬʘɾˋ˅Ĝʡ‫ݢ‬༑! āāāჟఱ‫ۿ‬ᅙʑʉʐʽĜˁĜ࡙༑ć! āāāāĆૄฤࡖ࠰ĪǍ໲ġǓ໲า๱īɈʑʉʐʽĜ˃ɬ੼౰‫ݢ‬༑ă! āāāāĆ੼౰ȱȹʑʉʐʽĜ˃Ɉ଴຦ဿ৩‫ݢ‬༑ă! āāāāĆʑʉʐʽĜ˃Ɉ૪ਟɅɄɥɂ૵຦Ɂࠫപ຦੼ާ઻ă! āāā‫ܒ‬౳ʩʑᅅၡʹĜ˃ഗఒ࡙༑ć! āāāāĆ޶ຎȳɥʩʑɈ૪ਟĪஈྩާ઻Ɉ૪ਟɁɜ‫ݢ‬༑īɅɄɥɂ๨ሃɺʡ˄ʑɅʹĜ˃ഗఒ‫ݢ‬༑ă! āāāɺˁĜʠʹĜ˃ഗఒ࡙༑ć! āāāāĆɺˋʞʢऄ຦ृĂฆఒ࡙ࡉ‫௵ڽ‬ɄɃɈ‫௵ڽ‬Ȧཡ౺ȱȹ௲ਗĂ๨ሃɺʡ˄ʑɅɺˁĜʠʹĜ˃ɬഗఒă! āāāထౘ‫ܒ‬౳ࠣ౫ĪǑ‫ܒ‬౳ɘɁࠣᆅ‫ݢ‬īć! āāāāĆʑʉʐʽĜˁĜɂວᅕɅထౘ๨ሃȱȹ‫ܒ‬౳Ɉʩʑɬ೔ɀ෮ɓĂʑʉʐʽĜ˃ɬ౺౰‫ݢ‬༑ă! āāāāĆྼᅟɅܾȲʩʑɈ୭ɄɤɞȷɈ૪Ɉᄭಪ๱ɬ଴຦ဿ৩ȱĂჟఱ‫ۿ‬ᅙʑʉʐʽĜˁĜ‫ݢ‬༑ă! āāāพ๝ൎ઄ćࠣ౫ᅙ QD ɂʟɻʑʯ˄ɼᅙɈ VQT ɬಡ඲ă! āāāWjtjcmfUjnf Ɉ211ယᆎĪœī࿍૲࡙༑ă! āāā૪ਟ࿍૲ćVU ᄭಪɂ KU ᄭಪ࿍૲ಜɤൖȢ࡙༑ɬ૩Ⱦă! āāāBPT ŕ MPT ࢒ɍ NBY!FM Ɉ B[ ߍɈʈˁʭɻʛʇ࿍૲࡙༑ɬ૩Ⱦă! āāāāāŦ BPTĪBdrvjtjujpo!pg!TjhobmīĂMPTĪMptt!pg!Tjhobmī― 13 ―

! āāā໸‫ڷ‬໲૪Ɉʩʑʏʷʽ˄Ĝʠ࡙༑ɬ૩ȾăĆ! ʍʮ QD Ȥɢɍဋࠣ౫ଆᅙ˂ʺĜʠ QD! āāāPTćXjoepxt!8Ī75ʫʛʠīɘȹɉ Xjoepxt8Ī75ʫʛʠī! āāāDQVćɼˋʞ˃ Dpsf!j4ʯ˅ʓʛʍĜ! āāāʹʺ˂ćǐHC า๱! āāāʺʣʗ ;2:ɼˋʙĪǍ൤ī
Ĳɺˋʞʢࠠ૗࡙ĳĆ! ʥʛʠˇĜʇʃʹˁĆ! ᄕ࠰௎ცĪMFE ຂ৉ࡉīĲHQT ିఒ࡙ĳ
Ć! HQT ିఒ࡙
Ć! ʗɼʸʋĜʡ౺౰࡙༑
Ć! Ǎqqt ౺౰࡙༑

ూ2/2/2/5/āႨʓˋʗĜɈఱ৙‫ܒ‬౳ࠣ౫ࣟ

ş2/2/3ā৉ߔโ˂ʺĜʠʓˋʏˋʈɅɢɥ൥࡜Ȥɢɍණ࿍ჶ௶ၡɈଲຶɂ‫ސ‬಑
ş2/2/3/2ā!!ණ௫ʍˋʯ˂ˋʈക඲ɂ඾೧ˁʶˋˁɼʘĜɅɢɥൎᆔ५ʀɺ˅ʖ˃Ɉູ౯࿎‫! !ݟ‬Īৡࢀථც +ĂKbnvsve!Bnjovejo++Ăᤁા෸ৠĂ࢏౦৘ცāāāāāāāāāā+ ൥ߔۡᅃਗ‫ݨ࢞ॸߔݨ‬ୌ઺‫ݻ‬าĂ++ ວ!ག઺‫ݻ‬าī൥࡜ෂɬ࿲ᄿȳɥ‫ܕ‬ൌɘȹɉঙൌɈᆙાɁȜɥʀɺ˅ʖ˃ɉĂၪଗେૅɬฆȲɀණ࢝‫ݗ‬ඤ‫ݛ‬Ʌ‫ࣗ܆‬ȳɥɕȥĂ‫܀‬ᆙɈ߇ɂɄȽɀ࡜েɅɜ൥ȧɄ‫ࣗ܆‬ɬᅇȢɥăʀɺ˅ʖ˃ोപၭɅɉĂ൥်ȱɀʍˋʯ˂ˋʈɅɢɥၫၭɂ
৉ߔโ˂ʺĜʠʓˋʏˋʈɅɢɥ଴ၭȦȜɥăDFSfT ɁɉĂ൥࡜ʟĜʗଲຶˁɼʘĜക඲ĪBunptqifsjd!Ebub!
Dpmmfdujpo! Mjebs-! BEDMīɈ‫ࠞێ‬ɂȱɀǏ༜ෳʥʭɿ˅ʹĜʗĂǓ༜ෳʀĜʍ˅ʹĜʗĂȤɢɍǎ൤Ɉ৉ߔૺ
ʩĜʞɻʇ˃ʃɾˋʗĜĪPQDīɅɢɤĂᇦറโɅ൥࡜ʀɺ˅ʖ˃ɬʍˋʯ˂ˋʈȱɀȞɥăႨॸ࢞ɁɉĂȭɦɣණ௫പࡉɅɢɥʟĜʗɅൎȱɀʷĜઢᅸोધɬ਄Ƚɀʀɺ˅ʖ˃Ɉ৉ߔູ౯ɬोધȱĂBEDM ɈʷĜઢᅸˁɼʘĜĂˁʶˋઢᅸˁɼʘĜɈोപय़‫ݪ‬ɬ྘ߏȱȹăˁɼʘĜၫาૺɬ‫ސ‬Ȟɀ௉ઢबౘɈ਒๱ယ࿫ɬຩ୸ȳɥȹɛɅɉĂ௉ઢबౘɂষၫઢᅸबౘɈ྘ɂȱɀᅇȢɣɦɥˁɼʘĜ྘Ȧ࿤‫ݢ‬ज़ɁȜɥăȭȭɁɉວ૾ळɁ Njf ઢᅸ
ఒਖɂ Sbnbo ઢᅸఒਖɬວ૪ोപ‫ݢ‬༑ɄˁɼʘĜɅɢɤĂ਒๱ယ࿫ɬ࠸ɛȹˁɼʘĜ྘Ɉ૪ृᇙဿ‫ݛ‬ɬຩ୸ȱȹăʷĜઢᅸˁɼʘĜɁɉĂ൥࡜ෂɅଗ୸ȱȹʩ˃ʑ˄ĜʎĜ৉Ɉ‫ێ‬ငȦষၫઢᅸȯɦɀॳ୸ക඲ɅᄋɥȹɛĂॳ୸༜ෳɉଗ୸˄ĜʎĜ৉ɂວ‫ێ‬ɁȜɥĪජ౯ઢᅸīăʷĜઢᅸɈˁɼʘĜၫาૺɁɉĂʀɺ˅ʖ˃ɂယાɅɢɥ
ষၫઢᅸबౘ‫ެڬ‬ɅĂܽဌɈ৉ᇭɈຟ‫ݿ‬ᆎĪʀɺ˅ʖ˃ɂယાɈ௉ઢबౘɬ৉ᇭɅ‫ܨ‬ȽɀಓယȳɥȭɂɅɢɤຶ
ɣɦɥຟ‫ݿ‬ᆎīȦ჎ඪౘɂɄɥăȭɈȠȻĂऋ࡜ယાĪ඾೧Ăબ೧īɅȾȞɀɉܴ෸ယ࿫ɉɕɖड़ɘȽɀȤɤĂȷɈষၫઢᅸबౘɂ௉ઢबౘɉ˄ɼ˂ĜઢᅸɈଲɤ‫ڙ‬ȞɅɢȽɀᆯȞ౼๱ɁైฤɁȧɥă‫ێ‬ၫĂʀɺ˅ʖ˃ɉȷ
Ɉ৉ߔູ౯Ɉဿ຦ဍȦ൥ȧȩĂ௉ઢबౘɂষၫઢᅸबౘɈ྘ɂȱɀᅇȢɣɦɥˁɼʘĜ྘Ɉඩɉ21ġ211ts Ɉཱྀ‫ڱ‬Ɂ൥ȧȩဿ‫ݛ‬ȳɥăȭɈȹɛĂʷĜઢᅸˁɼʘĜඍ຾ɁɉˁɼʘĜ྘Ɉඩɬ‫ڷێ‬โɅड़ɛɣɦȴĂʀɺ˅ʖ˃௉ઢबౘɬ౷ߊɅ࢙ɛɥȭɂɉ‫ཾێ‬Ʌɉਲ໧ɁȜɥăˁʶˋઢᅸɅȤȞɀɉĂઢᅸɬ਄ȠယાɅܾȲɀॳ୸ȯɦɥ༜ෳȦဿ‫ݛ‬ȳɥĪྥජ౯ઢᅸīăȭɈȹɛĂ඾೧ယાɈɢȠɅ࿈โယાɈ਒๱ယ࿫ȦࡕඪɁȜɦɊĂ৉Ɉຟ‫ݿ‬ᆎĂȳɄɩȻʀɺ˅ʖ˃ઢᅸबౘɬ຾ᆏɅ࢙ɛɣɦ
ɥᆀ๘ȦȜɥăȹȺȱĂઢᅸ৉ࣅ๱ɉʷĜઢᅸɞ˄ɼ˂ĜઢᅸɅ྘ɓɀǏख़า๱ழȯȩĂ഼Ɉઢᅸ৉ɞ༬ा৉ɬ
୥ယɅதࢦȳɥȭɂȦྼᅟɂɄɤĂࠫപɉᄕ࠰ɈəɅ౫ঔȯɦɥăႨॸ࢞ɁɉĂOe;ZBH ˄ĜʎĜɈǏ༰༜ɁȜ
ɥ༜ෳ466on Ɉ˄ĜʎĜ৉ɬଗ୸ȱĂ466on ʙʻˋʥ˃ɁʷĜઢᅸɬĂ498on ʙʻˋʥ˃Ɂ඾೧ယાɈˁʶ
ˋઢᅸɬࠫപȱȹăʷĜઢᅸɈोધɁɉĂʀɺ˅ʖ˃Ɉᆙशယ࿫ɂထ೧औಠᆎȦࡊႨโɄʩˁʹĜʗɁȜɥăᆙशယ࿫ɅȾȞɀɉĂǎ൤Ɉ PQDĪ˂ʂˋ LD33C-! LD12Eīȥɣᆙशཱྀ‫ڱ‬1/19ġ1/6̂n ɅȤȞɀʟĜʗȦଲຶɁȧɥăȭȭɁɉĂǎၤ౯Ɉൎౘ౷ࡤယ࿫ɬ‫ݜ‬ฤȱĂȷɦȸɦɅȾȞɀʺĜʡ཰शn j Ăဍx j Ăࡤ߆‫ݛ‬ฤౘo j ɬʩˁʹĜʗ‫ݛ‬ȱ

― 14 ―

ȹĪj Ł2-3īăထ೧औಠᆎɅȾȞɀɉ෸ಞɈोപɉ໧ȱȞȦĂʥʭɿ˅ʹĜʗĪUTJ4674īȥɣຶɣɦɥǏ༜ෳ
Ī561-!661-!811onīɈǓġ281๱Ȥɢɍ:1ġ281๱ɈઢᅸबౘĂʀĜʍ˅ʹĜʗĪNbhff!BF42īȥɣຶɣɦɥǓ༜ෳĪ481-! 581-! 631-! 6:1-! 771-! 9:1-! :61onīɈ࢓େबౘɬʭɻʛʠȳɥɢȠɅထ೧औಠᆎଌౘငĂࢭౘငɬʩˁʹĜʗɂȱȹă

ూ2/2/3/2/.2āණ௫ʍˋʯ˂ˋʈʟĜʗɈʭɻʛʞɻˋʈय़‫ݪ‬Ī3128༃Ǎॢ34໲32;11KTUīూ2/2/3/2/.3ā๷ࡠɈĪǽī਒ଈ๱૪Īଈ๱92ġ:3œīɂĪǾīฝଈ๱૪Ī55ġ58œīɈʀɺ˅ʖ˃ᆙशယ࿫Ɉ྘ߏ

― 15 ―

ూ2/2/3/2/.2ɅĂ3128༃Ǎॢ34໲32;11KTU Ɉණ௫ʍˋʯ˂ˋʈʟĜʗɈʭɻʛʞɻˋʈय़‫ݪ‬ɬ૲ȳăǎȾɈᆙशယ࿫ɅȾȞɀĂĪn j -!x j -!o j īŁĪ1/1172:-!1/75-!5/25Ŀ214ī-!Ī1/1692-!1/33-!24/6Ŀ214īɁȜɤĂऔಠᆎ
ɉ2/66.1/127j-! ˁɼʘĜ྘ɉ73/9ts ɁȜɥăూ2/2/3/2/.3ɅĂ๷ࡠɈĪǽī਒ଈ๱૪Īଈ๱92ġ:3œīɂĪǾīฝଈ๱૪Ī55ġ58œīɈʀɺ˅ʖ˃ᆙशယ࿫Ɉ྘ߏɬ૲ȳăྫழᆙાതɈപฤɬ਄Ƞ PQDĪLD33CīɅɉࡏଫക඲Ȧ࿥ȞɀȤɤĂ91༰า๱Ɉࡏଫɬ਄ȽɀᆙાౘɬപฤȱɀȞɥăȭɈʭɻʛʠɁɉĂ༰ᆎɬ෮౲ȱɀĂ
LD33C Ɉ੕൥ᆙાȦ LD12E Ɉ੕ழᆙાɂວȲယ࿫ඩɬ૲ȳɢȠɅယ࿫ɬड़ɛɀȞɥă਒ଈ๱ɁɉĂᆙशယ࿫Ȧᆙા཰शȦ൥ȧɄതɅʏʭʠȱɀȤɤĂɘȹĂʃɾˋʠඩɜฝଈ๱૪Ʌ྘ɓɀ൥ȧȞभ৐Ȧॽɣɦɥă
ూ2/2/3/2/.4Ʌ Ǎ ॢ34໲31;41ġ33;41Ɉ ˁ ɼ ʘ Ĝ ఒ ਖ ɂ ȷ Ɉ ‫ ސ‬಑ य़ ‫ ݪ‬ɬ ૲ ȳă ວ ూĪ ǽ ī ɉ ʷ Ĝ ઢ ᅸ
Ī466onīĂ඾೧ˁʶˋઢᅸĪ498onīɈఒਖɁȜɥăˁʶˋఒਖɅȾȞɀɉĂ‫ސ‬಑૪Ɉྫယ‫ܩ‬ધɅɂɜɄȠʦɼʒɬฝঌȳɥȹɛɅĂိߦ‫ݛ‬ɬȥȫɀȞɥăĪǾīɉĂʷĜઢᅸఒਖɈ Gfsobme ၭĪऋ࡜ယાɂʀɺ˅ʖ˃Ɉ
ఒਖȥɣʀɺ˅ʖ˃ɬ‫ސ‬಑īɅɢɥʀɺ˅ʖ˃௉ઢबౘɈ‫ސ‬಑य़‫ݪ‬ɂĂˁʶˋఒਖɈɺ˃ʌ˂ʒʸɅɢɥʀɺ˅
ʖ˃௉ઢबౘɈ਒๱ယ࿫ĂĪǿīɉວȲȩষၫઢᅸबౘɈ਒๱ယ࿫ɬ૲ȱɀȞɥăʷĜઢᅸɈ Gfsobme ‫ސ‬಑Ɂɉණ௫ȥɣ௫ऋɘɁ‫ێ‬ฤɈˁɼʘĜ྘ĪȭȭɁɉ46tsīɬ‫ݜ‬ฤȱɀȞɥȹɛĂᆤଞɈ࠰Ʌഊ‫ۅ‬Ȧ౺ȲɀȞɥăĪǾīɈ௉ઢबౘɂĂĪǿīɈষၫઢᅸबౘȥɣˁɼʘĜ྘ɬड़ฤȱȹɈȦĂĪȀīɈय़‫ݪ‬ɁȜɥăණ௫࿥ࣷɉˁɼʘĜ୭Ʉɤ࠲ౘɈ‫ࣗ܆‬ɬିȫɀழȯɄඩɅɄȽɀȞɥȦĂ਒๱ౘ211n ɢɤ௫ऋɁɉĂൃຎɄယ࿫ȦຶɣɦɀȞɥɂ৽Ȣɣɦɥă
൥࡜Ȧ྘ߏโ౸௺ɁˁɼʘĜࠫപɅไȱȹ௸ॣɁȜȽȹ3128༃Ǎॢ34໲ġ35໲ɅȤȫɥˁʶˋˁɼʘĜ‫ސ‬಑य़‫ݪ‬ɈȠȻĂ਒๱2-611n ‫ݚڬ‬ɅȤȫɥˁɼʘĜ྘Ī੕൥ඩīɈ૪ृᇙဿ‫ݛ‬ɂĂණ௫പࡉɅɢɥˁɼʘĜ྘Ɉ૪ृᇙဿ‫ݛ‬ɬ྘ߏȱȹय़‫ݪ‬ɬూ2/2/3/2/.5Ʌ૲ȳă೐཰ɈǍॢ34໲Ɉᄕ࠰ɅȾȞɀɉĂᆤଞɅᆯȞ‫ێ‬ඳȦəɣɦɀȤɤĂຶɣɦȹඩɈཱྀ‫ڱ‬Ī73ġ87tsīɜൃຎɄౘඩɁȜɥăষ཰ɈǍॢ35໲჎ცɈʟĜʗɁɉĂˁʶˋˁɼ
ʘĜɅɢɥ‫ސ‬಑ඩȦ྘ߏโ൥ȧɄཱྀ‫ڱ‬Ī61ġ91tsīɁဿ຦ȱɀȞɥăɘȹĂ35໲Ɉ17૪ɁɉĂණ௫പࡉɅࡊȿ
ȩˁɼʘĜ྘Ȧ211ts ɬ෰ȢɀȞɥă਱ষĂණ௫പࡉɈʟĜʗɈ‫ސ‬಑ɅȤȫɥʩˁʹĜʗೊฤၭɞĂూ2/2/3/2/.3ɅɜॽɣɦɥɢȠɄപࡉ໘Ī྘ߏโฝଈ๱īɂଌ൥࡜Ī਒ଈ๱īɈଈ๱ੇɅɢɥᆙशဿ‫ݛ‬ɬ৽ᆞȳɥȭɂɅɢȽɀ‫ޜ‬೑Ȧॽਮɘɦɥă‫ڬ‬௫ĂႨॸ࢞ɁɉĂණ௫ʀɺ˅ʖ˃ोപക඲ɅɢȽɀຶɣɦɥઢᅸĆ࢓େबౘȤɢɍᆙशယ࿫ʟĜʗȥɣʷĜઢᅸɅɢɥʏʷʽ˄Ĝʏʿˋɬ਄ȽɀˁɼʘĜ྘ɬຩ୸ȱĂᆤ଴ၭȥɣຶɣɦɥय़‫ݪ‬Ɉ྘ߏɬ਄ȽȹăႨอ‫ڨ‬଴ၭɅɢɤĂණ௫ʀɺ˅ʖ˃ोപക඲ɈʟĜʗɬ‫ݚ‬඘ɁɈࣃ‫ॣ௸ޢ‬ɂȳɥഽ༜ෳˁɼʘĜ‫ސ‬಑Ȧ‫ݢ‬༑ɂɄɤĂ௫ऋɅ‫܀‬Ȧശ੭ȳɥȹɛɅܳၫɁɈࣃ‫ॣ௸ޢ‬ȦଲຶɁȧɄȞ௲ਗɁȜȽɀɜĂˁɼʘĜఒਖɬฤᆲโɅ‫ڙ‬ȢɥɢȠɅɄɥă਱ষĂȭɈၫၭɬᆀᅙȱɀĂˁɼʘĜɬ઴ᅙȱȹʀɺ˅ʖ˃Ʌɢɥ‫܀‬౺౰‫ݿ‬าຑɈॸ࢞Ȧమ๐ȳɥȭɂȦࡖ൒ȯɦɥă

ూ2/2/3/2/.4āˁɼʘĜఒਖɂȷɈ‫ސ‬಑य़‫ݪ‬ĪǍॢ34໲31;41ġ33;41KTUī― 16 ―

ూ2/2/3/2/.5āˁʶˋˁɼʘĜɂණ௫ʍˋʯ˂ˋʈʟĜʗȥɣຶɣɦȹˁɼʘĜ྘Ī466onīɈ྘ߏş2/2/4/ā!!ࣷಞ˂ʺĜʠʓˋʏˋʈɅɢɥˁĜʐʭʛʠʯ˂ˋʠˁɼʘĜʏʷʽ˄ĜʏʿˋɈȹɛɈୃࠁ৭ഢʟĜʗଲຶĪႨഽ‫ݣ‬ცĂߝঈয়શīĪǍīɉȲɛɅ
ȭɦɘɁၡਠȱɀȧȹɢȠɅĂഽߍࠫപʟĜʗɬᅙȞȹ‫ܒ‬౳৉ߔʓˋʍɅɢɥᆌ‫ۊ‬ఆ౺Ɉණ௫ʨɼʂʶʑైฤ
ɺ˃ʌ˂ʒʸާཡɬ਄ȽɀȧȹăHDPN.D0THMJ ࠫപʟĜʗɅൎȳɥວ଴ၭɈไᅙɉĂ3128༃๱ষ཰ɅᅅฤȯɦɀȞɥă‫ێ‬ၫĂວɺ˃ʌ˂ʒʸɬ THMJ Ʌไᅙȱȹय़‫ݪ‬Ɉॳ௠ɉĂଌപɅɢɥʨɼʂʶʑोപඩɈେୠɈəɁ
ɉ࿤ഫɁȜɥȭɂɉცཆɁȜɥă‫ࢦݿ‬Ɉʨɼʂʶʑ෮ੈय़‫ݪ‬ɬࡥሃȱȹဦॷɈౘɜঔɣɦɀȞɥăୃ਒Ȥɢɍ࣑਒෸शɬोപȱȹ෮ੈɉ౦‫߂ޢ‬ණɁ਄ɩɦɀȤɤĂȷɦɣɈʟĜʗȥɣɺ˅ʹʠ˂ĜૺɬᅙȞɀʨɼʂʶʑైฤ
ɬ਄ȞĂȷɈඩɬॳ௠ඩɂȱɀᅙȞɥȭɂȦॳບȯɦɀȞɥăȱȥȱɄȦɣĂȷɈɢȠɄ෮ੈʟĜʗɁȜȽɀɜĂఝᆹɈ౰ෳɞᇚ‫ݛ‬ɬ৽ᆞȳɥɂĂ‫ܒ‬౳ࠫപ૪ȥɣܳȞ‫ࢦݿ‬ɈʟĜʗɬᆀᅙȳɥȭɂɉɁȧɄȞăȭɈɢȠɅĂ‫ܒ‬౳Ʌɢɥණ௫ʨɼʂʶʑైฤඩɈॳ௠Ʌɉᆀᅙ‫ݢ‬༑ɄʟĜʗɈ࿤ഫȦ൥ȧɄᄎ൨ɂɄɥă‫ێ‬ၫĂ઀਱ˁĜʐʭʛʠʯ˂ˋʠɈʑʲĜʑˁɼʘĜɅɢɥୃ਒ोപ଴ၭȤɢɍʨɼʂʶʑైฤ଴ၭȦާཡȯɦȾȾȜɥăဴਡɈ OBTB Ȧ࣡ණɅȤȫɥ࿉ஸɂ‫ޠ‬࿉ɈৎȯɬोപȳɥᄆโɁ3114༃ȥɣ311:༃Ʌ‫ۿ‬ᅙȱȹ
JDFtbu Ȧ຃੪ȱȹʑʲĜʑˁɼʘĜɈࠫപʟĜʗɉĂᆌ‫ۊ‬ఝᆹɈୃ਒ైฤ‫ݢ‬༑౯Ȧࡖ൒ȯɦౘഽȩɈॳ௠ȦଌૈȯɦȹȦĂୃ਒ైฤ౼๱ɉᄝǐn ȥɣǔn Ɉိࣧ૵௮িੇɬɜȻĂɂȩɅभଚණɅȤȫɥైฤ౼๱ɉ൥ȧȩฝ‫ݚ‬ȳɥȭɂȦၡਠȯɦɀȞɥăȭɦɅൎȱĂʶ˃ʙʭʛʠʯ˂ˋʠɅɢɤණྉჶɈभଚၒ౷ɬ‫ݢ‬༑ɂȳɥఛȹɄʑʲĜʑˁɼʘĜާཡȦࡖ൒ȯɦɀȞɥăऋ࠰โɅࣷಞȳɥණ࿍ჶɅൎȱɀထౘɈ˄ĜʎĜʩ˃ʑɬ௎ଗȱĂ߂ʭʛʠʯ˂ˋʠȥɣɈ˂ʗĜˋఒਖɬ‫ސ‬಑ȳɥȭɂɅɢɤখęɈʭʛʠʯ˂ˋʠ໘Ɉୃ਒ɬైฤȱĂȥȾࠫപȯɦȹʯʛʠʭ˂ˋʠ࠰ɈभଚɅɢȽɀୃ਒ైฤඩɬၒ౷ȳɥ଴ၭɬᅙȞɀʏˋʈ˃ʭʛʠʯ˂ˋʠɁᄎ൨ɂɄȽ
ȹभଚණɅȤȫɥైฤিੇɬॎঌȳɥȭɂȦ‫ݢ‬༑ɂ৽ȢɣɦɀȞɥăʑʲĜʑˁɼʘĜɅɢɥୃ਒ȤɢɍʨɼʂʶʑɈైฤȦ‫ݢ‬༑ɅɄɦɊĂ೔౦‫ޢ‬Ɂ႐൥ɄౘɈʍˋʯ˃ȦᆀᅙɁȧɥȭɂɅɄɤĂ৉ߔɼʹĜʐʻɅɢɥʨɼʂʶʑైฤඩɈॳ௠ʟĜʗɂȱɀᆀᅙȳɥȭɂȦ‫ݢ‬༑ɂɄɥăჟሄĂȭɈఛȹɄʑʲĜʑˁɼʘĜɅɢɥୃ਒Ȥɢɍʨɼʂʶʑైฤ౼๱ȦɃɈา๱৐௫ȳɥȥɅȾȞɀɉ୥ယɅ
ॳບȯɦɥɓȧɁȜɤĂȷɈȹɛɅɉˁɼʘĜʟĜʗɈିఒఒਖʏʷʽ˄ĜʏʿˋȦྼీɂɄɥăȭɦɘɁɅĂˁĜʐʭʛʠʯ˂ˋʠˁɼʘĜȦఝᆹɬࠫപȱȹ੫Ɉఒਖʏʷʽ˄ĜʏʿˋɅȾȞɀɉĂୃࠁʺʟ˃ɬᅙȞȹ‫ݜ‬೻ఝᆹɬᅙȞȹ଴ၭɞʑʺĜ˃ʭʛʠʯ˂ˋʠɈਂऋ࡙ˁɼʘĜʟĜʗɬᅙȞȹɜɈȦၡਠȯɦɀȞɥăୃࠁʺʟ˃ɬᅙȞȹ‫ݜ‬೻ఝᆹɁɉĂ৉ࢻਗɅɢɥୃवɬ৽ᆞȱɀȞɄȞȹɛĂএଌɈఝᆹ໘ɈઢᅸൌĪᅝĂ૊ຑīɈె෸ယ࿫Ȧ੔এɁȧɀȞɄȞ‫ݢ‬༑౯Ȧ਒ȩĂʑʺĜ˃ʭʛʠʯ˂ˋʠɈਂऋ࡙ˁɼʘĜʟĜʗɉˁĜʐʭʛʠʯ˂
ˋʠɈఒਖʏʷʽ˄Ĝʏʿˋɬ਄ȠɅɉ๘დ๱ȦฝȳȨɥɂȞȠᄎ൨ȦȜɥăȷȭɁĂႨ༃๱ɉˁĜʐʭʛʠʯ˂ˋʠɈఒਖʏʷʽ˄ĜʏʿˋɬଌૈȳɥɅഫɥ๘დ๱ɬᄵȳɥࣷಞ˂ʺĜʠʓˋʏˋʈʟĜʗɅɢɥ๘दʟĜʗ౺౰ɂĂȷɈ๘दʟĜʗɬᅙȞȹࠤ‫ڹ‬ʏʷʽ˄Ĝʏʿˋɬ਄ȞĂࣷಞ˂ʺĜʠʓˋʏˋʈɅɢȽɀଲຶȱȹ๘दɅɢȽɀˁĜʐʭʛʠʯ˂ˋʠɈఒਖʏʷʽ˄ĜʏʿˋɈ‫ݢ‬༑౯ॳບɬ
਄Ƚȹă

― 17 ―

ĪǎīʑʺĜ˃ʭʛʠʯ˂ˋʠɈࣷಞˁɼʘĜʟĜʗɅɢɥʏʷʽ˄Ĝʏʿˋ
ూ2/2/4/.2ɉழळჟఱʰ˂Ʌ຃੪ȱȹ˄ĜʎĜʑʅʻʢɅɢ
ɤଲຶȱȹʃˁʶʜᆹɈǏ૫ই๘दʟĜʗɁȜɥăୃࠁव௻ȦცߊɅനȢɣɦɀȤɤĂȥȾᆹஸĪණྉჶīɘɁ˄ĜʎĜȦ਒დ๱Ɂຟ‫ݿ‬ȱɀȞɥȭɂȦɩȥɥă๘დ๱ɉ611๘ 0n3
ɬ෰ȢɥăȭɈɢȠɄʟĜʗɬᅙȞɀˁĜʐʭʛʠʯ˂ˋʠ
ˁɼʘĜɈఒਖʏʷʽ˄Ĝʏʿˋɬ਄ȢɊĂএଌɈఝᆹɅȤȫɥఒᅲ౯ɈȜɥय़‫ݪ‬ɬࡖ൒ɁȧɥăୃࠁɈ੕௫඘ɂණྉɂ
Ɉ [ ඩɈੇȥɣᅎ‫ڹ‬Ʌୃ਒Ɉोപɜ‫ݢ‬༑ɂɄɥăȱȥȱɄȦɣĂȭɈɢȠɄ൥ჶಓɈࠫപൎ௣ɅൎȱɀୃࠁɅࣷಞȱȹ਒๱ȥɣࠫപɬ਄Ƞ௲ਗĂʯˁʛʠʭʁĜʸɁȜɥྦ᩼ൌĪ਱Ɉ௲ਗழळჟఱʰ˂īɉထౘˁɼˋɈࠫപೀɅȷȽɀྦ਄ȳɥྼᅟȦȜɥăȷɈࠫപೀ࠰ɈဍȦঢ়ȞɂĂྦ᩼ൌ෸‫ݚ‬ၫ৐ȥɣ൥ȧɄߍ๱ɬᄵȳɥࠫപၫ৐ɈʟĜʗɈߠਗȦ਒ȩɄɥăʑʲĜʑˁɼʘĜɉ෸‫ݚ‬ၫ৐Ɉࠫപɬ਄ȠȹɛĂȷɈɢȠɄ൥ߍ๱Ɉ๘दɈߠਗȦ൥ȧȩɄɥɂไಜɄʏʷʽ˄Ĝʏʿˋ
ూ2/2/4/.2
Ȧ਄ȢɄȩɄɥᄎ൨ȦȜɥɈɁ෉‫ڷ‬ȦྼᅟɁȜɥăྦ᩼ൌྦ਄ࡨಙɈ෸‫ݚ‬ȥɣ࣏Ȟཱྀ‫ڱ‬Ɉߍ๱Ɂࠫപȯɦȹ๘दɈəɬᅙ
ȞɥȭɂɁȭɈᄎ൨ɬྤȫɥȭɂȦ‫ݢ‬༑ɁȜɥȦĂȷɈ௲ਗĂࠫപೀ࠰ɈဍɅɢȽɀɉଌ੫ɅɉୃࠁȦശ੭ȳɥɅɜȥȥɩɣȴĂ๘दɈശ੭ȱɄȞᆴ‫ۊ‬Ȧཡ౺ȱɀȱɘȠăȭɈ๘ɬ৽ᆞȱɀĂʑʲĜʑˁɼʘĜɈఒਖʏʷʽ˄ĜʏʿˋɅᅙȞɥ๘दʟĜʗɈଲຶɈ੫Ʌɉ࣡ᆵࠫപೀ࠰ɈࢯᆋɬழȯȩɂɥྼᅟȦȜɥă‫ڬ‬௫Ɉ๘ɬ৽ᆞȱɀĂୃࠁ௫ऋ31n ġ51nĪଚჶɈȹɛୃࠁɘɁɈࢯᆋɉ‫ێ‬ฤɁɉɄȞīɅȤȞɀĂ23ॢ24໲Ăࠫപೀ࠰ࢯᆋɬ࣡ᆵಞࣷȯȵȹĪࠫപೀ࠰ࢯᆋ3/6nīࠫപɬĂழळჟఱʰ˂ɬᅙȞɀ਄Ƚȹăࠫപඩɉ਒
ඪॻɈଆটგɁĂൎ௣Ɉఝᆹɉဲ੍ୃࠁɈ௎ᅝୃᆹɁȜɥă˄ĜʎĜʑʅʻʢɂວ૪຃੪ȱȹʟʐʗ˃ʃʹˁɅ
ɢȽɀଲຶȯɦȹ‫ކ‬ജȥɣ TgN ɅɢɥǏ૫ই๘दʟĜʗȤɢɍʂ˃ʕ‫ކ‬ജɜ౺౰ȱȹూ2/2/4/.3Ȥɢɍూ2/2/4/.4ă௫ऋȥɣɈଖణએ‫܆‬Ɂɉຎ೓ɄȦɣဲ੍ୃࠁɈࠫപൎ௣ᆹɅȤȞɀᆹஸɉ࿤‫ݢ‬૗ɁȜɤĂȷɈȹɛ TgN ɅɢɥǏ૫ই๘दɁɉᆹஸɉ೔ȩ๘दȦശ੭ȱɄȞă‫ێ‬ၫĂూ2/2/4/.5Ʌ૲ȳɢȠɅĂࣷಞˁɼʘĜʟĜʗɁɉĂᅝჶಓდ๱Ɉ൥ȧɄဲ੍ୃࠁ௎ᅝୃᆹɄȦɣɜᆹஸɅຖൿȱȹʩ˃ʑȦഽౘശ੭ȱĂȷɈȹɛණྉɬယᆋȳɦɊණྉɈණवȦცߊɅএɦɥȭɂȦယȥɥăȭȭɁĂණྉȤɢɍୃࠁငɈ๘दʟĜʗယᆋɉ઀༃๱ၡਠȱȹණྉෆ୸଴
ၭɬᅙȞɀ਄ȽɀȞɥă

ూ2/2/4/.3āTgN Ʌɢɥ๘दɈǏ૫ই࿍૲

ూ2/2/4/.4āTgN Ʌɢɥʂ˃ʕ‫ކ‬ജ

― 18 ―

ూ2/2/4/.5āࣷಞˁɼʘĜࠫപɁଲຶȱȹ๘दɂວ๘दȥɣယᆋȱȹණྉʟĜʗʑʲĜʑˁɼʘĜɈఒਖʏʷʽ˄ĜʏʿˋɁɉĂʭʛʠʯ˂ˋʠ໘Ɉණྉभଚɬཱ‫܇‬ȱȹஐᆅȦྼీɁȜɥă௫ࡥʟĜʗɬᅙȞɀୃࠁȥɣɈ˂ʗĜˋఒਖȤɢɍණྉȥɣɈ˂ʗĜˋఒਖɈ୭௼ȦभଚɅɢȽɀɃɈɢȠɅဿ‫ݛ‬ȳɥȥĂএଌɈఝᆹࠫപɬ਄ȽȹʟĜʗɅൎȱɀණྉɈəɈभଚɬဿ‫ݛ‬ȯȵɥȭɂɁȷɈ‫ࣗ܆‬ɬ࿎‫ݟ‬ȳɥȭɂȦ‫ݢ‬༑ɁȜɥă
ూ2/2/4/.6ɉూ2/2/4/.5Ɂ૲ȱȹʟĜʗɬᅙȞĂୃࠁ๘दɈ [ ඩȥɣණྉ਒ɬۜȞȹୃࠁ਒ʺʟ˃ĪEDNīɁȜɥăȭɈ EDN ȥɣˁĜʐʭʛʠʯ˂ˋʠɈʭʛʠʯ˂ˋʠᆴ‫ۊ‬ɬಜ୸ȱĂ‫ݜ‬೻โɅණྉभଚɬဿ‫ݛ‬ȯȵȹ௲ਗĂିఒఒਖȦɃɈɢȠɅဿ‫ݛ‬ȳɥȥɬʏʷʽ˄ĜʠȳɥȭɂȦɁȧɥăూ2/2/4/.6ɉȷɈय़‫ݪ‬ɁȜɥăȭɈూɁɉĂ୬૾Ȧഊൎ਒๱ɬ૲ȱĂ݁૾Ȧഊൎఒਖࣅ๱ɬ૲ȱɀȞɥăూෂɈ౉ိೀɉණྉ‫ڮ‬඲ɬ૲ȱɀȞɥăᅝჶಓდ๱Ɉ਒Ȟဲ੍ୃࠁɁȜɥȦɠȢɅණྉ‫ڮ‬඲ȥɣɈ˂ʗĜˋఒਖࣅ๱ɉழȯȞȦĂණྉभଚȦࠥɞȥɄɂȧɉୃࠁȥɣɈ˂ʗĜˋఒਖࣅ๱ɉ൥ழǎȾɈʬĜʇȥɣ౰ɥăȱȥȱĂණྉभଚȦ൥ȧȩɄɥɂĂණྉȥɣɈ˂ʗĜˋఒਖɂഊൎࣅ๱ɈழȯɄୃࠁȥɣɈʬĜʇȦ୭௼ȱĂ‫ॽێ‬ණྉȥɣɈ˂ʗĜˋఒਖɈʬĜʇɈɢȠɅॽȢɥɢȠɅɄɥăȭɈȭɂɉ࢖भଚȥȾᅝჶಓდ๱Ɉ਒ȞఝᆹɁɉĂɌɂȾɈ˂ʗĜˋఒਖɈəɬ‫ސ‬಑ȱɀɜୃ਒ైฤȦਲ໧ɁȜɥȭɂɬ૲ȱɀȞɥă਱ষɉˁĜʐʭʛʠʯ˂ˋʠɈਂऋ࡙ˁɼʘĜଌঅɁࠫപȯɦȹʟĜʗɬළଌɅ੔এɁȧɥɢȠɄʏʷʽ˄Ĝʏʿˋ଴ၭɬާཡȳɥᅅฤɁȜɥă

ూ2/2/4/.6āూ2/2/4/.5Ɂ૲ȱȹ๘दʟĜʗȥɣ੼౰ȱȹୃࠁ਒ʺʟ˃

ూ2/2/4/.7ā‫ڽ‬ɄɥभଚɈණྉჶȥɣɈ˂ʗĜˋఒਖʏʷʽ˄Ĝʏʿˋय़‫ݪ‬― 19 ―

ĪǏīTgN Ʌɢɥ๘दʟĜʗᆀᅙɈ‫ݢ‬༑౯೐ಣɁ୺ɓȹɢȠɅĂࣷಞˁɼʘĜɅɢȽɀࠫപȯɦȹୃࠁ৭ഢɬ࿍ȳǏ૫ই๘दʟĜʗɉĂˁĜʐʭʛʠʯ
˂ˋʠˁɼʘĜɈఒਖʏʷʽ˄ĜʏʿˋɅᆀᅙɁȧɥ‫ݢ‬༑౯Ȧ਒Ȟă‫ێ‬ၫɁĂฝʋʑʠɁഽౘɈʟĜʗେୠȦᅎ‫ڹ‬Ʉʡ˅Ĝˋऋએଖణȥɣ TgN ஐᆅɅɢȽɀ౺౰ȯɦȹ๘दʟĜʗȦᆀᅙɁȧɦɊĂ઀਱Ɉʡ˅ĜˋɈ࿱࢒Ɉ
௻࣍ȥɣĂ࣡ɛɀഽౘɈࠫപʟĜʗɬᆀᅙɁȧɥ‫ݢ‬༑౯ȦȜɥăȱȥȱɄȦɣĂȳɁɅ୺ɓȹɢȠɅĂဲ੍ୃࠁɈఝᆹɁɉĂୃࠁ࿍ჶɈव௻ɉଲຶɁȧɥɜɈɈĂୃࠁ໘ငȥɣᆹஸɅȥȫɀɈ௶ၡɉɕɂɭɃຶɥȭɂȦɁȧɄȞăࠫപൎ௣ɈఝᆹɈᆏᄄდ๱ȦฝȩĂȥȾୃ਒ȦฝȞɢȠɄఝᆹɁɉණྉჶȦଖణɅଖɥߊᆎȦ਒ȩɄɤĂ౺౰๘दȥɣණྉɬယᆋɁȧɥɢȠɄ௲ਗɜശ੭ȳɥȦĪూ2/2/4/.8ઞ௎īĂ‫ཾێ‬โɅɉɕɂɭɃࡖ൒ɁȧɄȞăȹɂȢɊĂూ2/2/4/.9Ʌ૲ȳʃˁʶʜᆹɉާၪୃࠁɁȜɤĂᆹஸɈଖణȥɣɩȥɥɢȠɅᆏᄄდ๱ɉȷɦɕɃ਒
ȩɄȞăȷɦɁɜ TgN ʟĜʗȥɣ౺౰ȱȹ๘दȥɣණྉɬෆ୸ȱɢȠɂȱɀɜ౰োȱɄȞăȭɈɢȠɄĂᅝჶಓდ๱ȦȯɕɃ൥ȧȩɄȞఝᆹɅȤȞɀɉණ௫˄ĜʎĜɅɢɥ๘दɬᅙȞɥɕȠȦᄵᆀɂ৽ȢɣɦɥăȱȥȱɄȦɣĂණ௫˄ĜʎĜɁɉࢍɅୃ෴࿥ࣷɈʟĜʗȦଲຶɁȞɄȞ௲ਗȦȜɤĂୃ਒ोപɈȹɛɈʟĜʗଲຶၫၭɂ
ȱɀɉ౫ঔɈȜɥ௲ਗɜഽȞă

ూ2/2/4/.8āᆏᄄდ๱ɈฝȞଭ༃ɈʪʦʅᆹɁ TgN Ʌɢɥ๘दȥɣණྉယᆋɬ਄Ƚȹᇉ

ూ2/2/4/.9āᆏᄄდ๱ȦฝȞɅɜȥȥɩɣȴĂණྉෆ୸Ʌ଄༨ȱȹᇉȷȭɁĂ௫ऋȥɣɈ TgN Ʌɢɥ๘दɂĂණ௫˄ĜʎĜɅɢɥᆹஸȥɣɈ๘दɬᅃਗȳɥȭɂɁࣷಞˁɼʘĜʟĜʗɅɢɥ๘दɅྴเȳɥɢȠɄ๘दʟĜʗɬ੼౰ȳɥၫၭɜ৽ȢɣɦɥăȹȺȱĂএ૪๘ɅȤȫɥණ௫˄ĜʎĜɅɢɥʟĜʗଲຶɉʋʑʠɞ˄ĜʎĜʑʅʻʢ૵ൌɈ‫ུݢ‬౯ɞࠫപཱྀ‫ڱ‬Ɉ๘ɁĂ൥ჶಓɬʃʨĜȳɥࠫപɅɉ൥ȧɄ౫ঔȦȜɥăණ௫Ɂએ‫܆‬ȱȹଖణȥɣɈ TgN ɅɢȽɀᆹஸȥɣɈǏ૫ই๘दȦ౺౰ɁȧɦɊණ௫˄ĜʎĜɬᅙȞȴɂɜ௫ऋɂᆹஸȥɣɈोപʟĜʗɈᅃਗȦฝʋʑʠɁଌএɁȧɥ‫ݢ‬༑౯ȦȜɥĪూూ2/2/4/.:ઞ௎īăȱȥȱĂȷɈၫၭ
ሄɉఝᆹ໘ɈोപɅ࠲ȱɀɉߊᆏȱɀȤɣȴĂ਱ষॳບȳɓȧ‫ݻ‬൨ɁȜɥă

― 20 ―

ూ2/2/4/.:āණ௫એ‫܆‬ଖణɬᅙȞȹ TgN ɅɢɥʃˁʶʜᆹɈ๘दʟĜʗ― 21 ―

2/3/āʯ˅ʈˁʸǎćණ࢝࿍೸௶ၡຕਗʯ˅ʈˁʸĮ‫ޱ‬ᅟį
ණ࢝࿍೸௶ၡຕਗʯ˅ʈˁʸɉʟĜʗɈ੼౰ĂຕਗĂ৊ާɬࡊ૾ɂȱɀĂ଱Ʌ൥࡜५Ćᆌ‫ۊ‬Ɉࠞࣃॸ࢞ɬైమ
ȳɥăଲɤ‫ڙ‬ȠʟĜʗɉ‫ܒ‬౳ࠫപʟĜʗĂණ௫ࠫപʟĜʗĂॸ࢞౰‫ݪ‬ɂȱɀɈࠞࣃʟĜʗɁȜɥăႨʯ˅ʈˁʸɅ࠸ɘɦɥ଱ᅟɄॸ࢞ʞĜʶɉĂ‫ܒ‬౳ʟĜʗɈၒ౷Ć೐ஐᆅĂ႐൥Ʉ‫ܒ‬౳ʟĜʗɈৌᆎɈᆯȞஐᆅ଴ၭɈߊᆏĂ‫ܒ‬౳ʟĜʗɂණ௫ɈʟĜʗຕਗɅɢɥࠞࣃʺʣʗ˂ˋʈ଴ၭɈާཡĂȤɢɍ‫ܒ‬౳ʟĜʗȥɣɈ൥࡜Ćᆌ‫ࣃࠞۊ‬௶ၡɈෆ୸ɁȜɥăɄȤĂႨʯ˅ʈˁʸɉ DFSfT ɂȱɀɈ߂ହʟĜʗ৊ާĪWMĈोધ࡙ʟĜʗʱĜʑ‫ࣞޏۙڳ‬ოīĂࢼᄵʏʑʞʸɈ‫ۿ‬ᅙĪDFSfT!HbjbīɅდಞɅ࠲बȳɥăණ࢝࿍೸௶ၡຕਗʯ˅ʈˁʸɈ൦Ǐࡖෂࡖᄆ࿈Ćෂࡖो‫࠰ࡖކ‬Īိ౰39.44༃๱īɅȤȫɥॸ࢞‫ݻ‬൨Ȥɢɍൿ౰ᄆ࿈ɉ‫ݚڬ‬ɈฆɤɁȜɥă൦ǎࡖɅȤȞɀଌૈȱȹॸ࢞ʞĜʶɈູଋɅࡊȿȩʯ˅ʈˁʸॸ࢞ɬཡ๐ȯȵĂȯɣɅ୭๘‫ݻ‬൨ɬಡฤȱȹăĮෂࡖो‫࠰ࡖކ‬Ɉॸ࢞‫ݻ‬൨Ȥɢɍൿ౰ᄆ࿈įśॸ࢞‫ݻ‬൨Ć! ණ௫˂ʺĜʠʓˋʏˋʈɬߤᅙȱȹණ࢝൥࡜ࠞࣃɈࡊྉॸ࢞ɂȱɀĂDFSfT ଱ຩɈਡ੫ණ௫ࠫപʥʛʠˇĜʇĪTLZOFUīɂ OBTB ଱ຩɈʥʛʠˇĜʇĪBFSPOFUīɈ଱ᆵ࡙੮Ɉ෮ሆࠫപɬާ઻ȱĂȷɈʟĜʗɈ࿚ଋɅ࠲ȳɥఛȱȞඪॽɬຶɥăĆ! ˂ʺĜʠʓˋʏˋʈɬߤᅙȱȹණ࢝൥࡜ࠞࣃɈܾᅙॸ࢞ɂȱɀĂBvsb0PNJ ຑɈ‫ܒ‬౳ࠫപɞ TLZOFU ຑɈණ௫ࠫപɬߤᅙȱɀɺʐɺ‫ۊ‬Ɉ߂ହ൥࡜౰ယĪྫᆲʄʑĂʀɺ˅ʖ˃ɄɃīɈ૪ऋ࠰ယ࿫ɬఛȹɅცɣȥɅȳɥăĆ! ‫ݗ‬ଆৌ‫ݪ‬ʄʑࠫപࡳ୹‫ܒ‬౳ǎਖĪ3128༃๱൅Ȼ௫ȬᅅฤīɈ‫ݗ‬ଆৌ‫ݪ‬ʄʑࠫപʓˋʍĪUBOTP.GUT3īɈ༂ಘެʑʲʇʠ˃ȥɣ୦ᅰȥɣɈ໩બ‫ݛ‬ඖ೧ĂʹʗˋɅ‫ݡ‬ȢɀఛȹɅ࡜‫ݗ‬Ă౉௾࡜Ɉ਒๱ʯ˅ʭɹɼ˃ɬຩ
୸ȳɥɺ˃ʌ˂ʒʸɬާཡȱĂ‫ܒ‬౳ȤɢɍʓˋʍɈާཡইɁȜɥਡᆏࠞࣃॸ࢞ஒɂۧහਂऋॸ࢞ާཡ࡙৭Ʌ
ʟĜʗஐᆅʯ˅ʈˁʸɬอࢷȳɥăĆ! ໲ႨɈ‫ݗ‬ଆৌ‫ݪ‬ʄʑࠫപࡳ୹‫ܒ‬౳ HPTBU ʏ˂ĜʒĪHPTBUĂHPTBU3īɈ໩બ‫ݛ‬ඖ೧ȤɢɍʹʗˋɈ೔
࢝਒๱ʯ˅ʭɹɼ˃Ɉෳࡖ࠰ʟĜʗɈʟĜʗଋɬॳ௠ȱĂ‫ܒ‬౳ࠫപɅɢɥ೔࢝‫ݗ‬ଆৌ‫ݪ‬ʄʑ༏๱Ɉෳࡖभ৐
ɬცɣȥɅȳɥă
Ć! USNN ‫ۿ‬ᅙࡖ࠰Ī2::9.3125īɈ೔࢝ಇો࡜௣‫ܒ‬౳ਏ౉ʵʞˋʏʻ˃ʶʛʯɬާཡĆ੼౰ȱĂ৊ާȳɥă
Ć! NUTBUĪ3116.3126īࡖ࠰ɁɈຄĆຄ໤ɺʐɺ‫ۊ‬ɁɈ‫ܒ‬౳໲ଗĆਏ౉ᆲʯ˅ʘʇʠɬߤᅙȱȹᆌ‫౉ۊ‬ஃࠞ‫ސࢦݿ‬಑ɬଌૈȱĂ౉ஃࠞ‫ݿ‬าɬცɣȥɅȱĂ‫ސ‬಑य़‫ݪ‬ɬ৊ާȳɥăĆ! ࡜েఫඣɅ࠲ɩɥǐʓˋʗĜĪຄࢶ൥ߔ൥࡜‫ޠ‬ᅖॸĂშগ‫ݎ‬൥ߔۧහණ࢝ࠞࣃॸ࢞ஒĂຄ႘൥ߔ൥࡜‫ޠ‬ᅖဿ຦ࠫപॸ࢞ʓˋʗĜĂDFSfTīɈᇦ़ɅɢɤʨĜʙʻ˃ˁʴˁʠ˂Ĝɬव౰ȱĂ߂ʓˋʗĜɈູఋɂॸ࢞૝
દɬߤȥȱȹॸ࢞ɂ࣋‫ۋ‬ɬယඐĆᇦ़ȱɀଌૈȳɥăĆ! ණᆅऋ࠰ʟĜʗɈࢼᄵʏʑʞʸĪDFSfT! Hbjbīɬਡ੫โɅ๐ާĆ‫ۿ‬ᅙȱĂ௶ၡຕਗɅɢɥණ࢝ࠞࣃॸ࢞ɬ
ైమȳɥă
Ć! HDPN ʏ˂ĜʒɁɈॳ௠ʟĜʗʏɿɺ˂ˋʈɬ਄ȠĪʯ˅ʈˁʸǍɂɈᇦ़īăś୭๘‫ݻ‬൨ćɌɘɩɤǔğǕਖʟĜʗɬߤᅙȱȹ˂ʺĜʠʓˋʏˋʈ଴ၭɈާཡ
āāāāāāĪOpwfm!sfnpuf!tfotjoh!cbtfe!po!Ijnbxbsj.90:!nfufpspmphjdbm!tbufmmjuf!ebubīĆ! ɌɘɩɤǔਖൎܾɈʶ˃ʙʙʻˋʥ˃ɬᅙȞȹ਒౼๱ਏ౉ʵʞˋʏʻ˃ʶʛʯɬާཡĆ੼౰ȳɥăĆ! ʇˁɾʡࡳ୹ɬߤᅙȱĂɌɘɩɤǔğǕਖʟĜʗɂණ௫ࠫപᄀʟĜʗĪਏ౉ᆲĂ൥࡜ܸಹʺʣʗ˂ˋʈຑīɬஈ˂ɺ˃ʗɼʸɁ਒ബ‫ݢ‬૗‫ݛ‬ȳɥࡳ୹ɬާཡȱĂ˂ʺĜʠʓˋʏˋʈ଴ၭɅɢɥࠞࣃॸ࢞Ʌߤᅙȳɥă
Program 2: Integrated use of geoinformation
This program aims to promote atmospheric/terrestrial environmental studies based on integrated use
of geoinformation including satellite remote sensing data, ground measurement data, and extracted
environmental data. Main research subjects in this program are correction and preprocessing of satellite            
by integrating satellite data and ground data, and extraction of atmospheric/terrestrial environmental
parameters. This program has close relationship with the operation of the data distribution and sharing
systems of the whole CEReS.

― 22 ―

Įॸ࢞໘ᅎɂိ౰39༃๱Ɉ౰‫ݪ‬į

ş2/3/2/ā!!ಇો࡜௣‫ܒ‬౳दɅɢɥਏ౉࠲ᇦᅟ೧ෆ୸Ă࢒ɍȷɈᆀᅙ! !
Īྦྷ৏ຼૂĂঢ়౧მૂĮই WM ູ໸஝࣋Ăএࢶ൥ᆅ൥ߔۡ౺įīࣷ༃Ă‫ܒ‬౳ਏ౉ʯ˅ʘʇʠɉɢɤ˂ɺ˃ʗɼʸɅࣷȞʟĜʗ୅ᅟȦ਒ɘɤĂKBYB ‫ܒ‬౳ʯ˅ʘʇʠ HTNbQ ɉɌɘɩɤǔਖɢɤोધȯɦȹ‫܀‬Ɉ‫ھ‬຦ʱʇʠ˃Ʌ41ယެ೾ɬ਄ȠȭɂɁĂബၡ౯ɬࣅ‫ݛ‬ȱȹ HTNbQ`OPX ɬ༯ఒȱɀȞɥă
Ⴈʈ˃Ĝʯɉ3126༃๱ɢɤɌɘɩɤǔਖʟĜʗɬᅙȞȹਏ౉࠲ᇦᅟ೧ෆ୸ާཡɬʑʗĜʠȱɀȞɥĪ଴ၭĪˁˋʘʸʭʁ˄ʑʠၭ <! SGīɅȾȞɀɉ3126༃๱༃ၡ2/3/6/3/ ɬઞ௎ī
ă3127༃๱ɉ HQN Ɂߔ୔ȯȵĂोધȱȹਏ౉࠲ᇦ௶ၡɈॳ௠ɬ਄Ƚȹăॳ௠ʟĜʗɉ࡜௣ෝ˄ĜʘĜɺʹʘʑɁȜɤĂູɅ‫ڃ‬༂൑ɁɈ੔এ౯Ɉॳ௠
ɈȹɛĂ‫݋‬໢˄Ĝʘ‫ۊ‬ɬယᆋȱɀ်๫ॳ௠ɬ਄Ƚȹă
ూ2/3/2/.2ɅɌɘɩɤǔਖɁɈ SG ɅɢɥైฤĂ˄ĜʘĜɺʹʘʑࠫപඩĂȤɢɍ HTNbQ Ɉʑʢʛʯʏʿʛ
ʠɬȷɦȸɦ૲ȳăႨૢᇉɉ൤ဇಞࣷ૪ɈɜɈɁȜɤĂ‫݋‬໢Ⴈ๿႘င‫ޠ‬ᅖ‫ۊ‬ɁɈ੧ȥɄʓ˃௻Ɉਏ౉‫ۊ‬ȦɌɘɩɤǔਖైฤĂ˄ĜʘĜɺʹʘʑࠫപɁɉ໻ɛɣɦɥȦĂHTNbQ Ɂɉც૲โɅɉైฤȯɦɀȞɄȞăHTNbQɁɉ‫ސ‬ജ୸ᅰɀȞɄȞȹɛɁȜɤĂȭȠȱȹʓ˃௻Ɉਏ౉࠲ᇦ௶ၡɈෆ୸ɅɉĂ਒ऋ࠰Ć਒૪࠰ယ‫ސ‬༑ɁȜɥɌɘɩɤǔਖɈູ౯ȦߤȧɀȞɥăూ2/3/2/.3Ʌਏ۫‫ۊ‬Ʌ࠲ȳɥɌɘɩɤǔਖļSGĂHTNbQ Ɉ uisfbe! tdpsf
ĪUTīɬ૲ȳăࡠಣ౯ɬ৽ᆞȳɥȹɛĂǐॢġǕॢĪ୽ġ‫ݤ‬ĈBTīĂ21ॢġǏॢĪ୑ġ๷ĈPNīɅယȫĂȯɣɅ SG ၭɁᆀᅙɁȧɥʨˋʡౘɈ‫ۅ‬ȞɅɢɤĂ໲ෂĪEbz<! EīĂᅄၫĪUxjmjhiu<! UīĂȤɢɍᄕ࠰ĪOjhiu<! OīɅယȫĂHTNbQ ɉʶɼʇ˅༜ၪଗोࠫപɈᄵჟĪopNXSīɁယȫɀȞɥăʶɼʇ˅༜ၪଗोࠫപɈჟȞ૪࠰൑ĪopNXSīɈ UT ɢɤฝȫɦɊĂႨʑʅĜʸຩ໴ɉ૫ࡖ HTNbQ ɅɼˋʩʇʠɬᅇȢɄȞȭɂɬ૲ȳăড়Ȟూ
2/3/2/.3ɢɤĂএඦިɁɈɌɘɩɤǔਖైฤඩɬ൦‫ైێ‬ฤඩɂȱɀᆀᅙȱȹ੫ɅĂவɄȩɂɜਏ౉‫ۊ‬Ʌ࠲ȱɀɉ౼๱Ȧ‫ݛڏ‬ȳɥȭɂɉჟȞȭɂȦယȥɥăȹȺȱĂʶɼʇ˅༜ၪଗोɅɢɥ UTĪNXS! ୽‫ݤ‬Ɂ1/56า๱Ă୑๷
Ɂ1/5า๱īɢɤɉĂɃɈ૪࠰൑ɁɜฝȞभ৐ɅȜɥĪ1/4ġ1/5ĂȹȺȱɃɈ૪࠰൑Ɂɜ୑๷ɢɤ୽‫ݤ‬ɈၫȦ UTɉ਒Ȟīăਏ౉ࣅ๱Ʌ࠲ȱɀɈॳບĪూ2/3/2/.4īɉ೔ൌโɅਏ۫‫ۊ‬ɁɈॳບɢɤ‫ڏ‬ȩɄɥभ৐ɅȜɥăࣅ۫‫ۊ‬Ɉߔ୔Ɂ෇ᄕᄎɩȴʍˋʯ˃ɬഝɞȳஐᆅɅဿ৩ɬȱɀȞɥȦĂࡊႨโɅɉࣅ۫‫ۊ‬ɈႨ଴ၭɁɈైฤਏ౉ࣅ๱Ɉ
‫ݿ‬ழ࿎‫ݟ‬Ȧ‫ࣗ܆‬ɬᅇȢɀȞɥăູɅ୽‫ݤ‬ĆᅄၫĪBT! UīɈ SNTF Ȧ‫ڏ‬ȞăএඦިɁɈైฤɁɉਏ౉ʏʑʞʸɈ૪࠰ཡ๐Īএ਄ HTNbQ Ɉ NWL ഊຎīɬ‫ێ‬ಜ৽ᆞȱɀȞɄȞȭɂɬ࠯əɥɂĂ‫ݿ‬๱ɅྒྷࠫȳɥྼᅟɉჟȞɂ৽Ȣɥă‫ݜ‬೻‫ࡠݤ‬༂൑‫ۊ‬Ī‫݋‬໢˄ĜʘīɁɈ SNTF ෂܻඩɉǍnn0is ɁȜɤĂਏ౉‫ۊ‬ɁɈ਒࿎‫ݟ‬ɂ౲ਗโɁȜɥăႨॸ࢞ɉ KBYB ൦ǔ‫ ޑ‬QNN!SB Ɉૅ‫ܧ‬ɬຶɀ਄Ƚȹă

ూ2/3/2/.2ā!!ʑʢʛʯʏʿʛʠɈᇉă੆௫ćɌɘɩɤǔਖļHQN ߔ୔Ʌɢɥ SG ၭైฤඩĂ‫ۦ‬௫ć˄ĜʘĜɺʹʘʑɅɢɥोപඩĂ੆‫ݚ‬ćHTNbQ! NWL ైฤඩɬȷɦȸɦ૲ȳăႨʉĜʑɉ൤ဇಞࣷ૪Ɉ
ɜɈɁĂୈ‫ܯ‬ငɅʓ˃௻Ɉਏ౉‫ۊ‬Ȧ˄ĜʘĜɺʹʘʑĂɌɘɩɤǔਖļǮǢၭɁɉߊ໻Ɂȧɥă

― 23 ―

Tread score

Himawri-8

GSMaP

0.6
0.5
0.4
0.3
0.2
0.1
0
AS D

OS_D

AS N

OS N

AS T

OS T

JJA tropic AS MWR OS MWR

AS
OS
noMWR noMWR

ూ2/3/2/.3ā!!˄ĜʘĜɺʹʘʑɅɢɥɌɘɩɤǔਖļHQN0EQS ߔ୔Ʌɢɥ SG ၭɅɢɥĂਏ౉‫ۊ‬Ʌ࠲ȳɥॳ௠य़‫ݪ‬Īuisfbe!
tdpsfīăࡠಣɅɢɥ‫ۅ‬Ȟɬ৽ᆞȳɥȹɛĂǐॢġǕॢĪ୽ġ‫ݤ‬ĈBTīĂ21ॢġǏॢĪ୑ġ๷ĈPNīɅယȫĂȯɣɅ SG ၭɁᆀᅙɁȧɥʨˋʡౘɈ‫ۅ‬ȞɅɢɤĂ໲ෂĪEbz<! EīĂᅄၫĪUxjmjhiu<! UīĂȤɢɍᄕ࠰ĪOjhiu<! UīɅယȫɀॳ௠ɬ਄ȽɀȞɥă‫ݡ‬ȢɀĂ‫ڃ‬༂൑‫ۊ‬Īࡷૣ༂൑‫ۊ‬īɁɈైฤ౼๱ॳ௠ɈȹɛĂ‫݋ࡠݤ‬໢˄Ĝʘ‫ۊ‬ɈəɁɈॳ௠ĪKKB! uspqjdīɜଌૈȱɀȞɥă྘ߏൎ௣ɂɄɥ HTNbQ ɉʶɼʇ˅༜ၪଗोɈࠫപɈᄵჟĪopNXSīɂࡠಣĪ೐୺īɁယᆋȱɀȞɥă߂ʴʛʇʑ໘ɈಘೀȦෂܻඩɁȜɤĂʴʛʇʑɈ૲ȳཱྀ‫ڱ‬ɉ36.86ʩĜʓˋʗɼ˃ඩɁȜɥă

ూ2/3/2/.4āూ2/3/2/.3ɂວȲĂȹȺȱਏ౉ࣅ๱ɅȾȞɀɈ੕ழ໩௮িੇĪSNTFīɁȜɤĂ୬૾Ɉඍ‫ڮ‬ɉ nn0is ɁȜɥă

ş2/3/3/ā੕ಪ඘˂ʺĜʠʓˋʏˋʈɅɢɥ൥࡜ࠞࣃဿ຦ॸ࢞Ī໴৮ॸ࢞ଆīൣ࿍โɄ൥࡜ܸಹဘଋɈɌɂȾɁȜɥ໩બ‫ݛ‬ᆘ݉ĪTP3īɉĂબ౯۫ɞʀɺ˅ʖ˃Ɉ೐ऄ࡜ൌɂȱɀɈᄜߠɬ
ฆȲɀĂఱൌɞ౺ൔृĂ࡜௣ɄɃɅ‫ࣗ܆‬ɬ࢒ɖȳȹɛĂȷɈ༏๱ဿ຦Ɉᅟۚɬ‫ސ‬ცȳɥȭɂɉ୭ᅟɁȜɥăȭɦɘɁ TP3Ɉࠫപɉ଱Ʌණ࿍༏๱Ʌ்๘ȦຎɀɣɦଌૈȯɦɀȧȹȦĂȭɦɬʀɺ˅ʖ˃Ɉᅅപʺʟ˃ɒɈʟĜʗວ‫ݛ‬ຑɈܾᅙॸ࢞Ʌᆀᅙȳɥ௫Ɂɉऋ࠰ൣ࿍౯Ʌᆗ‫ڷ‬ȳɥྼᅟȦȜɥăȷɈɢȠɄ༬ाɈ‫ݚ‬ĂႨॸ࢞ɁɉĂɺʐɺ൥ᆌȥɣɈෳࢯᆋᄪഗɞ‫ݮ‬ટʄʑɄɃᅕęɄ‫ࣗ܆‬ɬିȫɥȭɂȦ৽ȢɣɦɥࣻୋණၫĪဏ݊ॻ୽໲ીīɅȤȞɀഽ૾ੇယ࢓େယ৉ၭĪNvmuj.Byjt! Ejggfsfoujbm! Pqujdbm! Bctpsqujpo! Tqfdusptdpqz;! NBY.EPBTīɂঘɊɦɥ
ණ௫˂ʺĜʠʓˋʏˋʈ଴ၭɅɢɥᇦറࠫപɬ਄Ƚȹă༜ෳ‫ۊ‬421.431on Ɉപฤʑʲʇʠ˃ɬ EPBT ၭɁ‫ސ‬಑ȱĂ਒๱ǌ.Ǎln ೸໘Ɉ TP3ိࣧ༏๱ɬ౉ိʑʉĜ˃21ln า๱Ɂຩ୸ȱȹăɉȲɛɅĂ3125༃Ǔ. ǔॢɅȤȞɀ໲੕൥ඩȦǑqqcw ɬ෰Ȣɥ໲ɬ਒༏๱໲ɈࡊஈɅȱȹɂȭɧĂǓ໲࠰ɬູฤȳɥȭɂȦɁȧȹăȭɦɣɈ໲ɬൎ௣Ʌʨʛʇʠˁʐɿʇʠ˂Ĝ‫ސ‬಑ɬ਄ȽȹɂȭɧĂ‫ݮ‬ટࡧ঍ɂ൥ᆌࡧ঍ɈǎȾɈʉĜʑɅယᇆȳɥȭɂȦɁȧĂ‫ݮ‬ટࡧ঍ɅȾȞɀɉ‫چ‬೩ટȤɢɍઇ๿Ă൥ᆌࡧ঍ɅȾȞɀɉෂਡɞ࠴ਡȥɣɈෳࢯᆋᄪഗɈ‫ࣗ܆‬Ȧ૲੄ȯɦȹăȭɈय़‫ݪ‬ɬຝɘȢĂ‫ސ‬಑ൎ௣ࡖ࠰ɬ3125༃Ǎॢġ3127༃ǕॢɅ‫ܤ‬ɊȱɀĂ‫ݮ‬ટࡧ঍Ȥɢɍ൥ᆌࡧ঍Ɉ

― 24 ―

‫ࣗ܆‬ɅȾȞɀฤᆲโɄ‫ސ‬಑ɬ਄ȽȹăȭɈࡖ࠰Ɉ໲੕൥ඩɈိࣧඩɉ4/4qqcwĂ໲੕൥ඩɈෂܻඩɉ3/2qqcw ɁȜȽȹăɘȴɉ‫ݮ‬ટࡧ঍Ɉ‫ࣗ܆‬ɅȾȞɀĂऋ࡜‫ޒ‬Ȧ‫ݮ‬ટɬฆ‫ݿ‬ȱȹɂ཯ඣȳɥཱྀ‫ڱ‬Ɉ൥ȧȯɬဿȢȹ௲ਗɁ໲੕
൥ඩɈိࣧඩɈ྘ߏɬ਄ȽȹɂȭɧĂ‫ݮ‬৏ෂఘࣷȩɬฆ‫ݿ‬ȱɀȧȹɕȠȦ਒༏๱ɬ૲ȳɂȞȠभ৐Ȧॽɣɦȹă‫چ‬೩ટɈ‫ࣗ܆‬ɬିȫȹ௲ਗɈ໲੕൥ඩɈိࣧඩɉᄝǒqqcwĂઇ๿ɉᄝǐqqcw ɁȜɤĂ‫چ‬೩ટɈ‫ࣗ܆‬Ɉ൥ȧȯȦ૲੄ȯɦȹă૫Ʌ൥ᆌࡧ঍Ɉ‫ࣗ܆‬ɅȾȞɀĂ໲੕൥ඩɈိࣧඩɂĂෂਡĆ࠴ਡ௫ऋɁɈऋ࡜‫ޒ‬Ɉ൘ᆗ૪࠰ȤɢɍෂਡĆ࠴ਡȥɣᄪഗȯɦɀȩɥɘɁɈ૪࠰ɈෳȯɂɈ࠲बɅȾȞɀȷɦȸɦ྘ߏɬ਄ȽȹȦĂഊ࠲ɉॽɣɦɄ
ȥȽȹăɘȹĂ൥ᆌȥɣɈऋ࡜‫ޒ‬Ȧຖൿȱȹ໲ɅȤȫɥ໲੕൥ඩɈိࣧඩɉᄝ3/5qqcw ɁȜȽȹă๬ીငୈ၃ȥɣɈऋ࡜‫ޒ‬Ȧຖൿȱȹ௲ਗɬॽɀɜວᅕɈय़‫ݪ‬ɁȜȽȹăȭɦɣɈय़‫ݪ‬ɢɤĂࣻୋɅȤȞɀ൥ᆌɈ‫ࣗ܆‬ɉ‫ݮ‬ટɈ‫ࣗ܆‬ɢɤɜȦழȯȞȭɂȦ૲੄ȯɦȹă

ş2/3/4/ā!ਂ
! ऋ࡙ʟĜʗɅɢɥ HPTBU Ɉ໩બ‫ݛ‬ඖ೧ʯ˅ʭɹɼ˃Ȥɢɍʹʗˋʯ˅ʭɹ
ɼ˃Ɉॳ௠‫ސ‬಑Īᥓນஶાī‫ݗ‬ଆৌ‫ݪ‬ʄʑࠫപࡳ୹‫ܒ‬౳ HPTBUĪHsffoipvtf! Hbtft! Pctfswjoh! TbufmmjufīɉĂ311:༃ǍॢɈ൅Ȼ௫Ȭȥɣᄝǔ༃ɬॄ‫ݿ‬ȱȹএ੭ɜஏ෮ɅࠫപɬറȫɀȤɤĂ໩બ‫ݛ‬ඖ೧ĂʹʗˋɄɃɈ‫ݗ‬ଆৌ‫ݪ‬ʄʑɈෳࡖ࠰೔࢝
ʟĜʗɬอࢷȱɀȞɥăHPTBU Ʌ຃੪ȯɦɀȞɥ UBOTPĪUifsnbm! Boe! Ofbs.jogsbsfe! Tfotps! gps! dbscpo!
Pctfswbujpoī.GUT Ɉ༂ಘެ༜ෳᆴ‫ۊ‬ĪUJS ʨˋʡīȥɣɉĂ໩બ‫ݛ‬ඖ೧࢒ɍʹʗˋɈܴ෸༏๱ယ࿫Īʯ˅ʭɹɼ˃īɬຩ୸ȳɥȭɂȦɁȧɥăᥓນȦෂఘɂɄȽɀĂຄࢶ൥ߔ൥࡜‫ޠ‬ᅖॸ࢞ஒĂۧහਂऋॸ࢞ާཡ࡙৭Ăਡᆏࠞࣃॸ࢞ஒɂࢼວɁާཡȱȹ
UJS ʨˋʡɈ˂ʠ˂Ĝʨ˃ɺ˃ʌ˂ʒʸɁஐᆅȱȹ໩બ‫ݛ‬ඖ೧ȤɢɍʹʗˋɈʯ˅ʘʇʠĪW12/YYīɉȳɁɅ౦‫ޢ‬ෂɈॸ࢞ଞɅ༯ఒȯɦɀȤɤĂఒᅲ౯Ɉ਒Ȟਂऋ࡙ࠫപʟĜʗɄɃɈ෸ಞࠫപʟĜʗɂɈ྘ߏɬฆȱɀĂʟĜʗଋɈॳ௠‫ސ‬಑ɬమɛɀȞɥɂȭɧɁȜɥă઀༃๱ɉĂ௫ငൎᆔ५࢒ɍ‫ݚ‬ငൎᆔ५ɅȤȫɥ໩બ‫ݛ‬ඖ೧ʯ˅ʘʇʠɈʟĜʗଋɬॳ௠ȳɥȹɛɅĂ3121༃Ɉ‫ێ‬༃ယɈ DPOUSBJMĪDpnqsjifotjwf! Pctfswbujpo! Ofuxpsl!
gps!Usbdf!hbtft!cz!BjsmjofsīĮNbdijeb!fu!bm/-!3119įɈ౉ိྦ਄૪Ɉਂऋ࡙ࠫപʟĜʗɂĂਂऋ࡙ࠫപ਒๱Ɉ
௫‫ݚ‬Ǎln ‫ڬ‬໘Ɉ௸ॣɁෆ୸ȱȹ UJS ʨˋʡɈ໩બ‫ݛ‬ඖ೧ʟĜʗɈ྘ߏɬ਄Ƚȹă྘ߏɈय़‫ݪ‬Ă႘཰࢝Ɂɉ‫ޱ‬ɇ
1/6œ‫ڬ‬໘Ă໤཰࢝Ɂɉ1/2œɁ UJS ʨˋʡɈ໩બ‫ݛ‬ඖ೧ʟĜʗɂਂऋ࡙ࠫപʟĜʗȦ‫ێ‬ඳȳɥȭɂȦɩȥȽȹăȱȥȱɄȦɣĂ႘཰࢝Ɉ୽ࡠ࢒ɍ‫ࡠݤ‬Ɂɉ UJS ʨˋʡɈ໩બ‫ݛ‬ඖ೧ʟĜʗɅ੕൥3/5qqn Ɉ࿹ʨɼɺʑȦശ੭ȱɀȞɥȭɂȦɩȥȽȹĮTbjupi!fu!bm/-!BNU-!3127į
ă਱༃๱ɉĂDPOUSBJM!Dpoujovpvt!DP3!Nfbtvsjoh!FrvjqnfouĪDNFīʟĜʗɂɈ྘ߏɬ3121༃ȥɣ3123
༃ɈǏ༃ယɅ߄ෟȱĂಪɅ࿎‫ݟ‬ȱȹࡠಣĆ‫ۀ‬๱൑‫گ‬ശɈʨɼɺʑȦ UJS ʨˋʡɈ໩બ‫ݛ‬ඖ೧ʟĜʗɈ࿱၅โɄູ
෡ɁȜɥȥɬ෮ੈȱȹăూ2/3/4/.2ɅĂ௫ငൎᆔ५ɁɈ UJS ʨˋʡɈ໩બ‫ݛ‬ඖ೧ʟĜʗ࢒ɍಪঅඩʟĜʗɂ DNF
ʟĜʗɂɈ྘ߏय़‫ݪ‬ɬࡠಣ်Ă‫ۀ‬๱൑်Ʌ૲ȳă

ూ2/3/4/.2ā!!௫ငൎᆔ५ɁɈࡠಣ်Ă‫ۀ‬๱൑်ʨɼɺʑĪਥćUJS.DNFĂ!
‫ޡ‬ćɺʯ˂ʂ˂ .DNFīă3121Ă3122Ă3123༃ɬȷɦȸ
ɦଌೀĂ༟ೀĂ๘ೀɁ࿍ɩȳă― 25 ―

ూȥɣĂUJS ʨˋʡɈ໩બ‫ݛ‬ඖ೧ʟĜʗɈ DNF ʟĜʗɅൎȳɥ࿹ʨɼɺʑȦĂ3122༃Ă3123༃ɂ༃ɬॄɀ
߄൥ȳɥभ৐ɅȜɥȭɂȦɩȥɥăȷȭɁĂUJS ʟĜʗĂಪঅඩʟĜʗĂDNF ʟĜʗɈȷɦȸɦɈ༏๱ഝ‫ݡ‬ᆎɂࡠಣဿ຦Ɉచဍɬोધȱȹăూ2/3/4/.3Ʌ૲ȳฆɤĂUJS ʟĜʗɈ3121༃ȥɣ3123༃Ɉ໩બ‫ݛ‬ඖ೧༏๱ഝ‫ݡ‬ᆎȦಪঅඩʟĜʗɅ৤ഩȯɦɀ‫ݿ‬ழ࿎‫ݟ‬ɁȜɥȹɛɅĂDNF ʟĜʗɂɈ༏๱ੇȦ༃ę൥ȧȩɄȽɀȞȩȭɂȦɩȥɥăȱȥȱɄȦɣĂᆤଞɈࡠಣဿ຦Ī‫ێ‬༃ୈࡖɂ཰༃ୈࡖɈਗ౰īɈచဍɅȾȞɀɉĂ႘཰࢝ෂ‫ۀ‬๱ɬதȞɀ൥ဿɢȞ‫ێ‬ඳɬ૲ȱɀȞɥăႨॸ࢞౰‫ݪ‬ɉĂTbjupi!fu!bm/!ĮTPMB-!3128-!jo!sfwjtjpoįɅຂ৶੟əɁȜɥă

ూ2/3/4/.3ā!!౰๜ĽʏʡʣĜ၆Ɉ߂ᆴ‫ۊ‬Ɂोધȱȹ UJSĪਥīĂɺʯ˂ʂ˂Īཊ‫ޡ‬īĂDNFĪ༏‫ޡ‬īʟĜʗɈ໩બ‫ݛ‬ඖ೧༏๱ഝ‫ݡ‬ᆎĪhspxui!sbufīɂࡠಣဿ຦Ī‫ێ‬༃ୈࡖɂ཰༃ୈࡖɈਗ౰īɈచဍă૫ɅĂUJS ʨˋʡɈ‫ݚ‬ငൎᆔ५࢒ɍෂငൎᆔ५Ī847iQb.398iQbīɈ໩બ‫ݛ‬ඖ೧ʟĜʗɈʟĜʗଋɬĂऋৱ௫ऋɈ DNF ʟĜʗɂɈ྘ߏɅࡊȿȞɀ࿎‫ݟ‬ȱĂ3121༃ȥɣ3123༃ɈࡠಣȮɂĂ‫ۀ‬๱൑ȮɂĂ਒๱ȮɂɈʨɼɺʑၒ౷ඩɬધ୸ȱȹăȯɣɅ೔࢝൥࡜ᄪഗʺʟ˃ Opoizesptubujd!JDptbifesbm!Bunptqifsjd!NpefmĪOJDBNī.cbtfe!usbotqpsu!npefmĪUNīɈ໩બ‫ݛ‬ඖ೧ʟĜʗĮOjxb!fu!bm/-!3122įɂɈ೔࢝྘ߏɬ਄ȞĂऋৱ௫ऋɈঔ
ɣɦȹᆴ‫ۊ‬Ɂધ୸ȱȹʨɼɺʑၒ౷ඩɈൃຎ౯ɬ࿎‫ݟ‬ȱȹăȷɈय़‫ݪ‬ĂɃɈ༃ĂɃɈ‫ۀ‬๱൑ĂɃɈࡠಣɜ‫ݚ‬ငൎᆔ५࢒ɍෂငൎᆔ५Ɂɉ UJS ʟĜʗȦ DNF ʟĜʗɅൎȱɀ௵Ʌ࿹ʨɼɺʑɬ૩ȻĂູɅ652.4:9iQb Ɂ࿹ʨɼɺʑȦ੕൥ɅɄɥभ৐ȦȜɥȭɂȦɩȥȽȹăɘȹĂOJDBN.UN ʟĜʗɂɈ྘ߏȥɣĂऋৱ௫ऋɂȞȠঔɣɦȹᆴ‫ۊ‬ɁɈ྘ߏɅࡊȿȞɀಡฤȯɦȹʨɼɺʑၒ౷ඩɉĂฝ‫ۀ‬๱Ɉෂ௫ငൎᆔ५‫ެڬ‬ɉĂൎܾȳɥ‫ۀ‬๱൑Ɉ်Ɉ
ĮBNUE-!3128įɅຂ৶੟əɁȜɥăᆴ‫ۊ‬Ʌɜไᅙ‫ݢ‬༑ɁȜɥȭɂȦ૲ȯɦȹăႨॸ࢞౰‫ݪ‬ɉĂTbjupi!fu!bm/!
ଟ૷ćDPOUSBJM Ɉ໩બ‫ݛ‬ඖ೧ʟĜʗɉĂ࡜௣ॸ࢞ஒɈ௄૊્Ă៛્Ăਡᆏࠞࣃॸ࢞ஒɈ෨๜્ɢɤอࢷɬି
ȫȹɜɈɁȳăDPOUSBJM ʯ˅ʐɿʇʠɉ໲ႨਂऋĆ໲ਂੰචĆKBNDP Ɉഽ൥ɄࢾᆵɈɜɂɅଌૈȯɦɀȞɘȳăOJDBN.UN ʟĜʗɉ DFSfT ࢼວᆀᅙॸ࢞Ɉ‫ࠞێ‬ɂȱɀ࡜௣ॸ࢞ஒɈඌ۩્ɢɤอࢷɬିȫȹɜɈɁȳă

ş2/3/5/ā!!࡜েఫඣृɅ࠲ɩɥʨĜʙʻ˃ˁʴˁʠ˂ĪWMīɈव౰!!
Ī࢏౦৘ცĂྦྷ৏ຼૂĂᥓນஶાĂ໴৮ల઺Ăᤁા෸ৠĂ݊ႨৰīĮ‫ޱ‬ᅟį
઀਱Ɉ‫࡜௵ڽ‬௣Ć‫ݗ‬ඤ‫ݛ‬এ௣Ă‫ސ܀‬ജʺʟ˃Ɉ೔࢝ɁɈ‫ݲ‬ລຑɈఛȱȞ௻࣍‫ݚ‬ɅȤȞɀĂএ੭࡜েఫඣɈࡊࠎ
ʟĜʗɂɄɥఱ৙‫ܒ‬౳ʟĜʗɈେୠĆ‫ސ‬಑Ȥɢɍอࢷɉॸ࢞ʋʷʽʣʞɻɒɈਇॷɈəɄɣȴĂଜ‫ޏ‬ɒɈ௶ၡ࠮
ইɈࠫ๘ȥɣɜ‫ࡹڷ‬ȦȜɥăȭȠȱȹ༬ाȥɣĂණ࢝࡜েृɈఫඣɬ਄Ƞȹɛ‫ބ‬ȦਡɁ࡜েĆࠞࣃॸ࢞ɬైమ
ȳɥǐॸ࢞ஒĆॸ࢞ʓˋʗĜĪຄࢶ൥ߔ൥࡜‫ޠ‬ᅖॸ࢞ஒĮBPSJįĂშগ‫ݎ‬൥ߔۧහණ࢝ࠞࣃॸ࢞ஒĮJTFFįĂຄ႘൥ߔ൥࡜‫ޠ‬ᅖဿ຦ॸ࢞ʓˋʗĜĮDBPTį
ĂȤɢɍಫᅝ൥ߔࠞࣃ˂ʺĜʠʓˋʏˋʈॸ࢞ʓˋʗĜĮDFSfTįī
Ȧࢾລȱɀ‫ݜ‬೻ॸ࢞ଆĪʨĜʙʻ˃ˁʴˁʠ˂Ĉ‫ ݚڬ‬WMīɬव౰ȱĂ߂ࢪ๘Ɉູఋɂॸ࢞૝દɬߤȥȱȹॸ࢞ɂ࣋‫ۋ‬ɬ3118༃๱ɢɤယඐĆᇦ़ȱɀ਄ȽɀȞɥăWM ɂȱɀණ࢝࡜েृఫඣɅ࠲ɩɥ୭ᅟɄ‫ݻ‬൨Ʌଲɤ೨əĂණ࢝‫ݗ‬ඤ‫ݛ‬ɼʣʏɺʙʮĂ౉ஃࠞɼʣʏɺʙʮĂණ࢝ࠫപຕਗʏʑʞʸĪHFPTTīຑɈ‫ބ‬ȦਡɅȤȫɥ୭ᅟ‫ݻ‬൨ɅਇॷȱɀȞɥăȭɈሌ೨əɈෂĂDFSfT ɉಇો࡜௣‫ܒ‬౳ʟĜʗɈେୠĆஐᆅȤɢɍ৊ާĂȤɢɍେୠȯɦȹಇો࡜௣‫ܒ‬౳ʟĜʗɈ਒๱‫ݛ‬Ă‫ސ܀‬ജʺʟ˃‫ޜ‬೑ɈȹɛɈ‫ܒ‬౳ʟĜʗɈᄵৌߤᅙĂȤɢɍএ௣ᆅ‫ސ‬ɈȹɛɈ߂ହ‫ސ‬಑ɬ਄Ƚɀ
ȞɥăDFSfT! WM Ɉູ෡ɂȱɀĂWM ࡙࠲ɈəɄɣȴĂ‫ܒ‬౳࠲ब࡙࠲Ī࡜௣ෝ‫ܒ‬౳ʓˋʗĜĂKBYB0FPSD ຑīĂ― 26 ―

მ࠰ࡅࣞĪɾɿʎĜʣʽĜʑīɂɈᇦ़ɬఠɛɀȞɥɈȦູ෡ɁȜɥăĮိ౰39༃๱ߤ຦‫ޱ‬ᆒį
DFSfT Ɂɉ WM ૅ‫ܧ‬ଆɬಡȫ WM ైమĂWM ᇦ़࡙࠲ɂɈ෮౲ɈᄜߠɬඐȽɀȞɥăߤ຦ɂȱɀɉĂෂ߇โૢࣞɁȜɥಇો࡜௣‫ܒ‬౳ʟĜʗदɈஐᆅĆ৊ާɅ‫ݡ‬ȢĂఛȹɄᇦ़वൔɈჹઅɬ਄ȽɀȞɥăȱȥȱĂಇો࡜௣‫ܒ‬౳ʟĜʗஐᆅɜȷɦɄɤɈɾɿĜʠɬಬɛɀȞɥȹɛĂʟĜʗʱĜʑ‫ޏۙڳ‬ĪʟĜʗૅ‫ܧ‬ଆīɂɜᇦ຦ȱĂৌᆎɈᆯȞ‫܄ۿ‬ɬ਄Ƞ๰ᆵɜॅറȱɀȞɥăိ౰39༃๱ DFSfT ɉࠎૢ৫ɁȜɤĂWM ᇦ़࡙࠲ɂɈ‫ࠓৄॽڷ‬ɈȹɛɈ WM ࢾࡼ‫ޏ‬ĪWM ਆ୔‫ޏ‬ɂວ໲īɈଌૈĂɄɣɍɅ WM ਆ୔‫ޏ‬ɬާ੓ȱȹĪ2/3/5/4/īă
WM ࢾࡼ‫ޏ‬Ɂɉ઀༃๱Ɉࢾࡼ‫ޏ‬ɁɈ॰‫ૢڨ‬ਐɁȜɥ WM Ɉ‫ࡹڷ‬ɬ૲ȳဦ௕Ɉ‫ีޜ‬ɂ߂൥ߔɈߤ຦ၡਠȦɄȯɦȹăဦ௕‫ีޜ‬ɉ‫ݚڬ‬ɈɢȠɅɄȯɦȹăಫᅝ൥ߔࠞࣃ˂ʺĜʠʓˋʏˋʈॸ࢞ʓˋʗĜćႨૢࣞɅȤȞɀ੕୒โɅɛȰȳ࡜েृɈఫඣၫၭɈߊᆏɅ৐
ȫĂࠞࣃ˂ʺĜʠʓˋʏˋʈॸ࢞ʓˋʗĜɉ‫ܒ‬౳ʟĜʗɈɺĜʃɼʮ࢒ɍ‫ܒ‬౳ʟĜʗɈ‫ސ‬಑Ćॳ௠ࡳ୹Ɉާཡɬ
ฆȲɀʺʟ˃ोધय़‫ݪ‬ɂɈ྘ߏ‫ސ‬಑ɬ਄ȞĂʺʟ˃‫ޜ‬ᆯɅࡍᅇȳɥăȯɣɅɺʐɺ‫ۊ‬ɬෂఘɅਡ੫โɄࢾວɅ
ɢɤ๐ާȯɦɀȞɥၪଗࠫപʥʛʠˇĜʇ TLZOFU Ɉ‫܄ۿ‬Ă‫ڿ‬૩ɬ਄ȞĂȷɈʟĜʗɬ‫ܒ‬౳Ăʺʟ˃ॳ௠Ɉȹ
ɛɅ߂࠲बʋʷʽʣʞɻɅอࢷȳɥăႨʓˋʗĜɁɉĂ࡜েृɈఫඣɅྼᅟɄ‫ܒ‬౳ʟĜʗɈɺĜʃɼʮ࢒ɍ‫ܒ‬౳Ćණ௫ࠫപʟĜʗɅɢɥණ࢝࿍೸ࠞࣃɈ‫ސ‬಑Ćॳ௠ࡳ୹ɈާཡɅɂȩɅ෉ᆵȱĂȷɈ‫ݿ‬าɁྼᅟɂɄɥ࡜েʺ
ʟ˃ĂဘଋஃࠞʟĜʗĂ౉ஃࠞʟĜʗຑɉ഼ࢪ๘ɁާཡĆ౲ྩȱȹɜɈɬߤᅙȳɥăᇦ़ਆࡹĆਆ୔‫ޏ‬Ʌ࠲ȱɀɉާ੓ॄྣɂߔ౺Ɉઞ‫ྣݡ‬࿹ඐɬࢪ๘೔ൌɁယඐȳɥɂɂɜɅĂߔငĆ൥ߔۡ౺Ɉॸ࢞ৄᆔɅ࠲ȳɥૅ‫ܧ‬ຑɬฆȲĂ૫౦ൣɈॸ࢞ଞ‫ۋ‬౰Ʌਇॷȳɥăຄࢶ൥ߔ൥࡜‫ޠ‬ᅖॸ࢞ஒćႨૢࣞɅȤȞɀ੕୒โɅɛȰȳ࡜েृɈఫඣၫၭɈߊᆏɅ৐ȫɀĂ൥࡜‫ޠ‬ᅖॸ࢞ஒɉ
ණ࢝࡜েʺʟ˃Ɉ‫ޜ‬೑ɂʟĜʗວ‫ސݛ‬಑ࡳ୹ɈާཡɬฆȱɀĂ࡜েʺʟ˃ोધय़‫ݪ‬Ɉ྘ߏ‫ސ‬಑Ćʺʟ˃‫ޜ‬ᆯɬ਄ȠăɘȹĂ߂ࢪ๘ȦȭɈɢȠɄ࡜েʺʟ˂ˋʈय़‫ݪ‬ɬᆀᅙȱɀĂ࡜েव౰ɂ࡜েဿ‫ʹݛ‬ʃʣʒʸɈᆅ‫ސ‬Ɉ‫ޜ‬೑ɬూɥȹɛɈૅ‫ܧ‬ɬ਄Ƞăຶɣɦȹ൥࡜‫ޠ‬ᅖʺʟ˃दĂʟĜʗ‫ސ‬಑ʜĜ˃दɬຕਗȳɥȭɂɅɢɤĂ߂ॸ࢞ࢪ๘Ȧɢɤᇦ़ȱɀ࡙༑ȳɥʨĜʙʻ˃ˁʴˁʠ˂ĜɬᄆૄȳăɘȹĂʨĜʙʻ˃ˁʴˁʠ˂ĜɅĂɢɤഽȩɈ൥ߔຑɈॸ࢞ʈ˃ĜʯȦઞ‫ݡ‬ɁȧɥɢȠɄॸ࢞ৄᆔɬైమȱĂȷɦɬ‫ݢ‬༑ɅȳɥʏʑʞʸɈ‫ޜ‬ᆯɬଌૈȳɥăႨॸ࢞ஒɁɉĂ࡜েʺʟ˃ɈާཡɂȷɈ‫ޜ‬೑Ăȷɦɬᆀᅙȱȹʺʟ˃ʏʷʽ˄ĜʏʿˋɅູ‫ݛ‬ȱȹॸ࢞ɬ਄ȠăȭɈɢȠɄॸ࢞ɅྼᅟɄ‫ܒ‬౳ʟĜʗĂဘଋஃࠞʟĜʗĂ౉ஃࠞʟĜʗɈଲຶɂĂʺʟ˃ඩɂ྘ߏȳɥȹɛɈʜĜ˃ɉ഼ࢪ๘ɁާཡȱȹɜɈɬᅙȞɥăɘȹĂᇦ़ਆࡹɅ࠲ȱɀɉĂާ੓ॄྣɂߔ౺Ɉઞ‫ྣݡ‬࿹ඐɬࢪ๘೔ൌɁယඐȳɥăშগ‫ݎ‬൥ߔۧහණ࢝ࠞࣃॸ࢞ஒćႨૢࣞɅȤȞɀĂ੕୒โɅɛȰȳ࡜েृɈఫඣၫၭɈߊᆏɅ৐ȫɀĂۧහණ࢝ࠞࣃॸ࢞ஒɉ‫܀‬Ćਏ౉ृɅ࠲ȳɥྦ᩼ൌ຃੪Ȥɢɍණ௫ಡ඲Ɉ࡙ࡉɬᅙȞȹࠫപʟĜʗɈଲຶĂ౉େૅ‫ސ‬಑ၭɈާཡĂ਒‫ސ‬ജ๱൥࡜‫ޠ‬ᅖʺʟ˃Ɉާཡɬယඐȳɥă഼ࢪ๘ɁާཡĆ౲ྩȯɦȹ࡜েʺʟ˃Ă‫ܒ‬౳ʟĜʗຑɬߤᅙ
ȱĂࠫപʟĜʗɂ࡜েʺʟ˃Ɉ྘ߏ‫ސ‬಑ɬ߂ࢪ๘ɂᇦ़ȱɀ਄ȠȭɂɁ࡜েဿ‫ʹݛ‬ʃʣʒʸɈᆅ‫ސ‬Ʌࡍᅇȳɥăਆ୔‫ޏ‬Īᇦ़ਆࡹīɅȾȞɀɉᆾྈɁඐຎȱĂඐຎ༃‫ެڬ‬Ʌɜߔ౺Ɉઞ‫ྣݡ‬ɬ࿹ඐȳɥɄɃਆ୔‫ާޏ‬੓ɅࢾᆵȱĂႴ༃Ɉਆ୔‫ާޏ‬੓ɬ‫ݢ‬༑ɅȳɥăɘȹĂႨॸ࢞ஒ຾૵Ɉਡ੫โɄਆ୔‫ޏ‬ɞଭ଴ॸ࢞ଞɈ‫ۋ‬౰ɬૅ‫ܧ‬ȳɥăຄ႘൥ߔ൥࡜‫ޠ‬ᅖဿ຦ॸ࢞ʓˋʗĜć࡜েဿ຦ᅅപɈఫඣɅɂȽɀ࿤‫ݢ‬ज़ɄဘଋஃࠞɅबɥʟĜʗᆀᅙɂʺʟ˃
਒๱‫ݛ‬ɬɛȰȱĂ൥࡜‫ޠ‬ᅖဿ຦ࠫപॸ࢞ʓˋʗĜɉࠫപȤɢɍʺʟ˃‫ސ‬಑ɬฆȱɀĂ‫ݗ‬ඤ‫ݛ‬ɈঈۚɂɄȽɀȞɥ‫ݗ‬ଆৌ‫࡜ݪ‬ൌɈණ࢝ࡤჹɈဿ຦ɂஃࠞĂɄɣɍɅ࡜েɅ൥ȧɄ‫ࣗ܆‬ɬ࢒ɖȳʀɺ˅ʖ˃ɂ‫܀‬Ɉஜູ౯ɬ‫ސ‬ცȳɥăȷɈȹɛɅĂႨʓˋʗĜɈ൥࡜ࠫപĂ‫ޠ‬ᅖࠫപȤɢɍ࿉ஸʋɺ‫ސ‬಑ຑɅɢȽɀຶɣɦȹ‫ݗ‬ଆৌ‫࡜ݪ‬ൌʟĜʗɞĂၪଗĂʀɺ˅ʖ˃Ă‫܀‬Ă࡜௣ʩˁʹĜʗɈᇦറණ௫ࠫപʟĜʗɬ WM Ɉॸ࢞ஒĆʓˋʗĜɅอࢷȱȾȾĂȷɦɣɁާཡȯɦȹ߂ହʺʟ˃Ȥɢɍ‫ܒ‬౳ʟĜʗຑɬߤᅙȱĂᇦ़ॸ࢞ɬైమȳɥăᇦ़ਆࡹĆਆ୔‫ޏ‬Ʌ࠲ȱɀɉĂާ੓ॄྣɂߔ౺Ɉઞ‫ݡ‬ᆟྣɬࢪ๘೔ൌɁယඐȳɥă
ş2/3/5/2/ā!!ಇ ો࡜௣‫ܒ‬౳ʟĜʗେୠĆஐᆅĆ৊ާĪྦྷ৏Ăඹෂ‫܉‬௃ĮKBYB0FPSD<! DFSfT! ࢊۙஂ࣋ୂĂই
WM ູ໸஝࣋įĂಆᄄĮʟĜʗૅ‫ܧ‬ଆįī
WM ާ઻ȥɣ‫࠭ێ‬ȱɀ໲ႨɈ NUTBUĆHNT ‫ܒ‬౳ĂဴਡɈ HPFT ‫ܒ‬౳Ă݂ୋɈ NFUFPTBU ‫ܒ‬౳ĂෂਡɈ
GZ3‫ܒ‬౳ʟĜʗɅൎȱĂ‫ۀ‬๱Ľॄ๱੐࿈ृɒဿࠓɬૈȱȹʈ˂ʛʡʟĜʗɈ guq ৊ާɬॅറȱɀȞɥăɘȹĂ
NFUFPTBU ʟĜʗɬதȞɀɉĂ༯ఒʟĜʗɈஈ˂ɺ˃ʗɼʸିఒĆʈ˂ʛʡဿࠓĆ‫ކ‬ജ੼౰Ćguq ৊ާɈ੼ࣞɬ૵຦‫ݛ‬ȱɀȞɥăஈ˂ɺ˃ʗɼʸஐᆅɬȱɀȞɄȞ NFUFPTBU ‫ܒ‬౳दɅ࠲ȱɀɉĂNfufptbu.JEPDĪɼˋʡᅖ௫īɉ FVNFUTBU ʵĜʗ˃ʍɼʠɅʾĜʎ๨ሃȱĂʟĜʗɬɼˋʗĜʥʛʠॄᄻɁଲຶĂʈ˂ʛʡʟĜʗஐᆅɬʂʭˁɼˋɁ˃ĜʙˋஐᆅɂȱɀʟĜʗૅ‫ܧ‬ଆɈಆᄄ્Ʌ‫گ‬ᅲȱɀȞɥăʟĜʗᆲɈ൥ȧȞ NTH
ĪNfufptbu!Tfdpoe!Hfofsbujpoīʏ˂ĜʒɉʫʐʿˋʞʛʇଜɬฆȲɀ FVNFUTBU ɅʟĜʗଲຶ‫گ‬ᅲɬ਄ȞĂ― 27 ―

Ǐˎॢယɬᄆ‫ڤ‬ɂȱɀ ubqfĪMUP5īɁʟĜʗଲຶɬ਄ȞĂʞĜʯɈ຿ə୸ȱĂʈ˂ʛʡʟĜʗஐᆅɬວȲȩʟĜʗૅ‫ܧ‬ଆɂࢾລȱɀଌૈȱɀȞɥăိ౰39༃๱ɉǎȾɈʠʬʛʇȦȜɥăɌɂȾɉ3126༃ǓॢǓ໲ɢɤ౷ૺ‫ۿ‬ᅙȯɦȹɌɘɩɤǔਖɈ hsjeefe!
qspevdu Ɉ˂˂ĜʑĪూ2/3/5/2/.2īɁȜɥăඹෂ્ȦާཡȱɀȞɥാᅣၪଗʯ˅ʘʇʠᅙɅວ્Ȧާཡȱȹ౼დࡐ‫ݝ‬ၒ౷ʑʅĜʸɬ‫ھ‬ఆȱȹɜɈɁĂူᇙஐ඲ɅൎܾȱɀȞɥȭɂȦູෳɁȜɥĪ51DQV! 367HC ʹʺ˂຃੪ʍĜʨɁ੕඗51࿓Ɂ೔ɀɈʨˋʡʟĜʗɈஐᆅȦ‫ݢ‬༑īăႨʟĜʗʓʛʠɈ˂˂ĜʑʦĜʠɬǑॢ2:໲Ʌཡ࿍ȱĂஈ˂ɺ˃ʗɼʸĂ‫ࢦݿ‬ယࢼɅ guq! tfswfs ɬฆȲɀ৊ާȱɀȞɥĪʘɾˋ˅Ĝʡଌಕɉ21/4/! ɬઞ௎īăႨஐᆅĆ৊ާɁ WM ɈʍʵĜʠɬຶɀȞɥă㸦+6)'⌫ᙧ㸧

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ూ2/3/5/2/.2āɌɘɩɤ࿈ஈʟĜʗĪIT-!GEīɢɤĂhsjeefe!qspevdu!Ɉ౺౰

ɜȠ‫ێ‬Ⱦɉɺʹ˂ʃ൦જ౦ൣಇો࡜௣‫ܒ‬౳ HPFT.S ɒɈൎܾɁȜɥă3128༃ǏॢɅ樋৏ĂඹෂɁ OBTB!
Bnft ॸ࢞ʓˋʗĜɬၸᄎȱĪଖణ2/3/5/2/.2īĂHPFT.S ʟĜʗɬᅙȞȹࢼວॸ࢞ɬైమȳɥȭɂɅȾȞɀਗ‫ڷ‬ȱĂࡕɅʯ˅ʐɿʇʠɂȱɀ຦ȧ୸ȱɀȞɥĪᇉćూ2/3/5/2/.3īăHPFT.S ɉ3127༃22ॢ2:໲Ʌ஑ࠫപȦ਄ɩɦĂ3128༃೐཰Ʌ౷ૺ‫ۿ‬ᅙާ઻ᅅฤɁȜɥăHPFT.S ɅɉɌɘɩɤǔਖ຃੪ʓˋʍ BIJĪBewbodfe! Ijnbxbsj!
JnbhfsīɅࣷȞ઱ᅕɬ૩Ⱦ BCJĪBewbodfe! Cbtfmjof! Jnbhfsīɬ຃੪ȱɀȤɤĂɌɘɩɤǔਖɁຶȹඪॽɬܾ
ᅙȱ‫ڹ‬ȞăȷɈȹɛĂHPFT.S ɈʟĜʗอࢷɅ࠲ȱɀɜĂႨࢼວॸ࢞ɬෂ߇ɂȱɀ‫ݢ‬༑ɁȜɥɂૃɩɦɥă

ଖణ2/3/5/2/.2āOBTB!Bnft ॸ࢞ʓˋʗĜၸᄎ૪Ɉʯ˄ʔˋɈᅕાă― 28 ―

ూ2/3/5/2/.3ā!!OBTB! Bnft ॸ࢞ʓˋʗĜɢɤอࢷȯɦȹʍˋʯ˃ʟĜʗɢɤ࿑‫ކ‬ȱȹ HPFT.S ʨˋʡǎɈ gvmm.ejtl ɼʹĜʐĪඹෂ્੼౰ĂȤɢɍอࢷī

ş2/3/5/3/āWM ɅȤȫɥ TLZOFU Ɉএ࣍ɂߤ຦ၡਠĪ໴৮Ă݊Ⴈī
3122༃ǏॢɅཡ౺ȱȹຄ໲Ⴈ൥ర੠ɂȷɦɅ཮Ƞဏ๿ঈાᆵཡ๝ஒɈૢঠɈय़‫ݪ‬౺ȲȹఠਟɄʀʥ˃ʆĜ୅ࢣɈ྿ཋɬॄঅȱȹষĂɢɤ਒๱Ʉʀʥ˃ʆĜʶʥʐʹˋʠʏʑʞʸĪFofshz! Nbobhfnfou! Tztufn<! FNTīɒɈଜ‫ޏ‬โᅟಃȦ਒ɘȽɀȞɥă਒๱Ʉ FNT ɬ৭භȳɥ௫ɁĂ੕୭ᅟɄ੔౺‫ݢ‬༑ʀʥ˃ʆĜɈɌɂȾɁȜɥാᅣ৉ཡ๝Ɉᆀᅙɉज़ȥȵɄȞăಇો࡜௣‫ܒ‬౳ɌɘɩɤǔਖɈ೔๏໲ଗᆲʟĜʗɉാᅣ৉ཡ๝ᆲɈ༘‫ڐ‬ɅᄵৌɁȜɥȦĂైപඩɁȜɥȹɛĂȷɈॳ௠Ȧ୭ᅟɁȜɥăႨॸ࢞ɁɉĂಫᅝ൥ߔɅȤȞɀණ௫ಡ඲ळɈ೔๏໲ଗो
ĪDN32īɂɌɘɩɤǔਖɈʟĜʗɬ྘ߏȱĂɌɘɩɤǔਖɈ౼๱࿎‫ݟ‬ɬ਄ȽȹăɘȴĂɌɘɩɤǔਖɈʟĜʗɉࠫപ๘ࣷႁɈ‫܀‬Ɉ‫ࣗ܆‬Ȧ୥ယɅ৽ᆞɁȧɀȞɄȞȹɛɅĂ౴๏໲Ɂɜ DN32Ɉඩɂ঄ුɅੇȦ౺Ȳɥ௲ਗȦȜɥȭɂȦယȥȽȹăȭɈय़‫ݪ‬ɬຝɘȢɀࣷႁɈ‫܀‬Ɉ‫ࣗ܆‬ɬ༧தȳɥȹɛɅ51ҵĿ51ҵɈᆴ‫ۊ‬ɁɈɌɘɩɤǔਖʟĜʗɈ࿈ஈှੇɬोધȱȹă࿈ஈှੇɬᆀᅙȱɀࣷႁɈ‫܀‬Ɉ‫ࣗ܆‬ɜதެȱȹɂȭɧĂɌɘɩɤǔਖɈ೔๏໲ଗ
ᆲʟĜʗȦ DN32ʟĜʗɢɤɜृຕโɅ‫ݿ‬൥ɂɄȽɀȞɥȭɂȦယȥȽȹăၪଗ๙ൿʺʟ˃Ʌɢɥोધɬ਄Ƚȹ
ɂȭɧĂȭɦɉɌɘɩɤǔਖɈ೔๏໲ଗᆲɈైฤɈ੫Ʌ৽ᆞȱɀȞɄȞʀɺ˅ʖ˃Ɉ‫ࣗ܆‬ɁȜɥȭɂȦယȥȽȹă൥࡜ෂɈʀɺ˅ʖ˃ɉĂණ࢝Ɉ࡜েɬ੆‫ۦ‬ȳɥ࣡ɛɀ୭ᅟɄۚાɁȜɥăȱȥȱĂȷɈ౺౰ʹʃʣʒʸɉထઔɁȜɥȠȢĂູɅຄɺʐɺ‫ۊ‬ɅȤȞɀɉ༃ęɈ೐ऄ࡜ൌɈ༧୸ᆲॽಓɜɤɈ࿤ߊฤ౯Ȧ൥ȧȞȹɛĂࣷ༃Ɉʀɺ˅ʖ˃Ɉ༃ęɈʠ˄ˋʡɉ୥ယɅᆅ‫ސ‬ȯɦɀȞɄȞăȭɈɢȠɄ௻࣍ɈෂĂႨॸ࢞ɁɉĂ໲Ⴈ௫ऋɁෳࡖ
ɅɩȹȽɀଲຶȱȹ NPEJTĂQSFEF ʑʃɼˁʐʂʹĜʗĪTLZOFUīĂDJNFM ʍˋʭʁʠʹĜʗĪOBTB0BFSPOFUīɈʀɺ˅ʖ˃৉ߔโৎȯĪBPUīɈʟĜʗɬᅙȞɀĂ໲Ⴈ௫ऋɈʀɺ˅ʖ˃Ɉʠ˄ˋʡ‫ސ‬಑ɬ਄ȽȹăฤᆲโɄʠ˄ˋʡ‫ސ‬಑ɬ਄ȠȹɛɅĂɘȴĂ3126༃22.23ॢɅಫᅝɅȤȞɀ QSFEF ʑʃɼˁʐʂʹĜʗĂ
DJNFM ʍˋʭʁʠʹĜʗĂQGS ˁʐʂʹĜʗĪXNP0HBXīɂɈວ૪ࠫപɬ਄ȞĂʑʃɼˁʐʂʹĜʗɈ౼๱࿎‫ݟ‬ɬଌૈȱȹăȭɦɅɢɤĂ611on Ɉ BPU ʟĜʗɅȾȞɀĂʑʃɼˁʐʂʹĜʗɂ DJNFM ʍˋʭʁʠʹĜʗɈੇȦ1/115ľ1/118ĂQGS ˁʐʂʹĜʗɂɈੇȦĽ1/127ľ1/123ɂྥ௵ɅழȯȞȭɂȦယȥȽȹăȭɦɅࡊȿȧĂ໲ႨɈǒණ๘ĪಫᅝĂ൥ੳĂཆ࿝Ăဏ৮๿Ă၃টგĂ࢔গ๿īɁෳࡖɅɩȹȽɀଲຶȯɦȹ QSFEF ʑʃɼˁʐʂʹĜʗɂ DJNFM ʍˋʭʁʠʹĜʗɈ611on Ɉ BPU ɈʟĜʗɬᅙȞɀĂ໲Ⴈ௫ऋɈʀɺ˅ʖ˃Ɉʠ
˄ˋʡ‫ސ‬಑ɬ਄ȞĂNPEJT Ɉ BPU ʟĜʗɂɈ྘ߏɬଌૈȱȹăȳɥɂĂಫᅝɁɉ3117.3126༃ɅိࣧɁᄝǐœ
Ī1/12īğ༃Ăဏ৮๿Ɂɉ3119.3125༃ɅᄝǎœĪ1/117īğ༃Ă၃টგɁɉ3118.3124༃ɅᄝǎœĪ1/116īğ༃Ă࢔গ๿Ɂɉ3117.3123༃ɅᄝǏœĪ1/119īğ༃Ă൥ੳɁɉ3119.3126༃ɅᄝǎœĪ1/11:īğ༃Ăཆ࿝Ɂ
ɉ3116.3126༃ɅᄝǎœĪ1/117īğ༃ɁঌவȱȹȭɂȦॽಓɜɣɦȹăȭɦɉ NPEJT Ɉ BPU ʟĜʗȥɣॽಓ― 29 ―

ɜɣɦȹʠ˄ˋʡɂǒණ๘ෂǑණ๘ɅȤȞɀฤᆲโɅᄝ46œ‫ڬ‬໘Ɂ౲ਗȳɥȭɂȦယȥȽȹăȭɈय़‫ݪ‬ɉĂ೐ऄ࡜ൌɈ༧୸ᆲɈ࿎‫ݟ‬ɅᄜᆏȾȭɂȦࡖ൒ȯɦɥă൥࡜ෂɅȤȞɀĂ౉௾࡜ɉණ࢝Ɉ࡜েɬ੆‫ۦ‬ȳɥ୭ᅟɄᄜߠɬ‫ݪ‬ȹȱɀȞɥăൎᆔ५Ɉ౉௾࡜Ɉܴ෸ʃˁʸᆲĪ‫ݢ‬ਏ౉ᆲīɞܴ෸ယ࿫Ɉฤ௵ᇦറࠫപɬ਄ȠȹɛɅĂණ௫ȥɣɈ˂ʺĜʠʓˋʏˋʈɉ࣡ɛɀᄵৌɁȜɥȦĂ൥࡜৭ഢɈထઔȯɞණ௫ȥɣൎᆔ५௫඘Ʌȥȫɀ༏๱Ȧ൥ȧȩঌவȳɥɄɃɈᆅᄻȥɣฤᆲโɄ࿎‫ݟ‬ɉঔɣɦɀȞɥăႨॸ࢞ɁɉĂ3126༃23ॢ33໲ȥɣ3127༃Ǎॢ42໲ɘɁĂಫᅝ൥ߔ৙ߔृ഍ਗॸ࢞ງĪ46/74ŋOĂ!
251/21ŋFīɅȤȞɀĂණ௫˂ʺĜʠʓˋʏˋʈക඲ɁȜɥʶɼʇ˅༜ၪଗोǏ൤ĪXWS2236ĂNQ2613Ă
NQ2615īĂຄಀ໤႘ȷɦȸɦɈၫ‫ڮ‬Ʌ৐ȫȹǐ൤Ɉഽ૾ੇယ࢓େယ৉ၭĪNBY.EPBTīക඲ĂʍˋʭʁʠʹĜʗĜĪDJNFMīɈोǔ൤Ʌɢɥວ૪ࠫപɬ਄ȽȹăɘȴĂਏ۫ɄɃɈɼʱˋʠɈɄȞǍଢ଼࠰Ʌ෉ᄆȱĂᄕ࠰ɜࠫപ‫ݢ‬༑Ʉʶɼʇ˅༜ၪଗो XWS2236ɬࡊஈɂȱɀĂȷɦȸɦɈ଴ၭɁຶɣɦȹ‫ݢ‬ਏ౉ᆲɂɈੇɈိࣧɂ࿈ஈ
ှੇɬ࢙ɛȹăȭɈࡖ࠰ෂɈ XWS2236ɅɢȽɀࠫപȯɦȹ‫ݢ‬ਏ౉ᆲɈိࣧɉ1/8ľ1/3dn ɁȜɤĂ‫ۓ‬௱ॻȾȩɊીɈˁʐʂʖˋʟɈࠫപʟĜʗɂ‫ێ‬ඳȱȹăʶɼʇ˅༜ၪଗोວ઺Ɉ྘ߏɁɉ XWS2236ɂ NQ261302615
Ɉ࠰Ʌᄝ31œɈृຕโɄੇȦॽɣɦȹăಪ਄ॸ࢞ȥɣੇɉॳฤฤౘɈ࿤ߊȥȯɅࡧۚȱɀȞɥ‫ݢ‬༑౯Ȧ૲੄ȯɦȹă഼ၫĂDJNFMĂNBY.EPBT ɂɈੇɉ21œ‫ڬ‬໘ɂ྘ߏโழȯȞȭɂȦယȥȽȹăDJNFM ɞ NBY.EPBT ɉ౉௾࡜ɈࠫപɅູ‫ݛ‬ȱȹࠫപ଴ၭɁɉɄȞȦĂਏ۫ɄɃɈɼʱˋʠɈɄȞ‫ڤ‬ฤȱȹ൥࡜௸ॣ‫ݚ‬Ɂɉ21œา๱Ɉ౼๱ɁࠫപɁȧɥȭɂȦယȥȽȹă!
ş2/3/5/4/ā!!൦21‫ޑ‬Ķණ࢝࡜েृɈఫඣɅ࠲ɩɥʨĜʙʻ˃ˁʴˁʠ˂ĜɈव౰ķĪWMīਆ୔‫ޏ‬Ɉާ੓!
Īᤁા෸ৠĂၹ຀৹‫ێ‬Ă݊Ⴈৰī
ိ౰39༃Ǖॢ31Ă32໲Ɉᆤ໲Ă൦21‫ޑ‬Ķණ࢝࡜েृɈఫඣɅ࠲ɩɥʨĜʙʻ˃ˁʴˁʠ˂ĜɈव౰ķਆ୔‫ޏ‬ɬຎ৫Ʌɀާ੓ȱɘȱȹăȭɈଲɤ೨əɉႴ༃૩Ȼ‫ޑ‬ɤɁĂႨ൥ߔȦࡥ༄ȳɓȧ൦21‫ޑ‬ɬିȫ૩Ȼɘȱȹă଱ࠎ৫ɂȱɀो‫ކ‬ĆଌૈȳɥɺʡʨˋʞĜʐɬ౺ȥȱĂഁȞඦިȥɣ˂ʺĜʠʓˋʏˋʈယᄘɒɈ࠲ఘɬ਒ɛɀ
ɜɣȤȠɂܾၕൎ௣ɬॸ࢞ଆ༯മ೐Ɉߔင౺ɅɘɁঢ়Ȭɘȱȹăຎ໲ɉ൤ဇ27ਖȦಞࣷȳɥɂȞȠȜȞɅȩɈ๏েɂɄɤĂઞ‫ݡ‬ɬඣ༄ȵȰɥɬຶɄȞၫɜȤɣɦɘȱȹɄȥĂߔင౺3:ఱɬ࠸ɚ64შɈઞ‫ݡ‬ȦȜɤɘȱȹă਱‫ޑ‬Ɉਆ୔‫ޏ‬ʞĜʶɂȱɀĂ໲ႨȦপɥණ࢝ࠫപ‫ܒ‬౳दɬඪȽɀɜɣȞĂ˂ʺĜʠʓˋʏˋʈɅɢɥණ࢝ࠫപ
Ʌ࣓Ⴭɬ૩ȽɀɜɣȠȭɂɬऻȬĂǍ໲ᄆɅɌɘɩɤǔਖɬᅙȞȹʋˋʬʽĜʗ‫୔ܩ‬Ăǎ໲ᄆɅ໲ႨɈණ࢝ࠫപ‫ܒ‬౳Ɉ௘‫ގ‬ɂȞȠǎင৭౰ɁଌૈȱɘȱȹăʋˋʬʽĜʗ‫୔ܩ‬ɁɉĂXfc ʱĜʑɈ੕ఛ‫ސ‬಑ʜĜ˃ɬ઴ȽɀɌɘɩɤǔਖɈ‫ܒ‬౳ʟĜʗɬஐᆅȱĂಇો‫ކ‬ɞ຦‫ކ‬ɬ੼౰ȱɀණ࢝Ɉ࡜েဿ຦ɬࠫઍȱɀɜɣȞɘȱȹăᤁાູ໸஝࣋ɂၹ຀ູ໸ॸ࢞ۙȦෂఘɂɄɤʈˁʭɻʃ˃Ʉɼ
ˋʗĜʭɿĜʑɬ੼౰ȱĂ‫ܒ‬౳ʟĜʗɬଲɤ‫ڙ‬ȽȹȭɂɈɄȞઞ‫ݡ‬ଞɅɂȽɀɜ࠲ఘɬ਒ɛɣɦɥɢȠɄࠞࣃɬᅙ‫ڷ‬ȱɘȱȹăɘȹĂǎ໲ᄆɈĶ໲ႨɈණ࢝ࠫപ‫ܒ‬౳ɬඪɧȠķɁɉĂএ੭੕೐ೀɁߤᄠෂɈਆુɈၫęɅਆ‫ܩ‬ȱɀȞȹȺȧɘȱȹăɄȤĂȭɈ WM ਆ୔‫ޏ‬Ɉ‫ޱ‬ᅟĪʯ˅ʈˁʸĆɺˋʉĜʠɈୠोय़‫ݪ‬ɬ࠸ɚīɉĂိ౰39༃ǕॢɈʣʽĜʑ˄ʗĜ
Op/241Ʌɜऻ੪ȱɀȞɘȳă
ş2/3/5/5/ā!!ʧɼʩĜʑʲʇʠ˃ʃʹˁɅɢɥ൥࡜ܸಹʄʑɈɼʹĜʐˋʈोപ!
!
ĪᤁાĂ࢏౦ī
DFSfT ɁɉʧɼʩĜʑʲʇʠ˃ʃʹˁĪIT ʃʹˁīɬᆀᅙȱȹ൥࡜ෂɈྫᆲ࡜ൌɈɼʹĜʐˋʈोപ଴ၭɈ
ॸ࢞ɬమɛɀȞɥă઀༃๱ɘɁɅ๏ऋ৉ɈʧɼʩĜʑʲʇʠ˃‫ކ‬ജĪIT ‫ކ‬ജĂ‫ߍކ‬ć24ŋĿǕŋĂ‫ކ‬ജʍɼʒć
751Ŀ591ʬʇʓ˃Ă༜ෳཱྀ‫ڱ‬ć511ġ861onĂ༜ෳယ‫ސ‬༑ćǍonīȥɣ଱ᅟɄ൥࡜ܸಹʄʑɈ‫ێ‬ହɁȜɥ໩બ‫ݛ‬඾೧ĪOP3īɈੇယʑˁˋʠʃˁʸᆲĪౘდ๱Ʌଌৌ৉ᇭෳɬߙȫȹɜɈɁĂ‫ ا‬TDE ɂ࿍ࡥȳɥīɬຩ୸
ȱĂOP3Ɉǎ૫ইယ࿫ɬ‫ݢ‬૗‫ݛ‬ȳɥȭɂɅ౰োȱȹăȭɈ଴ၭɬܾᅙȱɀ OP3ऋ࠰ယ࿫Ɉ౉ိၫ৐ྥ‫ێ‬ᅕ౯ɬ෮ɓɥȹɛĂಫᅝ൥ߔɅȜɥǔި८ɀʫ˃Ɉ‫ݎ‬௫ĪTLZOFU ಫᅝʍɼʠīȥɣ೔ၫ‫ߍڮ‬ɬʃʨĜȳɥࠫപɬ਄ȽȹĪ3127༃ǎॢ2:໲īăထౘɈ IT ‫ކ‬ജɬॆȬɥ― 30 ―

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OP3‫ ا‬TDE
21280dn3

Fmfw/!) ŋ*ȭɂɅɢɤĂ౉ိၫ৐471ŋĿܴ෸ၫ৐ǕŋɈʩʦˁʶ‫ކ‬ജɬ੼౰ȱȹăȭɈʩʦˁʶ‫ކ‬ജȥɣຩ୸ȯɦȹ OP3‫ا‬TDE Ɉඩɬూ2/3/5/5/.2Ʌ૲ȳăOP3‫ ا‬TDE ɉ႘ಀၫ৐Ȥɢɍຄၫ৐Ɂ൥ȧȞȭɂȦယȥɥăಫᅝ൥ߔȥɣॽɀ႘ಀၫ৐Ʌɉ‫࠹ޠ‬ೀɅ‫ܨ‬Ƚɀ਒ബັᇭȦȜɤĂ๬ી‫ݛ‬ɜమɭɁȞɥăຄၫ৐Ʌɉ਼ઔ๱Ɉ਒Ȟ਒ബັᇭɈɼˋ
ʗĜʙɿˋʐȦȜɥȭɂȥɣĂȭɦɣȦ OP3‫ ا‬TDE Ȧ൥ȧȞঈۚɅɄȽɀȞɥɂ৽ȢɣɦɥăɄȤĂ଴೐Ɉ८ဘငယɁ OP3‫ ا‬TDE ȦழȯȩɄȽɀȞɥ଱Ʉঈۚɉଌৌ৉ᇭෳȦ඗ȞȹɛɁȜɤĂOP3Ɉഽȩɉ८ဘɢɤষၫ
Ʌယ࿫ȱɀȞɥȭɂȦယȥɥăIT ʃʹˁɁപฤȯɦȹ OP3‫ ا‬TDE Ɉඩɬ TLZOFU ಫᅝʍɼʠɅಡ඲ȯɦȹ5!
B[.NBYEPBT ʏʑʞʸɁപฤȯɦȹࣷȞ૪ਟɈඩɂ྘ߏȳɥɂĂപฤ౼๱Ɉཱྀ‫ڱ‬ɁᆤଞȦɕɖ‫ێ‬ඳȳɥȭɂȦߊȥɛɣɦȹă

ూ2/3/5/5/.2āOP3‫ ا‬TDE Ɉʩʦˁʶ‫ކ‬ജ૫ɅĂࣟஒ঍ȥɣ༧୸ȯɦɥ OP3Ɉ૪࠰ဿ‫ݛ‬ɬ෮ɓɥȹɛĂಫᅝॻ౰๜ીɈࢾᆵɬຶɀ౰๜ऋৱࣷȩɈ৊‫ܠ‬Ī౰๜ીȯȩɣɈટ৊‫ܠ‬īȥɣ౰๜ऋৱߦഖᇭၫ৐Ɉࠫപɬ਄Ƚȹăࠫപ໲Ī3128༃Ǎॢ34໲īɉഁ෥Ʌ໔Ƚ
ɀȞȹȦĂ෇೐Ʌɉฝࣚߍၫ৐ɬதȞɀ‫܀‬ɉɄȩɄȽȹă࡜௣ෝɈࠫപɅɢɥɂĂ౰๜ીɁɉ22૪ȥɣ25૪ਰɘɁॅറโɅ႘ಀɘȹɉ႘႘ಀၫ৐ȥɣိࣧဇബǕġ23n0t า๱ɈࣅȞဇȦ౅ȞɀȞȹăȜɥྦ਄࡙Ȧᆋᆌȱȹ෸ষɅଲຶȱȹ IT ‫ކ‬ജɬ‫ސ‬಑ȱȹय़‫ݪ‬ĂȻɡȠɃྦ਄࡙Ȧᆋᆌȱȹ࿥ࣷɁ OP3‫ ا‬TDE Ȧ൥ȧȩɄȽɀȤɤĂᆤᅫɅȜɥʀˋʐˋȥɣ OP3ȦʐɿʛʠɈɢȠɅလȧ୸ȱɀȞɥᅕાȦߊ໻ɁȧȹăɘȹĂ31࿓࠰ߒɈᇦറએ
‫܆‬Ɂଲຶȱȹ IT ‫ކ‬ജɬ‫ސ‬಑ȱȹय़‫ݪ‬ĂOP3Ȧ༧୸ȯɦɀ‫ ا‬TDE Ȧഝ‫ݡ‬ȱĂဇɅɢȽɀ߄ઢȯɦɀ‫ ا‬TDE ȦঌவȳɥᅕાȦɉȽȧɤॽɀଲɦȹă‫ڬ‬௫Ɉ‫ސ‬಑य़‫ݪ‬ɉʏʷʽ˄Ĝʏʿˋɬ઴Ƚɀଌപȯɦȹʑʲʇʠ˃ɬ੔এȳɥɢȠɅ OP3‫ ا‬TDE Ɉ੕ไ‫ݛ‬ɬ਄ȽȹɜɈɁȜɥȦĂȭɈ‫ސ‬಑ɅɉǍ‫ކ‬ജຎȹɤౘ૪࠰า๱Ɉोધ૪࠰ȦྼᅟɁȜɥă‫ێ‬ၫĂIT ‫ކ‬ജȥɣȞȩȾȥɈʬĜʇ༜ෳɅȤȫɥੇယ৉ߔโৎȯɬोધȱɀഫȱਗɩȵȹɜɈĪʬĜʇʍʸīɉǍ‫ކ‬ജຎȹɤౘယɁो
ધɁȧĂOP3‫ ا‬TDE ɂᆯȞഊ࠲ɬ૲ȳȭɂȥɣĂʬĜʇʍʸɬᆀᅙȱɀ‫ސ‬಑ɬ਒ബ‫ݛ‬Ɂȧɥᄆ๫ȦᆏȽȹă― 31 ―

2/4/āʯ˅ʈˁʸǏć‫ܒ‬౳ᆀᅙ਒๱‫ݛ‬ʯ˅ʈˁʸĮ‫ޱ‬ᅟį
ۧහࡊႨၭɈ౰ᆏĪ3119༃īɅɢɤĂĶۧහާཡɂᆀᅙķɅ࠲ȳɥ‫ބ‬ȦਡɈૈ઄ɉĶॸ࢞ާཡķȥɣࡳ୹Ɉဍঢ়ȞĶᆀᅙķɒɂဿ‫ݛ‬ȱȹă਱ষɈࠞࣃ˂ʺĜʠʓˋʏˋʈɅȤȞɀɉइൌโɄᄎ൨ɈཡॽĆᆅ‫ސ‬Ć‫ސ‬ड़Ăૈ઄ɒɈཱ‫܇‬ɬᄆૄȱȹഽȩɈ࠲ᇦယᄘɈࢾລൌ౫ɈෂɅȤȫɥ˂ʺĜʠʓˋʏˋʈࡳ୹ɈᆀᅙၫၭɈߊᆏɬైమ
ȳɥྼᅟȦȜɥăȷȭɁĂႨʯ˅ʈˁʸɁɉ໲ႨȤɢɍ౦‫ޢ‬ɅȤȫɥ‫ސ‬ȩɓȧ୭ᅟɄ‫ݻ‬൨ɬಡฤȱĂ˂ʺĜʠʓˋʏˋʈɈ౰‫ݪ‬ɬණ௫ɅȤȫɥ௶ၡɂᅃਗȯȵĂ‫ڽ‬ယᄘࢾລɅɢɥ‫ܒ‬౳ᆀᅙၫၭɈ਒๱‫ݛ‬ɬൿ౰ȳɥȭɂɬᄆโɂȳɥă3126༃ɉਡ੫โɄණ࢝ࠞࣃɼʣʏɺʞɻʮɁȜɥʭʽĜʙʻĜĆɺĜʑĪGFīȦ઻຦ȱȹ༃ɁɜȜɥăGF ɁɉʑʞĜʇʳ˃ʘĜɂᄎ൨‫ސ‬ड़ɬࢼᄵȳɥሌ೨əɈෂɁʍɼʀˋʑȦᄜߠɬ‫ݪ‬ȹȳȭɂȦ࢙ɛɣɦɥ
ɉȴɁȜɥă‫ߔݨ‬ɈັइɂȱɀɈ˂ʺĜʠʓˋʏˋʈɜĶ‫ߔݨ‬ɈȹɛɈ‫ߔݨ‬ķɈັइȥɣĶଜ‫ޏ‬ɂɂɜɅȜɥ‫ߔݨ‬ķɈȹɛɈັइɒʏʭʠȱɄȫɦɊɄɣɄȞăȷȭɁĂ3126༃๱ɉᅕęɄଲɤ೨əɬ਄ȽȹȦĂູɅ VBWĪVonboofe! Bfsjbm! WfijdmfīɅɢɥࣷಞ˂ʺĜʠʓˋʏˋʈɅଲɤ೨əĂɢɤʑʞĜʇʳ˃ʘĜɅࣷȞ˂ʺĜʠʓˋʏˋʈɈߊᆏɬ૚əȹă‫ܒ‬౳ᆀᅙ਒๱‫ݛ‬ʯ˅ʈˁʸɈ൦Ǐࡖෂࡖᄆ࿈Ćෂࡖो‫࠰ࡖކ‬Īိ౰39.44༃๱īɅȤȫɥॸ࢞‫ݻ‬൨Ȥɢɍൿ౰ᄆ࿈ɉ‫ݚڬ‬ɈฆɤɁȜɥă൦ǎࡖɅȤȞɀଌૈȱȹॸ࢞ʞĜʶɈູଋɅࡊȿȩʯ˅ʈˁʸॸ࢞ɬཡ๐ȯȵĂȯɣɅ୭๘‫ݻ‬൨ɬಡฤȱȹăśॸ࢞‫ݻ‬൨Ć! ਢဘɈ఍ᆧ౺દɈഝ൥ɂ৐௫ɬᄆโɂȱɀĂ౉‫ے‬Ɉ౺દᆲɬైฤĆᅅപȳɥၫၭɬߊᆏȳɥăĆ! ౉‫ے‬Ɉ౺દࡊྉɁȜɥ౉Ć๲௳Ć࡜েɈࠞࣃɬ˂ʺĜʠʓˋʏˋʈĆHJT Ɉࡳ୹Ɂ༘‫ڐ‬ȱĂȷɈ౺દࡊྉɬ
‫ޜ‬ᆯĆ৐௫ȯȵɥၫၭɬߊᆏȳɥăĆ! ໲Ⴈɂຄ໤ɺʐɺɬൎ௣ɂȱĂ༔ࣞ။ঃɈෂ߇ɁȜɥഹޮੈฤʯ˅ʓʑɅ˂ʺĜʠʓˋʏˋʈʟĜʗĂHJTĂ
࡜௣ʟĜʗຑɈऋ࠰௶ၡɬไᅙȳɥȭɂɅɢɤഹޮੈฤɬৌᆎ‫ݛ‬ȳɥၫၭɬߊᆏȳɥă
Ć! VBTĪVonboofe! Bjsdsbgu! Tztufntīɂȱɀʶ˃ʙʋʯʗĜɞঙฤᅫ࡙ɬ઴Ƚȹฝ਒๱Ɉࣷಞ˂ʺĜʠʓˋʏˋʈࡳ୹ɬߊᆏȯȵĂ˂ʺĜʠʓˋʏˋʈɬᅕęɄ‫ݻ‬൨Ʌൎܾȯȵɥʯ˅ʠʋ˃ɬ੼౰ȱĂଜ‫ޏ‬ଌകȳɥăĆ! ʭɻĜ˃ʡˇĜʇĂ˂ʺĜʠʓˋʏˋʈĂʺʟ˂ˋʈɬฆȲɀఝᆹ౺ൔृɞঢைĆ‫ݭ‬ರɈ౉ଋʺʣʗ˂ˋʈɬ਄ȠăĆ! ˂ʺĜʠʓˋʏˋʈɂ HJT ɬᅙȞȹ๬ીࠞࣃɈ༘‫ڐ‬ĂȤɢɍ˂ʺĜʠʓˋʏˋʈ଴ၭɅɢɥ๬ીʑʉĜ˃Ɉ੠ޮ༘‫ڐ‬Ɉॸ࢞ăś୭๘‫ݻ‬൨ć!!ʡ˅Ĝˋɬߤᅙȱȹࣷಞ˂ʺĜʠʓˋʏˋʈ! !
ĪQspyjnjuz!sfnpuf!tfotjoh!cbtfe!po!espof!pctfswbujpotī
Ć! ʶ˃ʙʋʯʗĜɞঙฤᅫ࡙ɬ઴Ƚȹฝ਒๱Ɉࣷಞ˂ʺĜʠʓˋʏˋʈࡳ୹ɬߊᆏȱĂ˂ʺĜʠʓˋʏˋʈɬ
ᅕęɄ‫ݻ‬൨Ʌൎܾȯȵɥʯ˅ʠʋ˃ɬ੼౰ȱɀଜ‫ޏ‬ଌകȳɥă
Program 3: Advanced application of satellite remote sensing
Since the establishment of the “Aerospace Basic Act” in 2008, the major purpose of the national policy
over the space development and utilization has changed from the stage of research and development tothat of wide-range, practical utilization. Thus, it is absolutely needed for the environmental remote sensing              
solving various problems on both scientific and social bases. In view of such background, this program(Program 3) aims at assigning important problems that must be solved on national and global levels,
integrating the results of satellite and ground-based observations, and realizing the advanced application
methodology of satellite remote-sensing data through the synergetic activities of scientists representing        
Study on spatial information system that nurtures the disaster and environmental literacy.
Įॸ࢞໘ᅎɂိ౰39༃๱Ɉ౰‫ݪ‬į

ş2/4/2/āᄎ൨‫ސ‬ड़ɈȹɛɈ˂ʺĜʠʓˋʏˋʈĆHJT
ş2/4/2/2/āɼˋʗĜʥʛʠɅɢɥଜ‫ࡊޏ‬ྉ௶ၡɈอࢷĪࣷນூྷīȭɈ‫ݻ‬൨ɉ൦ǎࡖෂࡖो‫ކ‬ȥɣॅറɈĶ੠ޮĆࠞࣃ˂ʞˁʏĜɬఀ౰ȳɥऋ࠰௶ၡʏʑʞʸɅ࠲ȳɥॸ࢞ķɅൎܾȳɥă੠ޮĆࠞࣃɅ࠲ɩɥʟĜʗʓˋʗĜ࡙༑ɂȱɀĂ‫ܒ‬౳‫ކ‬ജĂ଱൨ూ௶ၡɬɉȲɛɂȳɥˁʑʗĜ‫ކ‬ജɬʘɾˋ˅ĜʡɁȧɥʍɼʠɬ৊ާȱɀȞɥăိ౰39༃๱ɘɁॅറȱɀ৊ާȱɀȞɥਐᄆɉ‫ݚڬ‬ɈฆɤɁȜɥă

― 32 ―

ĪǍīਡ๲෮ੈ౰‫ݪ‬ూ࿍ਡ๲෮ੈĆ๲ණယᇆࡊႨ෮ੈɈ࿍೸ණଋూĂණवယᇆూĂ๲௳ూĂ๲ණᆀᅙএ࣍ూɬ
‫ކ‬ജʟĜʗĪ511EQīɬʘɾˋ˅ĜʡăĪǎī੠ޮᆂᇘూĽ31჈ယɈǍ๲ණ။೔ࡊႨ෮ੈ
໲ႨɈ๬ັ࿬ॻɈȠȻĂ43๬࿬ॻɁ੼౰ȯɦɀȞɥ੠ޮᆂᇘూɈ‫ܜ‬ᅿăĪǏīᆀ౉এ࣍ూĆ෮ੈங‫ृ౉ࢡێ‬Ī21:౉ृī࢒ɍȷɈୈ၃ණ‫ۊ‬ɬൎ௣ɅĂᆔ‫ۊ‬໘Ɉ౉ဦĂᆀ౉Ă૭౉Ʌ࠲ȳɥࡕശ૝ᆧɈେୠ౲ᆅĂএණ෮ੈຑɬ਄ȞĂȷɈय़‫ݪ‬ɬĂ଱ᅟ౉ृ෮ੈங࢒ɍᆀ౉এ
࣍ూɅɂɤɘɂɛȹɜɈă
Īǐī61჈ယɈǍ๲ණယᇆూ
ϱ႘‫ັޠ‬ණၫĂϲຄ႘ණၫĂϳ࠲ຄĆෂငණၫĂϴෂငĆࣷ࡞ණၫĂϵෂਡĆહਡණၫĂ϶ࣻୋණၫĂɈ61჈ယɈǍණवယᇆూĂ࿍೸ණଋూĂ๲௳ూɈ Ujgg ‫ކ‬ജăĪǑīණ‫౉ݚ‬ʶʛʯȭɈ‫ݻ‬൨ɉ࣋‫ۋ‬ɂ࠲ɩɤĂ3125༃๱ȥɣಫᅝ൥ߔࠡীߔॸ࢞‫ݨ‬Ķ੠ޮࠡীʈ˅Ĝʨ˃˂ĜʘĜᅤ౰ʯ˅ʈˁʸķɅȤȫɥĶࠞࣃ႕੠ߔķɅȤȞɀऋ࠰௶ၡɬߤᅙȱɀȞɥăɘȹĂ3121༃๱ȥɣಇ݊൥ߔ႕੠഍ਗʓˋ
ʗĜĶ੠ޮ‫ߔݨ‬โࡊೣɬ૩Ƚȹ႕੠ଌოଞɈᅤ౰ķĪɏȲɈȩɅ႕੠ʭɿ˅Ĝᅤ౰ਆ੐īķɅȤȫɥĶණᆅߔ‫ܩ‬୔ķɅȤȞɀ࣋੮ɂȱɀॅറȱɀߤᅙȱɀȞɥă
ş2/4/2/3/āණ‫ۊ‬Ɉࠞࣃဿ຦Ʌ࠲ȳɥॸ࢞ĪࣷນூྷīȭɈ‫ݻ‬൨ɉॅറ‫ݻ‬൨ɁȜɥĶෂਡɅȤȫɥࠞࣃဿ຦Ʌ࠲ȳɥॸ࢞ķĂĶɺʐɺɅȤȫɥࠞࣃဿ຦Ɉʺʣʗ˂ˋʈ
ɂᅟۚ‫ސ‬಑ķɅ޶ຎȳɥăණ࢝ࠞࣃဿ຦ɉʈ˅Ĝʨ˃ʑʉĜ˃Ɂ஡ęɅ঄ɦɥɈɁɉɄȩĂູฤණ‫ۊ‬ɅȤȞɀಪ਄ȱɀ୸এȳɥăࠞࣃᄎ൨ɉȷɦȦʈ˅Ĝʨ˃ʙɿˋʐɅ࠲ɩɥɜɈɁȜȽɀɜĂᄎ൨ɂȱɀɉණ‫ۊ‬ɅȤȫɥఱɂ૵೓Ɉ࠲ब౯Ʌ࠲ɩɥᄎ൨ɂȱɀ୸এȳɥăȱȹȦȽɀĂණ‫ۊ‬Ɉࠞࣃᄎ൨ɬĂණ‫ۊ‬౯Ī࡜েĂණवĂఆ౺ĂຑɈණ‫ۊ‬Ɉູ෡Ăဇ๲īɂఱ࠰ߤ຦ɂɈ࠲ɩɤɅࡊȿȞɀᆅ‫ސ‬ȳɥȭɂȦ୭ᅟɁȜɤĂȷɦɅɢȽɀɈə౷ȱȞൎ઄ɬਆȲɥȭɂȦ‫ݢ‬༑ɅɄɥăȭɈɢȠɄ৽ȢၫɅࡊȿȧĂိ౰39༃๱Ʌଌૈȱȹ‫ݻ‬൨ɉ‫ࡥݚ‬ɈฆɤɁȜɥă
ĪǍī! Efmjofbujpo!pg!efcsjt.dpwfsfe!hmbdjfst!cbtfe!po!b!dpncjobujpo!pg!hfpnpsqipnfusjd!qbsbnfufst!boe!
MboetbuĮUJS0
ĪOJS0TXJSīįcboe!sbujpĪඐຎć‫ޠ‬༂อ‫چ‬ᆵၑī
Īǎī! Bobmztjt! pg! Eftfsujgjdbujpo! Tjuvbujpo! Vtjoh! Sfnpuf! Tfotjoh! boe! HJT! .! B! Dbtf! Tuvez! jo! Pohojve!
Cboofs-!Ipsrjo!Tboez!MboeĪඐຎćཆ୐ᇥī
ĪǏī! Nbqqjoh!pg!Uspqjdbm!Gpsftu!boe!Cjpnbtt!Ftujnbujpo!Vtjoh!Njdspxbwf!boe!Pqujdbm!Sfnpuf!TfotjohĪඐຎćOhvzfo!Wjfu!MvpohīĪǐī! Bobmz{joh! Tqbujp.Ufnqpsbm! Mboe.Vtf! boe! Mboe.Dpwfs! Dibohf! jo! Tbokjboh! Qmbjo! up! gjoe! Esjwjoh!
GpsdftĪඐຎć‫ڤ‬ൗၤī
ĪǑī! ᆱ‫ݭ‬ᆔ‫ۊ‬๲ණྡဒɈ૪ऋ࠰ဿ຦ɂॄ੟ཡ๐ĆࠞࣃဿೋɈ࠲ᇦĪඐຎć鄧གဦī
ş2/4/2/4/āঈાᆵ੠ޮɅ࠲ɩɥॸ࢞ଞɈᄜߠĪࣷນூྷīຄࢶ๝ᆵဏ๿൦‫ێ‬ঈાᆵཡ๝ஒɈૢঠɅɢɤĂဏ๿ॻȤɢɍຄ໲ႨɈঢ়ཱྀ‫ڱ‬Ȧၪଗ༑ɅɢȽɀܸಹȯɦȹঈાᆵ੠ޮɉĂࣷൣဦცɈࡊྉɬૅȢɥ‫ߔݨ‬โඪૻɈ౺દɬඐȠॸ࢞ଞɅɂȽɀࠡ‫ݿ‬ɁȧɄȞૢ௣ɁȜɥăࠞࣃɅ࠲ɩɥ‫ߔݨ‬ଞɈᆏ௲ɂȱɀɉၪଗ౯ဘଋɈʹʃʣʒʸॸ࢞ĪູɅၪଗ౯ဘଋ‫ھ‬਄Ʌ࠲ɩɥ‫ݻ‬൨īɂĂএ௲ɬࡊྉɂ
ȱȹ഍ਗโĂၟߣโɄဌ࣓ૅ‫ܧ‬ɈෂɁ‫ߔݨ‬ଞɈᄜߠɬ‫ݪ‬ȹȳ໩ȾɈᆏ௲ȦȜɥă೐ଞɈᆏ௲ȥɣɉĂϱટණĪᆊટīᆔ‫ۊ‬ɅȤȫɥၪଗ౯ဘଋɈယ࿫ɂ‫ھ‬਄ʹʃʣʒʸĂϲ VBW Ʌɢɥऋ࠰ೀᆲᆎപฤɈࡳ୹ߊᆏĂɅ࠲ȳɥॸ࢞ɬ਄ȽȹăȭɈॸ࢞ߤ຦ɉʭʽĜʙʻĜĆɺĜʑĪGFīɅȤȫɥ෰ߔ੫Īʠˁˋʑʟɻʏʯ˂ʢ˂ʞɻĜīɈൿ౰ɂდಞɅ࠲ɩɥ‫ݻ‬൨ɁȜɥăঈાᆵ੠ޮɅȤȞɀɉʑʞĜʇʳ˃ʘĜȦඋɁȜɥȥɬ୼်ȱĂഽ೸โɄʑ
ʞĜʇʳ˃ʘĜɈ৭ഢɬᆅ‫ސ‬ȱĂ‫ڽ‬Ʉɥᆏ௲ɬസ୭ȱȹอ‫ڨ‬ɬ਄ȠྼᅟȦȜɥăȭɈ‫ݻ‬൨ɉ GF ो‫ކ‬ɅȤȞɀ଱ෟȳɓȧࡊႨโɄ৽ȢၫɈఀ౰Ʌਇॷȱȹă෰ߔ੫Ʌ࠲ȱɀĂණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬3127ɅȤȫɥĶࠞࣃᄎ൨Ɉএ௲ɅȤȫɥ‫ߔݨ‬ଞɂʑʞĜʇʳ˃ʘĜɈࢾລķʓʛʏʿˋĂDFSfT.SJIO ਗວˇĜʇʏʿʛʯĶࠞࣃᄎ൨Ɉএ௲ɅȤȫɥ෰ߔ੫ॸ࢞Ɉఛ๐ާķĪ21ॢǕ໲ġ21໲īɬާ੓ȱĂࡼሄɬఠɛȹă― 33 ―

ş2/4/2/5/āۗᘧைᆔ‫౉ۊ‬ஃࠞ०೔‫ݛ‬Ʌ࠲ɩɥߤ຦ĪࣷນூྷĆ៤ࠀīϱ VBW Ʌɢɥູฤެᅰ౺ဘĶʢʄʀʜ˃ʦʊɼʠɾķɈ౺‫ʺۋ‬ʣʗ˂ˋʈ
ȭɈ‫ݻ‬൨ɉෂࡖो‫ކ‬ɈĶಫᅝॻɅȤȫɥ०೔Ʉ౉ஃࠞɂ౺ဘഽᅕ౯Ɉ੔౺ķĂɂ࠲ᇦȱɀȞɥă3127༃๱ɉ઀༃๱ɅۜȧറȧĂ਄౱ĆીმࢾລɁଌૈȱȹĶʢʄʀʜ˃ʦʊɼʠɾࢾລऄத੼ಱķɈɄȥɁĂVBW ɬ઴Ƚȹယ࿫ɂ౺‫ۋ‬Ɉʺʣʗ˂ˋʈɬଌૈȱȹă౰‫ݪ‬ɉۗᘧைᆔ‫౉ۊ‬ஃࠞ०೔‫ࡼޏݛ‬ɈʳĜʸʲĜʐɅ˂ˋʇĪiuuq;00
jocb.ovnb/dpn0īȳɥɂɂɜɅĂሄဦɂȱɀଲɤɘɂɛෂɁȜɥăȭɈߤ຦ɉʭʽĜʙʻĜĆɺĜʑĪGFīो‫ކ‬ɅȤȫɥʠˁˋʑʟɻʏʯ˂ʢ˂ʞɻĜɈଌএɬᄆૄȱȹॸ࢞ɁȜɥă

ూ2/4/2/5/ā!!ಫᅝॻۗᘧைᆔ‫ۊ‬Ăठ༐ರ‫ݚ‬ᆔɅȤȫɥऄதଌঅ೐ɂऄதଌ
অষɈ‫ັݭ‬ୈ၃Ɉʂ˃ʕऋෂଖణăʢʄʀʜ˃ʦʊɼʠɾɈ
౰ෳɂĂऄதষɈ੔౺ɬۜȧറȧʺʣʗ˂ˋʈෂɁȜɥăϲۗᘧைᆔ‫ۊ‬ɅȤȫɥ඾೧ஃࠞɅ࠲ȳɥॸ࢞ĪࣷນூྷĆ៤ࠀĆႥ৮౱ୃīȭɈ‫ݻ‬൨ɉෂࡖो‫ކ‬ɈĶ൤ණĽฝණृ౉ஃࠞɈ౺ൔृʍĜʫʑ࡙༑Ɉ࿎‫ݟ‬ķĂɂ࠲ᇦȱɀȞɥăۗᘧைɬɉȲɛɂȳɥ๬ીࣷਉɈဲ੍౯ᆔ‫ۊ‬Ɂɉ࿩‫܉‬ᅤ‫ݛ‬Ȧ‫ސ‬ड़ȳɓȧࠞࣃᄎ൨ɂɄȽɀȞɥȦĂȭɈᄎ൨Ʌ໩ȾɈࠫ๘ȥɣଲɤ೨ɭȺăɌɂȾɉĂۗᘧைɒɈ඾೧࿹‫ݷ‬ᆲɈ౷ߊɄધ୸ɁȜɥăۗᘧைঢை౉ଋ။೔ो‫ކ‬Ɂɉᆔ‫ۊ‬ȥɣɈ඾೧࿹‫ݷ‬ᆲɬोધȳɥȹɛɈঈඍ‫ڮ‬Ȧ৩ఛȯɦɀȞɄȞȦĂ੕ఛɈॸ࢞౰‫ݪ‬ɅࡊȿȞɀધฤȯɦȹఛȱȞঈඍ‫ڮ‬ɬᅙȞɀĂۗᘧைɒɈ඾೧࿹‫ݷ‬ᆲɬ੔ोધȱȹăȷɈय़‫ݪ‬Ăএ਄ɢɤɜ൥ȧɄ඾೧࿹‫ݷ‬ᆲȦ࢙ɛɣɦȹȦĂ਱ষɉ਄౱ɂીმɈࢾລɅɢɥఛȹɄ඾೧࿹‫ݷ‬ᆲɈધฤɂĂᆔ‫ۊ‬ൎ઄Ɉ઄ฤɬమɛɥࡊྉโɄ౰‫ݪ‬ɬຶɥȭɂȦɁȧȹĪႥ৮౱ୃĂ3128ಫᅝ൥ߔലࣞሄဦćಫᅝॻۗᘧைᆔ‫ۊ‬Ɉ඾೧࿹‫ݷ‬ᆲɈ੔ॳບīăɜȠ‫ێ‬ȾɈࠫ๘ɉĂ൤ණȥɣ‫ݭ‬ರɅࢷࢣȯɦɥ඾೧ɈᄪഗʹʃʣʒʸɁȜɥă൤ණɬਟɚඇ෿ɅીმɂࢾລɁଌঅᆔ‫ۊ‬ɬಡ඲ȱĂ౉ஃࠞĆဘଋஃࠞɅ࠲ɩɥࢼວॸ࢞ɬ਄ȽȹăණଋĂණवĂ౉ဦĂ౺ൔɈಮᄑ‫ݦ‬ȦࢾລȳɥȭɂɅɢɤĂఛȹɄ඾೧ஃࠞɼ
ʹĜʐȦຶɣɦȹȦĂ౰‫ݪ‬ɉଲɤɘɂɛෂɁȜɥă
ş2/4/2/6/āࢤཹණवూɬᅙȞȹಫᅝॻ႘ငɈ๲ණᆀᅙɈဿೋĪࣷນூྷĆႥ৮౱ୃīȭɈ‫ݻ‬൨ɉෂࡖो‫ކ‬ɈĶᇘષโණᆅ௶ၡɅɢɥࠞࣃဿೋɅ࠲ȳɥॸ࢞ķɅൎܾȳɥăۗᘧைᆔ‫ۊ‬ɬൎ௣ɂȱɀĂ఻ബപూĪ2991༃ਰīĂࢤཹණवూĪ2:11༃ਰ‫ڬ‬ਏīĂဴधଖణĪ2:58༃ਰīĂऋෂଖణɺĜʃɼʮĪ2:71༃ਰ‫ڬ‬ਏīɬණᆅ௶ၡʏʑʞʸɁʟĜʗʱĜʑ‫ݛ‬ȱĂණ‫ۊ‬ɈဿೋɈ‫ސ‬಑ɬ‫ݢ‬༑ɂȱȹăູɅĂऋෂଖణɉ TgN.
NWT ࡳ୹ɬᅙȞɀĂʂ˃ʕ‫ݛ‬Ɂȧɥȭɂɬଌ௠ȱĂఛȹɄࠞࣃ‫ސ‬಑ʜĜ˃Ɉߤᅙ౯ɬ൱Ȟȹă౰‫ݪ‬ూ࿍ɉĂ3127༃21ॢ3:ġ41໲Ʌާ੓ȯɦȹۗᘧைᆔ‫ࣃࠞۊ‬ĆൌঅʭɿɺĪ଱੓ćಫᅝॻīɅȤȞɀʮĜʑ๐૲ȱĂණూɬ‫ގ‬ȱȹીმɂɈৄᆔɬూȽȹă― 34 ―

ూ2/4/2/6/āಫᅝ൥ߔʮĜʑɅȤȫɥᅕęɄ଱൨ూ௶ၡɈ๐૲

ş2/4/2/7/āVBW ˂ʺĜʠʓˋʏˋʈɅɢɥ౉‫ے‬౺‫ʺۋ‬ʣʗ˂ˋʈĪࣷນூྷĂ๜ෂऱĂ៤ࠀīȭɈ‫ݻ‬൨ɉෂࡖो‫ކ‬ɈĶࣷಞ଴ၭɅɢɥʂˋʟʶˋʡĆ˂ʺĜʠʓˋʏˋʈķɂ࠲ɩɥăVBWĂȭȭɁɉˁʐʋˋ๝຦ʶ˃ʙʋʯʗĜĂɅʃʹˁĂʓˋʍĜɬ຃੪ȱĂ౉‫ے‬Ɉ౺‫ʺۋ‬ʣʗ˂ˋʈɬ਄ȠȭɂɅɢɤĂϱൣ೿ȧ౉ိ౼๱Ɉߊ໻Ăϲ౺‫ۋ‬ɚɣĂϳฃྠ૪ࡖɈड़ฤĂϴʗˋʩʇଋ࠸ᄵᆲైฤĪ఍ჍఫඣīĂϵେᆲᅅപĂ϶๵ညᅅപĂຑɅᆀᅙɁȧɥࡳ୹ɬߊᆏȯȵȹăȭɈࡳ୹Ɉএ௲ɒɈଌകɉĂ୑๜ॻĂఛߟॻĂ੹࣢ॻĂಫᅝॻɁ਄ȞĂఛߟॻĂ੹࣢ॻɁɉ VBW ˂ʺĜʠʓˋʏˋʈɅɢɥ౺‫ʺۋ‬ʣʗ˂ˋʈɬ਄Ƚɀ౺દȱȹဴɅĶ๏૗ɈဴĪɀɭȱɈɘȞīķĂĶɃɧĜɭဴķɂშ࿥ȫĂ࿥‫ݟݡ‬ඩɬ࿥ȫɀྀ༸ȳɥȭɂȦɁȧȹă୑๜ॻĂఛߟॻɁɉຄ৉
์৙Ī߰īĂࣸ‫ۈ‬๱ᆲਅĪ߰īɂɈࢼວॸ࢞ɂȱɀଌૈȱȹăɘȹĂಫᅝॻɅȤȫɥ౉‫ʺے‬ʣʗ˂ˋʈɉಫᅝॻ
༔ᆹ഍ਗॸ࢞ʓˋʗĜɂɈࢼວॸ࢞Ɉ౰‫ݪ‬ɁȜɥă

ూ2/4/2/7/ā!!VBW Ʌɢɤोപȱȹʋʏʪʃ˂၎௲ĪಫᅝॻīɈ OEWJ ɂĂණ௫ोപɅ
ɢɥ౉‫ے‬౺‫ۋ‬ʩˁʹĜʗɈࡠಣဿ‫ݛ‬ăǏ༃࠰Ʌɩȹɥ VBW ˂ʺĜʠʓˋʏˋʈɈ౰‫ݪ‬ɅɢɤĂ౉‫ے‬੝༱ૅ‫ܧ‬Ɉ଴ஏɬߊᆏȯȵɥȭɂȦɁȧȹă

ş2/4/3/2/ā!!఍ᆧ‫ڤ‬೔။௩ɬᄆૄȱȹ࡜েဿ຦ไܾ઄ɂȱɀɈ༔ࣞ။ঃɅȤȫɥഹޮ࿎‫ݟ‬଴ၭɈ৭භɂଜ‫ޏ‬ଌകĪႨࣕಫ୽ī
࡜েဿ຦ɞ૵೓੠ޮɄɃɅɢɥ఍ᆧ౺દᆲɈঌவɅൎȳɥไܾĆൎܾ઄Ɉ઄ฤɉĂಪమਡĂ๫௫ਡɬᄎɩȴ਒Ȟ࠲ఘૢɁȜɤĂࡇ࡙ൎ઄ɂȱɀɈ఍ᆧ‫ڤ‬೔။௩Ȧ࢙ɛɣɦɀȞɥă఍ᆧ‫ڤ‬೔။௩Ɉ˂ʑʇɉฝ‫ۀ‬๱ණ‫ۊ‬Ɂɢɤ൥ȧȞȭɂȦၡਠȯɦɀȤɤĂɼˋʡʥʏɺ౱࿬ɉĂ࡜েဿ຦Ʌൎȳɥಊଯ౯ɂ࢖ॗɄఱ৏ഝ‫ݡ‬Ɉࠫ๘ȥɣĂ఍ᆧഝદɈȹɛɈ૩റโɄ౺દࠣᆅʏʑʞʸɈ৭භɂࣅ‫ݛ‬ɬਡ‫ݦ‬ᄆ࿈ɂȱɀऻȬɀȞɥăȭɈɢȠɄ༬ाɅൎȳ― 35 ―

ɥਡ੫โɄ຦৐ɂȱɀĂ༔ࣞ။ঃɈຩ໴ɂ࿱࢒ȦȜȬɣɦɥă༔ࣞ။ঃɉĂGBP Ȧฤࡹȳɥ఍ᆧ‫ڤ‬೔။௩ɈǐႨɈ෈ɈɌɂȾɁȜɥĶTubcjmjuzķɈതჶɬඐ။ȳɥଜ‫ޏ‬ɼˋʭˁɁȜɥă༔ࣞ။ঃ౫๱ɈᄆโɉĂ࡜েဿ຦Ʌ
ɢȽɀିȫɥେߋɈʘʹĜʐɬॎঌȱ༔‫ݦ‬ȦॅറĆ૩റโɅ༔ࣞ౺દɬɁȧɥɢȠૅ‫ܧ‬ȳɥȭɂɂວ૪ɅĂਡ‫ݦ‬ɂȱɀਡმɈȹɛɅ။௩ȱɄȫɦɊɄɣɄȞ఍ᆧɈߊ။ĂദȻ఍ᆧ‫ڤ‬೔။௩ɈଌএɅࡍᅇȳɥȭɂɁȜɥăႨ‫ݻ‬൨ɉĂ࡜েဿ຦Ɉไܾ઄ɁȜɥ༔ࣞ။ঃ౫๱Ɉ૚਄โଲɤ೨əɬާ઻ȱȹɼˋʡʥʏɺɬൎ௣ɂȱɀĂ။ঃ౫๱Ɉෂ߇ɂɄɥഹޮ࿎‫ݟ‬ɬৌᆎโɅଌૈȳɥȹɛɈఛȱȞഹޮ࿎‫ݟ‬଴ၭɬߊᆏȳɥȭɂɬᄆโɂȱɀȞɥăᄆโൿ౰ɈȹɛɅĂĪǍī౉‫ے‬ɈࠍɊȾޮĂ࿒්ޮĂ౉ޮɬഹޮ࿎‫ݟ‬ൎ௣੠ޮɂȱɀĂ‫ܒ‬౳ĂVBWĂHJTĂଌപ෮ੈʟĜʗɄɃɈऋ࠰௶ၡɬऄ઴ȱȹࢊࠫโĂৌᆎโĂঢ়‫ۊ‬โɅഹޮ࿎‫ݟ‬ɬଌૈȳɥ଴ၭɈߊᆏĂĪǎīএ਄။
ঃ౫๱ɂఛȱȞഹޮ࿎‫ݟ‬଴ၭɈຕਗɂଜ‫ޏ‬ଌകĂĪǏīഹޮ࿎‫ݟ‬଴ၭɈ‫ۿ‬ᅙȤɢɍ‫ޜ‬ᆯɅྼᅟɄ௶ၡࡊྉɈ౲ྩĂĪǐī࿎‫ݟ‬଴ၭɈާཡȤɢɍ‫ۿ‬ᅙɅ࠲ȳɥʅʻʩʏʞɻĆʟɻʱ˅ʯʹˋʠɬ਄ȠăȭɦɅɢɤĂɼˋʡʥʏɺ
ɅȤȞɀ࡜েဿ຦ɅɢȽɀ౺Ȳɥ༔ࣞ౺દଞɈॄ੟โഹޮȦॎঌȯɦĂ༔ࣞ౺દɈૅ‫ܧ‬ൌ౫ȦߊᆏȱĂ఍ᆧ‫ڤ‬೔။௩ɈଌএɅࡍᅇȳɥăႨॸ࢞ɉĂI39༃๱ KTU0KJDB ණ࢝ࡤჹ‫ݻ‬൨ൎܾਡ੫‫ࢾ୹ࡳߔݨ‬ᆵʯ˅ʈˁʸĪTBUSFQTīɅ௸ॣ࿥ȧੜ൰ȯɦĂS0E ำय़ষɈ I3:༃๱ȥɣ౷ૺާ઻ă

ş2/4/3/3/āɼˋʡʥʏɺɅȤȫɥ౉‫ے‬౺દᆲɈණ‫ູۊ‬౯ɂ౉ࠣᆅ଴ၭɈ࠲बĪႨࣕಫ୽īႨॸ࢞Ɂൎ௣ɂȱȹɼˋʡʥʏɺɁɉĂఱ৏ഝ‫ݡ‬Ʌɢɥ఍ᆮ୅ᅟɈ߄൥Ă࡜েဿ຦Ʌɢɥ੼ဘ౺દ౯Ɉฝ‫ݚ‬ȦᅅപȯɦɀȞɘȳă‫ࢦݿ‬Ʌɜਡ໘Ɉ౺દ௻࣍ɅɢȽɀౘ୥჈ʠˋȥɣౘ࿄჈ʠˋɈʋʹɈᄪ໴ɬ਄ȽɀȤɤĂ਱ষɈ఍ᆧɈ‫ڤ‬ฤ౺દɂഝદȦ‫ݻ‬൨ɂɄȽɀȞɥăႨॸ࢞ɁɉĂKJDB Ɉ൥ࡤჹុឺʯ˅ʐɿʇʠȦଌૈȯɦɀុឺɈ౲ྩȦమɭɁȞɥಀʐʻˇɈණ‫ۊ‬ɂĂʨ˂๿຾૵Ɉ౉ࠣᆅ೨ਗĪʑʨʛʇīɅɢɤុឺ౉ᇭȦ౲ྩĆ‫ڿ‬૩ࠣᆅȯɦɀȞɥණ‫ۊ‬ɬൎ௣ɂȱɀĂණ‫ູۊ‬౯Ɉ྘ߏɬ਄Ƚȹă‫ܒ‬౳‫ކ‬ജȥɣ౉‫ے‬Ɉ౺દᆲɬైฤȱĂǎȾɈණ‫ۊ‬ɬ྘ߏȱȹय़‫ݪ‬Ă౉ࠣᆅ଴ၭɅɢɤ౺દᆲɈऋ࠰ယ࿫Ʌ‫ۅ‬ȞȦߊ໻ȯɦȹă൥ࡤჹុឺࣾ‫ۊ‬Ɂɉ၎௲ȮɂɈɊɣȾȧȦ൥ȧȩĂ‫ݚ‬ᆔതɈେᆲȦฝȩɄȽɀȞɥभ৐ȦॽɣɦȹăȭɦɘɁɅĂ‫ݚ‬ᆔതɈ౉๜ɘɁࣧຑɅ౉Ȧ਄ȧ๧ȽɀȞɄȞȭɂȦૄ฾ȯɦȤɤĂ౉࿤ഫɅɢɤ౺દᆲȦฝ‫ݚ‬ȱɀȞɥȭɂȦ৽Ȣɣɦȹă‫ێ‬ၫĂʑʨʛʇɅɢɥុឺࣾ‫ۊ‬Ɂɉ၎௲ȮɂɈɊɣȾȧȦழȯȩĂ‫ݭ‬ರɬࣃɅ౺
દᆲȦ‫ڽ‬ɄȽɀȞɥभ৐ɬߊ໻ȱȹă౉ࠣᆅȦ่ฦȯɦɀȤɤĂុឺʈ˃Ĝʯ໘Ɂɉ౉Ȧ৊ိɅယ༯ȯɦɀȞɥȦĂុឺʈ˃ĜʯȮɂɅ౺દᆲɅੇȦɁɀȞɥȭɂȦైઍȯɦȹăএ੭Ă੝༱ࠣᆅ଴ၭɈ‫ޜ‬೑઄ɬอ‫ڨ‬ȳɥȭɂɬ੕୒ᄆ࿈ɂȱɀĂȭɦɣɈय़‫ݪ‬ɬຝɘȢɀȯɣɅ‫ސ‬಑ɬమɛɀȞɥă

― 36 ―

ȮˎŞȁ‫ވ‬൳၌ဥࡄ‫ݪ‬ĳįĲįġġ‫ވ‬൳၌ဥࡄ‫ٽݪ‬ါȁ୷ဩఱ‫ޏ۪ڠ‬ςκȜΠΓϋΏϋΈࡄ‫ݪ‬ΓϋΗȜȪńņœŦŔȫ
͉́Ȃ౷‫̳ͥ۾ͅޏ۪ݩ‬ςκȜΠΓϋΏϋΈܿ੅͈‫ܖ‬ய͂؊ဥࡄ‫ͬݪ‬ಎ૤ͅȂ‫ވ‬൳၌ဥȆ‫ވ‬൳ࡄ‫ݶݪ‬ത̱͂̀ςκȜΠΓϋΏϋΈ۪ͥ͢ͅ‫͈ݪࡄޏ‬อജȂńņœŦŔ ͈ঔ୭Ȇ୭๵͞਋૞Ȇਓਬ̱̹‫ିמ‬ΟȜΗȆ۪‫ޏ‬ΟȜΗ͈ခ࢘၌ဥ͈̹͛ͅȂఱ‫ڠ‬Ȃ̷͈ఈ͈ࡄ‫ͅ۾ܥݪ‬ਫ਼௺̳ͥࡄ‫ݪ‬৪͂൚ΓϋΗȜ͈ࡄ‫ݪ‬৪̦‫ފ‬ႁ̱̀‫ވ‬൳၌ဥࡄ‫ͬݪ‬ଔૺ̱̞̳̀͘ȃࡄ‫ݪ‬ਅ༆͉ȂίυΈρθࡄ‫ݪ‬Ȃཀٔഎ̈́ඤယ͜‫ࡄ๊͚֚܄‬‫ݪ‬Ȃࡄ‫ݪ‬ٛȂ̤͍࣭͢ष‫ވ‬൳၌ဥࡄ‫ͅݪ‬໦̥̤ͦ̀ͤȂఱ‫ܨ‬Ȃକ੏۪Ȃ૒୆Ȃ૙ၳȂब‫ିמ͈̓̈́ٺ‬ΟȜΗ͈ٜଢ଼͞ັଟ̳ͥ౷ષ۷௶ࡄ‫ݪ‬൝͈໙ࢩ̞ΞȜζ́ࡄ‫ͬݪ‬৘ঔ̱̞̳̀͘ȃࣽාഽ͉ȂΓϋΗȜ̦ଔૺ̱̞̀ͥȶ୶౤ςκȜΠΓϋΏϋΈίυΈρθȷȂȶ౷‫ݩ‬ນ௄ૂ༭ൡࣣίυΈρθȷȂȶ‫ିמ‬၌ဥࣞഽ‫ا‬ίυΈρθȷ͂ࡄ‫ݪ‬ਬٛͅ‫̢̀ح‬Ȃ‫ވ‬൳၌ဥࡄ‫ͬݪ‬೒̲̀ࡄ‫ݪ‬ΙȜθͬࠁ଼̱Ȃఱ߿ထॳ૭୏Ȇ‫ڕ‬ං̬̭̾̈́ͥ͂ͬͅ࿒എͅȂˏ͈̾ਹത‫ه‬ఴȶ୶౤ζͼ·υ෨ςκȜΠΓϋΏϋΈȷȶ͌ͩͤ͘˔İ˕࣢ΟȜΗͬ‫ڰ‬ဥ̱̹ςκȜΠΓϋΏϋΈ਀༹͈‫ٳ‬อȷȶΡυȜϋͬ‫ڰ‬ဥ̱̹߃୪ςκȜΠΓϋΏϋΈȷͅచ̳ͥ‫ވ‬൳ࡄ‫͈ݪ‬༡ਬ࣐̞ͬȂĵĹ࠯͈‫ވ‬൳၌ဥࡄ‫ݪ‬Ȃ‫࣭͈࠯˔͍ݞ‬ष‫ވ‬൳၌ဥࡄ‫ݪ‬ȪέͻςάϋȂͼϋΡΥΏͺȂαΠ΢θȂ΂ȜΑΠρςͺȂༀ࣭Ȃಎ࣭ȫ̦৘ঔ̯̱̹ͦ͘ȃȁ̹͘Ȃ‫ވ‬൳ࡄ‫ͬض଼͈ݪ‬อນ‫ૂ͍ݞ‬༭࢐͈۟ા̜́ͥలĲĺٝ ńņœŦŔ ۪‫ޏ‬ςκȜΠΓϋΏϋΈΏϋεΐ;θ͉ȂĳıĲĸාˎ࠮Ĳķ඾ͅ୷ဩఱ‫̧̫͞ڠ‬ٛ‫ٳ́܁‬ट̯̱̹ͦ͘ȃࣽාഽ͉Ȃˏ͈̾ίυΈρθࡄ‫۾ͅݪ‬Ⴒ̱̹Ĳķ࠯͈࢛൮อນ͂ĳĹ࠯͈εΑΗȜอນ̦࣐ͩͦȂķķྴ͈४‫ح‬৪̦ͣ෎૤݈ͅაͬ࢐̱̱̹ͩ͘ȃȁո‫͉ئ‬Ȃ࣭ඤ‫࣭͍ݞ‬ष‫ވ‬൳၌ဥࡄ‫͈ݪ‬न఼࠯ତඤ࿫ȪນˍȫȂ̹͘‫۾ܥ‬༆ͅ໦႒̱̹ນȪນˎȫ̳́ȃນˍȁ໹଼ĳĹාഽ‫ވ‬൳၌ဥࡄ‫ݪ‬न఼ඤ࿫࣭ඤȪĵĹ ࠯ȫ‫ވ‬൳ࡄ‫ݪ‬ਅ༆࣭षȪ˔࠯ȫ

ࠗ૧ܰࡄ‫ݪ‬

ࠑ௽ࡄ‫ݪ‬

૧ܰࡄ‫ݪ‬

ࠑ௽ࡄ‫ݪ‬

ίυΈρθˍȪ‫͚܄‬ਹത‫ه‬ఴȫ

Ĵ

Ĳı

ĳ

ĳ

Ĳĸ

ίυΈρθˎ

ĳ

Ĵ

ı

ı

Ķ

ίυΈρθˏ

Ĵ

ĵ

Ĵ

Ĳ

ĲĲ

ίυΈρθˍȂˏ‫۾‬Ⴒ

Ĳ

ı

ı

ı

Ĳ

๊֚ࡄ‫ݪ‬

ĸ

ĲĲ

ı

ı

ĲĹ

ࡄ‫ݪ‬ٛ

Ĵ

Ĳ

ı

ı

ĵ

ࠗ

Ĳĺ

ĳĺ

Ķ

Ĵ

Ķķ

ນˎȁ໹଼ĳĹාഽ४‫۾ܥح‬ତȪయນ‫ݪࡄ͍ݞ‬໦౜৪͈ਫ਼௺‫۾ܥ‬ȫ‫ߊ۾ܥ‬໦

४‫۾ܥح‬ତ࣭࢖ၛఱ‫ڠ‬Ȫࣞ୺‫͚܄‬ȫĴĶȪඤ୷ဩఱ‫ڠ‬໐ޫˏ࠯ȫজၛఱ‫ڠ‬

Ĳĵఱ‫ވڠ‬൳၌ဥ‫૽༹۾ܥ‬Ĳ

ඊၛ࣐ଽ༹૽൝࢖എࡄ‫۾ܥݪ‬

Ĳı

ྦྷ‫۾ܥۼ‬

Ĳĳ‫۾ܥ࣭ٸ‬

ĲĵࠗĹķ

― 37 ―

ĳįĲįĲįġ‫ވ‬൳၌ဥࡄ‫هݪ‬ఴ֚။ȪĵĹ࠯ȫ
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૧ܰ
ȟ
ࠑ௽

Ĳ

ࠑ௽

ĳ

ࠑ௽

Ĵ

ࠑ௽

ˏষࡓΟȜΗͬဥ̞̹૩ႅΨͼ΂ζΑ঩ ခٖȁ֚ࢩ࡙΀ΥσΆȜ၌ဥ‫خ‬ෝၾଔ೰ֳസ‫ݠ‬ఱ‫ڠ‬෠‫ڠ‬໐‫ح‬൥ȁȁࡐ౷ષτȜΎࠗ௶௡౾

ĵ

૧ܰ

߬ࡔȁဈঃ
୆‫̫̤ͥͅ࠷ޏ۪ڰ‬ńŐˎෛഽ͈ࠗ௶͂
֟ઽఱ‫֖ࢩڠ‬କ࠷۪‫شޏ‬࠿બ‫ݪࡄ֗ޗڠ‬ΓϋΗȜ‫ݛ‬ଲȁࢤྶȁĶࠑ௽‫ݛ‬ଲȁࢤྶ

ট‫ٸ‬Ȃ‫خ‬ণȂ߃୤‫ٸ‬໦࢕࢕ഽࠗ͂
฽ৣ௶೰௡౾ķࠑ௽ུఉȆ‫ࡔک‬สώ‫ڡ‬૩ႅ۷௶ΗχȜ‫ݛ‬ଲȁࢤྶ

ȁ‫ݛ‬ଲȁࢤྶ

œŢŮŢρͼΘȜȂŉŔœōȂ౷ષࠗ௶௡౾͈͂൳শ۷௶̷͈͂ΟȜΗఱஜȁࢤგ‫ڼ‬৆ٛ২ΓϋΞϋΏͺπ΍έ͹ΛΠΡυȜϋ઀‫ـ‬გȁࢤ෗‫ڼ‬৆ٛ২ΫΐοϋΞΛ·‫ح‬൥ȁȁࡐ౷ષτȜΎ௶ၾ‫֚ܕܥ‬৆ȂłųŤňŊŔ

ࡄ‫هݪ‬ఴ

ࡄ‫ݪ‬యນ৪̤͍͢ਫ਼௺

‫࢓ܨ‬κΟσତ౵৘ࡑࠫ‫ିמͥ͢ͅض‬ί ૩५ȁٗဎυΘ·Π൵੄ͺσΌςΒθ͈࠿બಿॄఱ‫ڠ‬ఱ‫شݪࡄڠࢥ֭ڠ‬அ୼ȁ౺ࢬฒ૗࢕τȜΎȜͬဥ̞̹‫أ‬৒࢘‫΄ض‬࢖‫़ף‬౬༹૽τȜΎȜܿ੅Α͈ࠗ௶༹͈‫ٳ‬อ௙ࣣࡄ‫ݪ‬ਫ਼ͺͼΑͺσΐȜ͈ςκȜΠΓϋΏϋΈ਀ ಱߨȁࢫং༹͈‫ٳ‬อ
൐‫ނ‬෠ުఱ‫ڠ‬୆໤ॲު‫ڠ‬໐૩ႅ͈ඵ༷࢜଻฽ৣၚ৘௶ΟȜΗ͂Ώ ઐ५ȁဢηντȜΏοϋκΟσͬဥ̞̹‫ ିמ‬ਉസఱ‫ڠ‬൐‫ނ‬സঌ۪‫شݪࡄڠشޏ‬฽ৣၚ͈࠿બ৘ࡑ

చ؊‫֥ޗ‬‫ވ‬൳၌ဥΟȜΗȆ୭๵ུఉȁ‫ྶد‬୷ဩఱ‫ڠ‬௙ࣣιΟͻͺ‫ܖ‬๕ΓϋΗȜࣞ௸‫ॳ׵‬΍ȜΨȪŔœĲķıııȫ

‫ݛ‬ଲȁࢤྶ

໦࢕‫ܕ‬

ĸ

ࠑ௽

࿐‫ئ‬ȁ‫ୃܮ‬࢕‫דڠ‬௨ȆτȜΘȜΟȜΗȆ‫ْିמ‬௨ΟȜ ৅঱ോఱ‫ڠ‬‫ڠ֗ޗ‬໐‫֗ޗ‬৘க௙ࣣΓῌͥ͢‫غ‬५໨‫͈׸‬൲ఠٜଢ଼
ϋΗȜ

Ĺ

૧ܰ

ট‫ٸ‬ρζϋρͼΘȜͥ͢ͅచၠ࠷΀ͺυΖఆ५ȁ၌ࢨσ͈࢕‫ڠ‬എ଻ৗ‫͍ݞ‬କ૊‫۾ͅޣגܨ‬൐‫ނ‬٬ဢఱ‫֭ݪࡄ੅ڠڠ‬̳ͥࡄ‫ݪ‬

ĺ

ࠑ௽

Ĳı

૧ܰ

ĲĲ

ࠑ௽

ಎႹȁో჊
ζσΙΓϋΏϋΈͥ͢ͅਏ‫ࢹۍ‬௮ࠗ௶ཤ٬ൽఱ‫ڠ‬ཤ༷୆໤࠷
༹͈‫ٳ‬อ
έͻȜσΡ‫ڠش‬ΓϋΗȜུఉȆ‫ࡔک‬สώ‫ڡ‬૩ႅ۷௶ΗχȜ

Ĳĳ૧଼ࣣܰ‫࢛ٳ‬τȜΘ۪ͥ͢ͅ‫ ̳۾ͅ௶ࠗޏ‬৹ႅȁဉ෗ͥࡄ‫ݪ‬඾ུఱ‫ڠࢥڠ‬໐π΍έ͹ΛΠ
ུ‫ޡ‬ȁ୷੉
‫ح‬൥ȁȁࡐŎŐŅŊŔΟȜΗȂζͼ·υ෨ഥเ௶೰ΏΑΞθȂņŏŗŊ

ĲĴ

ࠑ௽

ౘֵȁဢٚ
ňŐŔłŕ͂ఱ ‫ ܨ‬࿶ ௣ κ Οσͬဥ ̞̹‫ܨ‬ય಩‫ܨ‬યࡄ‫ݪ‬ਫ਼٬ဢȆńŐˎȆńŉː͈ෛഽ་൲͈ٜଢ଼
౷‫ݪࡄڠاݩ‬໐

᠟൥ȁંঊ

ȁ

Ĳĵ

ࠑ௽

‫ିמ‬ΟȜΗͬ၌ဥ̱̹చၠ࠷Ȇ଼௄࠷ ࢺ࢛ȁऴ༠͈໤ৗ࿶௣ً೾ͅ‫ݪࡄ̳ͥ۾‬߇ਗఱ‫ڠ‬؊ဥႁ‫ݪࡄڠ‬ਫ਼᠟൥ȁંঊ୓গ‫ܨ‬ય‫ିמ‬ΟȜΗȂޭܴൽȂਔܴٝൽ‫ିמ‬ΟȜΗȂठٜଢ଼ΟȜΗ૧ܰ΃ΠςȁίρΟͻȜίŔŌŚŏņŕ ۷௶΀ͺυΖσΩριȜΗ͈൐ཤఱ‫ڠ‬ఱ‫֭ڠ‬ၑ‫شݪࡄڠ‬ࢋओບ‫͂ث‬ٜଢ଼ΏΑΞθ͈ࣞഽ‫ا‬ఱ‫ܨ‬٬ဢ۷௶ࡄ‫ݪ‬ΓϋΗȜවࢺȁ૾আΑ΃ͼρΐ΂ιȜΗȜȪŔŌŚŏņŕȫ
Ȃ΍ϋγΠιȜΗȪłņœŐŏņŕȫͥ͢ͅ΀ͺυΖσ͈ΟȜΗȂ඾ৣࠗ۷௶
͈඾ৣၾȪ஠ഛȂ८၄ȂೄోȫΟȜΗȂζͼ·υ෨۷௶͈କ૊‫ܨ‬ΟȜΗĲķࠑ௽ૼबশ͈ೋ෨ஸષब‫ྵ૽̫̤ͥͅٺ‬ς
Α·͈ບ‫ࡘ͂ث‬बచॐ߄ঊȁఱඵ჊
ȡ૰ජ୼ࡇ٬‫͈֖܅‬ೋ෨ஸષ̤̫ͥͅब ‫ڼ‬৆ٛ২ီ۪ۜ‫ޏ‬κΣΗȜ‫৻ٺ‬৪͈අ଻ȡπ΍έ͹ΛΠ

ȁ

Ĳĸ

ࠑ௽

ĲĹ

ࠑ௽

Ĳĺ

૧ܰ

ĳı

ĲĶ

ńőĮŔłœ ࠿બဥ Ŗłŗͅ൏श̳ͥ‫غ‬५΄ΑΓϋ΍͈‫ٳ‬อࡄ‫ݪ‬Ȫˏȫ࢕‫ڠ‬৆Γϋ΍‫ٳ‬อٜࣞ௨ഽ౷ࠁȆ૒୆ΟȜΗͬဥ̞̀০
࿂༲ٟͬထ౶̧̥́ͥȉ்୼ȁဉᄏ൐‫ނ‬ఱ‫ૂۼߗڠ‬༭‫ݪࡄڠش‬ΓϋΗȜ‫߃ֲޡ‬ȁ‫૳ם‬൐‫ނ‬ఱ‫ڠ‬୆ॲܿ੅ࡄ‫ݪ‬ਫ਼ౘֵȁੳ‫ݛ‬ߗज़ဥྫ૽ΰς΋ίῌͥ͢ျ౷ْ௨
‫ڼ‬৆ٛ২Β΋ȜΏλ௙ࣣͬဥ̞̹ஃ᠒ߊ֖͈ಒ੄
‫ݪࡄڠش‬ਫ਼५ॄȁ໲ဎུ‫ޡ‬ȁ୷੉

ȁ૧ܰ࿡‫ْିמ࢕ۼ‬௨̤͍͢ ňŊŔͬ၌ဥ̱̹ ઐ࿤ȁణ࿟ଲ‫͈ٮ‬ளऺΑΠΛ·͈ଔࠗ୷ဩఱ‫ڠ‬ఱ‫شݪࡄڠࢥ֭ڠ‬५ॄȁ໲ဎ౷ၑૂ༭ΟȜΗଲ‫ٮ‬ΈυȜΨσാ౷๭ໞȂłųŤňŊŔĲıȂņŏŗŊ

ĳĲ૧ܰΏηντȜΏοϋκΟσ͂ςκȜΠΓϋུ‫ۼ‬ȁࣝܲ
ΏϋΈͬဥ̞̹କ֞୆ॲၾଔ೰༹͈࠿
൐ཤఱ‫ڠ‬ఱ‫֭ڠ‬෠‫شݪࡄڠ‬൦ུ‫ޡ‬ȁ୷੉

ņŏŗŊ

ĳĳ

ࠑ௽

ఱᚧȁࣞࢼ
Ψςോ̤̫ͥͅĳıĲĶා͈΀σΣȜΣο ;Θμ΢ఱ‫ڠ‬٬ဢ‫ڠش‬ςκȜΠΓϋΏϋΈࡄ‫ݪ‬Γϋ࡛યͤ͢ͅ෠ު͈ۙ͊̾‫ޣג‬ΗȜུ‫ޡ‬ȁ୷੉

ȁ౷ષτȜΎ௶ၾ̤͍͢ ŔŧŎ ఉণതৢ૯௶ၾͥ͢ͅ૩ႅඤ໐͈౷ࠁȆ૒୆ࠁેࠗ௶਀༹͈‫ږ‬ၛςκȜΠΓϋΏϋΈͥ͢ͅুடब‫͈ٺ‬๭‫ٺ‬෤՜

― 38 ―‫ح‬൥ȁȁࡐ౷ၑૂ༭ΟȜΗαȜΑȂ౷ၑૂ༭ΏΑΞθȂςκȜΠΓϋΏϋΈْ௨ੜၑΕέΠ;Ϳͺ๭ब౷ͬ۷௶̱̹‫ْିמ‬௨͞ŅņŎȆْ௨ٜଢ଼ΕέΠ൝

๔࣢

૧ܰ
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ĳĵ

ĳĶ

ĳķ

ࡄ‫هݪ‬ఴ

ࡄ‫ݪ‬యນ৪̤͍͢ਫ਼௺

చ؊‫֥ޗ‬ཪȁٗࢫŖłŗ ْ௨ͬဥ̞̹କ͈֞୆֗‫ۯ‬ၑͅ൐ཤࢥުఱ‫ڠࢥڠ‬໐۪‫ޏ‬‫ݪࡄ̳ͥ۾‬΀ΥσΆȜ‫شڠ‬ུ‫ޡ‬ȁ୷੉

ȁπ΍έ͹ΛΠ

ŖłŗȂْ௨ٜଢ଼ΕέΠ;Ϳͺ

߃൥ȁ઎຃

ȁ

π΍έ͹ΛΠ

ഩ෨ྫ‫ޣ‬৒Ȇζͼ·υ෨ഥเ௶೰ΏΑΞθȆࣞਔ෨ٝႹȆഩ෨ΏηντȜΗ‫ݛ‬ଲȁࢤྶ

ఱ‫ܨ‬۷௶௡౾

වࢺȁ૾আ

ࠗॳ‫ܥ‬

‫ݛ‬ଲȁࢤྶȁ๳࢛ȁඈ঎ఉ෨ಿζͼ·υ෨༶ৣࠗΟȜΗȂ‫ڎ‬ਅ࡛౷۷௶ΟȜΗ

ဠȁȁȁռ

ȁ

వ࿤ȁຮྶ

ȁ

ུఉȆ‫ࡔک‬ŖłŗȪŔőŊŅņœȫ

වࢺȁ૾আŔŌŚŏņŕΟȜΗ൝͈౷ນ࿂۷௶ΟȜΗ઀߿ ŖłŗȪྫ૽࣎ߗ‫ܥ‬ȫ͂ŔŧŎĮŎŗŔ
ȪŔŵųŶŤŵŶųŦġ ŧųŰŮġ ŎŰŵŪŰůġ Ţůťġ ŎŶŭŵŪġ᠟൥ȁ૾ࠑ௽ ŗŪŦŸġ ŔŵŦųŦŰȫৢ૯௶ၾͬဥ̞̹০࿂
‫۾‬൐‫֭ڠ‬ఱ‫ࠐڠ‬फ‫ڠ‬໐༲ٟ౷͈౷ࠁ་‫͂ا‬૒୆་‫ا‬ಒ੄ͅ‫ݪࡄ̳ͥ۾‬ςκȜΠΓϋΏϋΈΟȜΗͬ‫ڰ‬ဥ̱̀ ‫ؖ‬നȁ૞࣐ࠑ௽ ηΜΨΙ͈୆௳Ȇ୆֗ߗ‫͈ۼ‬໦ଢ̷଼͈ ‫ڼ‬৆ٛ২΂σΠസঌ۪‫ࡄޏ‬
‫ݪ‬ਫ਼
ĵ
ඳ෨ȁ֚ܵ
଼ࣣ‫࢛ٳ‬τȜΘ൏शζͼ·υ‫ ିמ‬ဥ୷ဩఱ‫ڠ‬ఱ‫֭ڠ‬ဏࣣ‫ڠش‬ࠑ௽Ňőňł ͈‫ٳ‬อ
ࡄ‫شݪ‬
๑ாȁ஝
‫ْିמ‬௨ੜၑ͈̹͈͛༶ৣഥోκΟσგࢬஜఱ‫ڠ‬ఱ‫֭ڠ‬ၑࢥ‫ڠ‬
͈࠿બ
ࡄ‫شݪ‬
࿤࢛ȁ࣐࣪
ౝऔ‫ܥ‬ςκȜΠΓϋΏϋΈΟȜΗͬဥජၻ੫ঊఱ‫ু֭ݪࡄڠ‬ட̞̹‫ିغ‬ఱ‫ݪࡄ͈ޏ۪ܨ‬
‫ࠏڠش‬

ĳĸ

ࠑ௽

ĳĹ

ࠑ௽

ĳĺ

ࠑ௽

Ĵı

ࠑ௽

ĴĲ

૧ܰ

Ĵĳ

ࠑ௽

ĴĴ

૧ܰ

Ĵĵ

ࠑ௽

ĴĶ

૧ܰ

͌ͩͤ͘˔࣢ͥ͢ͅ૒୆‫ܬ‬୯་‫͈ا‬ಿ ઐ‫ؖ‬ȁ૯ශ‫ܢ‬۷௶਀༹͈ࢹಃ
ࣞ౶ఱ‫ݪࡄ֗ޗڠ‬໐Ĵķࠑ௽ॸள ł ΨϋΡͬ၌ဥ̱̹·υυέͻσ
௩നȁ࠲ඵࠖ࢕͈໦࢕ْ௨ࠗ௶ȇକനȆ૩ႅ͈͒୓‫ؖ‬ఱ‫੅ܿڠ‬໐
؊ဥ

Ĵĸ

ࠑ௽

ĴĹ

૧ܰ

Ĵĺ

ࠑ௽

ĵı

ĵĲ

ĵĳ

ζͼ·υ෨༶ৣࠗȄ८၄ࠗ‫͍ݞ‬ιΕ‫ܨ‬ࣝୌȁ࣪ੇયκΟσͬဥ̞̹ဢષ໓ႁ঩࡙ၾଔ೰
૰࡫ఱ‫ڠ‬٬ম‫شݪࡄڠش‬਀༹͈‫ٳ‬อ୒ၐȁგୃఉ෨ಿζͼ·υ෨༶ৣࠗΟȜΗͬဥ̞‫ܨ‬ય಩‫ܨ‬યࡄ‫ݪ‬ਫ਼ర໓ࡄ̹କ໤ৗςΠςȜΨσ͈ࡄ‫ݪ‬‫ݪ‬໐లˍࡄ‫ݪ‬৒ςκȜΠΓϋΏϋΈΟȜῌͥ͢࡮ઔ ઐ‫ئ‬ȁ໲ࠐ‫ܖ‬ய୆ॲၾଔ೰ͺσΌςΒθ͈‫ٳ‬อಆ෨ఱ‫ڠ‬୆ྵ۪‫ࠏޏ‬ুடब‫ͤ͢ͅٺ‬୆̲̹ഩၗ࠷་൲͈೰ ಎനȁဉ෗ၾഎٜଢ଼୷ဩఱ‫ڠ‬ఱ‫شݪࡄڠࢥ֭ڠ‬‫֔ז‬ȁ૞
ŖłŗςκȜΠΓϋΏϋΈ۷௶ͥ͢ͅၖ ࣭ၛࡄ‫ٳݪ‬อ༹૽٬ဢࡄ
‫ٳݪ‬อ‫ࢹܥ‬౷‫ݩ‬ນ௄໤ৗ౷ၖ५͈૒໤ਅఉအ଻͈౷଎‫ا‬੏۪ࡄ‫ݪ‬໦࿤‫ݛ‬঴ȁ୍
ŔŌŚŏņŕΟȜΗͬဥ̞̹ఱ‫͈ޏ۪ܨ‬ජၻ੫ঊఱ‫ু֭ݪࡄڠ‬ட
ࡄ‫ݪ‬
‫ࠏڠش‬

‫ވ‬൳၌ဥΟȜΗȆ୭๵ŉŪŮŢŸŢųŪĮ˔İłŉŊ ͈ΟȜΗȂŉŪŮŢŸŢųŪĮ˔İłŉŊ ΟȜΗ͈͒ͺ·ΓΑဥࠗॳ‫ܥ‬ΏΑΞθńńŅ ໦࢕‫ܕ‬ȪŐŤŦŢůġŐűŵŪŤŴġ
ŖŔŃĳıııȫȂഛఘབ‫ޢ׿‬‫ݛ‬ଲȁࢤྶ ȪŗŪŹŦůġЋĲĴıŮŮȫ
ȂۙખέͻσΗȜȪłůťŰŷŦųġճ஌ಎ૤෨ಿ
ĸķıįķĹůŮȂΨϋΡ໙ˍůŮȫ‫ࡔک‬ȁࢫং

୷ਝȁฎ‫ܮ‬΃ιρͬဥ̞̹‫ିغ‬ນ௄۪‫ޏ‬۷௶͈࠿୷ဩࢥުఱ‫ڠ‬თିౝऔࡄ‫ݪ‬൦ΓϋΗȜఉ༷࢜۷௶ΟȜΗͬဥ̞̹ૻဩਏႅȆࢩ ப५ȁങঊဩਏႅ͈໦႒༹༷͈‫ٳ‬อഛၑఱ‫ڠ‬
್ྴȁోဎྫ૽઀߿๲࣐ఘ൏शဥ ōņŅηΣρͼ୷ဩఱ‫ڠ‬ఱ‫֭ڠ‬ဏࣣ‫ڠش‬ΘȜͥ͢ͅ࿤‫ٸ‬ΘΑΠ‫ݷ‬൲۷௶ࡄ‫شݪ‬‫ݛ‬ଲȁࢤྶ

༶ৣાͬࠗॳ̳̹͈ͥ͛ΕέΠ;Ϳͺུఉȁ‫ྶد‬ȁ‫ݛ‬ଲȁࢤྶȁ૧ܰ૩ȁࢫ‫૾ݛ‬߃‫ݻ‬ၗρͼΘȜͥ͢ͅ౷ນ࿂ఱ‫௶ࠗܨ‬୷ဩఱ‫ڠ‬ఱ‫֭ڠ‬ဏࣣ‫ڠش‬ΟȜΗ̥͈ͣૂ༭ಒ੄
ࡄ‫شݪ‬π΍έ͹ΛΠ

ȁࠑ௽ŕœŎŎ শయոஜ͈஠‫ࣛݩ‬କζΛίί ਹȁં֚υΘ·Π͈দै͂ࣛକ͈‫࢓ܨ‬་൲ٜଢ଼‫ނ‬സఱ‫ڠ‬ఱ‫֭ڠ‬ၑ‫شݪࡄڠ‬๳࢛ȁඈ঎Ĳĺĺĸාոஜ͈୓গ‫ܨ‬ય‫ିמ‬ȪňŎŔˎĮː࣢ȫȆ‫ିמ‬൏शζͼ·υ෨༶ৣࠗΟȜΗȪŔŔŮİŊȫ͂ࠗॳ‫͈ܥ‬၌ဥ૧ܰŅŦŷŦŭŰűŮŦůŵġŢůťġŷŢŭŪťŢŵŪŰůġŰŧġ
ňņŏśłŏŐġŏŊńŐōł
ŢťŷŢůŤŦťġŴŢŵŦŭŭŪŵŦġťŢŵŢġŢůŢŭźŴŪŴġ
ńũŪţŢġŖůŪŷŦųŴŪŵź
ŵŦŤũůŪŲŶŦŴġŧŰųġŮŰůŪŵŰųŪůŨġŢůťġ
ȪŖůŪŷŦųŴŪŵźġŰŧġ
ŮŪŵŪŨŢŵŦġůŢŵŶųŢŭġŢůťġŦůŷŪųŰůŮŦůŵŢŭġ
ŃŢŴŪŭŪŤŢŵŢȫ
ųŪŴŬŴ

໚໐ȁ࣪ྜ

ŎŕŔłŕĮˍœĭġŎŕŔłŕĮˎ― 39 ―

๔࣢

૧ܰ
ȟ
ࠑ௽

ࡄ‫هݪ‬ఴ

ࡄ‫ݪ‬యນ৪̤͍͢ਫ਼௺

చ؊‫֥ޗ‬

໚໐ȁ࣪ྜŎŕŔłŕĮˍœĭġŎŕŔłŕĮˎĭġŉŊŎłŘłœŊĮ˔İ˕ĮłŉŊུఉȁ‫ྶد‬୷ဩఱ‫ޏ۪ڠ‬ςκȜΠΓϋΏϋΈࡄ‫ݪ‬ΓϋΗȜུఉȁ‫ྶد‬

ȁ

๳࢛ȁඈ঎

ȁ

߃൥ȁ઎຃

ȁ

‫ݛ‬ଲȁࢤྶ౷ષ΀ͺυΖσ௶೰௡౾ུఉȁ‫ྶد‬ȁĵĴ૧ܰŅŦŷŦŭŰűŮŦůŵġŢůťġűŦųŧŰųŮŢůŤŦġ
ŷŢŭŪťŢŵŪŰůġŰŧġŵũŦġŢűűŭŪŤŢŵŪŰůġŰŧġŵũŦġ
œŔŕġȪœŰţŶŴŵġŔŢŵŦŭŭŪŵŦġŕŦŤũůŪŲŶŦȫ
ġŗŢŭŦųŪŰġŕųŢŮŶŵŰŭŪ
ŢűűųŰŢŤũġŵŰġŉŊŎłŘłœŊ Į˔ŖůŪŷŦųŴŪŵźġŰŧġŃŢŴŪŭŪŤŢŵŢ
İ˕ġųŢťŪŢůŤŦŴġŧŰųġůŢŵŶųŢŭĭġ
ŦůŷŪųŰůŮŦůŵŢŭġŢůťġŪůťŶŴŵųŪŢŭġ
ųŪŴŬġŧŰųŦŤŢŴŵĭġŮŰůŪŵŰųŪůŨġŢůťġ
ŮŪŵŪŨŢŵŪŰůġŪůġŋŢűŢůġȪœŔŕĮŉĮŋŢűŢůȫĵĵ૧ܰఱ‫ܨ‬౷ષ࠿બဥ‫଻ऺܥ‬ෝ࢜ષࡄ‫ݪ‬ٛ

ĵĶ

૧ܰ

ĵķ

૧ܰ

ĵĸ

૧ܰ

ĵĹ

ࠑ௽

๳࢛ȁඈ঎
‫ିמ‬ΟȜΗȄତ౵κΟσͬဥ̞̹ൡࣣഎ̈́
୷ဩఱ‫ޏ۪ڠ‬ςκȜΠΓϋ૙ၺ୆ॲၾଔ೰ͅ‫ݪࡄ̳ͥ۾‬ٛΏϋΈࡄ‫ݪ‬ΓϋΗȜ߃൥ȁࢫ‫ݛ‬ఱ‫ވڠ‬൳၌ဥ‫૽૽༹۾ܥ‬۪‫ޏ‬࿚ఴ͈࡛ા಼̤̫ͥͅ‫ڠ‬षࡄ‫ݪ‬‫ۼ‬໲‫ࢹܥݪࡄا‬ȁ௙ࣣ౷͈૧ജ‫ٳ‬‫ݪࡄڠޏ۪ݩ‬ਫ਼ࡄ‫ܖݪ‬๕࣭षΓϋΗȜ
‫ିغ‬౷ນဥ ōņŅġōŊŅłœ ͈‫؟ ଻ޏ۪ٸؚ‬໐ȁೄ૽ෝບ‫ݪࡄ̳ͥ۾ͅث‬ٛ໛‫ؖ‬ఱ‫ڠ‬ၑ‫ڠ‬໐‫ࡔک‬ȁࢫং
૩ႅ໦࿤౷ષ࠿બ‫ڰ‬ဥࡄ‫ݪ‬ٛ୷ဩఱ‫ޏ۪ڠ‬ςκȜΠΓϋΏϋΈࡄ‫ݪ‬ΓϋΗȜ‫ވ‬൳၌ဥΟȜΗȆ୭๵ĳįĲįĳįġ࣭ष‫ވ‬൳၌ဥࡄ‫هݪ‬ఴ֚။Ȫ˔࠯ȫ
๔࣢
Ĳ

૧ܰ
ȟ
ࠑ௽

૧ܰ

ĳ

૧ܰ

Ĵ

૧ܰ

ࡄ‫هݪ‬ఴ

ࡄ‫ݪ‬యນ৪̤͍͢ਫ਼௺

ŒŶŢůŵŪŧźŪůŨġŢŦųŰŴŰŭġŨųŰŸŵũġŶŴŪůŨġ ōłňœŐŔłŔġŏŰŧŦŭġŅŦŭŢġńųŶŻ
łůŨŴŵųöŮġŤŰŦŧŧŪŤŪŦůŵġŢŴġŮŦŢŴŶųŦťġ ŎŢůŪŭŢġŐţŴŦųŷŢŵŰųźĭġ
łŵŦůŦŰġťŦġŎŢůŪŭŢġ
ŧųŰŮġŨųŰŶůťĮţŢŴŦťġŪůŴŵųŶŮŦůŵŴġ
ŖůŪŷŦųŴŪŵź
ŢůťġŴŢŵŦŭŭŪŵŦġťŢŵŢ
ŏŨŶźŦůġōŶŰůŨġŗŪŦŵ
ŔŵŶťźġŰŧġŧŰųŦŴŵġŴŵųŶŤŵŶųŢŭġ
ŔűŢŤŦġŕŦŤũůŰŭŰŨźġ
ŤũŢųŢŤŵŦųŪŴŵŪŤŴġŪůġŮŢůŨųŰŷŦġŧŰųŦŴŵġġ
ŊůŴŵŪŵŶŵŦġ
ȪŔŕŊȫĭġŗŪŦŵůŢŮġ
ŪůġŗŪŦŵůŢŮġŶŴŪůŨġłōŐŔĮˎġŔłœġ
łŤŢťŦŮźġŰŧġŔŤŪŦůŤŦġ
ťŢŵŢŢůťġŕŦŤũůŰŭŰŨźġ
ȪŗłŔŕȫ
őņœņœłġōŪźŢůŢŨŦġ
ŌŪŵũŴŪųŪ
ŔŤũŰŰŭġŰŧġńŪŷŪŭġ
łġœŦŮŰŵŦġŔŦůŴŪůŨġŢůťġňŊŔġţŢŴŦťġ
ņůŨŪůŦŦųŪůŨġŢůťġġ
łűűųŰŢŤũġŵŰġŎŪŵŪŨŢŵŦġņŭŦűũŢůŵĮ
ŔŶųŷŦźŪůŨĭġŇŢŤŶŭŵźġŰŧġ
ŉŶŮŢůġńŰůŧŭŪŤŵġŪůġŔųŪġōŢůŬŢ
ŉŦŢŭŵũĭġņůŨŪůŦŦųŪůŨġŢůťġ
ŔŤŪŦůŤŦŴĭġŖůŪŷŦųŴŪŵźġŰŧġ
ŔŰŵũŦųůġŒŶŦŦůŴŭŢůť
ŔűŢŵŪŢŭġńũŢųŢŤŵŦųŪŴŵŪŤŴġŰŧġōŢůťġ
ŃłœŖŔġŃłŃł
ŕŦůŶųŦġŪůġőŰŵŦůŵŪŢŭġŢųŦŢġŰŧġ
ŃŰŨŰųġłŨųŪŤŶŭŵŶųŢŭġ
łŨųŪŤŶŭŵŶųŢŭġœŪŤŦġŇŪŦŭťġőųŰŵŦŤŵŪŰůġ
ŖůŪŷŦųŴŪŵź
ŪůġŊůťŰůŦŴŪŢ
ŔŉņŏġŎŪŢŰŨŦů
ŎŶŭŵŪĮűŭŢŵŧŰųŮġŴŢŵŦŭŭŪŵŦġ
ŊůŴŵŪŵŶŵŦġŰŧġ
ŰţŴŦųŷŢŵŪŰůŴġŧŰųġŪŮűųŰŷŪůŨġ
ŕŪţŦŵŢůġőŭŢŵŦŢŶġ
ųŦŵųŪŦŷŢŭġŰŧġűŭŢůŵġűũŦůŰŭŰŨźġŰůġŵũŦġ
œŦŴŦŢųŤũĭńũŪůŦŴŦġ
ŕŪţŦŵŢůġőŭŢŵŦŢŶ
łŤŢťŦŮźġŰŧġŔŤŪŦůŤŦŴ
ŎŶŭŵŪĮŕŦŮűŰųŢŭġŔłœġ
őņœŊŔŔŊŏġŅŢůŪŦŭŦ
ŊůŵŦųŧŦųŰŮŦŵųźġŧŰųġŪůŧųŢŴŵųŶŤŵŶųŦġ
őŶųťŶŦġŖůŪŷŦųŴŪŵź
ŮŰůŪŵŰųŪůŨ
łűűŭŪŤŢŵŪŰůġŰŧġŴűŢŤŦġŢůťġŨųŰŶůťġ
ŐŖśŐŖŏŐŗġġŅŊŎŊŕłœ
ŵŦŤũůŰŭŰŨŪŦŴġŧŰųġťŪŴŢŴŵŦųġųŪŴŬġ
ńũŢűŮŢůġŖůŪŷŦųŴŪŵź
ŮŪŵŪŨŢŵŪŰůĻġŎŶŭŵŪĮŴŦůŴŰųġŘŦţġŧŰųġ
ŦŢųŵũŲŶŢŬŦġŦŢųŭźġťŦŵŦŤŵŪŰůį

ĵ

ࠑ௽

Ķ

૧ܰ

ķ

૧ܰ

ĸ

ࠑ௽

Ĺ

ńũŢųŢŤŵŦųŪŴŵŪŤŴġŢůťġŦŷŪťŦůŤŦŴġŰŧġ
ŴŦŪŴŮŰĮŪŰůŰŴűũŦųŪŤġűųŦŤŶųŴŰųŴġŪůġŋŢűŢů
ࠑ௽ȪŔŵŶťźġŢůťġŕŦŴŵġŧŰųġŊŰůŰŴűũŦųŪŤġ
ņŢųŵũŲŶŢŬŦġőųŦŤŶųŴŰųŴġŪůġŋŢűŢůȫ

ōŊŖġŋŢůůġŚŦůŲ
ŏŢŵŪŰůŢŭġńŦůŵųŢŭġ
ŖůŪŷŦųŴŪŵź

― 40 ―

చ؊‫֥ޗ‬‫ވ‬൳၌ဥΟȜΗȆ୭๵‫ݛ‬ଲȁࢤྶ

ŎŶŭŵŪĮŸŢŷŦŭŦůŨŵũġŭŪťŢųļġŨųŰŶůťġ
ŪůŴŵųŶŮŦůŵŴġ
ȪŢŦŵũŢŭŰŮŦŵŦųĭġ
ůŦűũŦŭŰŮŦŵŦųĭġŸŦŢŵũŦųġ
ŮŰůŪŵŰųȫļġŴŶůġűũŰŵŰŮŦŵŦųġ
ťŢŵŢļġŴŢŵŦŭŭŪŵŦġťŢŵŢļ

߃൥ȁ઎຃

߃൥ȁ઎຃

ུ‫ޡ‬ȁ୷੉

ųŦŮŰŵŦġŴŦůŴŪůŨĭġŴűŢŵŪŢŭġťŢŵŢġ
ŢůťġŪůŧŰųŮŢŵŪŰůġŧŰųġŭŢůťġ
űųŰŵŦŤŵŪŰůġŢůťġųŦŸŢųťŪůŨġ
ŮŦŵũŰťġŵŰġŧŢųŮŦųġŢůťġŰŵũŦųŴ

ဠȁȁȁռŴŢŵŦŭŭŪŵŦġťŢŵŢġųŦŴŰŶųŤŦŴġŢŵġ
ńņœŦŔπ΍έ͹ΛΠ

ńŰŮűŶŵŦųŴġŢůťġŔłœġŴŦůŴŰųŴġŪŧġ
ŢŷŢŪŭŢţŭŦ

໚໐ȁ࣪ྜŉŪŮŢŸŢųŪ Į˔İ˕ŮŦŵŦŰųŰŭŰŨŪŤŢŭġŴŢŵŦŭŭŪŵŦġťŢŵŢ

໚໐ȁ࣪ྜňŰŭţŢŭġŊŰůŰŴűũŦųŦġŎŢűġŰŧġŵũŦġ
ňőŔġŵŰŵŢŭġŦŭŦŤŵųŰůġŤŰůŵŦůŵ

ĳįĳįġġ‫ވ‬൳၌ဥίυΈρθࡄ‫͈ݪ‬મळ

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-04䛇Ẽೃ䝰䝕䝹ᩘ್ᐇ㦂⤖ᯝ䛻䜘䜛⾨ᫍ䝥䝻䝎䜽䝖ᑟฟ䜰䝹䝂䝸䝈䝮䛾᳨ド
Validation of satellite product estimation algorithm using climate model simulation data䠄◊✲௦⾲⪅ྡ䠅㻌 ᳃ᒣ㞞㞝㻌 䠄㛗ᓮ኱Ꮫ䠅
Masao Moriyama (Nagasaki University)㻌 㻌 䠄◊✲ᐇ᪋⪅䠅㻌 㤿ῡ࿴㞝㻌 䠄༓ⴥ኱Ꮫ⎔ቃ䝸䝰䞊䝖䝉䞁䝅䞁䜾◊✲䝉䞁䝍䞊ᐈဨ䠅㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 Kazuo Mabuchi (CEReS, Chiba University)䛆せ᪨䛇ᮏᖺᗘ䛿䚸␗䛺䜛᳜⏕ศᕸ䝕䞊䝍䜢⏝䛔䛯䝰䝕䝹ᩘ್ᐇ㦂⤖ᯝ䛾ẚ㍑䜢⾜䛔䚸᳜⏕ศᕸ䛾㐪䛔䛜Ẽೃ䝰䝕䝹ฟຊ䛻୚䛘䜛ᙳ㡪䜢㏻䛧䛶䚸⾨ᫍ䝕䞊䝍䛛䜙ᢳฟ䛥䜜䛯᳜⏕ศᕸ䝕䞊䝍䛾⢭ᗘ䛾㔜せᛶ䛾☜ㄆ䜢⾜䛖䛣䛸䜢┠ⓗ䛸䛧䛶䚸๓ᖺᗘ䛻⾜䛳䛯䝁䞁䝖䝻䞊䝹ᐇ㦂䛷౑⏝䛧䛯᳜⏕ศᕸ䛸␗䛺䜛᳜⏕ศᕸ䜢⏝䛔䛯ᩘ್ᐇ㦂䜢⾜䛳䛯䚹䝁䞁䝖䝻䞊䝹ᐇ㦂⤖ᯝ䛸ẚ㍑䛧䛯⤖ᯝ䚸 㧗⦋ᗘ䛚䜘䜃ప⦋ᗘ䛤䛸䛻᳜⏕ุู䛾㔜せᛶ䛜♧၀䛥䜜䛯䚹௒ᚋ䜒䚸⾨ᫍ䝥䝻䝎䜽䝖䛸䝰䝕䝹䝥䝻䝎䜽䝖䛾┦஫฼⏝䛾ྍ⬟ᛶ䜢ᐇド䛧䛶䛔䛟ணᐃ䛷䛒䜛䚹

䛆Abstract䛇

In this fiscal year, we compared the model numerical simulation results using different vegetation
distribution data. As a result, at high latitude, it turned out that discrimination of vegetation height isimportant. Moreover, at low latitude, it turned out that discrimination of the existence or nonexistence of
seasonal change of vegetation is important. We will prove the capability of mutual verification of satellite
products and model products furthermore.

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

䝰䝕䝹䛷෌⌧䛥䜜䜛ྛせ⣲䛿䚸⥲ྜⓗ䛺᳨ド䛿ᚲせ䛷䛒䜛䜒䛾䛾䚸≀⌮ⓗ䛚䜘䜃⏕≀⏕ែᏛⓗ䛻▩┪䛧䛺䛔┦஫స⏝㛵ಀ䜢ᵓ⠏䛧䛶䛔䜛䚹⾨ᫍほ 䝥䝻䝎䜽䝖䛸䝰䝕䝹䝥䝻䝎䜽䝖䜢ẚ㍑᳨ド䛩䜛䛣䛸䛻䜘䜚䚸䛭䜜䜙┦஫䛾᳨ド䚸䛚䜘䜃≀⌮ⓗ䞉⏕≀⏕ែᏛⓗ䝯䜹䝙䝈䝮䛾᥈✲䛜ྍ⬟䛸䛺䜛䚹䛥䜙䛻≀⌮ⓗ⏕≀⏕ែᏛⓗᅉᯝ㛵ಀ䛾⌮ゎ䜒㐍䜐䛸⪃䛘䜙䜜䜛䚹ᮏᖺᗘ䛿䚸␗䛺䜛᳜⏕ศᕸ䝕䞊䝍䜢⏝䛔䛯䝰䝕䝹ᩘ್ᐇ㦂⤖ᯝ䛾ẚ㍑䜢
⾜䛔䚸᳜⏕ศᕸ䛾㐪䛔䛜Ẽೃ䝰䝕䝹ฟຊ䛻୚䛘䜛ᙳ㡪䜢㏻䛧䛶䚸⾨ᫍ䝕䞊䝍䛛䜙ᢳฟ䛥䜜䛯᳜⏕ศᕸ䝕䞊䝍䛾⢭ᗘ䛾㔜せᛶ䛾☜ㄆ䜢⾜䛖䛣䛸䜢┠ⓗ䛸䛧䛶䚸๓ᖺᗘ䛻⾜䛳䛯䝁䞁䝖䝻䞊䝹ᐇ㦂䛷౑⏝䛧䛯᳜⏕ศᕸ䛸␗䛺䜛᳜⏕ศᕸ䜢⏝䛔䛯ᩘ್ᐇ㦂䜢⾜䛳䛯䚹䝁䞁䝖䝻䞊䝹ᐇ㦂䛷⏝䛔䛯Ẽೃ䝰䝕䝹⏝᳜⏕ศᕸ䝕䞊䝍䛿䚸Major World Ecosystem Complexes Ranked
by Carbon in Live Vegetation dataset (Olson et al. 1983)䜢ᇶ䛻䛧䛶సᡂ䛧䛯䚹୍᪉䚸䝁䞁䝖䝻䞊䝹ᐇ㦂䛸ẚ㍑䛩䜛䛯䜑䛻⾜䛳䛯ᩘ್ᐇ㦂䛷⏝䛔䛯᳜⏕ศᕸ䝕䞊䝍䛿䚸᭮ᒣ䠄ኳ⌮኱Ꮫ䠅䛜సᡂ䛧䛯GLCV1᳜⏕ศᕸ䝕䞊䝍䜢⏝䛔䛯䚹ᮏᩘ್ᐇ㦂䛻䛚䛔䛶䛿䚸኱Ẽഃ≀⌮㔞䛾ึᮇ್䛸䛧䛶䠎䠐᫬㛫䛤䛸䛾䠌䠌䠶ᐈほゎᯒ䝕䞊䝍䜢౑⏝䛧䛯䠐䠔᫬㛫✚ศ䛾୪ิ㐃⥆ᐇ⾜䜢⾜䛔䚸኱Ẽ୰䠟䠫䠎⃰ᗘ䛚䜘䜃㝣ᇦㅖせ⣲䛾್䛿䚸✚ศᮇ㛫୰䚸䝰䝕䝹ィ⟬⤖ᯝ䜢䛭䛾䜎䜎ᘬ䛝⥅䛠ᡭἲ䜢᥇䛳䛯䚹ゎᯒᑐ㇟䝕䞊䝍䛿䚸ྛ䠐䠔᫬㛫✚ศᚋ༙䛾䠎䠐᫬㛫䛾ィ⟬⤖ᯝ䜢ᑐ㇟䛸䛧䛯䚹䛣䜜䜙䛻䜘䜚䚸⌧ᐇ䛻㏆䛔኱Ẽ⎔ቃ᮲௳䛻䛚䛡䜛኱Ẽ㝣ᇦ≀⌮⏕≀㐣⛬䝣䝹䜹䝑䝥䝹┦஫స⏝䛻㛵䛩䜛ゎᯒ䛜ྍ⬟䛸䛺䜛䚹㻌㻌㻌㻌㻌㻌ᅗ㻌 Ẽೃ䝰䝕䝹ᩘ್ᐇ㦂⏝᳜⏕ศᕸ䚹ᕥ䠖GLCV1᳜⏕ศᕸ䚸ྑ䠖䝁䞁䝖䝻䞊䝹᳜⏕ศᕸ䚹䝁䞁䝖䝻䞊䝹ᩘ್ᐇ㦂⤖ᯝ䛸GLCV1᳜⏕ศᕸ䜢⏝䛔䛯ᩘ್ᐇ㦂⤖ᯝ䜢ẚ㍑䛧䛯䚹䛭䛾⤖ᯝ䚸 㧗⦋ᗘ᳜⏕䛻㛵䛧䛶䛿䚸ⲡཎ⣔䠄పᶞ㧗⣔䠅᳜⏕䛛᳃ᯘ⣔䠄㧗ᶞ㧗⣔䠅᳜⏕䛛䛾ุู䛾㔜せᛶ䛜♧၀䛥䜜䛯䚹䜎䛯䚸ప⦋ᗘ᳜⏕䛻㛵䛧䛶䛿䚸Ꮨ⠇ᛶ䛾᭷↓䠄ᖖ⥳ᯘ⣔䛛Ꮨ⠇ᯘ⣔䛛䠅䛾ุู䛾㔜せᛶ䛜♧၀䛥䜜䛯䚹

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

┦஫䛻ᅉᯝ㛵ಀ䛾↓䛔⾨ᫍ䝥䝻䝎䜽䝖䛸Ẽೃ䝰䝕䝹ฟຊ䝥䝻䝎䜽䝖䛾⊂❧䛧䛯䝥䝻䝎䜽䝖䛸䛧䛶䛾┦஫ẚ㍑᳨
ド䛿䚸཮᪉䛾䝥䝻䝎䜽䝖䛾⢭ᗘྥୖ䛻䛸䛳䛶㠀ᖖ䛻᭷ຠ䛷䛒䜛䚹⾨ᫍ䝥䝻䝎䜽䝖䛜䝰䝕䝹᳨ド⏝᝟ሗ䛸䛺䜛୍᪉䛷䚸䝰䝕䝹䛻䜘䜛෌⌧⤖ᯝ䛻䛴䛔䛶䜒䚸⾨ᫍ䛻䜘䜛㛫᥋ほ 䝕䞊䝍䛛䜙ಶู䛻䛭䜜䛮䜜䛾䜰䝹䝂䝸䝈䝮䛻䜘䜚ᢳฟ䛥䜜䜛ྛせ⣲䝕䞊䝍䛾䚸ᗈᇦⓗ┦஫᳨ド䛾䛯䜑䛾䚸┦ᑐⓗᇶ‽᝟ሗ䛸ᡂ䜚ᚓ䜛䛸⪃䛘䜙䜜䜛䚹௒ᚋ䜒䚸⾨ᫍ䝥䝻䝎䜽䝖䛸䝰䝕䝹䝥䝻䝎䜽䝖䛾┦஫฼⏝䛾ྍ⬟ᛶ䜢ᐇド䛧䛶䛔䛟䛸䛸䜒䛻䚸䛭䜜䜙䛾䝥䝻䝎䜽䝖䜢⥲ྜⓗ䛻฼⏝䛧䛯ᆅ⌫䝅䝇䝔䝮⌮ゎ䛾䛯䜑䛾䝅䝇䝔䝮ᵓ⠏䜢┠ᣦ䛧䛯䛔䛸⪃䛘䛶䛔䜛䚹― 41 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-05䛇㻌 ⓑⰍග䝺䞊䝄䞊䜢⏝䛔䛯 ᐊຠᯝ䜺䝇䛾ィ ἲ䛾㛤Ⓨ
㻌 Development of greenhouse gas measurement using the white light laser systemᰁᕝ㻌 ᬛᘯ㻌 䠄බ┈㈈ᅋἲே䝺䞊䝄䞊ᢏ⾡⥲ྜ◊✲ᡤ䠅Toshihiro Somekawa 㻌 䠄Institute for Laser Technology 䠅䛆せ᪨䛇ᐊຠᯝ䜺䝇䛻䜘䜛ᆅ⌫ ᬮ໬䛾㐍⾜䛿䚸ᆅ⌫つᶍ䛷䛾ᙳ㡪䛾኱䛝䛥䜔῝้䛥䛛䜙䜏䛶㔜せ䛺⎔ቃၥ㢟䛾䜂䛸䛴䛷䛒䜚䚸㧗ᙉᗘ䝣䜵䝮䝖⛊䝺䞊䝄䞊䜢⏝䛔䛶⏕ᡂ䛥䛫䛯ⓑⰍග䝺䞊䝄䞊䛻䜘䜛㛗ග㊰ᕪศ྾཰ศග䠄DOAS䠅ἲィ 䛻䜘䜚䚸ከ✀㢮䛾 ᐊຠᯝ䜺䝇⃰ᗘ䜢ྠ᫬䛻ホ౯䛩䜛ᡭἲ䜢㛤Ⓨ䛧䛶䛔䜛䚹ᮏ◊✲䛷䛿䚸ⓑⰍග䝺䞊䝄䞊䜢኱Ẽ୰䛻ఏᦙ䛥䛫䠄ග㊰㛗䠖452 m䠅䚸䛭䛾኱Ẽ㏱㐣䝇䝨䜽䝖䝹䜢ྲྀᚓ䛧䚸HITRAN䝕䞊䝍䝧䞊䝇䜢⏝䛔䛯䝅䝭䝳䝺䞊䝅䝵䞁⤖ᯝ䛸ẚ㍑䛩䜛䛣䛸䛷䚸኱Ẽ୰䛾CO2⃰ᗘィ 䜢ᐇ᪋䛧䛯䚹䛆Abstract䛇 We applied a broadband white light laser to the detection of a variety of greenhouse gases on thebasis of differential optical absorption spectroscopy (DOAS). We performed the white light DOAS
measurements and proposed a method for retrieving atmospheric CO2 concentrations using the
DOAS evaluation procedure.

◊✲䛾ᡂᯝ㻌 ᅗ1䛻ⓑⰍග䝺䞊䝄䞊䜢⏝䛔䛯DOASᐇ㦂㓄⨨ᅗ䜢♧䛩䚹㧗ᙉᗘ䝣䜵䝮䝖⛊䝺䞊䝄䞊䜢ᕼ䜺䝇䛻㞟ග䛩䜛䛣䛸䛷䚸⣸እ䛛䜙㉥እ䜎䛷䛾㐃⥆䝇䝨䜽䝖䝹䜢᭷䛩䜛ⓑⰍග䝺䞊䝄䞊䜢⏕ᡂ䛥䛫䜛䛣䛸䛜ྍ⬟䛸䛺䜛䚹Ἴ㛗800
nm䚸ฟຊ100mJ䚸䝟䝹䝇ᖜ100 fs䛾䝢䞊䜽ᙉᗘ䛜TW䛻㐩䛩䜛䝺䞊䝄䞊䝟䝹䝇䜢Kr䜺䝇䛻㞟ග↷ᑕ䛩䜛䛣䛸䛻䜘䛳䛶ⓑⰍග䜢⏕ᡂ䛧䚸኱Ẽఏᦙᚋ䛾㉥እ䝇䝨䜽䝖䝹ィ 䜢ᐇ᪋䛧䛯䚹 ᆅ⌮ⓗไ⣙䛛䜙┤⥺ග㊰䛷䛿䛺䛟䚸」ᩘ䛾䝭䝷䞊䜢⏝䛔䛶ග㊰㛗452 m䛸䛧䚸ཧ↷ಙྕ䛿䜺䝇䝉䝹ᚋ䛾0 m䛾఩⨨䛾䝇䝨䜽䝖䝹䜢᥇⏝䛧䛯䚹ほ᪥ᙜ᪥䛾CO2⃰ᗘ䛿398 ppm䛷䛒䜚䚸 ᗘ2.6Υ䚸‵ᗘ䛿77%䛷䛒䜛䚹㻌 DOAS䝇䝨䜽䝖䝹䛾HITRAN䝕䞊䝍䝧䞊䝇䜢⏝䛔䛯ゎᯒ⤖ᯝ䜢ᅗ2䛻♧䛩䚹㐣ཤ䛾ᩥ⊩䠄Somekawa et al.,2011䠅䛷♧䛧䛯㏱㐣⋡䛷ホ౯䛩䜛ᚑ᮶ᡭἲ䛷䛿䚸ᐇ㦂䝕䞊䝍䛸䝅䝭䝳䝺䞊䝅䝵䞁⤖ᯝ䛜䛒䜎䜚୍⮴䛧䛶䛔䛺䛔䚹
୍᪉䚸DOASἲ䛾ゎᯒ䛻䛺䜙䛔䚸Ἴ㛗䛸䛸䜒䛻⦆䜔䛛䛻ኚ໬䛩䜛ᡂศ䜢䚸Ἴ㛗䛾పḟከ㡯ᘧ䜢⏝䛔䛶ྲྀ䜚㝖䛔䛯ගᏛⓗཌ䛥䛷䛿䚸ᚑ᮶ᡭἲ䜘䜚䜒୍⮴䛧䛶䛔䜛䛣䛸䛜䜟䛛䜛䠄ᅗ2ྑ䠅䚹DOASἲ䛻๎䛧䛯ᡭἲ䛷䛿ཧ↷䝇䝨䜽䝖䝹䛾SN䛜ᝏ䛔㝿䛻ᚑ᮶ᡭἲ䜘䜚䜒᭷ຠ䛸䛺䜛䠄Plat and Stutz, 2008䠅䚹TW䝺䞊䝄䞊䜢⏝䛔䛯ⓑⰍග䛷䛿䚸୰ᚰἼ㛗䛾800 nm䛛䜙㞳䜜䛯2000 nm௜㏆䛾㉥እᇦ䛾ⓑⰍගᙉᗘ䛜ᚤᙅ䛻䛺䜛䛯䜑䚸ཧ↷䞉྾཰䛸䜒
䛻SN䛾Ⰻ䛔䝇䝨䜽䝖䝹ᙉᗘ䛜ᚓ䜙䜜䛺䛛䛳䛯䛣䛸䛜ཎᅉ䛰䛸⪃䛘䜙䜜䜛䚹䛧䛯䛜䛳䛶䚸TW䝺䞊䝄䞊䜢⏝䛔䛯ⓑⰍග䛾྾཰ィ 䛻䜘䜛⃰ᗘホ౯䛻䛿DOASἲ䛻๎䛧䛯⃰ᗘホ౯ᡭἲ䛜᭷ຠ䛷䛒䜛䛣䛸䛜䜟䛛䛳䛯䚹
f=5m

M(R=10m)
HAMAMATSU C9914GB(1100䡚2200nm)~12m

Kr gas cell 䠄9m, 0.5 atm䠅Spectrometer
~35m
䐣A䡈 M

䐟Al M

1

1.20
TW Laser System(100mJ, 100 fs,
10 Hz, 800 nm)

1.00

~50m
䐤Au M

Difference Optical Depth䠎㻌 ᐊຠᯝ䜺䝇䛻䜘䜛ᆅ⌫ ᬮ໬䛾㐍⾜䛿䚸ᆅ⌫つᶍ䛷䛾ᙳ㡪䛾኱䛝䛥䜔῝้䛥䛛䜙䜏䛶㔜せ䛺⎔ቃၥ㢟䛾䜂䛸䛴䛷䛒䜚䚸 ᐊຠᯝ䜺䝇䛾✵㛫ศᕸ䛾ᢕᥱ䛿ᒁᡤⓗ䛺Ⓨ⏕※䜈䛾ᑐᛂ䜔䚸ᆅ⌫ ᬮ໬䛾ண ⢭ᗘ䜢ྥୖ䛥䛫䜛䛯䜑䛻㠀ᖖ䛻㔜せ䛷䛒䜛䚹䛧䛛䛧䛺䛜䜙䚸 ᐊຠᯝ䜢♧䛩䜺䝇䛻䛿Ỉ⵨Ẽ䚸஧㓟໬Ⅳ⣲䚸䝯䝍䞁➼䛜䛒䜚䚸」ᩘ✀㢮䛾䜺䝇䜢ྠ᫬䛻ホ౯䛩䜛䛣䛸䛿ᅔ㞴䛷䛒䜛䚹䛭䛣䛷䚸ᮏ◊✲䛷䛿ከ✀㢮䛾 ᐊຠᯝ䜺䝇䛾྾཰ᖏ䜢䜹䝞䞊䛩䜛ⓑⰍග䛾䝺䞊䝄䞊䜢⏝䛔䛶 ᐊຠᯝ䜺䝇䛾⃰ᗘ䜢ྠ᫬䛻ホ౯䛩䜛䛯䜑䛾ᇶ♏◊✲䛸䛧䛶䚸TW䝺䞊䝄䞊䝅䝇䝔䝮䜢⏝䛔䛯㛗ග㊰ᕪศ྾཰ศග䠄DOAS䠅ἲ䛻䜘䜛኱Ẽ୰䛾CO2⃰ᗘホ౯ᡭἲ䜢㛤Ⓨ䛧䛯䚹Transmittance

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⫼ᬒ
┠ⓗ
᪉ἲ

Simulation

0.80
0.60
Data

0.40
0.20

0.5

0

-0.5

䐢Al M
䐡A䡈 M

0.00
䐠Al M

ᅗ1 TW䝺䞊䝄䞊䜢⏝䛔䛯DOASᐇ㦂㓄⨨ᅗ䠄ග㊰㛗䠖452 m䠅

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

1900

1950

2000
Wavelength (nm)

2050

2100

-1
1900

1950

2000
Wavelength (nm)

2050

2100

ᅗ2 DOAS䝇䝨䜽䝖䝹䛾HITRAN䝕䞊䝍䝧䞊䝇䛻䜘䜛䝅䝭䝳䝺䞊䝅䝵䞁⤖ᯝ䠄ᕥ䠖㏱㐣⋡䚸ྑ䠖ගᏛⓗཌ䛥䠅㻌 㛤Ⓨ䛧䛯ᡭἲ䛿䚸䝺䞊䝄䞊䜢⏝䛔䛯䝸䝰䞊䝖䝉䞁䝅䞁䜾䛸㧗ᙉᗘ䝺䞊䝄䞊ᢏ⾡䜢⼥ྜ䛥䛫䛯᪂つᡭἲ䛷䛒䜚䚸኱Ẽ୰䜺䝇⃰ᗘィ 䜈䛾ᛂ⏝ྍ⬟ᛶ䜢♧䛧䛯◊✲䛷䛒䜛䚹ⓑⰍග䜢⏝䛔䜛䛣䛸䛷䚸䛣䜜䜎䛷䝺䞊䝄䞊䛾Ⓨ᣺Ἴ㛗䛻ไ㝈䛥䜜䛶䛝䛯✀䚻䛾⎔ቃィ 䛜1ྎ䛾ィ 䝅䝇䝔䝮䛷ᐇ᪋ྍ⬟䛻䛺䜛䚹ྍᦙᆺTW䝺䞊䝄䞊䝅䝇䝔䝮䛿᪥ᮏ䛷䛿㝣⥲◊䛻⿦ഛ䛥䜜䚸䛭䛾䝅䝇䝔䝮䜢⏝䛔䛯䝷䜲䝎䞊ᡭἲ䛿⅏ᐖᑐ⟇➼䜈䛾฼⏝䛜ィ⏬䛥䜜䛶䛔䜛䚹ᮏᐇ㦂䛻䜘䜚䚸TW䝺䞊䝄䞊䝅䝇䝔䝮䛾䛥䜙䛺䜛⎔ቃィ 䜈䛾ᛂ⏝ྍ⬟ᛶ䜢♧䛫䛯䛸䛔䛘䜛䚹― 42 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-07䛇䠏ḟඖ䝕䞊䝍䜢⏝䛔䛯᳃ᯘ䝞䜲䜸䝬䝇㈨※䜶䝛䝹䜼䞊฼⏝ྍ⬟㔞᥎ᐃ
Estimating available amounts of forest biomass resources for energy with 3D data䠄◊✲௦⾲⪅ྡ䠅 ᭷㈡㻌 ୍ᗈ㻌 䠄Ᏹ㒔ᐑ኱Ꮫ䞉㎰Ꮫ㒊䠅
Kazuhiro Aruga 㻌 䠄Utsunomiya University 䞉Faculty of Agriculture 䠅䛆せ᪨䛇ᮏ◊✲䛷䛿UAV-S䡂M䚸⯟ 䞉ᆅୖ䝺䞊䝄䛺䛹䛻䜘䜚ᗈᇦ䛛䛴ヲ⣽䛻᳃ᯘ㈨※䜢ィ 䛩䜛䛣䛸䛻䜘䜚䚸䛣䜜䜎䛷䜘䜚䜒㧗⢭ᗘ䛻᳃ᯘ䝞䜲䜸䝬䝇㈨※䛾䜶䝛䝹䜼䞊฼⏝ྍ⬟㔞䜢᥎ᐃ䛩䜛ᡭἲ䜢ᵓ⠏䛩䜛䚹᫖ᖺᗘ䜎䛷䛾◊✲䛷䛿䝇䜼䞉䝠䝜䜻䛾㔪ⴥᶞ䜢ᑐ㇟䛸䛧䛯䛜䚸ᮏᖺᗘ䛿㏻┤䛺䝇䜼䞉䝠䝜䜻䛾㔪ⴥᶞ䛸䛿␗䛺䜚䚸฼⏝ྍ⬟㔞᥎ᐃ䛜ᅔ㞴䛷䛒䜛ᗈⴥᶞ㈨※䛾฼⏝ྍ⬟㔞᥎ᐃᡭἲ䜢ᵓ⠏䛧䛯䚹Ᏹ㒔ᐑ኱Ꮫ㎰Ꮫ㒊㝃ᒓ⯪⏕₇⩦ᯘ䛻䛚䛔䛶䚸ᆅୖ䝺䞊䝄䝇䜻䝱䝘䜢⏝䛔䛶ᗈⴥᶞ䠎ḟᯘ䜢ィ 䛧䚸䝁䝘䝷䚸䜽䝸䚸䝩䜸䝜䜻䚸䝃䜽䝷䛾䠐ᶞ✀䛻䛴䛔䛶ᶞᖿ䛾ᢳฟ䜢ヨ䜏33䛯䚹ᖿᮦ✚䛻㛵䛧䛶ᐇ ್䛸ẚ㍑䛧䛯䛸䛣䜝䚸RMSE䛿0.065m 䛷䚸㔪ⴥᶞ0.162m 䛸ẚ㍑䛧ᑠ䛥䛛䛳䛯䚹௒ᚋ䛿ᆅୖ䝺䞊䝄䝕䞊䝍䛻䛚䛡䜛㔪ⴥᶞ䚸ᗈⴥᶞ䛾ᶞᖿ䚸ᯞⴥ䛾⮬ືᢳฟᡭἲ䜢ᵓ⠏䛩䜛ணᐃ䛷䛒䜛䚹
䛆Abstract䛇 In the present study, a secondly broadleaved forest was measured using low cost portable TLS. Then,
DBH, height, top end diameters, sweep, and stem volumes were analyzed and compared with results ofconiferous plantation forests using terrestrial LiDAR. RMSE of DBH was 1.91 cm which was higher thanconiferous plantation forests. RMSE of stem volumes in the present study was 0.065 m3 which was lower
than coniferous plantation forest even though using low cost portable TLS because lower RMSEs of top
end diameters and shorter distances from portable TLS.

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⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

◊✲௦⾲⪅䜙䛿䛣䜜䜎䛷䛻GIS䜢⏝䛔䛶⤒῭ᛶ䜢⪃៖䛧䛯㛗ᮇⓗ䛺᳃ᯘ䝞䜲䜸䝬䝇㈨※䛾䜶䝛䝹䜼䞊฼⏝ྍ⬟㔞䜢᥎ᐃ䛩䜛ᡭἲ䜢ᵓ⠏䛧䛶䛝䛯䚹䛧䛛䛧䛺䛜䜙䚸GIS䝕䞊䝍䛾⢭ᗘ䛿ప䛟䚸䝸䝰䞊䝖䝉䞁䝅䞁䜾䛺䛹䛾ᡭἲ䜢⏝䛔䛶䚸䜘䜚㧗⢭ᗘ䛻᳃ᯘ䝞䜲䜸䝬䝇㈨※䛾䜶䝛䝹䜼䞊฼⏝ྍ⬟㔞䜢᥎ᐃ䛩䜛䛣䛸䛜ồ䜑䜙䜜䛶䛔䜛䚹䛭䛣䛷ᮏ◊✲䛷䛿UAV-S䡂M䚸⯟ 䞉ᆅୖ䝺䞊䝄䛺䛹䛻䜘䜚ᗈᇦ䛛䛴ヲ⣽䛻᳃ᯘ㈨※䜢ィ 䛩䜛䛣䛸䛻䜘䜚䚸䛣䜜䜎䛷䜘䜚䜒㧗⢭ᗘ䛻᳃ᯘ䝞䜲䜸䝬䝇㈨※䛾䜶䝛䝹䜼䞊฼⏝ྍ⬟㔞䜢᥎ᐃ䛩䜛ᡭἲ䜢ᵓ⠏䛩䜛䚹᫖ᖺᗘ䜎䛷䛾◊✲䛷䛿䝇䜼䞉䝠䝜䜻䛾㔪ⴥᶞ䜢ᑐ㇟䛸䛧䛯䛜䚸ᮏᖺᗘ䛿㏻┤䛺䝇䜼䞉䝠䝜䜻䛾㔪ⴥᶞ䛸䛿␗䛺䜚䚸฼⏝ྍ⬟㔞᥎ᐃ䛜ᅔ㞴䛷䛒䜛ᗈⴥᶞ㈨※䛾฼⏝ྍ⬟㔞᥎ᐃᡭἲ䜢ᵓ⠏䛧䛯䚹䠄䠍䠅Ᏹ㒔ᐑ኱Ꮫ㎰Ꮫ㒊㝃ᒓ⯪⏕₇⩦ᯘ䛻䛚䛔䛶䚸ᆅୖ䝺䞊䝄䝇䜻䝱䝘䜢⏝䛔䛶ᗈⴥᶞ䠎ḟᯘ䜢ィ 䛧䚸䝁䝘䝷䚸䜽䝸䚸䝩䜸䝜䜻䚸䝃䜽䝷䛾䠐ᶞ✀䛻䛴䛔䛶ᶞᖿ䛾ᢳฟ䜢ヨ䜏䛯䠄ᅗ䠍䠅䚹⬚㧗10cmᖜ
䛾᩿㠃䜢ぢ䜛䛸䚸䝁䝘䝷䚸䜽䝸䛾ᶞ⓶䛾ฝพ䜔䚸䝃䜽䝷䛾ᖿ᭤䛜䜚
䛻䜘䜛Ⅼ⩌䛾೫ᖹ䛜⾲⌧䛥䜜䚸ᆅୖ䝺䞊䝄䝇䜻䝱䝘䛻䜘䜛ᗈⴥᶞ䠎ḟᯘ䛾෌⌧ᛶ䛾㧗䛥䜢☜ㄆ䛩䜛䛣䛸䛜䛷䛝䛯䚹䠄䠎䠅⬚㧗┤ᚄ䛸ᶞ㧗䛻㛵䛧䛶ᐇ ್䛸ẚ㍑䛧䛯䛸䛣䜝䚸஧஌ᖹᆒᖹ᪉᰿ㄗᕪRMSE䛿䛭䜜䛮䜜1.91cm䚸2.06m䛷䛒䛳䛯䚹㔪ⴥᶞ
䛾RMSE䛿䛭䜜䛮䜜1.34cm䚸1.92m䛷䛒䛳䛯䛣䛸䛛䜙䚸ᗈⴥᶞ䛾⬚㧗┤ᚄRMSE䛿㔪ⴥᶞ䜘䜚኱䛝䛔䜒䛾䛾䚸ᶞ㧗䛿㔪ⴥᶞ䛸ྠ⛬ᗘ䛷䛒䛳䛯䛣䛸䛜ศ䛛䜛䚹䛺䛚䚸୍⯡䛻⬚㧗┤ᚄ䛿2cmᣓ⣙䛧䛶⏝䛔䜛䛣䛸䛛䜙䚸ᗈⴥᶞ䜒ᐇ⏝䛾⠊ᅖෆ䛷䛒䜛䛸ゝ䛘䜛䚹

䝁䝘䝷

䜽䝸

䝩䜸䝜䜻

䝃䜽䝷

ᆅୖ䝺䞊䝄䠄cm䠅

䠄䠏䠅୸ኴᮎཱྀᚄ䚸୸ኴᮦ✚䚸ᖿᮦ✚䛻㛵䛧䛶ᐇ ್䛸ẚ㍑䛧䛯䛸
33䛣䜝䠄ᅗ䠎䠅䚸RMSE䛿䛭䜜䛮䜜2.19cm䚸0.014m 䚸0.065m 䛷䛒䛳 ᅗ1 ᶞᖿ䛸⬚㧗᩿㠃
40
33䛯䚹㔪ⴥᶞ䛾RMSE䛿䛭䜜䛮䜜3.33cm䚸0.037m 䚸0.162m 䛷䛒䛳䛯䛣䛸䛛䜙䚸䛔䛵䜜䜒ᗈⴥᶞ䛾RMSE䛜ᑠ䛥䛛䛳䛯䚹䛣䜜䛿௒ᅇ䚸
20
ᗈⴥᶞ2ḟᯘ䛿᳃ᯘᵓ㐀䛜」㞧䛷ᶞᖿ䜒㏻┤䛷䛺䛔䛣䛸䛛䜙䚸ᡭື䛷ᶞᖿ䜢ᢳฟ䛧䚸ᯞⴥ䜢䜋䜌ྲྀ䜚㝖䛟䛣䛸䛜䛷䛝䛯䛾䛻ᑐ䛧䛶䚸㔪ⴥᶞ䛷䛿⮬ື䛷ᶞᖿ䜢ᢳฟ䛧䛯䛯䜑䚸ᯞⴥ䜢᏶඲䛻䛿ྲྀ䜚㝖䛟䛣䛸䛜0䛷䛝䛺䛛䛳䛯䛯䜑䛷䛒䜛䚹ᅗ2 ୸ኴᮎཱྀᚄ 0

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ᡂᯝᒎ㛤䛾
≧ἣ

ᐇ

20
್䠄cm䠅

40

GIS䜢⏝䛔䛶᥎ᐃ䛧䛯᳃ᯘ䝞䜲䜸䝬䝇㈨※䛾䜶䝛䝹䜼䞊฼⏝ྍ⬟㔞䛿䚸ᰣᮌ┴䛻䛚䛡䜛᳃ᯘ䝞䜲䜸䝬䝇䛾䜶䝛䝹䜼䞊฼⏝ィ⏬䛻⏝䛔䜙䜜䜛䛸䛸䜒䛻䚸᥎ᐃᡭἲ䛿௚ᆅᇦ䛻䛚䛡䜛฼⏝ྍ⬟㔞᥎ᐃ䛾㝿䛻ཧ⪃䛸䛥䜜䛶䛔䜛䚹௒ᚋ䛿ᆅୖ䝺䞊䝄䝕䞊䝍䛻䛚䛡䜛㔪ⴥᶞ䚸ᗈⴥᶞ䛾ᶞᖿ䚸ᯞⴥ䛾⮬ືᢳฟᡭἲ䜢ᵓ⠏䛩䜛䛸䛸䜒䛻䚸UAV-S䡂M䚸⯟ 䝺䞊䝄䛸⼥ྜ䛩䜛䛣䛸䛻䜘䜚䚸䛣䜜䜎䛷䜘䜚䜒㧗⢭ᗘ䛷ᗈᇦ䛻᳃ᯘ䝞䜲䜸䝬䝇㈨※䛾䜶䝛䝹䜼䞊฼⏝ྍ⬟㔞䜢᥎ᐃ䛩䜛ᡭἲ䜢ᵓ⠏䛩䜛ணᐃ䛷䛒䜛䚹― 43 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌•䛆CJ16-09䛇•⏕ά⎔ቃᅪ䛻䛚䛡䜛CO2⃰ᗘ䛾ィ 䛸᳨ド•Measurement and validation of CO2 concentration in human activity area•◊✲௦⾲⪅ྡ䠖᱓ཎ♸ྐ (Ⲉᇛ኱Ꮫ)•㻌 㻌 㻌 㻌 㻌 㻌 㻌 Yuji Kuwahara (Graduate School of Science and Engineering, IBARAKI) University䛆せ᪨䛇䛣䜜䜎䛷䚸ே㛫䛾άື⠊ᅖෆ䛷䛒䜛ᆅ⾲௜㏆䛾஧㓟໬Ⅳ⣲⃰ᗘ䜢ᗈᇦ䛷 ᐃ䛩䜛᪉ἲ䛜䛺䛛䛳䛯䚹ᮏ◊✲䛷䛿䚸
DOASἲ䜢⏝䛔䛶㛗ග㊰䛻䛚䛡䜛஧㓟໬Ⅳ⣲䛾⃰ᗘ䜢ィ 䛧䚸ᐃⅬほ 䛻䜘䜛䝕䞊䝍䛜䛭䛾ᆅᇦ䛾䛹䛾⛬ᗘ䛻䜎䛷㐺ᛂ䛷䛝䜛䛛䛹䛖䛛䜢☜ㄆ䛧䛶䛝䛯⤖ᯝ䚸௨ୗ䛾⤖ᯝ䜢ᚓ䜙䜜䛯䚹ᐃⅬほ 䛻䜘䜛஧㓟໬Ⅳ⣲⃰ᗘ䛜423ppm䛷䛒䛳䛯䛣䛸䚸䛭䛾᫬㛫ᖏ䛷䛾DOASἲ䛻䜘䜛㛗㊥㞳ほ 䛷䛾஧㓟໬Ⅳ⣲⃰ᗘ䛿427ppm䛷䛒䜚䚸ᐃⅬほ 䛾䝕䞊䝍䛸㠀ᖖ䛻㏆䛔್䛸䛺䛳䛯䚹䛆Abstract䛇 Since 2007 Ibaraki University has been carrying out fixed point observation of the concentration of carbon dioxidein Ibaraki Prefecture. In such fixed point observations, however, the point data may not represent the surrounding
concentrations. The Differential Optical Absorption Spectroscopy (DOAS) method measures the average concentration of tracecomponents including CO2 averaged over the optical path of a few kilometers. Therefore, in this research, we performed
DOAS observation of CO2 concentration from the Hitachi campus of Ibaraki University in February 2017 to examine to what
extent the data of fixed point observation agree with the concurrent DOAS result. The resulting concentration over a round trip
distance of 7.4 km from Ibaraki University to Umegaoka Hospital was measured to be 427 ppm, which was very close to thevalue of 423 ppm from the fixed point observation conducted at Ibaraki University.

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᪉ἲ

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◊✲䛾
ᡂᯝ

•㻌 Ⲉᇛ኱Ꮫ䛷䛿2007ᖺ䛛䜙Ⲉᇛ┴ෆ䛾ᩘ䛛ᡤ䛻⡆᫆ᆺ䛾ⓒⴥ⟽䜢タ⨨䛧䠈ே㛫䛾άື䠈⏕ά㡿ᇦ䛻䛚䛡䜛஧㓟໬Ⅳ⣲⃰ᗘ䛾ᐃⅬほ 䜢⾜䛳䛶䛝䛯䠊䛧䛛䛧䛣䛾ᐃⅬほ 䛷䛿䛭䛾ほ Ⅼ䛷ᚓ䜙䜜䜛䝕䞊䝍䛜䛭䛾࿘ᅖ䛾஧㓟໬Ⅳ⣲⃰ᗘ䛸ᚲ䛪䛧䜒୍⮴䛧䛺䛔䛣䛸䛜䛒䜛䠊䜎䛯⾨ᫍ䜢฼⏝䛧䛯ほ 䛷䛿㏆㉥እ⥺䜢⏝䛔䜛䛜䠈ᆅ⾲㠃௜㏆䛷䛾 ᐃឤᗘ䛜ప䛟䠈୺䛻ୖ✵䛾䝕䞊䝍䛜཯ᫎ䛥䜜䛶䛧䜎䛖䠊ᮏ◊✲䛾┠ⓗ䛿䠈஧㓟໬Ⅳ⣲䛾⠊ᅖほ 䜢⾜䛔ᐃⅬほ 䛻䜘䜛䝕䞊䝍䛜䛭䛾ᆅᇦ䛾䛹䛾⛬ᗘ䛻䜎䛷㐺ᛂ䛷䛝䜛䛛䛹䛖䛛䜢☜ㄆ䛩䜛䛣䛸䛷䛒䜛䠊䛣䛾䛯䜑䠈DOASἲ䜢⏝䛔䜛䛣䛸䛷㛗ග㊰䛷䛾஧㓟໬Ⅳ⣲⃰ᗘ䛾ィ 䜢ᐇ᪋䛧䛯䠊(1)ィ 䛻⏝䛔䜛ᮃ㐲㙾䜢䠈ཷග⏝䛸ᢞග⏝䛷஧䛴⏝䛔䛯䠊䛣䜜䛻䜘䜚䝣䝸䞁䝆䝜䜲䝈䜢పῶ䛧䛯ィ 䛜ྍ⬟䛸䛺䛳䛯䠄ᅗ1䠅䠊(2)  ᚟䛷7.4 km䛸䛔䛖㛗ග㊰䜢☜ಖ䛩䜛䛣䛸䛷䚸SN䛾䜘䛔ಙྕ䜢ྲྀᚓ䛩䜛䛣䛸䛜ྍ⬟䛻䛺䛳䛯䠄ᅗ2䠅䠊䝣䝸䞁䝆䛾ᙳ㡪䛜䜋䛸䜣䛹䛺䛔䛯䜑䚸䝅䝭䝳䝺䞊䝅䝵䞁䝇䝨䜽䝖䝹䛸䛾┤᥋ẚ㍑䛜
ྍ⬟䛷䛒䜛䚹(3)㛗ග㊰䛻䛚䛡䜛஧㓟໬Ⅳ⣲⃰ᗘ䜢ィ 䛩䜛䛣䛸䛷ᐃⅬほ䛷ᚓ䜙䜜䜛஧㓟໬Ⅳ⣲⃰ᗘ䛜䛹䛾⠊ᅖ䜎䛷䛾⃰ᗘ䜢ᤊ䛘䛶䛔䜛䛛䛾᳨ド䜢⾜䛳䛯䠊(4)Ⲉᇛ኱Ꮫ᪥❧䜻䝱䞁䝟䝇䛻䛶ᐃⅬほ 䛷ᚓ䜙䜜䛯⃰ᗘ䛿
423ppm䛷䛒䜚䠈DOASἲ䛷ᚓ䜙䜜䛯⃰ᗘ䛿427ppm䛷䛒䛳䛯䚹

ᅗ1

ほ

⿦⨨

ᅗ2 •ᚓ䜙䜜䛯䝕䞊䝍䛸䝅䝭䝳䝺䞊䝅䝵
䞁䛾ẚ㍑

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

•㻌 ௒ᅇ䛾ィ 䛷䠈⣙7400m䛾㊥㞳䛷䜒ィ 䛜ྍ⬟䛷䛒䜛䛣䛸䛜ศ䛛䛳䛯䠊௒ᚋ䠈㛗ᮇ㛫䛷ィ 䜢⾜䛔䠈㢼ྥ㢼㏿䝕䞊䝍䜢⏝䛔䜛䠈䛭䛧䛶䠈ィ ᪉఩䜢ኚ䛘䜛䠈䛸䛔䛳䛯䛣䛸䛜䛹䛾⛬ᗘィ 䛥䜜䜛⃰ᗘ䛻ᙳ㡪䜢୚䛘䜛䛾䛛᫂䜙䛛䛻䛩䜛Ⅼ䜢௒ᚋ䛾┠ᶆ䛸䛩䜛䠊― 44 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-17䛇䜰䜲䝇䜰䝹䝆䞊䛾䝸䝰䞊䝖䝉䞁䝅䞁䜾ᡭἲ䛾㛤Ⓨ
Development of remote sensing method for ice algae䠄◊✲௦⾲⪅ྡ䠅 ᮅ㝰㻌 ᗣྖ㻌 䠄ᮾி㎰ᴗ኱Ꮫ㻌 ⏕≀⏘ᴗᏛ㒊䠅
Koji Asakuma 㻌 䠄Tokyo University of Agriculture 䠅䛆せ᪨䛇 ளᐮᖏᇦ䛻䛚䛡䜛䜰䜲䝇䜰䝹䝆䞊䛻䜘䜛䝞䜲䜸䝬䝇䜢ぢ✚䜒䜛䛯䜑䛻䚸䝺䞊䝄䞊䜢ບ㉳ග※䛧䛶ᾏị୰䛾䜽䝻䝻䝣䜱䝹a䛻䜘䜛⺯ග䜢ほ 䛩䜛䝅䝇䝔䝮䜢㛤Ⓨ୰䛷䛒䜛䚹ほ 䛥䜜䛯⺯ග್䛛䜙䜽䝻䝻䝣䜱䝹a⃰ᗘ䜢ᐃ㔞䛩䜛䛯䜑䛻䛿䚸⎔ቃ䛻䜘䛳䛶ኚ໬䛩䜛ᾏị䛾㏱㐣≉ᛶ䜢▱䜛ᚲせ䛜䛒䜛䚹ᮏᖺᗘ䛿䚸⤖ị ᗘ䜢ኚ໬䛥䛫䛶సᡂ䛧䛯ேᕤᾏị䛾ᾘᩓಀᩘ䜢 ᐃ䛧䛯䚹䛭䛾⤖ᯝ䚸䜽䝻䝻䝣䜱䝹a䛾⺯ග䛷䛒䜛680 nm 䛻䛚䛔䛶䛿䚸⤖ị ᗘ䛜ప䛟䛺䜛䛻䛴䜜䛶ᾘᩓಀᩘ䛜ῶᑡ䛩䜛ഴྥ䛜䜏䜙䜜䛯䚹୍᪉䚸ບ㉳ග䛷䛒䜛405 nm 䛻䛚䛔䛶䛿⤖ị ᗘ䛸䛾㛵㐃ᛶ䛿ぢ䜙䜜䛺䛛䛳䛯䚹䛆Abstract䛇 In order to estimate the biomass of ice algae in the subarctic area, the fluorescence observing
system with using violet laser light as an excitation light source for chlorophyll a in sea ice has been developing.
To determine the chlorophyll a concentration from the observed fluorescence intensity, it is necessary to know
the transmission properties of sea ice which changes depending on the freezing environment. In this current
year, the extinction coefficient of the artificial sea ice was obtained with various changed the frozen
temperature. As a result, there was a tendency for the extinction coefficient at 680 nm, which is wavelength of
the fluorescence of chlorophyll a, to decrease as the freezing temperature decreases. On the other hand, no
relation between the coefficient at 405 nm which is the excitation light with the freezing temperature was found.

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┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

䠏

ᴟᇦ䚸ளᐮᖏᇦ䛾⏕≀⎔ቃ䜢䝰䝙䝍䝸䞁䜾䛩䜛䛖䛘䛷䚸ị䛾୰䛷⏕ά䜢䛩䜛⸴㢮䛷䛒䜛䜰䜲䝇䜰䝹䝆䞊䛾Ꮡᅾ䛿㔜せ䛷䛒䜛䚹䜰䜲䝇䜰䝹䝆䞊䜢䝰䝙䝍䝸䞁䜾䛩䜛䛯䜑䛻䛿䚸ேຊ䛷ᾏị䜢䝃䞁䝥䝸䞁䜾䛩䜛ᚲせ䛜䛒䜛䛜䚸኱ኚ䛺㔜ປാ䛷䛒䜛䚹䛣䛾䛯䜑䚸ᗈ⠊ᅖ䛾ほ 䜢ᐇ⌧䛩䜛䛯䜑䛾䝸䝰䞊䝖䝉䞁䝅䞁䜾ᡭἲ䛜ᮃ䜎䜜䛶䛔䜛䚹ᮏ◊✲䛿䚸ịୖ➃䛛䜙ບ㉳ග䜢↷ᑕ䛧䛶䚸ᾏị୰䛾䜰䜲䝇䜰䝹䝆䞊䛻䜘䜛⺯ග䜢ほ 䛩䜛᪉ἲ䛾㛤Ⓨ䜢┠ⓗ䛸䛩䜛䚹䛧䛛䛧䛺䛜䜙䚸ᾏịୖ➃䛷ほ 䛥䜜䛯⺯ග䛛䜙䜽䝻䝻䝣䜱䝹a⃰ᗘ䜢ᐃ㔞䛩䜛䛻䛿䚸ᾏịෆ㒊䛾ᨺᑕఏ㐩㐣⛬䜢▱䜛ᚲせ䛜䛒䜛䚹ᾏị䛿䛭䛾⏕ᡂ㐣⛬䛻䜘䜚㏱㐣≉ᛶ䛜ᵝ䚻䛻ኚ໬䛩䜛䚹䛣䛾䛯䜑䚸༙ᑟయ䝺䞊䝄䞊䜢⏝䛔䛶ບ㉳ග䛺䜙䜃䛻⺯ග䛻ᑐ䛩䜛ᾏị䛾⤖ị ᗘ䛸㏱㐣≉ᛶ䛾㛵ಀ䛾ᑟฟ䜢ᐇ᪋䛧䛯䚹䠄䠍䠅䝃䝻䝬†䜢ᑐ㇟䛻䚸ỶỈ†䛾ሷศ⃰ᗘ䠄32 ‰䠅䛻㏆䛔ேᕤᾏỈ䛛䜙䚸␲ఝᾏị䜢సᡂ䛧䚸䛣䛾␲ఝᾏị䛾ୗ䛻䜽䝻䝻䝣䜱䝹a ᶆ‽≀㉁ 䝞䜲䜸䝺䝑䝖䝺䞊䝄䞊䜢㓄⨨䛧␲ఝⓗ䛻䜰䜲䝇䜰䝹䝆䞊䜢෌⌧䛩䜛⎔ቃ䜢ᵓ⠏䛧䜎䛧䛯䚹䛣䛾 䠄405 nm, 200 mW,
CW䠅␲ఝᾏịୖ➃䛛䜙ບ㉳ග䛷䛒䜛༙ᑟయ䝞䜲䜸䝺䝑䝖䝺䞊䝄䞊ග䠄405
nm, 200 mW䠅䜢↷ᑕ䛧䚸ᾏịୗ㒊䛛䜙ᡠ䛳䛶䛟䜛⺯ග䠄680 nm䠅䜢䝇␲ఝᾏị䠄32 ‰䠅䝨䜽䝖䝻䝯䞊䝍䞊䠄Ocean Optiocs, USB-2000䠅䛷ほ 䛩䜛䚸␲ఝ䜰䜲䝇䜰䝹䝆䞊ほ 䝅䝇䝔䝮䜢ᵓ⠏䛧䜎䛧䛯䠄ᅗ䠍䠅䚹䛣䜜䛻䜘䜚䚸䜰䜲䝇䝁䜰䜰䜲䝇䜰䝹䝆䞊
䛺䛹䜢᥇ྲྀ䛫䛪䛻䚸㠀◚ቯ䛷ỶỈ†䛾ᾏị୰䛻᳇ᜥ䛩䜛䜰䜲䝇䜰䝹䝆䞊䛾䝞䜲䜸䝬䝇䜢ィ 䛩䜛ྍ⬟ᛶ䜢ぢ䛔ฟ䛧䜎䛧䛯䚹䠄䠎䠅ᾏị୰䛾䜰䜲䝇䜰䝹䝆䞊䛻䜘䜛⺯ග್䛛䜙䚸䜽䝻䝻䝣䜱䝹a ⃰ᗘ䜢ᅗ1 䜰䜲䝇䜰䝹䝆䞊ィ 䛾ᵝᏊᐃ㔞䛩䜛䛯䜑䛻䛿䚸ᾏịෆ䛾ᨺᑕఏ㐩㐣⛬䜢᫂䜙䛛䛻䛩䜛ᚲせ䛜䛒䜚䜎䛩䚹⤖ị ᗘ䜢-3 Υ䛛䜙-8 Υ䜎䛷䛭䜜䛮䜜䛻ኚ᭦䛧䛯␲ఝᾏị䜢సᡂ䛧䛶䚸䛭䜜䛮䜜䛾㏱㐣ගᙉᗘ䜢ほ 䛧䜎䛧䛯䚹⺯ග䛷䛒䜛㉥Ⰽග
䠄 680 nm䛷䛿䚸⤖ị ᗘ䜢ప䛟䛩䜛䛻䛴䜜䛶ᾘᩓಀᩘ䛜ᑠ䛥䛟䛺䜛
䠄㏱㐣⋡䛜㧗䛟䛺䜛䠅ഴྥ䛻䛒䜛䛣䛸䛜䜟䛛䜚䜎䛧䛯䠄ᅗ2䠅䚹䛣䜜䛿䚸ỈศᏊ䛻䜘䜛྾཰䛻䜘䜛䜒䛾䛸⪃䛘䜙䜜䜎䛩䚹䠄䠏䠅୍᪉䚸ບ㉳ග䠄405 nm䠅䛷䛿䚸ᾘᩓಀᩘ䛜ᵝ䚻䛷䛒䜚䚸䛣䛾⠊ᅖ䛷䛾⤖ị ᗘ䛸䛾㛵㐃ᛶ䛿ぢ䛔䛰䛫䜎䛫䜣䛷䛧䛯䚹䛣䜜䛿䚸ᾏị䛾⤖ᬗᵓ㐀䠄Grine; ▷෉≧⤖ᬗ䠅䛸ሷ㢮䛾ᢤ䛡䛯Ꮝ䠄Braine channel䠅䛻䜘䜛ᩓ஘䛻䜘䜛䜒䛾䛸⪃䛘䜙䜜䜎䛩䚹௒ᚋ䚸2Ἴ㛗䝺䞊䝄䞊䜢⏝䛔䛶䜘䜚ከ䛟䛾⤫ィ್䜢䛸䜛䛣䛸䛻䜘䜚䚸䜰䜲䝇䜰䝹䝆䞊䛾䝞䜲䜸䝬䝇䛾䜏
ᅗ2 680 nm 䛻䛚䛡䜛䚸␲ఝᾏị䛾䛺䜙䛪䚸䛭䛾᳇ᜥ⎔ቃ䠄ᾏịᵓ㐀䠅䛾ྠ᫬ほ 䛜ྍ⬟䛜♧၀䛥䜜䜎䛩䚹⤖ị ᗘ䛸㏱㐣⋡䛾㛵ಀ㛤Ⓨ䛧䛯ᡭἲ䛿䚸䝺䞊䝄䞊ᦚ㍕UAV䠄↓ே⯟✵ᶵ䠅䚸ROV䠄↓ே₯Ỉᶵ䠅䛻㌿⏝ணᐃ䛷䛩䚹

ᡂᯝᒎ㛤䛾
≧ἣ

― 45 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-21䛇᳃ᯘ䛾஧᪉ྥᛶ཯ᑕ⋡ᐇ 䝕䞊䝍䛸䝅䝭䝳䝺䞊䝅䝵䞁䝰䝕䝹䜢⏝䛔䛯⾨ᫍ཯ᑕ⋡䛾᳨ドᐇ㦂
Validation study of land surface reflectance from satellite at forest using BRDF simulationand observational data䠄◊✲௦⾲⪅ྡ䠅 ᯇᒣ㻌 ὒ䠄㤳㒔኱Ꮫᮾி㻌 ᆅ⌮Ꮫᩍᐊ䠅
Hiroshi Matsuyama 䠄Department of Geography, Tokyo Metropolitan University䠅䛆せ᪨䛇㻌 ᮏ◊✲䛷䛿䚸BRDF䛾᥎ᐃ䛻ᚲせ䛺䝟䝷䝯䞊䝍䛾୍䛴䛷䛒䜛᳜⏕䛾DSMసᡂ䛻㝿䛧䚸UAV䛷᧜ᙳ䛧䛯⏬ീ䜢฼⏝䛧䛶DSM䜢෌⌧䛩䜛䛣䛸䜢┠ⓗ䛸䛧䛶䚸ᩳ䜑ど⏬ീ䛾฼⏝䜢᳨ウ䛧䜎䛧䛯䚹ᡂᯝ䛸䛧䛶䚸ᗈゅ䜹䝯䝷䛷᧜ᙳ䛧䛯┤ୗど⏬ീ䛾䜏䜢⏝䛔䛶సᡂ䛧䛯DSM䛿䚸ྠ䛨䜹䝯䝷䛾ᩳ䜑ど⏬ീ䜢⏝䛔䛶సᡂ䛧䛯DSM䛻㏆䛔䛣䛸䛜ศ䛛䜚䜎䛧䛯䚹௒ᚋ䚸䛣䛾DSMసᡂᡭἲ䛸BRDF᥎ᐃ䝰䝕䝹䜢฼⏝䛩䜛䛣䛸䛷䚸௵ព䛾ኴ㝧᮲௳䞉ほ ᮲௳䛷ᚓ䜙䜜䜛཯ᑕ⋡䜢᥎ᐃ䛷䛝䜛䜘䛖䛻䛺䜚䜎䛩䚹䛭䛧䛶䚸⾨ᫍ䛾ほ ᮲௳䛸➼䛧䛔᮲௳ୗ䛷䛾཯ᑕ⋡䛾᥎ᐃ䚸⾨ᫍ཯ᑕ⋡䛻㛵䛩䜛ᆅୖ᳨ドᐇ㦂䛜⾜䜟䜜䜛䛣䛸䛜ᮇᚅ䛥䜜䜎䛩䚹㻌䛆Abstract䛇 㻌 In this study, we tried to create more detail DSM which is one of the parameters of estimating BRDF,
based on images taken by UAV. We used oblique images for making precise DSM along with nadir
images. When we used wide angle camera, we can get high-quality DSM using nadir images alonethat is compatible as DSM created by oblique images as well. In the near future, we can estimate
canopy reflectance under any condition of the sun and radiometer by using detail DSM and BRDF
simulator. Also, it is expected to carry out simultaneous observation of the passage of satellites.

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◊✲䛾
ᡂᯝ

㻌 ᮏ◊✲䛾⫼ᬒ䛻䛿䚸UAV䜢౑⏝䛧䛯஧᪉ྥᛶ཯ᑕศᕸ㛵ᩘ䠄BRDF䠅ほ ཬ䜃䝅䝭䝳䝺䞊䝅䝵䞁䛻ᇶ䛵䛟
BRDF䛾᥎ᐃ䛜ᣲ䛢䜙䜜䜎䛩䚹ᆅ⾲㠃䝰䝙䝍䝸䞁䜾䛻䛚䛔䛶᭱㔜せ䛷䛒䜛ᆅୖほ ≀䛾཯ᑕ⋡䛿䚸ほ ᑐ㇟䛾✀㢮䞉ᙧ≧䞉ほ ᫬䛾ኴ㝧䛸䝉䞁䝃䛾఩⨨㛵ಀ䛻䜘䛳䛶኱䛝䛟ኚ໬䛧䜎䛩䚹⵳✚䛥䜜䛯ほ 䝕䞊䝍䛛䜙䜘䜚⢭ᗘ䛾㧗䛔BRDF᥎ᐃ䜢⾜䛖䛯䜑䛻䚸⌧ᐇ䜢཯ᫎ䛧䛯DSM䛜ᚲせ䛻䛺䛳䛶䛝䜎䛩䚹䛣䛾䛯䜑䚸ᮏ◊✲䛾┠ⓗ䛿䚸UAV䜘䜚᧜ᙳ䛧䛯⏬ീ䜢ඖ䛻䜘䜚෌⌧ᛶ䛾㧗䛔3D䝰䝕䝹䞉DSM䛾సᡂ䜢⾜䛖䛣䛸䛷䛩䚹2016ᖺ8᭶䛻䚸ඵ䞄ᓅ༡㯄䛻䛶UAV䛻䜘䜛᳃ᯘୖ✵䛾᧜ᙳ䜢⾜䛔䜎䛧䛯䚹」ᩘ䛾ᩳ䜑ど⏬ീ䜢ྲྀᚓ䛧䚸UAV䜘䜚ᚓ䜙䜜䛯᧜ᙳ⏬ീ䜢฼⏝䛧3D䝰䝕䝹୪䜃䛻DSM䜢సᡂ䛧䚸䛣䜜䜙䛾ẚ㍑䜢⾜䛔䜎䛧䛯䚹䠄䠍䠅௒ᅇ䛾◊✲䛻䛚䛔䛶䛿䚸UAV䛾」ᩘᅇ䛾䝣䝷䜲䝖䛻䜘䜚」ᩘ᪉ྥ
䛾ᩳ䜑ど⏬ീ䜢᧜ᙳ䛧䛶䝰䝕䝹సᡂ䛻฼⏝䛧䜎䛧䛯䚹UAV᧜ᙳ෗┿
䛛䜙3D䝰䝕䝹䛸DSM䜢సᡂ䛩䜛㝿䛻PhotoScan䠄3D䝰䝕䝹సᡂ䝋䝣䝖䠅䜢౑⏝䛧䜎䛧䛯䚹䛣䛾䝋䝣䝖䛻䛚䛔䛶䚸⏬ീ䛻෗䛳䛶䛔䛺䛔ᆅ≀䛿෌⌧䛷䛝䜎䛫䜣䚹ᶞ㛫䜔ᮌ䛾ᙧ≧䛺䛹䜢䜘䜚⌧ᐇ䛻༶䛧䛯ᙧ䛷DSM䛻཯ᫎ䛩䜛䛯䜑䛻䜒䚸ᩳ䜑ど⏬ീ䛾฼⏝䛜᭷⏝䛸䛥䜜䛶䛔䜎䛩䚹ᮏ◊✲䛾䜘䛖䛻」ᩘ᪉ྥ䛾ᩳ䜑ど䜢฼⏝䛧䛯䝰䝕䝹సᡂ䛾஦౛䛿ᑡ䛺䛟䚸䝰䝕䝹䛾෌⌧ᛶྥୖ䛻」ᩘ᪉ྥ䛾ᩳ䜑ど⏬ീ䛜᭷⏝䛷䛒䜛䛛᳨ウ䛧䜎䛧䛯䚹䠄䠎䠅䛭䛾⤖ᯝ䚸ᗈゅ䜹䝯䝷䜢฼⏝䛩䜛䛸1ᯛ䛾┤ୗど⏬ീ䛻䛚䛔䛶䜒ᩳ䜑ど䛻㏆䛔᝟ሗ䜢᭷䛧䛶䛔䜛䛯䜑䚸ᩳ䜑ど⏬ീ䜢฼⏝䛫䛪䛸䜒⡆౽䛻ᩳ䜑ど䜢฼⏝䛧䛯䝰䝕䝹䛻㏆䛔䜒䛾䛜సᡂ䛷䛝䜛ྍ⬟ᛶ䛜䛒䜛䛣䛸䛜ศ䛛䜚䜎䛧䛯䠄ᅗ1䠅䚹䜎䛯UAV䛾䝣䝷䜲䝖䝥䝷䞁䜢䚸୍⯡ⓗ䛻ᬑཬ䛧䛶䛔䜛
Single Grid Mission䜘䜚䚸㻝䝣䝷䜲䝖䛷㻞᪉ྥ䛛䜙᧜ᙳ䛷䛝䜛Double
Grid Mission䛻䛩䜛᪉䛜䚸」ᩘ᪉ྥ䛛䜙䛾᧜ᙳ䛻䛚䛔䛶᭷⏝䛷䛒䜛䛣䛸䛜ุ᫂䛧䜎䛧䛯䠄ᅗ2䠅䚹䠄䠏䠅ᮏ◊✲䛷䛿䚸᧜ᙳ᫬䛾ኳೃ䛾ᙳ㡪䜢ᙉ䛟ཷ䛡䛯䛯䜑䚸⏬ീ䛾㍤ᗘ䛜୙ᆒ୍䛻䛺䜚䚸3D䝰䝕䝹ཬ䜃DSMసᡂ䛻ᝏᙳ㡪䜢ཬ䜌䛧䛶䛔䜎䛧䛯䚹䜎䛯䚸
ᗈゅ䜹䝯䝷䛿᝟ሗ䜢ቑ䜔䛩༙㠃䚸⏬ീෆ䛻ṍ䜏䛜ከ䛟䚸䝰䝕䝹సᡂ䛻䜒ᙳ㡪䛧䛶䛔䜛䛸⪃䛘䜙䜜䜎䛩䚹䛣䜜䜙䜢⪃៖䛩䜛䛣䛸䛷䚸䜘䜚᫂☜䛻ᩳ䜑ど䜢ຍ䛘䛯฼Ⅼ䛜ุ᫂䛧䚸෌⌧ᛶ䛾ྥୖ䛻䛴䛺䛜䜛䛸⪃䛘䜙䜜䜎䛩䚹

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

ᅗ1

DSMẚ㍑

ᅗ2 UAV䝣䝷䜲䝖⤒㊰㻌 ฼⏝䛧䛯ᡭἲ䛿䜎䛰᳨ウ䛜୙༑ศ䛷䛒䜚䚸௚䛾◊✲䜈䛾ά⏝䜔ᐇ⏝໬➼䛿䛥䜜䛶䛔䜎䛫䜣䚹䛧䛛䛧䛺䛜䜙䚸௒ᚋ䚸ᮏ◊✲䛾⤖ᯝᚓ䜙䜜䛯㻰㻿㻹䜢㻮㻾㻰㻲䝰䝕䝹䛾ቃ⏺᮲௳䛸䛧䛶䝅䝭䝳䝺䞊䝅䝵䞁䜢⾜䛖䛣䛸䛷䚸௵ព䛾ኴ㝧᮲௳䞉ほ ᮲௳䛷ᚓ䜙䜜䜛཯ᑕ⋡䜢᥎ᐃ䛷䛝䜛䜘䛖䛻䛺䜚䜎䛩䚹䛣䜜䛻䜘䜚䚸⾨ᫍ䛾ほ ᮲௳䛸➼䛧䛔᮲௳ୗ䛷䛾཯ᑕ⋡䜢ᚓ䜛䛣䛸䛜䛷䛝䚸⾨ᫍ཯ᑕ⋡䛻㛵䛩䜛ᆅୖ᳨ドᐇ㦂䛜ྍ⬟䛻䛺䜚䜎䛩䚹㻌― 46 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-23䛇ගᏛᫎീ䞉䝺䞊䝎䞊䝕䞊䝍䞉⾨ᫍ⏬ീ䝕䞊䝍䛻䜘䜛ⅆᒣᄇ↮䛾ືែゎᯒ
Analysis of dynamic properties of volcanic clouds on the bases of optical images, radar data and satellite
image data䠄◊✲௦⾲⪅ྡ䠅ᮌୗ ⣖ṇ (㮵ඣᓥ኱Ꮫ㻌 䞉ᩍ⫱Ꮫ㒊ᩍ⫱ᐇ㊶⥲ྜ䝉䞁䝍䞊)
Kisei Kinoshita㻌 䠄Kagoshima University䞉 Center for Educational Research andDevelopment, Faculty of Education 䠅䛆せ᪨䛇㮵ඣᓥ኱-⇃ᮏ኱䜾䝹䞊䝥䛷䛿䚸ᵝ䚻䛺ᫎീほ 䛻䜘䛳䛶ᄇ↮䛾Ⓨ㐩䛸⛣ὶᣑᩓ䛾ᙧែ䜢㏣✲䛧䛶᮶䛯䚹ᗈᇦ䛾ᣑᩓ䛿⾨ᫍ⏬ീ䛛䜙ุ䜛䛜䚸䛭䜜䜢䜒䛯䜙䛧䛯ᄇ↮ᨺฟ䛾᫬㛫⤒㐣䛸䛾㛵ಀ䜒㔜せ䛷䛒䜛䚹䛥䜙䛻䝺䞊䝎⏬ീ䛻䜘䛳䛶ὶྥ䛜ᐜ᫆䛻ศ䛛䜚䚸ෆ㒊ᵓ㐀䛜ぢ䛘䜛ྍ⬟ᛶ䛜䛒䜛䚹ᮏᖺᗘ䛿2015-2016ᖺ䛾㜿⸽୰ᓅ䛸ᱜᓥ䛾ᄇ↮άື䜢ከ㠃ⓗ䛻ゎᯒ䛧䛶䚸ᄇ↮䛾ືែ䜢ゎ᫂䛧䛯䚹

䛆Abstract䛇 Results of web-camera observation of eruption clouds at Aso and Sakurajima volcanoes in Kyushu,
Japan in 2015 and 2016 were analysed, combined with the satellite image data. Furthermore, those of
Sakurajima volcano were compared with radar images to clarify the advection and diffusion of them.

䠍
⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

⾨ᫍ䛻䜘䜛ⅆᒣᄇⅆ䛾ほ ┘どయไ䛿඘ᐇ䛧䚸⾨ᫍ⏬ീ䝕䞊䝍䛾⵳✚䜒㐍䜣䛷䛔䜛䚹䛧䛛䛧䛭䛾ά⏝䛿ᮍ䛰≉䛻኱䛝䛺ᄇⅆ䛻㝈䜙䜜䛶䛔䜛䚹ᮏ◊✲䛾┠ⓗ䛿ᄇⅆ䛾⾨ᫍ┘ど䛻䜘䜛᳨ฟྍ⬟ᛶ䚸㝆㞵䝺䞊䝎䞊䛻䜘䜛ほྍ⬟ᛶ䜢ᗈ䛢䜛ᇶ♏䛸䛧䛶䚸᭱㏆䜎䛷㜿⸽䜔ᱜᓥ䛷䛧䜀䛧䜀ぢ䜙䜜䛯つᶍ䛾ᄇⅆ䛻䛴䛔䛶MODIS䛸ASTER䛾⾨ᫍ䝕䞊䝍䜢ゎᯒ䛧䛶ྍど䞉㏆㉥እ䜴䜵䝤䜹䝯䝷䜔඲ኳ䜹䝯䝷➼䛾ᆅୖᫎീほ 䞉X䝞䞁䝗MP䝺䞊䝎䞊ほ 䛾⤖ᯝ䛸↷ྜ䛧䚸ᄇ↮ᨺฟ䛾᫬㛫⤒㐣䜢᳨ウ䛧䛯䚹䠄䠍䠅MODIS⾨ᫍ䝕䞊䝍ゎᯒ䛷䛿䚸ᮏ䜾䝹䞊䝥䛷㛤Ⓨ䛧䛶᮶䛯⇕㉥እ12,11μmᕪ⏬ീ䛜ከ䛟䛾ሙྜ䛻᭱䜒᭷ຠ䛷䛒䜚䚸㜿⸽䜔ᱜᓥ䛾ᵝ䚻䛺䝇䜿䞊䝹䛾ᄇ↮䜢䛧䜀䛧䜀᳨ฟ䛷䛝䜛䠄ᅗ䠍䠅䚹䛣䜜䛻䜘䜚䚸㟼ṆẼ㇟⾨ᫍ䛾⭾኱䛺䝕䞊䝍䛛䜙䛾᳨ฟྍ⬟ᛶ䜢☜ᐇ䛻ᗈ䛢䜛䛣䛸䛜ฟ᮶䜛䚹
䠄䠎䠅ᵝ䚻䛺ᄇ↮ᫎീ䛸↷ྜ䛧䛶䚸X䝞䞁䝗MP䝺䞊䝎䞊䝕䞊䝍䛻ᆅᙧ䜶䝁䞊䜢ᾘ䛩MTI䝣䜱䝹䝍䞊ฎ⌮䛧䛯⏬ീ䛷䛿ᄇ↮㧗ᗘ1000-1500m⣭䛾⇿Ⓨᄇ↮䛷䜒᳨ฟ䛻᭷ຠ䛷䛒䜛䛣䛸䛜᫂䜙䛛䛻䛺䛳䛯䠄ᅗ䠎䠅䚹
ᅗ1䠄䠏䠅ᱜᓥ䛾ᄇ↮άື䛾ከ䛟䛾஦౛䛻䛴䛔䛶䚸ከⅬほ 䛸⾨ᫍ⏬ീ䞉䝺䞊䝎䞊⏬ീ䜢୍䛴䛾䝃䜲䝖䛻䜎䛸䜑䚸ከゅⓗ᳨ウ䛾ᇶ♏㈨ᩱ䛸䛧䛯䚹

ᅗ1.

ᅗ2.

䕿䕿䛾䝅䝇䝔䝮

Terra/MODIS b32-b31⏬ീ(2015.1.7_10:55JST)

ᆶỈẼ㇟䝺䞊䝎䞊MTIฎ⌮Ỉᖹ೫Ἴ⏬ീ

ᅗ2(2015.1.7_09:19JST)

䠏⾨ᫍ䛻䜘䜛ⅆᒣᄇⅆ䛾᳨ฟྍ⬟ᛶ䜢ᗈ䛢䜛䛣䛸䛿䚸⯟✵ᶵᏳ඲㐠⯟䛾䛯䜑䛾ほ ┘ど䜔ఫẸ䛻䛸䛳䛶䛾㝆⅊ண 䛾◊✲㛤Ⓨ䛾ᇶ♏㈨ᩱ䛸䛺䜛䚹ᡂᯝᒎ㛤䛾 䜎䛯䚸ᫎീほ 䞉⾨ᫍ⏬ീ䛸䝺䞊䝎䞊⏬ീ䛾ᑐᛂ䛿䚸䜎䛰䜋䛸䜣䛹䜟䛛䛳䛶䛔䛺䛔㝆Ỉ᫬䛾⇿Ⓨⓗᄇⅆ䛾ඛ➃ⓗẼ㇟䝺䞊䝎䞊䛻䜘䜛ほ ◊✲䛾㊊䛜䛛䜚䛸䛺䜛䚹≧ἣ

― 47 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-24䛇⣸እ䝷䝬䞁䝷䜲䝎䞊䛻䜘䜛ᑐὶᅪ䜶䜰䝻䝌䝹䛾ගᏛⓗᛶ㉁ཬ䜃Ỉ⵨Ẽᙳ㡪䛻㛵䛩䜛◊✲Study of the optical and hygroscopic properties of the tropospheric aerosols using a UV Raman Lidar䠄◊✲௦⾲⪅ྡ䠅 ᮧᒣ㻌 ฼ᖾ㻌 䠄ᮾிᾏὒ኱Ꮫ䞉ᾏὒᕤᏛ㒊䠅
Toshiyuki Murayama 㻌 䠄Tokyo University of Marine Science and Technology 䠅䛆せ᪨䛇ᮾி㒔ᚰ䛻఩⨨䛩䜛ᮾிᾏὒ኱Ꮫ㉺୰ᓥ䜻䝱䞁䝟䝇䛻䛶䚸355nm䛾⣸እ䝺䞊䝄䞊䜢⏝䛔䛯䝭䞊䞉䝷䝬䞁䝷䜲䝎䞊䛻䜘䛳䛶ᑐὶᅪ䜶䜰䝻䝌䝹䛾ගᏛⓗᛶ㉁ཬ䜃䛭䛾‵ᗘᙳ㡪䜢ᐃᖖⓗ䛻ほ 䛩䜛䛯䜑䛾ᡭἲ䚸ゎᯒ᪉ἲ䜢䝃䞁䝣䜷䝖䝯䞊䝍䞊ほ 䛸⤌䜏ྜ䜟䛫☜❧䛩䜛䛣䛸䜢ᮏᖺᗘ䛿┠ⓗ䛸䛩䜛䚹⌧ᅾ䚸ᡴ䛱ୖ䛢䛾ணᐃ䛥䜜䛶䛔䜛
EarthCARE䛷䛿355nm䛷䛾HSRL䜢ᦚ㍕䛩䜛䛯䜑䚸䛭䛾ᆅୖ᳨ド䜔䚸㒔ᚰ‴ᓊᇦ䛻䛒䜛䛯䜑኱Ẽởᰁ䜶䜰䝻䝌䝹➼䛾ᾏ㝣㢼ᚠ⎔䛺䛹⯆࿡䛒䜛䜲䝧䞁䝖䛾ほ ᆅⅬ䛸䛧䛶䜒ᮇᚅ䛥䜜䜛䚹

䛆Abstract䛇 To establish how to retrieve the optical properties of tropospheric aerosols and the effect of the humidity
by using a 355 nm UV Mie-Raman lidar in the central of Tokyo combined with Sunphotometere
observation. The method is expected as a validation of the spaceborne lidar EarthCARE, 355 nm HSRL.
A sea-land breeze circulation㻌 of air-pollution aerosols is also expected because this site locates at the
Bay area.

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

ᑐὶᅪ䜶䜰䝻䝌䝹䛾ᐃ㔞ⓗ䛺䝷䜲䝎䞊ほ 䛻䛿䝷䝬䞁䝷䜲䝎䞊䛜୺䛻⏝䛔䜙䜜䛶䛔䜛䚹ᮏ◊✲䛾┠ⓗ䛿䚸ᮾிᾏὒ኱Ꮫ䠄Ụᮾ༊㉺୰ᓥ䠅䛻䛶2003ᖺ䛻〇స䛧䛯ከἼ㛗䝭䞊䞉䝷䝬䞁䝷䜲䝎䞊䝅䝇䝔䝮䛾୍㒊䜢⣸እ䝷䝬䞁䝷䜲䝎䞊䛸䛧䛶ᐃᖖⓗ䛺ᑐὶᅪ䜶䜰䝻䝌䝹䛸Ỉ⵨Ẽΰྜẚ䛾ほ 䜢䚸᪥୰䛾䝃䞁䝣䜷䝖䝯䞊䝍䞊ほ 䛸⤫ྜ䛧䛶䚸ᑐὶᅪ䜰䜶䝻䝌䝻䝹䛾ගᏛⓗᛶ㉁䜢ᑟ䛟ᡭἲ䜢☜❧䛩䜛䛣䛸䜢┠ⓗ䛸䛧䛯䚹䛣䛾䛯䜑䚸䝷䜲䝎䞊䛿᪥୰䛛䜙ኪ㛫䜎䛷䛾㐃⥆䛧䛯 ᐃ䜢⾜䛔䚸᪥୰䛿䝃䞁䝣䜷䝖䝯䞊䝍䞊䛾ྍど䞉⣸እ䝏䝱䝛䞁䝹䛛䜙355nm䛷䛾኱Ẽ䜒ගᏛⓗཌ䛥䜢ồ䜑䛯䚹

䠄䠍䠅Nd:YAG䝺䞊䝄䞊䛾➨䠏㧗ㄪἼ䛷䛒䜛355nm䛾䝺䞊䝄䞊ග䜢⏝䛔䛯䝷䝬䞁䝷䜲䝎䞊䝅䝇䝔䝮䜢ᩚഛ䛧䜎䛧䛯䚹㷝㔝䛾䝷䝆䜸䝌䞁䝕䝕䞊䝍䜢⏝䛔䚸ᚑ᮶䛾ゎᯒ᪉ἲ䜢㐺⏝䛧䚸⃰ᗘ䛾ⷧ䛔᪥ᖖⓗ䛺䜶䜰䝻䝌䝹䛻ᑐ䛧䛶䜒䚸䜶䜰䝻䝌䝹䛾ᚋ᪉ᩓ஘ಀᩘ䚸ᾘᩓಀᩘ䚸䝷䜲䝎䞊ẚ䚸Ỉ⵨Ẽΰྜẚ䛾ᑟฟ䛜ኪ㛫ྍ⬟䛷䛒䜛䛣䛸䜢♧䛧䜎䛧䛯䠄ᅗ䠍䠅䠄䠎䠅᪥୰䛾䝃䞁䝣䜷䝖䝯䞊䝍䞊ほ 䛸䝷䜲䝎䞊䛾䝭䞊ᩓ஘ಙྕ䛛䜙᪥୰䛻䛚䛔䛶䜒䜶䜰䝻䝌䝹䛾䝷䜲䝎䞊ẚ䜢ᑟฟ䛩䜛䛣䛸䛜ྍ⬟䛷䛒䜛䛣䛸䜢♧䛧䚸ኪ㛫䛾್䛸䜒኱䛝䛺䛪䜜䛾䛺䛔䛣䛸䜢☜ㄆ䛧䜎䛧䛯䚹䠄䠏䠅ᬕኳ᫬䛻䛚䛔䛶䛿䚸䛣䛾䜘䛖䛺ᰯṇ䛥䜜䛯䝃䞁䝣䜷䝖䝯䞊䝍䞊䛸䝷䝬䞁䝷䜲䝎䞊ほ 䛾᫨ኪ㛫䜢㏻䛨䛯 ᐃ䜢⾜䛖䛣䛸䛻䜘䛳䛶䚸䛣䛣䛷♧䛧䛯䜘䛖䛺䝷䜲䝎䞊ẚ➼䛾ヲ⣽䛺㆟ㄽ䛜ྍ⬟䛻䛺䜛䛣䛸䜢♧䛧䜎䛧䛯䚹䛣䜜䛻䜘䜚䚸ᮾி㒔ᚰ䛾኱Ẽ䜶䜰䝻䝌䝹䛾ගᏛ≉ᛶཬ䜃䚸䛭䛾䛸䛝䛾Ỉ⵨Ẽΰྜẚ䛾㖄┤ศᕸ᝟ሗ䛛䜙䚸ᑐὶᅪ䜶䜰䝻䝌䝹䛾≉ᚩ䜢ᢳฟ䛩䜛䛣䛸䛜ྍ⬟䛸䛺䜚䜎䛩䚹ᅗ䠍 ኪ㛫䛾䝷䝬䞁䝷䜲䝎䞊 ᐃ䛷䜶䜰䝻䝌䝹䛾ගᏛ≉ᛶ䜢ồ䜑䜙䜜䜎䛩䚹

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

㛤Ⓨ䛧䛯ᡭἲ䛿ᆅ⌫ほ ⾨ᫍEarthCARE䛻ᦚ㍕䛥䜜䜛355nm HSRL䛾ᆅୖ᳨ド䛸䛧䛶䜒฼⏝䛩䜛䛣䛸䛜ฟ᮶䜎䛩䚹ほ ⿦⨨䞉ᡭἲ䛿⮬ື✌ാ䛧䛶䛔䜛䝅䞊䝻䝯䞊䝍䞊䚸䝇䜹䜲䝷䝆䜸䝯䞊䝍䞊䛸౪䛻䚸䜘䜚⥲ྜⓗ䛺ᒁᆅᚠ⎔䛺䛹䛾ᙳ㡪䜢᥈䜛䛾䛻⏝䛔䜙䜜䜎䛩䚹― 48 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-38䛇
CP-SAR᳨ド⏝UAV䛻ᦚ㍕䛩䜛ⅆᒣ䜺䝇䝉䞁䝃䛾㛤Ⓨ◊✲䠄3䠅ගᏛᘧ䝉䞁䝃㛤Ⓨ
Development of optical volcanic gas sensing system mounted on the UAV verification for CP-SAR䠄◊✲௦⾲⪅ྡ䠅኱๓㻌 ᏹ࿴䠄ᰴᘧ఍♫䝉䞁䝔䞁䝅䜰䠅
Hirokazu Ohmae㻌 䠄Sentencia Corpoation䠅䛆せ᪨䛇䛣䜜䜎䛷䚸ⅆᒣ䜺䝇᳨ฟ䝅䝇䝔䝮䛸䛧䛶≉ᐃ䛾໬Ꮫ⣲Ꮚ䜢⏝䛔䛯䝉䞁䝃䞊㛤Ⓨ䜢⾜䛳䛶䛝䛯䚹୍᪉䚸ከᙬ䛺ⅆᒣ䜺䝇䜢᳨ฟ䛩䜛䛻䛿䚸≉ᐃ䛾ⅆᒣ䜺䝇䛿≉ᐃ䛾ගἼ㛗䛻ᑐ䛧䛶྾཰䜢㉳䛣䛩஦䛛䜙䚸䛭䛾Ἴ㛗䛷䛾ග㔞ῶ⾶䜢ᐃ䛩䜛䛣䛸䛷䚸ⅆᒣ䜺䝇䜢᳨ฟ䛩䜛䛣䛸䛜ฟ᮶䜛䚹䛭䛣䛷䚸䛣䛾ཎ⌮䜢⏝䛔䛶ගᏛᘧⅆᒣ䜺䝇᳨ฟ䝉䞁䝃䝅䝇䝔䝮䜢ᵓ⠏䛩䜛䛣䛸䜢⪃䛘䚸௒ᖺᗘ䛿䚸䛭䛾ගᏛ䝰䝕䝹䛾ᵓ᝿䛸䝉䞁䝃䝅䝇䝔䝮䛾᪉ᘧཬ䜃䛭䛾せ௳䜢ᢳฟ䛩䜛䛣䛸䜢┠ⓗ䛸䛧䛶◊✲㛤Ⓨ䜢⾜䛳䛯䚹㻌We have been developing sensors using specific chemical elements as a volcanic gas detection system.

䛆Abstract䛇 On the other hand, in order to detect a variety of volcanic gases, since a specific volcanic gas absorbs a
specific light wavelength, it is possible to detect a volcanic gas by measuring light attenuation at thatwavelength . Therefore, considering constructing an optical type volcanic gas detection sensor systemusing this principle, this fiscal year, research and development was conducted with the aim of extracting
the concept of the optical model, the method of the sensor system and requirements.

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

䛣䜜䜎䛷䛾᪉ᘧ䛷䛒䜛໬Ꮫ⣲Ꮚ䜢⏝䛔䛯䝉䞁䝃䝅䝇䝔䝮䛾ሙྜ䛿䚸᳨ฟ䜺䝇✀䛻ᛂ䛨䛯⣲Ꮚ䛜」ᩘಶᚲせ䛷ᑠᆺ໬䛜㞴䛧䛔஦䚸䜎䛯㼁㻭㼂ᦚ㍕䛺䛹䛜ᅔ㞴䚸䜒䛧䛟䛿ほ ⠊ᅖ䛜㝈ᐃ䛥䜜䜛䛣䛸䛷䚸ᶵືᛶ䜢㜼ᐖ䛩䜛䚸䛸䛔䛖≧ἣ䛜ᮏ◊✲䛾⫼ᬒ䛸䛧䛶䛒䜛䚹㻌ᮏ◊✲䛾┠ⓗ䛿୍ᗘ䛻ከ✀㢮䛾ⅆᒣ䜺䝇䜢᳨ฟ䛷䛝䜛ගᏛᘧ䜺䝇᳨ฟ䝉䞁䝃䝅䝇䝔䝮䛾㛤Ⓨ䛷䛒䜛䚹㻌䛣䛾䛯䜑䚸ᇶᮏᵓ㐀䛿༢୍ගᏛ⣔䛸䛧ᑠᆺ໬䜢ᛕ㢌䛻ගᏛ⣔䜢᳨ウ䚸᳨ฟ䜺䝇✀䛿䝣䜱䝹䝍䞊䜢ྛ✀౑⏝䛩䜛䛣䛸䛷ᑐᛂ䛩䜛᪉ἲ䜢᥇⏝䛧䚸 ගᏛ⣔䛾᳨ウ䜢ᐇ᪋䛧䛯䚹
䠏Ⅼ௨ୗ䛻䝫䜲䞁䝖䜢⤠䜚㎸䜣䛷グ㍕䛧䛶ୗ䛥䛔䚹䠄䠍䠅㠀ᖖ䛻༢⣧䛺ගᏛ⣔᪉ᘧ䛸䛧䛶ᵓ⠏䛧䚸ⓑⰍග※㻔㼀㻮㻰㻕㻌䜘䜚㞟ගග᮰䜢㻌ᑟἼ㊰䛻↷ᑕ䛧䚸ฟᑕග䜢䝣䜱䝹䝍䞊䛻䜘䜚ศග䛩䜛᪉ᘧ䚸㻌ẚ㍑ⓗᏳ౯䛺༢⣲Ꮚ᳨ฟჾ䜢⏝䛔䜛䛣䛸䛜ྍ⬟䛺ගᏛᘧ䝉䞁䝃䝰䝕䝹㻌䜢᳨ウ䛧䛯䚹㻌䠄ᅗ䠍䠅䚹㻌䛣䜜䛻䜘䜚䚸ග㊰㛗䛾ᣑ኱䛜䛜ྍ⬟䛸䛺䜛䚹
ᅗ1 ගᏛᘧ䝉䞁䝃䛾ཎ⌮ᅗ㻌䠄䠎䠅ගᏛ⣔䛾タィ᮲௳䛸䛧䛶䚸ᮏయ䛾䝃䜲䝈㻞㻜㼏㼙㽢㻞㻜㼏㼙䜢䝧䞊䝇䛸䛧䛯䚹㻌⌧≧ගᏛ䝅䝭䝳䝺䞊䝅䝵䞁⤖ᯝ䛛䜙䛿䚸ග㊰㛗䛸䛧䛶㻝㼙⛬ᗘྍ⬟䛸⪃䛘䛶䛔䜛䚹䛣䜜䛿㼁㻭㼂䠄䝗䝻䞊䞁䠅ᦚ㍕䜢⪃䛘䛶䛾ไ㝈᮲௳䛷䛒䜛䚹኱ᆺ䝗䝻䞊䞁䜢౑⏝ฟ᮶䜛⎔ቃ䛷䛒䜜䜀኱䛝䛟䛶䜒ၥ㢟䛿↓䛔䛸䛿⪃䛘䜙䜜䜛䛜䚸ᐇ㝿䛻౑⏝ฟ᮶䜛ᶵᮦ䚸䛴䜎䜚୍⯡䚸Ᏻ౯䛻䚸䛛䛴ẚ㍑ⓗᡭ㍍䛻౑⏝ฟ᮶䜛ᶵᮦ䜢⪃៖䛧䛯᮲௳䛷䛒䜛䚹㻌•䠄䠏䠅㻞㼙䛾ග㊰㛗䜢ᐇ⌧䛩䜛䛯䜑䛻䛿䚸ගᏛ䝰䝕䝹䛻䛚䛔䛶䚸㻌㻔㼍㻕㻞䛴䛾㙾㠃㒊䛾㊥㞳䜢㞳䛩㻌㻔㼎㻕㙾㠃㒊䛾୍యᵓ㐀䜢ከẁ໬䛩䜛㻌஦䛷ᑐᛂฟ᮶䜛䛾䛷䛿䛺䛔䛛䛸⪃䛘䛶䛔䜛䚹䠄ᅗ䠎䠅䚹•䛣䜜䛻䜘䜚䚸௨ୗ䛾ᘧ䛷⾲䜟䛥䜜䜛䜺䝇䛾྾ගᗘ䚸㻌䈄㻌 㻌 㻌 㻌 㻭䠄䃚䠅䠙䃔䠄䃚䠅㽢㻯㽢㻸㻌㻌䛾㻿㻺䜢ྥୖ䛥䛫䜛䛣䛸䛜ฟ᮶䜛䛸⪃䛘䛶䛔䜛䚹

䠏
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≧ἣ

ᅗ2 ගᏛ⣔ᵓ᝿䝰䝕䝹㻔ᑟἼ㊰䛾཯ᑕ㠃䝰䝕䝹㻕㻌

㛤Ⓨ䛧䛯ᡭἲ䛿྾ගᗘ ᐃᡭἲ䛸䛧䛶䛿㠀ᖖ䛻༢⣧䛷䛒䜛䛯䜑䚸Ᏻ౯䛺 ᐃ䛷䛿㔜せ䛺ᙺ๭䜢ᯝ䛯䛩䛸⪃䛘䛶䛔䜛䚹ᡂᯝ䛾ᐇ⌧䛿ᮍ䛰༙䜀䛷䛒䜛䛜䚸኱ᆺ䛾㉸㛗ග㊰ᆺ ᐃჾ䛸ẚ㍑䛧䛶䚸ᶵືⓗ䛺 ᐃ䛜ᐇ᪋䛷䛝䜛䛣䛸䛛䜙䚸㔝እ ᐃ䛻䛚䛔䛶᭷⏝䛷䛒䜛䚹― 49 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-43䛇㧗ゎീᗘᆅᙧ䞉᳜⏕䝕䞊䝍䜢⏝䛔䛶ᩳ㠃ᔂቯ䜢ண▱䛷䛝䜛䛛䠛
Detection of symptoms of slope failure with high-resolutional topographic and vegetation data䠄◊✲௦⾲⪅ྡ䠅 ᑠⰼ࿴㻌 ᏹஅ㻌 䠄ᰴᘧ఍♫䝡䝆䝵䞁䝔䝑䜽䠅
Hiroyuki Obanawa㻌 䠄VisionTech Inc.䠅
䛆せ᪨䛇

UAV-SfM 㔞ᡭἲ䜢⏝䛔䛶䚸ᩳ㠃ᔂቯ≧ἣ䛚䜘䜃䛭䛾๓඙⌧㇟䛾ほ ྍ⬟ᛶ䜢᳨ウ䛧䛯⤖ᯝ䚸௨ୗ䛾⤖ㄽ䛜ᚓ䜙䜜䛯䚹䐟ᒾ┙ᔂⴠ䚸ⴠ▼䚸䝔䞁䝅䝵䞁䜽䝷䝑䜽䛺䛹䚸୺䛻〄ᆅᩳ㠃䛷Ⓨ⏕䛩䜛䝬䝇䝮䞊䝤䝯䞁䝖䛾᳨ฟ䛚䜘䜃ኚ໬㔞䛾᥎ᐃ䛿ྍ⬟䚹䐠᳜⏕䛷そ䜟䜜䛯ᩳ㠃䛾ኚ໬䜢᳨▱䛩䜛䛣䛸䛿㞴䛧䛔䚹ᆅ㠃䛾ື䛝䛻క䛖ᶞᮌ఩⨨䛾ኚ໬㔞䛾᳨ฟ䜢ヨ䜏䛯䛜䚸ⴠⴥ➼䛻䜘䜛ᶞෙᙧ≧䛾Ꮨ⠇ኚ໬䛾ᙳ㡪䛜኱䛝䛔䚹

䛆Abstract䛇 To detect the symptoms of slope failure such as rock fall, landslide and snow avalanche we have carriedout multi-temporal aerial surveys using UAV-SfM. As a result the following knowledge was acquired. 1)
Mass movement mainly occurred on the bare land such as rock fall and tension crack and their
topographic changes are detectable. 2) Detection of the topographic change of the slope covered by thevegetation is difficult. We have tried to measure the temporal change of tree crown on the ground as a
symptom of mass movement, however, effects of the seasonal change of canopy shape due to leaf falland vegetation growth were so large to detect the ground movement.

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┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

㻌 ᛴᓧ䛺ᒣᆅ䛜ከ䛟䜎䛯㝆Ỉ㔞䜒ከ䛔᪥ᮏ䛷䛿䚸ᆅ䛩䜉䜚䜔ᓴᔂ䜜䛸䛔䛳䛯ᅵ◁⅏ᐖ䛜ከⓎ䛧䛶䛔䜛䚹䛯䛸
䛘䜀䚸2015ᖺ䛻Ⓨ⏕䛧䛯ᅵ◁⅏ᐖ䛾௳ᩘ䛿䚸ᆅ䛩䜉䜚䛜44௳䚸ᓴᔂ䜜䛜599௳䛷䛒䜛䠄ᅜᅵ஺㏻┬, 2015䠅䚹䛭䜜䜙⅏ᐖ䜢ᮍ↛䛻㜵䛠䛒䜛䛔䛿⿕ᐖ䜢㍍ῶ䛩䜛䛯䜑䛻䛿䚸⅏ᐖ䛾ཎᅉ䛸䛺䜛䝬䝇䝮䞊䝤䝯䞁䝖䠄㔜ຊᛶ䛾ᅵ◁⛣ື䠅䛾Ⓨ⏕༴㝤ಶᡤ䛾᥎ᐃ䛚䜘䜃┘どᢏ⾡䛜ᚲせ䛷䛒䜛䚹ᅵ◁⅏ᐖ༴㝤ಶᡤ䛾᥎ᐃ᪉ἲ䛸䛧䛶䚸ᚑ᮶䛿䚸ᩳ㠃䛾ഴᩳ䜔㧗䛥䜢䜒䛸䛻ᅵ◁⅏ᐖ䛜Ⓨ⏕䛩䜛䛚䛭䜜䛾䛒䜛ಶᡤ䠄ᛴഴᩳᆅᔂቯ༴㝤༊ᇦ䠅䛜ᣦᐃ䛥䜜䛶䛝䛯䚹䛧䛛䛧䛭䛾ᩘ䛿඲ᅜ䛷33୓䛛ᡤ䜢㉸䛘䛶䛚䜚䚸┘ど䝁䝇䝖䛾㠃䛷ၥ㢟䛜䛒䜛䚹䜎䛯䚸ᩳ㠃ᔂቯ䛾┘どᡭἲ䛸䛧䛶䚸ఙ⦰ィ䜢⏝䛔䛯ᔂቯ㢌㒊䛾ᘬᙇ๭䜜┠䠄䝔䞁䝅䝵䞁䜽䝷䝑䜽䠅䛾ኚ␗ィ 䛜୍⯡ⓗ䛰䛜䚸඲䛶䛾ᑐ㇟ᆅ䛻タ⨨䛩䜛䛣䛸䛿⌧ᐇⓗ䛷䛿↓䛔䚹䛭䛣䛷ᮏ◊✲䛷䛿௨ୖ䛾≧ἣ䜢㋃䜎䛘䛶䚸ᆅᙧィ 䝒䞊䝹䛾୍䛴䛸䛧䛶㏆ᖺᛴ㏿䛻฼⏝䛜ᣑ኱䛧䛶䛔䜛䚸UAV-SfMィ ᡭἲ䠄ᑠᆺ↓ேᶵ䜢⏝䛔䛯✵᧜䛚䜘䜃Structurefrom Motionᢏ⾡䜢฼⏝䛧䛯෗┿ 㔞䠅䛻䜘䜛䚸ᩳ㠃ᔂቯ๓඙⌧㇟䛾ᢕᥱ䛾ྍ⬟ᛶ䛻䛴䛔䛶᳨ウ䛧䛯䚹䠄䠍䠅ᒾ┙ᔂⴠ䛚䜘䜃ⴠ▼䛾ᆅᙧኚ໬䛾ᢳฟྍ⬟ᛶ䜢ホ౯䛩䜛䛯䜑䛻䚸༓ⴥ┴䛔䛩䜏ᕷ䛾㞛ᓥ䜢ᑐ㇟䛻ከ᫬ᮇほ 䜢ᐇ᪋䛧䛯䚹ᙜᆅᇦ䛿ኴᖹὒ䛻㠃䛧䛶䛚䜚䚸ㆤᓊタഛ䛾እഃ䠄ᾏഃ䠅䛻఩⨨䛩䜛䛯䜑3m䚸Ἴᾉ䛾ᙳ㡪䛻䜘䜛౵㣗䛜⃭䛧䛔䚹ᚑ᮶䛾ほ ᡭἲ䛷䛿ゎീᗘ䚸䜰䜽䝉䝇䚸䝁䝇䝖➼䛾㠃䛷ヲ⣽䛺ィ 䛜䛷䛝䛺䛛䛳䛯䛜䚸UAV-SfM
2ᡭἲ䛻䜘䜚䚸㧗ゎീᗘ䞉㧗㢖ᗘ䞉ప䝁䝇䝖䛺ィ 䛾ᐇ⌧䛻ᡂຌ䛧䛯䚹1
2014ᖺ䛾ィ 䝕䞊䝍䛸ẚ㍑䛧䛯䛸䛣䜝䚸2ᖺ㛫䛷ྜィ419ੑ䛾౵㣗
0䛜Ⓨ⏕䛧䛯䛣䛸䛜᫂䜙䛛䛸䛺䛳䛯䠄ᅗ1䠅䚹䜒䛧䛣䛾㏿ᗘ䛷౵㣗䛜⥅⥆
ᅗ1 2ᖺ㛫䛾ᆅᙧኚ໬䠄㞛ᓥ䠅䛩䜛䛸䚸⣙60ᖺ䛷ᓥ䛜ᾘ⁛䛩䜛䛣䛸䛜♧၀䛥䜜䛯䚹䠄䠎䠅ᆅ䛩䜉䜚䛾䜰䝘䝻䝆䞊䛸䛧䛶䚸㞷ᔂᩳ㠃䛻ὀ┠䛧䛶UAV-SfMィ 䜢ᐇ᪋䛧䛯䚹ᑐ㇟ᆅ䛿᪂₲┴㨶἟ᕷ኱ⓑᕝ䛾ᒣᆅᩳ㠃䛷䛒䜛䚹✚㞷ᮇ䛸↓㞷ᮇ䠄⼥㞷ᚋ䠅䛾2᫬ᮇ䛻ྠ䛨ᩳ㠃䜢ィ 䛧䚸䛭䛾ᕪศ䜢ồ䜑䜛䛣䛸䛷䚸㞷䜔᳜⏕䛻䜘䜛ᆅ⾲㠃䛾ᶆ㧗ኚ໬䜢ィ 䛧䛯䚹䜎䛯ྠ᫬䛻䚸snow probe䠄 ῝Წ䠅䜢⏝䛔䛶✚㞷῝䛾ᐇ 䜢⾜䛳䛯䚹䛭䛾⤖ᯝ䚸㞷ᔂᩳ㠃ୖ㒊䛻ᙧᡂ䛥䜜䛯䜾䝷䜲䝗䜽䝷䝑䜽䛾⠊ᅖ䛚䜘䜃ᙧ≧䚸✚㞷῝䛾ヲ⣽䛺✵㛫ศᕸ䛾ィ 䛻ᡂຌ䛧䛯䚹௒ᚋ䚸㧗㢖ᗘ䛺UAV-SfMィ 䜢ᐇ᪋䛩䜛䛣䛸䛷䚸䜾䝷䜲䝗䜽䝷䝑䜽➼䛾㞷ᔂண඙⌧㇟䛾᪩ᮇⓎぢ䜔䚸ヲ⣽䛺✚㞷῝䝕䞊䝍䜢⏝䛔䛯༴㝤ᗘホ౯䛾㧗ᗘ໬䛜ྍ⬟䛻䛺䜛䛸⪃䛘䜙䜜䜛䚹䠄䠏䠅ᩳ㠃ᔂቯ䛾ண඙⌧㇟䛾ᢳฟ䜢┠ⓗ䛸䛧䛶䚸ᰣᮌ┴䛾᪥ග⳹ཝ䛾⁪䛾㇂ቨᩳ㠃䜢ᑐ㇟䛸䛧䛯UAV-SfM
ィ 䜢ᐇ᪋䛧䛯䚹䛭䛾⤖ᯝ䚸ᆅୖ䛛䜙䛾䜰䜽䝉䝇䛜ᴟ䜑䛶ᅔ㞴䛺⁪࿘㎶䛾ᆅᙧ䝕䞊䝍䛾ྲྀᚓ䛻ᡂຌ䛧䛯䚹䛧䛛䛧䚸ᶞෙ䛾ኚ໬䛛䜙䛭䛾ୗ䛾ᆅ㠃䛾ኚື䠄䝔䞁䝅䝵䞁䜽䝷䝑䜽䛺䛹䠅䛾ᢕᥱ䜢ヨ䜏䛯䛜䚸ⴠⴥ䜔᳜≀䛾ᡂ㛗䛻䜘䜛ᶞෙᙧ≧䛾Ꮨ⠇ኚ໬䛻䜘䜚䚸ᆅ┙ኚື䛾᫂☜䛺ᢳฟ䛻䛿⮳䜙䛺䛛䛳䛯䚹㻌 ◊✲ᡂᯝ䛿௨ୗ䛾Ꮫ఍Ⓨ⾲䚸Ꮫ⾡ㄽᩥ䛸䛧䛶බ⾲䛧䛯䠄୍㒊䛾䜏♧䛩䠅䚹Yuichi S. Hayakawa and Hiroyuki Obanawa (2016) Erosion of a small coastal island revealed byrepeated measurements using TLS and UAS-photogrammetry. AGU2016.
ᑠⰼ࿴ᏹஅ䞉Ἑᓥඞஂ䞉ᯇඖ㧗ᓠ䞉ఀ㇧㒊ຮ䞉኱๓ᏹ࿴ (2016) ᑠᆺ UAV 䜢⏝䛔䛯✚㞷ศᕸ䛾3ḟඖィ㞷ị, 78(5), 317-328.

― 50 ―.

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-45䛇䝬䝹䝏䝉䞁䝅䞁䜾䛻䜘䜛ᶞෙᵓ㐀ィ ἲ䛾㛤Ⓨ
Development of measurement method of forest canopy structure by using multi-sensing approach୰㊰ 㐩㑻㻌 䠄໭ᾏ㐨኱Ꮫ䞉໭᪉⏕≀ᅪ䝣䜱䞊䝹䝗⛉Ꮫ䝉䞁䝍䞊䠅
Tatsuro Nakaji 㻌 䠄Hokkaido University 䞉Field Science Center for Northern Biosphere)䛆せ᪨䛇ᶞᮌ䛾ᶞෙᵓ㐀䛾ᢕᥱ䛿᳃ᯘ䛾Ⅳ⣲㈓⵳䜢䛿䛨䜑⏕≀䛸䛾┦஫స⏝䜢⪃䛘䜛ୖ䛷㠀ᖖ䛻㔜せ䛺ᇶ♏᝟ሗ䛸䛺䜛䚹ᮏ◊✲䛷䛿䝺䞊䝄䞊䝇䜻䝱䝘䜔SfM䜢㥑౑䛧䚸ᆅୖ䛸ୖ✵䛛䜙䛾ከ㠃ⓗ䛺ほ 䛻䜘䛳䛶ᶞෙᵓ㐀䜢㧗⢭ᗘ䛷ண 䛩䜛䛣䛸䜢┠ⓗ䛸䛧䛶䚸ᖖ⥳㔪ⴥᶞᯘ䛻䛚䛔䛶⌧ᆅㄪᰝ䜢ᐇ᪋䛧䛯䚹໭ᾏ㐨኱Ꮫ㞵㱟◊✲ᯘෆ䛻タ⨨䛥䜜䛯500m㽢500m䛾኱つᶍㄪᰝ䝥䝻䝑䝖䛾ୖ✵䜢ᑠᆺUAV䜢⏝䛔䛶✵᧜䛧䚸SfM䛻䜘䜛ゎᯒ䜢㛤ጞ䛧䛯䚹ྠᆅⅬ䛾ᆅୖ䝺䞊䝄䞊ほ 䛸ྜ䜟䛫䛶䚸ᆅୖ㒊䝞䜲䜸䝬䝇䜔ᶞෙᵓ㐀䜢ᐃ㔞໬䛩䜛䛯䜑✵㛫ゎᯒἲ䛾㛤Ⓨ䜢⾜䛖䚹䛆Abstract䛇

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

The 3D structure of forest canopy is important information not only for estimating the carbon stock inabove ground biomass but for understanding the biological interaction in forest ecosystem. In thisprogram, we have tried to measure the canopy structure of northern forests by multiple use of ALS
and SfM technique. In 2016, the aerial photo images were captured by UAV in large scale researchplot (500 m㽢500m) at natural Sakhalin spruce forest in Hokkaido. Based on the previous ALS dataand current canopy image data, we start the integrated analysis for accurate calculation of canopy
structure.

䛣䜜䜎䛷䛾◊✲䛻䜘䜚䚸ᆅୖ䛛䜙᳃ᯘෆ䜢㧗ศゎ⬟䝺䞊䝄䞊䝇䜻䝱䞁䛩䜛䛣䛸䛻䜘䛳䛶䚸ᶞෙᵓ㐀䜔❧ᮌ఩⨨䚸⬚㧗┤ᚄ䜢䛒䜛୍ᐃ䛾⢭ᗘ䛷ồ䜑䜙䜜䜛䜘䛖䛻䛺䛳䛶䛝䛯䚹୍᪉䚸ୖ✵䛛䜙UAV䛻䜘䛳䛶ほ 䛧䛯䝺䞊䝄䞊䝇䜻䝱䞁䛚䜘䜃㐃⥆⏬ീ䛛䜙䛿䚸ᶞ㧗䜔ᶞ✀䚸⾲㠃ᵓ㐀䛾ゎᯒ䜒ྍ⬟䛷䛒䜛䚹䛭䛣䛷䚸ᮏ◊✲䛷䛿䚸䝞䜲䜸䝬䝇䜔❧ᮌ఩⨨䜔ᶞ✀䛸䛔䛳䛯ᆅୖ᳨ド䝕䞊䝍䛜ᗈᇦ䛷ᩚഛ䛥䜜䛶䛔䜛໭ᾏ㐨኱Ꮫ◊✲ᯘ䜢ᑐ㇟䛸䛧䛶䚸୧ᡭἲ䛾ほ 䜢」ྜⓗ䛻㔝እ䛷ᐇ᪋䛧䚸䝕䞊䝍ゎᯒ䜰䝹䝂䝸䝈䝮䛾㛤Ⓨ䜢㏻䛨䛶䚸ᶞෙ䛾ᵓ㐀䜔䝞䜲䜸䝬䝇ィ ⢭ᗘ䜢᳨ド䛧䚸ᗈᇦ䛛䛴㧗⢭ᗘ䛷᳃ᯘ᝟ሗ䜢䝉䞁䝅䞁䜾䛩䜛ᡭἲ䛾㛤Ⓨ䜢㐍䜑䜛䚹໭ᾏ㐨኱Ꮫ㞵㱟◊✲ᯘ䠄ᖠຍෆ⏫ẕᏊ㔛䠅䛾䜰䜹䜶䝌䝬䝒‵ᆅᯘ䠄ᅗ䠍䠅䛷䛿䚸500m㽢500m䛾኱つᶍㄪᰝ䝥䝻䝑䝖䜢タ⨨䛧䚸100m䛚䛝25ᆅⅬ䠄ィ2.5ha䠅䛾ẖᮌㄪᰝ䛸ᆅୖ䝺䞊䝄䞊ほ 䜢ᐇ᪋䛧䛶䛔䜛䚹௒ᖺᗘ
䛿䚸9/5䡚9/8䛻䚸ᑠᆺUAV䠄䝗䝻䞊䞁䠅䜢⏝䛔䛶䛣䛾ㄪᰝ䝥䝻䝑䝖඲ᇦ䛾✵᧜䜢ᐇ᪋䛧䛯䚹㧗ᗘ120m䚸2m/s
䛷1s䜲䞁䝍䞊䝞䝹䛷✵᧜䜢ᐇ㝿䛩䜛䛣䛸䛷䚸㧗⢭ᗘ䜸䝹䝋⏬ീ䛚䜘䜃SfMゎᯒ䛜ྍ⬟䛺⏬ീ䝕䞊䝍䝉䝑䝖䜢ᚓ䛯䠄ᅗ䠎䠅䚹୍᪉䚸ᯘᗋ᳜⏕䜔䝜䜲䝈䜢ྵ䜐䚸ᆅୖ䝺䞊䝄䞊ほ 䛷ᚓ䜙䜜䜛Ⅼ⩌䝕䞊䝍䛛䜙ᆅ┙㧗䜢ண䛩䜛䛯䜑䛾䝣䜱䝹䝍䞊ฎ⌮䠄䜲䝍䝺䞊䝅䝵䞁䠅䛾㛤Ⓨ䛻䜒ྲྀ䜚⤌䜏䚸᭱㐺䛺ᡭἲ䜒᫂䜙䛛䛻䛺䛳䛯䠄ᅗ3䠅䚹௒ᚋ䛿䚸ᆅୖ䝺䞊䝄䞊ほ 䛷ᚓ䜙䜜䛯ᯘᗋ䡚ᶞෙ䜎䛷䛾✵㛫᝟ሗ䛸䚸ୖ✵䛛䜙䛾᧜ᙳ䞉SfM䛷ᚓ䜙䜜䛯ᶞෙ✵㛫᝟ሗ䛾⤫ྜゎᯒ䜢㐍䜑䚸ẖᮌ䝕䞊䝍䛸ẚ㍑䛩䜛䛣䛸䛷䚸◊✲ᯘศ䛾䝞䜲䜸䝬䝇䜔ᶞෙᵓ㐀䛾ᐃ㔞໬䜢⾜䛖ணᐃ䛷䛒䜛䚹ึᮇᯘᗋ䝕䞊䝍

ᅗ1 䜰䜹䜶䝌䝬䝒‵ᆅᯘ

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

ᅗ2 ✵᧜䛻䜘䜛䜸䝹䝋⏬
ീ䛾୍㒊.㻌 ୰ኸ䛿సᴗ㐨䠄ᖜ⣙1.5m䠅

ᒁᡤ໙㓄䝣䜱䝹䝍䝸䞁䜾

ᅗ3 ᆅ⾲㠃ฎ⌮䛾୍౛䝜䜲䝈䛸ᛮ䜟䜜䜛พฝ䛾㝖ཤ䛻ᡂຌ䠊Ꮫ఍䜔ᅜ㝿ㄅ➼䛷䛾බ⾲䜢⾜䛖䛯䜑䛾‽ഛ䜢㐍䜑䜛䚹໭ᾏ㐨኱Ꮫ㞵㱟◊✲ᯘ䛻䛚䛡䜛኱つᶍㄪᰝ䝥䝻䝑䝖䛾ᴫせ䛻䛴䛔䛶䛿䚸᪥ᮏ᳃ᯘᏛ఍䛻䛚䛔䛶Ⓨ⾲䛧䛯䠄୰㊰㐩㑻䞉⛅ὠ᭸Ꮚ䞉ྜྷ⏣ಇஓ䞉᪥ᾆຮ䞉୰ᮧㄔᏹ䞉ᰘ⏣ⱥ᫛䞉ዉబཎ㢧㑻㻌 䠄2017䠅᳃ᯘ⏕ែ䝸䝰䞊䝖䝉䞁䝅䞁䜾◊✲䛾䛯䜑䛾኱つᶍ᳃ᯘㄪᰝ䝥䝻䝑䝖䛾ᩚഛ䠊➨128ᅇ᪥ᮏ᳃ᯘᏛ఍኱఍, 2017/3/26䡚3/29, 㮵ඣᓥ኱Ꮫ䠅䚹― 51 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-33䛇ྜᡂ㛤ཱྀ䝺䞊䝎䛻䜘䜛⎔ቃィ 䛻㛵䛩䜛◊✲A study on environmental measurement by synthetic aperture radar䠄◊✲௦⾲⪅ྡ䠅ⱝᯘ㻌 ⿱அ㻌 䠄᪥ᮏ኱Ꮫ䞉ᕤᏛ㒊䠅
Hiroyuki Wakabayashi㻌 䠄College of Engineering䞉Nihon University䠅䛆せ᪨䛇 㻌 ᮏ◊✲䛷䛿䚸ྜᡂ㛤ཱྀ䝺䞊䝎(SAR)䝕䞊䝍䜢౑⏝䛧䛯⎔ቃィ 䛾㧗⢭ᗘ໬䜢┠ⓗ䛸䛧䛶䛔䜛䚹H28ᖺᗘ䛿⎔ቃィศ㔝(᳃ᯘ䚸㎰ᴗ䚸㞷ị)䛾୰䛷㞷ịศ㔝䛻⤠䛳䛶◊✲䜢⾜䛳䛯䚹Pi-SAR-L2䛾ከ೫Ἴほ 䝕䞊䝍䛛䜙䚸䝃䝻䝬†䛾ᮾす᪉ྥ䛻䛭䛳䛶ከ೫Ἴ䝟䝷䝯䞊䝍䛾䝥䝻䝣䜯䜲䝹䜢⟬ฟ䛧䛯䚹䛭䛾⤖ᯝ䚸ᵝ䚻䛺✀㢮䛾ᾏị䛚䜘䜃ᾏỈᇦ䛾ከ೫Ἴ䝟䝷䝯䞊䝍䛾ධᑕゅ≉ᛶ䜢ᢳฟ䛩䜛䛣䛸䛜䛷䛝䛯䚹䛭䛾⤖ᯝ䚸኱䛝䛔ධᑕゅ䛷ほ 䛧䛯VV䛸HH䛾ᚋ᪉ᩓ஘ẚ䛿ᾏịཌ䛸㧗䛔┦㛵䜢ᣢ䛱䚸ᾏỈ㠃䛾ᩓ஘䜶䞁䝖䝻䝢䛿኱䛝䛔ධᑕゅ䛷ほ 䛧䛯㝿䜒ᾏị䜘䜚ᑠ䛥䛔್䜢♧䛧䛯䚹㻌 㻌 The main objective of this research is to improve an accuracy of environmental monitoring by usingsynthetic aperture radar (SAR) data. Among the environmental monitoring fields, the snow and ice was䛆Abstract䛇 selected to focused target in JFY2016.By taking profiles of polarimetric parameters along the line crossing
from the west edge to the eastern area of Lake Saroma, the polarimetric and the incidence angle
characteristics for various ice types and open water were extracted. It was found that VV to HH
backscattering ratio at higher incidence angle was correlated with ice thickness and sensitive to thickness
difference. The scattering entropy of OW was lower than any other ice types even at the higher incidence
angles.

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㻌 ᮏ◊✲䛷䛿䚸ྜᡂ㛤ཱྀ䝺䞊䝎(SAR)䝕䞊䝍䜢౑⏝䛧䛯⎔ቃィ 䛾㧗⢭ᗘ໬䜢┠ⓗ䛸䛧䛶䛔䜛䚹㏆ᖺ⾨ᫍᦚ
㍕SAR䛾ほ 䝟䝷䝯䞊䝍䛜ከᵝ໬䛧䚸࿘Ἴᩘ䚸೫Ἴ䚸ධᑕゅ䛜㑅ᢥ䛷䛝䜛䜘䛖䛻䛺䛳䛶䛝䛯䚹ᮏ◊✲䛷䛿䚸
SAR䝕䞊䝍䜢౑⏝䛧䛯᳃ᯘ䚸㎰ᴗ䚸㞷ịศ㔝䛷䛾⎔ቃィ 䛻䛚䛡䜛᭱㐺䛺ほ 䝟䝷䝯䞊䝍䜢ᢳฟ䛩䜛䛣䛸䜢┠ᣦ䛩䚹ᖹᡂ28ᖺᗘ䛿ᑐ㇟ศ㔝䛾୰䛷䚸㞷ị(ᾏị)ศ㔝䛻ⓗ䜢⤠䛳䛶◊✲䜢ᐇ᪋䛧䛯䚹㻌 ⯟✵ᶵSAR(Pi-SAR-L2)䛜䝃䝻䝬†䛷ྲྀᚓ䛧䛯ከධᑕゅከ೫ἼSAR䝕䞊䝍䛛䜙ᾏị≀⌮㔞䛻ឤᗘ䛜㧗䛔䝟䝷䝯䞊䝍䛾ᢳฟ䜢ヨ䜏䛯䚹ᮏ◊✲䛻䛚䛡䜛Pi-SAR-L2䝕䞊䝍ゎᯒ䛾⤖ᯝ䚸௨ୗ䛾ᡂᯝ䜢ᚓ䛯䚹(1)䝃䝻䝬†䛾ᮾす᪉ྥ䛾䝥䝻䝣䜯䜲䝹䝕䞊䝍䛛䜙䚸኱䛝䛔ධᑕゅ䛷ほ㧗䛔┦㛵䜢ᣢ䛴䛣䛸䛜䜟䛛䛳䛯(ᅗ1)䚹

䛧䛯VV/HHᚋ᪉ᩓ஘ẚ䛿ᾏịཌ䛸(2)ᾏỈ㠃䛾ᩓ஘䜶䞁䝖䝻䝢䛿ධᑕゅ20ࠥ60ᗘ䛾⠊ᅖ䛷ᾏị䜘䜚䜒ᑠ䛥䛔್䜢♧䛧䛯(ᅗ2)䚹
(3)ⷧị䛾VV/HHᚋ᪉ᩓ஘ẚ䛻ᑐ䛩䜛ධᑕゅ≉ᛶ䜢ᚓ䜛䛣䛸䛜䛷䛝䚸ᾏịཌ䛾ほ䛷ほ 䛩䜛䛸ịཌ䛻ᑐ䛩䜛ឤᗘ䛜኱䛝䛔䛣䛸䛜䜟䛛䛳䛯(ᅗ3)䚹

ᅗ1. HH/VVᚋ᪉ᩓ஘ẚ䢈䢛䢗䢈䡣䡮䢕

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ᅗ2. ᾏỈ㠃䛾ᩓ஘䡰䢙䢀䢗䢇䢛

䛻䛿45ᗘ⛬ᗘ䛾ධᑕゅ

ᅗ3. ⷧị䛾HH/VVᚋ᪉ᩓ஘ẚධᑕゅ≉ᛶᮏ◊✲䛻㛵㐃䛩䜛ᡂᯝ䛻䛴䛔䛶䛿䚸௨ୗ䛾Ꮫ఍䛻䛶Ⓨ⾲῭䜎䛯䛿Ⓨ⾲ணᐃ䛷䛒䜛䚹(1) H. Wakabayashi: Backscattering characteristics of ice on Lake Saroma observed by PALSAR-2
and Pi-SAR-2L, Proceedings of International Geoscience and Remote Sensing Symposium,
pp.2076-2079 (2016.7)(2) ISRS2017(3) IGARSS2017― 52 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-10䛇
GOSAT䛸኱Ẽ㍺㏦䝰䝕䝹䜢⏝䛔䛯CO2䞉CH4䛾⃰ᗘኚື䛾ゎᯒ
Analysis of CO2 and CH4 concentration variations using GOSAT and a transport model䠄◊✲௦⾲⪅ྡ䠅 ୹⩚㻌 ὒ௓㻌 䠄Ẽ㇟ᗇẼ㇟◊✲ᡤ䠅Yosuke Niwa 㻌 䠄Meteorological Research Institute䠅䛆せ᪨䛇஧㓟໬Ⅳ⣲(CO2)䜔䝯䝍䞁(CH4)䛺䛹䛾 ᐊຠᯝ䜺䝇䛾኱Ẽ୰䛷䛾᫬✵㛫ኚື䜢ᢕᥱ䛩䜛䛯䜑䛻䛿䚸ᐦ䛺ほ䝕䞊䝍䛜ᚲせ䛷䛒䜛䚹 ᐊຠᯝ䜺䝇ほ ᢏ⾡⾨ᫍGOSAT䛿 ᐊຠᯝ䜺䝇䛾኱Ẽ⃰ᗘ䜢ᆅ⌫つᶍ䛷ᗈ⠊ᅖ䛻䜟䛯䛳䛶ほ 䛷䛝䜛᭷⏝䛺䝥䝷䝑䝖䝣䜷䞊䝮䛷䛒䜛䛜䚸TANSO䝉䞁䝃䞊䛛䜙䝸䝖䝸䞊䝞䝹䛻䜘䛳䛶ᚓ䜙䜜䜛ほ ್䛻䛿኱䛝䛺୙☜ᐃᛶ䛜Ꮡᅾ䛩䜛䚹ᮏ◊✲䛷䛿䚸኱Ẽ㍺㏦䝰䝕䝹NICAM-TM䜢⏝䛔䛶䚸TANSO䛾⇕㉥እ䝉䞁䝃
TIR䛾CO2䝸䝖䝸䞊䝞䝹್䛻䛴䛔䛶᪋䛥䜜䛯䝞䜲䜰䝇⿵ṇ䛾᭷ຠᛶ䜢᳨ド䛧䛯䚹䛣䛣䛷䚸NICAM-TM䛷ᚓ䜙䜜䜛3ḟඖ⃰ᗘศᕸ䛿⯟✵ᶵほ CONTRAIL䛾ほ 䝕䞊䝍䛷᭱㐺໬䛥䜜䛶䛔䜛䚹᳨ド䛾⤖ᯝ䚸TIR䝸䝖䝸䞊䝞䝹್䛿
䚸6-8᭶䛾⇕ᖏᇦ䜢㝖䛔䛶䚸ጇᙜ䛺䝞䜲䜰䝇⿵ṇ䛜䛥䜜䛶䛔䜛䛣䛸䛜䜟䛛䛳䛯䚹䛆Abstract䛇 A dense observation network is required to monitor spatiotemporal variations of atmospheric CO2 andCH4. The GOSAT is useful in that it has a globally wide observational coverage. However, the retrieval
data of GOSAT have significant uncertainties. In this study, we evaluated the bias corrections applied to
the CO2 data that are retrieved from TANSO TIR. The evaluation utilizes the atmospheric transport model
NICAM-TM, which is optimized by the aircraft data of CONTRAIL. The result elucidates the validity of thebias corrections, except for the data obtained in tropical regions during June-August.

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ᐊຠᯝ䜺䝇ほ ᢏ⾡⾨ᫍGOSAT䛿ᗈ⠊ᅖ䛺ほ ⥙䜢᭷䛩䜛䛜䚸ᆅୖ䝇䝔䞊䝅䝵䞁䛺䛹䛻䛚䛡䜛in-situほ䛸ẚ䜉䛶䚸ほ ್䠄䝸䝖䝸䞊䝞䝹್䠅䛾ㄗᕪ䛿኱䛝䛔䚹䛭䛣䛷ᮏ◊✲䛷䛿䚸GOSAT䛾⇕㉥እ䠄TIR䠅䝉䞁䝃䛻
䜘䜛CO2䝸䝖䝸䞊䝞䝹್䛾䝞䜲䜰䝇⿵ṇ䛻䛴䛔䛶䚸䛭䛾᭷ຠᛶ䜢䚸኱Ẽ㍺㏦䝰䝕䝹NICAM-TM䜢⏝䛔䛶᳨ド
䛩䜛䚹NICAM-TM䛾⃰ᗘィ⟬್䛿䚸⯟✵ᶵほ CONTRAIL䛾䝕䞊䝍䛛䜙䜲䞁䝞䞊䝆䝵䞁ゎᯒ䛻䜘䛳䛶᭱㐺໬䛩䜛䚹䝸䝖䝸䞊䝞䝹್䛻ᑐ䛩䜛䝞䜲䜰䝇⿵ṇ䜒CONTRAIL䝕䞊䝍䛜⏝䛔䜙䜜䛶䛔䜛䛜䚸GOSAT䛸CONTRAIL䛾ほ Ⅼ䛜䛒䜛⠊ᅖ䛻཰䜎䛳䛯䝕䞊䝍䛾䜏౑䜟䜜䛶䛔䜛䚹䛭䛾䛯䜑䚸䝰䝕䝹䛾3ḟඖศᕸ䛸ẚ
㍑䛩䜛䛣䛸䛷䚸䜘䜚ᴫᣓⓗ䛺ホ౯䛜ྍ⬟䛸䛺䜛䚹䠄䠍䠅ᑐὶᅪ୰䞉ୗ㒊䛻䛚䛔䛶䚸CONTRAIL䝕䞊䝍䜢౑䛳䛶㻌 㻌 䝞䜲䜰䝇⿵ṇ䜢⾜䛳䛯TIR䝸䝖䝸䞊䝞䝹್䛜䚸䝞䜲䜰䝇㻌 㻌 ⿵ṇ๓䛸䛟䜙䜉䛶䚸NICAM-TM䛸䛾඲⌫ⓗ䛺ᩚྜᛶ䛜㻌 㻌 ኱ᖜ䛻ྥୖ䛧䛶䛔䜛䛣䛸䛜䜟䛛䛳䛯䠄ᅗ䠍䠅䚹䛣䜜䛻䜘䜚䚸㻌 㻌 ⯟✵ᶵほ ⥙䛜✵㛫ⓗ䛻㝈䜙䜜䛶䛔䛶䜒䠄✵ ୖ✵䛾㻌 㻌 䜏䠅䚸䝞䜲䜰䝇⿵ṇ䛜᭷ຠ䛷䛒䜛䛣䛸䛜♧၀䛥䜜䛯䚹
䠄䠎䠅6-8᭶䛾⇕ᖏ䠄20S-20N䠅䛻䛚䛡䜛TIR䝸䝖䝸䞊䝞䝹್䛻㻌 㻌 䛴䛔䛶䛿䚸䝞䜲䜰䝇⿵ṇ䛜㐣๫䛷䛒䜛䛣䛸䛜NICAM-TM㻌 㻌 䛸䛾ẚ㍑䛛䜙䜟䛛䛳䛯䚹䛣䜜䛿䚸䛾CO2྾཰䝞䞁䝗㻌 㻌 䜢௚䛾྾཰䝞䞁䝗䛸ే䛫䛶䝸䝖䝸䞊䝞䝹䛻⏝䛔䛶䛔䜛䛣䛸㻌 㻌 䛜ཎᅉ䛷䛒䜛ྍ⬟ᛶ䛜䛒䜚䚸௒ᚋ䛾䝸䝖䝸䞊䝞䝹⢭ᗘ䛾㻌 㻌 ྥୖ䛻᭷⏝䛺▱ぢ䜢ᚓ䜛䛣䛸䛜ฟ᮶䛯䚹

ᅗ1

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GOSAT TIR䝸䝖䝸䞊䝞䝹್䛸NICAMTM䛾ィ⟬್䛸䛾ᕪ䛾㢖ᗘศᕸ䚹Ⅼ⥺䛜䝞䜲䜰䝇⿵ṇ๓䚸ᐇ⥺䛜䝞䜲䜰䝇⿵ṇᚋ䚹ᮏ◊✲䛷NICAM-TM䝰䝕䝹䜢⏝䛔䛶ホ౯䛧䛯䚸GOSAT/TANSO-FTS䛾TIR䝞䞁䝗䛾CO2䝕䞊䝍䛾䝞䜲䜰䝇⿵ṇ್䛿ㄅୖබ⾲ᚋ䚸GOSAT䛾䝕䞊䝍䝴䞊䝄䞊䛻බ㛤䛥䜜䚸TIR䝞䞁䝗䛾CO2䝕䞊䝍䜢⏝䛔䛯◊✲䛻ά⏝䛥䜜䜛ぢ㎸䜏䛷䛩䚹― 53 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-16䛇
⾨ᫍ䝕䞊䝍䜢฼⏝䛧䛯ᑐὶᅪ䞉ᡂᒙᅪ䛾≀㉁㍺㏦㐣⛬䛻㛵䛩䜛◊✲Study for dynamical process in troposphere and stratosphere using satellite data䠄◊✲௦⾲⪅ྡ䠅Ụཱྀ⳯✑ (஑ᕞ኱Ꮫ㻌 ᛂ⏝ຊᏛ◊✲ᡤ)
Nawo Eguchi (Research Institute for Applied Mechanics, Kyushu University)䛆せ᪨䛇 ⾨ᫍほ 䛛䜙ᑟฟ䛥䜜䛯኱Ẽᚤ㔞ᡂศ➼䛾䝕䞊䝍䜢⏝䛔䛶䚸ᑐὶᅪ䛚䜘䜃ᡂᒙᅪෆ䛾≀㉁㍺㏦䛚䜘䜃ᑐὶᅪᡂᒙ
ᅪ㛫䛾≀㉁஺᥮㐣⛬䜢᫂䜙䛛䛻䛩䜛䛣䛸䜢┠ⓗ䛸䛩䜛䚹ᮏᖺᗘ䛿䚸GOSAT/TANSO-FTS TIR ͤ䜘䜚ᑟฟ䛥䜜䛯 CO2
䛾 Level 2, Version 01.00 䜢⏝䛔䛶䚸୰䞉ୖ㒊ᑐὶᅪ䛾 CO2 䛾Ꮨ⠇ኚ໬䚸ᖺ䚻ኚ໬䜢ㄪᰝ䛧䛯䚹 Saito et al. [2016]䛷⯟✵ᶵほ 䝕䞊䝍䛸䛾ẚ㍑⤖ᯝ䛛䜙ᚓ䜙䜜䛯⿵ṇ್䜢㐺⏝䛧䛯䚹⤖ᯝ䚸Ꮨ⠇㐍⾜䛿㍺㏦䝰䝕䝹 (NIES-TM) 䛸䜋䜌ྠᵝ䛷䛒䛳䛯䚹䜎䛯ప⦋ᗘ䛷⿵ṇ䛜ᙉ䛔ഴྥ䛜䜏䜙䜜䛯䛜䚸๓ᅇᣦ᦬䛧䛯୰㒊ᑐὶᅪ䛾ᴟ኱䛿ゎᾘ䛥䜜䛶䛔䛯䚹ͤ Greenhouse gases Observing SATtelite, Thermal And Near-infrared Sensor for carbon Observation- Fourier Transform Spectrometer, Thermal Infra-Red

䛆Abstract䛇 This study aims to investigate dynamical processes of transport in free-troposphere and stratospheretroposphere exchange by profile data of long- and short-lived trace gases (e.g., CO2 and Ozone profiles) in the
troposphere and stratosphere. This fiscal year investigated the seasonal and interannual variations of CO2 at
the middle and upper troposphere by the level2 ver.01.00 data adopting the bias correction along Saito et al.
[2016]. The seasonal march is similar with that from NIES Transport model. The strong reduction were seen in
the low latitudes of the boreal hemisphere and southern hemisphere due to the bias correction. However theisolated maximum at the middle troposphere in the low latitudes seen in the original data were disappeared.

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ᡂᯝ

⾨ᫍほ 䛛䜙ᑟฟ䛥䜜䛯኱Ẽᚤ㔞ᡂศ䚸䛚䜘䜃㞼≀⌮㔞䛾䝕䞊䝍䜢⏝䛔䛶䚸ᑐὶᅪ䛚䜘䜃ᡂᒙᅪෆ䛾≀㉁㍺㏦㐣⛬䛚䜘䜃ᑐὶᅪ䛸ᡂᒙᅪ㛫䛾≀㉁஺᥮㐣⛬䜢᫂䜙䛛䛻䛩䜛䛣䛸䜢┠ⓗ䛸䛩䜛䚹 ゎᯒ䛻䛿 GOSAT/TANSO-FTS TIR 䜘䜚ᑟฟ䛥䜜䛯 CO2 䛾 Level 2, Version 01.00 䜢⏝䛔䛯䚹䜎䛯ẚ㍑䛾䛯䜑䚸NIES㍺㏦䝰
䝕䝹 (NIES-TM) 䜢⏝䛔䛯䚹๓ᅇ䜎䛷䛾◊✲䛾⤖ᯝ䚸᫨ኪ䛾䝕䞊䝍㛫䛾㐪䛔䛿䛭䜜䜋䛹኱䛝䛟䛺䛔䛾䛷䚸୧䝕䞊䝍䜢ᖹᆒ䛧䛶ゎᯒ䛻⏝䛔䛯䚹䛥䜙䛻௒ᅇ䛿䚸 Saitoh et al. [2016] 䛚䜘䜃 Saitoh et al. [in preparation] 䛷⯟✵ᶵほ 䝕䞊䝍䛸䛾ẚ㍑ゎᯒ䛾⤖ᯝᚓ䜙䜜䛯⿵ṇ್䜢㐺⏝䛧䛯䚹䠄䠍䠅⿵ṇ䜢᪋䛧䛯䝕䞊䝍䜢⏝䛔䛶䚸୰䞉ୖ㒊ᑐὶᅪ䛾 CO2 䛾Ꮨ⠇㐍⾜䛚䜘䜃ᖺ䚻ኚື䜢☜ㄆ䛧䛯䚹Ꮨ⠇㐍⾜䛚䜘䜃⤒ᖺኚ໬䛿኱Ẽ㍺㏦䝰䝕䝹 (NIES-TM)䛾ኚື 䛸䜋䜌ྠᵝ䛷䛒䛳䛯 (ᅗ┬␎)䚹୰⦋ᗘ䛷᣺ᖜ䛜኱䛝䛟䚸᫓Ꮨ䛻ᴟ኱䚸ኟᏘ䛻ᴟᑠ䛷䛒䛳䛯䚹⤒ᖺኚື䛿ప⦋ᗘ䜋䛹ቑຍ⋡䛜㧗䛔ഴྥ䛷䛒䛳䛯䚹䠄䠎䠅໭༙⌫ప⦋ᗘ䛚䜘䜃༡༙⌫ഃ䛷⿵ṇ䛜ᙉ䛔ഴྥ䛜䜏䜙䜜䛯䠄ᅗ┬␎䠅䚹䛧䛛䛧௒ᅇ䛾⿵ṇ䛷䚸๓ᅇᣦ᦬䛧䛯ప⦋ᗘ䛾୰㒊ᑐὶᅪ䛻Ꮩ❧䛧䛶Ꮡᅾ䛧䛶䛔䛯ᴟ኱䛿ゎᾘ䛥䜜䛶䛔䛯䚹Ꮨ⠇ኚື䛾᣺ᖜ䛜኱䛝䛔୰⦋ᗘ䛻╔┠䛩䜛䛸䚸1᭶䛸4᭶䛻ᑐὶᅪୗᒙ䛛䜙ୖᒙ䜎䛷㧗⃰ᗘ䛜䜏䜙䜜䜛䚹㏫䛻7᭶䛸10᭶䛿ᑐὶᅪ඲ᒙ䛷ప⃰ᗘ䛸䛺䛳䛶䛚䜚䚸㖄┤㍺㏦䛜ᙅ䛔ഴྥ䛜ᣦ᦬䛥䜜䛶䛔䜛 NIES-TM 䛻ẚ䜉䜛䛸ᑐὶᅪ඲ᒙ䛻Ώ䛳䛶Ꮨ⠇ኚ໬䛜䜏䜙䜜䛶䛔䛯䚹

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

ᮏ◊✲䛷ᐇ᪋䛧䛯䚸GOSAT/TANSO-FTS 䛾 TIR 䝞䞁䝗䛾 CO2 䝕䞊䝍䛾䝞䜲䜰䝇⿵ṇᚋ䛾⃰ᗘศᕸ䛾ホ౯⤖ᯝ䛿䚸ㄅୖබ⾲ᚋ䛻୍⯡䛻බ㛤䛥䜜䜛ணᐃ䛾 TIR 䝞䞁䝗䛾Ꮨ⠇ู䞉⦋ᗘᖏ䞉㧗ᗘᖏู䛾 CO2 䝕䞊䝍䛾䝞䜲䜰䝇⿵ṇ್䛾᭷⏝ᛶ䜢౛ド䛩䜛䜒䛾䛷䛒䜚䚸௒ᚋ䛾 TIR 䝞䞁䝗䛾 CO2 䝕䞊䝍䜢⏝䛔䛯䝃䜲䜶䞁䝇◊✲䛷ཧ↷䛥䜜䜛䜒䛾䛷䛒䜛䚹― 54 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-27䛇
SKYNET ほ 䜶䜰䝻䝌䝹䝟䝷䝯䞊䝍䛾ㄗᕪホ౯䛸ゎᯒ䝅䝇䝔䝮䛾㧗ᗘ໬
Error evaluation of SKYNET observed aerosol parameters and advancement of data analysis system䠄◊✲௦⾲⪅ྡ䠅 䜹䝖䝸㻌 䝥䝷䝕䜲䞊䝥㻌 䠄ᮾ໭኱Ꮫ ኱Ꮫ㝔⌮Ꮫ◊✲⛉䠅
Khatri Pradeep㻌 䠄Tohoku University 䞉Graduate school of science䠅䛆せ᪨䛇

SKYNETほ 䜶䜰䝻䝌䝹ගᏛⓗ䝟䝷䝯䞊䝍䛾ㄗᕪホ౯䛻㛵䛩䜛▱㆑䜢䛥䜙䛻ᣑ኱䛩䜛䛯䜑䚸SKYNET䛷䜶䜰䝻䝌䝹ほ ⏝䛾ᶆ‽ᶵᮦ䛷䛒䜛䝇䜹䜲䝷䝆䜸䝯䞊䝍䛸ほ ᪉ἲ䛜␗䛺䜛ศගᨺᑕィ䛾ほ 䝕䞊䝍䛛䜙䜶䜰䝻䝌䝹䝟䝷䝯䞊䝍䜢᥎ᐃ䛧䚸SKYNET䛾ᶆ‽䜶䜰䝻䝌䝹䝥䝻䝎䜽䝖䛸䛾ẚ㍑䜢⾜䛳䛯䚹䛭䛾⤖ᯝ䛿䚸Khatri et al. (2016)䛷ᣦ᦬䛥䜜
䛯䜘䛖䛻SKYNET䛾䜶䜰䝻䝌䝹ගᏛⓗཌ䛥(AOT)䛿㧗⢭ᗘ䛷᥎ᐃྍ⬟䛰䛜䚸୍ḟᩓ஘䜰䝹䝧䝗(SSA)䜢㐣኱ホ౯䛩䜛䛣䛸䛜᫂䜙䛛䛻䛺䛳䛯䚹䜎䛯䚸SKYNET䛾䜶䜰䝻䝌䝹䝥䝻䝎䜽䝖䛾⢭ᗘྥୖ䛻ྥ䛡䛶䚸⌧ᅾ䛾䝕䞊䝍ゎᯒ䝅䝇䝔䝮ෆ䛻⾨ᫍほ 䛾ᆅ㠃཯ᑕ⋡䞉䜸䝌䞁㔞➼䛾䝕䞊䝍฼⏝䛾ྍ⬟ᛶ䜢᳨ウ䛧䚸ணഛⓗ䛺䝕䞊䝍ゎᯒ䜢ᐇ᪋䛧䛯䚹To evaluate errors of SKYNET observed aerosol optical parameters in more detail, standard aerosol
䛆Abstract䛇 products of SKYNET have been compared with aerosol parameters retrieved from an observation systemdifferent from sky radiometer of SKYNET, i.e., spectral irradiances observing radiometer. Aerosol optical
thickness (AOT) from those different instruments agreed quite well; however, single scattering albedo(SSA) from sky radiometer is found to be overestimated. This result is consistent with Khatri et al. (2016).
An attempt is also made to improve data analysis system of sky radiometer of SKYNET by implementing
satellite-observed information.

⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

ᅜ㝿ᆅୖほ 䝛䝑䝖䝽䞊䜽(SKYNET)䛾䜶䜰䝻䝌䝹䝥䝻䝎䜽䝖䛿䚸⾨ᫍほ 䜔ᩘ್䝰䝕䝹䛾᳨ド䛾䜋䛛ᆅ⌫⎔ቃ䛾ᵝ䚻䛺◊✲ศ㔝䛻䛚䛔䛶㈗㔜䛺ᮦᩱ䛸䛺䜚䚸䛭䛾䝥䝻䝎䜽䝖䛾ㄗᕪホ౯䜎䛯䛿⢭ᗘྥୖ䛜ồ䜑䜙䜜䛶䛔䜛䚹䛣䛾ᚲせᛶ䛻ᛂ䛨䛶NASA/AERONET䛾䝕䞊䝍䜢⏝䛔䛶SKYNET䛾䜶䜰䝻䝌䝹䝕䞊䝍䛾ㄗᕪホ౯䜢⾜䛳䛯䠄e.g,,khatri et al.,2016)䛜䚸SKYNET䛸AERONET᥇⏝ᶵᮦ䛾ほ ᪉ἲ䞉ཎ⌮䛜䜋䜌୍⮴䛩䜛䛯䜑䚸ᮏ◊✲䛷䛿SKYNET䛾ᶆ‽ᶵᮦ(䝇䜹䜲䝷䝆䜸䝯䞊䝍䠅䛸ほ ᪉ἲ䛜␗䛺䜛ศගᨺᑕィ䛾䝕䞊䝍䜢⏝䛔䛶
SKYNETほ 䜶䜰䝻䝌䝹䝕䞊䝍䛾⢭ᗘホ౯䜢䛥䜙䛻᳨ウ䛩䜛䚹䛣䛾䛯䜑䚸SKYNET䛾䝇䞊䝟䞊䝃䜲䝖䛷✌ാ୰䛾ศගᨺᑕィ䛾䝕䞊䝍䛛䜙䜶䜰䝻䝌䝹䝟䝷䝯䞊䝍䜢᥎ᐃ(Khatri et al., 2012)䛧䚸ྠ᫬୪⾜ほ 䛾䝇䜹䜲䝷䝆䜸䝯䞊䝍䛻䜘䜛䜶䜰䝻䝌䝹䝥䝻䝎䜽䝖䛸ẚ㍑䛩䜛䚹
1.6
500nm
SKYNET䛾䝇䞊䝟䞊䝃䜲䝖䛷䛒䜛㎶ᡞᓁ䚸Ἀ⦖䛸⚟Ụᓥ䚸㛗ᓮ䛻䛚
RMSE=0.024
䛡䜛䝇䜹䜲䝷䝆䜸䝯䞊䝍䛸ศගᨺᑕィ(MS-700)䛾䝕䞊䝍䜢⏝䛔䛶ᮏ
1.2◊✲䜢ᐇ᪋䛧䛯䚹䛭䛾୧⪅㛫ほ ཎ⌮䚸䝕䞊䝍䛾✀㢮䛰䛡䛷䛺䛟ゎᯒ䜰䝹䝂䝸䝈䝮䜎䛷␗䛺䜛䚹䝇䜹䜲䝷䝆䜸䝯䞊䝍䛸ศගᨺᑕィ䛻䜘䜛
0.8
䜶䜰䝻䝌䝹䝟䝷䝯䞊䝍䛾᥎ᐃ䛿䚸䛭䜜䛮䜜Nakajima et al. (2009)䛸
Khatri et al. (2012)䛷㛤Ⓨ䛥䜜䛯䜰䝹䝂䝸䝈䝮䛻ᇶ䛵䛟䚹୧⪅䛛䜙ᚓ䜙䜜䛯䝕䞊䝍䛾ẚ㍑౛䛸䛧䛶ᅗ䠍䛻䜶䜰䝻䝌䝹ගᏛⓗཌ䛥(AOT)䛾
0.4
ẚ㍑䜢♧䛩䚹䝕䞊䝍㛫ẚ㍑䜘䜚௨ୗ䛾䛣䛸䛜᫂䜙䛛䛻䛺䛳䛯䚹• 䝇䜹䜲䝷䝆䜸䝯䞊䝍ほ 䛾䜶䜰䝻䝌䝹ගᏛⓗཌ䛥䠄AOT)䛜ศගᨺ
0ᑕィ䛾䝕䞊䝍䛛䜙᥎ᐃ䛧䛯್䛸䜋䜌୍⮴䛩䜛䚹䛭䛾୍᪉䚸䝇䜹䜲
0
0.4
0.8
1.2
1.6
䝷䝆䜸䝯䞊䝍䛻䜘䜛୍ḟᩓ஘䜰䝹䝧䝗(SSA)䛿䚸ศගᨺᑕィ䛾᥎
AOT(ࢫ࢝࢖ࣛࢪ࣓࣮࢜ࢱ)ᐃ್䜘䜛䜒኱䛝䛟䛺䜛䚹ᅗ䠍䠖SKYNET䛾㎶ᡞᓁ䚸Ἀ⦖䝃䜲䝖䛻• 䛭䛾䝇䜹䜲䝷䝆䜸䝯䞊䝍䛸ศᨺᑕィ䛻䜘䜛AOT䛸SSA䛾ẚ㍑
䛚䛡䜛ศග᪥ᑕィ䛸䝇䜹䜲䝷䝆䜸䝯䞊䝍㻌 㻌 ⤖ᯝ䛿䚸Khatri et al. (2016)䛻♧䛧䛯䜘䛖䛻SKYNET䛸㻌 㻌㻌 㻌 AERONET㛫䛾ẚ⤖ᯝ䛸୍⮴䛩䜛䚹ᮏ◊✲䜘䜚㻿㻷㼅㻺㻱㼀䛾䝇䜹䜲㻌 㻌䛻䜘䜛䜶䜰䝻䝌䝹ගᏛⓗཌ䛥(AOT)䛾
ẚ㍑䚹
㻌 㻌 䝷䝆䜸䝯䞊䝍䛻䜘䜛㻿㻿㻭䛜኱ホ౯䛩䜛䛸䛔䛖䛣䛸䜢᫂☜䛻䛧䛯䚹AOT(ศගᨺᑕィ)䠍㻷㼔㼍㼠㼞㼕㻌 㼑㼠㻌 㼍㼘㻚㻌 㻔㻞㻜㻝㻢㻕䛸ᮏ◊✲䛛䜙᫂䜙䛛䛻䛺䛳䛯㐣኱ホ౯䛩䜛㻿㻷㼅㻺㻱㼀㻛䝇䜹䜲䝷䝆䜸䝯䞊䝍䛻䜘䜛㻿㻿㻭䛾⢭ᗘྥୖ䛻ྥ䛡䛶༓ⴥ኱䛾◊✲䜾䝹䞊䝥䛿䚸䝇䜹䜲䝷䝆䜸䝯䞊䝍䛾䛯䜑᪂䛧䛔᳨ウ᪉ἲ䛾㛤Ⓨ䛧䛶䛚䜚䚸ᮏ◊✲⪅䛜ゎᯒ䝅䝇䝔䝮䛾ᙉ໬䛻ຊ䜢ᑾ䛟䛧䛶䛔䜛䚹ලయⓗ䛻䚸MODISほ 䛛䜙ᚓ䜙䜜䜛ᆅ㠃ᆅ㠃཯ᑕ⋡䚸OMI
䛛䜙ᚓ䜙䜜䜛䜸䝌䞁㔞䜢⌧ᅾ䛾ゎᯒ䝅䝇䝔䝮䛻ᑟධ䛷䛝䜛᪉ἲ䜢ᥦ᱌䛧䚸䛭䛾ᨵⰋ∧䛾䝅䝇䝔䝮䛾᳨ウ䜢ᐇ᪋䛧䛶䛔䜛䚹

䠏ᡂᯝᒎ㛤䛾≧ἣ

SKYNET 䛾䝇䜹䜲䝷䝆䜸䝯䞊䝍䛛䜙䜶䜰䝻䝌䝹䛾䜋䛛㞼䚸Ỉ⵨Ẽ䚸䜸䝌䞁➼䛾኱Ẽ䝟䝷䝯䞊䝍䛾᥎ᐃ䜒ฟ᮶䚸䛭䜜䜙䛾㧗⢭ᗘ᥎ᐃ䛾䛯䜑䜶䜰䝻䝌䝹䛾ṇ䛧䛔᝟ሗ䛜୙ྍḞ䛷䛒䜛䚹ᮏ◊✲䛾ᡂᯝ䛿䛭䛾䜘䛖䛺኱Ẽ䝟䝷䝯䞊䝍䛾᥎ᐃཬ䜃ㄗᕪホ౯䛩䜛㝿䛻ά⏝ฟ᮶䜛䚹䜎䛯䚸ᮏ◊✲䛾ᡂᯝ䛿SKYNET䛾䛥䜙䛺䜛ᅜ㝿໬䛾䛯䜑䛻⏝䛔䜙䜜䜛䛣䛸䜢ᮇᚅ䛩䜛䚹― 55 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆C16-30䛇•㻌 㟈⅏᫬䛾ὠἼ㐳ୖ⅏ᐖ䛻䛚䛡䜛ே࿨䝸䝇䜽䛾ホ౯䛸ῶ⅏ᑐ⟇㻌 㻌 㻌 㻌 - ⚄ዉᕝ┴ᾏᓊᇦ䛾ὠἼ㐳ୖ䛻䛚䛡䜛⅏ᐖᙅ⪅䛾≉ᛶ㻌 –• Evaluation of Refuge Life Risk using㻌 Social and Geographical Models for Disaster Vulnerable㻌 Groups㻌䠄◊✲௦⾲⪅ྡ䠅㔠Ꮚ ኱஧㑻㻌 䠄(ᰴ)㻌 㐶ឤ⎔ቃ䝰䝙䝍䞊௦⾲ྲྀ⥾ᙺ䠅
Daijiro Kaneko 㻌 䠄President㻌 of㻌 Remote Sensing Environmental Monitor, Inc. 䠅䛆せ᪨䛇༡㛵ᮾᆅ㟈䛾㟈※ᇦ䛻䛒䜛•༡ᆅᇦ䛿䠈ὠἼἼ㧗䛜㤳㒔ᅪ䛾୰䛷᭱䜒㧗䛔䚹䛣䜜䜎䛷䛾◊✲䛷䛿䠈ே࿨䝸䝇䜽䛾䝰䝕䝹䛾୰䛷⅏ᐖᙅ⪅䛷䛒䜛㧗㱋⪅䛾๭ྜ䜢⤌䜏㎸䜣䛷䛝䛯䛜䠈ⱝᖺᒙ䛻䛴䛔䛶䛿ᮍ᳨ウ䛷䛒䛳䛯䠊㧗㱋⪅䜘䜚ேཱྀᩘୖ䛷䛿༙ศ௨ୗ䛸ᑠ䛥䛟䛸䜒䠈ඣ❺䛾ேⓗᦆኻ䛿♫఍ⓗ䛻ၥ㢟䛜䛒䜚䠈䛧䜀䛧䜀Ꮚ౪䛾Ṛஸ䜿䞊䝇䛻䛴䛝㑊㞴ᥐ⨨䛜㐺ษ䛷䛒䛳䛯䛛ッゴ䛜㉳䛣䛥䜜䛶䛝䛯䠊䛭䛣䛷䠈㧗㱋⪅䜀䛛䜚䛷䛺䛟ඣ❺䛾ேⓗ⿕ᐖ䛾㍍ῶ䜢┠ⓗ䛸䛧䛶䠈≉䛻㙊಴䛾ⱝᖺ㱋ᒙ䛻ὀ┠䛧䠈ே࿨䝸䝇䜽䜢᳨ウ䛧䛯䛾䛷ሗ࿌䛧䛯䠊㟈⅏᫬䛾ὠἼ䛻䜘䜛ே࿨䝸䝇䜽䛜᭱䜒㧗䛔㙊಴㥐༡㒊䛛䜙ᮦᮌᗙ࿘㎶䛻䠈⅏ᐖᙅ⪅䛷䛒䜛ඣ❺䛜ከ䛟ఫ䜣䛷䛚䜚䠈ၥ㢟䛷䛒䜛䠊䜎䛯㧗㱋⪅䛿㥐࿘㎶㒊䛻ከ䛟ᒃఫ䛧䛶䛔䜛䠊㑊㞴ᑐ⟇䜈䛾㓄៖䜔ᮌ㐀ఫᏯ䛾᭦䛺䜛㉁ⓗ⪏㟈ᛶ䛾ྥୖ䠈ᡈ䛔䛿䠈䜘䜚ᢤᮏⓗ䛺ᑐ⟇䛸䛧䛶ⴭ⪅䛜ᥦ᱌䛧䛶䛔䜛㜵⅏ᯇᯘୣ㝠䛜᭷ຠ䛷䛒䜛䠊

䛆Abstract䛇
Author has developed social and geographical models using factors such as population density,
wooden-house ratio, evacuation distance, and tsunami flooding depth to evaluate the distribution oflife risk characteristics in the area. The obtained results can contribute to the society for preparing
planning policies of disaster prevention measures for disaster vulnerable against tsunami.

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༡㛵ᮾᆅ㟈䛾㟈※ᇦ䛻䛒䜛•༡ᆅᇦ䛿䠈ὠἼἼ㧗䛜㤳㒔ᅪ䛾୰䛷᭱䜒㧗䛟䠈ῶ⅏䜢ᅗ䜙䛽䜀䛺䜙䛺䛔≉䛻㔜せ䛺ᆅᇦ䛸䛺䛳䛶䛔䜛䠊䛭䛾ᑐ⟇䛸䛧䛶ⴭ⪅䛿䠈ὠἼே࿨䝸䝇䜽♫఍䝰䝕䝹䛾㛤Ⓨ䛸㧗つ᱁ᾏᓊ㐨㊰䛸ほග㌴୧䛾㥔㌴ሙ䜢ᇙタ䛧䛺䛜䜙ᗈᇦ㑊㞴ᆅ䜢ෆⶶ䛧䛯ὠἼ㜵⅏ᯇᯘୣ㝠䛾ᘓタ䜢ᥦ᱌䛧䛶䛝䛯䠊䛣䜜䜎䛷䛾◊✲䛷䛿䠈ⱝᖺᒙ䛻䛴䛔䛶䛿ᮍ᳨ウ䛷䛒䛳䛯䠊㧗㱋⪅䜘䜚ேཱྀᩘୖ䛷䛿༙ศ௨ୗ䛸ᑠ䛥䛟䛸䜒䠈ඣ❺䛾ேⓗᦆኻ䛿♫఍ⓗ䛻ၥ㢟䛜䛒䜚䠈䛧䜀䛧䜀Ꮚ౪䛾Ṛஸ䜿䞊䝇䛻䛴䛝㑊㞴ᥐ⨨䛜㐺ษ䛷䛒䛳䛯䛛ッゴ䛜㉳䛣䛥䜜䛶䛝䛯䠊䛭䛣䛷䠈㧗㱋⪅䜀䛛䜚䛷䛺䛟ඣ❺䛾ேⓗ⿕ᐖ䛾㍍ῶ䜢┠ⓗ䛸䛧䛶䠈≉䛻㙊಴䛾ⱝᖺ㱋ᒙ䛻ὀ┠䛧䠈ே࿨䝸䝇䜽䜢᳨ウ䛧䛯䛾䛷ሗ࿌䛧䛯䠊㻌 㛤Ⓨ䛧䛯䝰䝕䝹䛾ᇶᮏ䛸䛺䜛ᙧᘧ䛿䠈㤳㒔䛾㟈⅏䛻క䛖ྠ᫬ⅆ⅏᫬䛻䛚䛔䛶ᐃᘧ໬䛧䛯⾨ᫍ฼⏝ᆺ䛾䜾䝸䝑䝗䝰䝕䝹䛷䛒䜛䠊ᮏ◊✲䛷䛿䠈ὠἼ㐳ୖ䛾ᾐỈ῝䜢ேⓗ⿕ᐖ䛜ᛴቑ䛩䜛㌺㧗䛷ᶆ‽໬䛧䠈ே࿨䝸䝇䜽䛜䠍䜢㉸䛘䜛䛺䜙䜀ᆅᙧ䞉ᶆ㧗䜔㑊㞴㊥㞳䛒䜛䛔䛿ேཱྀᐦ㞟ᆅᖏ䛷㒔ᕷィ⏬ୖ䛻ఱ䜙䛛䛾ㄢ㢟䛾䛒䜛ᆅᇦ䛷䛒䜛䛣䛸䜢ព࿡䛩䜛䚹㻌 ィ⟬䛥䜜䛯ὠἼ㑊㞴ே࿨䝸䝇䜽䛿䠈㙊಴㥐༡㒊䛛䜙ᮦᮌᗙ䛻䛛䛡䛶㧗䛟䠄ᅗ䠍䠅䠈ྠ᫬䛻⅏ᐖᙅ⪅䛾ⱝᖺ⪅䜒䛣䛾༴㝤ᆅᇦ䛻ከ䛔䛣䛸䛜䠈ྠ䛨ᆅᇦ䛾ඣ❺䛾ேཱྀᐦᗘศᕸ䛷䛒䜛ᅗ䠎䛛䜙ุ᫂䛧䛯䠊䛣䛾≧ἣ䛿䠈ඣ❺䛾ே࿨ᑛ㔜ୖ䛷኱䛔䛻ၥ㢟䛷䛒䜛䠊1)䛭䛾㑊㞴䝸䝇䜽䛾≉ᛶ䛿䚸ேཱྀ䛾㧗ᐦᗘᆅᇦ䛜䠈㙊಴ᕷ୰ᚰ㒊䛷䛒䜛㥐༡ᮾ㒊䛾ᮦᮌᗙ࿘㎶䛷䛒䜛䠊2) ඣ❺䛜䛣䛾ᕷ༡ᮾ㒊ᐦ㞟ᆅᇦ䛻⣙1,423ே䛸ከ䛔䠊୍᪉䠈㧗㱋⪅䛿㙊಴ᕷ⾤୰ᚰ㒊䛸໭㒊䛻,ඣ❺䛾⣙2ಸ䛾㧗ᐦᗘ䛷ᒃఫ䛧䛶䛔䜛䠊3䠅ඣ❺䛜ከ䛔ᮦᮌᗙ࿘㎶䛿䠈ᶆ㧗䛜ప䛟䠈ὠἼᾐỈ῝䛜኱䛝䛔䛯䜑༴㝤䛷䛒䜛䠊䜎䛯䠈㥐ᮾ༡㒊䛛䜙ᮦᮌᗙ䛻䛛䛡䛶ᮌ㐀ఫᏯ⋡䛾㧗䛔ᆅᇦ䛜ศᕸ䛩䜛䠊㻌 ᚑ䛳䛶䠈ὠἼ㑊㞴䛻ᙜ䛯䜚䠈ᗈᇦ㑊㞴ᆅ䛾㔜Ⅼⓗ䛺ᑐ⟇䜢᥇䜛䜀䛛䜚䛷䛺䛟䠈ᐙᒇಽቯ䛻䜘䜛ୗᩜ䛝䛜ከᩘ䛾↝Ṛ䜢ᣍ䛔䛯⚄ᡞ㟈⅏䛾౛䛜䛒䜛䛯䜑䠈ᩆฟ䜢ᚅ䛴㛫䛻⁒Ṛ䛩䜛ၥ㢟䜢ᅇ㑊䛩䜛ᮌ㐀ఫᏯ⪏㟈໬䛸Ᏻ඲⋡䜒㔜せ䛸䛺䜛䠊㏸Ꮚᕷ䛾⮫ᾏ㒊䛾పᆅ䛻㧗㱋⪅䛜ከᩘᒃఫ䛧䛶䛔䜛䛣䛸䜒ὀព䛫䛽䜀䛺䜙䛺䛔䠊

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≧ἣ

ᅗ1 㙊಴䛻䛚䛡䜛ὠἼே࿨䝸䝇䜽䛾㧗䛔ᆅᇦ

ᅗ2 㧗䛔ὠἼே࿨䝸䝇䜽ᇦ䛸䛭䛣䛻ఫ䜐ⱝᖺ⪅ᩘ䜢▱䜛䛣䛸䛜䛷䛝䜎䛩䚹䠍䠊㟈⅏᫬䛾ὠἼ䛻䜘䜛ே࿨䝸䝇䜽䛜᭱䜒㧗䛔㙊಴㥐༡㒊䛛䜙ᮦᮌᗙ࿘㎶䛻䠈⅏ᐖᙅ⪅䛷䛒䜛ඣ❺䛜ከ䛟ఫ䜣䛷䛚䜚䠈ῶ⅏䛾㓄៖䛜ᚲ⏝䛷䛒䜛䠊䜎䛯㧗㱋⪅䛿㥐࿘㎶㒊䛻ከ䛟ᒃఫ䛧䛶䛔䜛䠊㑊㞴䛾஦๓ィ⏬䜔ᮌ㐀ఫᏯ䛾᭦䛺䜛㉁ⓗ⪏㟈ᛶ䛾ྥୖ䛜㔜せ䛷䛒䜛䚹䜎䛯䠈䜘䜚ᢤᮏⓗ䛺ᑐ⟇䛸䛧䛶㜵⅏ᯇᯘୣ㝠䜢ᥦ᱌䛧䛶䛔䜛䠊䠎䠊䛣䜜䜙䛾ே࿨䝸䝇䜽⤖ᯝ䜢䝥䝺䝊䞁䛷♧䛧䚸㙊಴ᕷ䚸㏸Ꮚᕷ䚸⚄ዉᕝ┴ᗇ䛾⅏ᐖ䜔㒔ᕷィ⏬䛾ྛㄢ䛸䝸䝇䜽䛚䜘䜃ᑐ⟇䛸䛧䛶䛾㜵⅏ᯇᯘୣ㝠䠄ᗈᇦ㑊㞴ᆅ䚸㥔㌴ሙ䚸㧗つ᱁㐨㊰ෆ⮚䠅䛾༠㆟䜢䛧,ຓゝ䛧䜎䛧䛯䚹― 56 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌㧗⢭⣽ᆅᙧᆅ≀᝟ሗ䜢⏝䛔䛯᳜⏕ᙧ≧䛸ᆅᙧኚ໬䛾┦஫స⏝䛾ホ౯:᪥ᮏิᓥ୰㒊䛾୰㉳అὶᇦ䜢౛䛻䛆CJ16-01䛇 ᆅୖ䝺䞊䝄 㔞䛚䜘䜃SfMከどⅬ෗┿ 㔞䛻䜘䜛᳃ᯘෆ㒊䛾ᆅᙧ䞉᳜⏕ᙧ≧ィ ᡭἲ䛾☜❧Development of a methodology for topographic measurement in forests using terrestrial laser scanning and SfM-MVS photogrammetry௦⾲⪅䠖᪩ᕝ⿱ᘤ䠄ᮾி኱Ꮫ✵㛫᝟ሗ⛉Ꮫ◊✲䝉䞁䝍䞊䠅Yuichi S. Hayakawa (Center for Spatial Information Science, The University of Tokyo)ඹྠⓎ⾲⪅䠖⼎ྡ┈ோ䠄ᮾி኱Ꮫ䠅䞉ຍ⸨ 㢧䠄༓ⴥ኱Ꮫ䠅䞉ᑠⰼ࿴ᏹஅ䠄䝡䝆䝵䞁䝔䝑䜽䠅䛆せ᪨䛇ᮏ◊✲䛷䛿䚸᳃ᯘෆ䛻䛚䛡䜛ᶞᮌ䛾఩⨨䜔ᙧ≧䛾ィ 䚸䝞䜲䜸䝬䝇䛾᥎ᐃ䚸䛒䜛䛔䛿䛭䛾ᇶ┙䛸䛺䜛ᆅ⾲㠃ᙧ≧䛾ྲྀᚓ➼䜢⾜䛖䛯䜑䚸㏆ᖺᛴ㏿䛻ᬑཬ䛧䛴䛴䛒䜛ᆅୖ䝺䞊䝄 㔞䠄TLS䠅䛸SfM䠄Structure from Motion䠅ከどⅬ䝇䝔䝺䜸෗┿ 㔞䛸䛔䛳䛯ィ ᡭἲ䜢㐺⏝䛧䚸䛣䜜䜙䜢⏝䛔䛯ຠ⋡ⓗ䛺ィ 䞉ゎᯒᡭἲ䜢☜❧䛩䜛䛣䛸䜢┠ⓗ䛸䛩䜛䚹㻌 ᮏሗ࿌䛻䛚䛔䛶䛿䠈㊊ᑿᒣᆅᑠὶᇦ䠄ᰣᮌ┴㮵἟ᕷ䠅䜢୺せᑐ㇟ᆅ䛸䛧䠈୺䛻TLS䛾Ⅼ⩌䝕䞊䝍䜢⏝䛔䛶䠈ᶞᮌᙧ≧䛸ᆅᙧ⎔ቃ䛾᫬✵㛫ⓗ䛺㛵ಀ䛻䛴䛔䛶᫂䜙䛛䛻䛧䛯䚹䛩䛺䜟䛱䠈䝇䜼䞉䝠䝜䜻䛸䛔䛳䛯┤⥺ⓗ䛺ᖿᙧ≧䜢䜒䛴ᶞᮌ䛻䛴䛔䛶䠈䛭䛾ഴ䛝㔞䛸᪉఩䜢Ⅼ⩌䝕䞊䝍䜘䜚⟬ฟ䛧䠈ᩳ㠃䛾ᆅᙧ㔞䠄໙㓄䠈᪉఩䠅䛸䛾㛵ಀ䜢䠈2005ᖺ䛻ྲྀᚓ䛧䛯䝕䞊䝍䛸ẚ㍑䛧䛴䛴䠈᫬✵㛫ⓗ䛺ኚ໬䜢ᢳฟ䛧䛯䚹䛣䛖䛧䛯ᶞᮌᙧ≧䛾≉ᚩ䛿䠈ᆅᙧ䞉ᅵተ䛺䛹࿘㎶⎔ቃ䛾ᙳ㡪䜢ཷ䛡䜛䛣䛸䛜᫂♧䛥䜜䠈௒ᚋ䠈ᶞᮌᙧ≧䜢⢭ᰝ䛩䜛䛣䛸䛷䠈࿘㎶⎔ቃ䛾ኚ໬䜢㏫⟬ⓗ䛻᥎ᐹ䛩䜛ᡭἲ䛜㛤Ⓨ䛥䜜䜛䛣䛸䛜ᮇᚅ䛥䜜䜛䚹The purpose of this study is to develop an efficient method to utilize high-definition topographic data
䛆Abstract䛇
by lidar or SfM-photogrammetry for applications in forestry and geomorphology. Here we report a case study at asmall headwater channel, in which tree inclinations are found to be affected by surrounding geomorphlogicalconditions. We used multi-temporal 3D point cloud data in 2005 and 2016 to reveal the spatio-temporal changes of
the tree shape and landforms. Further applications of morphological investigations of tree shapes are expected to be
applied in other areas where geoenvironmental changes are predicted.

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ᡂᯝ

䠏

㻌 ㏆ᖺ䛾ィ ᢏ⾡䛾㐍ᒎ䛻䜘䜚䚸ᆅୖ䛻䛚䛡䜛ᑐ㇟≀䛾ᙧ≧䛻㛵䛧䛶㧗ゎീᗘ䛾3ḟඖ䝕䞊䝍䛜ẚ㍑ⓗᐜ᫆䛻ྲྀᚓ䛷䛝䜛䜘䛖䛻䛺䛳䛶䛝䛯䚹䛭䛾 㔞ᢏ⾡䛾㐺⏝ྍ⬟ᛶ䛿䚸ᆅᙧᏛ䜔㎰Ꮫ䚸᳃ᯘ⛉Ꮫ䛾ศ㔝䛻䛚䛔䛶ᗈ䜎䜚䛴䛴䛒䜛䜒䛾䛾䚸䜎䛰඘ศ䛻᳨ド䛥䜜䛯ẁ㝵䛻䛿⮳䛳䛶䛔䛺䛔䛸⪃䛘䜙䜜䜛䚹䛭䛣䛷ᮏ◊✲䛷䛿䚸ᆅୖ䝧䞊䝇䛻⾜䛖᭱᪂䛾ィ ᢏ⾡䛷䛒䜛ᆅୖ䝺䞊䝄 㔞䛚䜘䜃SfMከどⅬ䝇䝔䝺䜸෗┿ 㔞䚸䜎䛯360ᗘ䜹䝯䝷䛻䜘䜛䝟䝜䝷䝬⏬ീ䛾ྲྀᚓ䜢䚸᳃ᯘෆ䛾ᶞᮌ䜔ᆅᙧ䜢ᑐ㇟䛻ᐇ᪋䛧䚸䛭䜜䜙䛾ຠ⋡ⓗ䛺ィ ᡭἲ䛛䜙ゎᯒᡭἲ䜎䛷䛾୍㐃䛾䝥䝻䝖䝁䝹䜢☜❧䛩䜛䛣䛸䜢┠ⓗ䛸䛧䚸䛭䛾ヨ㦂ⓗ䛺ィ 䛸ゎᯒ䜢ᐇ᪋䛩䜛䚹㻌 ᮏᖺ䛾୺䛺◊✲ᡂᯝ䛿௨ୗ䛾Ⅼ䛻㞟⣙䛥䜜䜛䚹䠄䠍䠅ᆅୖ䝺䞊䝄 㔞䠄TLS䠅䛻䜘䜛ὶᇦ䛾㇂ᗏ௜㏆䛻䛚䛡䜛ᆅᙧ䛚䜘䜃᳜⏕䛾Ⅼ⩌䝕䞊䝍䜢ྲྀᚓ䛧䠈䛭䛾ᙧែⓗ≉ᚩ䛚䜘䜃᫬⣔ิኚ໬䛻䛴䛔䛶ゎᯒ䜢⾜䛳䛯䠄ᅗ1䠅䚹ᆅᙧ䛻㛵䛧䛶䛿䠈2005ᖺ䛻ྲྀᚓ䛧䛯TLS䝕䞊䝍䛸䛾ᕪศ䜢ồ䜑䠈㇂ᗏ䛚䜘䜃࿘㎶ᩳ㠃䛻䛚䛡䜛ᆅᙧኚ໬䛾᫬✵㛫ศᕸ䜢᫂䜙䛛䛻䛧䛯䚹䛩䛺䜟䛱䠈2005ᖺ䛻Ⓨ⏕䛧䛯ᅵ▼ὶ䛻䜘䜚ᛴ⃭䛻౵㣗䛥䜜䛯㇂ᗋሁ✚≀䛜䠈䛭䛾ᚋ䛾10ᖺ㛫䛻䛚䛡䜛䠈ẚ㍑ⓗ⦆䜔䛛䛺ᅵ◁⛣ື䛻䜘䜚䠈ᅵ▼ὶⓎ⏕๓䛾≧ἣ䜎䛷ᅇ᚟䛧䛴䛴䛒䜛䛣䛸䛜♧䛥䜜䛯䚹䜎䛯䠈㒊ศⓗ䛻䛿㇂ቨ䛾౵㣗䜒ほᐹ䛥䜜䛯䚹୍᪉䠈᳜⏕䛻㛵䛧䛶䛿䠈䝇䜼䞉䝠䝜䜻䛾┤⥺ⓗ䛺ᶞᖿ䛾ഴ䛝䜢䠈Ⅼ⩌䝕䞊䝍䛛䜙ᡭືィ 䛧䠈䛭䛾ゅᗘ䞉᪉఩䛾✵㛫ศᕸ䛸᫬㛫ኚ໬䜢᳨ド䛧䛯䠄ᅗ2䠅䚹ᶞᖿ䛾ഴ䛝䛿䠈䛸䛟䛻ᩳ㠃᪉఩䛸䛾㛵ಀ䛜䜏䜙䜜䠈䜎䛯䛭䛾ኚ໬䛿ᩳ㠃໙㓄䛸㛵ಀ䛩䜛䛣䛸䛜♧၀䛥䜜䛯䚹䛩䛺䜟䛱䠈ᩳ㠃᪉఩䛻䜘䜚ᶞෙ䛾୙ᆒ㉁䛺ᡂ㛗䛜ᶞᖿ䛾ഴ䛝䜢ㄏⓎ䛩䜛䛣䛸䠈䜎䛯䠈ᛴ໙㓄ᩳ㠃䛻䛚䛡䜛ᅵተ䛾୙Ᏻᐃ໬䜔㇂ᗏ䛻䛚䛡䜛ഃቨ䛾౵㣗䛜䠈䛭䛖䛧䛯ᶞᖿ䛾ഴ䛝䜢ቑ኱䛥䛫䜛䛿䛯䜙䛝䜢䜒䛴䛣䛸䛜᥎ᐹ䛥䜜䜛䚹䠄䠎䠅ᮏ◊✲䛷䛿䠈TLS䛻䜘䜚ྲྀᚓ䛥䜜䛯3ḟඖⅬ⩌䝕䞊䝍䛾ゎᯒ䛛䜙䠈᳜⏕䛸ᆅᙧ䛾ᙧ≧ⓗ≉ᚩ䛸ኚ໬ᢳฟ䛻ᡂຌ䛧䛯䚹ḟ䛾ẁ㝵䛸䛧䛶䠈UAS䠄↓ே⯟✵䝅䝇䝔䝮䠅䛻䜘䜚᧜ᙳ䛥䜜䜛ప✵✵୰෗┿䛾SfMከどⅬ䝇䝔䝺䜸෗┿ 㔞䛻䜘䜛3ḟඖ᝟ሗ䜢⏝䛔䛶䠈䜘䜚ᗈ⠊ᅖ䛻䛚䛡䜛᳜⏕ᙧ≧䛾≉ᚩ䜔ኚ໬ᢳฟ䜢⾜䛔䠈䛭䛾ᗏ㠃䛻䛚䛡䜛ᆅᙧኚ໬䜢᥎ᐃ䛷䛝䜛ྍ⬟ᛶ䜢᳨ウ䛩䜛䚹䛣䛖䛧䛯ヨ䜏䛻䜘䜚䠈㧗⢭⣽3ḟඖᙧ≧䝕䞊䝍䛾᳃ᯘ䜢୰ᚰ䛸䛧䛯䝣䜱䞊䝹䝗䝃䜲䜶䞁䝇䛻䛚䛡䜛฼ά⏝䛜㐍䜏䠈ᮏᡭἲ䛾䛔䛳䛭䛖䛾ᬑཬ䛜ᮇᚅ䛥䜜䜛䚹

ᅗ1 ㊊ᑿᒣᆅᑠὶᇦ䛾TLS䝕䞊䝍ᅗ2 ᶞᮌ䛾ഴ䛝䛾ศᕸ䛸䛭䛾ኚ໬ㄽᩥ䞉Ꮫ఍Ⓨ⾲ᡂᯝᒎ㛤䛾 •
≧ἣ•⼎ྡ┈ோ䠄2017䠅୕ḟඖⅬ⩌䝕䞊䝍䜢⏝䛔䛯ᶞᮌᙧ≧䛸ᆅᙧኚ໬䛾ゎᯒᡭἲ䛾᳨ウ䠊ᮾி኱Ꮫ኱Ꮫ㝔᪂㡿ᇦ๰ᡂ⛉Ꮫ◊✲⛉♫఍ᩥ໬⎔ቃᏛᑓᨷ2016ᖺᗘಟኈㄽᩥ䠊
Ebina, M., Hayakawa, Y.S., Kato, A. (2016) Relationships between topography and tree inclination: an approach using
multiple time series of 3D point cloud data. Abstracts, IJJSS 2016.

― 57 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-08䛇䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅䝸䝰䞊䝖䝉䞁䝅䞁䜾䛻䜘䜛⮬↛⅏ᐖ䛾⿕ᐖᢕᥱ䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Detecting damage caused by a natural disaster using remote sensing technology䠄◊✲௦⾲⪅ྡ䠅 㒓ྑ㏆㻌 ⱥ⮧㻌 䠄ᮾி኱Ꮫ⏕⏘ᢏ⾡◊✲ᡤ㒔ᕷᇶ┙Ᏻ඲ᕤᏛᅜ㝿◊✲䝉䞁䝍䞊(ICUS)䠅
Hideomi Gokon㻌 䠄ICUS, Institute of Industrial Science, The University of Tokyo䠅䛆せ᪨䛇ᮏ◊✲䛷䛿䠈2011ᖺᮾ໭ᆅ᪉ኴᖹὒἈᆅ㟈ὠἼ⿕⅏ᆅ䜢ᑐ㇟䛸䛧䠈⿕⅏๓ᚋ䛾ALOS/PALSAR⏬ീ䛾ኚ໬ᢳฟ䛻䜘䜛䠈ὶኻᘓ≀Ჷᩘ䛾᥎ィᡭἲ䜢㛤Ⓨ䛧䛯䠊ᐑᇛ┴௝ྎᕷ䛻䛚䛔䛶䠈⿕⅏๓ᚋ䛾ALOS/PALSAR⏬ീ䛾ኚ໬㔞䛸䠈ᘓ≀ὶኻ⋡䛾㛵ಀ䜢♧䛩᥎ィᘧ䜢᪂䛧䛟ᵓ⠏䛧䠈ᮏ᥎ィᘧ䛾௚ᆅᇦ䛾㐺⏝ᛶ䜢ᐑᇛ┴ர⌮⏫䛻䛶᳨ド䛧䛯䠊ᮏᘧ䛻䜘䜛䠈ᘓ≀ὶኻᲷᩘ䛾᥎ィ⢭ᗘ䛿䠈௝ྎᖹ㔝䛻䛚䛔䛶┦㛵ಀᩘ0.97䠈ர⌮⏫䛻䛚䛔䛶┦㛵ಀᩘ0.83䛷䛒䛳䛯䠊䛆Abstract䛇
A method for estimating the number of washed-away buildings based on pre- and post-event
ALOS/PALSAR data has been developed focusing on the 2011 Tohoku earthquake and tsunami. The result
showed good performance in estimating the number of washed away buildings showing correlation
coefficients of 0.97 in Sendai city and 0.83 in Watari town of Miyagi prefecture.

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

㻌䛆⫼ᬒ䞉┠ⓗ䛇㻌 ᆅ㟈䞉ὠἼ⅏ᐖ䛻䜘䜚⏕䛨䛯ᗈᇦ⿕ᐖ䜢ᢕᥱ䛩䜛䛻䛿䠈ྜᡂ㛤ཱྀ䝺䞊䝎䛻䜘䜛⾨ᫍ䝸䝰䞊䝖䝉䞁䝅䞁䜾ᢏ⾡䛜᭷ຠ䛷䛒䜛䠊䛣䜜䜎䛷䛻䠈TerraSAR-X䜔ALOS/PALSAR䠈ALOS-2/PALSAR-2䛾䜘䛖䛺X-䝞䞁䝗䜔L䝞䞁䝗䛾䝉䞁䝃䛻䜘䜛䠈ὠἼ⿕⅏ᆅ䛾ᘓ≀⿕ᐖᢕᥱᡭἲ䛜ᥦ᱌䛥䜜䛶䛝䛯䠊≉䛻䠈X-䝞䞁䝗䛻䜘䜛⿕ᐖᢕᥱ䛷䛿䠈䛭䛾㧗ศゎ⬟䜢⏕䛛䛧䠈ᘓ≀୍Ჷẖ䛾⿕ᐖᢕᥱᢏ⾡䛜㛤Ⓨ䛥䜜䛶䛝䛯䠊䛧䛛䛧䠈ᘓ≀୍Ჷ䝧䞊䝇䛾ゎᯒᡭἲ䛷䛿䠈⎰♟䛸ᘓ≀䛜」㞧䛻ධ䜚⤌䜣䛰ᆅᇦ䛻䛚䛔䛶䠈ゎᯒ⢭ᗘ䛜ⴠ䛱䜛䛸䛔䛖ㄢ㢟䛜䛒䛳䛯䠊䛭䛾ㄢ㢟䜢ゎỴ䛩䜛䛯䜑䛻䠈ⴭ⪅䜙䛿䛣䜜䜎䛷䛾◊✲䛷䜸䝤䝆䜵䜽䝖䝧䞊䝇ゎᯒ䛸⿕⅏๓ᚋ䛾TerraSAR-X⏬ീ䛾ኚ໬ᢳฟ䜢⤌䜏ྜ䜟䛫䛯䠈᪂䛧䛔ᘓ≀⿕ᐖ᥎ィᡭἲ䜢ᥦ᱌䛧䠈Ⰻዲ䛺ᘓ≀ὶኻ⋡᥎ィ⢭ᗘ䜢ᚓ䜛஦䛜䛷䛝䛯䠄Gokon et al.,2016䠅䠊ᮏ◊✲䛷䛿䠈䛣䛾X-䝞䞁䝗SAR䛻㐺⏝䛧䛯ᡭἲ䜢L-䝞䞁䝗SAR
䠄ALOS/PALSAR䠅䜈ᣑᙇ䛩䜛஦䛻䜘䜚䠈᪂䛧䛔ᘓ≀⿕ᐖ᥎ィᡭἲ䜢ᵓ⠏䛩䜛஦䜢┠ⓗ䛸䛩䜛䠊䛆᪉ἲ䛇䐟2011ᖺᮾ໭ᆅ᪉ኴᖹὒἈᆅ㟈ὠἼ⿕⅏ᆅ䜢᧜ᙳ䛧䛯䠈⿕⅏๓ᚋ䛾ྜᡂ㛤ཱྀ䝺䞊䝎⏬ീ䠄L-䝞䞁䝗
SAR䠖ALOS/PALSAR䠅䛻䜘䜚䠈┦㛵ಀᩘ⏬ീ䛾ィ⟬䛻䜘䜛䠈ኚ໬ᢳฟฎ⌮䜢⾜䛖䠊䐠⿕⅏๓䛾ᘓ≀䝫䝸䝂䞁䝕䞊䝍䛻䜘䜚䠈ᘓ≀ᇦ䛾ᢳฟ䜢⾜䛖䠊䐡ᢳฟ䛧䛯ᘓ≀ᇦෆ䛻䛚䛔䛶䠈┦㛵ಀᩘ⏬ീ䛻䜸䝤䝆䜵䜽䝖䝧䞊䝇ゎᯒ䜢㐺⏝䛧䠈ྠ㉁䛺⏬⣲䜢䜸䝤䝆䜵䜽䝖䜈ኚ᥮䛩䜛䠊䐢ྛ䜸䝤䝆䜵䜽䝖䛻䛚䛔䛶䠈ᘓ≀䛾ὶኻ⋡䛸┦㛵ಀᩘ⏬ീ䛾ᖹᆒ್䜢㛵㐃䛵䛡䠈ᘓ≀䜢30Ჷ௨ୖྵ䜐䜸䝤䝆䜵䜽䝖䛾䜏䜢ᢳฟ䛧䠈ᅇᖐศᯒ䜢᪋䛩䛣䛸䛻䜘䜚䠈┦㛵ಀᩘ⏬ീ䛾ᖹᆒ್䜢ධຊ್䠈ᘓ≀ὶኻ⋡䜢ฟຊ್䛸䛩䜛䠈ᘓ≀⿕ᐖ᥎ィᘧ䜢ᵓ⠏䛩䜛䠊

䠎
◊✲䛾
ᡂᯝ

䠍䠊L-䝞䞁䝗ྜᡂ㛤ཱྀ䝺䞊䝎䛻䜘䜛ᘓ≀⿕ᐖ᥎ィᡭἲ䜢㛤Ⓨ䛧䛯䠊ᇶ♏䛸䛺䜛᥎ィᘧ䜢ᵓ⠏䛧䛯௝ྎᖹ㔝䛻䛚䛔䛶䛿䠈ὶኻᘓ≀Ჷᩘ䛾᥎ィ⢭ᗘ䛿┦㛵ಀᩘ0.97䛸䠈Ⰻዲ䛺ᩘ್䜢ᚓ䜛஦䛜䛷䛝䛯䠊䠎䠊ୖグ䛾ᘓ≀⿕ᐖ᥎ィᡭἲ䜢௚ᆅᇦ䛻㐺⏝䛧䠈ᘓ≀ὶኻᲷᩘ䛾᥎ィ䛾⢭ᗘ᳨ド䜢⾜䛳䛯䠈䛭䛾⤖ᯝ䠈┦㛵ಀᩘ0.83䛸Ⰻዲ䛺᥎ィ⢭ᗘ䜢ᚓ䜙䜜䜛஦䛜䜟䛛䛳䛯䠊
ᅗ1 ᐇ㝿䛾ᘓ≀⿕ᐖ᥎ィ䛾౛䠊䜎䛪䠈༊⏬
䝧䞊䝇䛷ᘓ≀ὶኻ⋡䛾ゎᯒ䜢⾜䛔䠈ḟ䛻䠈⿕⅏๓䛾ᘓ≀Ჷᩘ䛸䛭䛾ὶኻ⋡䜢᥃䛡ྜ䜟䛫䜛஦䛷䠈ᘓ≀ὶኻᲷᩘ䜢᥎ィ䛩䜛䠊

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

ᮏᡂᯝ䛾䠈♫఍ᐇ⿦䜈䛾ྍ⬟ᛶ䛻䛴䛔䛶⌧ᅾ◊✲䛷䛒䜛䠊ලయⓗ䛻䛿䠈GIS㛵ಀ䛾ᴗ⪅䜔ಖ㝤ᴗ⏺䜈䠈ᮏ◊✲ᡂᯝ䛾⅏ᐖⓎ⏕┤ᚋ䛾฼⏝ᕼᮃ᪉ἲ䛻䛴䛔䛶䠈⪺䛝ྲྀ䜚䛻䜘䜛䝙䞊䝈ㄪᰝ䜢ᐇ᪋䛧䛯䠊䜎䛯䠈ᡂᯝ䛾୍㒊䛿䠈Journal of Disaster Research (JDR)䜈ᥖ㍕ணᐃ䠄㻴㼕㼐㼑㼛㼙㼕㻌㻳㼛㼗㼛㼚㻘㻌㻿㼔㼡㼚㼕㼏㼔㼕㻌㻷㼛㼟㼔㼕㼙㼡㼞㼍㻌㼍㼚㼐㻌㻷㼕㼙㼕㼞㼛㻌㻹㼑㼓㼡㼞㼛㻘㻌㼂㼑㼞㼕㼒㼕㼏㼍㼠㼕㼛㼚㻌㼛㼒㻌㼍㻌㼙㼑㼠㼔㼛㼐㻌㼒㼛㼞㻌㼑㼟㼠㼕㼙㼍㼠㼕㼚㼓㻌㼎㼡㼕㼘㼐㼕㼚㼓㻌㼐㼍㼙㼍㼓㼑㻌㼕㼚㻌㼑㼤㼠㼑㼚㼟㼕㼢㼑㻌㼠㼟㼡㼚㼍㼙㼕㻌㼍㼒㼒㼑㼏㼠㼑㼐㻌㼍㼞㼑㼍㼟㻌㼡㼟㼕㼚㼓㻌㻸㻙㼎㼍㼚㼐㻌㻿㻭㻾㻌㼐㼍㼠㼍㻘㻌㻶㼛㼡㼞㼚㼍㼘㻌㼛㼒㻌㻰㼕㼟㼍㼟㼠㼑㼞㻌㻾㼑㼟㼑㼍㼞㼏㼔㻌㻔㻶㻰㻾㻕㻘㻌㼂㼛㼘㻚㻝㻞㻘㻌㻺㼛㻚㻞㻘㻌㻞㻜㻝㻣䠅䠊― 58 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-18䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅✵᧜⏝↓ே䝦䝸䝁䝥䝍䛻䜘䜛〄ᆅ⏬ീ䜢⏝䛔䛯ὸ♟༊ᇦ䛾ᢳฟ(◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Estimating shallow gravel area using bare soil image obtained froman unmanned helicopter䠄◊✲௦⾲⪅ྡ䠅 ୹⩚㻌 ຾ஂ㻌 䠄ᰴᘧ఍♫䝈䝁䞊䝅䝱䞉⥲ྜ⛉Ꮫ◊✲ᡤ䠅
Katsuhisa Niwa 㻌 䠄Zukosha Co., Ltd 䞉Synthetic Science Institute䠅䛆せ᪨䛇໭ᾏ㐨䛾኱つᶍ⏿సᆅᖏ䛷䛿䚸⫧Ỻᗘ௨እ䛻䚸ὸ♟ᒙ䜔᤼Ỉ୙Ⰻ䛻䜘䜚ᅡሙෆ䛾స≀⏕⫱䛜୙ᆒ୍䛷䛒䜛䚹䛭䛣䛷䚸ᅡሙෆ䛾ὸ♟༊ᇦ䜢ヲ⣽䛻ᢕᥱ䛩䜛䛯䜑䛻䚸✵᧜⏝↓ே䝦䝸䝁䝥䝍䜢⏝䛔䛶஝⇱᫬䚸㝆㞵┤ᚋ䛾〄ᆅ⏬ീ䜢᧜ᙳ䛧䛯䚹䛭䛾⤖ᯝ䚸஝⇱᫬䛾⏬ീ䛷䛿ὸ♟༊ᇦ䛸䛭䛾௚༊ᇦ䛻ᕪ␗䛜ぢ䜙䜜䛺䛛䛳䛯䛜䚸㝆㞵┤ᚋ䛾⏬ീ䛷䛿୧⪅䛻ᕪ␗䛜䛒䜚䚸ὸ♟༊ᇦ䛷䚸䛭䛾௚༊ᇦ䜘䜚䜒᫂䜙䛛䛻⥳ᇦ䛾཯ᑕ䝕䞊䝍䛜኱䛝䛔䛣䛸䜢☜ㄆ䛧䛯䚹䛣䛾䛣䛸䛛䜙䚸㝆㞵┤ᚋ䛾〄ᆅ⏬ീ䛛䜙ὸ♟༊ᇦ䛜ヲ⣽䛻ᢕᥱ䛷䛝䜛ྍ⬟ᛶ䛜♧၀䛥䜜䛯䚹

䛆Abstract䛇 Large upland fields of Hokkaidou, crop growth within a field were effected by soil fertility, shallow gravel
layer and poor drainage. This research aimed to estimate shallow gravel layer in an alluvial upland fields
of Hokkaidou using bare soil image obtained from an unmanned helicopter. We obtained drought andwet bare soil images and the relationship between image data and shallow gravel area were investigated.
As a result , we could understand the areas of shallow gravel layer from image data with wet soil
condition.

䠎
◊✲䛾
ᡂᯝ

໭ᾏ㐨䛾኱つᶍ⏿సᆅᖏ䛷䛿ᅡሙෆ䛾⫧Ỻᗘ䛾䝞䝷䝒䜻䜢⪃៖䛧䛯ྍኚ᪋⫧䛾ྲྀ䜚⤌䜏䛜ጞ䜎䛳䛶䛔䜛䛜䚸స≀⏕⏘䛿⫧Ỻᗘ௨እ䛻䚸ὸ♟䜔᤼Ỉ୙Ⰻ䛻ᙳ㡪䜢ཷ䛡䛶䛔䜛䛸䛔䛖≧ἣ䛜ᮏ◊✲䛾⫼ᬒ䛸䛧䛶䛒䜛䚹ᮏ◊✲䛾┠ⓗ䛿ᅡሙ䛾ὸ♟ᒙ䛾༊ᇦ䜢〄ᆅ⏬ീ䛛䜙ᢕᥱ䛩䜛䛣䛸䛷䛒䜛䚹䛣䛾䛯䜑䚸Ἑᡂሁ✚≀䜢ẕᮦ䛸䛩䜛Ἀ✚ᅵ䜢ᑐ㇟䛸䛧䚸⡆᫆ヨ᥀ㄪᰝ䛻䜘䜚ὸ♟ᆅⅬ䛾ᢕᥱ䜢⾜䛳䛯䚹䛥䜙䛻✵᧜⏝↓ே䝦䝸䝁䝥䝍䛻ᦚ㍕䛧䛯ගᏛ䝉䞁䝃䜢⏝䛔䛶ᑐ㇟ᅡሙ䛾⾲ᒙᅵተ䜢᧜ᙳ䛩䜛᪉ἲ䜢᥇⏝䛧䚸஝⇱᫬䚸㝆㞵┤ᚋ䛾2᫬ᮇ䛾⏬ീ䛛䜙䚸 ὸ♟༊ᇦ䛾ᢳฟ䜢ヨ䜏䛯䚹䠄䠍䠅✵᧜⏝↓ே䝦䝸䝁䝥䝍䛾〄ᆅ⏬ീ䛛䜙䚸஝⇱᫬䛾⏬ീ䛿ᅡሙෆ䛾ᅵⰍ䛾ኚ໬䛜ᑠ䛥䛟䚸ᴫ䛽ᆒ୍䛷䛒䛳䛯䚹䛭䜜䛻ᑐ䛧䛶䚸㝆㞵┤ᚋ䛾〄ᆅ⏬ീ䛻䛿䚸ⓑ䛔➽≧䛾⑞㊧䛜ㄆ䜑䜙䜜䚸᫂䜙䛛䛻ᅵⰍ䛜ᅡሙෆ䛷୙ᆒ୍䛷䛒䜛䛣䛸䜢☜ㄆ䛧䛯䠄ᅗ䠍䠅䚹ᅵተ஝⇱᫬䠄䠎)ὸ♟ᆅⅬ䛸䛭䛾௚ᆅⅬ䛾⏬ീ䝕䞊䝍䜢ẚ㍑
䛩䜛䛸䚸ᅵተ஝⇱᫬䛾⏬ീ䝕䞊䝍䛻䛿ᕪ䛜ㄆ䜑䜙䜜䛺䛛䛳䛯䛾䛻ᑐ䛧䛶䚸㝆㞵┤ᚋ䛾⏬ീ䛷䛿୧ᆅⅬ䛻ᕪ␗䛜ぢ䜙䜜䛯䚹౛䛘䜀䚸⥳ᇦ䛾཯ᑕ䛷䛿䚸ὸ♟ᆅⅬ䛻䛚䛔䛶䛭䛾௚䛾ᆅⅬ䜘䜚䜒᫂䜙䛛䛻㧗䛔್䜢♧䛧䛯(ᅗ2)䚹

⥳ᇦࡢ཯ᑕࢹ࣮ࢱ

䠄䠏䠅௨ୖ䛾䛣䛸䛛䜙䚸Ἀ✚ᅵᆅᖏ䛻䛚䛔䛶䛿䚸㝆㞵┤ᚋ䛾⏬ീ䜢฼⏝䛩䜛䛣䛸䛷ὸ♟༊ᇦ䛾⢭ᐦ䛺ᢳฟ䛜ྍ⬟䛷䛒䜛䛣䛸䛜᫂䜙䛛䛻䛺䛳䛯䚹⢭ᐦ䛺ὸ♟༊ᇦ䛾ᢳฟ䛿㝖♟సᴗ䛾ຠ⋡໬䜔䚸ྍኚ᪋⫧➼䜢⾜䛖ሙྜ䛾ᇶ♏᝟ሗ䛸䛧䛶᭷┈䛰䛸⪃䛘䜙䜜䜛䚹

ᅗ1ゎᯒ䛻฼⏝䛧䛯⏬ീ




ᅵተ஝⇱᫬









p = 0.4912








p = 0.002






ὸ♟ᆅⅬ

ᅗ2

㝆㞵┤ᚋ



⥳ᇦࡢ཯ᑕࢹ࣮ࢱ

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

ࡑࡢ௚ᆅⅬ

ὸ♟ᆅⅬ

ࡑࡢ௚ᆅⅬ

ὸ♟ᆅⅬ䛸䛭䛾௚ᆅⅬ䛾⏬ീ䝕䞊䝍

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

㛤Ⓨ䛧䛯ᡭἲ䛛䜙䚸ὸ♟䝬䝑䝥䜢సᡂ䛧䚸䛭䛾䝬䝑䝥䛻ᇶ䛵䛔䛯ྍኚ᪋⫧䛾◊✲䛻⏝䛔䜙䜜䛶䛔䜛䚹― 59 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-25䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅ኪ㛫ග⾨ᫍ⏬ീ䛚䜘䜃GIS䜢฼⏝䛧䛯ୡ⏺䛾⣲ᮦ䝇䝖䝑䜽䛾᥎ィ㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Estimation of in-use stock of materials in global scale using nighttime light images㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 and GIS䠄◊✲௦⾲⪅ྡ䠅 ᯇ㔝㻌 Ὀஓ㻌 䠄༓ⴥ኱Ꮫ኱Ꮫ㝔ᕤᏛ◊✲⛉㒔ᕷ⎔ቃ䝅䝇䝔䝮䝁䞊䝇䠅
Yasunari Matsuno㻌 䠄Dept. of Urban Environment Systems, Chiba University䠅ᮏ◊✲䛷䛿䚸୰ᅜ䞉ᮾ༡䜰䝆䜰䜢ᑐ㇟䛻䚸ᑠᆺ㟁Ẽ䞉㟁Ꮚᶵჾ䛻ྵ᭷䛥䜜䜛㔠䛻㛵䛩䜛ືⓗ䝬䝔䝸䜰䝹䝣䝻䞊ศᯒ(MFA)䜢⾜䛳䛯䚹ືⓗMFA䜢ᐇ᪋䛩䜛䛯䜑䛾䝕䞊䝍䛜ᚓ䜙䜜䛺䛔ᅜ䛻㛵䛧䛶䛿䚸ኪ㛫ග⾨ᫍ⏬ീ(Radiancecalibrated composite)䜢⏝䛔䚸㔠䛾䝇䝖䝑䜽㔞䜢᥎ィ䛧䛯䚹୰ᅜ䞉ᮾ༡䜰䝆䜰䛻䛚䛡䜛㟁Ẽ㟁Ꮚᶵჾ⏝㏵䛾㔠䛾
䝇䝖䝑䜽㔞䛿2007ᖺ䛛䜙2012ᖺ䛻䛛䛡䛶ୖ᪼䛧䚸2012ᖺ᫬Ⅼ䛷䛿360 䝖䞁 䜒䛾㔠䛜䝇䝖䝑䜽䛥䜜䛶䛔䜛䛣䛸䛜᥎ィ䛥䜜䛯䚹ኪ㛫ග⾨ᫍ⏬ീ䜢⏝䛔䛯ゎᯒ䛻䜘䜚䚸ືⓗMFA䛜㐺⏝䛷䛝䛺䛔ᅜ䛻䛚䛔䛶䚸2010ᖺ䛻䛚䛔䛶8.3䝖䞁
䛾㔠䛜䝇䝖䝑䜽䛥䜜䛶䛔䜛䛣䛸䛜᥎ィ䛥䜜䛯䚹

䛆Abstract䛇

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

In this work, a dynamic material flow analysis (MFA) of gold in China and South East Asian
countries were conducted to estimate the in-use stock in electric and electronic equipment.
Radiance calibrated nighttime light composites were used to estimate the in-use stock in whichdata were not available for the dynamic MFA. It was calculated that in-use stock of gold
increased during 2007 to 2012, resulted in 360 t in 2012. It was estimated that another 8.3 t ofgold was estimated in 2010 by using the nighttime light images.

㻌 ௒ᚋ䚸ୡ⏺ྛᅜ䛾⤒῭Ⓨᒎ䛜㐍䜐୰䛷䚸⣲ᮦ䛾ᣢ⥆ⓗ䛺౑⏝䛜ồ䜑䜙䜜䛶䛚䜚䚸⣲ᮦྛ✀䛾♫఍䛷䛾䝣䝻䞊䛸䝇䝖䝑䜽䛾ᢕᥱ䛜㔜せど䛥䜜䛶䛔䜛䚹䛭䜜䜖䛘䚸ྛ✀⣲ᮦ䛾ືⓗ䝬䝔䝸䜰䝹䝣䝻䞊ゎᯒ(Material Flow
Analysis, MFA)䛜┒䜣䛻ᐇ᪋䛥䜜䛶䛔䜛䛜䚸⤫ィ䝕䞊䝍䛾ᚓ䜙䜜䛺䛔ᅜ䛻㛵䛧䛶䛿䚸ືⓗMFA䜢ᐇ᪋䛩䜛䛣䛸䛜䛷䛝䛺䛔䚹䛭䛣䛷䚸ᮏ◊✲⪅䜙䛿䚸ே㛫䛾άື䛸ᙉ䛔┦㛵䛾ᣢ䛴ኪ㛫ගᙉᗘ䜢⏝䛔䛶⣲ᮦ䝇䝖䝑䜽㔞䜢᥎ィ䛩䜛䛣䛸䜢ᥦ᱌䛧䛶䛝䛯䚹㻌 ᮏ◊✲䛷䛿䚸ᑗ᮶䛾ேཱྀ䛾ቑ኱䛸⤒῭Ⓨᒎ䛻క䛔ྛ✀⣲ᮦ䛾䝇䝖䝑䜽㔞䛜ቑຍ䛩䜛䛸⪃䛘䜙䜜䛶䛔䜛୰ᅜ䞉ᮾ༡䜰䝆䜰䜢ᑐ㇟䛻䚸ᑠᆺ㟁Ẽ䞉㟁Ꮚᶵჾ䛻ྵ᭷䛥䜜䜛㔠䜢౛䛻ືⓗ䝬䝔䝸䜰䝹䝣䝻䞊ศᯒ䜢⾜䛔䚸㔠䛾䝇䝖䝑䜽㔞䜢᥎ィ䛩䜛䛣䛸䜢┠ⓗ䛸䛩䜛䚹䛥䜙䛻䚸⤫ィ䝕䞊䝍䛾ᚓ䜙䜜䛺䛔ᅜ䛻㛵䛧䛶䛿䚸ኪ㛫ග⾨ᫍ⏬ീ䜢฼⏝䛧䚸㔠䛾䝇䝖䝑䜽㔞䜢᥎ィ䛩䜛䛣䛸䜢┠ⓗ䛻䛩䜛䚹䠄䠍䠅⤫ィ䝕䞊䝍䛻ᇶ䛵䛔䛶2007ᖺ䛛䜙2012ᖺ䜎䛷䛾୰ᅜ䛚䜘䜃ᮾ༡䜰䝆䜰ㅖᅜ䛻䛚䛡䜛㟁Ẽ㟁Ꮚᶵჾ䠄ᦠᖏ㟁ヰ䚸䝟䝋䝁䞁䚸䝡䝕䜸䜹䝯䝷䚸䜹䝯䝷䚸䜸䞊䝕䜱䜸䚸CD䝥䝺䜲䝲䞊䚸㟁Ꮚ䝺䞁䝆䚸Ὑ℆ᶵ䚸ᤲ㝖ᶵ䚸ᤲ㝖ᶵ䚸⮬ື㌴䚸㟁ヰᶵ䠅⏝㏵䛾㔠䛾䝇䝖䝑䜽㔞䜢᥎ィ䛧䛯䚹䠄ᅗ䠍䠅㻌 ୰ᅜ䞉ᮾ༡䜰䝆䜰䛻䛚䛡䜛㟁Ẽ㟁Ꮚᶵჾ⏝㏵䛾㔠䛾䝇䝖䝑䜽㔞
䛿2007ᖺ䛛䜙2012ᖺ䛻䛛䛡䛶ୖ᪼䛧䚸2012ᖺ᫬Ⅼ䛷䛿360 䝖䞁䜒䛾㔠䛜䝇䝖䝑䜽䛥䜜䛶䛔䜛䛣䛸䛜᥎ィ䛥䜜䛯䚹㻌 ရ┠ู䛷䛿䜸䞊䝕䜱䜸䛻䜘䛳䛶ከ䛟䛾㔠䛜䝇䝖䝑䜽䛥䜜䛶䛚䜚䚸䛭䛾⌮⏤䛸䛧䛶䚸୍ྎᙜ䛯䜚䛾ᢞධ㔞䛜኱䛝䛔䛣䛸䜔౑⏝ᖺᩘ䛜ᖹᆒ䛷⣙18ᖺ䛸㛗䛔䛯䜑䛷䛒䜛䚹
䠄䠎䠅2010ᖺ䛻䛚䛡䜛ኪ㛫ග⾨ᫍ⏬ീ(Radiance calibrated
1)
composite)䜢⏝䛔 䚸⤫ィ䝕䞊䝍䛾ᚓ䜙䜜䛺䛔ᅜ䛻㛵䛧䛶ኪ㛫ග䛸୍ேᙜ䛯䜚䛾䝇䝖䝑䜽㔞䛸䛾┦㛵䜢᳨ウ䛧䛯䛸䛣䜝䚸㧗䛔┦㛵䛜☜ㄆ䛥䜜䛯䚹ᚓ䜙䜜䛯┦㛵ᘧ䛛䜙䝭䝱䞁䝬䞊䛚䜘䜃䝤䝹䝛䜲䛾㔠䛾䝇䝖䝑䜽㔞䜢᥎ィ䛧䛯⤖ᯝ䚸2010ᖺ䛻䛚䛔䛶᪂䛯䛻8.3䝖䞁䛾㔠䛜䝇䝖䝑䜽䛥䜜䛶䛔䜛䛣䛸䛜᥎ィ䛥䜜䛯䚹1) ᭹㒊䜙䚸ᮾி኱Ꮫ኱Ꮫ㝔ಟኈㄽᩥ(2015)

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

䝧䝖䝘䝮
䝅䞁䜺䝫䞊䝹
䜲䞁䝗䝛䝅䜰
୰ᅜ

400

䝍䜲
䝬䝺䞊䝅䜰
䝣䜱䝸䝢䞁

350

䝇䝖䝑䜽㔞 [t]

䛆せ᪨䛇

300
250
200
150
100
50
0
2007 2008 2009 2010 2011 2012

ᖺᅗ1

ືⓗMFA䛻䜘䜛ᅜูᑠᆺ㟁Ẽ䞉㟁Ꮚᶵჾ୰䛾㔠䛾䝇䝖䝑䜽㔞䛾᥎ィ⤖ᯝᮏ◊✲䛷䛿䚸୰ᅜ䞉ᮾ༡䜰䝆䜰䛻䛚䛡䜛ᑠᆺ㟁Ẽ䞉㟁Ꮚᶵჾ୰䛾㔠䛾䝇䝖䝑䜽㔞䛾᥎ィ䜢┠ⓗ䛸䛧䛶䛔䜛䛜䚸
㛤Ⓨ䛧䛯ᡭἲ䛿䚸ᇶ┙䝬䝔䝸䜰䝹䛷䛒䜛䚸ୡ⏺䛻䛚䛡䜛ᅵᮌ䛚䜘䜃ᘓ⠏䛻⏝䛔䜙䜜䛶䛔䜛㗰ᮦ䛾䝇䝖䝑䜽㔞䛾᥎ィ䛻䜒⏝䛔䜙䜜䛶䛔䜎䛩䚹䠄Feng-Chi Hsu, Christopher D. Elvidge and Yasunari Matsuno, Exploringand estimating in-use steel stocks in civil engineering and buildings from night-time lights, International
Journal of Remote Sensing, Vol.34, No.2, (2013) , 490-504䠅

― 60 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-32䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅䝅䝭䝳䝺䞊䝅䝵䞁䝰䝕䝹䛸䝸䝰䞊䝖䝉䞁䝅䞁䜾䜢⏝䛔䛯Ỉ✄⏕⏘㔞᥎ᐃἲ䛾᳨ウ㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Developing estimation method of rice yield based on simulation modelwith remote sensing䠄◊✲௦⾲⪅ྡ䠅 ᮏ㛫㻌 㤶㈗㻌 䠄ᮾ໭኱Ꮫ䞉㎰Ꮫ◊✲⛉䠅
Koki Homma 㻌 䠄Graduate School of Agricultural Science, Tohoku University䠅䛆せ᪨䛇ᮏ◊✲䛷䛿䝸䝰䞊䝖䝉䞁䝅䞁䜾䜢฼⏝䛧䛯Ỉ✄䛾཰㔞᥎ᐃ᪉ἲ䜢䜘䜚ỗ⏝໬䛩䜛䛯䜑䛻䠈䝅䝭䝳䝺䞊䝅䝵䞁䝰䝕䝹䛸䛾⤖ྜ䜢┠ᣦ䛧䛶䛔䜛䠊ᮏᖺᗘ䛿䛭䛾䛯䜑䛾䝸䝰䞊䝖䝉䞁䝅䞁䜾ᡭἲ䛸䛧䛶䝗䝻䞊䞁䛻䜘䜛✵᧜䜢᳨ウ䛧䛯䠊䝗䝻䞊䞁䛻䜘䜛✵᧜⏬ീ䛿ゎീᗘ䛜㧗䛔཯㠃䠈ᆅୖィ 䛸఩⨨䛾୙ᩚྜ䛜ㄢ㢟䛸䛺䜚䠈ゎᯒ᪉ἲ䛻䜘䜚୍ᒙ䛾ᨵⰋ䛜ᚲせ䛷䛒䜛䛸⪃䛘䜙䜜䛯䠊୍᪉」ᩘ᫬ᮇ䜢ྜ䜟䛫䛶NDVI䛾ቑຍ⋡䜢ồ䜑䜛䛣䛸䛻䜘䜚䠈཰㔞䛸䛾᭷ព䛺┦㛵䜢♧䛩䛣䛸䛜䛷䛝䛯䛯䜑䠈䝗䝻䞊䞁⏬ീ䜢⏝䛔䛶䝅䝭䝳䝺䞊䝅䝵䞁䝰䝕䝹䜢⿵ṇ䛩䜛䛣䛸䛻䜘䜚཰㔞䛜᥎ᐃྍ⬟䛷䛒䜛䛣䛸䛜♧၀䛥䜜䛯䠊

䛆Abstract䛇 This study aims to improve the simulation model with remote-sensing to estimate rice yield in order toenhance the adaptability of the model. This year we tried to use UAV to obtain the data to calibrate thesimulation model. The data by UAV showed its resolution was too high to be calibrated by GPS,
recommending new analysis method should be developed. However, the increase rate of NDVI which
was obtained by using 4 consequent data was significantly correlated with rice yield, suggesting the rice
simulation model calibrated by the UAV data can estimate rice yield.

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䝸䝰䞊䝖䝉䞁䝅䞁䜾䜢฼⏝䛧䛯Ỉ✄䛾཰㔞᥎ᐃ᪉ἲ䛿ᐇ⏝໬ᡭẁ䛸䛧䛶☜❧䛧䛴䛴䛒䜛䜒䛾䛾䠈㐺ษ䛺᫬ᮇ䛻⾨ᫍ⏬ീ䛜ᚓ䜙䜜䛺䛔䛣䛸䜔䠈ᅡሙ䛤䛸䛻᱂᳜᪥䛜␗䛺䜛䛣䛸䛻䜘䜛ᙳ㡪䛺䛹ᵝ䚻䛺ㄢ㢟䛜ṧ䛳䛶䛔䜛䠊ᮏ◊✲䛷䛿䛭䛾ゎỴᡭẁ䛾୍䛴䛸䛧䛶䝅䝭䝳䝺䞊䝅䝵䞁䝰䝕䝹䛾฼⏝䜢ヨ䜏䠈㐺⏝᪉ἲ䜢᳨ウ䛩䜛䠊ᮏᖺᗘ䛿䝸䝰䞊䝖䝉䞁䝅䞁䜾⏬ീ䛾ྲྀᚓᡭἲ䛾୍䛴䛸䛧䛶䠈䝗䝻䞊䞁䛾฼⏝䜢᳨ウ䛧䛯䠊䠄䠍䠅Ỉ✄䛾⏕⫱᫬ᮇ䛻ྜ䜟䛫䛶ィ4ᅇ䛾䝗䝻䞊䞁䛻ᦚ㍕䛧䛯䝬䝹䝏䝇䝨䜽䝖䝷䝹䜹䝯䝷䛷᧜ᙳ䜢⾜䛳䛯䠊NDVI䛺䛹䝸䝰䞊䝖䝉䞁䝅䞁䜾䛻䜘䜛ᣦᶆ್䛸䠈Ỉ✄䛾ⴥ㠃✚䛺䛹䛾⏕⫱್䛸䛾ᑐᛂ䜢ぢ䛯䛸䛣䜝䠈඲4ᅇ䛾䝕䞊䝍䜢ྜ䜟䛫䜛䛣䛸䛻䜘䜚᭷ព䛺㛵ಀᛶ䛜ᚓ䜙䜜䛯䜒䛾䛾䠈ྛィ 䛻䛚䛔䛶䛿ኚື䛜኱䛝䛛䛳䛯䠊䛣䜜䛿䝗䝻䞊䞁䛻䜘䜚㧗ゎീᗘ䛾䝕䞊䝍䛜ᚓ䜙䜜䜛䛾䛻཯䛧䠈఩⨨⢭ᗘ䛜ప䛔䛾䛜୍ᅉ䛷䠈ゎᯒἲ䛻᭦䛺䜛ᨵⰋ䛜ᚲせ䛸⪃䛘䜙䜜䛯䠊䠄䠎䠅ྛィ 䛻䛚䛡䜛NDVI䛛䜙ⴥ㠃✚䛾᥎ᐃ䛿⢭ᗘ䛜ప䛛䛳䛯䠊୍᪉䠈4ᅇ䛾ィ ⏬ീ䜢⏝䛔䛶NDVIቑຍ⋡䜢ồ䜑䜛䛸䠈ྛィ 䛻䛚䛡䜛ㄗᕪ䛜┦ẅ䛥䜜䜛䛸⪃䛘䜙䜜䜛䠊䛭䛣䛷NDV䛔ቑຍ⋡䜢ồ䜑䛶䠈Ỉ✄཰㔞䛸䛾┦㛵䜢ồ䜑䛯䛸䛣䜝᭷ព䛺㛵ಀᛶ䛜ᚓ䜙䜜䛯䠄ᅗ1䠅䠊䛣䛾䛣䛸䛿⤒᫬ⓗ䛻ィ 䛧䛯䝗䝻䞊䞁⏬ീ䜢⏝䛔䛶䝅䝭䝳䝺䞊䝅䝵䞁䝰䝕䝹䜢⿵ṇ䛩䜛䛣䛸䛻䜘䜚཰㔞䛜᥎ᐃྍ⬟䛷䛒䜛䛣䛸䜢♧၀䛩䜛䠊

ᅗ1 NDVIቑຍ⋡䛸཰㔞䛾㛵ಀ䠄䠏䠅ୖグ⤖ᯝ䛻ᇶ䛵䛝NDVIቑຍ⋡䛾ᅡሙෆኚ␗䜢ᆅᅗ໬䛧䛯䠄ᅗ2䠅䠊䛣䛾䜘䛖䛻䛧䛶♧䛥䜜䜛ᅡሙෆኚ␗䛿䠈୍᫬ᮇ䛾NDVI䛾ኚ␗䛺䛹䛷♧䛥䜜䜛ᅡሙෆኚ␗䜘䜚䜒䠈ᅵተ⫧Ỻᗘኚ␗䛻ᐦ᥋䛻䛛䛛䜟䛳䛶䛔䜛䛸⪃䛘䜙䜜䠈⫧ᇵ⟶⌮䛺䛹䛻᭷ຠ䛷䛒䜛䛸⪃䛘䜙䜜䜛䠊
ᅗ2 NDVIቑຍ⋡䛾ᅡሙෆኚ␗

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㛤Ⓨ䛧䛯ᡭἲ䛿ᮏ㒓༓᫓෸ᩍᤵ䛜௦⾲䜢ົ䜑䜛JST-JICAᆅ⌫つᶍㄢ㢟ᑐᛂᅜ㝿⛉Ꮫᢏ⾡༠ຊ䝥䝻䜾䝷䝮䛂㣗ᩱᏳ඲ಖ㞀䜢┠ᣦ䛧䛯Ẽೃኚື㐺ᛂ⟇䛸䛧䛶䛾㎰ᴗಖ㝤䛻䛚䛡䜛ᦆᐖホ౯ᡭἲ䛾ᵓ⠏䛸♫఍ᐇ⿦䛃䛻䛚䛔䛶ά⏝䛥䜜䜛ணᐃ䛷䛒䜛䠊― 61 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-34䛇㻌㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅䜲䞁䝗䝛䝅䜰䚸䝞䝸ᓥ䛻䛚䛡䜛䠎䠌䠍䠑ᖺ䛾䜶䝹䝙䞊䝙䝵⌧㇟䛻䜘䜛㎰ᴗᖸ䜀䛴䛾ᙳ㡪㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅 Impacts of El Nino㻌 䠎䠌䠍䠑 on Agriculture Drought in Bali, Indonesia䠄◊✲௦⾲⪅ྡ䠅 ኱⃝㻌 㧗ᾈ㻌 䠄䜴䝎䝲䝘኱Ꮫ䞉ᾏὒ⛉Ꮫ䝸䝰䞊䝖䝉䞁䝅䞁䜾◊✲䝉䞁䝍䞊䠅
Takahiro Osawa 㻌 䠄Udayana University 䞉Center for Remote Sensing and Ocean Sciences䠅䛆せ᪨䛇䜶䝹䝙䞊䝙䝵⌧㇟䛿䚸䜲䞁䝗䝛䝅䜰䛾㎰ᴗ⏕⏘㔞䛾పୗ䜢䜒䛯䜙䛩䛸䛥䜜䛶䛔䜛䚹㝆㞵㔞䛾ῶᑡ䛿䚸⤖ᯝ䛸䛧䛶䜲䞁䝗䝛䝅䜰䠄䝞䝸ᓥ䠅䛷ᖸ䜀䛴䜢ᘬ䛝㉳䛣䛧䛶䛔䜛䚹 2015ᖺ䛾䜶䝹䝙䞊䝙䝵⌧㇟䛿䚸1997ᖺ௨᮶䛾᭱䜒኱䛝䛺䜶䝹䝙䞊䝙䝵⌧㇟䛾1䛴䛻䛺䜛ྍ⬟ᛶ䛜䛒䜛䚹䝞䝸ᓥ䛾㎰ᴗ⏕⏘㔞䜢ุ᩿䛩䜛䛯䜑䛻䚸䝸䝰䞊䝖䝉䞁䝅䞁䜾䝕䞊䝍䛻ᇶ䛵䛟᳜⏕೺ᗣᣦᩘ䠄VHI䠅䜢ィ⟬䛧䛯䚹 ⤖ᯝ䛸䛧䛶䚸2015ᖺ䛾䜶䝹䝙䞊䝙䝵⌧㇟䛿䚸⡿䛚䜘䜃㔝⳯స≀䛾㎰ᴗ⏕⏘䜢䛭䜜䛮䜜8.67䠂䛚䜘䜃2.94䠂ῶᑡ䛥䛫䚸ᯝ≀స≀䛻ᙳ㡪䜢୚䛘䛺䛛䛳䛯䛣䛸䛜♧䛥䜜䛯䚹

䛆Abstract䛇 El Niño could potentially affect the food security such as reducing agricultural productivity in Indonesia

and causes drought in Bali as a results of declining rainfall. The 2015 El Niño is likely to be one of thestrongest El Niño events since 1997 (Blunden & Arndt, 2016); Moreover, the 2013 and 2014 is non-El
Niño event. To determine the severity of agriculture drought in Bali, Vegetation Health Index (VHI)
employed based on remote sensing data. As a results El Niño events in 2015 has decreased theagriculture production for rice and vegetable crops around 8.67% and 2.94% respectively, and no effect tofruit crops

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䜲䞁䝗䝛䝅䜰䛻䛚䛡䜛䜶䝹䝙䞊䝙䝵⌧㇟䛿䚸Ṕྐ䛻㎰ᴗ⏕⏘䛻኱䛝䛺ᙳ㡪䜢୚䛘䛶䛝䛶䛔䜛䠎䠌䠍䠑ᖺ䜶䝹䝙䞊䝙䝵⌧㇟䛿䚸䠍䠕䠕䠓ᖺ௨᮶䛾኱䛝䛺䞉䜶䝹䝙䞊䝙䝵⌧㇟䛷䛒䜚㎰ᴗ⏕⏘䛻኱䛝䛺ᙳ㡪䜢୚䛘䛶䛔䜛䛣䛸䛜ᮏ◊✲䛾⫼ᬒ䛸䛧䛶䛒䜛䚹ᮏ◊✲䛾┠ⓗ䛿䚸䠎䠌䠍䠑ᖺ䛾䜶䝹䝙䞊䝙䝵⌧㇟᫬䛾䜲䞁䝗䝛䝅䜰䚸䝞䝸ᓥ䛾㎰ᴗ⏕⏘㔞䜢ィ⟬䛩䜛䛣䛸䛷䛒䜛䚹䛣䛾䛯䜑䚸䝸䝰䞊䝖䝉䞁䝅䞁䜾䝕䞊䝍䛻ᇶ䛵䛟᳜⏕೺ᗣᣦᩘ䠄VHI䠅 䛾᪉ἲ䜢᥇⏝䛧䚸 5ᖺ㛫䠄2011䡚2015) 䛻䜟䛯䜚ィ⟬䜢ᐇ᪋䛧䛯䚹

䠄䠍䠅⾨ᫍ䝕䞊䝍䜢౑⏝䛧䛯᳜⏕೺ᗣᣦᩘ䠄VHI䠅ᡭἲ䜢㛤Ⓨ䛧䜎䛧䛯䠄ᅗ䠍䠅䚹䛣䜜䛻䜘䜚䚸㎰స≀䛾೺ᗣᣦᩘ䛾ィ⟬䛜ྍ⬟䛸䛺䜚䜎䛩䚹䠄䠎䠅 2015ᖺ䛾䜶䝹䝙䞊䝙䝵⌧㇟䛿䚸⡿䛚䜘䜃㔝⳯స≀䛾㎰ᴗ⏕⏘䜢䛭䜜
䛮䜜䚸8.67䠂䛚䜘䜃2.94䠂ῶᑡ䛥䛫䚸ᯝ≀స≀䛻ᙳ㡪䜢୚䛘䛺䛛䛳䛯䛣䛸䛜䜢᫂䜙䛛䛻䛧䜎䛧䛯䚹䠄ᅗ䠎䠅
䠄䠏䠅⾨ᫍ䝕䞊䝍䜢౑⏝䛧䛯᳜⏕೺ᗣᣦᩘ䠄VHI䠅ᡭἲ䜢☜❧䛧䜎䛧䛯䚹䛣䜜䛻䜘䜚䚸⾨ᫍ䝕䞊䝍䛛䜙㎰స≀䛾೺ᗣᣦᩘ䛾ィ⟬䛜ྍ⬟䛸䛺䜚䜎䛩䚹

ᅗ䠍㻌

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VHI䛾ィ⟬ᡭἲ✐≀⏕⏘ຊ䛾ẚ㍑䠄2011ᖺ䛛䜙2015ᖺ䠅㛤Ⓨ䛧䛯ᡭἲ䛿 䜲䞁䝗䝛䝅䜰䚸䝞䝸ᓥ䛾㎰ᴗ⏕⏘㔞䛾୍䛴䛾ᣦ㔪䛸䛧䛶౑⏝䛥䜜䚸㎰ᴗᒁ䚸ᆅ᪉㛤Ⓨᒁ䛻ᥦ౪䛥䜜䛶䛔䜎䛩䚹― 62 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-37䛇䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅 UAV⏬ീ䜢⏝䛔䛯Ỉ✄䛾⏕⫱⟶⌮䛻㛵䛩䜛◊✲㻌䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅 Study on rice growth management using UAV imagery䠄◊✲௦⾲⪅ྡ䠅 ∾㻌 㞞ᗣ㻌 䠄ᮾ໭ᕤᴗ኱Ꮫ䠅
Masayasu MAKI 㻌 䠄Tohoku Institute of Technology䠅䛆せ᪨䛇㏆ᖺ䠈㣗ᩱᏳ඲ಖ㞀䜈䛾㛵ᚰ䛜㧗䜎䜚䠈㣗ᩱ䛾Ᏻᐃ౪⤥䝅䝇䝔䝮䛾☜❧䛜ồ䜑䜙䜜䛶䛔䜛䚹స≀䛾⏕⫱䜢⟶⌮䛩䜛䛣䛸䛿䠈Ᏻᐃ౪⤥䝅䝇䝔䝮䛾☜❧䛻䛚䛔䛶᭱䜒㔜せ䛺䛣䛸䛾୍䛴䛷䛒䜚䠈䛭䛾䛯䜑䠈ᑐ㇟స≀䛾⏕⫱≧ែ䛾✵㛫ศᕸ䜢ṇ☜䛻┘ど䞉ண 䛩䜛䛣䛸䛜㔜せ䛸䛺䜛䚹㏆ᖺ䠈UAV䛻䜘䜛స≀䛾⏕⫱⟶⌮䛜⾜䜟䜜䜛䜘䛖䛻䛺䛳䛶䛝䛯䚹䛧䛛䛧䠈⌧ẁ㝵䛷䛿UAV䜢⏝䛔䛯స≀䛾⏕⫱⟶⌮ᡭἲ䛿☜❧䛥䜜䛶䛔䛺䛔䚹ᮏ◊✲䛿䠈Ỉ✄䜢ᑐ㇟䛻䛧
䛶䠈UAV⏬ീ䛸స≀䝰䝕䝹䜢⏝䛔䛯⏕⫱ண 䛾ྍ⬟ᛶ䛻䛴䛔䛶᳨ウ䛧䛯䚹䛆Abstract䛇 Recently, food security becomes a major concern in the world. And development of stable food supply
system has been required. Management of crop growth is one of the most important matters for stable
food supply system. Monitoring of accurate spatial distribution of growth status of target crop at the field
scale is required for the system. In recent years, unmanned aerial vehicle (UAV) has been used for
management of crop growth. However, the method for management of crop growth using UAV has notbeen yet established. In this study, the possibility of growth prediction using the UAV imagery of rice
paddy field and growth simulation model was evaluated.

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㏆ᖺ䠈⏕⏘⪅䛾㧗㱋໬䜔ᚋ⥅⪅୙㊊䜢⫼ᬒ䛻䠈ຠ⋡ⓗ䛺㎰ᆅ⟶⌮䛾䛯䜑䛾㎰஦⤌ྜἲே໬䜔䛭䜜䛻క䛖㎰ᆅ䛾኱つᶍ໬䛜㐍䜣䛷䛔䜛䚹኱つᶍ㎰ᆅ䛻䛚䛡䜛స≀䛾⏕⫱≧ែ䛾✵㛫ศᕸ䜢ᢕᥱ䛩䜛䛯䜑䠈䝸䝰䞊䝖䝉䞁䝅䞁䜾ᢏ⾡䛾฼⏝䛜ᮇᚅ䛥䜜䛶䛔䜛䚹㏆ᖺ䠈↓ே㣕⾜ᶵ䠄Unmanned Aerial Vehicle: UAV䠅䛚䜘䜃UAV䛻ᦚ㍕ྍ⬟䛺᳜≀䛾⏕⫱┘ど䛻㐺䛧䛯㏆㉥እ䜹䝯䝷䛜Ⓩሙ䛧䠈㎰ᆅ⟶⌮䛾䛯䜑䛻UAV䝸䝰䞊䝖䝉䞁䝅䞁䜾䛾฼⏝⎔ቃ䛜ᩚ䛳䛶䛝䛯䚹䛣䛾䜘䛖䛺⫼ᬒ䛛䜙䠈ᮏ◊✲䛷䛿UAV⏬ീ䛾㧗ᗘ䛺฼⏝᪉ἲ䛻䛴䛔䛶᳨ウ䛩䜛䛣䛸䜢┠ⓗ䛸䛧䠈UAV⏬ീ䛸స≀䝰䝕䝹䛸䛾⤖ྜ䛻䜘䜛Ỉ✄䛾⏕⫱ண 䛾ྍ⬟ᛶ䛻䛴䛔䛶ホ౯䛧䛯䚹䠄1䠅 ᅗ1䛿䠈ᆅୖィ 䛧䛯LAI䝕䞊䝍䜢⏝䛔䛯ᅡሙ䝟䝷䝯䞊䝍䛾ㄪᩚ䛸ㄪᩚᚋ䛾LAI᥎ᐃ⤖ᯝ䛾౛䛷䛒䜛䚹ᅗ୰䛾᭱ึ䛾2䛴䛾୸༳䛾ᐇ ್䜢⏝䛔䛶ᅡሙ䝟䝷䝯䞊䝍䜢ㄪᩚ䛧䠈ᅡሙ䝟䝷䝯䞊䝍ㄪᩚᚋ䛿䠈స≀䝰䝕䝹䛾
䜏䛷LAI䜢᥎ᐃ䛧䛯䚹䛣䛾ᆅⅬ䛻䛚䛡䜛ᅡሙ䝟䝷䝯䞊䝍ㄪᩚᚋ䛾LAI䛾᥎ᐃ⢭ᗘ䛿䠈3䛴┠䛾୸༳䛾ᐇ ್䜢⏝䛔䛶᳨ド䛧䛯䚹䛣䛾ᅗ䛛䜙䠈⏕⫱ึᮇ䛛䜙୰ᮇ䛻䛛䛡䛶ィ 䛧䛯2ᅇ⛬ᗘ䛾LAI䜢⏝䛔䛶ᅡሙ䝟䝷䝯䞊䝍䜢ㄪᩚ䛩䜛䛣䛸䛷䠈ᑐ㇟䛸䛧䛯ሙᡤ䛻㐺䛧䛯ᅡሙ䝟䝷䝯䞊䝍䛾タᐃ䛜ྍ⬟䛸䛺䜛䛸⪃䛘䜙䜜䜛䚹
䠄2䠅ᅗ2(a)䛿䠈ᅗ1䛾᭱ึ䛾2䛴䛾୸༳䛸ྠ䛨᪥䛻✵᧜䛧䛯UAV⏬ീ䛛䜙᥎ᐃ䛧䛯LAI⏬ീ䜢⏝䛔䛶ྛᆅⅬ䛾ᅡሙ䝟䝷䝯䞊䝍䜢ㄪᩚ䛧䠈ᅗ1䛾3䛴┠䛾୸༳䛾᪥䛾LAI䜢స≀䝰䝕䝹䛾䜏䛷᥎ᐃ䛧䛯⤖ᯝ䜢⏬ീ䛻䛧䛯䜒䛾䛷䛒䜛䚹ᅗ2(b)䛿䠈ᅗ1䛾3䛴┠䛾୸༳䛾᪥䛻✵᧜䛧䛯UAV⏬ീ䛛(b)䜙ᐇ ್䛸EVI್䛾ᅇᖐᘧ䛛䜙᥎ᐃ䛧䛯LAI⏬ീ䛷䛒䜛䚹䛣䛾ᅗ䛛 (a)䜙⤯ᑐ್䛿␗䛺䜛䛜䠈┦ᑐⓗ䛺LAI䛾ศᕸ䛿ண ྍ⬟䛷䛒䛳䛯䛣䛸
䛜ศ䛛䜛䚹

ᅗ1

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

ᆅୖィ LAI䝕䞊䝍䜢⏝䛔䛯⏕⫱䝅䝭䝳䝺䞊䝅䝵䞁䝰䝕䝹ෆ䛾ᅡሙ䝟䝷䝯䞊䝍䛾ㄪᩚ䛸ㄪᩚᚋ䛾LAI᥎ᐃ⤖ᯝᅗ2 ᅡሙ䝟䝷䝯䞊䝍ㄪᩚᚋ䛾స≀䝰䝕䝹䜢⏝䛔䛶ண 䛧䛯LAI⏬ീ䠄a䠅䛸UAV⏬ീ䛛䜙᥎ᐃ䛧䛯LAI⏬ീ䠄b䠅䛾ẚ㍑◊✲䛾ᡂᯝ䛻グ㍕䛧䛯ෆᐜ䛻䛴䛔䛶䚸௚䛾◊✲䜈䛾ά⏝≧ἣ䛒䜛䛔䛿ᬑཬ䞉ᐇ⏝໬䛾≧ἣ䜢グ㍕䛧䛶䛟䛰䛥䛔䚹䞉㛤Ⓨ୰䛾ᡭἲ䛾ᐇ฼⏝䛻ྍ⬟ᛶ䛻䛴䛔䛶䚸௝ྎᕷෆ䛾UAV✵᧜఍♫䛸ィ ᡭ㡰䜔ゎᯒᡭ㡰䛻䛴䛔䛶᳨ウ୰䛷䛒䜛䚹

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CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-36䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅ᑠᆺUAV䠄↓ே⯟✵ᶵ䠅䛸SfM-MVS䠄Structure from Motion and Multi View Stereo䠅㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 ෗┿ 㔞䜢⏝䛔䛯ᩳ㠃ᔂቯᆅ䛾ᆅᙧኚ໬䛸᳜⏕ኚ໬ᢳฟ䛻㛵䛩䜛◊✲㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Detection of topographic changes and re-vegetation in landslides using UAV(Unmanned Aerial Vehicle) and SfM-MVS (Structure from Motion and Multi View Stereo) photogrammetry䠄◊✲௦⾲⪅ྡ䠅 㰻⸨㻌 ோ㻌 䠄㛵ᮾᏛ㝔኱Ꮫ䞉⤒῭Ꮫ㒊䠅
Hitoshi Saito㻌 (Kanto Gakuin University 䞉College of Economics)䛆せ᪨䛇㻌 ᮏ◊✲䛷䛿䠈ᑠᆺUAV䛸SfM-MVS෗┿ 㔞䜢⾲ᒙᔂቯᆅ䛾ᆅᙧゎᯒ䛻ᛂ⏝䛧䠈ヲ⣽䛺⾲ᒙᔂቯᆅ䛾✵㛫ศᕸ䛸ᅵ◁⏕⏘㔞䠈䛚䜘䜃᳜⏕ኚ໬䜢᫂䜙䛛䛻䛩䜛䛣䛸䛷䛒䜛䠊ᑐ㇟ᆅᇦ䛿䠈2016ᖺ⇃ᮏᆅ㟈䛸䠈2012 ᖺ7 ᭶஑ᕞ໭㒊㇦㞵䛻క䛔ከᩘ䛾⾲ᒙᔂቯ䛜Ⓨ⏕䛧䛯㜿⸽ᒣ䞉୰ኸⅆཱྀୣ䛾௝㓉ᓙᆅᇦ䛷䛒䜛䠊⤖ᯝ䠈✵㛫ゎീᗘ
0.04 m 䛾䜸䝹䝋⏬ീ䠈䛚䜘䜃0.16 m 䛾Digital Surface Models 䛜ᚓ䜙䜜䛯䠊2016ᖺ⇃ᮏᆅ㟈䠈䛚䜘䜃2012ᖺ
7᭶஑ᕞ໭㒊㇦㞵䛻క䛖ᅵ◁⏕⏘㔞䛿䠈䛭䜜䛮䜜 105 m3/km2 䜸䞊䝎䞊䛸䠈 104 m3/km2 䜸䞊䝎䞊䛷䛒䛳䛯䠊䜎
䛯2012ᖺ7᭶஑ᕞ໭㒊㇦㞵䛻క䛖ᩳ㠃ᔂቯᆅ䛷䛿᳜⏕䛜ᅇ᚟䛜㐍䜣䛷䛔䜛䛣䛸䛜♧䛥䜜䛯䠊
䛆Abstract䛇 㻌 This study detected spatial distributions of shallow landslides and their sediment yields triggered by the2016 Kumamoto Earthquake and the heavy rainfall in July 2012 using small UAVs and SfM-MVS
photogrammetry at the Sensuikyo area at Aso Volcano, Japan. We obtained ortho-rectified photographswith spatial resolutions of 0.04, and digital surface models (DSMs) with spatial resolutions of 0.16 m.
Sediment yields triggered by the 2016 Kumamoto Earthquake and the heavy rainfall in July 2012were ~105 m3/km2 and ~104 m3/km2 , respectively. Additionally, recovery of vegetation was detected
inside of landslides triggered by the heavy rainfall in July 2012.

䠍㻌 㜿⸽ᒣ࿘㎶䛾ⲡᆅ䛿䠈䛣䜜䜎䛷㢖⦾䛻㇦㞵䛻䜘䜛㞟ᅋⓗᩳ㠃ᔂቯ䛜Ⓨ⏕䛧䛶䛚䜚䠄౛䛘䜀䠈2012ᖺ7᭶䠈
2001ᖺ6᭶䠈1990ᖺ7᭶䛺䛹䠅䠈ᆅᙧኚ໬䛾㏿䛔ᆅᇦ䛷䛒䜛䠊䜎䛯ᖹᡂ28ᖺ⇃ᮏᆅ㟈䛷䛿䠈ከᩘ䛾ᩳ㠃ᔂቯ䛜Ⓨ⏕䛧䛯䠊ᩳ㠃ᔂቯᚋ䛾ᆅᙧⓗ≉ᚩ䜔䛭䛾ኚ໬䠈᳜⏕ᅇ᚟䜢᫂䜙䛛䛻䛩䜛䛣䛸䛿䠈௒ᚋ䛾ຠ⋡ⓗ䛺ᅵ◁⅏ᐖᑐ⟇䜔䠈㜿⸽䜢≉ᚩ䛵䛡䜛ⲡᆅᬒほ䛾ಖ඲䛾ほⅬ䛛䜙㔜せ䛷䛒䜛䠊䛧䛛䛧䛺䛜䜙䠈୍⯡ⓗ䛺⾨ᫍ⏬ീ䜔✵୰෗┿䛷䛿䠈䛭䛾᧜ᙳ㢖ᗘ䜔ศゎ⬟䛚䜘䜃䝁䝇䝖䛾㠃䛷䠈ᩳ㠃ᔂቯᆅ䜔䛭䛾࿘㎶䛾᫬㛫䞉✵㛫ⓗ䛺ኚ໬䜢ヲ⣽䛻ᤊ䛘䜛䛣䛸䛿ᐜ᫆䛷䛺䛔䠊䛭䛣䛷2014ᖺᗘ䜘䜚UAV䛸SfM-MVS䛻䜘䜛෗┿ 㔞䛻䜘䜚䠈ᩳ㠃ᔂቯᆅ䛾ప✵✵᧜⏬ീ䛾ྲྀᚓ䛸䛭䛾ゎᯒ䜢䛚䛣䛺䛳䛶䛝䛯䠊ᮏ◊✲䛷䛿䠈䛣䜜䜎䛷䛾◊✲䜢Ⓨᒎ䛥䛫䠈2012ᖺ7᭶஑ᕞ໭㒊㇦㞵䛸2016ᖺ⇃ᮏᆅ㟈䛻క䛖ᩳ㠃ᔂቯᆅ䛾ศᕸ䛸ᅵ◁⏕⏘㔞䠈䛚䜘䜃᳜⏕ኚ໬䜢᫂䜙䛛䛻䛧䛯䠊䠎䠄䠍䠅 ᮏ◊✲䛷䛿䠈 UAV䛸SfM-MVS䛻䜘䜛෗┿ 㔞䜢⏝䛔䛶䠈㧗⢭⣽䛺䜸䝹䝋⏬ീ䛸DSM䜢ྲྀᚓ䛩䜛ᡭἲ䜢☜❧䛧䛯䠊䛣䜜䛻䜘䜚ᩳ㠃ᔂቯ䠄ᅵ◁⅏ᐖ䠅Ⓨ⏕┤ᚋ䛻䠈㎿㏿䛻✵㛫ゎീᗘ
0.10 m ⛬ᗘ䛾䜸䝹䝋⏬ീ䛸DSM䜢ྲྀᚓ䛩䜛䛣䛸䛜ྍ⬟䛸䛺䜛䠊䜎䛯㧗㢖ᗘ䛻䝕䞊䝍䜢ྲྀᚓ䛩䜛䛣䛸䛷䠈ᩳ㠃ᔂቯ䛾ᅵ㔞䜔ᅵ◁⏕⏘㔞䜢㧗⢭ᗘ䛻ィ 䛩䜛䛣䛸䜔䠈᳜⏕䛾ኚ໬䛾᳨ฟ䛜ྍ⬟䛸䛺䜛䠊

⫼ᬒ
┠ⓗ
᪉ἲ

◊✲䛾
ᡂᯝ

䠄䠎䠅 㜿⸽ᒣ䛾௝㓉ᓙ䜢ᑐ㇟䛻䠈 2016ᖺ⇃ᮏᆅ㟈䛸䠈2012ᖺ7 ᭶஑ᕞ໭㒊㇦㞵䛻క䛖ᩳ㠃ᔂቯᆅ䛾✵㛫ศᕸ䛸䛭䛾ᅵ◁⏕⏘㔞䠈䛚䜘䜃᳜⏕䛾ኚ໬䛻䛴䛔䛶ゎᯒ䜢䛚䛣䛺䛳䛯䠊䛣䜜䜙䛾䜲䝧䞁䝖䛾๓ᚋ䛾㧗⢭⣽䛺䜸䝹䝋⏬ീ䛸DSM䜢ẚ㍑䛩
䜛䛣䛸䛷䠈 2016ᖺ⇃ᮏᆅ㟈䠈䛚䜘䜃2012ᖺ7᭶஑ᕞ໭㒊㇦532
㞵䛻క䛖ᅵ◁⏕⏘㔞䛿䠈䛭䜜䛮䜜 10 m /km 䜸䞊䝎䞊䛸䠈
4
3
2
10 m /km 䜸䞊䝎䞊䛷䛒䛳䛯䠊䜎䛯2012ᖺ7᭶஑ᕞ໭㒊㇦㞵䛻క䛖ᩳ㠃ᔂቯᆅ䛷䛿᳜⏕䛜ᅇ᚟䛜㐍䜣䛷䛔䜛䛣䛸䛜♧
䛥䜜䛯䠊

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

ᅗ1

✵㛫ゎീᗘ 0.04 m 䛾䜸䝹䝋⏬ീ䛸䠈
2012ᖺ7᭶஑ᕞ໭㒊㇦㞵䛻క䛖ᩳ㠃ᔂቯᆅ䛾ศᕸ䠄ⓑᯟ䠅䠄㰻⸨䜋䛛䠈2016䠅㰻⸨㻌 ோ䞉ෆᒣᗉ୍㑻䞉ᑠⰼ࿴ᏹஅ䞉᪩ᕝ⿱ᘤ䞉J.T. 䝇䝸 䝇䝬䞁䝔䜱䝶 2017䠊㜿⸽ᒣ䞉௝㓉ᓙ䛻䛚䛡䜛ᩳ㠃ᔂ㻌ቯ䛾㧗⢭⣽ᆅᙧゎᯒ䠊༓ⴥ኱Ꮫ⎔ቃ䝸䝰䞊䝖䝉䞁䝅䞁䜾◊✲䝉䞁䝍䞊➨19ᅇ ⎔ቃ䝸䝰䞊䝖䝉䞁䝅䞁䜾䝅䞁䝫
䝆䜴䝮䠈No. 15䠊㰻⸨㻌 ோ䞉ෆᒣᗉ୍㑻䞉ᑠⰼ࿴ᏹஅ䞉᪩ᕝ⿱ᘤ 2016䠊ᖹᡂ 24ᖺ䠄2012ᖺ䠅 7᭶஑ᕞ໭㒊㇦㞵䛻క䛖㜿⸽ⅆᒣᆅᇦ䛷䛾ᅵ◁⏕⏘㔞䛾᥎ᐃ -UAV䛸SfMከどⅬ䝇䝔䝺䜸෗┿ 㔞䜢⏝䛔䛯㧗⢭⣽ᆅᙧ䝕䞊䝍䛾ά⏝-䠊ᆅ⌮Ꮫホㄽ 89䠈347-359䠊

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CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-44䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅䝸䝰䞊䝖䝉䞁䝅䞁䜾䝕䞊䝍䜢ά⏝䛧䛯䝭䝒䝞䝏䛾⏕ᜥ䞉⏕⫱✵㛫䛾ศᯒ㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Analysis of honeybee’s habitat using remote sensing data•ᒸ⏣㻌 ಙ⾜ (䜸䝹䝖㒔ᕷ⎔ቃ◊✲ᡤ䞉௦⾲ྲྀ⥾ᙺ)
OKADA, Nobuyuki (alt Planning office Co., Ltd. 䞉㻌 representative director)
䛆せ᪨䛇㻌 ≉䛻㒔ᕷ㒊䛻䛚䛔䛶䛿䚸⏕ά⎔ቃ࿘㎶䛻Ꮡᅾ䛧䛶䛔䜛⮬↛⎔ቃ䜢ᐇឤ䛧䛻䛟䛔≧ἣ䛻䛒䜚䜎䛩䚹㒔ᕷ䛻䛚䛔䛶䜒⮬↛⎔ቃ䛾Ꮡᅾ䛿㔜せ䛷䛒䜚䚸㒔ᕷ䛸⎔ቃ䛸䛾㛵ಀᛶ䜢ఫẸ䛻䜟䛛䜚䜔䛩䛟ఏ䛘䜛᪉ἲ䛜ồ䜑䜙䜜䛶䛔䜎䛩䚹㻌 ⚾䛯䛱䛿ᆅᇦ䛾᪉䚻䛜㌟㏆䛺⎔ቃ䜢ᐇឤ䛩䜛ዎᶵ䛸䛺䜛䛣䛸䜢┠ᣦ䛧䛶䝭䝒䝞䝏䜢㣫⫱䛧䛶䛔䜎䛩䚹㻌 ᮏ◊✲䛿䚸䝭䝒䝞䝏䛾ᕢ⟽࿘㎶䛾᳜⏕≧ἣ䛾ᢕᥱ䜢┠ᣦ䛧䚸䝗䝻䞊䞁䜔䝡䝹䛾ᒇୖ䜢ά⏝䛧䛶ᕷ⾤ᆅ䛻䛚䛡䜛᳜⏕᝟ሗ➼䛾ྲྀᚓᡭἲ䜢㛤Ⓨ䛩䜛䛣䛸䜢┠ⓗ䛸䛧䛶䛔䜎䛩䚹䛆Abstract䛇

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

We have been trying to investigate the vegetation around areas of the hive using satellite remotesensing data.
The purpose of this study is to develop the observation method of vegetation information in a city using
UAV or rooftop of Skyscraper.

㻌 ᮏᖺᗘ䛿䚸䜘䜚ヲ⣽䛺⏕ᜥ⏕⫱⎔ቃ䛾ᢕᥱ䜢┠ᣦ䛧䚸䝗䝻䞊䞁䜢ά⏝䛧䛶⾨ᫍ䝸䝰䞊䝖䝉䞁䝅䞁䜾䝕䞊䝍䜢⿵᏶䛩䜛ᕢ⟽࿘㎶䛾᳜⏕᝟ሗ➼䛾ྲྀᚓ䜢ヨ䜏䜎䛧䛯䚹䕔᪉ἲ䠍䠖㣫⫱ሙᡤ࿘㎶䛻䛚䛡䜛NDVI䛾ྲྀᚓ㻌 UAV䛻ᦚ㍕䛩䜛NIR䜹䝯䝷䜢⏝䛔䛶䐟㣫⫱ሙᡤ࿘㎶䛾᳜≀άᛶᗘ䛾ኚ໬䛾ほ 䚸䐠UAV䛻ᦚ㍕䛩䜛᧜ᙳჾᮦ䛾㐠⏝᪉ἲ䛾⵳✚䜢┠ⓗ䛸䛧䛯ほ 䜢ᐇ᪋䛧䜎䛧䛯䚹䕔᪉ἲ䠎䠖NIR䜹䝯䝷䜢ᦚ㍕䛧䛯UAV䛾䝔䝇䝖㻌 ᮏᖺᗘ䛿䚸ᶵᮦ䛾㐠⏝䝔䝇䝖䜢ᐇ᪋䛧䚸Ᏻ඲ᛶ䞉Ᏻᐃᛶ䛾☜ㄆ䛩䜛䛸䛸䜒䛻䚸ᦚ㍕䛩䜛NIR䜹䝯䝷䜢⏝䛔䛯᧜ᙳ䝔䝇䝖䜢ᐇ᪋䛧䜎䛧䛯䚹㻌䠄䠍䠅㣫⫱ሙᡤ࿘㎶䛻䛚䛡䜛NDVI䛾ྲྀᚓ㻌 10᭶ึ᪪䛛䜙12᭶ᮎ䛻䛛䛡䛶භᮏᮌ䝠䝹䝈ᒇୖ䛛䜙䚸UAV䛻ᦚ㍕䛩䜛ᑠᆺNIR䜹䝯䝷䛻䜘䜛᧜ᙳ䜢ᐇ᪋䛧䛯䚹ほ ሙᡤ䛛䜙༡ᮾ᪉ྥ䛾Ⱚබᅬ䜢ྵ䜐ᕷ⾤ᆅ䜢ᑐ㇟䛸䛧䚸᪥ᙳ䜢⪃៖䛧䛶༗ᚋ䛾᫬㛫ᖏ䛻᧜ᙳ䜢ᐇ᪋䛧䜎䛧䛯䚹㻌 NIR䜹䝯䝷䜢⏝䛔䛯㧗ᒙ䝡䝹䛛䜙䛾ほ 䛻䜘䛳䛶䚸䝃䜽䝷䜔䜲䝏䝵䜴䚸䜿䝲䜻䛺䛹䛾ⴠⴥᶞ䛜ከ䛟᳜᱂䛥䜜䚸୺せ䛺⻤※䛸䛺䛳䛶䛔䜛䛸⪃䛘䜙䜜䜛Ⱚබᅬ䚸䜲䝍䝸䜰኱౑㤋࿘㎶䛾⥳ᆅ䛻䛚䛡䜛NDVI䛜⛅Ꮨ䛛䜙෤Ꮨ䛻䛛䛡䛶ῶ⾶䛧䛶䛔䛟Ꮨ⠇ኚ໬䜢ᤊ䛘䜛䛣䛸䛜䛷䛝䜎䛧䛯䚹

ᅗ1 㧗ᒙ䝡䝹䛛䜙䛾ほ 䛻䜘䜛NDVI䠄䠎䠅NIR䜹䝯䝷䜢ᦚ㍕䛧䛯UAV䛾䝔䝇䝖㻌 UAV䛻ᦚ㍕䛧䛯ᑠᆺNIR䜹䝯䝷䛷䝗䝻䞊䞁䝣䜱䞊䝹䝗ෆ䜢᧜ᙳ䛧䜎䛧䛯䚹㻌 ᧜ᙳ䛧䛯」ᩘ䛾⏬ീ䜢䜒䛸䛻Photo Scan䛷䠏D䝯䝑䝅䝳䝰䝕䝹䜢⏕ᡂ䛧䚸᧜ᙳ䝕䞊䝍䜢䝬䝑䝢䞁䜾䛧䜎䛧䛯䚹㻌 ྜᡂ䛧䛯⏬ീ䜢ゎᯒ䛧䚸᧜ᙳᑐ㇟ᆅ䛾NDVI䝬䝑䝥䜢సᡂ䛩䜛䛣䛸䛜䛷䛝䜎䛧䛯䚹
ᅗ2 䝗䝻䞊䞁䜢⏝䛔䛯NDVI䝬䝑䝥సᡂ

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䕔ᆅᇦ䛾⎔ቃᩍ⫱䛾ሙ䛻䛚䛡䜛ά⏝㻌 㻌㻌 ᮏ◊✲䛾ᡂᯝ䛿䚸 ༊Ⱚᆅ༊䛻䛚䛡䜛㣴⻏䝥䝻䝆䜵䜽䝖䜢䛿䛨䜑䚸㒔ᕷ䛻䛚䛡䜛㣴⻏䝥䝻䝆䜵䜽䝖䛻䛚䛔䛶䚸ཧຍ䛧䛯ᕷẸ䛾ⓙ䛥䜣䛻䝥䝻䝆䜵䜽䝖䛷᥇䜜䛯䝝䝏䝭䝒䛾⏤᮶䜢⪃䛘䛶㡬䛟㐣⛬䛷ά⏝䛧䛶䛚䜚䚸㒔ᕷ䛻䛚䛡䜛⮬↛⎔ቃ䛾Ꮡᅾ䜢ᐇឤ䛩䜛୍ຓ䛻䛺䛳䛶䛔䜎䛩䚹― 65 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-02䛇㻌 ྜᡂ㛤ཱྀ䝺䞊䝎ᦚ㍕䝬䜲䜽䝻⾨ᫍ⏝䠢䠬䠣䠝䛾㛤Ⓨ
㻌 Development of FPGA for Microsatellite onboard Synthetic Aperture Radar䠄◊✲௦⾲⪅ྡ䠅㞴Ἴ ୍㍤ (༓ⴥ኱Ꮫ)Kazuteru Namba (Chiba university)䛆せ᪨䛇෇೫Ἴྜᡂ㛤ཱྀ䝺䞊䝎 (CP-SAR) ᦚ㍕↓ே⯟✵ᶵ䛻䛚䛔䛶⾜䜟䜜䜛 Synthetic Aperture Rader (SAR) ಙྕฎ⌮䛻䛚䛔䛶䛿኱㔞䛾䝕䞊䝍䛻ᑐ䛧䠈㧗㏿䛻 FFT➼䛾₇⟬䜢⾜䛖䛣䛸䛜ồ䜑䜙䜜䛶䛔䜛䠊䛭䛾䛯䜑 SAR ಙྕฎ⌮䝅䝇䝔䝮ᵓᡂ⎔ቃ䛸䛧䛶䠈ᚑ᮶䛾 Digital Signal Processer (DSP) 䛛䜙୪ิᗘ䛾㧗䛔 Field Programmable
Gate Array (FPGA) 䜈䛾⛣⾜䛜ᙉ䛟ồ䜑䜙䜜䛶䛔䜛䠊᫖ᖺᗘ䜎䛷䛾◊✲䛷䛿䠈タィ䛧䛯䝅䝇䝔䝮䜢FPGAୖ䛻ᵓᡂ䛧䛶䛔䛯䠊ᮏᖺᗘ䛿㍍㔞໬䠈┬㟁ຊ໬䜢┠ⓗ䛸䛧䛯䝅䝇䝔䝮䛾ᨵⰋ䜢⾜䛳䛯䠊
Signal processing for unmanned aerial vehicle (UAV) with circularly-polarized synthetic aperture radar䛆Abstract䛇 (CP-SAR) uses high-speed FFT computation for large amounts of data. So, it is strongly required thatsignal processing system for CP-SAR is constructed on field programmable gate arrays (FPGAs)
providing high-speed parallel processing and not traditional digital signal processers (DSPs). In the past
years, we designed a SAR image processing system on an FPGA board. In this year we improved thedesigned system to save weight and power.

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⌧ᅾ䠈༓ⴥ኱Ꮫ⎔ቃ䝸䝰䞊䝖䝉䞁䝅䞁䜾◊✲䝉䞁䝍䞊䛷䛿䠈ᆅ⾲⎔ቃ䞉⾲ᒙ䛻䛚䛡䜛ᵝ䚻䛺᝟ሗ䜢⢭ᐦ䛛䛴㧗⢭ᗘ䛻ほ 䛷䛝䠈ୡ⏺ึ䛛䛴᪥ᮏ⊂⮬䛾ᢏ⾡䛻䜘䜛෇೫Ἴྜᡂ㛤ཱྀ䝺䞊䝎䠄CP-SAR䠅䝉䞁䝃ᦚ㍕䛾䝬䜲䜽䝻⾨ᫍ䜢㛤Ⓨ䛧䛶䛔䜛䠊ᮏ◊✲䛷䛿䠈䝬䜲䜽䝻⾨ᫍ䛾䝁䝬䞁䝗䞉䝕䞊䝍䝝䞁䝗䝸䞁䜾䛻䜒䛳䛸䜒㔜せ䛺㒊ศ䛷䛒䜛୰ኸไᚚ㒊䛾ᵓᡂ䛾䛯䜑䠈CP-SAR䛾㧗㏿ฎ⌮䛻᭱㐺䛺FPGA䛾㛤Ⓨ䜢⾜䛖䠊᫖ᖺᗘ䜎䛷䛾◊✲䛷䛿䠈タィ䛧䛯䝅䝇䝔䝮䜢ᐇ㝿䛻FPGAୖ䛻ᵓᡂ䛧䛶䛔䛯䠊ᮏᖺᗘ䛿㍍㔞໬䠈┬㟁ຊ໬䜢┠ⓗ䛸䛧䛯䝅䝇䝔䝮䛾ᨵⰋ䜢⾜䛳䛯䠊
䠄䠍䠅ᚑ᮶䛿⏬ീ䛾ฎ⌮䛚䜘䜃䛭䛾ಖᏑ䛾䛯䜑䠈2ᯛ䛾FPGA䝪䞊䝗䛸 PC䜢฼⏝䛧䛶䛔䛯(ᅗ1)䠊䛣䜜䜢1ᯛ䛾FPGA䛸1ᯛ䛾䝗䞊䝍䝪䞊䝗䛰䛡䛷ᵓᡂ䛧┤䛧䛯(ᅗ2)䠊

䠄䠎䠅䠄䠍䠅䜢ᐇ⌧䛩䜛䛯䜑䠈ᚑ᮶䝅䝇䝔䝮䛷䛿1ᯛ䛾FPGA䝪䞊䝗(SP605) 䛸 PC 䜢⏝䛔䛶⾜䛳䛶䛔䛯SSD䛾᧯స䜢䝗䞊䝍䝪䞊䝗(XM104) 䛰䛡䛷ᐇ⌧䛷䛝䜛䜘䛖䛻䛧䛯䠊ᅗ1 ᚑ᮶䛾䝅䝇䝔䝮䠄䠏䠅䠄䠍䠅䛻䜘䜚䠈㍍㔞໬䛚䜘䜃┬㟁ຊ໬䛻ᡂຌ䛧䛶䛔䜛䠊㔜㔞➼䛾ไ⣙䛜ཝ䛧䛔↓ே⯟✵ᶵୖ䛷䛾౑⏝䜢⪃䛘䜛䛸䠈䛣䛾ព⩏䛿኱䛝䛔䠊ᅗ2 ᮏᖺᗘసᡂ䛧䛯䝅䝇䝔䝮ᚑ᮶䜘䜚㒊ရ䛜ᑡ䛺䛟㍍㔞䛷䛒䜛䚹

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ᮏ◊✲ᡂᯝ≀䛿䠈༓ⴥ኱Ꮫ⎔ቃ䝸䝰䞊䝖䝉䞁䝅䞁䜾◊✲䝉䞁䝍䞊䛷㛤Ⓨ䛥䜜䛶䛔䜛෇೫Ἴྜᡂ㛤ཱྀ䝺䞊䝎
䠄CP-SAR䠅䝉䞁䝃ᦚ㍕↓ே⯟✵ᶵୖ䛷౑⏝䛥䜜䜛ணᐃ䛷䛒䜛䠊― 66 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CP16-03䛇㻌 ⾨ᫍ⏬ീฎ⌮䛾䛯䜑䛾ᨺᑕఏ㐩䝰䝕䝹䛾᳨ド㻌 Validation of Radiative Transfer Models for Satellite Image Processing䠄◊✲௦⾲⪅ྡ䠅 㣤಴㻌 ၿ࿴㻌 䠄ᘯ๓኱Ꮫ䞉⌮ᕤᏛ◊✲⛉䠅
Yoshikazu Iikura 㻌 䠄Hirosaki University 䞉Graduate School of Science and Technology䠅䛆せ᪨䛇⾨ᫍ⏬ീ䛛䜙᭷⏝䛺᝟ሗ䜢ྲྀ䜚ฟ䛩䛻䛿䚸኱Ẽ䜔ᆅᙧ䛾ᙳ㡪䜢⿵ṇ䠄኱Ẽ䞉㝜ᙳ⿵ṇ䠅䛩䜛ᚲせ䛜䛒䜛䚹⿵ṇ䛾䛯䜑䚸䛔䛟䛴䛛䛾ᨺᑕఏ㐩䝰䝕䝹䛜㛤Ⓨ䞉බ㛤䛥䜜䛶䛔䜛䛜䚸ฟຊ䛩䜛኱Ẽ䝟䝷䝯䞊䝍䛾ᐃ⩏➼䛻㐪䛔䛜䛒䜚䚸฼⏝䛻䛿ὀព䛜ᚲせ䛷䛒䛳䛯䚹ᮏ◊✲䛷䛿䚸௦⾲ⓗ䛺ᨺᑕఏ㐩䝰䝕䝹䛷䛒䜛6S䛸RSTAR䜢⏝䛔䛶⿵ṇ䛻ᚲせ䛺䝟䝷䝯䞊䝍䛾ィ⟬᪉ἲ䜢᳨ウ䛧䛯䚹஧䛴䛾䝰䝕䝹䛷ィ⟬䛧䛯኱Ẽ䝟䝷䝯䞊䝍䠄䝟䝇䝷䝕䜱䜰䞁䝇䜢㝖䛟䠅䛷ᩚྜᛶ䛾䛒䜛⤖ᯝ䜢ᚓ䜛䛣䛸䛜䛷䛝䛯䚹䜎䛯䚸RSTAR䛻䛚䛔䛶┦㛵k-ศᕸ䛾సᡂ䛻䝉䞁䝃䛾ᛂ⟅㛵ᩘ䜢⪃៖䛩䜛䛣䛸䛻䜘
䜚䚸䠒S䛻ẚ㍑䛧䛶䠐ಸ䜋䛹㧗㏿䛺ィ⟬䛜ྍ⬟䛸䛺䛳䛯䚹䛆Abstract䛇

Atmospheric and illumination effects should be corrected when extracting useful information from satellite
images. For this purpose, some radiative transfer codes could be utilized but cautions are needed
because of the difference in their definitions of the resulting atmospheric parameters. In this research, we
considered the utilization of RSTAR in comparison with 6S. Although most of the results were found to beconsistent, RSTAR was almost four time faster than 6S owing to the use of the correlative k-distribution
formulation that incorporates response functions of sensor bands.

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⾨ᫍ⏬ീ䛛䜙᭷⏝䛺᝟ሗ䜢ྲྀ䜚ฟ䛩䛻䛿䚸኱Ẽ䜔ᆅᙧ䛾ᙳ㡪䜢⿵ṇ䛩䜛ᚲせ䛜䛒䜛䚹䛣䜜䜎䛷䛻䚸䛔䛟䛴䛛䛾ᨺᑕఏ㐩䝰䝕䝹䛜㛤Ⓨ䞉බ㛤䛥䜜䛶䛔䜛䛜䚸ฟຊ䛩䜛኱Ẽ䝟䝷䝯䞊䝍䛾ᐃ⩏➼䛻㐪䛔䛜䛒䜚䚸฼⏝䛻䛿ὀព䛜ᚲせ䛷䛒䛳䛯䚹䜎䛯䚸㉳అ䛾䛒䜛ᆅᙧ䛷㔜せ䛸䛺䜛ኳ✵ග䛾␗᪉ᛶ䛺䛹䛾ྲྀ䜚ᢅ䛔䛻䛴䛔䛶䛿䚸ᐇ䝕䞊䝍䛻䜘䜛᳨ド䜢ྲྀ䜚ධ䜜䜛ᚲせ䛜䛒䜛䚹㻌 ᮏ◊✲䛷䛿䚸௦⾲ⓗ䛺ᨺᑕఏ㐩䝰䝕䝹䛾ฟຊ㛫䛾ᩚྜᛶ䜢䝏䜵䝑䜽䛧䚸㐪䛔䛜䛒䜜䜀ྛ䝟䝷䝯䞊䝍䛾ᐃ⩏䛚䜘䜃ィ⟬᪉ᘧ䛻㋃䜏㎸䜣䛷ゎ᫂䜢⾜䛖䚹䛥䜙䛻䚸༓ⴥ኱Ꮫ䛷⾜䜟䜜䛶䛔䜛኱Ẽ䝟䝷䝯䞊䝍䛾ほ ⤖ᯝ䛸䛾ᩚྜᛶ䛻䛴䛔䛶䜒᳨ウ䜢ຍ䛘䚸䝰䝕䝹䛾ᨵၿ䛜ᚲせ䛛䛹䛖䛛䛾᳨ウ䜢⾜䛖䚹᫖ᖺᗘ䛻㛤Ⓨ䛧䛯⾨ᫍ䝉䞁䝃ᑐᛂ∧䛾RSTAR䛻ᑐ䛧䛶௨ୗ䛾ᨵⰋ䜢⾜䛳䛯䚹䠄䠍䠅ኳ✵཯ᑕ⋡䚸⫼ᬒᨺᑕ㍤ᗘ䚸⎔ቃᨺᑕ↷ᗘ䛾ᑟฟ䛻」ᩘ䛾ᆅ⾲㠃཯ᑕ⋡䛷䛾ィ⟬䛜ᚲせ䛷䛒䛳䛯䛜䚸䛣䜜䜙䜢୍䛴䛾ᆅ⾲㠃཯ᑕ⋡䛷ィ⟬䛷䛝䜛䜘䛖䛻㝶᫬䝥䝻䜾䝷䝮䜢ᨵⰋ䛧䛯䠄ᅗ䠍䠅䚹
䠄䠎䠅RSTAR䛷䛿኱Ẽᡂศ䛻䜘䜛ග䛾྾཰ィ⟬䛻┦㛵kศᕸἲ䜢䜒䛱䛔䛶䛔䜛䚹௒ᅇ䚸⾨ᫍ䝉䞁䝃䛾ᛂ⟅㛵ᩘ䜢⪃៖䛧䛶k-ศᕸ䛾✚ศⅬ䛸㔜䜏䜢䝷䞁䝗䝃䝑䝖ETM+䛻ᑐ䛧䛶䝔䞊䝤䝹໬䛧䛯䚹䛣䛾⤖ᯝ䚸RSTAR䛾ィ⟬㏿ᗘ䛜䠒S䛾䠐ಸ䜋䛹㧗㏿䛻䛺䛳䛯䚹䛧䛛䛧䚸䝟䝇䝷䝕䜱䜰䞁䝇䛜䠒S䛸␗䛺䜛ィ⟬⤖ᯝ䛸䛺䛳䛯䠄ᅗ䠎䠅ཎᅉ䛜䜋䜌≉ᐃ䛷䛝䛯䛾䛷䚸ಟṇ∧䜢సᡂ୰䛷䛒䜛䚹
䠄䠏䠅⾨ᫍ䛾ほ ᪥䠄ධຊ䠅䛻ᛂ䛨䛯ኴ㝧ᨺᑕ㍤ᗘ䜢タᐃ䛷䛝䜛䜘䛖䛻䛧䛯䚹䠄䠐䠅ᆅ⾲㠃䛾㧗䛥䛚䜘䜃䜶䜰䝻䝌䝹䛾㖄┤ศᕸ䜢ᰂ㌾䛻タᐃ䛷䛝䜛䜘䛖䛻䛧䛯䚹
䠄䠑䠅RSTAR䛾ධຊ䝣䜯䜲䝹(data)䛾⾨ᫍ⏬ീ䛾᧜ᙳ᮲௳䛻ᛂ䛨䛯᭩䛝᥮䛘䜔ฟຊ䝣䜯䜲䝹䛛䜙ᚲせ䛺᝟ሗ䛾ᢳฟ䜢ᰂ㌾䛻⾜䛖䝥䝻䜾䝷䝮䜢Python䜢⏝䛔䛶సᡂ䛧䛯䚹

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䠏
ᡂᯝᒎ㛤䛾
≧ἣ

ኳ✵཯ᑕ⋡䛾䠒S䠄㯮䠅䛸䛾ẚ㍑

ᅗ䠎

ᨺᑕ㍤ᗘ䛾䠒S䠄㯮䠅䛸䛾ẚ㍑

⾨ᫍ⏬ീ䛛䜙ᆅ⾲㠃཯ᑕ⋡䛸䜶䜰䝻䝌䝹䛾ගᏛⓗཌ䛥䜢ྠ᫬䛻᥎ᐃ䛩䜛᪉ἲ䠄ྠ᫬᥎ᐃἲ䠅䜢㛤Ⓨ䛧䚸䝥䝻䜾䝷䝮䜢Githubୖ䛻බ㛤䛧䛯䚹䛺䛚䚸኱Ẽ䝟䝷䝯䞊䝍䛾ィ⟬䛻䛿䠒S䛻௦䛘䛶䚸ᮏ◊✲䛷㛤Ⓨ䛧䛶䛔䜛RSTAR䛾⾨ᫍ䝉䞁䝃ᑐᛂ∧䜢฼⏝䛩䜛ணᐃ䛷䛒䜛䚹― 67 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-06䛇㻌 ᥈ᰝᶵ䝸䝰䞊䝖䝉䞁䝅䞁䜾䝕䞊䝍䜢⏝䛔䛯ⅆᫍ኱Ẽ⎔ቃ䛾◊✲㻌 A study on the Martian atmospheric environment using remote sensing data obtainedby Mars orbiter missions䠄◊✲௦⾲⪅ྡ䠅 㔝ཱྀ㻌 ඞ⾜㻌 䠄ዉⰋዪᏊ኱Ꮫ䠅
Katsuyuki Noguchi 㻌 䠄Nara Women’s University䠅䛆せ᪨䛇ᮏ◊✲䛷䛿䚸⡿ᅜ䛾ⅆᫍ᥈ᰝᶵMars Reconnaissance Orbiter䠄MRO䠅ᦚ㍕䛾㉥እศගィMars Climate
Sounder 䠄MCS䠅䛻䜘䜛ほ 䛛䜙ᚓ䜙䜜䛯Ẽ 䚸Ỉị㞼䚸䝎䝇䝖䛾ྛ≀⌮㔞䛾⤫ィⓗ䛺ゎᯒ䜢⾜䛺䛖䛣䛸䛷䚸䛭䜜䜙䛾┦஫స⏝䜢᫂䜙䛛䛻䛩䜛䛸ඹ䛻ⅆᫍẼ㇟䞉Ẽೃ䛻୚䛘䜛ᙳ㡪䜢ホ౯䛩䜛䛣䛸䜢┠ⓗ䛸䛩䜛䚹๓ᖺᗘ䜎䛷䛻䚸༡༙⌫䛾≉ᚩⓗ䛺ᆅᙧ䛾୍䛴䛷䛒䜛䝦䝷䝇┅ᆅ௜㏆䛻䛚䛔䛶Ẽ 䛾ୖ᪼䞉Ỉị㞼䛾ῶᑡ䞉䝎䝇䝖䛾ቑຍ䛸ゝ䛳䛯┦㛵䛜ẖᖺ⌧䜜䛶䛔䜛䛣䛸䜢᫂䜙䛛䛻䛧䛯䚹௒ᖺᗘ䛿䚸኱つᶍ䛺ᒣᓅᆅᙧ䛷䛒䜛䝍䝹䝅䝇ᒣᆅୖ✵䛾Ẽ 䚸Ỉị㞼䚸䝎䝇䝖䛾┦㛵䛻╔┠䛧䛯䚹䝦䝷䝇┅ᆅ䛸䛿␗䛺䜚䚸䝎䝇䝖䛻㛵䛧䛶䛿᫂☜䛺┦㛵䛜ぢ䜙䜜䛺䛛䛳䛯䚹䛆Abstract䛇 This study aims to reveal the nature of dust, clouds and thermal structures (temperature) and theirinteractions in the Martian atmosphere by statistical analyses of remote sensing data mainly obtained byMartian explorers’ data. We utilized the observational results obtained by Mars Climate Sounder (MCS)
onboard Mars Reconnaissance Orbiter (MRO), which was launched in 2005 by NASA. We focused on thelongitudinal distributions of water ice clouds, dust and temperature and their correlations over the Tharsis
region in the Martian atmosphere.

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

ⅆᫍ䛿ᆅ⌫䛾୰ᒙ኱Ẽ䛻┦ᙜ䛩䜛⛬ᗘ䛾኱Ẽ䜢ᣢ䛳䛶䛚䜚䚸ᆅ⌫኱Ẽ䛷ᚓ䜙䜜䛯▱ぢ䜢ඖ䛻ⅆᫍ䛷ほ 䛥䜜䛯኱Ẽ⌧㇟䛾Ⓨ⏕䝯䜹䝙䝈䝮䜢ゎ᫂䛩䜛䛣䛸䛿䚸ᑗ᮶䛾↓ே䞉᭷ே᥈ᰝ䛻ᚲせ䛺ⅆᫍ኱Ẽ⎔ቃ䝕䞊䝍䛾ධᡭ䛻␃䜎䜙䛪䚸ᆅ⌫኱Ẽ䛷䛾▱ぢ䛜䛭䛾௚䛾ᝨᫍ䛻ᑐ䛧䛶䜒㏻⏝䛩䜛ᬑ㐢ⓗ䛺ἲ๎䛛䛹䛖䛛䜢ヨ䛩ୖ䛷䜒㔜せ䛷䛒䜛䚹ᮏ◊✲䛷䛿䚸⡿ᅜ䛾ⅆᫍ᥈ᰝᶵMars Reconnaissance Orbiter䠄MRO䠅ᦚ㍕䛾㉥እศගィ
Mars Climate Sounder 䠄MCS䠅䛻䜘䜛ほ 䛛䜙ᚓ䜙䜜䛯Ẽ 䚸Ỉị㞼䚸䝎䝇䝖䛾ྛ≀⌮㔞䛾⤫ィⓗ䛺ゎᯒ䜢⾜䛺䛖䛣䛸䛷䚸䛭䜜䜙䛾┦஫స⏝䜢᫂䜙䛛䛻䛩䜛䛸ඹ䛻ⅆᫍẼ㇟䞉Ẽೃ䛻୚䛘䜛ᙳ㡪䜢ホ౯䛩䜛䛣䛸䜢┠ⓗ䛸䛧䛶䛔䜛䚹≉䛻䚸௒ᖺᗘ䛿䝍䝹䝅䝇ᒣᆅୖ✵䛻╔┠䛧䛶ゎᯒ䜢ᐇ᪋䛧䛯䚹䠄䠍䠅䝍䝹䝅䝇ᒣᆅୖ✵䛷䛾Ỉị㞼䚸Ẽ䜢ゎᯒ䛧䜎䛧䛯䠄ᅗ䠍䠅䚹䚸䝎䝇䝖䛾⤒ᗘ䠉㧗ᗘศᕸ䠄䠎䠅ኪഃ䛾ほ 䝕䞊䝍䛻䛚䛔䛶䚸䝦䝷䝇┅ᆅ䛷ぢ䜙䜜䛯䛾䛸ྠᵝ䛺Ỉị㞼䛸Ẽ 䛾཯┦㛵䛜ぢ䜙䜜䜎䛧䛯䠄ᅗ୰䛾㉥୸䠅䚹୍᪉䛷䚸䝎䝇䝖䛿䚸ゎᯒᑐ㇟ᮇ㛫୰䛻ቑຍ䞉ῶᑡ䛾ኚື䛿䜏䜙䜜䛯䜒䛾䛾䚸䛭䜜䜙䛾ኚື䛿Ỉị㞼䜔Ẽ 䛸᫂☜䛺┦㛵䛿క䛺䛔䜎䛫䜣䛷䛧䛯䚹䛺䛚䚸᫨ഃ䛾䝕䞊䝍䛻䛿᫂☜䛺┦㛵䛿ぢ䜙䜜䜎䛫䜣䛷䛧䛯䚹䠄䠏䠅ྠᮇ㛫୰䛾䝦䝷䝇┅ᆅ䛷䛿䚸Ỉị㞼䞉Ẽ 䞉䝎䝇䝖䛾඲䛶䛻┦㛵䛜ぢ䜙䜜䚸䛂䝎䝇䝖㔞䛾ቑຍ䝎䝇䝖䛻䜘䜛ኴ㝧ග྾཰䛸Ẽ ୖ᪼Ỉị㞼䛾ῶᑡ䛃䛸䛔䛖௬ㄝ䜢❧䛶䜎䛧䛯䛜䚸䝍䝹䝅䝇ᒣᆅ䛷䛾⤖ᯝ䛿䛣䛾௬ㄝ䛜ᡂ䜚❧䛯䛺䛔ሙྜ䛜䛒䜛䛣䛸䜢♧䛧䛶䛔䜎䛩䚹ᅗ1 ⅆᫍ᥈ᰝᶵMROᦚ㍕MCS䝉䞁䝃䛻䜘䜛Ỉị㞼䚸Ẽ

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

䚸䝎䝇䝖䚹

ᮏ◊✲䛷᫂䜙䛛䛻䛥䜜䛯ྛ≀⌮㔞䛾┦㛵䜢ඖ䛻䚸᫖ᖺᗘ䛾ᡂᯝ䛸ే䛫䛶ᩘ್䝰䝕䝹䛸䛾ẚ㍑䛻฼⏝䛩䜛஦䜢᳨ウ䛧䛶䛔䜎䛩䚹― 68 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-11䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅䝬䜲䜽䝻Ἴᨺᑕィ䚸ᩓ஘ィཬ䜃䝯䝋Ẽ㇟䝰䝕䝹䜢⏝䛔䛯ὒୖ㢼ຊ㈨※㔞᥎ᐃᡭἲ䛾㛤Ⓨ㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Development of estimation method for offshore wind energy resources using
microwave radiometer, scatterometer and mesoscale meteorological model䠄◊✲௦⾲⪅ྡ䠅 㤶す㻌 ඞಇ㻌 䠄⚄ᡞ኱Ꮫ䞉ᾏ஦⛉Ꮫ◊✲⛉䠅
Katsutoshi Kozai 㻌 䠄Kobe University 䞉Graduate School of Maritime Sciences 䠅䛆せ᪨䛇୍⯡䛻ὒୖ㢼㏿䛿㧗ᗘ䛜ୖ䛜䜛䜋䛹኱䛝䛟䛺䜚䚸Ẽ 䛸ᾏ㠃Ỉ 䛾ᕪ䛜㢼㏿䝥䝻䝣䜯䜲䝹䠄㖄┤㢼㏿ศᕸ䠅䛻ᙳ㡪䜢ཬ䜌䛩䛣䛸䛜▱䜙䜜䛶䛔䜛䚹䝬䜲䜽䝻Ἴᩓ஘ィ䛿䛩䛷䛻୰❧≧ែ䜢௬ᐃ䛧䛯10m㧗䛾㢼㏿䠄Equivalent Neutral Wind, ENW䠅䛜⏝䛔䜙䜜䛶䛔䜛䛜䚸䝬䜲䜽䝻ἼᨺᑕィAMSR2䛛䜙᥎ᐃ䛥䜜䜛㢼㏿䛿኱ẼᏳᐃᗘ䜢⪃៖䛩䜛ᚲせ䛜䛒䜛䛛䛹䛖䛛䛸䛔䛖≧ἣ䛜ᮏ◊✲䛾⫼ᬒ䛸䛧䛶䛒䜛䚹䜎䛯ὒୖ㢼ຊ㈨※㔞䜢᥎ᐃ䛩䜛ሙྜ䚸㢼㌴䝝䝤㧗ᗘ䠄80~100m䠅䛾㢼㏿䜢᥎ᐃ䛩䜛䛯䜑㢼㏿䛾㧗ᗘ⿵ṇ䛜ᚲせ䛷䛒䜛䚹䛭䛣䛷ᮏ◊✲䛾┠ⓗ䛿AMSR2 䠄ver3䠅㢼㏿䜢➼౯୰❧㢼䠄ENW䠅䛸௬ᐃ䛩䜛䛣䛸䛻䜘䜚䚸䝯䝋Ẽ㇟䝰䝕䝹WRF䚸㢼㏿䝥䝻䝣䜯䜲䝹䝰䝕䝹COARE3.0䜢⏝䛔䛯㧗ᗘ⿵ṇ䜢క䛖኱ẼᏳᐃᗘ౫Ꮡ㢼㏿(SDW)䜢᳨ド䛧䚸
AMSR2 ver3㢼㏿䝥䝻䝎䜽䝖䛾≉ᛶ䜢ᢕᥱ䛩䜛䛣䛸䛷䛒䜛䚹᪥ᮏἢᓊᇦ䛾KEO䝤䜲䚸໭ᮾኴᖹὒ䛾PAPA䝤䜲䛾2012ᖺ7᭶
䜘䜚2014ᖺ12᭶䜎䛷䛾ẖ᫬㢼㏿䝕䞊䝍䜢᳨ド⏝䛸䛧䛶౑⏝䛧䛯⤖ᯝ䚸୧⪅䛾RMSE䛿䜋䜌➼䛧䛛䛳䛯䛜䚸PAPA䛾䝞䜲䜰䝇
䛿㈇䜢♧䛧䛯䚹䛣䜜䛿AMSR2䛛䜙ᑟ䛛䜜䛯15m/s௨ୖ䛾Ᏻᐃᗘ౫Ꮡ㢼㏿䛜㐣ᑠホ౯䛥䜜䛶䛔䜛䛣䛸䛜ཎᅉ䛸⪃䛘䜙䜜䜛䚹䛆Abstract䛇 In order to estimate offshore wind energy resources it is necessary to convert wind speed from satellitederived 10m wind speed to turbine hub height wind speed considering atmospheric stability. Assuming AMSR2derived wind speed as ENW(Equivalent Neutral Wind) speed, this study validates stability dependent wind (SDW)
speed from mesoscale meteorological model WRF and wind speed profile model COARE3.0 against KEO andPAPA buoy wind speed. RMSE of both buoys are almost same. However bias of PAPA shows negative. It is
attributable to the fact that SDW speeds more than 15m/s derived from AMSR2 are underestimated.

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

䠎

◊✲䛾
ᡂᯝ

ᮏ◊✲䛾⫼ᬒ䛸䛧䛶䠍䠊䝬䜲䜽䝻ἼᨺᑕィAMSR2䛛䜙᥎ᐃ䛥䜜䜛㢼㏿䛿኱ẼᏳᐃᗘ䜢⪃៖䛩䜛ᚲせ䛜䛒䜛䛛䛹䛖䛛䚸䠎䠊኱ẼᏳᐃᗘ䜢⪃៖䛧䛯㢼㏿䝥䝻䝣䜯䜲䝹䝰䝕䝹䛿䛹䛾ἢᓊᇦ䛻䛚䛔䛶䜒㐺⏝ྍ⬟䛷䛒䜛䛛䛹䛖䛛䚸䠏䠊㢼㏿䝥䝻䝣䜯䜲䝹䝰䝕䝹䛸䝯䝋Ẽ㇟䝰䝕䝹WRF䛾⤌䜏ྜ䜟䛫䛿኱ẼᏳᐃᗘ䜢⪃៖䛧䛯AMSR2㢼㏿䛻᭷ຠ䛷䛒䜛䛛䛹䛖䛛䛸䛔䛖≧ἣ䛜ᮏ◊✲䛾⫼ᬒ䛸䛧䛶䛒䜛䚹ᮏ◊✲䛾┠ⓗ䛿AMSR2 䠄ver3䠅㢼㏿䜢➼౯୰❧㢼䠄ENW䠅䛸௬ᐃ䛩䜛䛣䛸䛻䜘䜚䚸䝯䝋Ẽ㇟䝰䝕䝹WRF䚸㢼㏿䝥䝻䝣䜯䜲䝹䝰䝕䝹COARE3.0䜢⏝䛔䛯㧗ᗘ⿵ṇ䜢క䛖኱ẼᏳᐃᗘ౫Ꮡ㢼㏿(SDW)䜢᳨ド䛧䚸AMSR2 ver3㢼㏿䝥䝻䝎䜽䝖䛾≉ᛶ䜢ᢕᥱ䛩䜛䛣䛸䛷䛒䜛䚹኱ẼᏳᐃᗘ౫Ꮡ㢼㏿䜢᳨ド䛩䜛䛯䜑䚸᪥ᮏἢᓊᇦ䛾KEO䝤䜲䚸໭ᮾኴᖹὒ䛾PAPA䝤䜲䛾2012ᖺ7᭶䜘䜚
2014ᖺ12᭶䜎䛷䛾ẖ᫬㢼㏿䝕䞊䝍䜢౑⏝䛧䛯䚹
䠏Ⅼ௨ୗ䛻䝫䜲䞁䝖䜢⤠䜚㎸䜣䛷グ㍕䛧䛶ୗ䛥䛔䚹
䠄䠍䠅PAPA䛸KEO䛾᳨ド⤖ᯝ䛿䚸RMSE䛿䜋䜌➼䛧䛔䛜
2
PAPA䛾䝞䜲䜰䝇䛿㈇䛸䛺䜚䚸PAPA䛾R ್䛿KEO䜘䜚ప䛔䚹䛣䛾⌮⏤䛸䛧䛶AMSR2䛛䜙ᑟ䛛䜜䛯15m/s௨ୖ䛾Ᏻᐃᗘ౫Ꮡ㢼㏿(SDW)䛜㐣ᑠホ౯䛥䜜䛶䛔䜛䛣䛸䛜ᣲ䛢䜙䜜䜛䚹䠄ᅗ䠍ᕥ䠅䚹
ᅗ1
䠄䠎䠅㢼㏿䝥䝻䝣䜯䜲䝹䝰䝕䝹䠄COARE3.0䚸ᑐᩘ๎䠅䛸䛭䛾⤌䜏ྜ䜟䛫䛾୰䛷䚸COARE3.0+WRF䛿KEO䛻䛚䛡䜛Ᏻᐃᗘ౫Ꮡ㢼㏿䛾᥎ᐃ䛻䛚䛔䛶┦ᑐ䝞䜲䜰䝇䛸┦ᑐRMSE䜢1䡚䠎%ᨵၿ䛧䛯䠄ᅗ䠎䠅䚹

PAPA䠄ᕥ䠅䛸KEO䠄ྑ䠅䛻䛚䛡䜛㢼㏿䝥䝻䝣䜯䜲䝹䝰䝕䝹䛻ᇶ䛵䛟᳨ド⤖ᯝ (㯮⥺: ୍ᑐ୍┤⥺, ㉥⥺:ᅇᖐ┤⥺,2012/7~2014/12)

䠄䠏䠅COARE3.0+䝤䜲 䛸COARE3.0+WRF䜢ẚ㍑䛧䛯⤖ᯝ䚸┦ᑐ䝞䜲䜰䝇䛸┦ᑐRMSE䛻䜋䛸䜣䛹ᕪ䛿ぢ䜙䜜䛺䛛䛳䛯䚹
䛣䜜䛿WRF䜢AMSR2䛛䜙ᑟ䛛䜜䜛Ᏻᐃᗘ౫Ꮡ㢼㏿䛾᥎ᐃ䛻⏝䛔䜛᭷⏝ᛶ䜢♧၀䛧䛶䛔䜛䚹

ᅗ2

䠏

KEO䛻䛚䛡䜛㢼㏿䝥䝻䝣䜯䜲䝹䝰䝕䝹䛾┦ᑐ䝞䜲䜰䝇䛸┦ᑐRMSE◊✲䛾ᡂᯝ䛻グ㍕䛧䛯ෆᐜ䛻䛴䛔䛶䚸௚䛾◊✲䜈䛾ά⏝≧ἣ䛒䜛䛔䛿ᬑཬ䞉ᐇ⏝໬䛾≧ἣ䜢グ㍕䛧䛶䛟䛰ᡂᯝᒎ㛤䛾 䛥䛔䚹ୖグ䛷㛤Ⓨ䛧䛯ᡭἲ䛿 ᩓ஘ィ㢼㏿䛸䛸䜒䛻㢼㌴䝝䝤㧗ᗘ䠄80䡚100m䠅䛾㢼㏿᥎ᐃ䛻䜘䜛ὒୖ㢼ຊ㈨※㔞≧ἣ᥎ᐃ䛾◊✲䛻⏝䛔䜙䜜䜛䛣䛸䛜ᮇᚅ䛥䜜䜛䚹― 69 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-12䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅ከἼ㛗䝬䜲䜽䝻Ἴᨺᑕィ䝕䞊䝍䜢⏝䛔䛯Ỉ≀㉁㔞䝸䝖䝸䞊䝞䝹䛾◊✲㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Study on hydrometeor retrieval using multi-frequency microwave radiometer data䠄◊✲௦⾲⪅ྡ䠅 㟷᲍࿴ṇ㻌 䠄Ẽ㇟ᗇẼ㇟◊✲ᡤ䠅
Kazumasa Aonashi 㻌 䠄Japan Meteorological Agency Meteorological Research Institute 䠅䛆せ᪨䛇㞼ゎീ䝰䝕䝹䠄CRM)䛻䝬䜲䜽䝻Ἴ䜲䝯䞊䝆䝱(MWI) TB䜢ྠ໬䛩䜛EnVAR䝇䜻䞊䝮䜢㛤Ⓨ䛧䛯䚹䛣䛾䝇䜻䞊䝮䛷䛿䚸㝆Ỉ≀⌮㔞䛾䝃䞁䝥䝸䞁䜾ㄗᕪ䜢ῶ䜙䛩䛯䜑䚸2䝇䜿䞊䝹䛾Neighboring Ensemble 䜢౑䛳䛯䚹ᡃ䚻䛿䚸䛣䛾䝇䜻䞊䝮䛾᳨ド䛾䛯䜑䚸ྎ㢼1518䛾஦౛䛻䛴䛔䛶䚸MWI TB䜢ྠ໬䛩䜛ᐇ㦂䜢⾜䛺䛳䛯䚹
2015/9/8/17UTC 䛾AMSR2䛾TB䛾single observation䛾ྠ໬䛿䚸ྎ㢼䛸䛭䛾༡ᮾഃ䜢୰ᚰ䛸䛧䛶䚸ᗈ䛔⠊ᅖ䛷ゎᯒ䜲䞁䜽䝺䝯䞁䝖䜢స䜚䚸CRM䛾㝆Ỉணሗ䜢30᫬㛫䛻ர䛳䛶㢧ⴭ䛻ᨵၿ䛧䛯䚹The present study developed an Ensemble-based Variational Assimilation (EnVAR) scheme for the
Cloud-Resolving Model (CRM). In order to address serious sampling error for CRM precipitation-related
䛆Abstract䛇
variables, we introduced the dual-scale neighboring ensemble method (hereafter referred as DuNE).
We performed experiments using the above EnVAR scheme to assimilate Advanced Scanning
Microwave Radiometer 2 (AMSR2) brightness temperatures (TBs) for a Typhoon Etau (T1518) case (17UTC 8st Sep. 2015). The assimilation significantly improved a CRM precipitation forecast up to 30 hours,in particular, by strengthening and stagnating a rain band over the Kanto Plain.

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Ỉ≀㉁䛿䝬䜲䜽䝻Ἴ䜢ᨺᑕ䚸྾཰䚸ᩓ஘䛧䛶䛔䜛䚹Ỉ≀㉁䜢ྵ䜐኱Ẽ䛾䝬䜲䜽䝻Ἴᨺᑕఏ㐩䛿䚸Ỉ≀㉁䛾
┦䠄Ỉ⵨Ẽ䚸ᾮỈ䚸ᅛయ䠅䛷␗䛺䜚䚸䝬䜲䜽䝻Ἴ䛾Ἴ㛗䛻䜘䛳䛶䜒ኚ໬䛩䜛䚹ᚑ䛳䛶䚸ከἼ㛗䝬䜲䜽䝻Ἴᨺᑕィ䝕䞊䝍䜢⏝䛔䜛䛣䛸䛷䚸␗䛺䜛┦䜢ᣢ䛴Ỉ≀㉁䛾㔞䜢᥎ᐃ䛷䛝䜛䛣䛸䛜ᮇᚅ䛥䜜䜛䚹ᮏ◊✲䛾┠ⓗ䛿䚸ከἼ㛗䝬䜲䜽䝻Ἴᨺᑕィ䝕䞊䝍䛸䚸䛣䜜䛻ྠᮇ䛧䛯Ỉ≀㉁䛾⌧ᆅほ 䝕䞊䝍䜢⵳✚䛧䚸䛣䜜䜢䜒䛸䛻䚸ከἼ㛗䝬䜲䜽䝻Ἴᨺᑕィ䝕䞊䝍䜢౑䛳䛯䚸Ỉ≀㉁㔞䝸䝖䝸䞊䝞䝹ἲ䜢ᨵၿ䛩䜛䛣䛸䛷䛒䜛䚹䠍䠅㻌 㞼ゎീ䝰䝕䝹䠄CRM)䛻䝬䜲䜽䝻Ἴ䜲䝯䞊䝆䝱(MWI) TB䜢ྠ໬䛩䜛EnVAR䝇䜻䞊䝮䜢㛤Ⓨ䛧䛯䚹䛣䛾䝇䜻䞊䝮䛷䛿䚸㝆Ỉ≀⌮㔞䛾䝃䞁䝥䝸䞁䜾ㄗᕪ䜢ῶ䜙䛩䛯䜑䚸2䝇䜿䞊䝹䛾Neighboring Ensemble 䜢౑䛳䛯䚹䜎䛯䚸䛣䛾䝇䜻䞊䝮䛿䚸㝆Ỉ䛾㠀ṇつศᕸ䛻ᑐᛂ䛩䜛䛯䜑䚸≀⌮㔞䛾☜⋡ศᕸ(PDF)䜢䚸ᬕኳᇦ䛸㞼㝆Ỉᇦ䛾2䛴䛾ṇつศᕸ䛩䜛䝺䝆䞊䝮䛾ΰྜ䛷㏆ఝ䛧䚸䝺䝆䞊䝮ẖ䛻␗䛺䜛TB䛾ほ ㄗᕪ䜢㐺⏝䛧䛯䚹䛣䛾䝇䜻䞊䝮䛿䚸Ỉ≀㉁䛻㛵䛩䜛ไᚚኚᩘ䛸䛧䛶RTW䛸㝆Ỉᙉᗘ䜢౑䛔䚸䛭䛾௚䛾Ỉ≀㉁䛾ゎᯒ್䛿䚸ୖグ2䛴䛾ゎᯒ್䛛䜙䚸➼౯⥺ᙧ໬ᡭἲ䛷ィ⟬䛧䛯䚹䠎䠅㻌 ᡃ䚻䛿䚸䛣䛾䝇䜻䞊䝮䛾᳨ド䛾䛯䜑䚸ྎ㢼
1518䛾஦౛䛻䛴䛔䛶䚸MWI TB䜢ྠ໬䛩䜛ᐇ㦂䜢⾜䛺䛳䛯䚹2015/9/8/17UTC 䛾AMSR2䛾
10,18,23,36,89 GHz䛾㖄┤೫Ἴ䛾TB䛾single
observation䛾ྠ໬䛿䚸ྎ㢼䛸䛭䛾༡ᮾഃ䜢୰ᚰ䛸䛧䛶䚸ᗈ䛔⠊ᅖ䛷ゎᯒ䜲䞁䜽䝺䝯䞁䝖䜢స䜚䚸
CRM䛾㝆Ỉணሗ䜢30᫬㛫䛻ர䛳䛶㢧ⴭ䛻ᨵၿ䛧䛯䚹㻌 䜎䛯䚸ணሗゎᯒ䝃䜲䜽䝹䛻䜘䜛2015/9/7/14UTC
䛛䜙2015/9/8/17UTC䜎䛷䛾
GMI,SSMIS,AMSR2䛾TB䛾ྠ໬䛿䚸CRM䛾㝆Ỉணሗ䜢䠉≉䛻䚸㝆Ỉᖏ䜢㛵ᮾ௜㏆䛷ᙉ໬䛧䚸೵⁫䛥䛫䜛䛣䛸䛻䜘䜚䠉䛥䜙䛻ᨵၿ䛧䛯䚹

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ᅗ1ᖺ᭶᪥87&ࡢ๓㸯᫬㛫㝆Ỉ㔞 PP ྑୖ㸧࣮ࣞࢲゎᯒ㞵㔞ྑୖ㸧ࢹ࣮ࢱྠ໬࡞ࡋணሗ
ྑୗ㸧0:,ࢹ࣮ࢱྠ໬࠶ࡾ
㹌㹆㹋ணሗ )7 K 

㛤Ⓨ䛧䛯ᡭἲ䛿Ẽ㇟◊✲ᡤ⤒ᖖ◊✲䛂ྎ㢼䛾㐍㊰ணሗ䞉ᙉᗘゎᯒ䛾⢭ᗘྥୖ䛻㈨䛩䜛◊✲䛃䠄๪ㄢ㢟䠍䠖඲⌫ཬ䜃㡿ᇦゎᯒ䞉ணሗ䝅䝇䝔䝮䜢⏝䛔䛯ྎ㢼㐍㊰ணሗ䛾⢭ᗘྥୖ䛻㛵䛩䜛◊✲䠅䠄ᖹᡂ䠎䠒䠉䠏䠌ᖺᗘ䠅䛷฼⏝䛥䜜䛶䛔䜛䚹

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CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-13䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅䝸䝰䞊䝖䝉䞁䝅䞁䜾䝕䞊䝍䛻䜘䜛†἟ᇶ♏⏕⏘㔞᥎ᐃ䜰䝹䝂䝸䝈䝮䛾㛤Ⓨ㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Development of a algorithm for estimating primary productivity in lakes㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 from remote sensing data䠄◊✲௦⾲⪅ྡ䠅 ᯇୗ㻌 ᩥ⤒㻌 䠄⟃Ἴ኱Ꮫ䠅
Bunkei Matsushita 㻌 䠄University of Tsukuba 䠅䛆せ᪨䛇ᮏ◊✲䛿䚸䜎䛪஧✀㢮䛾QAA䠄Qusi-Analytical Algorithm䠅䜰䝹䝂䝸䝈䝮䠄QAA-V5䛸QAA_turbid䠅䜢⏝䛔䛶MERIS(MEdium Resolution Imaging Spectrometer)䝕䞊䝍䛛䜙㟘䞄ᾆ†Ỉ䛾᳜≀䝥䝷䞁䜽䝖䞁྾཰ಀᩘ䠄aph䠅䛸᭷ගᒙỈ῝䜢᥎ᐃ䛧䛯䚹ḟ䛻ඛ⾜◊✲䛛䜙ᚓ䛯MERIS䝕䞊䝍䛻䜘䜛㟘䞄ᾆ†Ỉ䛾Chl-a䛸䛒䜟䛫䛶䚸Chl-abased䝰䝕䝹䛸aph-based䝰䝕䝹䛻䜘䛳䛶㟘䞄ᾆ†Ỉ䛾ᇶ♏⏕⏘㔞䜢᥎ᐃ䛧䛯䚹䛥䜙䛻䚸㟘䞄ᾆ䝕䞊䝍䝧䞊䝇䛛䜙ᚓ䛯㟘䞄ᾆ†Ỉᇶ♏⏕⏘㔞䛾ᐇ ್䛸ẚ㍑䛩䜛䛣䛸䛻䜘䛳䛶䚸䛭䜜䛮䜜䝰䝕䝹䛾᥎ᐃ⢭ᗘ䜢ホ౯䛧䛯䚹᭱ᚋ䛻䚸㟘䞄ᾆ䛾⌧ᆅㄪᰝ䝕䞊䝍䜢⏝䛔䛶䚸2✀㢮䝰䝕䝹᥎ᐃ⢭ᗘ䛾㐪䛔䛾ཎᅉ䜢ヲ⣽䛻⪃ᐹ䛧䛯䚹

䛆Abstract䛇 We used two Qusi-analytical algorithms (i.e., QAA_v5 and QAA_turbid) to estimate absorption coefficientof phytoplankton (aph), euphotic zone depth from Medium Resolution Imaging Spectrometer (MERIS)
data. By combining chlorophyll-a (Chl-a) from MERIS, we estimated net primary production in Lake
Kasumigaura using Chl-a based model and aph-based model. Moreover, we evaluated estimation
accuracy of the two models using the Kasumigaura database. Finally, we discussed the cause of thedifferent estimation accuracy between the two types of model in detail using in situ data.

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†἟䛾ᇶ♏⏕⏘㔞䛿†Ỉ䛾ᐩᰤ㣴໬⛬ᗘ䜔Ⅳ⣲ᅛᐃ㔞䛺䛹䜢 䜛㔜せ䛺ᣦᶆ䛾୍䛴䛷䛒䜛䛯䜑䚸඲⌫†἟୍ḟ⏕⏘㔞䛾᥎ᐃ䛿೺඲䛺Ỉ฼⏝䚸Ỉᇦ⏕ែ⣔䛾ಖ඲䚸ཬ䜃䜾䝻䞊䝞䝹䛺Ⅳ⣲ᚠ⎔䛾ぢ✚䜒䜚䛻୙ྍḞ䛺Ꮡᅾ䛷䛒䜛䚹䝸䝰䞊䝖䝉䞁䝅䞁䜾䛻䜘䜛Ỉᇦ୍ḟ⏕⏘㔞䛾᥎ᐃ䝰䝕䝹䛸䛧䛶䚸䜽䝻䝻䝣䜱䝹a⃰ᗘ䜢䝧䞊䝇䛻䛧䛯䝰䝕䝹䠄Chl-a-based䝰䝕䝹䠅䛸᳜≀䝥䝷䞁䜽䝖䞁䛾྾཰ಀᩘ䜢䝧䞊䝇䛻䛧䛯䝰䝕䝹䠄aph-based䝰䝕䝹䠅䛜ᥦၐ䛥䜜䛯䛜䚸†἟䛷䛾䝰䝕䝹᥎ᐃ⢭ᗘ䛾᳨ド䛿䜎䛰୙༑ศ䛷䛒䜛䚹ᮏ◊✲䛿䛣䛾ၥ㢟Ⅼ䛻╔┠䛧䚸ୖグ2✀㢮䛾䝰䝕䝹䛾᭷⏝ᛶ䜢᳨ド䛩䜛䛣䛸䜢┠ⓗ䛸䛧䛯䚹䛣䛾䛯䜑䚸㟘䞄ᾆ䜢ᑐ㇟䛻䚸⾨ᫍ䝕䞊䝍ཬ䜃⌧ᆅ䝕䞊䝍䛾ゎᯒ䛻䜘䛳䛶䚸2✀㢮䝰䝕䝹᥎ᐃ⢭ᗘ䛾㐪䛔䛾ཎᅉ䜢ヲ⣽䛻⪃ᐹ䛧䛯䚹
䠄䠍䠅⾨ᫍ⏬ീ䛻ᑐ䛩䜛኱Ẽ⿵ṇἲ䚸኱Ẽ⿵ṇ῭䜏䛾⾨ᫍ⏬ീ䛛䜙†Ỉᅛ᭷ගᏛ≉ᛶ䞉ᾘᩓಀᩘ䞉᭷ගᒙỈ῝䞉䜽䝻䝻䝣䜱䝹a⃰ᗘ䛺䛹䛾᥎ᐃ䜰䝹䝂䝸䝈䝮䜢㛤Ⓨ䛧䜎䛧䛯䠄ᅗ䠍䠅䚹䛣䜜䛻䜘䜚䚸⾨ᫍ⏬ീ䛛䜙†Ỉᇶ♏
⏕⏘㔞䛾᥎ᐃ䛜ྍ⬟䛸䛺䜚䜎䛩䚹ᅗ1 †἟ᇶ♏⏕⏘㔞᥎ᐃ䜰䝹䝂䝸䝈䝮䠏䠄䠎䠅MERIS䝕䞊䝍䛻䜘䜛㟘䞄ᾆ†Ỉᇶ♏⏕⏘㔞䛾᥎ᐃ⤖ᯝ䛿䚸Chl-based䝰䝕䝹䛻ẚ䜉䚸aph-based䝰䝕䝹䛾᪉䛜᥎ᐃ⢭ᗘ䛜㧗䛟䚸┦ᑐㄗᕪ䛿⣙47䠂䛷䛒䛳䛯䚹䛧䛛䛧䚸ᇶ♏⏕⏘㔞Ꮨ⠇ኚ໬䛾෌⌧䛻䛴䛔䛶䛿䚸Chl-based䝰䝕䝹䛾᪉䛜ඃ䜜䛶䛔䜛䚹䜎䛰◊✲ẁ㝵୰䚹ᡂᯝᒎ㛤䛾≧ἣ

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CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-14䛇㻌 ⮬↛⅏ᐖ䛻䜘䜚⏕䛨䛯㟁㞳ᅪኚື䛾ᐃ㔞ⓗゎᯒ㻌 Quantitative analysis of ionospheric perturbations associated with natural hazards
䠄◊✲௦⾲⪅ྡ䠅 ୰⏣㻌 ⿱அ㻌 䠄༓ⴥ኱Ꮫ䞉኱Ꮫ㝔ᕤᏛ◊✲⛉䠅
Hiroyuki Nakata 䠄Chiba University 䞉Graduate School of Engineering䠅䛆せ᪨䛇ᆅ㟈䠄ὠἼ䠅䚸ⅆᒣ䚸ྎ㢼䛺䛹䛻䜘䜚㟁㞳ᅪᨐ஘䛜Ⓨ⏕䛩䜛䛣䛸䛜▱䜙䜜䛶䛔䜛䛣䛸䛛䜙䚸䛣䛾䜘䛖䛺⮬↛⌧㇟䛻䜘䜚⏕䛨䛯㟁㞳ᅪኚື䛸Ἴື※䛸䛾㛵ಀ䛻䛴䛔䛶᫂䜙䛛䛻䛩䜛䛣䛸䜢┠ⓗ䛸䛧䚸◊✲䜢㐍䜑䛯䚹䜎䛯䚸୧⪅䛾㛵ಀ䜢᫂䜙䛛䛻䛩䜛䛣䛸䛻䜘䜚䚸㟁㞳ᅪ୰ᛶ኱Ẽᅛయᆅ⌫䛾」ྜ⣔䛻䛚䛡䜛┦஫స⏝䛸䛔䛖䚸Ꮫ⾡ⓗ䛺㔜せ䛺▱ぢ䜢♧䛩䛸䛸䜒䛻䚸㟁㞳ᅪኚື䛛䜙⮬↛⌧㇟䛾つᶍ䜢ぢ✚䜒䜛䛣䛸䛜ྍ⬟䛻䛺䜛䛯䜑䚸㟁㞳ᅪᨐ஘䛾ほ䛻䜘䜛⅏ᐖ㆙ሗ䛺䛹䛾ᛂ⏝䛺䛹䛻䜒ᮇᚅ䛷䛝䜛䚹

䛆Abstract䛇 It is well-known that the ionospheric disturbances associated with natural hazards, such as
earthquakes (tsunamis), volcanic eruptions, typhoons, and so on. In this study, we have examined
the ionospheric disturbances in order to clear the relationship between the ionosphericdisturbances and their sources. This result contributes to showing the scientific knowledge of
coupling process of the ionosphere-neutral atmosphere-solid earth. In addition, this is alsoavailable to the warning system of natural hazards using ionospheric observations.

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◊✲䛾
ᡂᯝ

ᆅ㟈䜔ⅆᒣᄇⅆ䛺䛹䛾኱つᶍ䛺⮬↛⅏ᐖ䛻క䛔㟁㞳ᅪኚື䛜ほ 䛥䜜䛶䛔䜛䚹䛣䜜䜙䛿䚸⅏ᐖ䛻క䛔Ⓨ⏕䛧䛯኱ẼἼື䛜㟁㞳ᅪ䜎䛷ఏᦙ䛧䚸䝥䝷䝈䝬䜢ኚື䛥䛫䜛䛣䛸䛷⏕䛨䜛䛣䛸䛜▱䜙䜜䛶䛔䜛䚹ᆅ㟈䛻క䛔ኚື䛿ほ ᩘ䜒ከ䛟䚸䛭䛾䝯䜹䝙䝈䝮䛜᫂䜙䛛䛻䛥䜜䛶䛝䛯䛜䚸ྎ㢼䜔ⅆᒣᄇⅆ䛻䛴䛔䛶䛿䚸䛭䛾䝯䜹䝙䝈䝮䛿᫂䜙䛛䛻䛺䛳䛶䛔䛺䛔䚹䜎䛯䚸䛣䜜䜙䛾⮬↛⅏ᐖ䛾つᶍ䛸㟁㞳ᅪኚື䛜ᐃ㔞ⓗ䛻᫂䜙䛛䛻䛺䜛䛣䛸䛷䚸㟁㞳ᅪほ 䜢⏝䛔䛶䚸⅏ᐖ䛾つᶍ䜢ぢ✚䜒䜛䛣䛸䛜ྍ⬟䛻䛺䜛䛸䛔䛖஦ᐇ䛜䚸ᮏ◊✲䛾⫼ᬒ䛸䛧䛶䛒䜛䚹䛭䛣䛷䚸ᮏ◊✲䛾┠ⓗ䛿㟁㞳ᅪኚື䛸⮬↛⅏ᐖ䠄ᮏ◊✲䛷䛿䚸ᆅ㟈䚸ྎ㢼ⅆᒣᄇⅆ䜢ᑐ㇟䛸䛧䛯䠅䛸䛾㛵ಀ䜢᫂䜙䛛䛻䛩䜛䛣䛸䛷䛒䜛䚹⏝䛔䛯ほ 䛿GPS䚸HF䝗䝑䝥䝷䞊䛷䛒䜛䚹GPS䛿㧗ᗘ⣙350 km䚸HF䝗䝑䝥䝷䞊䛿150ࠥ250km䛾㟁㞳ᅪኚື䜢᫂䜙䛛䛻䛩䜛䛣䛸䛜ྍ⬟䛷䛒䜛䚹䠄䠍䠅ྎ㢼䛻క䛖㟁㞳ᅪኚື䛻䛴䛔䛶ゎᯒ䜢⾜䛔䚸HF 䝗䝑䝥䝷䞊䛻䜘䜛㟁㞳ᅪほ 䛷䛿䚸ྎ㢼䛻క䛖ኚື䜢ᐜ᫆䛻ᤊ䛘䜙䜜䜛䛜䚸GPS䛻䜘䜛㟁Ꮚᩘほ 䛷䛿䚸ྎ㢼䛻క䛖㟁㞳ᅪኚື䜢ᤊ䛘䜛䛣䛸䛿㞴䛧䛔䛣䛸䜢᫂䜙䛛䛻䛧䜎䛧䛯䚹HF䝗䝑䝥䝷䞊䛻ẚ䜉䚸GPS䛷ᑟฟ䛥䜜䜛㟁Ꮚᩘ䛿䜘䜚㧗㧗ᗘ䛾ᙳ㡪䛜ᙉ䛔䛣䛸䛜䜟䛛䛳䛶䛚䜚䚸ྎ㢼䛷ぢ䜙䜜䜛ኚື䛿㟁㞳ᅪኚື䛸䛧䛶䛿䚸ᴟ䜑䛶㧗࿘Ἴᩘ䛷䛒䜚䠄ᩘ10 mHz䠅䚸䛣䛾䜘䛖䛺㧗࿘Ἴ䛾Ἴື䛿䚸㧗㧗ᗘ㟁㞳ᅪ䛷䛿ᙉ䛟ῶ⾶䜢ཷ䛡䜛䛯䜑䚸GPS䛷䛿ᤊ䛘䜛䛣䛸䛜㞴䛧䛔䛣䛸䛜᥎ 䛥䜜䜎䛩䚹䠄䠎䠅LFᖏ㟁Ἴほ 䜢⾜䛔䚸䛭䛾≉ᛶ䛻䛴䛔䛶ゎᯒ䜢㐍䜑䜎䛧䛯䚹᫬้ྜ䜟䛫䛻⏝䛔䜙䜜䜛ᶆ‽㟁Ἴ䠄䠒䠌䡇Hz䠅䜢ほ 䛧䚸㟁㞳ᅪ䛷཯ᑕ䛥䜜฿㐩䛩䜛✵㛫Ἴ䛾ᙉᗘ䛻䛴䛔䛶ゎᯒ䜢⾜䛳䛯䛸䛣䜝䚸㟁㞳ᅪ㟁Ꮚᐦᗘ䛸䜘䛔┦㛵䜢ᣢ䛴䛣䛸䛜᫂䜙䛛䛻䛺䜚䜎䛧䛯䚹䛣䜜䛿㟁㞳ᅪ㟁Ꮚᐦᗘ䛜㟁Ẽఏᑟᗘ䛸䜘䛔┦㛵䜢ᣢ䛴䛯䜑䛰䛸⪃䛘䜙䛘䜎䛩䚹䛣䜜䛻䜘䜚䚸LFᖏ㟁Ἴほ 䛻䜘䜚㟁㞳ᅪほ 䜢⾜䛘䜛᮲௳䜢᫂䜙䛛䛻䛩䜛䛣䛸䛜ྍ⬟䛻䛺䜚䜎䛩䚹
䠄䠏䠅GPS䚸HF䝗䝑䝥䝷䞊ほ 䜢⏝䛔䛶䚸ⅆᒣᄇⅆ䛻క䛖㟁㞳ᅪኚື䛾ゎᯒ䜢⾜䛔䜎䛧䛯䚹ᅗ䠍䛾ୖẁ䛻ⅆᒣᄇⅆᚋ䛾GPS䛻䜘䜛㟁Ꮚᩘኚື䚸ୗẁ䛻HF䝗䝑䝥䝷䞊䛻䜘䜛㟁㞳ᅪୖୗኚື䜢♧䛧䛶䛔䜎䛩䚹䛔䛪䜜䜒ⅆᒣᄇⅆᚋ䛻ኚື䛜ほ䛥䜜䜛䛣䛸䛿▱䜙䜜䛶䛔䜎䛧䛯䛜䚸HF䝗䝑䝥䝷䞊䛷䛿䚸䛭䛾ኚື䛜஧䛴䛾䝰䞊䝗䛻䜟䛡䜙䜜䜛䠄䐟䠖ᄇⅆ䛾⾪ᧁ䛻䜘䜛ኚື䚸䐠䠖㟁㞳ᅪୗ㒊䛸ᆅ㠃䛸䛾ඹ㬆䛻䜘䜛ኚື䠅䛣䛸䛜᫂䜙䛛䛻䛺䜚䜎䛧䛯䚹䛣䛾䛣䛸䛿䜎䛰ሗ࿌䛥䜜䛶䛔䛺䛔஦ᐇ䛷䛒䜚䚸ᄇⅆ䛻క䛖㟁㞳ᅪኚື䛾᪂䛧䛔▱ぢ䛷䛩䚹

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

GPS-TEC

0422

300km

ᄇⅆ

䐟
HF Doppler

5006kHz

264km
䐟

䐠

ᄇⅆ
ᅗ䠍 ⅆᒣᄇⅆ䛻క䛖㟁㞳ᅪኚືほ ⤖ᯝ䚹ୖẁ䛿GPS䛻䜘䜚ᑟฟ䛧䛯㟁Ꮚᩘほ 䚸ୗẁ䛿HF 䝗䝑䝥䝷䞊䛻䜘䛖r㟁㞳ᅪୖୗኚື䚹ᮏ◊✲䛾ᡂᯝ䜘䜚䚸䠄䠍䠅ྎ㢼䛻㟁㞳ᅪኚື䛿GPS䛷䛸䜙䛘䜛䛣䛸䛿㞴䛧䛔䚸䠄䠎䠅LFᖏ㟁Ἴ䛻䜘䜛㟁㞳ᅪほ䛿䚸㟁Ꮚᐦᗘ䛜㧗䛔᫬ᮇ䛷䛒䜛䚸ኟ⮳䞉෤⮳௜㏆䛷䛿䚸ኚື䜢ほ 䛷䛝䜛ᶵ఍䛜ከ䛔䚸䠄䠏䠅ⅆᒣᄇⅆ䛻క䛖ኚື䛿GPS䛷䜒༑ศほ 䛜ྍ⬟䛷䛒䜚䚸䛣䜜䛿᭱ึ䛾⾪ᧁἼ䛻క䛖ኚື䜢䛸䜙䛘䛶䛔䜛䛣䛸䛜᫂䜙䛛䛸䛺䛳䛯䚹䛣䜜䜎䛷䛾ᆅ㟈䛻䛸䜒䛺䛖ኚືほ ⤖ᯝ䛸䛒䜟䛫䚸௒ᚋ䚸䜘䜚ᐃ㔞ⓗ䛺ゎᯒ䜢㐍䜑䛶䛔䛟ணᐃ䛷䛒䜛䚹― 72 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-15䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅UAV䝸䝰䞊䝖䝉䞁䝅䞁䜾ほ 䛻䜘䜛㔛ᆅ㔛ᒣ䛾᳜≀✀ከᵝᛶ䛾ᆅᅗ໬㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Mapping of vegetation diversity in SATOYAMA by UAV remote-sensing䠄◊✲௦⾲⪅ྡ䠅 Ọ஭㻌 ಙ㻌 䠄ᾏὒ◊✲㛤Ⓨᶵᵓ䞉ᆅ⌫⾲ᒙ≀㉁ᚠ⎔◊✲ศ㔝䠅
Shin Nagai 㻌 䠄Japan Agency for Marine-Earth Science and Technology䠅䛆せ᪨䛇㔛ᆅ㔛ᒣ䛻䛚䛡䜛᳜≀✀ከᵝᛶ䜢㧗⢭ᗘ䛻ᆅᅗ໬䛩䜛䛣䛸䛿䚸Ẽೃኚືୗ䛻䛚䛡䜛⏕ែ⣔䛾ᶵ⬟䜔䝃䞊䝡䝇䛸ே㛫άື䛾┦஫స⏝䜢⌮ゎ䛩䜛ୖ䛷㔜せ䛺ㄢ㢟䛷䛒䜛䚹ᮏ◊✲䛿䚸༓ⴥ䛾㔛ᆅ㔛ᒣ䜢ᑐ㇟䛻䚸UAV(unmanned areal vehicle)䛻ᦚ㍕䛧䛯䝕䝆䝍䝹䜹䝯䝷䛻䜘䜚」ᩘ䛾᫬ᮇ䛻✵୰෗┿᧜ᙳ䜢⾜䛔䚸┠どุㄞ䛻䜘䜚ᶞ✀ศᕸ䛾ᆅᅗ໬䜢⾜䛳䛯䚹䛭䛾⤖ᯝ䚸ྛᶞ✀䛾᳜≀Ꮨ⠇䜔ᶞෙ䛾ᵓ㐀䛾≉ᚩ䛻䜘䜚䚸ᶞ✀ุู䛜ྍ⬟䛷䛒䜛䛣䛸䜢᫂䜙䛛䛻䛧䛯䚹䛆Abstract䛇 Mapping of vegetation diversity in the SATOYAMA ecosystem is an important issue to understandthe relationship between ecosystem functions and service and human activities under climatechange. We periodically photographed the canopy surface using a digital camera mounted on a
UAV (unmanned areal vehicle) and mapped geographical distribution of each tree species by visual
discrimination. We identified that the characteristics of plant phenology and structure of tree canopy
provide useful information to discriminate each tree species.

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

㏆ᖺ䛾㔛ᆅ㔛ᒣ䛷䛿䚸㛤Ⓨ䠄➨1䛾༴ᶵ䠅䜔฼⏝•⟶⌮䛾పୗ䠄➨2䛾༴ᶵ䠅䛻䜘䜚䚸⏕ែ⣔䝃䞊䝡䝇䜔⏕≀ከᵝᛶ䛜పୗ䛧䛶䛔䜛䠄JBO2䚸⎔ቃ┬䠅䚹䝸䝰䞊䝖䝉䞁䝅䞁䜾ほ 䛿䚸᳜⏕⿕そ䜔᳜≀Ꮨ⠇䛾᫬✵㛫ศᕸ䛾ኚື䜢ᗈᇦⓗ䛻᳨ฟ䞉ᆅᅗ໬䛩䜛᭷┈䛺ᡭἲ䛷䛒䜛䚹㏆ᖺ䛷䛿㧗ゎീᗘ䛷ỗ⏝ᛶ䛾㧗䛔ほ 䜢ྍ⬟䛸䛩䜛
UAV䠄↓ே⯟✵ᶵ䠅䜢⏝䛔䛯ほ 䛻ᮇᚅ䛜㧗䜎䛳䛶䛔䜛䚹ᮏ◊✲䛾┠ⓗ䛿䚸UAV䛻ᦚ㍕䛧䛯䝕䝆䝍䝹䜹䝯䝷䜢⏝䛔䛶㔛ᆅ㔛ᒣ䛾ᆅ⾲㠃䛾≧ែ䜢᧜ᙳ䛧䚸䜹䝯䝷⏬ീ䛾ゎᯒ䛻䜘䜚᳜≀✀ከᵝᛶ䜢ᆅᅗ໬䞉ホ౯䛩䜛䛣䛸䛷䛒䜛䚹ᮏ◊✲䛿䚸༓ⴥ┴ᮾ㔠ᕷ䛾㔛ᆅ㔛ᒣ䜢ᑐ㇟䛻䚸UAV䛻䜘䜚✵୰෗┿䛾᧜ᙳ䜢3䞉4䞉6䞉11䞉12᭶䛻⾜䛔䚸✵୰෗┿䛸⌧ᆅㄪᰝ䛻䜘䜛ᶞ✀ศᕸ䛾᝟ሗ䛻ᇶ䛵䛔䛶䚸┠どุㄞ䛻䜘䜚ᶞ✀ศᕸ䛾ᆅᅗ໬䜢⾜䛳䛯䚹ྛᶞ✀䛾᳜≀Ꮨ⠇䠄᳃ᯘୖ㒊䛾ⴥ䛾Ⰽ䠅䛜≉ᚩⓗ䛺᫬ᮇ䛻᧜ᙳ䛧䛯✵୰෗┿䛻䜘䜚䚸ྛಶయ䛾ᶞ✀䜢ุูྍ⬟䛷䛒䛳䛯䠄ᅗ2䠅䚹䜎䛯䚸ྛᶞ✀䛾ᶞෙ䛾ᵓ㐀䛾≉ᚩ䜒ᶞ✀䜢ุู䛩䜛䛯䜑䛾㔜せ䛺᝟ሗ䜢ᥦ౪䛧䛯䚹䛣Ꮨ⠇䠄㛤䠄㛤ⰼ 㛤ⴥ ⣚ⴥ ⴠⴥⴠⴥ ᵝᘧ䜔ᮇ 䠅䜔ᶞෙ ᵓ㐀 ≉ᚩ䜢཰䛾⤖ᯝ䛿䚸ᵝ䚻䛺ᶞ✀䜢ᑐ㇟䛻᳜≀Ꮨ⠇䠄㛤ⰼ䞉㛤ⴥ䞉⣚ⴥ䞉ⴠⴥ䛾ᵝᘧ䜔ᮇ᪥䠅䜔ᶞෙ䛾ᵓ㐀䛾≉ᚩ䜢཰㞟䛩䜛䛣䛸䛻䜘䜚䚸」ᩘ䛾᫬ᮇ䛻᧜ᙳ䛧䛯✵୰෗┿䜢⏝䛔䛶ᶞ✀ศᕸ䛾ᆅᅗ໬䜢ᗈᇦⓗ䛻⾜䛘䜛ྍ⬟ᛶ䜢♧၀䛧䛯䚹䕿䕿䛻䜘䜛䕿䕿⏕⫱≧ἣ
䕿䕿
䕿䛻䜘
䕿䛻䜘䜛
䛻䜘䜛
䛻
䜘䜛
䜘䜛䕿䕿⏕
䕿䕿
䕿
䕿⏕
䕿
⏕⫱
⫱≧ἣ
⫱≧
≧ἣ
≧
ἣ
ᅗ1
ᅗ
1 䕿

ᅗ1 ᑐ㇟䝃䜲䝖䛻䛚䛡䜛௦⾲ⓗ䛺ᶞ✀ᑐ㇟䝃䜲䝖䛻䛚䛡䜛ᶞ✀ศᕸ䠄ᕥ䠖䝇䜼䞉୰䠖䝇䝎䝆䜲䛺䛹䞉ྑ䠗䝁䝘䝷䛺䛹䠅
ᅗ2ᅗ2

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

ᮏ◊✲䛾ᡂᯝ䛿䚸䝸䝰䞊䝖䝉䞁䝅䞁䜾䛻䜘䜛᳜≀✀ከᵝᛶ䛾ᆅᅗ໬䜔䚸ḟୡ௦䛾⾨ᫍ䛻ᦚ㍕䛥䜜䜛㧗ゎീᗘ䛺ྍど䞉㏆㉥እ䝉䞁䝃䞊䛾ᢏ⾡㛤Ⓨ䛻ᙺ❧䛶䜙䜜䜛䚹― 73 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-19䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅 SKYNET䝕䞊䝍䜢⏝䛔䛯኱Ẽ⎔ቃ䛾◊✲㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅 A study of atmospheric environment with the SKYNET data䠄◊✲௦⾲⪅ྡ䠅 ஂឿ㻌 ㄔ㻌 䠄ዉⰋዪᏊ኱Ꮫ䠅
Makoto KUJI 㻌 䠄Nara Women’s University䠅䛆せ᪨䛇ᮾ䜰䝆䜰䛻䛚䛡䜛኱Ẽ⎔ቃ䛾ᢕᥱ䛾䛯䜑䚸䜶䜰䝻䝌䝹䛾ືែ䜢ᢕᥱ䛩䜛䛣䛸䛿㔜せ䛷䛒䜛䚹ᮏ◊✲䛷䛿䚸✵Ẽ䝃䞁䝥䝸䞁䜾䚸┠ど䚸୪䜃䛻䝸䝰䞊䝖䝉䞁䝅䞁䜾䝕䞊䝍䜢⏝䛔䛶䚸ዉⰋᕷ䛻䛚䛡䜛䜶䜰䝻䝌䝹䛾≉ᚩ䜢ㄪ䜉䛯䚹䜎䛪䚸ዉⰋዪᏊ኱Ꮫ䛷ほ 䛧䛶䛔䜛 Optical Particle Counter (OPC) 䛸す㒊኱Ẽởᰁ┘どᒁ䛷 ᐃ䛥䜜䛶䛔䜛 PM2.5 䜢ẚ㍑
䛧䛯䛸䛣䜝䚸ẚ㍑ⓗ㧗䛔┦㛵䛜ᚓ䜙䜜䛯䚹ḟ䛻䚸OPC䛸ど⛬䛾ẚ㍑䜘䜚䚸ど⛬ᝏ໬䛻䛿ᑠ⢏Ꮚ䛾ቑຍ䛜኱䛝䛟ᙳ㡪䛧䛶䛔䜛䛣䛸䛜ศ䛛䛳䛯䚹䛥䜙䛻䚸OPC䛸䚸䜔䛿䜚ዉⰋዪᏊ኱Ꮫ䛷ኴ㝧┤㐩ග䜢ほ 䛧䛶䛔䜛 Microtops 䛸䛾ẚ㍑䛻䜘
䜚䚸኱Ẽୗᒙ䛾⢏Ꮚᩘ⃰ᗘ䛸኱Ẽ඲ᒙ䛾䜶䜰䝻䝌䝹㔞䛿ᴫ䛽ྠᵝ䛾ኚື䜢䛧䛶䛔䛯䛣䛸䛜ศ䛛䛳䛯䚹䛣䜜䜙䛾ゎᯒ⤖ᯝ䜢㋃䜎䛘䚸௒ᚋ䛿䜂䜎䜟䜚⾨ᫍ䜔SKYNETほ 䝕䞊䝍䛸䛾ẚ㍑䜢⾜䛖ணᐃ䛷䛒䜛䚹
䛆Abstract䛇 It is important to monitor the aerosol behavior over East Asia. We performed optical observations in terms
of aerosol properties with sun photometry and air sampling for three years at Nara. Comparisons of theparticle number concentration with the PM2.5 mass concentration, visibility, and aerosol optical thickness
revealed that these observations were consistent as a whole. We will continue these observations tovalidate Himawari satellite and SKYNET observations.

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㻌 䜶䜰䝻䝌䝹䛿኱Ẽ⎔ቃ䛻ᙳ㡪䜢୚䛘䜛せᅉ䛾୍䛴䛷䛒䜛䚹㏆ᖺ䚸䜰䝆䜰ᇦ䛷䛿ᛴ㏿䛺⤒῭Ⓨᒎ䛻క䛖኱Ẽởᰁ䛜㢧ᅾ໬䛧䛶䛚䜚䚸䜶䜰䝻䝌䝹䛻䜘䜛኱Ẽ⎔ቃ䜈䛾ᙳ㡪䛜ᠱᛕ䛥䜜䛶䛔䜛䚹䛭䛾Ⅽ䚸䜶䜰䝻䝌䝹䛾ືែ䜢ᢕᥱ䛩䜛䛣䛸䚸≉䛻ே㛫䛾ఫ䜐኱Ẽୗᒙ䛾䜶䜰䝻䝌䝹䛾ືែ䜢ᢕᥱ䛩䜛䛣䛸䛿㔜せ䛷䛒䜛䚹㻌 䛭䛣䛷䚸ᮏⓎ⾲䛷䛿✵Ẽ䝃䞁䝥䝸䞁䜾䚸┠ど䚸୪䜃䛻䝸䝰䞊䝖䝉䞁䝅䞁䜾䝕䞊䝍䜢⏝䛔䛶ዉⰋᕷ䛻䛚䛡䜛䜶䜰䝻䝌䝹䛾≉ᚩ䜢ㄪ䜉䛯䚹ලయⓗ䛻䛿䚸ዉⰋዪᏊ኱Ꮫ䛷 Microtops 䛸 OPC 䛾ほ 䜢⾜䛳䛯䚹䛣䛾௚䛻䚸ᮏᏛ䛛䜙⣙ 730 m 㞳䜜䛯ዉⰋᆅ᪉Ẽ㇟ྎ䛾ど⛬ほ 䝕䞊䝍䛸䚸⣙ 8 km 㞳䜜䛯す㒊኱Ẽởᰁ ᐃᒁ䛷ほ 䛥
䜜䛯 PM2.5 䛾䝕䞊䝍䜢⏝䛔䛶ẚ㍑ゎᯒ䜢⾜䛳䛯䚹ᮏ◊✲䛷ᚓ䜙䜜䛯ᡂᯝ䛿௨ୗ䛾㏻䜚䛷䛒䜛䚹䠄䠍䠅 Microtops䛻䜘䛳䛶ほ 䛥䜜䛯䜶䜰䝻䝌䝹䛾Ἴ㛗 440 nm 䛻䛚䛡䜛ගᏛⓗཌ䛥䛸䚸OPC䜢⏝䛔䛶ほ 䛥䜜䛯⢏ᚄ 0.3 μm ௨ୖ䛾⢏Ꮚᩘ⃰ᗘ䛾┦㛵䜢ㄪ䜉䛯䠄ᅗ䠍䠅䚹䛭䛾⤖ᯝ䚸┦㛵ಀᩘ䛿 0.72 䛸䚸ẚ㍑ⓗᙉ䛔ṇ䛾┦㛵䜢♧䛧䛯䚹䛣䜜䛻䜘䜚䚸኱Ẽ඲ᒙ䛸ୗᒙ䛾䜶䜰䝻䝌䝹㔞䛿ᴫ䛽ྠᵝ䛾ኚື䜢䛧䛶䛔䜛䛸⪃䛘䜙䜜䜛䚹䠄䠎䠅 ⢏ᚄ 0.3ࠥ2.0 μm 䛾⢏Ꮚᩘ⃰ᗘ䛸䚸㉁㔞⃰ᗘ䛷䛒䜛㻌 PM2.5 䛾┦㛵䜢ㄪ䜉䛯(ᅗ2)䚹䛭䛾⤖ᯝ䚸┦㛵ಀᩘ䛿0.85䛸䛺䜚䚸ᙉ䛔ṇ䛾┦㛵䜢䛔䜛♧䛧䛯䚹䛣䛾䛣䛸䛛䜙䚸⢏Ꮚᩘ⃰ᗘ䛸㉁㔞⃰ᗘ䛿ᴫ䛽ྠᵝ䛾ኚື䜢䛧䛶䛔䜛䛣䛸䛜ศ䛛䛳䛯䚹㻌䛷䠄䠏䠅 ᑐὶᅪ䛻䛚䛡䜛ど⛬䛿୺䛸䛧䛶䜶䜰䝻䝌䝹䛻䜘䜛ኴ㝧ᨺᑕ䛾ᩓ஘䛷䚸Ỵ䜎䜛䛯䜑䚸䜶䜰䝻䝌䝹䛾⢏Ꮚᩘ⃰ᗘ䛸ど⛬䛾┦㛵䜢ㄪ䜉䛯䚹䛭䛾⤖ᯝ䚸┦㛵ಀᩘ䛿 ⢏ᚄ 0.3ࠥ0.5 μm 䛷 -0.46䚸0.5ࠥ1.0 μm 䛷 -0.37䚸
1.0ࠥ2.0 μm 䛷 -0.27䚸2.0ࠥ5.0 μm 䛷 -0.17䚸5.0 μm ௨ୖ䛷 -0.10 䛸䛺䛳䛯䚹ᑠ⢏Ꮚ䠄0.3ࠥ0.5䚸0.5ࠥ1.0䚸1.0ࠥ2.0 μm䠅䛷䛿䜔䜔ᙅ䛔㈇䛾
┦㛵䜢♧䛩୍᪉䛷䚸኱⢏Ꮚ䠄2.0ࠥ5.0 μm䚸5.0 μm௨ୖ䠅䛷䛿䜋䛸䜣䛹┦㛵䛜ぢ䜙䜜䛺䛛䛳䛯䚹䛣䜜䜘䜚䚸ど⛬䛿኱⢏Ꮚ䜘䜚䜒ᑠ⢏Ꮚ䛾ᙳ㡪䜢ཷ䛡䚸ᑠ⢏Ꮚ䛜༟㉺䛩䜛䛸ど⛬䛿䜘䜚ᝏ໬䛩䜛䛸⪃䛘䜙䜜䜛䚹ᅗ1 䜶䜰䝻䝌䝹䛾ගᏛⓗཌ䛥䛸⢏Ꮚᩘ⃰ᗘ䛾┦㛵䚹5䛾⢏Ꮚᩘ⃰ᗘ䛸PM2.5䛾ᅗ2 ⢏Ꮚᩘ⃰ᗘ䛸PM2
┦㛵䚹

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

ୖグ䛾◊✲䛾ᡂᯝ䛿䚸䜎䛪䚸ዉⰋᕷ䛾኱Ẽ⎔ቃ䛾ᢕᥱ䛻ᙺ❧䛳䛶䛔䜛䚹䛣䛣䛷䚸す㒊኱Ẽởᰁ┘どᒁ䛷ほ䛥䜜䛶䛔䜛 PM2.5 䛿ᆅ⾲㠃௜㏆䛻䛚䛡䜛1ᆅⅬ䛾ほ 䛷䛒䜚䚸䜎䛯䚸ዉⰋᆅ᪉Ẽ㇟ྎ䛷ほ 䛥䜜䛶䛔䜛ど⛬䛿ዉⰋ┅ᆅ䛻䛚䛡䜛኱Ẽୗᒙ䛻䛚䛡䜛኱Ẽ䛾ぢ㏻䛧䜢♧䛧䛶䛔䜛䛯䜑䚸䛹䛱䜙䛛䛸ゝ䛘䜀䚸ᆅ⾲㠃௜㏆䛾ᒁᡤⓗ䛺ởᰁ䛾ᣦᶆ䛸䛺䜛䚹䛭䛾୍᪉䛷䚸኱Ẽ඲ᒙ䛾ほ 䛿ᮾ䜰䝆䜰䛾኱㝣㉳※䛾኱Ẽởᰁ䛾┘ど䛻㈉⊩䛩䜛䛸⪃䛘䜙䜜䜛䚹௒ᚋ䛿䚸䜂䜎䜟䜚⾨ᫍ䜔SKYNETほ 䝕䞊䝍䛸䛾ẚ㍑䜢㐍䜑䜛ணᐃ䛷䛒䜛䚹― 74 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-22䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅䜂䜎䜟䜚8ྕ䛻䜘䜛᳜⏕Ꮨ⠇ኚ໬䛾㛗ᮇほ ᡭἲ䛾ᵓ⠏㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Utilization of Himawari-8/AHI for long-term vegetation monitoring䠄◊✲௦⾲⪅ྡ䠅 ᯇᒸ㻌 ┿ዴ㻌 䠄㧗▱኱Ꮫ䞉ᩍ⫱◊✲㒊䠅
Masayuki Matsuoka 㻌 䠄Kochi University 䞉Agriculture Unit 䠅㻌䛆せ᪨䛇㻌 㻌 㻌 㻌 䜂䜎䜟䜚8ྕ䛻ᦚ㍕䛥䜜䛯AHI (Advanced Himawari Imager)䛿Ẽ㇟ほ 䛾䜏䛺䜙䛪䚸᳜⏕䜢䛿䛨䜑䛸䛩䜛㝣ᇦ⎔ቃ䛾ゎᯒ䜈䛾ά⏝䜒ᮇᚅ䛥䜜䛶䛔䜛䚹≉䛻䚸㟼Ṇ㌶㐨䛛䜙䛾㧗㢖ᗘほ 䛿䚸䛣䜜䜎䛷䛾ᆅ⌫ほ ⾨ᫍ䛻䛿䛺䛔≉ᚩ䛷䛒䜛䚹ᮏ◊✲䛾┠ⓗ䛿䚸䜂䜎䜟䜚䜢⏝䛔䛶᳜⏕Ꮨ⠇ኚ໬䛾㛗ᮇほ ᡭἲ䜢ᵓ⠏䛩䜛஦䛷䛒䜛䚹ᮏᖺᗘ䛿䚸᳜⏕䜢ほ 䛩䜛ୖ䛷㔜せ䛺せᅉ䛸䛺䜛䚸஧᪉ྥᛶ཯ᑕ≉ᛶ䛾ゎᯒ䜢⾜䛺䛳䛯䚹஧᪉ྥᛶ཯ᑕ䝰䝕䝹䛸䛧䛶䜹䞊䝛䝹ᆺ䛾BRDF(Bidirectional
Reflectance Distribution Function)䝰䝕䝹䜢⏝䛔䚸8᫬㛫ศ䛾᫬⣔ิAHI䝕䞊䝍䜢⏝䛔䛶䝟䝷䝯䞊䝍䛾᥎ᐃ䜢⾜䛺䛳䛯䚹䛭䛾⤖ᯝ䚸౑⏝䛩䜛䜹䞊䝛䝹䛻䜘䜛ᙳ㡪䛿ᑠ䛥䛔䛣䛸䚸኱Ẽୖ➃䛷䛾཯ᑕ⋡䜘䜚䛿䚸ศගᨺᑕ㍤ᗘ䜢⏝䛔䜛䜋䛖䛜䝰䝕䝹䛾㐺ྜᗘ䛜㧗䛔஦䛜♧䛥䜜䛯䚹䜎䛯䚸䝟䝷䝯䞊䝍䛜ᆅᙧ䛾ᙳ㡪䜢ཷ䛡䛶䛔䜛஦䛜᫂䜙䛛䛸䛺䛳䛯䚹䛆Abstract䛇The Advanced Himawari Imager (AHI) onboard Himawari-8 is available not only for the meteorologicalobservation but for environmental monitoring of the earth surface such as vegetation change. The purpose of thisstudy is to develop the monitoring scheme of vegetation phenology using Himawari-8/AHI. The bidirectionalreflectance was modeled using a kernel-driven BRDF model. We found that the performace of the model is almost
same by kernel combinations, and spectral radiance shows higher degree of fitness than the top-of-atmospherereflectance.

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◊✲䛾
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≧ἣ

䜂䜎䜟䜚8ྕ䚸9ྕ䛻ᦚ㍕䛥䜜䛯AHI䛻䜘䜚䚸㛗ᮇ䛻䜟䛯䜛᳜⏕Ꮨ⠇ኚ໬䛾ゎᯒ䛜ྍ⬟䛸䛺䛳䛯䚹⾨ᫍ䛷ほ䛥䜜䛯ศග཯ᑕ⋡䛿䚸᳜⏕䛾௚䛻䜒䚸ኴ㝧䛸⾨ᫍ䛾఩⨨㛵ಀ䛻䜘䜛཯ᑕ⋡䛾㐪䛔䠄஧᪉ྥᛶ཯ᑕ≉ᛶ䠅䜔኱Ẽ䛾ᙳ㡪䛻䜘䛳䛶ኚ໬䛩䜛䚹ᮏᖺᗘ䛿䚸஧᪉ྥᛶ཯ᑕ≉ᛶ䛻䛴䛔䛶䚸᪤Ꮡ䛾BRDF䝰䝕䝹䜢⏝䛔䛶ゎᯒ䜢⾜䛺䛳䛯䚹MODIS䛷฼⏝䛥䜜䛶䛔䜛䜹䞊䝛䝹ᆺ䝰䝕䝹䜢䚸AHI䛾᪥ᮏᇦ䝕䞊䝍䠄8᫬㛫ศ䚸192䝅䞊䞁䠅䛻㐺⏝䛧䛯䚹䝰䝕䝹䛾䝟䝷䝯䞊䝍䜢᭱ᑠ஧஌᥎ᐃ䛧䚸⮬⏤ᗘㄪᩚ῭䜏Ỵᐃಀᩘ䜢⏝䛔䛶(1)⏝䛔䜛䜹䞊䝛䝹䛻䜘䜛㐪䛔䛿䛒䜛䛛䚸(2) ኱Ẽୖ➃䛷䛾཯ᑕ⋡䛸ศගᨺᑕ㍤ᗘ䛷䛿䛹䛱䜙䛜㐺ྜᗘ䛜㧗䛔䛛䚸䜢ホ౯䛧䛯䚹䜎䛯䚸᥎ᐃ䛥䜜䛯䝟䝷䝯䞊䝍䛾✵㛫ศᕸ䛛䜙䝰䝕䝹䛾≉ᛶ䜢⪃ᐹ䛧䛯䚹䠄䠍䠅䝪䝸䝳䞊䝮䜹䞊䝛䝹䛸䛧䛶䚸Ross-Thick(RTK)䛸Ross-Thin⾲1 䝟䝷䝯䞊䝍᥎ᐃ᫬䛾Ỵᐃಀᩘ(RTN)䚸䝆䜸䝯䝖䝸䝑䜽䜹䞊䝛䝹䛸䛧䛶Li-Sparse-Reciprocal(LSR)ୖ䠖኱Ẽୖ➃䛷䛾཯ᑕ⋡䚸ୗ䠖ศගᨺᑕ㍤ᗘ
䛸Li-Dense(LDN)䜢౑⏝䛧䚸ྛ⤌ྜ䛫䛻䛚䛡䜛Ỵᐃಀᩘ䜢ồ䜑䛯䠄⾲1䠅䚹ୖẁ䛿኱Ẽୖ➃䛷䛾཯ᑕ⋡䜢⏝䛔䛯ሙྜ䚸ୗẁ䛿ศග
ᨺᑕ㍤ᗘ䠄ィ⟬䛿ኴ㝧ග཯ᑕ⋡䜢⏝䛔䛯䛜䚸ᐃ⩏䛛䜙ศගᨺᑕ㍤ᗘ䜢⏝䛔䛯ሙྜ䛸ྠ䛨䛷䛒䜛䛯䜑䚸ศගᨺᑕ㍤ᗘ䛸⾲グ䠅䜢⏝䛔䛯ሙྜ䜢⾲䛧䛶䛔䜛䚹᪥ᮏ䛾⏬⣲䛻䛚䛡䜛ᖹᆒ್䛷♧䛧䛶䛚䜚䚸ᣓᘼෆ䛿ᶆ‽೫ᕪ䛷䛒䜛䚹䛣䜜䛻䜘䜚䚸䜹䞊䝛䝹䛾⤌ྜ䛫䛻䜘䜛ᕪ䛿㠀ᖖ䛻ᑠ䛥䛔஦䛜᫂䜙䛛䛸䛺䛳䛯䚹䠄䠎䠅⾲1䛾ୖẁ䛸ୗẁ䛾ẚ㍑䛛䜙䚸኱Ẽୖ➃䛷䛾཯ᑕ⋡䜘䜚䛿䚸
ศගᨺᑕ㍤ᗘ䜢⏝䛔䛯䜋䛖䛜䝰䝕䝹䛾㐺ྜᗘ䛜㧗䛔஦䛜᫂䜙䛛䛸䛺䛳䛯䚹䛣䛾ཎᅉ䛿䚸኱Ẽୖ➃䛷䛾཯ᑕ⋡䛾ィ⟬䛻䛚䛔䛶ኴ㝧ኳ㡬ゅ䛾వᘻ䛷㝖⟬䛧䛶䛔䜛஦䛻䛒䛳䛯䚹䛭䜜䛻䜘䜚䚸ኴ㝧ኳ㡬ゅ䛾኱䛝䛔ᮅኤ䛾཯ᑕ⋡䛜ୖ᪼䛧䚸䝰䝕䝹䛜䛭䛾ኚື䜢෌⌧䛷䛝䛶䛔䛺䛛䛳䛯䚹䛣䛾⤖ᯝ䛛䜙䚸኱Ẽୖ➃䛷䛾཯ᑕ⋡䜘䜚䛿䚸ศගᨺᑕ㍤ᗘ䜢䝰䝕䝹໬䛧䛯ୖ䛷཯ᑕ⋡䜢⟬ฟ䛩䜛฼⏝᪉ἲ䛜♧၀䛥䜜䛯䚹䠄䠏䠅䝟䝷䝯䞊䝍䛾✵㛫ศᕸ䜢ᅗ1䛻♧䛩䚹㯮䛔㒊ศ䛿㞼䛜ከ䛟䛶䝟䝷䝯䞊䝍䛜᥎ᐃ䛷䛝䛺䛛䛳䛯㒊ศ䛷䛒䜛䚹䛭䛾࿘ᅖ䜔ᮾ໭䞉໭ᾏ㐨䛷䝟䝷䝯䞊䝍䛾ᒁᡤⓗ䛺ኚື䛜኱䛝䛟䚸㝖ཤ䛷䛝䛺䛛䛳䛯㞼䛾ᙳ㡪䜢ཷ䛡䛶䛔䛯䚹䜎䛯䚸Ᏻᐃ䛧䛯᥎ᐃ⤖ᯝ䛜ᚓ䜙䜜䛯୰ᅜ䞉ᅄᅜ䞉஑ᕞ䛾⤖ᯝ䛛䜙䚸䝟䝷䝯䞊䝍䛜ᆅᙧ䛾ᙳ㡪䜢ཷ䛡䛶䛔䜛஦䛜᫂䜙䛛䛸䛺䛳䛯䚹䛣䜜䛻䜘䜚䚸䜘䜚ヲ⣽䛺཯ᑕ⋡᥎ᐃ䜈䛾᪉ྥᛶ䛜♧䛥䜜䛯䚹 ᅗ1 䝟䝷䝯䞊䝍䛾⏬ീ௒ᖺᗘ䛾ゎᯒ䛛䜙䚸㞼ุู䛾㧗⢭ᗘ໬䚸኱Ẽ⿵ṇ䚸ᆅᙧ䛾ᙳ㡪䛾㝖ཤ䛺䛹䛾ᚲせᛶ䛜♧䛥䜜䜎䛧䛯䚹䛣䜜䜙䛾ㄢ㢟䜢ゎỴ䛩䜛஦䛷䚸AHI䛛䜙᳜⏕䛾Ꮨ⠇ኚ໬䜢㧗㢖ᗘ䛻ゎᯒ䛩䜛஦䛜ྍ⬟䛸䛺䜚䜎䛩䚹䜎䛯䚸ᡭἲ䜢฼⏝䛩䜛஦䛷䚸AHI䛛䜙ᢳฟ䛥䜜䛯᳜⏕ኚ໬䜢Ẽೃኚື䜔⏕ែᏛ䛾◊✲䛻ά⏝䛷䛝䜛䜘䛖䛻䛺䜚䜎䛩䚹― 75 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-29䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅㓟⣲A䝞䞁䝗䜢฼⏝䛧䛯䜽䝻䝻䝣䜱䝹⺯ග䛾ศග⏬ീィ 䠖Ỉ⏣䞉᳃ᯘ䜈䛾ᛂ⏝㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Spectral image measurement of chlorophyll fluorescence using the oxygen A band䠖㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 application to Rice field and forest䠄◊✲௦⾲⪅ྡ䠅 ቑ⏣㻌 ೺஧㻌 䠄㟼ᒸ኱Ꮫ䞉ᢏ⾡㒊䠅Kenji Masuda 㻌 䠄Shizuoka University 䞉Division of Technical Service 䠅䛆せ᪨䛇 ᡃ䚻䛿ᆅୖ䛷䛾䝸䝰䞊䝖䝉䞁䝅䞁䜾ィ 䛻䜘䜚䚸㔝እ䛾⩌ⴠ䝺䝧䝹䛷ά⏝ྍ⬟䛺ኴ㝧ගㄏ㉳䛾᳜≀⺯ග (ィ ἲ䜢㛤Ⓨ䛧䛶䛔䜛䚹⿦⨨䛾ᇶᮏⓗ䛺ᵓᡂ䛸䛧䛶䛿䚸ගᏛᮃ㐲㙾䛻ᑠᆺCCDศගჾ䜢⿦╔䛧䛶ྍど䞉㏆㉥እᇦ䛾䝇䝨䜽䝖䝹ィ 䜢⾜䛖䛸䛸䜒䛻䚸⊃ᖏᇦ䝣䜱䝹䝍䜢ྲྀ䜚௜䛡䛯෭༷CCD䜹䝯䝷䛷⏬ീ䛸䛧䛶䛾᳜≀⺯ගᙉᗘศᕸ䜢㐲㝸ィྍ⬟䛷䛒䜛䚹ᐃ㔞ⓗ䛺ゎᯒ䜢⾜䛖┠ⓗ䛷䚸᳜≀䛸ྠ᫬䛻ⓑᯈ䛾⏬ീ䜢ྲྀᚓ䛧䚸䝇䝨䜽䝖䝹₇⟬䛻䜘䜚SIFᙉᗘ䜢ᑟฟ䛧䛶䛔䜛䚹2016ᖺ8᭶30᪥䡚9᭶2᪥䚸ி㒔኱Ꮫ㎰Ꮫ㒊䛾䝎䜲䝈ᅡሙ䛻䛚䛔䛶䚸㊥㞳15䡚30 m䛛䜙┤㐩ኴ㝧ගㄏ㉳䛻䜘䜛᳜≀⺯ග䝇䝨䜽䝖䝹ィ 䜢⾜䛳䛯䚹A stand-off system has been developed for observing solar-induced vegetation fluorescence on the䛆Abstract䛇 canopy level. The system collects optical signals using a telescope, leading to the spectral
measurement using a CCD spectrometer, as well as the two-dimensional measurement of thefluorescence intensity distribution by means of a cooled CCD camera. The spectrum of whiteboard
taken simultaneously with that of vegetation canopy is used as a reference to extract the fluorescenceintensity. We describe the application of this system to soybean and rice fields recently performed in
Kyoto. It is found that the present approach based on spectral shapes is useful for extracting weakfluorescence signals even under daylight conditions.

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GOSAT䛾䝣䞊䝸䜶ศගჾ䠄TANSO-FTS䠅䛾㓟⣲A䝞䞁䝗䛾䝇䝨䜽䝖䝹䝕䞊䝍䛛䜙䜽䝻䝻䝣䜱䝹⺯ග䛜᳨ฟ䛥䜜䚸ᆅୖィ 䛷䛾᳨ド䛜ᚲせ䛸䛺䛳䛶䛔䜛䚹ኴ㝧ගບ㉳⺯ග䠄Solar Radiation-Induced Fluorescence,
SRIF䠅ἲ䜢⏝䛔䛯CCDศගჾ䛻䜘䜛䜽䝻䝻䝣䜱䝹⺯ගᙉᗘ䝇䝨䜽䝖䝹ィ 䛚䜘䜃CCD䜹䝯䝷䛻䜘䜛஧ḟඖⓗ䛺䜽䝻䝻䝣䜱䝹⺯ග⏬ീゎᯒἲ䜢☜❧䛩䜛䛸䛸䜒䛻䚸⏕⫱ሙᡤ䛻䛚䛔䛶䛿᳜≀ⴥ䛾 SRIFἲ䛻䜘䜛ศග䝸䝰䞊䝖䝉䞁䝅䞁䜾ィ 䛚䜘䜃ኴ㝧ග䝇䝨䜽䝖䝹୰䛾ᬯ⥺䛻䜘䜛FLD (Fraunhofer Line-Discrimination)ἲ䜢⏝䛔䛯᳜≀⺯ගศᕸ⏬ീ䝅䝇䝔䝮䛾㛤Ⓨ䜢⾜䛖䚹㻌 ᡃ䚻䛿ᆅୖ䛷䛾䝸䝰䞊䝖䝉䞁䝅䞁䜾ィ 䛻䜘䜚䚸㔝እ䛾⩌ⴠ䝺䝧䝹䛷ά⏝ྍ⬟䛺ኴ㝧ගㄏ㉳䛾᳜≀⺯ග(solar-induced fluorescence, SIF) ィ ἲ䜢㛤Ⓨ䛧䛶䛔䜛䚹㻌㻌 2016ᖺ8᭶30᪥䡚9᭶2᪥䚸ி㒔኱Ꮫ㎰Ꮫ㒊䛾䝎䜲䝈ᅡሙ䛻䛚䛔䛶䚸㊥㞳15䡚30 m䛛䜙┤㐩ኴ㝧ගㄏ㉳䛻䜘䜛᳜≀⺯ග䝇䝨䜽䝖䝹ィ 䜢⾜䛳䛯䚹ᑐ㇟ရ✀䛿䚸䝣䜽䝴䝍䜹䛺䛹䛷䛒䜛䚹Fig. 1䛻䚸ほ 䛥䜜䛯⺯ගᙉᗘ䝇䝨䜽䝖䝹䜢♧䛩䚹䝇䝨䜽䝖䝹ィ 䛾≉ᚩ䜢฼⏝䛧䛯⺯ගᙉᗘ⟬ฟἲ䛸䛧䛶䚸ᒇእ䛷ྠ᫬䛻ほ 䛧䛯ⓑᯈ䛾཯ᑕග䝇䝨䜽䝖䝹䜢᳜≀ⴥ䛛䜙䛾཯ᑕ䞉⺯ග䝇䝨䜽䝖䝹䛸ẚ
㍑䛩䜛䚹825 nm䜘䜚㛗Ἴ㛗ഃ䛷䛿᳜≀⺯ග䛜↓ど䛷䛝䜛䛾䛷䚸䛣䛾Ἴ㛗ᇦ䛷᳜⏕䛾┦ᑐ཯ᑕ⋡䜢᥎ᐃ䛧䚸750
䡚800 nm䛻䛚䛔䛶ᐇ 䛸䛾ᕪศ䛛䜙⺯ග䝇䝨䜽䝖䝹䜢⟬ฟ䛩䜛䚹
Fig. 2䛻䚸ኴ㝧ගㄏ㉳䛻䜘䜛䜽䝻䝻䝣䜱䝹⺯ගศග⏬ീ䜢♧䛩䚹CCD䜹䝯䝷䛻䜘䜛ィ 䛾ሙྜ䚸㓟⣲A䝞䞁䝗䛻┦ᙜ䛩䜛୰ᚰἼ㛗760.68 nm䚸㏱㐣ᖜ䛜 1 nm䛾⊃ᖏᇦ䝣䜱䝹䝍䞊 (F760) 䜢⏝䛔䚸⏬ീ䛾ྑ༙ศ䛻䛿ⓑᯈ䜢ྠ᫬䛻᧜ᙳ䛧䚸ⓑᯈ䛾ᙉᗘ䛻᳜≀ⴥ䛾┦ᑐ཯ᑕ⋡䠄䝇䝨䜽䝖䝹ィ 䛻䜘䜛್䠅䜢᥃䛡䛯ᩘ್䜢᳜≀ⴥ䛾཯ᑕᙉᗘ䛸䛧䛶ᕪ䛧ᘬ䛟䛣䛸䛷⺯ගᙉᗘ䜢ぢ✚䜒䛳䛯䚹

Fig.1 Proposed method based on relative reflectance.

Fig. 2 Soybean field imagery:(a) original
intensity image and (b) fluorescence intensity
calculated by subtracting the reference spectra.

㎰ᴗࡸᯘᴗ࡛ά⏝ࡋࡸࡍ࠸ࡼ࠺ࠊ㊥㞳10㹼100m⛬ᗘ࠿ࡽ⩌ⴠ࡛࣋ࣝࡢ⺯ගほ ࡀྍ⬟࡞ࢩࢫࢸ࣒ࢆ
㛤Ⓨࢆ┠ⓗ࡜ࡋ࡚࠸ࡿࠋᅡሙ࣭᳃ᯘ࡟࠾࠸࡚ࠊගྜᡂ ᐃჾ㸦Li-6400㸧࣭⇕⏬ീ࣓࢝ࣛ࡜⺯ග࣮ࣜࣔࢺࢭࣥࢩࣥࢢィ ࡢඹྠほ ࢆ⾜ࡗࡓࠋලయⓗ࡟ࡣࠊி㒔኱Ꮫ㎰Ꮫ◊✲⛉䛾ᅡሙ䛻䛚䛔䛶䚸䜲䝛䞉䝎
䜲䝈䜢15䡚30 m䛾㊥㞳䛛䜙ኴ㝧ගບ㉳⺯ගἲ䛻䜘䜛䜽䝻䝻䝣䜱䝹⺯ග䝇䝨䜽䝖䝹ィ 䜢⾜䛳䛯䚹䜎䛯䚸᳃ᯘ⥲ྜ◊✲ᡤ䛾ᒣᇛ䝃䜲䝖䛻䛚䛔䛶䚸᳃ᯘ (䝁䝘䝷) 䛾ኴ㝧ගບ㉳⺯ගἲ䛻䜘䜛⺯ගศග⏬ീィ 䜢⾜䛳䛯䚹― 76 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-35䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅䜹䝯䝷䜢⏝䛔䛯ⅆᫍ⾲ᒙ⎔ቃほ 䛾᳨ウ㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅 Camera observation of Martian surface environment䠄◊✲௦⾲⪅ྡ䠅 ༓⛅㻌 ༤⣖㻌 䠄༓ⴥᕤᴗ኱Ꮫ䞉ᝨᫍ᥈ᰝ◊✲䝉䞁䝍䞊䠅
Hiroki Senshu 㻌 䠄Chiba Institute of Technology 䞉PERC䠅䛆せ᪨䛇ᑗ᮶䛾ⅆᫍ╔㝣᥈ᰝ䛻䛚䛔䛶䠈┤㐩䞉ᩓ஘ኴ㝧ග䝇䝨䜽䝖䝹䛾ほ 䛛䜙኱Ẽ୰䛾䝎䝇䝖䛾⤌ᡂ䜔䝃䜲䝈ศᕸ䠈㖄┤ศᕸ䛸䛔䛳䛯䝎䝇䝖≉ᛶ䜢ồ䜑䜛䛣䛸䜢┠ᶆ䛸䛧䛶䛔䜛䠊䛭䛾䛯䜑䛻䜎䛪ᮏ◊✲䛷䛿䠈䝎䝇䝖≉ᛶ䛜ኴ㝧ග䝇䝨䜽䝖䝹䛻୚䛘䜛ᙳ㡪䜢ᩘ್ⓗ䛻ゎᯒ䛧䛯䠊䛣䛾⤖ᯝ䛿䠈せồ䛥䜜䜛䝎䝇䝖≉ᛶ䛾 ᐃ⢭ᗘ䛻ᇶ䛵䛔䛶䜹䝯䝷䛾䝇䝨䝑䜽䜢Ỵ䜑䜛㝿䛻ᚲせ䛺ᇶ♏䝕䞊䝍䛸䛺䜛䠊䛆Abstract䛇 Direct and scattered solar radiation spectra at the surface of Mars depend on the existence of dust
particles in the atmosphere. We simulated solar spectra at the surface of Mars as a function of dust
model parameters and estimated the errors in the retrieved dust model parameters. Our result canbe used as a reference to develop a camera onboard a Mars lander in future Mars missions.

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Ỉ䜔᳜⏕䛜䛺䛔ⅆᫍ䛷䛿䠈䝎䝇䝖䛿ᒾ▼໬䜔ᅵተ໬䛥䜜䜛䛣䛸䛺䛟䠈⾲ᒙ⎔ቃ䛻⵳✚䛥䜜⥆䛡䜛䚹䛭䛾⤖ᯝ䠈ⅆᫍ䛾኱Ẽ䛻䛿䠈ᆅ⌫䛸䛿␗䛺䜚䠈ᅛయ䛾ᑠ∦䛛䜙䛺䜛䝎䝇䝖䛜ᾋ㐟䛧䛶䛚䜚䠈኱Ẽ䛾ᨺᑕ ᗘᵓ㐀䜢ᨭ㓄䛧䛶䛔䜛䚹䛧䛛䛧ⅆᫍ኱Ẽ୰䛾䝎䝇䝖䛾䝃䜲䝈ศᕸ䜔㔞䠈䛭䛾⤖ᯝỴ䜎䜛⾲ᒙ䛾ᨺᑕ⎔ቃ䛻䛴䛔䛶䛿䠈ከ䛟䛾୙☜ᐃᛶ䛜ṧ䛥䜜䛶䛔䜛䚹ᚑ᮶䛾ほ 䛜኱Ẽᵓ㐀䛾ゎ᫂䜢୺┠ⓗ䛸䛧䛶䛔䛺䛔䛣䛸䠈䜎䛯ⅆᫍ኱Ẽ䛾䝰䝕䝹䛜㐣ᗘ䛻」㞧䛷ほ 䝕䞊䝍䛸䛾ᑐẚ䛜ᐜ᫆䛷䛿䛺䛔䛣䛸䛜ཎᅉ䛷䛒䜛䠊䛭䛣䛷ᮏ◊✲䛷䛿䠈䛣䜜䜎䛷䛾ᆅ⌫ほ 䛷ᚓ䜙䜜䛯▱ぢ䜢㋃䜎䛘䠈ᚲせ᭱ᑠ㝈䛾ⅆᫍ䛾ᨺᑕሙ䛾䝰䝕䝹䜢ᵓ⠏䛩䜛䛣䛸䠈䛣䛾䝰䝕䝹䜢䜒䛸䛻⌧ᐇⓗ䛺ⅆᫍ᥈ᰝィ⏬䠄ほ ィ⏬䠅䜢❧᱌䛩䜛䛣䛸䜢┠ⓗ䛸䛩䜛䚹䠄䠍䠅ᮏ◊✲䛷ᥦ᱌䛩䜛䝰䝕䝹䛷䛿䠈䝎䝇䝖䜢グ㏙䛩䜛䝟䝷䝯䝍䜢ྑ⾲䛻䛒䜛䠓䛴䛻⤠䛳䛯䠊䛣䜜䜙䛾䝟䝷䝯䝍䜢฼⏝䛩䜛䛸䝎䝇䝖䛾⤌ᡂ䜔䝃䜲䝈ศᕸ䠈㖄┤ศᕸ䜢⾲⌧䛷䛝䜛䠊୍᪉ⅆᫍ⾲㠃䛛䜙䛾䜹䝯䝷ほ 䛷䛿䠈3䛴䛾Ἴ㛗䛸4䛴䛾ኴ㝧㞳ゅ䜢᝿ᐃ䛧䛯䠊䠄䠎䠅䝟䝷䝯䝍䜢ኚ໬䛥䛫䜛䛸䠈᝿ᐃ䛩䜛ほ 㔞䛜䛹䛾䜘䛖䛺ᙳ㡪䜢ཷ䛡䜛䛾䛛䛻䛴䛔䛶䠈ᨺᑕఏ㐩䝁䞊䝗䠄MODTRAN5䠅䜢฼⏝䛧䛯ᩘ್䝅䝭䝳䝺䞊䝅䝵䞁䛻䜘䛳䛶ぢ✚䜒䛳䛯䠊䛭䛾⤖ᯝ䛭䜜䛮䜜䛾ほ 㔞䛜䛹䛾䝎䝇䝖䝰䝕䝹䝟䝷䝯䝍䛻ឤᗘ䛜䛒䜛䛾䛛䛜᫂䜙䛛䛻䛺䛳䛯䠊

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ᐇຠศᩓߩ஺䝦䝬䝍䜲䝖䛾య✚ΰྜ⋡݉଴䜿䜲㓟ሷ䛾」⣲ᒅᢡ⋡ᐇ㒊݇଴䜿䜲㓟ሷ䛾」⣲ᒅᢡ⋡⹫㒊‫ݖ‬௦䝇䜿䞊䝹䝝䜲䝖
䠄䠏䠅䛣䜜䜙䛾⤖ᯝ䜢䜎䛸䜑䜛䛸䠈ᡃ䚻䛜᝿ᐃ䛧䛯ほ ᑐ㇟䠄Ἴ㛗䛸ኴ㝧㞳ゅ䛾⤌䜏ྜ䜟䛫䠅䛾್䜢⤌䜏ྜ䜟䛫䜛䛣䛸䛻䜘䛳䛶䠈ⅆᫍ኱Ẽ䛻ྵ䜎䜜䜛䝎䝇䝖䛾⤌ᡂ䜔䝃䜲䝈ศᕸ䠈㖄┤ศᕸ䜢ᐃ㔞ⓗ䛻ồ䜑䜛䛣䛸䛜䛷䛝䜛஦䛜ᐇド䛷䛝䛯䠊䛥䜙䛻䠈ほ ್䛾⢭ᗘ䛜䝸䝖䝸䞊䝞䝹䛷ᚓ䜙䜜䜛䝟䝷䝯䝍䛾⢭ᗘ䛻䛹䛾䜘䛖䛻ఏ᧛䛩䜛䛾䛛䜒ᐃ㔞ⓗ䛻♧䛧䛯䠊䛣䛾⤖ᯝ䜢฼⏝䛩䜛䛸䠈௒ᚋ䛾ⅆᫍ╔㝣᥈ᰝ䛻䛚䛔䛶䠈ᨺᑕሙ䜢 ᐃ䛩䜛䜹䝯䝷䛻ồ䜑䜙䜜䜛ほ ⢭ᗘ䛜ぢ✚䜒䜙䜜䜛䠄ồ䜑䛯䛔ほ ⢭ᗘ䛾㛵ᩘ䛸䛧䛶䠅䠊㟁ຊ䜔㔜㔞䞉䝕䞊䝍㔞䛺䛹䛾䝸䝋䞊䝇䛜㠀ᖖ䛻㝈䜙䜜䜛ᝨᫍ᥈ᰝ䛻䛚䛔䛶䠈ほ ⢭ᗘ䛸⿦⨨タィ䛾⢭ᗘ䜢┤᥋㛵ಀ䛵䛡䛯䛾䛿䠈ᮏ◊✲䛜ึ䜑䛶䛾౛䛻䛺䜛䠊

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ᮏ◊✲䛾ᡂᯝ䛿Ꮫ⾡ㄽᩥ䛸䛧䛶䜎䛸䜑䠈Progress in Earth and Planetary Science (PEPS) 䛻ᢞ✏䛧䛯䠄Manago, N, K. Noguchi, G. L. Hashimoto, H. Senshu, N. Otobe, M. Suzuki, and H. Kuze, Feasibilityof retrieving dust properties and total column water vapor from solr spectra measured with a lander
camera on Mars䠅. ㄽᩥ䛿2017ᖺ3᭶17᪥⌧ᅾ䠈䝸䝞䜲䝈୰䛷䛒䜛䠊― 77 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-39䛇䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅ከ᪉ྥほ 䝕䞊䝍䜢⏝䛔䛯㔪ⴥᶞᯘ䞉ᗈⴥᶞᯘ䛾ศ㢮᪉ἲ䛾㛤Ⓨ䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Development of classification method for forest types using multi-angle observation data䠄◊✲௦⾲⪅ྡ䠅 ᭮ᒣ㻌 ඾Ꮚ㻌 䠄ኳ⌮኱Ꮫ䞉ே㛫Ꮫ㒊䠅
Noriko Soyama 㻌 䠄Tenri University 䞉Faculty of Human Studies䠅䛆せ᪨䛇 㻌 ඲⌫ᅵᆅ⿕そศ㢮䜰䝹䝂䝸䝈䝮䛻䛚䛔䛶䚸㔪ⴥᶞᯘ䛸ᗈⴥᶞᯘ䛾ศ㢮⢭ᗘ䛾ྥୖ䛜ồ䜑䜙䜜䛶䛔䜛䚹ᮏ◊✲䛷䛿䚸ከ᪉ྥྠ᫬ほ 䝕䞊䝍䛷䛿䛺䛔⾨ᫍ䝕䞊䝍䜢౑⏝䛧䛶␲ఝⓗ䛻ከ᪉ྥ䝕䞊䝍䜢సᡂ䛧䚸㔪ⴥᶞᯘ䛸ᗈⴥᶞᯘ䛾᳜⏕䝺䝇䝫䞁䝇䜢ㄪ䜉䛯䚹䛭䛾⤖ᯝ䚸཯ᑕ⋡䛿┦ᑐ᪉఩ゅ䛸ኴ㝧ኳ㡬ゅ䛻౫Ꮡ䛧䛶䛔䜛䛣䛸䛜䜟䛛䛳䛯䚹㔪ⴥᶞᯘ䛸ᗈⴥᶞᯘ䛾≉ᚩ䜢ㄪ䜉䜛䛯䜑䚸ゅᗘ౫Ꮡ䛾ᙳ㡪䛜ᑠ䛥䛔䝕䞊䝍䜢ᢳฟ䛧ㄪ䜉䛯⤖ᯝ䚸᳃ᯘ䝍䜲䝥ู䛾≉ᚩᕪ␗䛿᫂䜙䛛䛻䛷䛝䛺䛛䛳䛯䛜䚸᳃ᯘcanopy䛾⾲㠃≉ᚩ䛿Nadir䛸Slant䛾ẚ䛻ฟ䜛䛣䛸䛜䜟䛛䛳䛯䚹
Forest information of global land-cover data is important for global environmental studies. However, it isdifficult to correctly classify needle-leaves forest and broad-leaves forest using only phenology information
䛆Abstract䛇 extracted from nadir-view observation data. We attempt to differentiate needle-leaves and broad-leaves
forests using MOD09GA and MYD09GA. We find that NDVI and CIgreen change depending on the solar
zenith and relative azimuth. Using data in limited ranges of solar zenith and relative azimuth, it is notpossible to clearly show differences between the characteristics of needle-leaves forest and broad-leaves
forest from pseudo multidirectional observation data. However, we find differences for both NDVI and
CIgreen between nadir and slant data depending on the surface state of the forest.

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㻌 ඲⌫ᅵᆅ⿕そศ㢮䛻䛚䛔䛶䚸඲⌫䛻༨䜑䜛๭ྜ䛜኱䛝䛔᳃ᯘ䛻䛴䛔䛶䚸᳜⏕ᶵ⬟䝍䜲䝥ูศ㢮䛾⢭ᗘ䜢ୖ䛢䜛ᚲせ䛜䛒䜛䚹㔪ⴥᶞᯘ䛸ᗈⴥᶞᯘ䛾ศ㢮䛿䚸┤ୗど䛻䜘䜛ほ 䝕䞊䝍䜢౑䛳䛶ᢳฟ䛩䜛䝣䜵䝜䝻䝆䞊᝟ሗ䛰䛡䛷䛿㝈⏺䛜䛒䜛䛣䛸䛜䜟䛛䛳䛶䛔䜛䚹㏆ᖺ䚸ከ᪉ྥほ ᶵ⬟䜢ᣢ䛳䛯䝉䞁䝃䛾䝕䞊䝍䜢⏝䛔䛯᳃ᯘ䛾≉ᚩゎᯒ䛾◊✲䛜⾜䜟䜜䛶䛔䜛䚹ᮏ◊✲䛷䛿䚸ከ᪉ྥほ 䝉䞁䝃䞊䛾๓᪉ど䛸ᚋ᪉ど䝕䞊䝍䜢౑⏝䛧䛶㔪ⴥᶞᯘ䛸ᗈⴥᶞᯘ䛾ᶞෙᙧ≧䛾ᕪ␗䜢ᢳฟ䛩䜛᪉ἲ䜢㛤Ⓨ䛧䚸᳃ᯘ䜽䝷䝇ศ㢮䛾⢭ᗘ䜢䛒䛢䜛䛣䛸䜢┠ⓗ䛸䛩䜛䚹௒ᖺᗘ䛿Terra&Aqua/ MODIS䝕䞊䝍䝉䝑䝖(MOD09GA,MYD09GA)䜢౑⏝䛧䚸ኴ㝧䛸䝉䞁䝃䞊䛾ኳ㡬ゅ䚸䛚䜘䜃᪉఩ゅ䛤䛸䛻᳃ᯘ䝍䜲䝥ู䛻≉ᚩ䜢ㄪ䜉䛯䚹

䠄䠍䠅 2010ᖺMOD09GA,MYD09GA䝕䞊䝍䝉䝑䝖䛛䜙䚸sensor zenith䛜0㼻ࠥ10㼻䛾䝅䞊䞁䜢Nadir data䛸䛧䚸
45㼻ࠥ55㼻䛾䝅䞊䞁䜢Slant data䛸䛧䛶␲ఝⓗከ᪉ྥ䝕䞊䝍䝉䝑䝖䜢సᡂ䛧䚸ẚ㍑ⓗᖹᆠ䛺ᆅ⾲㠃䛻䛒䜛᳃ᯘ䝃䜲䝖䛾཯ᑕ⋡䝕䞊䝍䛾ゎᯒ䜢⾜䛳䛯䚹䛭䛾⤖ᯝ䚸Nadir data, Slant data䛸䜒䛻relative azimuth䛜90㼻
䛻㏆䛔䜋䛹཯ᑕ⋡䛿ୗ䛜䜚䚸solar zenith䛜㧗䛟䛺䜛䜋䛹཯ᑕ⋡䛜ୗ䛜䜛䛣䛸䛜䜟䛛䛳䛯䚹䠄䠎䠅㔪ⴥᶞᯘ䛸ᗈⴥᶞᯘ䛾≉ᚩ䜢ㄪ䜉䜛䛯䜑䚸solar zenith<30㼻䛛䛴䚸Nadir䛸Slant䛾relative azimuth䛾ᕪ䛜20㼻௨ୗ䛾཯ᑕ⋡䛾䜏䜢౑⏝䛧䚸NDVI(Normalized difference vegetation index)䛸CIgreen(the green
chlorophyll index)䜢ィ⟬䛧䚸≉ᚩᕪ␗䜢ㄪ䜉䛯䚹䛭䛾⤖ᯝ䚸ᗈⴥᶞᯘ䛾᪉䛜㔪ⴥᶞᯘ䜘䜚䚸Nadir䜘䜚Slant䛾䝕䞊䝍䛾᪉䛜್䛾䜀䜙䛴䛝䛜኱䛝䛔䛣䛸䛜䜟䛛䛳䛯䚹䠄䠏䠅䛥䜙䛻䝃䞁䝥䝹䝃䜲䝖䛤䛸䛻Nadir䛸Slant䛾㛵ಀ䜢ㄪ䜉䛯⤖ᯝ䚸⮬↛ಖㆤ༊ෆ䛾ᐦ䛺ⴠⴥᗈⴥᶞᯘ䝃䜲䝖(୺䛻oak䠅䛸ᶞ㱋400ࠥ500ᖺ䛾ᐦ䛺㔪ⴥᶞᯘ䝃䜲䝖(୺䛻old western hemlock, pacific yew,
and douglas-fir trees)䛿䚸Slant䛾䠲䠥್䛜Nadir䛾䠲䠥್䜘䜚㧗䛔䛣䛸䛜䜟䛛䛳䛯䠄ᅗ䠍䠅䚹㻌 㔪ⴥᶞᯘ䛾canopy䛾ᙧ≧䛿ୖ䛛䜙ぢ䛯᫬䚸ᗈⴥᶞᯘ䜘䜚พฝ䛾ᙧ≧䜢⾲䛩䛸⪃䛘䜙䜜䜛䚹䛧䛛䛧ᶞ㱋䛜㛗䛔ᮌ䛿ᯞ䛜኱䛝䛟ᗈ䛜䛳䛯ᙧ䛻䛺䜛䛣䛸䛜ከ䛟䚸ୖ䛛䜙ᶞᯘᖏ䜢ぢ䛯䛸䛝䚸䛭䛾ᙧ≧䛜ᐦ䛺ᗈⴥᶞᯘ䛸㢮ఝ䛧䛶
Relationship between
ᅗ1nadir and slant NDVI,䛚䜚䚸䛺䜑䜙䛛䛻䛺䜛䛣䛸䛜▱䜙䜜䛶䛔䜛䚹ᅗ䠍䛾⤖ᯝ䛿䛣䜜䜢♧䛧䛶䛔䜛
combining needle-leaves䛸⪃䛘䜙䜜䜛䚹
forest and broad-leaves
forest data.

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௒ᖺᗘ䛿䚸ከ᪉ྥྠ᫬ほ 䝕䞊䝍䛷䛿䛺䛔⾨ᫍ䝕䞊䝍䛾」ᩘ䛾䝅䞊䞁䜢౑䛔䚸␲ఝⓗ䛻ከ᪉ྥほ 䝕䞊䝍䜢సᡂ䛧䛶䚸㔪ⴥᶞᯘ䛸ᗈⴥᶞᯘ䛾≉ᚩゎᯒ䜢⾜䛳䛯䛰䛡䛷䛒䜚䚸᳃ᯘ䝍䜲䝥䛾ศ㢮䜰䝹䝂䝸䝈䝮䜈䛾㐺⏝䜎䛷⮳䜙䛺䛛䛳䛯䚹― 78 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-40䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅↓ேᑠᆺ㣕⾜యᦚ㍕⏝LED䝭䝙䝷䜲䝎䞊䛻䜘䜛㔝እ䝎䝇䝖ᣲືほ㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Dust flow monitoring at outdoor by LED mini-lidar for micro air vehicle䠄◊✲௦⾲⪅ྡ䠅 ᳝ྡ㻌 㐩㞝㻌 䠄༓ⴥ኱Ꮫ䞉኱Ꮫ㝔⼥ྜ⛉Ꮫ◊✲⛉䠅
Tatsuo Shiina 䠄Chiba University 䞉Graduate School of Advanced Integration Science 䠅䛆せ᪨䛇㻌 ᮏ◊✲䛷䛿H26-27䛾ඹྠ฼⏝䛻䛶䚸↓ேᑠᆺ㣕⾜య䠄Micro Air Vehicle ௨ୗ㻌 MAV䠅䜈ᦚ㍕ྍ⬟䛺䚸ᑠᆺ䚸
㍍㔞䚸పᾘ㈝㟁ຊ䛾LED䝭䝙䝷䜲䝎䞊䛾㛤Ⓨ䜢⾜䛳䛯䚹᫖ᖺᗘ䛾ᡂᯝ䛸䛧䛶䚸10cm䜻䝳䞊䝤LED䝭䝙䝷䜲䝎䞊䛻䛶ᐊෆ↷᫂ୗ䛷䛾㢼Ὕᐇ㦂䛻䛚䛔䛶䝎䝇䝖䛾ᣲື䜢ᤊ䛘䜛䛣䛸䛻ᡂຌ䛧䛶䛔䜛䚹ᮏ⏦ㄳ䛷䛿㛤Ⓨ䛧䛯LED䝭䝙䝷䜲䝎䞊䜢ᨵⰋ䛧㏞ග䜢పῶ䛥䛫䛶䚸㔝እ䛷䛾䝎䝇䝖ィ 䜢ᐇ⌧䛩䜛䚹䜎䛯䚸䝷䜲䝎䞊⿦⨨䛻䠏ḟඖຍ㏿ᗘ䝉䞁䝃䜢ᦚ㍕䛧䚸ほ ග㍈᪉ྥ䛸ጼໃไᚚ䛛䜙MAV䜈䛾タ⨨䜢᳨ウ䛩䜛䚹䛆Abstract䛇 In this study, compact, light weight, and low power consumption LED mini-lidar was developed for Micro
Air Vehicle. From our past achievements, the optical setup was accomplished 10cm cube size, andobserved the smoke activities in large wind tunnel. In this year, the developed lidar was improved toreduce the tray-light and the actual dust flow was captured at outdoor. We also considered to install the 3dimentional accelerator sensor into the mini-lidar to get the aiming direction and the attitude control on
MAV.

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ᮏ⏦ㄳ䛷䛿H26-27䛾ඹྠ฼⏝䛻䛶㛤Ⓨ䛧䛯LED䝭䝙䝷䜲䝎䞊(Version1)䜢ᨵⰋ䛧㏞ග䜢పῶ䛥䛫䛶, 㔝እ䛷3䛾䝎䝇䝖ィ 䜢ᐇ⌧䛩䜛䛣䛸䜢┠ⓗ䛸䛧䛶䛔䜛. ᫖ᖺ〇స䛧䛯10cm 䝭䝙䝷䜲䝎䞊䜢ᨵⰋ䛧, ㏦ಙගຠ⋡䜢ྥୖ䛧, 䛛䛴, ཷಙගᏛ⣔䛾㏞ග䜢పῶ䛥䛫䜛䛯䜑䛾ᕤኵ䜢᪋䛧䛯. 䛭䛾⤖ᯝ䛸䛧䛶, 䠏䠌m䜎䛷䛾኱Ẽ䜶䜰䝻䝌䝹3
䛾ᣲື䜢20s䛾✚⟬䛷ᤊ䛘䜙䜜䜛䜘䛖䛻䛺䛳䛯. ᮏ◊✲䛷䛿䛣䛾ᨵⰋ䛧䛯10cm 䝭䝙䝷䜲䝎䞊(Version2)䜢⏝䛔䚸㔝እ䛷ᐇ䝎䝇䝖ィ 䜢⾜䛳䛯. 㢼䛸䝎䝇䝖䛾┦㛵䜢ぢ䜛䛣䛸䛿䜒䛱䜝䜣, 䝎䝇䝖⮬య䛾ᣑᩓ䜔ᑐὶ䛸䛔䛳䛯ᣲື䜢ᤊ䛘䜛䛣䛸䛜┠ⓗ䛷䛒䜛. MAVᦚ㍕䛾䛯䜑䛾, ほ ග㍈᪉ྥ䛸ጼໃไᚚ䛾䛯䜑䛾䝉䞁䝃䛾ᑟධ䜢᳨ウ䛧䛶䛔䜛.
3䠄䠍䠅䝷䜲䝎䞊ᵓᡂ䛿10cm 䛾኱䛝䛥䛷, ග※䛻䛿385nm䛾▷Ἴ㛗䛷㧗ฟຊ(1W[MAX])䛾䝟䝽䞊LED䜢⏝䛔䛯䠊10ns䛾▷䛔㏦ಙ䝟䝹䝇ᖜ䛷䠈⧞䜚㏉䛧࿘Ἴᩘ䛿500kHz䛷㏦ಙ䛩䜛䠊㏦ಙගཱྀᚄ䛿30mm䠈䝡䞊䝮ᗈ䛜䜚ゅ䛿67mrad.䛷䛒䛳䛯䠊ཷಙගᏛ⣔䛻䛿ᑓ⏝䛾䜹䝉䜽䜧䝺䞁ᘧ䜢タィ䛧䛯䠊ཷಙど㔝ゅ䛿 3mrad.䛷䛒䜚䠈ᗈ䛔㏦ಙගᗈ䛛䜧䜚䛸⊃䛔ཷಙど㔝䛻䜘䜚䠈ග㍈ㄪᩚ䜢ᐜ᫆䛻䛧䛶䛔䜛䠊ヨసᶵ䛷䛿䝷䜲䝍䜧䞊⿦⨨䛾⣲ᮦ䛻㍍䛔ሷ໬䝡䝙䞊䝹ᶞ⬡䜢⏝䛔䜛஦䛷㍍㔞໬䜢ᅗ䜚䠈⥲㉁㔞䛿⣙800g(䝞䝑䝔䝸㎸䜏䛷 1kg)䛷䛒䛳䛯䠄ᅗ䠍䠅䠊ᑓ⏝䛾㧗㏿㧗ศゎ䝩䝖䞁䜹䜴䞁䝍䜒〇స䛧䛶䛔䜛䠊䠄䠎䠅ᆅୖᐇドᐇ㦂䛷䛿, ༓ⴥᕷ䛾✄ẟᾏᓊ䛷ᐇ䝎䝇䝖䛾ᣲືほᐹ䜢⾜䛳䛯. 䛣䛾ほ 䛷䛿㢼䛻䜘䛳䛶ᾋ㐟䛧䛯◁ሻ䛾ᵝᏊ䜢ᤊ䛘䜛䛣䛸䛻ᡂຌ䛧䛯(ᅗ2)䠊⢊ሻィ䛸䛾┦㛵䛜㧗䛔䛣䛸䛜䜏䛶䛸䜜䜛. 㢼ྥ㢼㏿䛸䛔䛳䛯Ẽ㇟䝉䞁䝃䚸⢊ሻィ➼䛸䛾ྠ᫬ィ 䛻䜘䜚䠈䝷䜲䝎䞊䝎䝇䝖䜶䝁䞊 ᐃ್䛾ᐃ㔞໬䛻ྥ䛡䛯ゎᯒ䜢⾜䛳䛶䛔䜛. ⌧ᅾ, 䠏ḟඖຍ㏿ᗘ䝉䞁䝃䜢ᦚ㍕䛧䛶,
ほ ග㍈᪉ྥ䛸ጼໃไᚚ䛛䜙MAV䜈䛾タ⨨䜢᳨ウ䛧䛶䛔䜛.

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

Version 1
ᅗ1

Version 2

10cm3 LED䝭䝙䝷䜲䝎䞊ᅗ2 ᐇ䝎䝇䝖ほ ⤖ᯝ : 18:34-18:39 6th Dec,
2016

㛤Ⓨ䛧䛯⿦⨨䛿, MAV䜈䛾ᦚ㍕䛾䜋䛛, ⅆᫍ⏝䝻䞊䝞䜈䛾ᦚ㍕䛯䜑䛾◊✲䛻⏝䛔䜙䜜䛶䛔䜛.
㛤Ⓨ䛧䛯ᡭἲ䛿, ᵝ䚻䛺Ẽ㇟䝉䞁䝃䛸䛾┦㛵䜢ぢ䛶, ᾋ㐟䝎䝇䝖䛾ᣲືゎᯒ䜈䛸㐍ᒎ䛧䛶䛔䜛.

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CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-41䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅㏆㊥㞳䝷䜲䝎䞊䛻䜘䜛ᆅ⾲㠃኱Ẽィ 䝕䞊䝍䛛䜙䛾᝟ሗᢳฟ㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Information Extraction from Ground Atmospheric Data㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 Measured by Short Distance Lidar䠄◊✲௦⾲⪅ྡ䠅 ᳃ ᗣஂோ㻌 䠄༓ⴥ኱Ꮫ኱Ꮫ㝔䞉⼥ྜ⛉Ꮫ◊✲⛉䠅Yasukuni Mori 䠄Chiba University䞉Graduate School of Advanced Integration Science䠅䛆せ᪨䛇䝷䜲䝎䞊䝕䞊䝍䛾䜘䛖䛺኱Ẽ䞉䝎䝇䝖䛾ศᕸィ 䛻䛚䛔䛶䠈䛭䛾ὶ䜜䜢ᢳฟ䛩䜛䛣䛸䛷㢼䜔௜㝶䛩䜛኱Ẽ≧ែ䛾᝟ሗ䜢ᚓ䜛䛣䛸䛿㠀ᖖ䛻᭷┈䛷䛒䜛䠊୍᪉䛷䠈㏆㊥㞳ཬ䜃ᆅ⾲㠃䛾኱Ẽ䛾ᣲື䛿㢼䛾䜏䛷Ỵ䜎䜛䛾䛷䛿䛺䛟䠈ᆅᙧ䜔䛭䛾⣲ᛶ䛻ᙉ䛟౫Ꮡ䛩䜛䠊䛭䛣䛷䠈ᮏ◊✲䛾┠ⓗ䛿䠈㏆㊥㞳ィ ⏝䝭䝙䝷䜲䝎䞊䛻䜘䜚ィ 䛧䛯ᆅ⾲㠃኱Ẽ䛛䜙䛾䜶䝁䞊Ἴᙧ䜢⏬ീ䛸䛧䛶ྍど໬䛧䠈䛭䛾≉ᛶ䜢ᶵᲔᏛ⩦䜔ಙྕฎ⌮䛾ᢏ⾡䜢⏝䛔䛶ゎᯒ䛩䜛䛣䛸䛷䠈ィ䝕䞊䝍䛛䜙䛾᝟ሗᢳฟ䜢ྍ⬟䛸䛩䜛䜰䝹䝂䝸䝈䝮䜢᳨ウ䛩䜛䛣䛸䛷䛒䜛䠊䛆Abstract䛇 In the atmospheric or dust measurements such as lidar data, it is so effective to obtain theinformation of the atmospheric and wind condition by extracting these flows. On the other hand, thebehavior of short distance and ground atmosphere are greatly affected by not just wind but also
landform. The aim of this study is to visualize the echoes by lidar and to analyze the characteristics
using the techniques of machine learning and signal processing.

䠍
⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

䠏

ᾏὒἼᾉ䛾ᙧ䛿Ỉ୰䛾ὶ䜜䛸Ỉ῝䛻ຍ䛘䠈㢼䛾ື䛝䛻኱䛝䛟ᙳ㡪䜢ཷ䛡䛶䛔䜛䠊䛭䛣䛷ᮏ◊✲䛿ᾏὒἼᾉ䛾ィ 䜢┠ⓗ䛸䛧䛶㛤Ⓨ䛧䛯LED䝷䜲䝎䞊䛻䜘䜚䠈㝣ୖ䛛䜙పゅ䛷኱Ẽ䛾≧ែ䛸ඹ䛻ᾏὒἼᾉἼᙧ䜢ィ 䛧䠈Ἴ䛾᝟ሗ䛾ᢳฟ䛚䜘䜃኱Ẽ䛾≧ែ䛸䛾㛵㐃䜢ゎᯒ䛩䜛᪉ἲ䜢᳨ウ䛩䜛䠊ᮏ◊✲䛷䛿ィ 䝕䞊䝍䛛䜙ᵝ䚻䛺䝜䜲䝈䜔ᚋ᪉ᩓ஘ග௨እ䛾ග䛺䛹䛾ᡂศ䜢ಙྕฎ⌮䛾ᡭἲ䜢⏝䛔䛶㝖ཤ䛩䜛䛣䛸䛻䜘䜚䠈Ἴᾉ㒊ศ䛸ᆅ⾲㠃䛾኱Ẽ䛾ᣲື䜢⾲䛧䛶䛔䜛㒊ศ䛾䜹䜴䞁䝖್䜢䠎ḟඖ᝟ሗ䛸䛧䛶ྍど໬䛧䛯䠊䜎䛯䠈㊥㞳ẖ䛾ྛィ ᫬⣔ิ䝕䞊䝍䜢䝣䞊䝸䜶ゎᯒ䛩䜛䛣䛸䛷䠈㊥㞳ẖ䛾࿘Ἴᩘ᝟ሗ䜒ྲྀᚓ䛩䜛䠊䠄䠍䠅䝷䜲䝎䞊䛛䜙䛾䜶䝁䞊䜢ᅗ䠍䛾䜘䛖䛻ᶓ㍈䜢᫬㛫䠈⦪㍈䜢䝷䜲䝎䞊䛛䜙䛾㊥㞳䛸䛧䛶䝠䞊䝖䝬䝑䝥䛻䜘䜚ྍど໬䛩䜛䛣䛸䛷䠈Ἴ䛾ᣲື䛸㝣ୖཬ䜃ᾏୖ⾲㠃䛾≧ែ䜢ྠ᫬䛻ほ䜛䛣䛸䛜ྍ⬟䛸䛺䛳䛯䠊䠄䠎䠅㊥㞳ศゎ⬟ẖ䛾᫬⣔ิ䝕䞊䝍䛻ᑐ䛧䛶䝣䞊䝸䜶ኚ᥮䛧䛯⤖ᯝ䜢ྠᵝ䛻䝠䞊䝖䝬䝑䝥䛸䛧䛶ྍど໬䛩䜛䛣䛸䜢᳨ウ䛧䛯䠄ᅗ䠎䠅䠊䠄䠏䠅ᅗ䠍䛷䛿ィ 䛧䛯ἼᾉἼᙧ䛻㢼㏿䛾ィ್䜢㔜䛽䛶䛔䜛䠊ᅗ䠍䛛䜙ศ䛛䜛䛸䛚䜚䠈㢼㏿䛜㧗䛟䛺䜛䛻䛴䜜䝷䜲䝎䞊䛷ィ 䛥䜜䛯䜶䝁䞊ᙉᗘ䛜㧗䜎䜛ഴྥ䛻䛒䜛䛣䛸䛜ぢ䛶ྲྀ䜜䜛䠊䜎䛯䠈㢼㏿䜔Ἴ䛾䜶䝁䞊ᙉᗘ䛻౫Ꮡ䛧䛶ᆅ⾲㠃኱Ẽ䛾ᣲື䛾஘䜜䛜ฟ䜛䛣䛸䛜☜ㄆ䛩䜛䛣䛸䛜䛷䛝䜛䠊ᅗ䠎䛛䜙䠈䛭䜜䛮䜜䛾ィ᫬้䛷Ἴ䛾୺せ䛺࿘Ἴᩘᡂศ䛜␗䛺䛳䛶䛚䜚䠈䝷䜲䝎䞊䛛䜙䛾㊥㞳5mࠥ20m⛬ᗘ䛾ᆅ⾲㠃኱Ẽ䛾䜖䜙䛞䜢☜ㄆ䛷䛝䜛䠄䠐䠅䛣䜜䜙䛾ྍど໬䛧䛯⤖ᯝ䜘䜚Ἴ䛾ᇶ♏
᝟ሗ䜢ᢳฟ䛩䜛᪉ἲㄽ䜢☜❧䛧䛯䠊䛣䜜䛻䜘䜚䠈Ἴ䛾࿘ᮇ䜔Ἴ㏿䠈₻఩ኚື㔞䛺䛹䜢᥎ᐃ䛩䜛䛣䛸䛜ྍ⬟䛸䛺䜛䠊䜎䛯Ἴ䛾ᣲື䛸ᆅ⾲㠃኱Ẽ䛸䛾┦㛵㛵ಀ䛺䛹䜢᫂䜙䛛䛻䛩䜛䛣䛸䛷䠈Ἴ䛾ື䛝䛾▷ᮇண 䛺䛹䛾ᛂ⏝䛜ᮇᚅ䛷䛝䜛䠊⌧᫬Ⅼ䛷䛿䠈㛤Ⓨ䛧䛯㏆㊥㞳䝷䜲䝎䞊䛻䜘䜚ィ

ᅗ1 䝷䜲䝎䞊䝕䞊䝍䛾ྍど໬ᅗ2 ㊥㞳ẖ䛾࿘Ἴᩘゎᯒ䛾ᵝᏊ䛧䛯䝕䞊䝍䛛䜙䠈䛹䛾䜘䛖䛺᝟ሗ䛜ྲྀ䜚ฟ䛫䜛䛛䜢᳨ウ䛧䛶ᡂᯝᒎ㛤䛾 䛔䜛ẁ㝵䛷䛒䜛䠊⌧ᅾ䠈ඹྠ◊✲䛜⥾⤖䛷䛝䜛䜘䛖◊✲䜢⾜䛳䛶䛔䜛᭱୰䛷䛒䜛䠊≧ἣ

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CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-42䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅TRMM᫬௦௨๓䛾඲⌫㝆Ỉ䝬䝑䝥䝥䝻䝎䜽䝖䛾ヨస䛸㝆Ỉ䛾Ẽೃኚືゎᯒ㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Development of GSMaP prototype in pre-TRMM era and satellite rainfall climate study䠄◊✲௦⾲⪅ྡ䠅 㔜㻌 ᑦ୍㻌 䠄ி㒔኱Ꮫ኱Ꮫ㝔⌮Ꮫ◊✲⛉䠅
Shoichi Shige㻌 䠄Graduate School of Science, Kyoto University 䠅䛆せ᪨䛇TRMM᫬௦௨๓䛻䛚䛡䜛䝬䜲䜽䝻Ἴᨺᑕィ䛚䜘䜃㉥እᨺᑕィ䜢⏝䛔䛯㧗ゎീᗘ⾨ᫍ㝆Ỉ䝕䞊䝍䜢ヨస䛧䚸㝆Ỉ䛾Ẽೃኚືゎᯒ䛻㈨䛩䜛䛣䛸䜢┠ⓗ䛸䛧䛶䛔䜎䛩䚹2015ᖺᗘ䛻ヨస䛧䛯඲⌫㝆Ỉ䝬䝑䝥䝥䝻䝎䜽䝖䜢ά⏝䛩䜛䛣䛸䛷䚸䝏䝧䝑䝖㧗ཎኟᏘ䝰䞁䝇䞊䞁䛻䛚䛡䜛㝆Ỉุᐃ⢭ᗘ䛾పୗཎᅉ䛜✚㞷䝇䜽䝸䞊䝙䞁䜾䛾ㄗุᐃ䛷䛒䜛䛣䛸䜢≉ᐃ䛧䚸GSMaP䝬䜲䜽䝻Ἴᨺᑕィ䜰䝹䝂䝸䝈䝮䛾ᨵၿ䛻䛴䛺䛜䜚䜎䛧䛯䚹䜂䜎䜟䜚䠐ྕ䛾㓄ಙ䝕䞊䝍䛻ᑐ䛧䛶ᗄఱ⿵ṇ䜢᪋䛧䛯⦋ᗘ-⤒ᗘᗙᶆኚ᥮䝁䞊䝗䜢㛤Ⓨ䛧䜎䛧䛯䚹䛆Abstract䛇

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

To contribute rainfall climate study by satellite data, this study aims to construct a prototype of the
GSMaP rainfall data in pre-TRMM era using microwave and infrared radiometers. In this fiscal year, we
identified causes of the deterioration of the deterioration of GSMaP rain detection over the Tibetan
Plateau during the summer monsoon season by an inadequate snow screening, and improved therain/no-rain classification method for microwave radiometers. We developed a code of geometrictransformation for GMS4.

䝬䜲䜽䝻Ἴᨺᑕィ䛸㉥እᨺᑕィ䝕䞊䝍䜢⤌䜏ྜ䜟䛫䛯⾨ᫍ㝆Ỉ䝬䝑䝥䛿1970ᖺ௦ᚋ༙䛛䜙Ꮡᅾ䛧䜎䛩䛜䚸᫬✵㛫ゎീᗘ䛾⣽䛛䛔㝆Ỉ⌧㇟䛻ᑐ䛧䛶༑ศ䛺ゎᯒ䛻䛿⪏䛘䜎䛫䜣䚹⇕ᖏ㝆㞵ほ ⾨ᫍ䠄TRMM䠅䛻䜘䜚䝬䜲䜽䝻Ἴᨺᑕィ㝆Ỉ᥎ᐃ䜰䝹䝂䝸䝈䝮䛿㣕㌍ⓗ䛺Ⓨᒎ䜢㐙䛢䚸⌧ᅾ䛷䛿㧗ゎീᗘ䠄0.1-0.25ᗘ䚸30ศ-3᫬㛫䠅䛾⾨ᫍ㝆Ỉ䝥䝻䝎䜽䝖䛜ᥦ౪䛥䜜䛶䛔䜎䛩䚹ᮏ◊✲䛿䚸TRMM᫬௦௨๓䛾ほ 䝕䞊䝍ᑐ䛧䛶᭱᪂䛾䝬䜲䜽䝻Ἴᨺᑕィ㝆Ỉ᥎ᐃ䜰䝹䝂䝸䝈䝮䜢㐺⏝䛧䛯㧗ゎീᗘ⾨ᫍ㝆Ỉ䝕䞊䝍䜢ヨస䛧䚸⣙30ᖺศ䛾㛗ᮇ㐃⥆䝕䞊䝍䜢ᵓ⠏䛩䜛䛣䛸䛷䚸⾨ᫍ䝕䞊䝍䛻䜘䜛㝆Ỉ䛾Ẽೃኚື䜢᫂䜙䛛䛻䛩䜛䛣䛸䜢┠ⓗ䛸䛧䛶䛔䜎䛩䚹䠄䠍䠅䝏䝧䝑䝖㧗ཎኟᏘ䝰䞁䝇䞊䞁䛻䛚䛡䜛㝆Ỉุᐃ⢭ᗘ䛾పୗཎᅉ䜢᫂䜙䛛䛻䛧䜎䛧䛯䚹ᆅ⾲㠃 ᗘ䛾᥎ᐃ䛻⏝䛔䜛ᆅ⾲㠃ᑕฟ⋡䜢䚸ᚑ᮶䛾ᅛᐃ್䛛䜙⾨ᫍほ 䛻ᇶ䛵䛔䛯᥎ᐃ್䛻ᕪ䛧᭰䛘䜛䛣䛸䛻䜘䜚䚸✚㞷䝇䜽䝸䞊䝙䞁䜾䛾ㄗุᐃ䜢ᅇ㑊䛩䜛䛣䛸䛜䛷䛝䜎䛧䛯䠄ᅗ䠍䠅䚹䜎䛯䚸㧗㧗ᗘᇦ䛻䜏䜙䜜䜛ほ ㍤ᗘ ᗘ䛾኱䛝䛺᪥࿘ኚ໬䜒㝆㞵/↓㝆㞵ุᐃ䛻ᙳ㡪䜢୚䛘䛶䛔䜛䛣䛸䜢♧䛧䜎䛧䛯䚹䛣䛾ᡂᯝ䛿䚸2015ᖺᗘ䛻ヨస䛧䛯඲⌫㝆Ỉ䝬䝑䝥䝥䝻䝎䜽䝖䜢ά⏝䛧䛯䜒䛾䛷䛩䚹䠄䠎䠅ୖグ䛾⤖ᯝ䜢ඖ䛻䚸GSMaP䝬䜲䜽䝻Ἴᨺᑕィ㝆Ỉ㔞᥎ᐃ䜰䝹䝂䝸䝈䝮䛾ᨵⰋ䜢⾜䛔䜎䛧䛯䚹2017ᖺ1᭶䛻ᨵゞ䛥䜜䛯᭱᪂∧䜰䝹䝂䝸䝈䝮䝞䞊䝆䝵䞁7䛻཯ᫎ䛥䜜䜎䛧䛯䚹䠄䠏䠅䜂䜎䜟䜚䠐ྕ䛾㓄ಙ䝕䞊䝍䛻ᑐ䛧䛶ᗄఱ⿵ṇ䜢᪋䛧䛯⦋ᗘ-⤒ᗘᗙᶆኚ᥮䝁䞊䝗䜢㛤Ⓨ䛧䜎䛧䛯䠄ᅗ䠎䠅䚹
TRMM᫬௦௨๓䛾㟼ṆẼ㇟⾨ᫍ䝕䞊䝍䜢ᩚഛ䛩䜛䛣䛸䛜䛷䛝䜛䜘䛖䛻䛺䜚䚸㉥እ䝕䞊䝍䜢⤌䜏ྜ䜟䛫䛯඲⌫㝆Ỉ䝬䝑䝥䝥䝻䝎䜽䝖䛾సᡂ䛜ྍ⬟䛸䛺䜚䜎䛩䚹ᅗ1 (a)TRMM PR䛜䝏䝧䝑䝖㧗ཎ䛷ᤊ䛘䛯㝆㞵䛻ᑐ䛩䜛(b)ᨵⰋ๓䚸(c) ᨵⰋᚋ䛾GSMaP㝆Ỉ㔞䛾ศᕸ

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

ᅗ2 1994ᖺ4᭶1᪥12᫬䠄᪥ᮏ᫬䠅䛻䛚䛡䜛䠄ᕥ䠅ྍど䠄ྑ䠅㉥እ⏬ീ(1)䛾ᡂᯝ䛿䚸IEEE Geosci. Remote Sens. Lett.䛻ᰝㄞ௜䛝ㄽᩥ䛸䛧䛶ཷ⌮䛥䜜䚸㏆᪥ฟ∧䛥䜜䜛ணᐃ䛷䛩䚹(2)䛾ᨵⰋ䜢᪋䛧䛯᭱᪂∧GSMaP䝥䝻䝎䜽䝖䛿JAXA䛛䜙බ㛤䛥䜜䛶䛔䜎䛩䚹(3)䛷㛤Ⓨ䛧䛯䝁䞊䝗䜢⏝䛔䛶䜂䜎䜟䜚䠐ྕ䛾ྍど䞉㉥እ䜾䝸䝑䝗䝕䞊䝍䛜సᡂ䛥䜜䚸CEReS䜘䜚බ㛤䛥䜜䜛ணᐃ䛷䛩䚹― 81 ―

㻾㼑㼜㼛㼞㼠㻌㼒㼛㼞㼙㻌㼒㼛㼞㻌㻯㻱㻾㼑㻿㻌㻻㼢㼑㼞㼟㼑㼍㼟㻌㻶㼛㼕㼚㼠㻌㻾㼑㼟㼑㼍㼞㼏㼔㻌㻼㼞㼛㼓㼞㼍㼙㻌㻞㻜㻝㻢㻌䛆Joint Research No. CJ16-47䛇
㻌 Title of Joint Research: Development and validation of advanced satellite data analysis techniques for 㻌 㻌monitoring and mitigate natural and environmental risks
Name of Principal Investigator:
Nicola Genzano 㻌 䠄Graduate School of Science, Chiba University, Japan & School of Engineering,
University of Basilicata, Italy䠅䛆Abstract䛇 (Approximately 100 words)
In the last 20 years, the general change detection method Robust Satellite Techniques (Tramutoli 1998, 2007)
was demonstrated to be a useful tool in the field of geohazard assessment and their mitigation. Thanks to its
full exportability on different satellite packages and geographical areas, RST has been used to identify andmonitor the space-time evolution of many natural and environmental phenomena. In this research project, thecapabilities of the RST methodology has been evaluated in context of the Fukushima Daiichi nuclear disaster,
occurred after the 9.0 magnitude Tohoku earthquake and subsequent tsunami on March 11, 2011.

䠍BackGround
Objective
Methodology

䠎Conclusions

䠏

Effect/OutcomeSince 1998, the Robust Satellite Techniques (RST) has been widely used in a large spectrum of
applications by using a large data set of satellite images acquired by sensors on board of polarand geostationary platforms.
The objective of this study is to verify the potentiality of the RST satellite data analysis techniquefor recognizing and identifying anomalous signal variations due to the explosions occurred at the
Fukushima Daiichi nuclear power station on March 2011, after the Tohoku earthquake (March 11,
2011; M 9.0) and subsequent tsunami.
To this aim, RST approach has been implemented on the radiances acquired in the Mid InfraRed(MIR) channel by the satellite sensors operating on board of the geostationary platforms
MTSAT-1R and 2 over the Japanese territory in the months of March from 2006 up to 2011.

RST analysis
performed at the timeof nuclear disaster of
the Fukushima
Daiichi nuclear power
station, showedanomalies, whichwere identified by the
ALICE (Absolutely
Llocal Index of
Change of theEnvironment;
Tramutoli 1998)
index, greater than 2times the historicalvariability of therecorded signal at thelocation of the
Fukushima Daiichi
nuclear power station.

Fig.1 Results of the analysis performed in the period March 8 -18, 2011 at thelocation of the Fukushima Daiichi nuclear power station. Times are given
in Coordinated Universal Time (UTC).

Robust Satellite Techniques has been implemented on the radiances acquired by the Japanesegeostationary satellite systems MTSAT-1R/-2, showing a good ability to recognizing and identifying
anomalous signal variations probably due to the explosions happened at the Fukushima Daiichi
nuclear power station on March 2011.

― 82 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-20䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅኱Ẽᆅୖ᳨ド⏝ᶵᮦᛶ⬟ྥୖ◊✲఍㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Workshop on Validation Equipment Performance Improvement for Air (VEPIA)䠄◊✲௦⾲⪅ྡ䠅 ᮏከ㻌 ჆᫂㻌 䠄༓ⴥ኱Ꮫ䞉⎔ቃ䝸䝰䞊䝖䝉䞁䝅䞁䜾◊✲䝉䞁䝍䞊䠅
Yoshiaki HONDA 䠄Center for Environmental Remote Sensing, Chiba University)
䛆せ᪨䛇㻌 ᙜ䝉䞁䝍䞊䜒㛵䜟䛳䛶䛔䜛Skynet㻌 䠄኱Ẽᆅୖ᳨ド䝛䝑䝖䝽䞊䜽䠅䛾ᆅୖ ჾ䛾᭦᪂᫬ᮇ䜢㏄䛘䛶䛔䜛䚹䜎䛯䚸ᙜヱ኱Ẽᆅୖ᳨ド䝛䝑䝖䝽䞊䜽䛿ᡃ䛜ᅜ䛾⾨ᫍ( GOSAT, GOSAT-2, GCOM-C䛺䛹䠅䛻䜘䜛䜶䜰䝻䝌䝹➼䛾኱Ẽほ 䛾ᆅୖ᳨ド䛻䜒㈨䛩䜛䜒䛾䛷䛒䜛䚹䛭䛾䛯䜑䚸ᙜヱ䝛䝑䝖䝽䞊䜽䛾ḟᮇᆅୖ ჾ䛾௙ᵝ䛜᪩ᛴ䛻ᚲせ䛷䛒䜛䚹ᮏ◊✲఍䛿䚸䛭䛾௙ᵝ᳨ウ䛾㆟ㄽ䜢ᨭ᥼䛩䜛䜒䛾䛷䛒䜛䚹䛆Abstract䛇 We are entering the time to update the ground measuring instruments of the Skynet (atmospheric groundverification network) which our center is also involved with. The atmospheric ground verification network
also contributes to ground verification of atmospheric observation such as aerosol by Japanese satellites(GOSAT, GOSAT - 2, GCOM - C etc). Therefore, the specification of the next ground instrument of theSkynet is urgently needed. This study group supports the discussion of the specification review.

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

ᙜ䝉䞁䝍䞊䜒㛵䜟䛳䛶䛔䜛Skynet㻌 䠄኱Ẽᆅୖ᳨ド䝛䝑䝖䝽䞊䜽䠅䛿ᆅ⌫ほ ⾨ᫍ䛾ᆅୖ᳨ド䛻኱䛔䛻ᙺ❧䛳䛶䛝䛯䚹䛧䛛䛧Skynet䛾ᆅୖ ჾ䛜᭦᪂䛾᫬ᮇ䛫䜎䛳䛶䛝䛶䛚䜚䚸䛣䛾ᶵ䛻䜘䜚㧗⢭ᗘ䛾᪂䛯䛺ᆅୖჾ䛜ᮃ䜎䜜䛶䛔䜛䚹㻌 䛭䛣䛷䚸ᮏ◊✲఍䛷䛿䚸኱Ẽศ㔝䜢ᑓ㛛䛸䛩䜛◊✲⪅䚸ᆅ⌫ほ 䛾◊✲⪅䚸䝝䞊䝗㛤Ⓨ䛾⤒㦂⪅䚸⾨ᫍ㛤
Ⓨᶵ㛵䛺䛹䛾᭷㆑⪅䜢㞟䜑䚸ḟᮇᆅୖ ჾ䛾ほ ᪉ἲ䚸௙ᵝ➼䜢᳨ウ䛩䜛䚹䛭䛾㝿䚸➨୍ẁ㝵䛸䛧䛶ヨసᶵ䜢ᛕ㢌䛻⨨䛝䚸ヨసᶵ䛻䜘䜛ᐇ㦂⤖ᯝ䜢ᚓ䛺䛜䜙䚸㔞⏘ᶵ䛾᳨ウ䜢㛤ጞ䛩䜛䚹ィ⏬䛷䛿ᩘᖺ௨ෆ䛾ᐇ⌧䜢┠ᣦ䛩䜒䛾䛸䛩䜛䚹௒ᖺᗘ䛾◊✲㞟఍䛷䛾㆟ㄽ䛾⤖ᯝ䠈௨ୗ䛾ヨసᶵ䛾௙ᵝ䛾୺䛺䜒䛾䛿䠎Ⅼ䛻㞟⣙䛥䜜䛯䚹䠄䠍䠅ḟᮇᆅୖ

ჾ䛻ᮃ䜎䜜䜛ほ᮲௳䞉 ᐃἼ㛗ᇦ㻌 䠏䠔䠌nmࠥ900nm
䞉ど㔝ゅ㻌 㖄┤᪉ྥ䠖䠕䠑ᗘ㻌 㻌 㻌 㻌 㻌 㻌 Ỉᖹ᪉ྥ䠖0.25ᗘ
䞉 ᐃゅᗘศゎ⬟㻌 㖄┤᪉ྥ䠖0.20ᗘ㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 㻌 Ỉᖹ᪉ྥ䠖0.25ᗘ䞉┤❧ග ග⏝ᕤᏛ⣔䜢᭷䛩䜛䛣䛸
䞉㍤ᗘ䛚䜘䜃Ἴ㛗ᰯṇ⣔䜢᭷䛩䜛䛣䛸䠄䠎䠅 ḟᮇᆅୖ⣲ᶵ䛾ほ᪉ᘧ䞉ศග᪉ᘧ䠖䝥䝸䝈䝮䜢ศᩓ⣲Ꮚ䛸䛩䜛䝻䞁䜾䝇䝸䝑䝖ศග䞉Ἴ㛗ศゎ⬟䠖䠕䠌䠌nm䛻䛚䛔䛶㻌 10nm⛬ᗘ䞉䝇䝬䝹ຠᯝ䛚䜘䜃Ⰽ཰ᕪ䜢ྍ⬟䛺㝈䜚ᢚไ䛩䜛䞉᳨ฟ㒊䛿䠎ḟඖ䝉䞁䝃䜢฼⏝䛩䜛䛣䛸㻌 㻌 1ḟඖ䛿✵㛫᪉ྥ䜒䛖୍ḟඖ䛿ศග᪉ྥ䞉㖄┤᪉ྥ䠕䠑ᗘ䛾ど㔝ゅ䜢ᣢ䛴䚸ගᏛ⣔䜢ᩘศ⛬ᗘ䛷䠍࿘䛩䜛ᅇ㌿ᯫྎ䛻㍕䛫䜙䜜䜛䛣䛸䞉ᒇእ䛻タ⨨䛧䚸㢼㞵䛻⪏䛘䜛䛣䛸

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

ᮏ◊✲㞟఍䛾ᨭ᥼䛷ྲྀ䜚䜎䛸䜑䛯ヨసᶵ䛾௙ᵝ䛻ᇶ䛵䛝䚸ヨసᶵ䛾〇㐀ィ⏬䛚䜘䜃ணഛⓗᐇ㦂䛾ィ⏬䜢❧䛶䚸䛭䜜䜙䛾⤖ᯝ䛾ศᯒ䚸ゎᯒ䜢䛩䜛䜑䜛䛣䛸䛜᳨ウ䛥䜜䛶䛔䜛䚹㻌 ᐇ㦂⤖ᯝ䛻ᇶ䛵䛔䛶䚸ၥ㢟Ⅼ䚸ᨵⰋⅬ䚸䛥䜙䛻䛿㔞⏘ᶵ䛻ྥ䛡䛯᳨ウ䜢ᨭ᥼䛩䜛䚹― 83 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-26䛇
⾨ᫍ䝕䞊䝍䠈ᩘ್䝰䝕䝹䜢⏝䛔䛯⤫ྜⓗ䛺㣗⣊⏕⏘㔞᥎ᐃ䛻㛵䛩䜛◊✲఍
Workshop on integrated estimation of yield production by using satellite data and umerical models䠄◊✲௦⾲⪅ྡ䠅 ᵽཱྀ㻌 ⠜ᚿ㻌 䠄༓ⴥ኱Ꮫ䞉⎔ቃ䝸䝰䞊䝖䝉䞁䝅䞁䜾◊✲䝉䞁䝍䞊䠅
Atsushi Higuchi 䠄Center for Environmental Remote Sensing, Chiba University)䛆せ᪨䛇ᮏ◊✲఍䛿䠈FY2013-FY2015䛻ᩥ⛉┬Ᏹᐂ⤒㈝䛷ᐇ᪋䛧䛯䠈㏻⛠䛂㣗⣊Ᏻ඲ಖ㞀䝟䝑䜿䞊䝆䛃䛷ᚓ䜙䜜䛯ᡂᯝ䛾᳨ド䠈䛚䜘䜃௒ᚋ䛾ᡓ␎䜢⦎䜛䛯䜑䛾◊✲఍䛷䛒䜛䠊 䛂㣗⣊Ᏻ඲ಖ㞀䝟䝑䜿䞊䝆䛃䛸䛿᪥ᑕ㔞䠈㝆Ỉ㔞䠈㠃ⓗ䛺┤᥋ィ 䛜㞴䛧䛔せ⣲䜢⾨ᫍධຊ䠄EXAM, GSMaP䠅䛻⨨䛝᥮䛘䠈Ẽ㇟ᗇᥦ౪䛾ᐈほゎᯒ䝕䞊䝍䠈෌ゎᯒ䝕䞊䝍➼䜢ධຊ䛸䛧䛶䠈⤫ྜ㝣㠃㐣⛬䝰䝕䝹 䛸స≀⏕㛗䝰䝕䝹 SIMRIW䜢㥑ື䛥䛫䜛䛣䛸䛷䝟䝑䜿䞊䝆䞁䜾໬䛩䜛
ヨ䜏䛷䛒䜛䠊◊✲఍䛿ᖹᡂ28ᖺ9᭶7᪥䛻༓ⴥ኱CEReS 䛻䛶ィ8ྡ䛾ཧຍ⪅䛷ᐇ᪋䛧䛯䠊௒ᚋ䛾ᒎ㛤䠈≉䛻⛉◊㈝➼䛾➇தⓗ㈨㔠䛻ᑐ䛩䜛ᛂເᡓ␎䛻䛴䛔䛶㔜Ⅼⓗ䛻㆟ㄽ䛜䛺䛥䜜䛯䠊䛆Abstract䛇 We planed to held the workshop on ”food security package by the integration of satellite products andnumerical modellings”. The workshop was carried out in 7th September 2016 at CEReS, Chiba University.
The eight participants discussed with future perspective of food security package in a basis of researchfunding.

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

䛂㣗⣊Ᏻ඲ಖ㞀䝟䝑䜿䞊䝆䛃䛿᪥ᑕ㔞䠈㝆Ỉ㔞䠈㠃ⓗ䛺┤᥋ィ 䛜㞴䛧䛔せ⣲䜢⾨ᫍධຊ䠄EXAM,GSMaP䠅䛻⨨䛝᥮䛘䠈Ẽ㇟ᗇᥦ౪䛾ᐈほゎᯒ䞉෌ゎᯒ䝕䞊䝍➼䜢ධຊ䛸䛧䛶⤌䜏ྜ䜟䛫䠈⤫ྜ㝣㠃㐣⛬䝰䝕䝹䛸స≀⏕㛗䝰䝕䝹䜢⤌䜏ྜ䜟䛫䜛䛣䛸䛷䠈㝣㠃㐣⛬䠄≀⌮㐣⛬䠈⏕ែ㐣⛬䠅䜢䝰䝕䝹䛻䜘䜚⾲⌧䛩䜛䠄㝣㠃㐣ཤゎᯒ䠈㏿ሗゎᯒ䠅䠈䛣䛾⤖ᯝ䜢ึᮇቃ⏺᮲௳䛸䛧䛶⏝䛔䠈㞼ゎീ䝰䝕䝹 CReSS 䛸ୖグ䝰䝕䝹⩌䜢䜹䝑䝥䝹䛥䛫䠈1-7᪥ඛ䜎䛷ண 䛩䜛䝅䞊䝮䝺䝇䛺䝟䝑䜿䞊䝆䜢ᣦ䛩䠊ᮏ◊✲㞟఍䛿䠈2013-2015ᖺᗘ䛷㛤Ⓨ䛧䛯ᮏ䝟䝑䜿䞊䝆䜢䛔䛛䛻Ⓨᒎ䛥䛫䜛䛛䠈୺䛻௒ᚋ䛾ᡓ␎䜢⦎䜛䛯䜑䛻◊✲㞟఍䜢ᐇ᪋䛧䛯䠊◊✲㞟఍䛷䛾㆟ㄽ䛾⤖ᯝ䠈௨ୗ䛾䠎Ⅼ䛻㞟⣙䛥䜜䛯䠊䠄䠍䠅඲⌫ᒎ㛤䛩䜛䛯䜑䛾ไ⣙䛿௨ୗ䛾䠎Ⅼ䛷䛒䜛䠊a. 㝆Ỉ䝥䝻䝎䜽䝖 GSMaP 䛿඲⌫䛷ᒎ㛤䛥䜜䛯䝥䝻䝎䜽䝖䛷䛒䜛䛾䛻ᑐ䛧䠈᪥ᑕ䝥䝻䝎䜽䝖 EXAM 䛿」ᩘ
䛾◊✲䝥䝻䝆䜵䜽䝖⤒㈝䛻䜘䜛䠈⌧≧䛷䛿䛂䜂䜎䜟䜚ᇦ䛃䛾䜏䛷䛾ᒎ㛤䛷䛒䜛䠊䛭䛾䛯䜑䠈」ᩘ䛾㟼ṆẼ
㇟⾨ᫍ䜢⏝䛔䛯EXAM䛾඲⌫ᒎ㛤䠄䝸䜰䝹䝍䜲䝮ศ䠈㐣ཤศඹ䛻䠅䛾ඃඛ㡰఩䛜ᴟ䜑䛶㧗䛔䠊b. 2013-2015䛾ᩥ⛉┬䝥䝻䝆䜵䜽䝖䛷ᵓ⠏䛧䛯䝟䝑䜿䞊䝆䛿స≀ᡂ㛗䝰䝕䝹䛿䜲䝛䛻䛴䛔䛶䛾䜏ྲྀ䜚ᢅ䛳䛶䛔䛯䠄SIMRIW) 䠈඲⌫ᒎ㛤䛩䜛䛯䜑䛻䛿௚䛾୺せ✐≀䜒㝧䛻ᢅ䛖స≀⏕㛗䝰䝕䝹䠄཰㔞᥎ᐃ䝰䝕䝹䜒ྵ䜐䠅䛸䛾䜹䝑䝥䝸䞁䜾䠈䛒䜛䛔䛿ඹྠ◊✲䛜ᚲせ䛷䛒䜛䠊䠄䠎䠅 (1) 䜢㋃䜎䛘䠈௨ୗ䛾᪉㔪䛷➇தⓗ㈨㔠䜈䛾ᛂເ䜢✚ᴟⓗ䛻⾜䛖䛣䛸䛷ྜព䛧䛯䠊a. (1).a 䜢㋃䜎䛘䠈䝇䝖䝺䞊䝖䛻᪥ᑕ䠄ኴ㝧ග䠈ኴ㝧ගⓎ㟁㔞䠅䛾඲⌫ᒎ㛤䛻㛵䛩䜛䝥䝻䝫䞊䝄䝹䜢䠈ྜ⮴䛩䜛ෆᐜ䛷᪩ᛴ䛻ฟ䛩ᚲせ䛜䛒䜛䠊䛣䜜䛿ᩥ㒊⛉Ꮫ┬DIAS䜰䝥䝸䜿䞊䝅䝵䞁䝣䜱䝆䝡䝸䝔䜱䝇䝍䝕䜱䞊䛜ྜ⮴䛧䛯䛯䜑䠈༓ⴥ኱Ꮫ䠈JAXA/EORC, ᮾᾏ኱Ꮫ䠈NICT䠈WNI 䛾ඹྠᥦ᱌䛸䛧䛶ᥦฟ䛧䠄௦⾲䠖ᵽཱྀ䠅䠈᥇ᢥ䛥䜜䛯䠊
b. (1).b. 䜢㋃䜎䛘䠈䝸䜰䝹䝍䜲䝮ᐇ⿦䛸㐣ཤศィ⟬䛾஧䛴䛾᪉ྥᛶ䛜⪃䛘䜙䜜䜛䛜䠈◊✲఍䛾ẁ㝵䛷䛿஧䛴䜢ศ䛡䛶⛉◊㈝䛷⏦ㄳ䛩䜛䛣䛸䛷ྜព䛧䛯䠊䝸䜰䝹䝍䜲䝮ᐇ⿦䛻䛴䛔䛶䛿䠈ி኱⏣୰Ặ䜢୰ᚰ䛻ྲྀ䜚䜎䛸䜑䠈㐣ཤศィ⟬䛻䜘䜛඲⌫ᒎ㛤䛿௦⾲⪅䠄ᵽཱྀ䠅䜢୰ᚰ䛻ྲྀ䜚䜎䛸䜑䜛䛣䛸䛻䛺䛳䛯䠊ᐇ㝿䛻䛿䠈(1).a䛾୙☜ᐇᛶ䛜䛒䛳䛯䛯䜑䠈⏦ㄳ䛿㐣ཤศィ⟬䛾䜏䠄ᵽཱྀ௦⾲䠈ᇶ┙B䠅䛷⾜䛳䛯䠊

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ᮏ◊✲㞟఍䛷୍㒊㆟ㄽ䛧䛯ෆᐜ䛾⤖ᯝ䛸䛧䛶䠈ᩥ㒊⛉Ꮫ┬DIAS䜰䝥䝸䜿䞊䝅䝵䞁䝣䜱䝆䝡䝸䝔䜱䝇䝍䝕䜱䞊(FS) 䛜௨ୗ䛾ㄢ㢟ྡ䛷᥇ᢥ䛥䜜䛯䠊䛂㟼ṆẼ㇟⾨ᫍ⩌䜘䜚ᑟฟ䛥䜜䛯ኴ㝧ᨺᑕ䞉ኴ㝧ගⓎ㟁㔞᥎ᐃ䛾ୡ⏺ᒎ㛤䠄௦⾲䠖ᵽཱྀ䠈༓ⴥ኱䠅䛃― 84 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-28䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅⎔ቃၥ㢟䛾⌧ሙ䛻䛚䛡䜛㉸Ꮫ㝿◊✲䛾᪂ᒎ㛤㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅New directions in on-site transdisciplinary research for solving environmental issues䠄◊✲௦⾲⪅ྡ䠅 ㏆⸨㻌 ᗣஂ㻌 䠄⥲ྜᆅ⌫⎔ቃᏛ◊✲ᡤ ◊✲ᇶ┙ᅜ㝿䝉䞁䝍䞊䠅
Yasuhisa Kondo (RIHN Center, Research Institute for Humanity and Nature)䛆せ᪨䛇2016ᖺ10᭶䛻⥲ྜᆅ⌫⎔ቃᏛ◊✲ᡤ䠄ி㒔ᕷ䠅䛻䛚䛔䛶䛂⎔ቃၥ㢟䛾⌧ሙ䛻䛚䛡䜛㉸Ꮫ㝿◊✲䛾᪂ᒎ㛤䛃䛸㢟䛩䜛䝽䞊䜽䝅䝵䝑䝥䜢ദ䛧䚸⎔ቃၥ㢟䛾⌧ሙ䛻䛚䛡䜛䝇䝔䞊䜽䝩䝹䝎䞊䛸䛾༠ാ䛾ᐇ㊶౛䜢ඹ᭷䛩䜛䛸䛸䜒䛻䚸♫఍䛻䛚䛡䜛⛉Ꮫ䛾ᙺ๭䛸䚸ㄢ㢟ゎỴ䜈䛾⛉Ꮫ⪅䛾㛵୚䛾䛒䜚᪉䛻䛴䛔䛶㆟ㄽ䛧䜎䛧䛯䚹䛭䛾ᡂᯝ䜢┒䜚㎸䜣䛷䚸◊✲⪅䛸䝇䝔䞊䜽䝩䝹䝎䞊䛜ᶫΏ䛧ேᮦ䛾௰௓䛻䜘䜚▱㆑䞉᝟ሗ䜢ඹ᭷䛩䜛䛣䛸䛻䜘䛳䛶ㄢ㢟ゎỴ䜢ᅗ䜛䛂▱䛾ᶫ䛛䛡◊✲䝰䝕䝹䛃䜢ᵓ᝿䛧䜎䛧䛯䚹䛆Abstract䛇 We held the two-day workshop titled “New directions in –n-site transdisciplinary research for solving
environmental issues” at the Research Institute for Humanity and Nature, Kyoto, Japan, in October 2016.
In the workshop, reports from collaborative projects with societal stakeholders in a specific site ofenvironmental issue were shared, and the role of science in society and engagement of scientists toissue solution were discussed. The discussion benefited the development of the “Knowledge Bridging
Research Model”, in which researchers and other stakeholders share knowledge and information withthe mediation of bridging agents towards solution of the issue.

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ୡ⏺ྛᆅ䛷ከⓎ䛩䜛⎔ቃၥ㢟䛻ᑐฎ䛩䜛䛯䜑䛻䚸䛂♫఍䛾䛯䜑䛾⛉Ꮫ䛃䛾ᐇ⌧䛜ႚ⥭䛾ㄢ㢟䛸䛺䛳䛶䛔䜎䛩䚹⎔ቃၥ㢟䜢ゎỴ䛩䜛䛯䜑䛻䛿䚸♫఍䛾ከᵝ䛺䝇䝔䞊䜽䝩䝹䝎䞊䠄฼ᐖ㛵ಀ⪅䠅䛸䛾༠ാ䚸䛩䛺䜟䛱⛉Ꮫ⪅䛜⛉Ꮫ▱䚸ពᛮỴᐃ⪅䛜ᨻ⟇▱䠄䜺䝞䝘䞁䝇䛾▱䠅䚸⏕ά⪅䛜ᅾ᮶▱䠄䛺䜚䜟䛔䛾▱䠅䜢ᣢ䛱ᐤ䜚䚸⇍㆟䛸┦஫⌮ゎ䜢㏻䛧䛶ྜពᙧᡂ䛻⮳䜛㉸Ꮫ㝿䜰䝥䝻䞊䝏䠄transdisciplinary approach䠅䛜ᚲせ䛷䛒䜛䛸䛔䜟䜜䛶䛔䜎䛩䚹䝇䝔䞊䜽䝩䝹䝎䞊䛿ከᒙⓗ䛷䛒䜚䚸䝇䝔䞊䜽䝩䝹䝎䞊㛫䛾฼ᐖㄪᩚ䜔ᑐ❧䚸ᨻ⟇Ỵᐃ⪅䛸䛾㛵ಀ䛺䛹䚸㉸Ꮫ㝿䛻㛵䜟䜛⛉Ꮫ⪅䛜⌮ゎ䛧䛶䛚䛟䜉䛝ㄢ㢟䛿䛯䛟䛥䜣䛒䜚䜎䛩䚹䛭䛣䛷2016ᖺ10᭶9䞉10᪥䛻ி㒔䛾⥲ྜᆅ⌫⎔ቃᏛ◊✲ᡤ䠄ᆅ⌫◊䠅䛻䛚䛔䛶䝽䞊䜽䝅䝵䝑䝥䜢ദ䛧䚸⎔ቃၥ㢟䛾⌧ሙ䛻䛚䛡䜛䝇䝔䞊䜽䝩䝹䝎䞊䛸䛾༠ാ䛾ᐇ㊶౛䜢ඹ᭷䛩䜛䛸䛸䜒䛻䚸♫఍䛻䛚䛡䜛⛉Ꮫ䛾ᙺ๭䛸䚸ㄢ㢟ゎỴ䜈䛾⛉Ꮫ⪅䛾㛵୚䛾䛒䜚᪉䛻䛴䛔䛶㆟ㄽ䛧䜎䛧䛯䚹䝽䞊䜽䝅䝵䝑䝥䛻䛿䚸ᆅ⌫◊䞉༓ⴥ኱Ꮫ䛺䛹䛻ᡤᒓ䛩䜛◊✲⪅䜔Ꮫ⏕䚸NPO⫋ဨ䛺䛹27ྡ䛜ཧຍ䛧䜎䛧䛯䚹㊃᪨ㄝ᫂䠄ᅗ1䠅䛻⥆䛔䛶䚸ᏳᒸၿᩥCEReS䝉䞁䝍䞊㛗䛜䛂⛉Ꮫᢏ⾡䜢♫఍䛾䛹䛖䛴䛺䛢䜛䛛䠖㉸Ꮫ㝿◊✲䛾
ᐇ㊶䛸᪉ἲㄽ䛃䛸㢟䛩䜛ᇶㄪㅮ₇䜢⾜䛔䜎䛧䛯䚹䛭䛾ᚋ䚸㛢㙐ᛶỈᇦ䚸ཎᏊຊ⅏ᐖ䚸᳃ᯘಖ඲䚸஝⇱ᆅ䚸䝸䝰䞊䝖䝉䞁䝅䞁䜾䛸䛔䛖5䛴䛾䝔䞊䝬䛷䚸◊✲⪅䛸䝇䝔䞊䜽䝩䝹䝎䞊䛾༠ാ䛻㛵䛩䜛ྲྀ䜚⤌䜏䛸ㄢ㢟䜢ሗ࿌䛧䚸䝕䜱䝇䜹䝑䝅䝵䞁䜢⾜䛔䜎䛧䛯[1] 䚹䝽䞊䜽䝅䝵䝑䝥䛷䛾㆟ㄽ䜢ྲྀ䜚㎸䜣䛷䚸◊✲⪅䛸䝇䝔䞊䜽䝩䝹䝎䞊䛜ᶫΏ䛧ேᮦ䛾௰௓䛻䜘䜚▱㆑䞉᝟ሗ䜢ඹ᭷䛩䜛䛣䛸䛻䜘䛳䛶ㄢ㢟ゎỴ䜢ᅗ䜛䛂▱䛾ᶫ䛛䛡◊✲䝰䝕䝹䛃䠄ᅗ2䠅䜢ᵓ᝿䛧䜎䛧䛯䚹
[1] http://www.chikyu.ac.jp/publicity/events/etc/2016/1009-10.html

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䝽䞊䜽䝅䝵䝑䝥䛾ᵝᏊᅗ2▱䛾ᶫ䛛䛡◊✲䝰䝕䝹♫఍䛸䛾༠ാ䛻䜘䜛ᆅ⌫⎔ቃၥ㢟䛾ゎỴ䛻㈨䛩䜛⌮ㄽ䛸᪉ἲㄽ䛾☜❧䛻ྥ䛡䛶䚸▱䛾ᶫ䛛䛡◊✲䝰䝕䝹䛾ά⏝䛻ྲྀ䜚⤌䜣䛷䛔䜎䛩䚹ලయⓗ䛻䛿䚸⥲ྜᆅ⌫⎔ቃᏛ◊✲ᡤ䛜ྲྀ䜚⤌䜣䛷䛔䜛䚸Ẽೃኚື䛻ᙉ䛔♫఍䛾ᐇ⌧䛻ྥ䛡䛯ᥦゝ䜔䚸⍇⍈†䛾Ỉⲡሁ⫧ά⏝䚸໭ᾏ㐨䞉▼⊁ᕝὶᇦ䛾ᑠつᶍୖỈ䝅䝇䝔䝮䛾ᢏ⾡㌿᥮䛺䛹䛾ᐇ㊶䝥䝻䝆䜵䜽䝖䛻䚸䛣䛾䝰䝕䝹䜢ᙜ䛶䛿䜑䜛䛣䛸䛻䜘䛳䛶䚸◊✲⪅䛸♫఍䛾ከᵝ䛺䝇䝔䞊䜽䝩䝹䝎䞊䛾㛫䛾▱㆑஺ὶ䜔┦஫⌮ゎ䜢῝䜑䚸ㄢ㢟ゎỴ䛻ྥ䛡䛯◊✲䜢ᐇ㉁໬䛧䛶䛔䛝䜎䛩䚹― 85 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌
䛆CJ16-31䛇㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅ⅆᫍᆅ⾲⏝LED LIDAR䛾ᒇእ⎔ቃᛶ⬟ホ౯䛻㛵䛩䜛◊✲఍㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Meeting on assessment of Martian LED LIDAR.
䠄◊✲௦⾲⪅ྡ䠅 எ㒊 ┤ே㻌 䠄⚟ᒸ኱Ꮫ䠅
Naohito Otobe 䠄Fukuoka University䠅䛆せ᪨䛇ⅆᫍ䛿䚸⾲㠃䛻ᾮయ䛾Ỉ䛜Ꮡᅾ䛫䛪䚸◁₍䛾䜘䛖䛺◁䜔䝎䝇䝖䛜ከ䛟Ꮡᅾ䛧䛶䛔䜛䚹䛭䜜䜙䛿䚸㢼䛻䜘䛳䛶ᐜ᫆䛻✵Ẽ୰䛻ᕳ䛝ୖ䛜䜚䚸ᶵᲔ䜔ᑗ᮶ⓗ䛻䛿ே㛫䛾άື䛻ከ኱䛺ᙳ㡪䜢୚䛘䜛䛸ඹ䛻Ẽ㇟Ꮫⓗ䛻䜒㔜せ䛺せ⣲䛸䛺䛳䛶䛔䜛䚹䛣䛾䜘䛖䛺䝎䝇䝖䛾 ᐃ䜢⾜䛖 ჾ䛸䛧䛶䚸LED䜢౑⏝䛧䛯LIDAR䜢㛤Ⓨ䛧䛶䛔䜛䚹ᮏ◊✲䛷䛿䚸䛭䛾LIDAR䜢ᒇእ䛷౑⏝䛧䛯㝿䛾ᛶ⬟ホ౯䜢⾜䛳䛶䚸䛭䛾⤖ᯝ䜢䜅䜎䛘䛯௒ᚋ䛾㛤Ⓨィ⏬䜢㆟ㄽ䛩䜛䛯䜑䛻◊✲఍䜢㛤䛔䛯䚹䛆Abstract䛇

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Mars is covered with dust particles of around 1 – 2 Pm in diameter. Suspended dust heavily
influences machine or human activities on its surface. Moreover dust plays an important role on themeteorology of the planet. For these reasons, we are developing an LED LIDAR for dust
monitoring toward a future rover mission. Using a prototype of the LIDAR system, we haveconducted an outdoor measurement campaign, and held a research meeting to discuss theperformance of the system and future development.

ⅆᫍ䛾䝎䝇䝖䜢ᆅ⾲䛻䛚䛔䛶ィ 䛩䜛 ჾ䛾1䛴䛸䛧䛶LED䜢⏝䛔䛯LIDAR䜢㛤Ⓨ䛧䛯䚹ᑠᆺ䚸ప䝸䝋䞊䝇䛺≀䛜㛤Ⓨ䛥䜜ึᮇ䛾ືస䝔䝇䝖䛿䚸⤊஢䛧䛶䛔䜛䛜䚸ᒇእ䛷䛾౑⏝䛿䛺䛚ㄢ㢟䛜䛒䜛䚹䛭䛾䛯䜑䛻䚸ᒇእ䛷䛾ᛶ⬟ホ౯䝔䝇䝖䜢⾜䛔䚸䛭䛾⤖ᯝ䜢ᣢ䛳䛶ၥ㢟Ⅼ䛾☜ㄆ䛸䚸ᨵၿⅬ䛾᳨ウ䜢䛩䜛◊✲఍䜢㛤䛔䛯䚹

䠄䠍䠅✄ẟᾏᓊ䛾◁὾䛷 2016/12/07 ኤ᪉㡭䛛䜙᪥ἐᚋ8᫬㐣䛞䜎䛷㢼䛻䜘䜚ᕳୖ䛢䜙䜜䛯◁䜢䚸㛤Ⓨ䛧䛯LED㻌 LIDAR䛷ィ 䛩䜛ᛶ⬟ホ౯䝔䝇䝖䜢⾜䛔䜎䛧䛯䠄ᅗ䠍䠅䚹䠄䠎䠅 ᐃ䛥䜜䛯䝎䝇䝖䛾㔞䜢㊥㞳x᫬㛫䛾㍈䛷ᥥ⏬䛧䛯䠄ᅗ2䠅䚹㻌 㻌 㻌 䛣䜜䛻䜘䜛䛸䚸䝎䝇䝖䛾⛣ື㏿ᗘ䛺䛹䛜ィ ฟ᮶䛶䛚䜚䚸㻌 㻌 㻌 㢼㏿ィ䛾್䜔䚸タ⨨ᆺ䛾䝎䝇䝖䜹䜴䞁䝍䞊䛾 ᐃ್䛸䛾㛫䛻㻌 㻌 㻌 Ⰻ䛔┦㛵䛜䛒䜛஦䛜☜ㄆ䛥䜜䜎䛧䛯䚹㻌 㻌 㻌 LED-LIDAR䛷䝎䝇䝖䛾ᒇእ ᐃ䜢⾜䛖䛣䛸䛿ྍ⬟䛷䛒䜛䛣䛸㻌 㻌 㻌 䛜☜ㄆฟ᮶䜎䛧䛯䚹

ᅗ1✄ẟᾏᓊ䛷䛾ᛶ⬟ホ౯ヨ㦂

䠄䠏䠅LED-LIDAR 䛾⌧ᅾ䛾ฟຊ䛷䛿䚸ኴ㝧ග䛾㻌 㻌 㻌 ୗ䛷䛿ほ 䛜ᅔ㞴䛷䛒䜛䛣䛸䛿ண᝿䛥䜜䛶㻌 㻌 㻌 䛔䜎䛧䛯䛜䚸ᚲせ䛺ฟຊ䛸䚸↷ᗘィ䛾㻌 㻌 㻌 䝕䞊䝍䛻䜘䜛⎔ቃ䛸䛾ẚ㍑䛷䚸᪂䛧䛔ග※䜔㻌 㻌 㻌 䝉䞁䝃䞊䛜ධᡭ䜒䛧䛟䛿㛤Ⓨ䛥䜜䛯ሙྜ䚸㻌 㻌 㻌 ᐇ⏝ⓗ䛷䛒䜛䛛䛹䛖䛛ᐇ㦂๓䛻䝇䜽䝸䞊䝙䞁䜾㻌 㻌 㻌 ྍ⬟䛺䝕䞊䝍䜢ᚓ䜛䛣䛸䛜ฟ᮶䜎䛧䛯䚹㻌 㻌 㻌 䝉䞁䝃䞊䛾㑅ᐃ䛾㏿ᗘ䜰䝑䝥䛜ᮇᚅ䛥䜜䜎䛩䚹
ᅗ2

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

ほ ⤖ᯝ䠖┤ᑕ᪥ගୗ(ᕥୖ)௨እ䛷䛒䜜䜀ほ ྍ⬟䛷䛒䜛䛣䛸䛜ศ䛛䜛⌧ᅾ䚸㛤Ⓨ୰䛾 ჾ䛷䛩䛾䛷䚸䛔䜎ᒎ㛤䛧䛶䛔䜛ᡂᯝ䛿䛒䜚䜎䛫䜣䚹䛧䛛䛧䚸ྍᦙᛶ䛷䛒䛳䛶ᑠ㟁ຊ䛷ືస䛜ྍ⬟䛷䛒䜛䛯䜑䚸䛯䛸䛘䜀ⅆᒣ䛾ᄇẼᏍ䛛䜙ฟ䛶䛔䜛⵨Ẽ䛾㔞䜢ィ 䛩䜛 ჾ➼䛸䛧䛶䜒ᛂ⏝ྍ⬟䛷䛿䛺䛔䛛䛸䛔䛖᳨ウ䜢㐍䜑䛶䛔䜎䛩䚹― 86 ―

CEReS ඹྠ฼⏝◊✲㻛◊✲ሗ࿌䠎䠌䠍䠒㻌䛆ㄢ㢟␒ྕ䛇 CJ16-46㻌 䠄◊✲ㄢ㢟ྡ䠖࿴ᩥ䠅᳃ᯘศ㔝ᆅୖ᳨ドά⏝◊✲఍㻌 䠄◊✲ㄢ㢟ྡ䠖ⱥᩥ䠅Workshop on Ground Validation Activity for Forest Science Field䠄◊✲௦⾲⪅ྡ䠅 Ლཎᗣྖ㻌 䠄༓ⴥ኱Ꮫ䞉⎔ቃ䝸䝰䞊䝖䝉䞁䝅䞁䜾◊✲䝉䞁䝍䞊䠅
Koji KAJIWARA 䠄Center for Environmental Remote Sensing, Chiba University)䛆せ᪨䛇኱Ꮫ䛾◊✲ᯘ䛻䛚䛔䛶㛗ᖺ⵳✚䛥䜜䛶䛝䛯᳃ᯘ䛻㛵䛩䜛ᆅୖ᝟ሗ䛿኱ኚ㈗㔜䛺䜒䛾䛷䛒䜚䚸ᗈᇦ⏕ែ⣔◊✲䛻ᚲせ䛺ᇶ♏᝟ሗ䛾ᐆᗜ䛸ゝ䛘䜛䚹୍᪉䚸᫖௒䛾ᆅ⌫ほ ⾨ᫍほ 䝕䞊䝍䛻䜘䛳䛶ᗈᇦ⏕ែ⣔◊✲䛜㣕㌍ⓗ䛻㐍䜐䛸ᮇᚅ䛥䜜䛶䛔䜛䚹䛧䛛䛧䛺䛜䜙䚸⏕⌮⏕ែᏛ䚸ᯘᏛ➼䛾ほⅬ䛛䜙཰㞟䛥䜜䛯䝕䞊䝍䛸䝸䝰䞊䝖䝉䞁䝅䞁䜾䝕䞊䝍䛻䜘䜛⏕ែ⣔◊✲䛾䜰䝥䝻䞊䝏䛾᥋Ⅼ䛸䛺䜛⥭ᐦ䛛䛴ຠᯝⓗ䛺⤌⧊䜢ᚲ䛪䛧䜒᭷䛧䛶䛔䛺䛔䚹䛭䛣䛷䚸᪥ᮏ䛾௦⾲ⓗ䛺◊✲ᯘ䛷䛒䜛໭ᾏ㐨኱Ꮫ◊✲ᯘ䛾◊✲⪅䛸༓ⴥ኱Ꮫ䛾ᆅ⌫ほ ⾨ᫍ฼⏝◊✲⪅䛜䜿䞊䝇䝇䝍䝕䜱䞊䜢㏻䛧䛶䛹䛾䜘䛖䛺◊✲άື䜔⤌⧊䛜᭷ຠ䛷䛒䜛䛛䜢ㄽ䛪䜛஦䜢┠ⓗ䛸䛩䜛䚹The ground information on forests that has been accumulated for many years in university research forests is very

䛆Abstract䛇 valuable and can be said to be a treasure of basic information necessary for wide area ecosystem research.

However, it does not necessarily have a tight and effective organization which is the point of contact of ecosystem
research approach based on data collected from the viewpoint of physiological ecology, forestry, etc. and remotesensing data. In order to discuss what kind of research activities and organizations are effective through casestudies, researchers at Hokkaido University research forest, which is a representative research forest in Japan, andresearchers who work on Satellite Earth observation at Chiba University.

䠍

⫼ᬒ
┠ⓗ
᪉ἲ

䠎
◊✲䛾
ᡂᯝ

኱Ꮫ䛾◊✲ᯘ䛻䛚䛔䛶㛗ᖺ⵳✚䛥䜜䛶䛝䛯᳃ᯘ䛻㛵䛩䜛ᆅୖ᝟ሗ䛿኱ኚ㈗㔜䛺䜒䛾䛷䛒䜚䚸ᗈᇦ⏕ែ⣔◊✲䛻ᚲせ䛺ᇶ♏᝟ሗ䛾ᐆᗜ䛸ゝ䛘䜛䚹୍᪉䚸᫖௒䛾ᆅ⌫ほ ⾨ᫍほ 䝕䞊䝍䛻䜘䛳䛶ᗈᇦ⏕ែ⣔◊✲䛜㣕㌍ⓗ䛻㐍䜐䛸ᮇᚅ䛥䜜䛶䛔䜛䚹䛧䛛䛧䛺䛜䜙䚸⏕⌮⏕ែᏛ䚸ᯘᏛ➼䛾ほⅬ䛛䜙཰㞟䛥䜜䛯䝕䞊䝍䛸䝸䝰䞊䝖䝉䞁䝅䞁䜾䝕䞊䝍䛻䜘䜛⏕ែ⣔◊✲䛾䜰䝥䝻䞊䝏䛾᥋Ⅼ䛸䛺䜛⥭ᐦ䛛䛴ຠᯝⓗ䛺⤌⧊䜢ᚲ䛪䛧䜒᭷䛧䛶䛔䛺䛔䚹䛭䛣䛷䚸᪥ᮏ䛾௦⾲ⓗ䛺◊✲ᯘ䛷䛒䜛໭ᾏ㐨኱Ꮫ◊✲ᯘ䛾◊✲⪅䛸༓ⴥ኱Ꮫ䛾ᆅ⌫ほ ⾨ᫍ฼⏝◊✲⪅䛜䜿䞊䝇䝇䝍䝕䜱䞊䜢㏻䛧䛶䛹䛾䜘䛖䛺◊✲άື䜔⤌⧊䛜᭷ຠ䛷䛒䜛䛛䜢ㄽ䛪䜛஦䜢┠ⓗ䛸䛩䜛䚹•䠍䠅໭ᾏ㐨኱Ꮫഃ䛸༓ⴥ኱ഃ䛸䛾᝟ሗ஺᥮•䠎䠅䜿䞊䝇䝇䝍䝕䜱䞊ィ⏬᱌䛾❧᱌•䠏䠅䜿䞊䝇䝇䝍䝕䜱䞊䛾⤖ᯝ᳨ウ•䠐䠅䛒䜛䜉䛝◊✲άື䜔⤌⧊䛾䛒䜚᪉䛾㆟ㄽ•䠑䠅୧኱Ꮫ௨እ䜈䛾ാ䛝䛛䛡䛻䛴䛔䛶䛾㆟ㄽ䛸◊✲⤌⧊ᣑ኱㻌 ᮏ◊✲㞟఍䛾ᡂᯝ䛸䛧䛶䚸໭኱䛸༓ⴥ኱Ꮫ䛾䜏䛺䜙䛪䚸ᾏὒ◊✲㛤Ⓨᶵᵓ䚸⟃Ἴ኱Ꮫ䚸㧗▱኱Ꮫ䚸ி㒔኱Ꮫ䚸㛗ᓮ኱Ꮫ䚸Ᏹᐂ⯟✵◊✲㛤Ⓨᶵᵓ䚸ᅜ❧⎔ቃ◊✲ᡤ➼䛾ྛᶵ㛵䛾◊✲⪅䛜JAXA䛾GCOM-C䝥䝻䝆䜵䜽䝖䛾ᆅୖ᳨ド䝃䜲䝖䛸䛧䛶ᗈᇦ䝔䝇䝖䝃䜲䝖䜢」ᩘタᐃ䛧䚸ྠ䝃䜲䝖⩌䛾㞟୰ほ యไ䜢ᩚ䛘䜛άື䛻⧅䛜
䛳䛯

䠏
ᡂᯝᒎ㛤䛾
≧ἣ

㻌 ᫖ᖺ䜎䛷䛾㆟ㄽ䛷䚸᳃ᯘ⏕ែᏛ㛵ಀ◊✲⪅䛸RS◊✲⪅䛾㐃ᦠయไ䛻䛴䛔䛶䚸ඹ㏻䛾䝃䜲䝖ほ 䛻䛚䛡䜛୧⪅䛾ほ 㡯┠䜢ඹྠほ 䛸䛔䛖ᙧ䛷⥅⥆䛩䜛ᚲせᛶ䛜☜ㄆ䛥䜜䛯䚹ᐇ㝿䚸᫖ᖺᗘ䛿ᮏ◊✲఍䛷㆟ㄽ䛥䜜䛯ෆᐜ䛻ᇶ䛵䛝䚸ඹ㏻䝃䜲䝖䛻䛚䛡䜛䝞䜲䜸䝬䝇䚸LAI➼䛾ほ 㡯┠䜢ඹྠほ 䛧䛶᝟ሗ䜢ඹ᭷䛩䜛άື䛜ᐇ᪋䛥䜜䛯䚹ᮏ◊✲఍䛷㐃ᦠ䛜ྍ⬟䛸䛺䛳䛯◊✲⤌⧊䞉䝯䞁䝞䞊㛫䛻䛚䛔䛶䚸䛣䛣䛷䛾㆟ㄽ䜢ྛ䝁䝭䝳䝙䝔䜱䞊䛷ඹ᭷䛩䜛ᚲせᛶ䛜ㄆ㆑䛥䜜䜛䛻⮳䛳䛯䚹― 87 ―

㻾㼑㼜㼛㼞㼠㻌㼒㼛㼞㼙㻌㼒㼛㼞㻌㻯㻱㻾㼑㻿㻌㻻㼢㼑㼞㼟㼑㼍㼟㻌㻶㼛㼕㼚㼠㻌㻾㼑㼟㼑㼍㼞㼏㼔㻌㻼㼞㼛㼓㼞㼍㼙㻌㻞㻜㻝㻢㻌䛆Joint Research No. CI16-111䛇
㻌 Title of Joint Research: Quantifying aerosol growth using Angstrom coefficient as measured from
Ground-based instruments and satellite data
Name of Principal Investigator:
Nofel Lagrosas, Ateneo de Manila University
䛆Abstract䛇 (Approximately 100 words)(Revised) In this study, temporal changes of scattering enhancement factor is analyzed using visibility data andand ground-based instruments (aethalometer, nephelometer and weather monitor) to analyze aerosol growthand variation of aerosol scattering properties due to changes in relative humidity in the atmosphere. This new
approach is part of the continuing three year joint project. Measurement of scattering enhancement allows us
to model the monthly variation of this parameter. This method allows us to look at aerosol growth that can bematched with measured scattering enhancement factors from similar remote sensing instruments.

䠍

BackGround
Objective
Methodology

䠎Conclusions

The background of this study㻌 arises from the fact that the scattering effects of aerosols in theatmosphere is not well-known because of the aerosols’ dynamics and chemistry. This study
investigates the scattering effects of aerosol over Chiba and look at temporal changes ofscattering properties via the scattering enhancement factor.
The objective of this study is to model the scattering enhancement factor of aerosols in Chiba,
Japan.
The methodology of this study is to use ground-measured instruments and visibility meter to infer
scattering properties of aerosols in the atmosphere with changing relative humidity. The
scattering coefficients are matched to measured ambient relative humidity to look at thedependence of the scattering enhancement factor with RH.
Brief descriptions of three (at maximum) conclusions
Conclusion1
Scattering enhancement factor ofaerosols in Chiba can bemodeled using visibility metermeasurements and groundmeasured instruments. Aerosols’
scattering coefficient in summer
have higher response to relative
humidity compared to spring andautumn values of aerosol
Measured and modeled f(RH) for the month of April 2014. The
scattering coefficient in winter is
Fig.1 modeled f(RH) increases with RH according to Eq. 2 with
due to the high relative humidity
during the early hours of the morning.

a=4.455 and b=14.38. b) Measured and modeled f(RH) for themonth of June 2014. The modeled f(RH) sharply increases with
RH according to Eq. 2 with a=16.88 and b=26.60.

Conclusion 2b
The power law relationship (y=ax +1) can be used to modeled aerosol scattering enhancement factor
in Chiba. This equation better characterizes the model of the scattering enhancement factor. Monthly
values of the parameters a and b are computed. The difference of the monthly values indicate thedifferent types of prevailing aerosols in Chiba and their optical response to increasing ambient relative
humidity. These values can be used to interpolate values of scattering coefficients at any RH.

䠏

Effect/Outcome(examples)
The result of this study is applied to possible atmospheric corrections due to aerosol growth.
The developed method is applied to studies of radiation budget (contribution from aerosols) in theatmosphere.

― 88 ―

㻾㼑㼜㼛㼞㼠㻌㼒㼛㼞㼙㻌㼒㼛㼞㻌㻯㻱㻾㼑㻿㻌㻻㼢㼑㼞㼟㼑㼍㼟㻌㻶㼛㼕㼚㼠㻌㻾㼑㼟㼑㼍㼞㼏㼔㻌㻼㼞㼛㼓㼞㼍㼙㻌㻞㻜㻝㻢㻌䛆Joint Research No. CI16-104 䛇㻌 Title of Joint Research: A Remote Sensing and GIS based Approach to Mitigate Elephant-Human
Conflict in Sri Lanka
Name of Principal Investigator:
PERERA, Liyanage Kithsiri, (University of Sothern Queensland, Australia)
䛆Abstract䛇 (Approximately 100 words)
Sri Lanka has a high population density (320 per 1 sq km), where over 5,850 (2011) wild elephants live. A
government report has reviled about 200 elephants and 50 people are killed by the human-elephant conflict
annually. In a previous study, MODIS satellite images were applied to identify high risk areas in a selected
region. This study attempted to identify island wide high risk areas. The methodology is linked to the seasonal
vegetation changes and very high resolution Google Earth images through GIS analysis to map the forest area
accurately. The hotspots will identify using the new refined forest cover map which will produce in 2017 project.

䠍

BackGround
Objective
Methodology

䠎Conclusions

Sri Lanka, with 65,610 sq km land area has a rich biodiversity (27% of Sri Lanka’s elephants areendemic). The population of the country has dramatically increased since 1900 and recently
passed 20 million. The rural area population has also increased sharply due to the natural
increase and improvements in free healthcare system. The Sri Lanka’s elephant population isabout 10% of the total in Asian region elephant population, but has the highest density in theregion. The elephant density of India is 0.0008 compare to Sri Lanka’s density is 0.088. This
struggle for land by people and elephant has made a sever conflict. This study has investigated
the applicability of GIS and remote Sensing to identify hotspots of human-elephant conflict.
However, the study also found existing forest cover map of Sri Lanka has some errors. Hence,the study will divert to produce an error-free forest map first, and then produce the humanelephant conflict hot zone identification.
Brief descriptions of three (at maximum) conclusions
Conclusion 1: The reasons aggravating human-elephant conflicts
were found as follows; proximity of human-elephant, changes in longterm rainfall, droughts, increased development activities, andbehavioural changes of elephants. These findings will apply toidentifying island-wide high risk area identification in next research
step.

Fig.1 Dry season MODIS NDVI•Conclusion 2: MODIS satellite images are providing apromising opportunity to link NDVI values with dynamic
ground conditions (rainfall, drought, and land coverchanges) to identify human-elephant conflict high-risk areas.
Figure 01 shows July 28, 2012, MODIS NDVI (dark green isheavy vegetation) image of the study area and identified
high-risk (black arrows) conflict zones.
•Conclusion 3: A successful national level human-elephantconflict high-risk area identification is not possible without anerror-free forest cover map of Sri Lanka. The 2016 study
found some errors in national level forest cover maps. The
forest cover map will be refined in next joint research project(2017), using multiple spatial data sources.

䠏

Effect/OutcomeFig.2 Existing forest cover map (inolive-green) needs to refine.

(examples)
The result of this study is applied to produce a new highly accurate forest cover map of Sri Lanka, toreplace the existing national level map wish has some errors.
The GIS and remote sensing based developed method can be applied to various studies where
seasonal changes of ground conditions are related to some environment conflicts.

― 89 ―

㻾㼑㼜㼛㼞㼠㻌㼒㼛㼞㼙㻌㼒㼛㼞㻌㻯㻱㻾㼑㻿㻌㻻㼢㼑㼞㼟㼑㼍㼟㻌㻶㼛㼕㼚㼠㻌㻾㼑㼟㼑㼍㼞㼏㼔㻌㻼㼞㼛㼓㼞㼍㼙㻌㻞㻜㻝㻢㻌䛆Joint Research No. CI16-107 䛇
Title of Joint Research: Spatial Characteristics of Land Tenure in Potential area of Agricultural Rice
Field Protection in Indonesia, A case study in Two villages in West Java
Name of Principal Investigator:
Baba Barus 䠄Department of Soil Science and Land Resources, Bogor Agricultural University, Indonesia䠅䛆Abstract䛇 (Approximately 100 words)
The government of Indonesia has program to protect rice field and to improve its productivity. The detail of land
utilization and land tenures are necessary for improving of land productivity through consolidation in planting
and management. Geospatial technology is employed for finding rice field pattern. The results show thedifferent variety of land utilization, between paddy and different crops. The farmer who own land and works
as farmers higher in Cigombong (Bogor), and more intensive and diverse than in Jayakarsa (Sukabumi).
The developed rule implemented for consolidation is block less 0.5 ha and its adjacent land., The average sizeof land after consolidation for management in Ciburay is 0.3 Ha, meanwhile in Jayakarsa is 0.4 Ha.

䠍
BackGround
Objective
Methodology

䠎Background : Rice field protection in Indonesia has been started since 2009 which provide
obligation to many local governments to inventory their agriculture lands, and finally assign themas protection areas. In addition, both central government and local governments have also toprovide incentives for rice farmers, which have consequence that detail data of rice field and its
farmer are necessary. The detail of land utilization and land tenures are necessary for improvingof land productivity through consolidation in planting and management. So far, geospatial
technology has been employed intensively for finding rice field for protection, and it may alsoutilize for finding spatial pattern
The objectives of the study are to find out spatial pattern of land ownership and utilization
based on land parcel and provide criteria for land consolidation in farm management at twovillage (Ciburay, Bogor District and Jayakarsa, Sukabumi City).
The methodology are (1) Investigation of spatial pattern of land utilization, land managed byland owner, land managed by non owner, and other employing spatial method, and (2) finding
criteria for effectively and efficiency in managing land area using size of rice field block/parcel
and it’s connectivity regarding with effective use of hand tractor
Brief descriptions of three (at maximum) conclusions

Conclusions

Conclusion 1 :Land rent farmers is bigger found in Jayakarsa (80%) with majority
lands are planted for paddy (low intensity) than in Ciburay (60%)
and lands are for paddy and horticultural crops (high intensity)
Conclusion 2: Criteria for landconsolidation developed based
operating capacity of hand tractor
over land, and the land with less Fig.1
0.5 ha is chosen, and merging
with adjacent lands

Fig.2 Spatial pattern after trial

land

䠏

Effect/Outcomeconsolidation using hand
tractor in Ciburay, Bogor

Spatial pattern of landownership in Jayakarsa,
Sukabumi, West Java

Conclusion 3:
The effective land management after consolidation is different
with the size is 0.3 Ha in Ciburay , and 0.4 Ha in Jayakarsa
These relate to land ownership status is higher and physicalcharacteristics which more undulating in Ciburay.

The result of this study can be utilized for consolidation of some small rice farms in particular placesuch as in Java, Indonesia, where many small rice blocks exist and work less efficient. However theconcepts are still in preliminary step, which still need more development of more quantitative
parameters.

― 90 ―

㻾㼑㼜㼛㼞㼠㻌㼒㼛㼞㼙㻌㼒㼛㼞㻌㻯㻱㻾㼑㻿㻌㻻㼢㼑㼞㼟㼑㼍㼟㻌㻶㼛㼕㼚㼠㻌㻾㼑㼟㼑㼍㼞㼏㼔㻌㻼㼞㼛㼓㼞㼍㼙㻌㻞㻜㻝㻢㻌䛆Joint Research No. CI16-101䛇
Title of Joint Research:Multi-platform satellite observations for improving retrieval of plant phenology on the Tibetan Plateau
Name of Principal Investigator:
SHEN Miaogen㻌 䠄Institute of Tibetan Plateau Research, Chinese Academy of Sciences䠅䛆Abstract䛇 Tibetan Plateau (TP) plays crucial roles in global carbon cycles. Understanding vegetation
activities on the TP is important for development of carbon cycle models. In this study, the linear regression
and partial regression techniques were applied to satellite NDVI and climate datasets to analyze the heatrequirement for vegetation green-up and responses of vegetation to climate changes. We found that the heatrequirement was different for different vegetation types, and inter-annual variations were driven by the numberof chilling days; the correlation coefficient between growing season NDVI and temperature in in a 15-year
moving window for alpine meadow showed little change.

䠍

BackGround
Objective
Methodology

The background of this study:㻌 Vegetation activity on the Tibetan Plateau grassland has been
substantially enhanced as a result of climate change, as revealed by satellite observations ofvegetation greenness (i.e., the normalized difference vegetation index, NDVI).
The objective of this study: (1) to analyze the changes in heat requirement for vegetation greenup on the Tibetan Plateau during 1998-2012; (2) to reveal the responses of vegetation activity to
climate changes on the Tibetan Plateau grassland.
The methodology of this study: Using NDVI data and meteorological records from 1982 to 2011,
linear regression and partial regression techniques were applied.

䠎Conclusions

Brief descriptions of three (at maximum) conclusions
Conclusion 1:
The accumulated growing degree-days (AGDD) requirement was significantly different for different
vegetation types and showed large spatial variations ranging from a few 䖚C-days in cold and wet areas
to more than 1000 䖚C-days in warm and dry areas of the Tibetan Plateau .
Conclusion 2:
The inter-annual variations in AGDD requirement were extensively driven by the number of chillingdays, while precipitation sum and insolation affected the AGDD requirement in limited areas.
Conclusion 3:
The inter-annual partial correlation coefficient between growing season (May–September) NDVI andtemperature (RNDVI-T) in a 15-year moving window for alpine meadow showed little change, likely
caused by the increasing RNDVI-T in spring (May–June) and autumn (September) and decreasing
RNDVI-T in summer (July–August).

䠏Effect/OutcomeThe result of this study is applied to understand the future projection of vegetation activities on the
Tibetan Plateau.

― 91 ―

㻾㼑㼜㼛㼞㼠㻌㼒㼛㼞㼙㻌㼒㼛㼞㻌㻯㻱㻾㼑㻿㻌㻻㼢㼑㼞㼟㼑㼍㼟㻌㻶㼛㼕㼚㼠㻌㻾㼑㼟㼑㼍㼞㼏㼔㻌㻼㼞㼛㼓㼞㼍㼙㻌㻞㻜㻝㻢㻌䛆Joint Research No. CJ16-106 䛇
Title of Joint Research: Interferometric Synthetic Aperture Radar ALOS PALSAR 2 For Estimation of
Carbon Loss in Tropical Peatland Case Study: Tropical Peatland in Dayun, Siak Regency,
Riau Province - Indonesia

Name of Principal Investigator:
PERISSIN Daniele 㻌 䠄Purdue University 䠅䛆Abstract䛇
Conversion of tropical peatland to others function such as cultivation, oil palm plantation, etc, by human activities,
leads to release carbon from previously stable, resulting subsidence that can be surrogate measureof CO2 loss to the atmosphere. Interferometric synthetic aperture radar (SAR) is a technique that can provide land
displacement map (subsidence) from radar images. By this technique, reclassification is needed to determine thearea of subsidence condition. By the equation that has relationship between carbon loss and water table, andbetween subsidence and water table, carbon loss from this research area was estimated 3.491,833.48 ton CO2 eq,
starting from August 15, 2015 until March 12, 2016

䠍BackGround
Objective
Methodology

The background of this study㻌 is- Interferometric Synthetic Aperture Radar (InSAR) / DInSAR (Differential InSAR)
is a technique that can provide displacement map from radar images. Subsidence in peatlands
area causes carbon loss to the atmosphere (influence to global warming effect)
The objective of this study is
Estimation of carbon loss from peatland area using InSAR analysis
The methodology of this study is
The main idea is how to estimate the carbon loss using the relationship between subsidence
condition in peatland area and carbon loss.

䠎Conclusions

Brief descriptions of three (at maximum) conclusions
Conclusion1
Subsidence in tropical peatland area because of water table decreasing.

Conclusion 2
Based on the subsidence condition, carbon loss in this area isaround 3.491,833.48 ton CO2 eq starting from August 15, 2015
until March 12, 2016

One or Two figures orphotos at maximum

Fig.1 Subsidence in peatland
area

Conclusion 3
Carbon loss due to subsidence in tropical peatlands can be
estimate by this method
Subsidence (cm)
0.6
22
42

Fig.2

䠏

Effect/Outcome

Prosentase
24.015%21.402%
14.485%

Area (Ha)22,664.11
22,664.11
22,664.11

Subsidence Area
5442.79
4850.57
3282.90

Carbon Loss /Ha
11.64
309.26587.40Carbon Loss
63367.00
1500079.73
1928386.27

Total Carbon Loss

3491833.00
ton CO2 eq

Subsidence classificationand carbon loss estimation(examples)
The result of this study is applied to tropical peatland in Indonesia.
The developed method is applied to support of peatland restoration in Indonesia in collaboration
between JMRSL – Ceres, Chiba University, Agency for the Assessment and Application ofTechnology (BPPT), and Peatland Restoration Agency (BGR) - Indonesia― 92 ―

㻾㼑㼜㼛㼞㼠㻌㼒㼛㼞㼙㻌㼒㼛㼞㻌㻯㻱㻾㼑㻿㻌㻻㼢㼑㼞㼟㼑㼍㼟㻌㻶㼛㼕㼚㼠㻌㻾㼑㼟㼑㼍㼞㼏㼔㻌㻼㼞㼛㼓㼞㼍㼙㻌㻞㻜㻝㻢㻌䛆Joint Research No. CI16-112 䛇㻌 Title of Joint Research: Application of space and ground technologies for disaster risk mitigation:
Multi-sensor Web for earthquake early detection.
Name of Principal Investigator:
Dimitar Ouzounov, Chapman University, CA ,USA㻌This proposal represents an innovative approach for integrating multi parameter sensor networks of preearthquake signal caused by increasing stress in the Earth’s crust prior to earthquakes. Latest observations
from space and ground have provided multiple evidences for detection of pre- earthquake signals and thelatest studies show their statistical significance, repeatability, and universality. The objective is thedevelopment of crosscutting Sensor web, which utilizes targeted sensor networks (global remote-sensing
satellite data, space plasma parameters from GPS/TEC, simultaneously with ground observations to detect
pre-earthquake phenomena) in order to achieve a forecast solution.

䠍

BackGround
Objective
Methodology

䠎Conclusions

The background of this study is based on the Lithosphere-Atmosphere- Ionosphere Coupling(Pulinets and Ouzounov, 2010), relating seismicity with the atmospheric /ionospheric signals is
one of the working model for the future Sensor Web system
The primary goal of our efforts will be focused on the validation of the atmospheric earthquake
signals to gain a better understanding of earthquake process and support future application inearthquake monitoring and forecasting
The methodology of this study is the development of crosscutting Sensor web, which utilizes
targeted sensor networks (global remote-sensing satellite data, space plasma parameters from
GPS/TEC, simultaneously with ground observations to detect pre-earthquake phenomena) inorder to achieve a novel solution

Brief descriptions of three (at maximum) conclusions
Conclusion1
Our initial results suggest that systematic use of multi-parameter
observations can be used for additional physical validation ofpre-seismic processes associated with the major earthquake events.
Conclusion 2
Our preliminary results show correlation between theappearance of pre-earthquake transients anomalies inatmosphere and ionosphere (with a short time-lag, from hours
up to few days) and the occurrence of 2016 Kumamoto,Japan earthquake series.

Fig.1 Satellite Thermal
anomaly 04.15.2016

Conclusion 3
Our initial prospective tests show that multi-parameter analysis
could reveal short-term pre-earthquake anomalies prior to
the largest earthquakes.

Fig.2

䠏

Effect/OutcomeTime series of Thermal
Anomalies night time data for2016 (red columns) for locationnear to the Kumamoto.

Our products of long time series (OLR, GPS/TEC, plasma,) over several areas of validation in Japan.
help to justify the abnormal level of change over the expected time scale.
The broader impact of this project includes advancing our knowledge of earthquake phenomena,
towards multisensory observations and data analysis― 93 ―

㻾㼑㼜㼛㼞㼠㻌㼒㼛㼞㼙㻌㼒㼛㼞㻌㻯㻱㻾㼑㻿㻌㻻㼢㼑㼞㼟㼑㼍㼟㻌㻶㼛㼕㼚㼠㻌㻾㼑㼟㼑㼍㼞㼏㼔㻌㻼㼞㼛㼓㼞㼍㼙㻌㻞㻜㻝㻢㻌䛆Joint Research No. CI16-113 䛇•㻌 Title of Joint Research: Characteristics and evidences of seismo-ionospheric precursors in Japan(Study and Test for Ionospheric Earthquake Precursors in Japan).
Name of Principal Investigator:
Jann-Yenq Liu, National Central University, TAIWAN㻌
In this study, we examine the temporal and spatial SIPs (seismo-ionospheric precursors) in the global
ionosphere map (GIM) of the total electron content (TEC) associated with the 2011 M9.0 Tohoku earthquake,and statistically examine temporal variations of the TEC extracted from the GIM over the epicenters of M>=6.0
earthquakes occurring in Japan during 1998-2016. Search existing ionospheric physical models to be
employed simulating and reproducing the SIPs to find the possible mechanisms associated with large
earthquakes in Japan, especially the 2011 M9.0 Tohoku earthquake.

䠍

BackGround
Objective
Methodology

䠎Conclusions

The GIM TEC can be used to locally monitor temporal SIPs at a certain location as well as
globally find the spatial distribution of SIPs. To find whether SIPs appear before the 2011 M9.0
Tohoku earthquake, we examine the GIM TEC associated with M>=6.0 earthquakes occurring inJapan during 1998-2016. To find the possible causal of SIPs, we also search existing models.
The research goals are to use the GIM statistically searching characteristics of temporal andspatial SIPs in the TEC, as well as utilize existing ionospheric physical models to find causal
mechanisms of SIPs associated with large earthquakes in Japan.
To find SIP characteristics of the GIM TEC, we not only apply the z test (Neter et al, 1988) tosearch for the statistical significance of the anomaly, but also employ the receiver operating
characteristic (ROC) curve (Swets, 1988) to confirm the SIP associated with the earthquakes inJapan. Existing models are used to reproduce the observed SIPs for finding causal mechanisms.
Brief descriptions of three (at maximum) conclusions
Conclusion1
The z test at significance level 0.05 shows the SIPs appears in different time/day zones prior tothree group of earthquakes (84              2016.
Conclusion 2
The ROC curves and the associated p-value indicate that a significant TEC enhancements(positive anomalies) in six zone, Zone A (1-2 days before, 0600-1000LT), Zone B (2-3 days
before,1900-2200LT, Zone C (2-3 days before, 0700-1000LT), Zone D (9-10 days before,15002100LT), Zone E (2-3 days before, 0100-0300LT), and Zone F (1-3 days before, 0700-0900LT)
yield reliable SIPs for three group earthquakes in Japan, respectively. Zone F yields thegreatest AUC (area under the curve), which agrees the appearance days of SIPs of the Tohoku
earthquake.
Conclusion 3
The average of median of the SIP strength (!") is increasing with the associated earthquake
magnitude and is closely related to the associated AUC. It implies that larger earthquakes havethe greater preparation, and in turn release a stronger SIP of GPS TEC.

䠏

Effect/Outcome

Our products of the statistical analyses show that the SIP characteristic of the GIM TEC in Japan are
positive polarity, local time in early morning, lead time of 1-3 days. This can be used to detect andindentify the temporal SIPs of the TEC in Japan.
On the other hand, the strength of SIP seems to be useful to predict forthcoming earthquake
magnitude.

― 94 ―

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boe! Tfotps! Ufdiopmphz! gps! Ivnbojubsjbo! Efnjojoh! boe! Dpvoufs!ĪJFEt! STU! 3127ī
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Ć Nvibnnbe! Gbv{bo! Fez! Qvsopnp-! Sbinbexbuj-! Ibej! Tvzpop-! Svez! Zvxpop-! boe! Kptbqibu! Ufuvlp!
Tsj! Tvnbouzp-!ĨEfwfmpqnfou! pg! M.Cboe! Boufoob! xjui! Mpx! Qpxfs! gps! Djsdvmbsmz! Qpmbsj{fe.Tzouifujd!
Bqfsuvsf! Sbebs!ĪDQ.TBSī!Bqqmjdbujpo! po! Vonboofe! Bfsjbm! Wfijdmf-ĩ!Uif! 8ui! Joepoftjb! Kbqbo! Kpjou!
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-!Q167-!31.35!Opwfncfs!3127!
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Tztufn! gps! Njdsptbufmmjuf! Dpnnvojdbujpot-ĩ!Uif! 8ui! Joepoftjb! Kbqbo! Kpjou! Tdjfoujgjd! Tznqptjvn!
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pg! Tzouifujd! Bqfsuvsf! Sbebs! pocpbse! Bjsdsbgu! boe! Njdsptbufmmjuf! gps! Hmpcbm! Mboe! Efgpsnbujpo!
Pcfswbujpo-ĩ!Uif! 8ui! Joepoftjb! Kbqbo! Kpjou! Tdjfoujgjd! Tznqptjvn!Ī JKKTT! 3127ī
-! Q173-! 31.35!
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Tvnbouzp-! boe! Ijspblj! Lv{f-!ĨDmpve! Sfusjfwbm! boe! Dmpve! Uzqf! Efufdujpo! gspn! Ijnbxbsj.9! Tbufmmjuf!
Ebub! Cbtfe! po! Uif! Tqmju! Xjoepx! Bmhpsjuin-ĩ!Uif! 8ui! Joepoftjb! Kbqbo! Kpjou! Tdjfoujgjd! Tznqptjvn!
ĪJKKTT!3127ī-!Q221-!31.35!Opwfncfs!3127!
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Ć Epej! Tvejbob-! Sfuop! Xjhbkbusj! Qvsobnbojohtji-! Tbsbi! B{! [bisb-! Cbncboh! Tfujbej-! boe! Kptbqibu!
Ufuvlp! Tsj! Tvnbouzp-!ĨEfgpsnbujpo! Bobmztjt! pg! Nfsbqj! Wpmdbop! vtjoh! EJoTBS! nfuipe! po! BMPT0QBMTBS! Jnbhf-ĩ!Uif! 8ui! Joepoftjb! Kbqbo! Kpjou! Tdjfoujgjd! Tznqptjvn!ĪJKKTT! 3127ī
-! Q239-! 31.35!
Opwfncfs!3127!ĪDijcb!;!JKKTTī
Ć Epej! Tvejbob-! Sfuop! Xjhbkbusj! Qvsobnbojohtji-! Tvmjtujzbojohtji-! Cbncboh! Tfujbej-! boe! Kptbqibu!
Ufuvlp!Tsj!Tvnbouzp-!ĨBobmz{joh!Mboe!Vtf!boe!Mboe!Dpwfs!vtjoh!Dpncjofe!Mboetbu!9!boe!BMPT.30
QBMTBS.3!Ebub.Dbtf!Tuvez!;!Cboevoh!Sfhfodz-ĩ!Uif!8ui!Joepoftjb!Kbqbo!Kpjou!Tdjfoujgjd!Tznqptjvn!
ĪJKKTT!3127ī-!Q23:-!31.35!Opwfncfs!3127!ĪDijcb!;!JKKTTī
Ć Bhvt!Ifoesb!Xbizvej-!Kptbqibu!Ufuvlp!Tsj!Tvnbouzp-!Iffjo!Zboh-!Nbutvnvsb!Lpifj-!boe!Zvub!J{vnj-!
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po!VBW-ĩ!Uif!8ui!Joepoftjb!Kbqbo!Kpjou!Tdjfoujgjd!Tznqptjvn!ĪJKKTT!3127ī-!Q241-!31.35!Opwfncfs!
3127!
ĪDijcb!;!JKKTTīĆ Lbjifj! Oblbnvsb-! Kptbqibu! Ufuvlp! Tsj! Tvnbouzp-! Dbizb! Fej! Tbouptb-! boe! Btjg! Bxbmvejo-!ĨTuvez! pg!
7.npevmf! Y.Cboe! Bssbz! Boufoob! gps! Bjscpsof! DQ.TBS! Bqqmjdbujpo-ĩ!Uif! 8ui! Joepoftjb! Kbqbo! Kpjou!
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-!Q244-!31.35!Opwfncfs!3127!ĪDijcb!;!JKKTTī
Ć Nbtbsv! Cvozb-! Lb{vufsv! Obncb-! boe! Kptbqibu! Ufuvlp! Tsj! Tvnbouzp-!ĨDQ.TBS! Jnbhf! Qspdfttjoh!
Tztufn! xjui! Ljoufy.8! GQHB! Cpbse-ĩ!Uif! 8ui! Joepoftjb! Kbqbo! Kpjou! Tdjfoujgjd! Tznqptjvn!ĪJKKTT!
3127ī-!Q25:-!31.35!Opwfncfs!3127!
ĪDijcb!;!JKKTTī
Ć Bljsb! Lbup-! Zvjdij! Ibzblbxb-! Ijspzvlj! Pcbobxb-! Lpkj! Lbkjxbsb-! Zptijblj! Ipoeb-! Nbtvup! Fcjob-! boe!
Kptbqibu!Ufuvlp!Tsj!Tvnbouzp-!ĨGpsftu!Ejtbtufs!Npojupsjoh!vtjoh!Hpphmf!Fbsui!Fohjof-!VBW.TgN-!boe!

― 99 ―

Ufssftusjbm!Mbtfs!Tdboofs-ĩ!Uif!8ui!Joepoftjb!Kbqbo!Kpjou!Tdjfoujgjd!Tznqptjvn!ĪJKKTT!3127ī-!Q273-!
31.35!Opwfncfs!3127!ĪDijcb!;!JKKTTīĆ Qblisvs! Sb{j-! Ivtovm! Lbvtbsjbo-! Hppe! Gsjfe! Qbohhbcfbo-! Njs{b! Nvibnnbe! Xbrbs-! Ebojfmf! Qfsjttjo-!
boe!Kptbqibu!Ufuvlp!Tsj!Tvnbouzp-!ĨWfmpdjuz!boe!Ujnf!Tfsjft!Mboe!Efgpsnbujpo!Npojupsjoh!jo!Tmpqf!
Bsfb! Vtjoh! QTJ! TBS! ;! Dbtf! Tuvez! jo! Lfmpl! :! Csjehf! Xftu! Tvnbusb-ĩ!Uif! 8ui! Joepoftjb! Kbqbo! Kpjou!
Tdjfoujgjd!Tznqptjvn!ĪJKKTT!3127ī
-!Q277-!31.35!Opwfncfs!3127!
ĪDijcb!;!JKKTTīĆ Divb!Njoh!Zbn-!Lpp!Wppo!Difu-!Mjn!Ifoh!Tjpoh-!Dibo!Zff!Lju-!boe!Kptbqibu!Ufuvlp!Tsj!Tvnbouzp-!
ĨQibtf! Dpefe! Tufqqfe! Gsfrvfodz! Mjofbs! Gsfrvfodz! Npevmbufe! Xbwfgpsn! Tzouifujt! Ufdiojrvf! gps!
Vmusb.Xjefcboe!Tzouifujd!Bqfsuvsf!Sbebs-ĩ!Uif!8ui!Joepoftjb!Kbqbo!Kpjou!Tdjfoujgjd!Tznqptjvn!
ĪJKKTT!
3127ī-!Q279-!31.35!Opwfncfs!3127!ĪDijcb!;!JKKTTīĆ Jowjufe! Mfduvsf! ;! Kptbqibu! Ufuvlp! Tsj! Tvnbouzp-!Ĩ Efwfmpqnfou! pg! DO.346! NQB! MQ0DQ.TBS-ĩ!
Sftfbsdi!Dfoufs!Cbmjucboh-!Joepoftjbo!Njojtusz!pg!Nbsjujnf!boe!Gjtifsz!Ľ!Lfnfoufsjbo!Lfmbvubo!ebo!
Qfsjlbobo!ĪLLQī-!Bodpm-!5!Bqsjm!3127
Ć Jowjufe! Mfduvsf! ;! Kptbqibu! Ufuvlp! Tsj! Tvnbouzp-!ĨEfwfmpqnfou! pg! Njdsptbufmmjuf! TBS-ĩ!QU! MFO!
Cboevoh-!8!Bqsjm!3127
Ć Jowjufe!Ubml!;!Kptbqibu!Ufuvlp!Tsj!Tvnbouzp-!ĨBewbodfe!Njdspxbwf!Sfnpuf!Tfotjoh!Ufdiopmphjft!gps!
Hmpcbm!Nbsjujnf!Byjt-ĩ
!PJTBB!Btjb!Ľ!Pdfbojb!Tznqptjvn!3127-!Vojwfstjuz!pg!Ipohlpoh-!:!Bqsjm!3127
Ć Jowjufe!Ubml!;!Kptbqibu!Ufuvlp!Tsj!Tvnbouzp-!Opcvzptij!Jnvsb-!boe!Spcfsuvt!Ifsv!Usjibsekboup-!ĨDQ.
TBS! pocpbse! Njdsptbufmmjuf! gps! Hmpcbm! Mboe! Efgpsnbujpo! Pctfswbujpo-ĩ!Npojupsjoh! boe! Qsfejdujpo! pg!
Ejtbtufst-!I.ET18.18-!212C-!Kbqbo!Hfptdjfodf!Vojpo!ĪKqHVī!Nffujoh!3127-!Nblvibsj!Nfttf-!Kbqbo!
35!Nbz!3127-!Kbqbo!Hfptdjfodf!VojpoĆ ஽൒ਆ‫ !ܩ‬Jowjufe! Ubml! ;! ိ౰39༃๱! ൦Ǎ‫ !ޑ‬൥ߔຑॸ࢞ৄᆔʍ˅ˋ!Ī൦41‫ޑ‬īĨ൥ߔཡ! ਗ౰ާ৏˄Ĝʘ຃੪!
ჟఱਂऋ࡙Ćਂऋ࡙Ćழळ‫ܒ‬౳Ɉާཡĩ!ຄ葛ʞʇʦʯˁʎĂ3127༃Ǔॢ39໲
Ć Hvftu!Mfduvsfs!;!Kptbqibu!Ufuvlp!Tsj!Tvnbouzp-!
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-!31!Tfqufncfs!3127-!Uif!Tbouptb!Ipubm-!Tfohjhj-!Mpncpl-!Joepoftjb!
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Ć Jowjufe! Ubml! ;! Kptbqibu! Ufuvlp! Tsj! Tvnbouzp-!ĨEfwfmpqnfoe! pg! Bewbodfe! Tzouifujd! Bqfsuvsf! Sbebs!
gps!VBW-!Bjsdsbgu!boe!Njdsptbufmmjuf-ĩ!BBV-!Zpzblbsub-!Joepoftjb-!24!Pdupcfs!3127
Ć Hfofsbmf! Mfduvsf! ;! Kptbqibu! Ufuvlp! Tsj! Tvnbouzp-!ĨEfwfmpqnfou! pg! Bewbodfe! Tzouifujd! Bqfsuvsf!
Sbebs! pocpbse! VBW-! Bjsdsbgu-! boe! Njdsptbufmmjuf! gps! Fbsui! Tvswfjmmbodf-ĩ!Joepoftjbo! Djwjm! Bwjbujpo!
Jotujuvuf!
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Ć Hfofsbmf! Mfduvsf! ;! Kptbqibu! Ufuvlp! Tsj! Tvnbouzp-!ĨEfwfmpqnfou! pg! Bewbodfe! Njdsptbufmmjuf! TBS!
pocpbse! gps! Hmpcbm! Fowjsponfoubm! Sfnpuf! Tfotjohĩ-! Gbdvmuz! pg! Fohjoffsjoh-! Obujpobm! Vojwfstjuz! pg!
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-!Lfoujohbo-!Tpmp-!31!Kbovbsz!3128
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Ć Ublbp! Lpzbnb-! Ublbzvlj! Lboflp-! Ublbp! Pinjobup-! Butvtij! Xbubobcf-! Njopsv! Ublfp-Ublbuptij!
Zbobhjtbxb-!boe!Zptijblj!Ipoeb-ĩ!Sfqfbufe!bfspnbhofujd!tvswfzt!jo!Tijonpf.eblf!wpmdbop-!Kbqbo!cz!
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Ī3127ī;! Vujmj{bujpo! pg! IJNBXBSJ.9! gps! gppe! tfdvsjuz;! Gppe! tfdvsjuz! qbdlbhf! boe! sfmbuf! bdujwjujft! jo!
DFSfT!boe!sfmbufe!sftfbsdifst-!Uif!3127!FVNFUTBU!Nfufpspmphjdbm!Tbufmmjuf!Dpogfsfodf-!3127༃Ǖॢ37໲ġ41໲!ĪEbsntubeu-!Hfsnbozī/ĪႨࣕಫ୽ī
Ć Dijibsv! Ipohp-! Dijlblp! Phbtbxbsb-! Fjtblv! Ubnvsb-! Hvobsej! Tjhju-! Vtf! pg! tbufmmjuf! ebub! up! jnqspwf!
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Ć Dijibsv!Ipohp-!Dijlblp!Phbtbxbsb-!Fjtblv!Ubnvsb!boe!Hvobsej!Tjhju-!Ftujnbujpo!pg!sjdf!zjfme!bggfdufe!

― 100 ―

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Sfofxbcmf! Fofshz! Ftujnbujpo-! Uif! Joufsobujpobm! Sfhjbujpo! Tznqptjvn! 3127-! Vojwfstjuz! pg! Bvdlmboh!
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B/! Qjufst-! O/! Ibp-! N/! Ujfgfohsbcfs-! K/! Ifsnbo-! O/! Bcvibttbo-! S/! Ipmmb-! B/! Cbjt-! E/! Cbmjt-! O/! Lpvsfnfuj-!
K/! Ipwjmb-! K/! Dipoh-! P/! Qptuzmzblpw-! K/! Nb-! G/! Hpvubjm-! K/.Q/! Qpnnfsfbv-! B/! Qb{njop-! N/! Obwbssp-! boe!
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I/! Ublbtijnb-! Z/! Lpnb{blj-! I/! Ubojnpup-! boe! [/! Xboh-! Qipupdifnjdbm! P{pof! Qspevdujpo! Sbuft!
boe! Mjnjujoh! Gbdupst! pwfs! Fbtu! Btjb;! Jnqbdu! pg! Sbejdbm! Difnjtusz! Nfdibojtn! boe! P{pof.Dpouspm!
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Wbmjebujpo! pg! sfqspdfttfe! HPNF.3! IDIP! boe! OP3! dpmvnot! vtjoh! hspvoe.cbtfe! NBYEPBT! dpmvno!
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Ć Jsjf-! I/-! U/! Ublbnvsb-! Q/! Libusj-! I/! Plbnpup-! U/! Ibublfzbnb-! T/! Povnb-! B/! Ebnjboj-! U/! Ipsjp-! U/!
Ublbop-! U/! Z/! Oblbkjnb-! U/! Oblbkjnb-! U/! Ojtij{bxb-! boe! TLZOFU! dpnnvojuz-! Wbmjebujpo! pg! HDPN.D!
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Ć Jsjf-! I/-! Wbmjebujpo! qmbo! gps! HDPN.D! bunptqifsf! qspevdut-! Kpjou! QJ! Nffujoh! pg! Hmpcbm! Fowjsponfou!
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ĪUplzpī-!Kbovbsz!38-!3128
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Ć Jnqbdu!pg!mjof!qbsbnfufs!ebubcbtf-!dpoujovvn!bctpsqujpo-!gvmm!hsjoe!dpogjhvsbujpo-!boe!M2C!vqebuf!po!
HPTBU! UJS! nfuibof! sfusjfwbm-! Bljopsj! Zbnbeb-! Obplp! Tbjupi-! Szptvlf! Opophblj-! Szpjdij! Jnbtv-! Lfj!
Tijpnj-!Bljijlp!Lv{f-!BHV!Gbmm!Nffujoh!3127
Ć Fwbmvbujpo!pg!cjbt!jo!mpxfs!boe!njeemf!uspqptqifsjd!HPTBU0UBOTP.GUT!UJS!W2/1!DP3!ebub!uispvhi!
dpnqbsjtpot!xjui!bjsdsbgu!boe!OJDBN.UN!DP3!ebub-!O/!Tbjupi-!I/!Ibuub-!S/!Jnbtv-!L/!Tijpnj-!B/!Lv{f-!Z/!
Ojxb-!U/!Nbdijeb-!Z/!Tbxb-!boe!I/!Nbutvfeb-!Bnfsjdbo!Hfpqiztjdbm!Vojpo!
ĪBHVī!Gbmm!Nffujoh-!3127
Īᅔā‫ڰ‬īĆ Ijlefj!Lpcbzbtij-!Xfj!Zboh-!Lb{vijup!Jdijj-!Dpnqbsjtpo!pg!uif!tjnvmbufe!uif!dbopqz!tdbmf!tvo.joevdfe!
dimpspqizmm!gmvpsftdfodf!boe!tbufmmjuf.cbtfe!TJG!nfbtvsfnfout!jo!opsuifso!ijhi!mbujuveft-!Hpmetdinjeu!

― 101 ―

Dpogfsfodf-!Kvof!3127-!Zplpibnb-!Kbqbo
Ć Xfj! Zboh-! Ijeflj! Lpcbzbtij-! Bljijlp! Lpoepi-! Ftujnbujpo! pg! Pwfstupsz! boe! Voefstupsz! Mfbg! Bsfb!
Joefy!jo!Ijhi!Opsuifso!Gpsftut!cz!NPEJT!CSEG!boe!Sfgmfdubodf!Qspevdut-!Bjtb!Pdfbojb!Hfptdjfodf!
Tpdjfuz-!Bvhvtu!3127-!Cfjkjoh-!Dijob
Ć Xfj! Zboh-! Ijeflj! Lpcbzbtij-! Bljijlp! Lpoepi-! B! Gpsftu! Tusvduvsf! Ezobnjdt! Npefm! gps! Esjwjoh! Uisff.
Ejnfotjpobm!Dbopqz!Sbejbujwf!Usbotgfs!Tjnvmbujpot-!Bnfsjdbo!Hfpqiztjdbm!Vojpo-!Efdfnfs!3127-!Tbo.
Gbodjtdp-!VTBĺਡ໘‫ࡼޏ‬ĻĪ࢏౦৘ცīĆ ྅ೲ೑ሆĂᤁા෸ৠĂ࢏౦৘ცĂ‫ܒ‬౳‫ކ‬ജɬᅙȞȹණ࿍ჶཱଗᆎɂ൥࡜৉ߔโৎȯɈວ૪ైฤၭɈ‫ޜ‬ᆯĂ໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫ޏ‬൦71‫ޑ‬Īိ౰39༃๱୽ࡠīߔ୹ਆ‫ޏܩ‬ĂC13Ă3127༃Ǒॢ23໲Ğ24໲!Ī໲൥୔ૂᄘīĆ ࢏౦৘ცĂOpgfm! MbhsptbtĂKbnsve! BnjoveejoĂᤁા෸ৠĂൎᆔ५ʀɺ˅ʖ˃Ɉණ௫ʍˋʯ˂ˋʈʟĜʗɂ৉ߔູ౯Ɉ࠲बĂ໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫ޏ‬൦71‫ޑ‬Īိ౰39༃๱୽ࡠīߔ୹ਆ‫ޏܩ‬ĂC14Ă3127༃Ǒ
ॢ23໲Ğ24໲!
Ī໲൥୔ૂᄘīĆ ञટ०໩Ăᤁા෸ৠĂႨ࠰਑ࡦĂഺ௄‫ݡ‬໖ાĂࢀഺॾ‫ێ‬Ăழ໤ᄽૂĂ࢏౦৘ცĂબ೧ B ʨˋʡɬᆀᅙȱȹʇ˅˅ʭɻ˃ॊ৉Ɉယ৉‫ކ‬ജोപć౉๜ĆఝᆹɒɈܾᅙĂ໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫ޏ‬൦71‫ޑ‬Īိ౰39༃๱୽ࡠīߔ୹ਆ‫ޏܩ‬ĂC24Ă3127༃Ǒॢ!23໲Ğ24໲!Ī໲൥୔ૂᄘīĆ Ⴢ‫ୃࡹ܊‬ĂৡࢀථცĂᤁા෸ৠĂඹ໘‫ܤ‬࿧Ă࢏౦৘ცĂ਒ʑʲʇʠ˃ယ‫ސ‬༑ˁɼʘĜɈ౿੼ɂˁɼʘĜ྘Ɉຩ୸Ă
൦45‫˄ޑ‬ĜʎʓˋʏˋʈʏˋʵʐɾʸĂQD27Ă3127༃Ǖॢǔ໲ĞǕ໲!Īᄘ൲‫ݗ‬ಶʋˋʱˋʏʿˋʳĜ˃īĆ Kbnsve! Bnjoveejo-! Upnpblj! Utvofzptij-! Zptijlj! Tvfobhb-! Obpijsp! Nbobhp-! boe! Ijspblj! Lv{f-!
Qmbo! Qptjujpo! Joejdbups!ĪQQJī!Mjebs! Nfbtvsfnfou! pg! Ipsj{poubm! Ejtusjcvujpo! pg! Bfsptpm! Fyujodujpo!
Dpfggjdjfou-!൦45‫˄ޑ‬ĜʎʓˋʏˋʈʏˋʵʐɾʸĂQD2:Ă3127༃Ǖॢǔ໲ĞǕ໲!
Īᄘ൲‫ݗ‬ಶʋˋʱˋʏʿˋʳĜ˃īĆ ৡࢀථცĂჂ‫ୃࡹ܊‬ĂBmjnveejo! KbnvsveĂᤁા෸ৠĂ࢏౦৘ცĂණ௫ʍˋʯ˂ˋʈʟĜʗɂɈ྘ߏɬɛȰȱȹˁʶˋˁɼʘĜɈ‫ޜ‬೑Ă൦45‫˄ޑ‬ĜʎʓˋʏˋʈʏˋʵʐɾʸĂQD8Ă3127༃Ǖॢǔ໲ĞǕ໲!Īᄘ൲‫ݗ‬ಶʋˋʱˋʏʿˋʳĜ˃īĆ ञટ०໩Ăᤁા෸ৠĂႨ࠰਑ࡦĂ࢏౦৘ცĂാᅣ৉ɬᆀᅙȱȹदᅶ˄ʱ˃ɁɈʑʗˋʡʂʭఆဘॊപฤĂ໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫!ޏ‬൦72‫ޑ‬Īိ౰39༃๱୑ࡠīߔ୹ਆ‫ޏܩ‬ĂT6Ă3217༃22ॢǍ໲Ğǎ໲!Īఛߟʞ˃ʍīĆ ྅ೲ೑ሆĂᤁા෸ৠĂ࢏౦৘ცĂණ࿍ჶཱଗᆎɂ൥࡜Ɉ৉ߔโৎȯɈວ૪ైฤၭɅȤȫɥཱဌ‫ސ‬Ɉ౯ଋĂ໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫!ޏ‬൦72‫ޑ‬Īိ౰39༃๱୑ࡠīߔ୹ਆ‫ޏܩ‬ĂC25Ă3217༃22ॢǍ໲Ğǎ໲!
Īఛߟʞ˃ʍīĪࣷນூྷī
Ć Usvpoh! Ohvzfo! Dvoh! RvfĆUpbo! Uiboh! OHVZFOĆOhvzfo! Ipoh! RvboĆࣷນூྷĪ3127/:/27īć
Rvboujgzjoh! uif! jnqbdu! pg! mboe! vtf0mboe! dpwfs! dibohft! boe! dmjnbuf! wbsjbcjmjuz! po! izespmphz! jo!!
Wjfuovnħt!Epoh!Obj!vqtusfbn!sjwfs!cbtjoĂ౉ဦĆ౉૝঍ߔ‫ޏ‬3127༃๱ॸ࢞ཡ࿍‫ޏ‬Īဏ๿īĆ ࿝๜ఙᄓĆ៤āࠀĆࣷນூྷĪ3127/6ī
ćழळ VBWĂฤ๘ʃʹˁɅɢɥۗᘧைᆔ‫ۊ‬ठ༐ರɅȤȫɥެᅰఆဘ
ʺʣʗ˂ˋʈĂ໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬3127ĪႷෟʹʛʓਡ੫‫ࡼޏ‬௲īĆ ៤āࠀĆႊॢāຼĆป݊য়࿧Ć๜ෂāऱĆࣷນூྷĪ3126/6ī
ćഽ૪ࡖࣷಞऋએ‫ކ‬ജɅɢɥ౉‫ے‬Ɉʭɿʦ˅ʐĜࠫപɂ౺‫ۋ‬ʩˁʹĜʗĜɈైฤĂ໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬3127ĪႷෟʹʛʓਡ੫‫ࡼޏ‬௲īĆ ๜ෂāऱĆࣷນூྷĪ3127/6īć3125ġ3126༃ɅȤȫɥ VBW ɬᅙȞȹ౉‫ے‬౺‫ʺۋ‬ʣʗ˂ˋʈɈ౰‫ݪ‬Ă໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬3127ĪႷෟʹʛʓਡ੫‫ࡼޏ‬௲īĆ ࿫ሆၣ‫ݙ‬Ć፛డ߆໲ߖĆࣷນூྷĆಫ୽ႨࣕĆ๜ഺ‫੼܉‬Ī3127/6īćഽ૪ࡖ MBOETBU ʟĜʗɬᅙȞȹʳ˃ʙˋණ‫ۊ‬Ɉ๲ණᆀᅙဿೋɅ࠲ȳɥॳບĂ໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬3127ĪႷෟʹʛʓਡ੫‫ࡼޏ‬௲īĆ ዁ā৮ĆࣷນூྷĪ3127/6īćෂਡ‫ݸ‬႘ိঈɅȤȫɥ๷ழདྷɈ༔ૢᇗဿ‫ݛ‬Ʌ࠲ȳɥॸ࢞Ă໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬3127ĪႷෟʹʛʓਡ੫‫ࡼޏ‬௲ī
Ć Usvpoh! Ohvzfo! Dvoh! RvfĂOhvzfo! Ipoh! RvboĂࣷນூྷĪ3127/6īć!ʱʠʢʸ ¦ ʡˋʢɼರᆔ‫ۊ‬௫ᆔငɅȤȫɥ๲ණᆀᅙğ๲ණྡဒဿ‫ݛ‬Ʌɢɥ‫ݭ‬ರᆔ࣍ဿ‫ݛ‬Ʌ࠲ȳɥॸ࢞Ă໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬3127ĪႷෟʹʛʓਡ੫‫ࡼޏ‬௲ī

― 102 ―Ć ࣷນூྷĆᄄႨৰ‫ێ‬Ć଴ൣᄄোࡊĪ3127/6/33ī
ćࠞࣃᄎ൨Ɉএ௲ɅȤȫɥ‫ߔݨ‬ଞɂʑʞĜʇʳ˃ʘĜɈࢾລćࠞࣃᄎ൨Ɉএ௲ɅȤȫɥ Tdjfoujtut ɂ Tublfipmefst ɂɈࢾລĂ໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬3127ĪႷෟʹʛʓਡ੫‫ࡼޏ‬௲īĆ ࣷນூྷĪ3127/6/33īćঈાᆵ੠ޮɅȤȫɥ‫ߔݨ‬ଞɂʑʞĜʇʳ˃ʘĜɈࢾລɈȜɤၫćࠞࣃᄎ൨Ɉএ௲Ʌ
Ȥȫɥ Tdjfoujtut ɂ Tublfipmefst ɂɈࢾລĂ໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬3127ĪႷෟʹʛʓਡ੫‫ࡼޏ‬௲īĆ ࣷນூྷĪ3127/6/33īćۗᘧைᆔ‫౉ۊ‬ஃࠞ०೔‫ݛ‬ɬଲɤࠆȩʠˁˋʑʟɻʏʯ˂ʢ˂ʞɻĜćࠞࣃᄎ൨Ɉএ
௲ɅȤȫɥ Tdjfoujtut ɂ Tublfipmefst ɂɈࢾລĂ໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬3127ĪႷෟʹʛʓਡ੫‫ࡼޏ‬௲īĪˀʍʭɹʛʠ!ʞʠʁʋ!ʑ˂!ʑʶˋʞɻˀīĨGQHB ɅɢɥഽᅕɄ‫ކ‬ജʍɼʒൎܾɈ DQ.TBSĆ ဦ‫ݎ‬ā஧Ă໧༜‫ࡩێ‬ĂKptbqibu! Ufuvlp! Tsj! TvnbouzpĂ
‫ކ‬ജஐᆅʏʑʞʸĩĂ๝ા௶ၡฆఒߔ‫࡙ !ޏ‬༑ୠಓ௶ၡʏʑʞʸॸ࢞‫ޏ‬ĪGvodujpobm! Joufhsbufe! Jogpsnbujpo!
Tztufn!īĂǒॢ3127༃
Ć ಶāᄬാĂEfnjsdi!TifwlfuĂNpie/![bgsj!CbibsveejoĂᅔāᾀలĂKptbqibu!Ufuvlp!Tsj!TvnbouzpĂĨ‫ܟ‬ှ༜ʭ˃ʵˁ˂ʹʠ˂ʛʇਗ౰ާ৏˄ĜʘɈ࿈ஈ˂ʭ˄ʇʗɬᅙȞȹ෸ೀɼˋʨĜʑ TBS ଌঅĩĂTBS ʓʛ
ʏʿˋĂ൦71‫ޑ‬Īိ౰39༃๱୽ࡠīߔ୹ਆ‫ޏܩ‬໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫ޏ‬Ă໲Ⴈ൥ߔ෿๜ைʅʻˋʩʑĂ
3127༃Ǒॢ23໲
Ć Kptbqibu! Ufuvlp! Tsj! Tvnbouzp! boe! Opcvzptij! Jnvsb-!ĨSftfbsdi! Qsphsftt! po! Tzouifujd! Bqfsuvsf!
Sbebs! gps! Bjsdsbgu! boe! Njdsptbufmmjuf-ĩ!ʏʑʞʸʓʛʏʿˋĂ൦71‫ޑ‬Īိ౰39༃๱୽ࡠīߔ୹ਆ‫ޏܩ‬໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫ޏ‬Ă໲Ⴈ൥ߔ෿๜ைʅʻˋʩʑĂ3127༃Ǒॢ24໲
Ć Livmevnvs!Vzbohb!boe!Kptbqibu!Ufuvlp!Tsj!Tvnbouzp-!ĨQfstjtufou!Tdbuufsfs!Joufsgfspnfusz!gps!Mboe!
Tvctjefodf! jo! Uplzp! bsfb-ĩ! ൦71‫ޑ‬Īိ౰39༃๱୽ࡠīߔ୹ਆ‫ޏܩ‬໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫ޏ‬Ă໲Ⴈ൥ߔ෿๜ைʅʻˋʩʑĂ3127༃Ǒॢ24໲Ć ဦ‫ݎ‬ā஧Ă໧༜‫ࡩێ‬ĂKptbqibu! Ufuvlp! Tsj! Tvnbouzp-ĨGQHB ɅɢɥഽᅕɄ‫ކ‬ജʍɼʒൎܾɈ DQ.TBS ‫ކ‬ജஐᆅʏʑʞʸĩĂ๝ા௶ၡฆఒߔ‫ޏ‬ĂGJJTĂǒॢ28໲
Ć Zvub! J{vnj-! Tfwlfu! Efnjsdj-! [bgsj! Cbibsveejo-! boe! Kptbqibu! Ufuvlp! Tsj! Tvnbouzp-!Ĩ Tuvez! pg!
Qpmbsjnfusjd! Dbmjcsbujpo! gps! Djsdvmbsmz! Qpmbsj{fe! Tzouifujd! Bqfsuvsf! Sbebs-ĩ!Dbmjcsbujpo! Nfuipepmphz!
boe!Ufdiojrvf!J-!DFPT!TBS!Dbmjcsbujpo!boe!Wbmjebujpo!Xpsltipq!3127-!8!Tfqufncfs!3127!ĪUplzp!;!
Uplzp!Efolj!VojwfstjuzīĆ Kptbqibu! Ufuvlp! Tsj! Tvnbouzp-! Opcvzptij! Jnvsb-! boe! Spcfsuvt! Ifsv! Usjibsekboup-!ĨEfwfmpqnfou! pg!
Djsdvmbsmz! Qpmbsj{fe! TBS! pocpbse! VBW-! Bjsdsbgu! boe! Njdsptbufmmjuf-ĩ!Joopwbujwf! TBS! Dpodfqu-! DFPT!
TBS!Dbmjcsbujpo!boe!Wbmjebujpo!Xpsltipq!3127-!:!Tfqufncfs!3127!
ĪUplzp!;!Uplzp!Efolj!Vojwfstjuzī
Ć Lbujb!Vsbub!Obhbnjof!boe!Kptbqibu!Ufuvlp!Tsj!Tvnbouzp-!ĨEftjho!pg!bo!M.Cboe!Efqmzpbcmf!Qbsbcpmjd!
Nfti!Boufoob!Tztufn!gps!b!DQ.TBS!Njdsptbufmmjuf-ĩ!Joopwbujwf!TBS!Dpodfqu-!DFPT!TBS!Dbmjcsbujpo!
ĪUplzp!;!Uplzp!Efolj!Vojwfstjuzī
boe!Wbmjebujpo!Xpsltipq!3127-!:!Tfqufncfs!3127!
Ć Lbhfblj! Jopvf-! Kptbqibu! Ufuvlp! Tsj! Tvnbouzp-! Bhvt! Ibsuplp-! B! Gbnb-! Ijspblj! Lv{f-!Ĩ Uif!
bsdifpmphjdbm! jowftujhbujpo! pg! uif! dfousbm! Kbwb! bqqmzjoh! uif! bewbodfe! sfnpuf! tfotjoh! ufdiopmphz-ĩ!
Bctusbdu!Qspdffejoht!pg!uif!72ui!Bvuvno!Dpogfsfodf!pg!Uif!Sfnpuf!Tfotjoh!Tpdjfuz!pg!Kbqbo-!Q47-!
Opwfncfs!2.3-!3127!ĪOjjhbub!;!Ojjhbub!VojwfstjuzīĆ Zvub! J{vnj-! U!Xbubobcf-! Npie! [bgsj! Cbibsveejo-! Tfwlfu! Efnjsdj-! Iffjo! Zboh-! Kptbqibu! Ufuvlp! Tsj!
Tvnbouzp-!ĨUif!bsdifpmphjdbm!jowftujhbujpo!pg!uif!dfousbm!Kbwb!bqqmzjoh!uif!bewbodfe!sfnpuf!tfotjoh!
ufdiopmphz-ĩ!Bctusbdu!Qspdffejoht!pg!uif!72ui!Bvuvno!Dpogfsfodf!pg!Uif!Sfnpuf!Tfotjoh!Tpdjfuz!
pg!Kbqbo-!C:-!Opwfncfs!2.3-!3127!ĪOjjhbub!;!Ojjhbub!VojwfstjuzīĆ ‫ݡ‬ນā঄Ăଭᆹᄽ་ĂഁರᄽቃĂழ‫ݴ‬ሆ৘་Ăˀʍʭɹʛʠ! ʞʠʁʋ! ʑ˂! ʑʶˋʞɻˀĂ༂൑ᆹɅȤȫɥఝᆹʺʣʗ˂ˋʈࡳ୹ɈߊᆏĂ൦2:‫ʺ˂ࣃࠞޑ‬ĜʠʓˋʏˋʈʏˋʵʐɾʸĂಫᅝ൥ߔȫɞȧ‫࠵ޏ‬Ă3128
༃ǎॢ27໲Ć ᥓນāలĂ໘ટஷ‫ێ‬ᇾĂழ‫ݴ‬ሆ৘་ĂഁರᄽቃĂˀʍʭɹʛʠ! ʞʠʁʋ! ʑ˂! ʑʶˋʞɻˀĂ‫چ‬೩ટĆ಩౐ࣄɅȤȫɥଚჶၦ‫ޓ‬Ɉ਒౼੧ණव‫ސ‬಑Ă൦2:‫ʺ˂ࣃࠞޑ‬ĜʠʓˋʏˋʈʏˋʵʐɾʸĂಫᅝ൥ߔȫɞȧ‫࠵ޏ‬Ă
3128༃ǎॢ27໲Ć ဦ‫ݎ‬ā஧Ă໧༜‫ࡩێ‬Ăˀʍʭɹʛʠ!ʞʠʁʋ!ʑ˂!ʑʶˋʞɻˀĂLjoufy.8ɬᅙȞȹ VBW ຃੪ DQ.TBS ʏʑʞʸĂ൦2:‫ʺ˂ࣃࠞޑ‬ĜʠʓˋʏˋʈʏˋʵʐɾʸĂಫᅝ൥ߔȫɞȧ‫࠵ޏ‬Ă3128༃ǎॢ27໲
Ć ൥೐৘ሆĂજ൮୻ાĂˀʍʭɹʛʠ!ʞʠʁʋ!ʑ˂!ʑʶˋʞɻˀĂ৉ߔૺʄʑॳ୸ʓˋʍʏʑʞʸĂ൦2:‫ޑ‬― 103 ―

ࠞࣃ˂ʺĜʠʓˋʏˋʈʏˋʵʐɾʸĂಫᅝ൥ߔȫɞȧ‫࠵ޏ‬Ă3128༃ǎॢ27໲
Ć Jowjufe! Ubml! ;! Kptbqibu! Ufuvlp! Tsj! Tvnbouzp-! Opcvzptij! Jnvsb-! Lb{vufsv! Obncb-! Gvnjp! Zbnb{blj-!
Bljsb!Lbup-!Lbutvnj!Ibuupsj-!boe!Dijibsv!Ipohp-!
ĨJoopwbujwf!Njdspxbwf!Sfnpuf!Tfotjoh-ĩ!Jotujuvuf!gps!
Hmpcbm!Qspnjofou!Sftfbsdi-!Ljdlpgg!Tznqptjvn-!Jodvcbups!Qspkfdu!Qsftfoubujpo.4-!q/32-!25!Opwfncfs!
3127!
ĪDijcb!;!Dijcb!VojwfstjuzīĆ Jowjufe! Ubml! ;! Kptbqibu! Ufuvlp! Tsj! Tvnbouzp-!ĨEfwfmpqnfou! pg! Tzouifujd! Bqfsuvsf! Sbebs! boe! Jut!
Bqqmjdbujpot! ;! Dpousjcvujpot! gps! Ejtbtufs! Qsfwfoujpo! bu! Kbqbo! boe! Btfbo-ĩ!KSD! Pggjdf-! 8! Efdfncfs!
3127!ĪOblbop!;!KSDīĪႨഽ‫ݣ‬ცīĆ ๜ෂࡦ൥Ăߝঈয়શĂႨഽ‫ݣ‬ცĂᆹ໘Ǐ૫ই๘दɬᅙȞȹୃᄄव௻Ɉෆ୸Ʌ࠲ȳɥॸ࢞Ă໲Ⴈଖణപᆲߔ‫ޏ‬
ိ౰39༃๱୑ࡠߔ୹ਆ‫ޏܩ‬Ī๬࢏ૂ‫࠵ޏ‬īĂ3127022021.22-!qq242.243Īဏ݊ॻīĆ ݊Ⴈ‫ވ‬౺Ăߝঈয়શĂႨഽ‫ݣ‬ცĂજ૫ই๘दʟĜʗɬᅙȞȹ೔༜वˁɼʘĜʟĜʗɈ੔এɅ࠲ȳɥॸ࢞Ă໲Ⴈଖణപᆲߔ‫ိޏ‬౰39༃๱୑ࡠߔ୹ਆ‫ޏܩ‬Ī๬࢏ૂ‫࠵ޏ‬īĂ3127022021.22-!qq48.49Īဏ݊ॻīĆ ߝঈয়શĂੂᄘྰ‫ݢ‬ાĂࣸā୉᠉ĂȷɈ഼27შĂNPSBMT Ʌɢɥ VBW ɬᅙȞȹଖణപᆲȤȫɥ‫ڽ‬Ʉɥोപ௸ॣȤɢɍ TgN ʕʭʠɾɿɺɅɢɥ౼๱࿎‫ݟ‬Ʌ࠲ȳɥ৽ઍĂ໲Ⴈଖణപᆲߔ‫ိޏ‬౰39༃๱୑ࡠߔ୹ਆ‫!ޏܩ‬Ī๬࢏ૂ‫࠵ޏ‬īĂ3127022021.22Īဏ݊ॻī
Ī樋৏ຼૂīĆ ੂນᅣᄼĂ樋৏ຼૂĂ਒ॽூ९Ăഺ௫ࣝఒĂഝ࿪ᄼશĂ๲‫ێݎ‬࿛Ăরນ൥ၓĂෂ๿‫܇‬૖Ī3127īć࠲ຄණၫɅȤȫɥ‫ࡠݤ‬ɬൎ௣ɂȱȹᆶ‫ݛ‬ৌ‫ݪ‬Ɉණ‫ູۊ‬౯Ʌ࠲ȳɥ৽ઍĂ໲Ⴈ࡜௣ߔ‫ޏ‬3127༃๱୽ࡠ൥‫ޏ‬ĂQ247Ă
3127༃Ǒॢ29໲ġ32໲Ăਡᆏʂ˂ˋʬʛʇࡥ༄ಆவ༃೰ၫʓˋʗĜĆ ෳ‫ݣݎ‬ცĂഺ๜०ષĂ樋৏ຼૂĂၹ຀৹‫ێ‬ĂႨ๜ᆅषĂ်ஒয়ാᇾĂჽᆀ஧ᓖĂۭರ०ാᇾĂഺ‫܊‬ሆ੖ĂᇑᄄāၹĂഺટ஋‫!ێ‬Ī3127ī;! ɌɘɩɤǔਖࠫപʟĜʗɈ˂ɺ˃ʗɼʸ৊ާĂ໲Ⴈණ࢝ላ౳ᇦਗ3127༃൥‫ޏ‬Ă
NHJ32.14Ă3127༃Ǒॢ33໲ġ37໲ĂႷෟʹʛʓĆ ঢ় ౧ მ ૂĂ 樋 ৏ ຼ ૂĂ ੘ ૹ ᄯ ூĂ ࢥ ྪ ඪ ᅂĂ ટ Ⴈ ୉ ஶĂ ୭ā ஶ ‫ێ‬Ă ៤ ๜ā ຼ!Ī3127īć!Beejujpobm!
jogpsnbujpo! pg! qsfdjqjubujoh! dmpve! mjgf! tubhft! gps! Jnqspwfnfou! pg! sbjo! sbuf! ebub! ftujnbufe! gspn!
Ijnbxbsj.9Ă໲Ⴈණ࢝ላ౳ᇦਗ3127༃൥‫ޏ‬ĂBDH21.Q15Ă3127༃Ǒॢ33໲ġ37໲ĂႷෟʹʛʓĆ ‫ۈ܊‬ளࡦĂ樋৏ຼૂ!Ī3127īć!๷ࡠɅ࢖ബɅཡൿȳɥ໤࠹ฝ࡜‫ڗ‬Ʌൎȳɥ໲Ⴈ‫ޠ‬௫ऋɈʹʕ௷ᅸɈ‫ࣗ܆‬Ă໲Ⴈණ࢝ላ౳ᇦਗ3127༃൥‫ޏ‬ĂBIX28.Q18Ă3127༃Ǒॢ33໲ġ37໲ĂႷෟʹʛʓ
Ć Ijhvdij-! B/!Ī3127ī
ć! Ijnbxbsj.9! sfmbufe! bdujwjujft! jo! DFSfT-! Dijcb! Vojwfstjuz-! 3oe! Kbqbo.Bvtusbmjb!
HFP.MFP!Bqqmjdbujpot!Xpsltipq-!iptufe!cz!KBYB-!3127༃ǕॢǍ໲ġǎ໲Īຄࢶ -!psbmīĆ 樋৏ຼૂĂঢ়౧მૂĂၹ຀৹‫ێ‬ĂࢥྪඪᅂĂ੘ૹᄯூĂ୭āஶ‫ێ‬ĂટႨ୉ஶĂඇ๜ީ‫ࡢڃ‬ൣĪ3127ī
ć! ಇો࡜௣‫ܒ‬౳दɬߤᅙȱȹਏ౉࠲ᇦ௶ၡɈෆ୸ĂȤɢɍȷɈᆀᅙĂ3127༃๱౉ဦĆ౉૝঍ߔ‫࢞ॸޏ‬ཡ࿍‫ޏ‬Ă
P.29Ă3127༃Ǖॢ26໲ġ28໲ĂʋˁʛʓɏȩȱɘĆ ངᄢാᇾĂஜ࿩ሆధĂழᆹဦცĂ൩ᄘ࿢ცĂ樋৏ຼૂĂ਒ഺმᅂ!Ī3127īć! ʭɿĜʒʡɺ˄ɼ࡜௣˄ĜʘĜɁॽȹ3126༃Ǖॢǐ໲Ʌ࠲ຄɁཡ౺ȱȹಓᅸ‫ !܀‬ĝ๬ఘငɅୠෂਛ۫ɂᆛࠆɈᄆॖɬɜȹɣȱȹૢᇉɅȾȞɀĝĂ໲Ⴈ࡜௣ߔ‫ޏ‬3127༃๱୑ࡠ൥‫ޏ‬Ă3127༃21ॢ37໲ġ39໲Ăშগ‫ݎ‬൥ߔĆ ঢ়౧მૂĂ樋৏ຼૂĂ੘ૹᄯூĂࢥྪඪᅂĂટႨ୉ஶĂ୭āஶ‫ێ‬Ă៤๜āຼ!
Ī3127ī
ć!ɌɘɩɤǔਖࠫപʟĜʗɬᅙȞȹ࡙‫୔ߔޟ‬ɅɢɥࣅȞ۫Ɉࣅ๱ైฤĂ໲Ⴈ࡜௣ߔ‫ޏ‬3127༃๱୑ࡠ൥‫ޏ‬Ă3127༃21ॢ37໲ġ39໲Ăშগ‫ݎ‬൥ߔĆ ஧ငāਛĂ樋৏ຼૂĂၹ຀৹‫!ێ‬Ī3127ī
ć!BQISP!KQ!Ʌॽɣɦȹ‫݋‬໢༳۫Ɉౘ୥༃ࡤჹဿ຦Ă໲Ⴈ࡜௣ߔ‫ޏ‬3127༃๱୑ࡠ൥‫ޏ‬Ă3127༃21ॢ37໲ġ39໲Ăშগ‫ݎ‬൥ߔĆ ၹ຀৹‫ێ‬Ă樋৏ຼૂĂඹෂ‫܉‬௃Ăੲ‫ݚ‬ാᅣ!Ī3127īć!Ɍɘɩɤǔਖ!Hsjeefe!ʯ˅ʘʇʠɈ৊ާɂ౼დࡐ‫ݝ‬ၒ౷೐ষɈ‫ڮ‬඲ၒ౷྘ߏĂ໲Ⴈ࡜௣ߔ‫ޏ‬3127༃๱୑ࡠ൥‫ޏ‬Ă3127༃21ॢ37໲ġ39໲Ăშগ‫ݎ‬൥ߔĆ ੧‫ګۈ‬ᆊĂ樋৏ຼૂĂၹ຀৹‫ێ‬Ăঢ়౧მૂĂ៤๜āຼ!Ī3127īć! USNN0QS Ɂॳ୸ȱȹɺʐɺ‫ۊ‬ɅȤȫɥ࣡඘Ʉਏ۫ɼʱˋʠɈཡ౺௲ஒɅȾȞɀĂ໲Ⴈ࡜௣ߔ‫ޏ‬3127༃๱୑ࡠ൥‫ޏ‬Ă3127༃21ॢ37໲ġ39໲Ăშগ‫ݎ‬൥ߔĪႨࣕಫ୽īĆ ழߚঈಫ਑ાĂႨࣕಫ୽Ă๜ഺ‫੼܉‬ĂHvobsej!TjhjućࠍɊȾޮɬିȫȹ౉‫ے‬౺દᆲɂ UWEJ Ɉ࠲बĂ໲Ⴈ˂ʺĜ― 104 ―

ʠʓˋʏˋʈߔ‫ޏ‬൦71‫୹ߔޑ‬ਆ‫ޏܩ‬ሄဦୠĂ228.229-!Ī3127ī
Ć ࿫ሆၣ‫ݙ‬ĂႨࣕಫ୽Ăழߚঈಫ‫ފ‬ાĂඌᄘෳෳĂ๜ഺ‫੼܉‬ćʟĜʗෆ୸ၫၭɈ‫ۅ‬ȞɅɢɥ౉‫ے‬Ɉେᆲైฤ౼
๱ɈॳບĂ໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫ޏ‬൦71‫୹ߔޑ‬ਆ‫ޏܩ‬ሄဦୠĂ246.247-!Ī3127ī
Ć ழߚঈಫ਑ાĂႨࣕಫ୽Ă๜ഺ‫੼܉‬ĂHvobsej! Tjhjuć‫ܒ‬౳ʟĜʗɬᅙȞȹ౉‫ے‬౺દᆲɈණ‫ູۊ‬౯Ɉ༘‫࢒ڐ‬ɍ
UWEJ ɂɈ࠲बĂ൦53‫ʺ˂ޑ‬Ĝʠʓˋʏˋʈʏˋʵʐɾʸਆ‫ܩ‬ሄဦୠĂ22.23-!Ī3128༃ǏॢīĪ໴৮ల઺īĆ ๜ෂ౸ऽĂബ౉āᅖĂજ‫ۺ‬ሆྷĂྲྀ࣌୐‫ێ‬Ăᥓᄘঢ়௓Ă໴৮ల઺ĂὪນ఑૭Ăຄࢶʑʃɼʜ˂ĜɬᅙȞȹ
3126༃ɈຄࢶɅȤȫɥණ࿍ɂ௫ऋɈᆙાɈࢫ຦ɅȾȞɀĂ໲Ⴈ࡜௣ߔ‫ޏ‬Ăຄࢶ๬୪ඇࣾĂ3127༃Ǒॢ29.32໲
Ć ྲྀ࣌୐‫ێ‬Ăۭᄘ‫ڭ‬෿ૂĂ໴৮ల઺Ăਥರ஋‫ێ‬Ă൥ঈᆀᤁĂຄ໤ɺʐɺ‫ۊ‬ɅȤȫɥʨɼʂʶʑĆʨĜʣˋʈࡧ঍༧୸ᆲɈ OP3ʃˁʸᆲɒɈ‫ࣗ܆‬࿎‫ݟ‬Ă໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬ĂಫᅝॻႷෟĂ3127༃Ǒॢ33.37໲
Ć ਱ీᆯ‫ێ‬Ă෨๜࿢෤ĂಆᄄୈશĂટ໘āࣉĂ௄‫܊‬ৡᅂĂ௄૊୐ሆĂࣸඇᄵਔĂ௄ॽāၹĂ଎๜ാᇾĂඇႨৰૂĂরນ൥ၓĂఝᄘāᄮĂ៛āᅏ‫ގ‬Ăด‫ࠌێۈ‬Ăඌ۩ᅖ‫ގ‬Ă१။෸ୃĂഺટுိĂჂࢀ็ᅂĂ൪ರ‫ދ‬་Ăඹඇဦ‫ێ‬ĂੂນᅣᄼĂඹ໘āொĂ໴৮ల઺Ăߚ‫ۈ‬য়ાĂTusvojo! NjlibjmĂGpnjo! CpsjtĂ˅ʏɺ౉ဦ࡜௣ࠞࣃ
ࠠ૗ࣟɈਂऋ࡙Ʌɢɥ႘࣡Ćಀʏʱ˂ɺ‫ۊ‬ɅȤȫɥ൥࡜ࠞࣃࠫപĂ໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬ĂಫᅝॻႷෟĂ
3127༃Ǒॢ33.37໲
Ć ཝટ౗൥Ă໴৮ల઺Ăʃʠ˂ĆʯˁʟɻĜʯĂ˂ʺĜʠʓˋʏˋʈɅɢɥ໲Ⴈ௫ऋɈʀɺ˅ʖ˃ʠ˄ˋʡ‫ސ‬಑ɂȷɈ࿎‫ݟ‬Ă໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬ĂಫᅝॻႷෟĂ3127༃Ǒॢ33.37໲
Ć ழைāഏĂ໴৮ల઺ĂLibusj! QsbeffqĂණ௫ȥɣɈ˂ʺĜʠʓˋʏˋʈɅɢɥ౉௾࡜Ɉܴ෸ʃˁʸᆲĆ਒๱ယ࿫ࠫപɈഊ঱྘ߏĂ໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬ĂಫᅝॻႷෟĂ3127༃Ǒॢ33.37໲
Ć ܼ੸১ᄓĂ໴৮ల઺ĂNBY.EPBT ɅɢȽɀࠫപȯɦȹࣻୋɈ໩બ‫ݛ‬ᆘ݉༏๱Ɉᅟۚ‫ސ‬಑Ă໲Ⴈණ࢝ላ౳‫ݨ‬ߔᇦਗ൥‫ޏ‬ĂಫᅝॻႷෟĂ3127༃Ǒॢ33.37໲
Ć ໴৮ల઺Ă‫ݡ‬ນඪັĂാᅣ৉ཡ๝ऄ຦ळ NBY.EPBTĪFdp.NBYEPBTīക඲ɈާཡĂ໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬ĂಫᅝॻႷෟĂ3127༃Ǒॢ33.37໲
Ć ໴৮ల઺Ăကນ൱ᄓĂྲྀ࣌୐‫ێ‬Ăਥರ஋‫ێ‬Ăۭᄘ‫ڭ‬෿ૂĂຄɺʐɺɈൎᆔ५໩બ‫ݛ‬඾೧༏๱Ă21༃೐Ɉ˄ʱ
˃Ʌ‫ޑ‬ဌĂ໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗ൥‫ޏ‬ĂಫᅝॻႷෟĂ3127༃Ǒॢ33.37໲
Ć Iprvf-! T/-! I/! Jsjf-! boe! B/! Tijnj{v-! Mpoh! ufsn! nvmuj! dpnqpofou! NBY.EPBT! pctfswbujpo! jo! Qijnbj-!
Uibjmboe-!൥࡜‫ߔݛ‬ບሄ‫ޏ‬Ă႘‫ັޠ‬ઑႦીĂ3127༃21ॢ23.25໲
Ć ழைāഏĂ໴৮ల઺Ăණ௫ȥɣɈ˂ʺĜʠʓˋʏˋʈɅɢɥ౉௾࡜Ɉܴ෸ʃˁʸᆲĆ਒๱ယ࿫Ɉഊ঱྘ߏĂ൥࡜‫ߔݛ‬ບሄ‫ޏ‬Ă႘‫ັޠ‬ઑႦીĂ3127༃21ॢ23.25໲
Ć ཝટ౗൥Ă໴৮ల઺Ăʃʠ˂ĆʯˁʟɻĜʯĂ˂ʺĜʠʓˋʏˋʈɅɢɥ໲Ⴈ௫ऋɈʀɺ˅ʖ˃ʠ˄ˋʡ‫ސ‬಑ɂȷɈ࿎‫ݟ‬Ă൥࡜‫ߔݛ‬ບሄ‫ޏ‬Ă႘‫ັޠ‬ઑႦીĂ3127༃21ॢ23.25໲
Ć ܼ੸১ᄓĂ໴৮ల઺ĂNBY.EPBT ɅɢȽɀࠫപȯɦȹࣻୋɈ໩બ‫ݛ‬ᆘ݉༏๱Ɉᅟۚ‫ސ‬಑Ă൥࡜‫ߔݛ‬ບሄ‫ޏ‬Ă႘‫ັޠ‬ઑႦીĂ3127༃21ॢ23.25໲
Ć ࣸඇᄵਔĂ࢔੸ሆড়Ăᄘ෿‫ދ‬ఱĂ໴৮ల઺Ă਒๿࢏ᅖĂ୽ࡠɅ݁ీ‫ފ‬ɅȤȫɥ൥࡜ෂʳ˃ʸɺ˃ʟʪʡɈ
NBY.EPBT ोപɂ PNJ ‫ܒ‬౳ࠫപɂɈ྘ߏć਒๱ယ࿫Ɉ‫ࣗ܆‬Ă൥࡜‫ߔݛ‬ບሄ‫ޏ‬Ă႘‫ັޠ‬ઑႦીĂ3127༃21
ॢ23.25໲Ć ෂ๿āৗĂ๧ᵚကૂĂટႨࡹᇾĂඹෂ‫܉‬௃Ăෂ๿‫܇‬૖Ă໴৮ల઺Ăᇑᄄ०ാᇾĂ‫ݚ‬๜ࢀ་Ă࠾೅ᄻྰાĂ໲਒‫ࡹێ‬Ăʀʥ˃ʆĜʶʥʐʹˋʠɅȤȫɥ࡜௣ߔɂ୅ᅟ‫ߔݨ‬ɈࢾລĂ໲Ⴈ࡜௣ߔ‫ޏ‬Ă‫ڈ‬ඪॻშগ‫ݎ‬ીĂ3127༃21ॢ
37.39໲Ć ࢔੸ᆅଝĂႥā‫ދ‬ᄽĂഺ௫āৰĂ໴৮ల઺ĂHDPN.D0THMJ ൥࡜ʯ˅ʘʇʠɈ৫౷ॳ௠ो‫ކ‬Ă໲Ⴈ࡜௣ߔ‫ޏ‬Ă‫ڈ‬ඪॻშগ‫ݎ‬ીĂ3127༃21ॢ37.39໲
Īߝঈয়શīĆ ๜ෂࡦ൥Ăߝঈয়શĂႨഽ‫ݣ‬ცĂᆹ໘Ǐ૫ই๘दɬᅙȞȹୃᄄव௻Ɉෆ୸Ʌ࠲ȳɥॸ࢞Ă໲Ⴈଖణപᆲߔ‫ޏ‬
ိ౰39༃๱୑ࡠߔ୹ਆ‫ޏܩ‬Ī๬࢏ૂ‫࠵ޏ‬īĂ3127022021.22-!qq242.243Īဏ݊ॻīĆ ݊Ⴈ‫ވ‬౺Ăߝঈয়શĂႨഽ‫ݣ‬ცĂજ૫ই๘दʟĜʗɬᅙȞȹ೔༜वˁɼʘĜʟĜʗɈ੔এɅ࠲ȳɥॸ࢞Ă໲Ⴈଖణപᆲߔ‫ိޏ‬౰39༃๱୑ࡠߔ୹ਆ‫ޏܩ‬Ī๬࢏ૂ‫࠵ޏ‬ī
Ă3127022021.22-!qq48.49Īဏ݊ॻīĆ ߝঈয়શĂੂᄘྰ‫ݢ‬ાĂࣸā୉᠉ĂȷɈ഼27შĂNPSBMT Ʌɢɥ VBW ɬᅙȞȹଖణപᆲȤȫɥ‫ڽ‬Ʉɥोപ௸ॣȤɢɍ TgN ʕʭʠɾɿɺɅɢɥ౼๱࿎‫ݟ‬Ʌ࠲ȳɥ৽ઍĂ໲Ⴈଖణപᆲߔ‫ိޏ‬౰39༃๱୑ࡠߔ୹ਆ‫ޏܩ‬Ī๬࢏ૂ‫࠵ޏ‬īĂ3127022021.22Īဏ݊ॻī― 105 ―

ĪᥓນஶાīĆ Uif!jnqbdu!po!DI5!sfusjfwbm!pg!HPTBU0UBOTP.GUT!UJS!cboe!gspn!uif!vodfsubjouz!pg!uif!dpoujovvn!
bctpsqujpo-!Bljopsj!Zbnbeb-!Obplp!Tbjupi-!Szpjdij!Jnbtv-!Lfj!Tijpnj-!boe!Bljijlp!Lv{fĂණ࢝ላ౳‫ߔݨ‬
ᇦਗ3127༃൥‫ޏ‬Ă3127༃ǑॢĆ OJDBN.UN ʟĜʗ࢒ɍਂऋ࡙ࠫപʟĜʗɅɢɥ HPTBU0UBOTP.GUT! UJS! DI5ʟĜʗɈ࿎‫ݟ‬Ăᄘę޼ᆢ‫ގ‬ĂᥓນஶાĂ਱ీᆯ‫ێ‬ĂܶॽāसĂඌ۩ᅖ‫ގ‬ĂಆᄄୈશĂ෨ఝႨణશĂ෨๜࿢෤Ă௄૊୐ሆĂ៛āᅏ‫ގ‬Ăด‫ࠌێۈ‬Ăණ࢝ላ౳‫ߔݨ‬ᇦਗ3127༃൥‫ޏ‬Ă3127༃ǑॢĆ ˁɼˋʩˁʹĜʗɈೊ൰Ȧ HPTBU! UJS! ʹʗˋ˂ʠ˂Ĝʨ˃ɅᅇȢɥ‫ࣗ܆‬Ɉ࿎‫ݟ‬Ăટ๜ც९ĂᥓນஶાĂ਱ీᆯ‫ێ‬ĂܶॽāसĂ࢏౦ࣝྷĂ൦33‫ޑ‬൥࡜‫ߔݛ‬ບሄ‫ޏ‬ĂઑႦĂ3127༃21ॢĆ ਂऋ࡙ࠫപʟĜʗɬᅙȞȹ HPTBU0UBOTP.GUT!UJS!DI5ʟĜʗɈ࿎‫ݟ‬Ăᄘę޼ᆢ‫ގ‬ĂᥓນஶાĂ਱ీᆯ‫ێ‬ĂܶॽāसĂඌ۩ᅖ‫ގ‬Ă෨๜࿢෤Ă௄૊୐ሆĂ៛āᅏ‫ގ‬Ăด‫ࠌێۈ‬Ă൦33‫ޑ‬൥࡜‫ߔݛ‬ບሄ‫ޏ‬ĂઑႦĂ3127༃
21ॢ
Ć HPTBU0UBOTP.GUT! UJS ʑʲʇʠ˃ɬᅙȞȹණ࿍ჶଗ୸ᆎైฤɈ૚əĂྲྀ෿ථ་ĂᥓນஶાĂܶॽāसĂ࢏౦ࣝྷĂ਱ీᆯ‫ێ‬Ă൦33‫ޑ‬൥࡜‫ߔݛ‬ບሄ‫ޏ‬ĂઑႦĂ3127༃21ॢ
Ć HPTBU Ȥɢɍ൥࡜ᄪഗʺʟ˃ OJDBN.UN Ɉ‫ݗ‬ଆৌ‫ݪ‬ʄʑ࡜෈ိࣧ༏๱Ɉ྘ߏ‫ސ‬಑Ăཞ๜ࠌັĂᥓນஶાĂ਱ీᆯ‫ێ‬ĂܶॽāसĂࢀ๜ড়౺Ăඌ۩ᅖ‫ގ‬Ă൦33‫ޑ‬൥࡜‫ߔݛ‬ບሄ‫ޏ‬ĂઑႦĂ3127༃21ॢ
ĆĨಀʏʱ˂ɺ௫ऋɈ HPTBUĪ༂ಘެʨˋʡīɂਂऋ࡙ࠫപɅɢɥʹʗˋɈ྘ߏĂౝ๜৽ષĂᥓນஶાĂᆹ๜ੂථાĂ෨๜࿢෤ĂઉರࡊୃĂ໲Ⴈ࡜௣ߔ‫ޏ‬3127༃୑ࡠ൥‫ޏ‬Ăშগ‫ݎ‬Ă3127༃21ॢĪᅔā‫ڰ‬īĆ Xfj! Zboh! boe! Ijeflj! Lpcbzbtij-! Bo! fnqjsjdbm! gpsftu! mboetdbqf! tjnvmbups! gps! esjwjoh! 4.E! dbopqz!
sbejbujwf!usbotgfs!npefmt/!Qspdffejoht!pg!uif!71ui!tqsjoh!dpogfsfodf!pg!uif!sfnpuf!tfotjoh!tpdjfuz!pg!
Kbqbo-!qq/66.67-!Nbz!3127-!Obsbtijop-!Kbqbo!
Ć Xfj! Zboh-! Ijeflj! Lpcbzbtij! boe! Lfomp! Ojtijeb! Obtbibsb-! Tbufmmjuf! Sfusjfwbm! pg! Pwfstupsz! boe!
Voefstupsz! Mfbg! Bsfb! Joefy! jo! Ijhi! Opsuifso! Gpsftut-! Kbqbo! Hfptdjfodf! Vojpo! boovbm! Nffujoh-! Nbz!
3127-!Nblvibsj-!Kbqbo
Ć Ijlefj! Lpcbzbtij-!Xfj!Zboh-! Lb{vijup!Jdijj-!Dpnqbsjtpo! pg!uif! tjnvmbufe!hmpcbm!uif!dbopqz! tdbmf!tvo.
joevdfe!dimpspqizmm!gmvpsftdfodf!boe!tbufmmjuf.cbtfe!TJG!nfbtvsfnfout-!Kbqbo!Hfptdjfodf!Vojpo!boovbm!
Nffujoh-!Nbz!3127-!Nblvibsj-!Kbqbo
ĺိ౰39༃๱৊ާਆ੐Ăਆ‫ޏܩ‬ĂˇĜʇʏʿʛʯຑɈଌૈ௻࣍ĻĪࣷນூྷī
შāā௔ćණ‫ࡠ୽ޏࢾ୹ࡳ౉ݚ‬ਆ୔‫ޏ‬Īപᆲණଋ०။‫࠵ޏ‬ī‫ޱ‬āāᅟćණ‫ޱ౉ݚ‬ತĝණ‫౉ݚ‬Ɉᆅሄɂଌ੫
ާ੓ࡖ࠰ćိ౰39༃Ǒॢ38໲ൎāā௣ć‫ཾێ‬ઞ‫ݡ‬ఱౘć71შშāā௔ćಫᅝીᮊ୹ဦ‫୶ݛ‬Īಫᅝીဦ‫ݛ‬ʳĜ˃ī‫ޱ‬āāᅟćȞȾɁɜĂɃȭɁɜ˂ʺĜʠʓˋʏˋʈĝʡ˅Ĝˋɬ઴Ƚȹࠞࣃोപ
ާ੓ࡖ࠰ćိ౰39༃Ǖॢ32໲ൎāā௣ć‫ཾێ‬ઞ‫ݡ‬ఱౘć61შშāā௔ćFOWJ!'!JEM!Vtfs!DpogfsfodfĪ୑ᅝঈ VEYī‫ޱ‬āāᅟćVBW ˂ʺĜʠʓˋʏˋʈĝʡ˅Ĝˋɬ઴Ƚȹࠞࣃोപ
ާ੓ࡖ࠰ćိ౰39༃21ॢ23໲ൎāā௣ć‫ཾێ‬ઞ‫ݡ‬ఱౘć211შ

― 106 ―

Īˀʍʭɹʛʠ!ʞʠʁʋ!ʑ˂!ʑʶˋʞɻˀīშāā௔ć!!U if! 27ui! Xpsltipq! po! TBS! Jnbhf! Qspdfttjoh! boe! Dijcb! Vojwfstjuz! Tvnnfs! Tdippm! po!
Njdspxbwf!Sfnpuf!TfotjohĪʍʶĜʑʇĜ˃ī‫ޱ‬āāᅟć!ߔ
! ౺ɬൎ௣ɂȱȹʶɼʇ˅༜˂ʺĜʠʓˋʏˋʈ࢒ɍ TBS ‫ކ‬ജஐᆅɅȾȞɀɈˇĜʇʏʿʛʯɬଌૈăާ੓ࡖ࠰ćိ౰39༃ǔॢǍ໲ġǏ໲ൎāā௣ćਡ໘Ɉߔ౺Ćॸ࢞ଞઞ‫ݡ‬ఱౘć66შშāā௔ćਗ౰ާ৏˄ĜʘˇĜʇʏʿʛʯ
‫ޱ‬āāᅟć!!ɼˋʡʥʏɺࡳ୹࿎‫ܾݟ‬ᅙෝɈॸ࢞ۙɬൎ௣Ʌਗ౰ާ৏˄ĜʘĪTBSīɅ࠲ȳɥࡊೣโɄˇĜʇʏʿʛʯɬଌૈăާ੓ࡖ࠰ćိ౰39༃Ǖॢ38໲ġ21ॢ39໲ൎāā௣ć‫࢞ॸެޠ‬ଞઞ‫ݡ‬ఱౘćǔშშāā௔ćਗ౰ާ৏˄ĜʘˇĜʇʏʿʛʯ
‫ޱ‬āāᅟć!!ɼˋʡʥʏɺۧහਂऋࣟĪMBQBOīɈॸ࢞ۙɬൎ௣Ʌਗ౰ާ৏˄ĜʘĪTBSīɅ࠲ȳɥࡊೣโɄˇĜʇʏʿʛʯɬଌૈăާ੓ࡖ࠰ćိ౰39༃22ॢ36໲ġ23ॢ33໲ൎāā௣ć‫࢞ॸެޠ‬ଞઞ‫ݡ‬ఱౘćǐშĪႨഽ‫ݣ‬ცĆߝঈয়શīშāā௔ćTdjfodf!Tvnnfs!Dbnq!3127ĪʍʶĜʅʻˋʯīĪᆹණࠫപණī‫ޱ‬āāᅟć!!‫ߔݨ‬Ʌ࣓Ⴭɬ૩Ⱦ૥ຮɬၕୠȱĂǏ໲࠰Ă૵೓ɈෂɁ౺ߤȱĂൌঅଌঅɬฆȱɀĶɃȠȱɀȺɧȠĉķĂĶɄȶȺɧȠĉķɂ‫ߔݨ‬โ৕ࡋఘɬ‫ۋ‬ɀɥȭɂɬᄆโɂȱɀଌૈăާ੓ࡖ࠰ćိ౰39༃ǔॢǑ໲ġǓ໲ൎāā௣ćਡ໘Ɉ‫ཾێ‬Ćߔ౺Ćॸ࢞ଞઞ‫ݡ‬ఱౘć:6შშāā௔ćCjpnbtt!TfnjofsĪʨɼʂʶʑʓʷʢĜćˇĜʇʏʿʛʯī‫ޱ‬āāᅟćఝᆹ˂ʺĜʠʓˋʏˋʈɅ࠲ȳɥਆ‫ޏܩ‬Ȥɢɍʟɻʑʃʛʏʿˋɬଌૈăާ੓ࡖ࠰ćိ౰3:༃ǎॢ38໲ൎāā௣ć‫ཾێ‬Ćߔ౺Ćॸ࢞ଞઞ‫ݡ‬ఱౘć31შ
Ī樋৏ຼૂī
შāā௔ćಫᅝ॑୹ဦ‫୶ݛ‬Ķ࡜௣‫ܒ‬౳Ɍɘɩɤķ‫ޱ‬āāᅟć‫ཾێ‬৐ȫɅɌɘɩɤǔਖ຦‫ކ‬ɬෂఘɂȱȹಇો࡜௣‫ܒ‬౳Ɉ‫ޱ‬ᅟɂॸ࢞๐ާɅȾȞɀತცăާ੓ࡖ࠰ćိ౰39༃Ǖॢǔ໲ൎāā௣ćਡ໘Ɉ‫ཾێ‬ઞ‫ݡ‬ఱౘć71შ

― 107 ―

ĺఛဧऻ੪ĆʹʟɻɺၡັຑĻ໲ā࿥ऻ੪૛Ăၪഗࣟğྈ೨შ

໘āāᅎ

ଲ੮ൎ௣ଞ

ိ౰39༃
ǒॢǒ໲

ʭʐʞ˄ʫğəɭɄɈʣʽĜʑĪʞ˄ʫīʈɺʞʶˁɅȤȫɥʶʼဦცɈ‫ۆ‬ಙཡॽɅ࠲ȳɥਗ౰ާ৏˄Ĝʘ‫ކ‬ജɈယ಑य़‫ݪ‬ɅȾȞɀತცăˀʍʭɹʛʠ

Ǔॢǒ໲෥໲ఛဧ୸ཹ epu
hpp ʫʐʥʑ FYદॄʣʽĜʑ
Nbslf[jofCJHMPCF ʣʽĜʑ຿༸ʂˋˁɼˋࠞࣃ๐ႊ൤OFXTBMUຄɺʐɺɈ൥࡜ෂ OP3ܸಹ˄ʱ˃ĂǑ༃೐Ɉ˄ʱ˃Ʌ‫ޑ‬ဌȱɀȞȹĊġ଱ɅෂਡɁ‫ޑ‬ဌĂ໲ႨĆ࠴ਡɁɉɞɞ‫ݛڏ‬Ɉभ৐ġ

໴৮ల઺

ိ౰39༃
ǔॢ32໲

Nfejb!Joepoftjb!Ofxtqbqfs!೔ਡ૒
Īਡެī

Nfsflb!zboh!Johjo!LfncbmjĪɼˋʡʥʏɺɅਇ
ॷȱȹॸ࢞ଞīˀʍʭɹʛʠ

Ⴔ໲ఛဧ೔ਡཹ

ĶɌɘɩɤ FZFķɈࢼວࡅ‫ކ‬Ćࠠୌိ౰39༃ǐॢġǕॢჂ
ɘɁ

樋৏ຼૂ

ိ౰39༃
Ǖॢǐ໲

OILğOIL!ʑʲʏʻ˃!NFHB!DSJTJT!ࢨ
Ķ۫ɬɜȹɣȳ‫܀‬ɬ၏ɘȢɥķॸ࢞Ʌ࠲ȳɥଲ੮൥ࡇ࡙൦ǍୠĶ‫࡜௵ڽ‬௣ɂɈಱȞķĪʞ˄
ࢾᆵ
ʫī

ိ౰39༃
23ॢ27໲

Ufnqp!Nbhb{jofĪઔ૛ī

Jmnvxbo! Joepoftjb! Cjljo! Tbufmju! sbebs! Njlsp!
Qfsubnb! ej! EvojbĪ‫୹ࡳߔݨ‬ć౦‫ޢ‬஑ழळ‫ܒ‬౳˄ĜʘɬȾȩȽȹɼˋʡʥʏɺॸ࢞ଞīˀʍʭɹʛʠ

ိ౰39༃
23ॢ2:໲

DQ.TBS! Qfsubnb! Vouvl! Tbufmju! ;! Jmnvxbo!
Joepoftjb! ej! Kfqboh! Cfsj! LfvohhvmboĪ౦‫ޢ‬஑
Lpnqbt!Ofxtqbqfst-!q/24!೔ਡ૒Īਡެī!
DQ.TBS ຃੪ழळ‫ܒ‬౳ć໲Ⴈ੭ɼˋʡʥʏɺॸ
࢞ଞȦਇॷȱȹīˀʍʭɹʛʠ

ိ౰39༃
23ॢ41໲

Usjcvotpmp!Ofxtqbqfs!ණၫ૒Īਡެī

Nfohfobm! Qspg! Kptbqibu-! Bmvnovt! TNBO!
2! Tpmp! zboh! Djqublbo! Njlsp! Sbebs! ebo!
Ejqfsfcvulbo! EvojbĪʕ˅൦Ǎ਒ຑߔ৫୸బɈ
ˀʍʭɹʛʠ࣋ୂȦ౦‫ޢ‬஑ழळ‫ܒ‬౳ɬާཡȱȹīˀʍʭɹʛʠ

ိ౰3:༃
ǍॢǍ໲Bohlbtb!Nbhb{jofĂqq/79.7:Īઔ૛ī

K p t b q i b u ! U f u v l p ! T s j ! T v n b o u z p - ! B o b l!
Lpqbthbu! Qfofnv! Sbebs! Qfohjoefsbbo! Kbvi!
UfsljojĪˀʍʭɹʛʠ࣋ୂĂ੕ఛ˂ʺĜʠʓˋʏˋʈࡳ୹ɬอ‫ڨ‬ȱȹīˀʍʭɹʛʠ

ိ౰3:༃
Ǎॢǔ໲

Ufnqp!Nbhb{jof-!qq/95.96Īઔ૛ī

Jmnv! '! Uflopmphj! ;! Tbufmju! Njoj! Tfufmbi! Mbnb!
CfsnjnqjĪෳȞழळ‫ܒ‬౳Ɉპīˀʍʭɹʛʠ

ိ౰3:༃
Ǎॢ28໲

Cfsjub!Usbot!೔ਡ૒Īਡެī

Qspg! Kptbqibu! Ufuvlp! Cfsjlbo! Lvmjbi! Vnvn!
ej! TUQJĪˀʍʭɹʛʠ࣋ୂȦɼˋʡʥʏɺਂऋ
൥ߔ৫Ʌࡊ෮ਆ‫ܩ‬īˀʍʭɹʛʠ

― 108 ―樋৏ຼૂ\ǐ^āି௤Ćާཡଌಕຑ
5/2/āି௤
௤Ɉშ௔ćBxbse!pg!Fydfmmfou!Dpouftubou!Ľ!Tuvefou!Bxbse!Qbqfs!Dpnqfujujpoି ௤ ଞćIffjo!ZbohĪˀʍʭɹʛʠॸ࢞ଆஒമߔ౺īି௤ॢ໲ćိ౰39༃ǐॢ33໲
ୂᅇචൌćJoufsobujpobm!Tznqptjvn!po!Sfnpuf!Tfotjoh!3127!
ĪJTST!3127ī
ॸ࢞൨ᄆć!!Tjhobm.up.Opjtf! Sbujp! Ftujnbujpo! gps! Vonboofe! Bfsjbm! Wfijdmf! po.cpbse! Tzouifujd! Bqfsuvsf!
Sbebs
௤Ɉშ௔ć໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫ޏ‬ᄭ୐ሄဦཡ࿍௤ି ௤ ଞćழߚঈಫ਑ાĆႨࣕಫ୽Ć๜ഺ‫੼܉‬ĆHvobsej!TjhjuĆB/!B/!Bzv!Njsbi!BejĆBoojf!Bncbsbxbuj
ି௤ॢ໲ćိ౰39༃Ǒॢ23໲ୂᅇචൌć!໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫ޏ‬ॸ࢞൨ᄆćɼˋʡʥʏɺɅȤȫɥ౉‫ے‬౺દᆲɈණ‫ູۊ‬౯ɂ౉ࠣᆅ଴ၭɈ࠲ब
௤Ɉშ௔ć3127༃๱໲Ⴈ൥࡜‫ߔޏߔݛ‬౺ᄭ୐ཡ࿍௤ି ௤ ଞćTzfevm!IprvfĪ໴৮ॸ࢞ଆஒമߔ౺īି௤ॢ໲ćိ౰39༃21ॢ25໲
ୂᅇචൌć໲Ⴈ൥࡜‫ޏߔݛ‬ॸ࢞൨ᄆćMpoh!ufsn!nvmuj!dpnqpofou!NBY.EPBT!pctfswbujpo!jo!Qijnbj-!Uibjmboe௤Ɉშ௔ćCftu!Qbqfs!Bxbset
ି!௤!ଞćDivb!Njoh!ZbnĪˀʍʭɹʛʠॸ࢞ଆஒമູ໸஝࣋īି௤ॢ໲ćိ౰39༃22ॢ35໲
ୂᅇචൌć!!U if! 8ui! Joepoftjb! Kbqbo! Kpjou! Tdjfoujgjd! Tznqptjvn-! Uif! 35ui! DFSfT! Joufsobujpobm!
Tznqptjvn-!uif!2tu!Tznqptjvn!po!Joopwbujwf!Njdspxbwf!Sfnpuf!Tfotjoh-!Uif!5ui!Tznqptjvn!
po!Njdsptbufmmjuft!gps!Sfnpuf!Tfotjohॸ࢞൨ᄆć!!Qibtf!Dpefe!Tufqqfe!Gsfrvfodz!Mjofbs!Gsfrvfodz!Npevmbufe!Xbwfgpsn!Tzouiftjt!Ufdiojrvf!
gps!Vmusb.Xjefcboe!Tzouifujd!Bqfsuvsf!Sbebs
௤Ɉშ௔ćCftu!Qsftfoufs!Bxbset
ି!௤!ଞćKbnsve!BnjoveejoĪ࢏౦ॸ࢞ଆஒമߔ౺īି௤ॢ໲ćိ౰39༃22ॢ35໲
ୂᅇචൌć!!U if! 8ui! Joepoftjb! Kbqbo! Kpjou! Tdjfoujgjd! Tznqptjvn-! Uif! 35ui! DFSfT! Joufsobujpobm!
Tznqptjvn-!uif!2tu!Tznqptjvn!po!Joopwbujwf!Njdspxbwf!Sfnpuf!Tfotjoh-!Uif!5ui!Tznqptjvn!
po!Njdsptbufmmjuft!gps!Sfnpuf!Tfotjohॸ࢞൨ᄆć!!Pctfswbujpo! pg! Bfsptpm! Pqujdbm! Qspqfsujft! cz! Nfbot! pg! Ijnbxbsj.9! Tbufmmjuf! gspn! Tqbdf! boe!
Mjebs!Tztufn!gspn!Tvsgbdf
௤Ɉშ௔ćCftu!Tuvefou!Bxbset
ି!௤!ଞćZvub!J{vnjĪˀʍʭɹʛʠॸ࢞ଆஒമߔ౺īି௤ॢ໲ćိ౰39༃22ॢ35໲
ୂᅇචൌć!!U if! 8ui! Joepoftjb! Kbqbo! Kpjou! Tdjfoujgjd! Tznqptjvn-! Uif! 35ui! DFSfT! Joufsobujpobm!
Tznqptjvn-!uif!2tu!Tznqptjvn!po!Joopwbujwf!Njdspxbwf!Sfnpuf!Tfotjoh-!Uif!5ui!Tznqptjvn!
po!Njdsptbufmmjuft!gps!Sfnpuf!Tfotjohॸ࢞൨ᄆć!!Qpmbsjnfusjd!Bobmztjt!Pg!Mpoh!Ufsn!Qbeez!Sjdf!Pctfswbujpo!Vtjoh!Hspvoe.cbtfe!Tbs!)HC.TBS*!
Tztufn― 109 ―

௤Ɉშ௔ćCftu!Qptufs!Bxbset
ି!௤!ଞćNjo.Xppl!Ifp!boe!Iffjo!Zboh+Ī+ ˀʍʭɹʛʠॸ࢞ଆஒമߔ౺īି௤ॢ໲ćိ౰39༃22ॢ35໲
ୂᅇචൌć!!U if! 8ui! Joepoftjb! Kbqbo! Kpjou! Tdjfoujgjd! Tznqptjvn-! Uif! 35ui! DFSfT! Joufsobujpobm!
Tznqptjvn-!uif!2tu!Tznqptjvn!po!Joopwbujwf!Njdspxbwf!Sfnpuf!Tfotjoh-!Uif!5ui!Tznqptjvn!
po!Njdsptbufmmjuft!gps!Sfnpuf!Tfotjohॸ࢞൨ᄆć!!Jnqmfnfoubujpo! Po! Sfevdujpo! Mvu! Nfnpsz! Tj{f! Jo! Dijsq! Tjhobm! Hfofsbujpo! Gps! Tbufmmjuf!
Po.cpbse!TBS
5/3/āާཡଌಕຑ
౰‫ݪ‬ဘშć!!‫ ݗ‬ଆৌ‫ݪ‬ʄʑࠫപࡳ୹‫ܒ‬౳ǎळĪHPTBU.3ī຃੪ UBOTP.GUT.3༂ಘެʨˋʡɈ HIH ຩ୸ɺ˃ʌ
˂ʒʸĪβཹīॸ࢞ଞშćᥓນஶા
‫ޱ‬āāᅟć!!HPTBU.30UBOTP.GUT.3Ɉ༂ಘެʨˋʡʑʲʇʠ˃ȥɣ HIH ༏๱࢒ɍ࡜‫ݗ‬ɬຩ୸ȳɥ૚੼ཹʕʭ
ʠɾɿɺĪβཹīɬ੼౰ȱĂKBYB ࢒ɍ OJFT Ʌ༐࿚ă― 110 ―

\Ǒ^āਡ੫ৄᆔ
6/2āެਡఱିȫ໴ɦެ ਡ ఱ ᅰ ၸ ଞ Ɉ ି ໴ ɦ ௻ ࣍ެਡఱᅰၸଞ
્āāāāშ

ਡāಔ

ஒമ࡙࠲შ

ఊāშ

ᅰၸᄆโ

ି໴࣋ۙ
્āāშ

ࡖā࠰

Nbef!Tvejbob!
Nbifoesb

ɼˋʡʥʏɺ

ɾʘʼʢ൥ߔ

࣋ୂࢼວॸ࢞ˀʍʭɹʛʠ

31270502

Besjbovt!Xbxpsvouv

ɼˋʡʥʏɺ

ɼˋʡʥʏɺ൥ߔ

࣋ୂ࿍ऽၸᄎˀʍʭɹʛʠ

312705024

Xjsezbojohtjiɼˋʡʥʏɺ

ɼˋʡʥʏɺ൥ߔ

ஂ࣋ୂ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

312705024

Epoh!Bcevm!Dibmjeɼˋʡʥʏɺ

ɼˋʡʥʏɺ൥ߔ

ਆુ࿍ऽၸᄎˀʍʭɹʛʠ

312705024

Epej!Tvejbob

ɼˋʡʥʏɺ

ɼˋʡʥʏɺ൥ߔ

ਆુ࿍ऽၸᄎˀʍʭɹʛʠ

312705024

Vqbsj!Sbibsej

ɼˋʡʥʏɺ

QU/!Mfo!Joevtusj

‫ݻ‬ෳ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

312706027

Qsjpop!Kpoj!I/ɼˋʡʥʏɺ

QU/!Mfo!Joevtusj

ॸ࢞ۙ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

312706027

Svtuboupɼˋʡʥʏɺ

QU/!Mfo!Joevtusj

ॸ࢞ۙ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

312706027

Gfoej!B/ɼˋʡʥʏɺ

QU/!Mfo!Joevtusj

ॸ࢞ۙ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

312706027

Ljn!Nppo!Lxboh

࠴ਡ

Nvoibl!Uifbufs

࠵ෳ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

312706034

Opgfm!Mbhsptbt

ʭɻ˂ʬˋBufofp!ef!Nbojmb!
Vojwfstjuz-!Nbojmb!
Pctfswbupsz࣋ୂॸ࢞൅Ȼਗɩȵ࢏౦৘ც

312706038

Hmfoo!Gsbodp!Cbssptp!
ʭɻ˂ʬˋ
Hbdbm

Bufofp!ef!Nbojmb!
Vojwfstjuz-!Nbojmb!
Pctfswbupszߔ౺ॸ࢞൅Ȼਗɩȵ࢏౦৘ც

312706038

Ebojfm!Mvjt!Cbvujtub!

ʭɻ˂ʬˋBufofp!ef!Nbojmb!
Vojwfstjuz-!Nbojmb!
Pctfswbupszߔ౺ॸ࢞൅Ȼਗɩȵ࢏౦৘ც

312706038

Kpio!Qbpmp!Evsbob!
Njsboebʭɻ˂ʬˋBufofp!ef!Nbojmb!
Vojwfstjuz-!Nbojmb!
Pctfswbupszߔ౺ॸ࢞൅Ȼਗɩȵ࢏౦৘ც

312706038

Ebwje!Hjmft

ဴਡ

OBTB!TDJFODF!
TZTUFNT!BOE!
BQQMJDBUJPOT!JOD

Dijfg!
Sftfbsdi!
Tdjfoujtu

࿍ऽၸᄎȤɢɍ
်ູʓʷʢĜ‫ॽڷ‬
ৄࠓ‫ޏ‬

໴৮ల઺

312706031

Libusj!QsbeffqʥʩĜ˃ຄ႘൥ߔ൥ߔۡ
ᆅߔॸ࢞‫ݨ‬࣋‫ૅ࢞ॸۋ‬‫ܧ‬ଞ်ູʓʷʢĜȤɢɍ‫ޏࠓৄॽڷ‬ઞ‫ݡ‬໴৮ల઺

312706031ġ
312706032

Gfsb!Blcbs

ɼˋʡʥʏɺ

ʩʘˋୋᆏ൥ߔ

ߔ౺ࢼວॸ࢞ˀʍʭɹʛʠ

312707025ġ
312708033

Gbsbi!Tbskboj

ɼˋʡʥʏɺ

ʩʘˋୋᆏ൥ߔ

ߔ౺ࢼວॸ࢞ˀʍʭɹʛʠ

312707025ġ
312708033

Zvtob!Kbnjbiɼˋʡʥʏɺ

ʩʘˋୋᆏ൥ߔ

ߔ౺ࢼວॸ࢞ˀʍʭɹʛʠ

312707025ġ
312708033

Sbinj!Tvlnbxbuj

ɼˋʡʥʏɺ

ʩʘˋୋᆏ൥ߔ

ߔ౺ࢼວॸ࢞ˀʍʭɹʛʠ

312707025ġ
312708033

Sbinbe!Bsjg!
Tzbgsjoepɼˋʡʥʏɺ

ʩʘˋୋᆏ൥ߔ

ߔ౺ࢼວॸ࢞ˀʍʭɹʛʠ

312707025ġ
312708033

Tibejr!Bmjɼˋʡʥʏɺ

ʩʘˋୋᆏ൥ߔ

ߔ౺ࢼວॸ࢞ˀʍʭɹʛʠ

312707025ġ
312708033

Kbsvqpohtblvm!
Uibobxbu

ʗɼUibjmboe!
Fowsponfoubm!
Jotujuvuf࣋ୂ࿍ऽ‫݊ڤ‬೑ဦ

― 111 ―

312707039

ެਡఱᅰၸଞ
્āāāāშ

ਡāಔ

ஒമ࡙࠲შ

ఊāშ

ᅰၸᄆโ

ି໴࣋ۙ
્āāშ

ࡖā࠰

࣋ୂ

UFJ.DFSfT!
Bunptqifsjd!
Sftfbsdi!
Nffujoh໴৮ల઺

312707039

Xftu!Dfoufs!
Vojwfstjuz

࣋ୂ

ࢼວॸ࢞

ˀʍʭɹʛʠ

31270802

ʈɺʞʶˁ

Xftu!Dfoufs!
Vojwfstjuz

ਆુ

ࢼວॸ࢞

ˀʍʭɹʛʠ

31270802

Bemuzb!Qnvohlbtɼˋʡʥʏɺ

ʨˋʡˋ৙‫ݨ‬൥ߔ

ߔ౺

ʜɼˋʇ˃
ʯ˅ʈˁʸ

ˀʍʭɹʛʠ

3127 0 8 0 4 ġ312708026

Bcsfibn!Zfivebɼˋʡʥʏɺ

ʨˋʡˋ৙‫ݨ‬൥ߔ

ߔ౺

ʜɼˋʇ˃
ʯ˅ʈˁʸ

ˀʍʭɹʛʠ

3127 0 8 0 5 ġ31270902

Ejub!Xbizmj!
Qsjnbtuvuj

ɼˋʡʥʏɺ

ɼˋʡʥʏɺ൥ߔ

ߔ౺

ʜɼˋʇ˃
ʯ˅ʈˁʸ

ˀʍʭɹʛʠ

3127 0 8 0 5 ġ312708026

T/!B/!Obvmjuub!
Qbohhbcfbo

ɼˋʡʥʏɺ

ಫᅝ൥ߔ JFDʂʭɻʑĪɼˋʡʥʏɺ൥ߔīఊۙJKKTT ஈྩˀʍʭɹʛʠ

31270807

Hfssz!Cbhubtbʭɻ˂ʬˋʭɻ˂ʬˋ൥ߔ

࣋ୂ

ࢼວॸ࢞

࢏౦৘ც

31270809

Zbrj!Kjෂਡ๝ા‫ࡳݨ‬൥ߔߔ౺໴૚ˀʍʭɹʛʠ

312709033ġ
312709034

Kplp!Xjepepɼˋʡʥʏɺ

ɼˋʡʥʏɺࡳ୹࿎‫ݟ‬
ܾᅙෝ

ॸ࢞ۙ

໴૚

ˀʍʭɹʛʠ

312709033ġ
312709034

Bsnbe!Nvubublljs!
Bmbnɼˋʡʥʏɺ

ᄄ৩෿਒ಮߔ౺ɼˋʗĜˋʏʛʯ

ˀʍʭɹʛʠ

312709033ġ
312709037

Lbnbm!Obtibsveejo!
Nvtubqibʶ˄Ĝʏɺʞʢʄʢʏʿʢ˃൥ߔ

ဋߔෳ

ࢾฤங෮ۗ

ˀʍʭɹʛʠ

31270:08

Kftmff!C/!Npibnfeʶ˄Ĝʏɺʞʢʄʢʏʿʢ˃൥ߔ

ߔ‫ݨ‬ෳ

ࢾฤங෮ۗ

ˀʍʭɹʛʠ

31270:08

Tjwbebtt!
Uijsvdifmwbn!

ʶ˄Ĝʏɺʞʢʄʢʏʿʢ˃൥ߔ

ߔ‫ݨ‬ෳ

ࢾฤங෮ۗ

ˀʍʭɹʛʠ

31270:08

Opsbtijeb!Ne!Ejoʶ˄Ĝʏɺʞʢʄʢʏʿʢ˃൥ߔ

ߔငෳ

ࢾฤங෮ۗ

ˀʍʭɹʛʠ

31270:08

Sbtzjljo!Sptmboʶ˄Ĝʏɺʞʢʄʢʏʿʢ˃൥ߔ

ॸ࢞ۙ

ࢾฤங෮ۗ

ˀʍʭɹʛʠ

31270:08

Ebooz!N/!Hboebobɼˋʡʥʏɺ

ɼˋʡʥʏɺࡳ୹࿎‫ݟ‬
ܾᅙෝ

଱໸ॸ࢞ۙ

Usbjojohˀʍʭɹʛʠ

31270:037ġ
3127021039

Bejuzb!Jo{boj!
Xbiejzbuɼˋʡʥʏɺ

ɼˋʡʥʏɺࡳ୹࿎‫ݟ‬
ܾᅙෝ

ॸ࢞ۙ

Usbjojohˀʍʭɹʛʠ

31270:037ġ
3127021039

Bsjt!Tvszb!Zvobubɼˋʡʥʏɺ

ɼˋʡʥʏɺࡳ୹࿎‫ݟ‬
ܾᅙෝ

ॸ࢞ۙ

Usbjojohˀʍʭɹʛʠ

31270:037ġ
3127021039

Zpnj!Hvopɼˋʡʥʏɺ

ɼˋʡʥʏɺࡳ୹࿎‫ݟ‬
ܾᅙෝ

ॸ࢞ۙ

Usbjojohˀʍʭɹʛʠ

31270:037ġ
3127021039

Nbsdfmmjob!Bzveib!
Lsjtubouj!Ujubtbsj

ɼˋʡʥʏɺ

ɼˋʡʥʏɺࡳ୹࿎‫ݟ‬
ܾᅙෝ

ॸ࢞ۙ

Usbjojohˀʍʭɹʛʠ

31270:037ġ
3127021039

Gsboej!Bej!Lbibskjup

ɼˋʡʥʏɺ

ɼˋʡʥʏɺࡳ୹࿎‫ݟ‬
ܾᅙෝ

ॸ࢞ۙ

Usbjojohˀʍʭɹʛʠ

31270:037ġ
3127021039

Bhjuub!Sjbobsjt

ɼˋʡʥʏɺ

ɼˋʡʥʏɺࡳ୹࿎‫ݟ‬
ܾᅙෝ

ॸ࢞ۙ

Usbjojohˀʍʭɹʛʠ

31270:037ġ
3127021039

Eboozb!Nbibsboj!
Qvusj!Vubnjɼˋʡʥʏɺ

ɼˋʡʥʏɺࡳ୹࿎‫ݟ‬
ܾᅙෝ

ॸ࢞ۙ

Usbjojohˀʍʭɹʛʠ

31270:037ġ
3127021039

Kblb!Tfncjsjohɼˋʡʥʏɺ

ʨˋʡˋ৙‫ݨ‬൥ߔ

ߔငෳ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

31270:037

Jbo!Kptfqi!Nbuifvt!
Fexbseɼˋʡʥʏɺ

ʨˋʡˋ৙‫ݨ‬൥ߔ

ߔ‫ݨ‬ෳ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

31270:037

Ohvzfo!Wjfu!Mvpoh

ʱʠʢʸʱʠʢʸ‫ۡ୹ࡳߔݨ‬Ćۧහࡳ୹ॸ࢞ஒ

ॸ࢞ۙ࿍ऽၸᄎˀʍʭɹʛʠ

312702104

ʗɼ

Uibjmboe!Fowjsponfou!
Jotujuvuf!Gpvoebujpo
ĪUFJī

Wjdups!Dbspm!
Ifsoboef{!Npo{pvʈɺʞʶˁ

Tfcbtujbo!Jhobdjp!
Dibsdibmbd!Pdipb!

Kbsvqpohtblvm!
Uibobxbu― 112 ―

ެਡఱᅰၸଞ
્āāāāშ

ਡāಔ

ஒമ࡙࠲შ

ఊāშ

ᅰၸᄆโ

ି໴࣋ۙ
્āāშ

ࡖā࠰

Gbkbs!Efxbohhbɼˋʡʥʏɺ

ʄʐʻʶʘ൥ߔ

ߔ౺

ʜɼˋʇ˃
ʯ˅ʈˁʸ

ˀʍʭɹʛʠ

312702104ġ
3127021025

Objtb!Bhjmb

ɼˋʡʥʏɺ

ʄʐʻʶʘ൥ߔ

ߔ౺

ʜɼˋʇ˃
ʯ˅ʈˁʸ

ˀʍʭɹʛʠ

312702104ġ
3127021025

Tjtlb!Spibnɼˋʡʥʏɺ

ɾʘʼʢ൥ߔ

ߔ౺

ʜɼˋʇ˃
ʯ˅ʈˁʸ

ˀʍʭɹʛʠ

312702104ġ
3127021041

Sjwj!Nfjbsujɼˋʡʥʏɺ

ʄʐʻʶʘ൥ߔ

ߔ౺KTUȯȩɣ
ʍɼʀˋʑʯˁˋ

ˀʍʭɹʛʠ

312702102:ġ
312702103:

Zvej!Boesfbo!
Qibobnbɼˋʡʥʏɺ

ɼˋʡʥʏɺ൥ߔ

ߔ౺KTUȯȩɣ
ʍɼʀˋʑʯˁˋ

ˀʍʭɹʛʠ

312702102:ġ
312702103:

Zpiboesjɼˋʡʥʏɺ

ʩʘˋୋᆏ൥ߔ

ਆુࢼວॸ࢞ˀʍʭɹʛʠ

3127021037

Tfpoh.ppl!Qbsl

࠴ਡ࠴ਡ‫ۡ୹ࡳߔݨ‬

࣋ୂ

ࢼວॸ࢞

ˀʍʭɹʛʠ

3127021038

Cbtbsjɼˋʡʥʏɺ

ɼˋʡʥʏɺ൥ߔ

ॸ࢞ۙ

ࢼວॸ࢞

ˀʍʭɹʛʠ

3127021042

Qbnvohlbt!Ebveɼˋʡʥʏɺ

ɼˋʡʥʏɺ‫ۡߔݨ‬

ॸ࢞ۙ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

312702202

Ebejo!Nbonwpjoɼˋʡʥʏɺ

ɼˋʡʥʏɺ‫ۡߔݨ‬

ॸ࢞ۙ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

312702202

Flp!Kpoj!Qsjtujinupɼˋʡʥʏɺ

ɼˋʡʥʏɺ‫ۡߔݨ‬

ॸ࢞ۙ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

312702202

Gbksj!Ebsxjt

ɼˋʡʥʏɺ

ɼˋʡʥʏɺ‫ۡߔݨ‬

ॸ࢞ۙ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

312702202

Bsjf!Tfsjbxbo

ɼˋʡʥʏɺ

ɼˋʡʥʏɺ‫ۡߔݨ‬

ॸ࢞ۙ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

312702202

Btijg!Bnjovmmpi

ɼˋʡʥʏɺ

ɼˋʡʥʏɺ‫ۡߔݨ‬

ॸ࢞ۙ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

312702202

Ibob!Bsjtfob

ɼˋʡʥʏɺ

ɼˋʡʥʏɺ‫ۡߔݨ‬

ॸ࢞ۙ

࿍ऽၸᄎ

ˀʍʭɹʛʠ

312702202

Bdinbe!Nvojs

ɼˋʡʥʏɺ

ʨˋʡˋ৙‫ݨ‬൥ߔ

ਆુ

ࢼວॸ࢞

ˀʍʭɹʛʠ

3127022028ġ
3127023036

Qvsopnp!Tjej!
Qsjbncpepɼˋʡʥʏɺ

ɼˋʡʥʏɺ൥ߔஂ࣋ୂJKKTT ઞ‫ݡ‬ˀʍʭɹʛʠ

3127022032ġ
3127022034

Cbtbsjɼˋʡʥʏɺ

ɼˋʡʥʏɺ൥ߔ஝࣋JKKTT ઞ‫ݡ‬ˀʍʭɹʛʠ

3127022032ġ
3127022034

N/!Gbv{bo!F/Q/!

ɼˋʡʥʏɺ

ʮˁɾɻʐʻʼ൥ߔਆુJKKTT ઞ‫ݡ‬ˀʍʭɹʛʠ

3127022031ġ
3127022035

Joesb!Sjzboupɼˋʡʥʏɺ

ʮʟɻ˃ʭ˃൥ߔਆુJKKTT ઞ‫ݡ‬ˀʍʭɹʛʠ

3127022031ġ
3127022037

Exjzboupɼˋʡʥʏɺ

ɼˋʡʥʏɺਡᆏਂऋ
ۧහࣟ

ॸ࢞ۙ

Usbjojohˀʍʭɹʛʠ

3127022036ġ
3127023033

Bef!Qvusjɼˋʡʥʏɺ

ɼˋʡʥʏɺਡᆏਂऋ
ۧහࣟ

ॸ࢞ۙ

Usbjojohˀʍʭɹʛʠ

3127022036ġ
3127023033

Npnpo!Tbejzbunpɼˋʡʥʏɺ

ɼˋʡʥʏɺਡᆏਂऋ
ۧහࣟ

ॸ࢞ۙ

Usbjojohˀʍʭɹʛʠ

3127022036ġ
3127023033

Ibssz!Tfquboupɼˋʡʥʏɺ

ɼˋʡʥʏɺਡᆏਂऋ
ۧහࣟ

ॸ࢞ۙ

Usbjojohˀʍʭɹʛʠ

3127022036ġ
3127023033

Opgfm!Mbhsptbt

ʭɻ˂ʬˋɺʞʥʂ¦ʟ¦ʶʣˁ൥ߔ

஝࣋ਡ੫ʏˋʵʐɾʸઞ‫ݡ‬Ăࢼວॸ࢞

࢏౦৘ც

3127022027ġ
3127022036

Binfe!Nvlbmb{j!
Lbmvncb໤ɺʭ˂ʃʯ˄ʠ˂ɺ൥ߔ

ॸ࢞ۙਡ੫ʏˋʵʐɾ
ʸĂ൅ਗȵ

࢏౦৘ც

3127022032ġ
3127022034

Njbphfo!Tifoෂਡෂਡ‫ۡߔݨ‬

ஂ࣋ୂ

ࢼວॸ࢞

ᅔā‫ڰ‬

3127022027ġ
312702202:

Tvov!Xjcjsbnb

ɼˋʡʥʏɺ

ʄʐʻʶʘ൥ߔ

ਆુࢼວॸ࢞ˀʍʭɹʛʠ

312802021ġ
312802022

Fsgbotzbi!Bmjɼˋʡʥʏɺ

Ufmlpn ൥ߔਆુ໴૚ˀʍʭɹʛʠ

312802041ġ
31280308

Qfcfsmjo!Tjupnqvm

ɼˋʡʥʏɺ

ɼˋʡʥʏɺਡᆏਂऋ
ۧහࣟ

ॸ࢞ۙ

໴૚

ˀʍʭɹʛʠ

312802042ġ
31280306― 113 ―

ି໴࣋ۙ
્āāშ

ࡖā࠰

໴૚

ˀʍʭɹʛʠ

3128 0 3 0 3ġ
31280305

ॸ࢞ۙ

ࢼວॸ࢞

ˀʍʭɹʛʠ

3128 0 3 0 7ġ
312804023

ຄࢶ൥ߔ

ູ໸ॸ࢞ۙ

ॸ࢞൅ਗȵ

ˀʍʭɹʛʠ

312803031

࠴ਡ࠴ਡ‫ۡ୹ࡳߔݨ‬

ॸ࢞ۙ

ॸ࢞ଆၸᄎ

ˀʍʭɹʛʠ

312803034

Yvfipoh!DIFOෂਡ႘ࢶુཱྀ൥ߔ

ஂ࣋ୂʏˋʵʐɾʸઞ‫ݡ‬ᅔā‫ڰ‬

Ezbi!Sbinbxbuj!
Ij{cbspoɼˋʡʥʏɺ

ʄʐʻʶʘ൥ߔ

ਡ੫ৄᆔ‫ݻ‬ෳࢼວॸ࢞൅ਗȵˀʍʭɹʛʠ

312804028

Qsjnb!Xjebzbojɼˋʡʥʏɺ

ʄʐʻʶʘ൥ߔ

ਆુࢼວॸ࢞൅ਗȵˀʍʭɹʛʠ

312804028

Sjoj!Sbdinbxbuj

ɼˋʡʥʏɺ

ʄʐʻʶʘ൥ߔ

ਆુࢼວॸ࢞൅ਗȵˀʍʭɹʛʠ

312804028

Epej!Tvejbob

ɼˋʡʥʏɺ

ɼˋʡʥʏɺ൥ߔ

ਆુ

ʜɼˋʇ˃

ˀʍʭɹʛʠ

312804028

Hvobxboɼˋʡʥʏɺ

ɼˋʡʥʏɺ൥ߔ

࣋ୂ

ʜɼˋʇ˃

ˀʍʭɹʛʠ

312804028

Ebojfmf!Qfsjttjoɼˋʡʥʏɺ

ʩĜʟʽĜ൥ߔ

஝࣋ˇĜʇʏʿʛʯ

ˀʍʭɹʛʠ

312804023ġ
312804029[jbevm!Gbjf{

ɼˋʡʥʏɺ ˂ɺɾɼʑˁʸ൥ߔ

൥ߔۡ౺

൅ਗȵ

ˀʍʭɹʛʠ

31280403:

Ofjm!Jitboɼˋʡʥʏɺ ˂ɺɾɼʑˁʸ൥ߔ

ߔင౺

൅ਗȵ

ˀʍʭɹʛʠ

31280403:

Sptzmnbi!Tzbsjg

ɼˋʡʥʏɺ ˂ɺɾɼʑˁʸ൥ߔ

ߔင౺

൅ਗȵ

ˀʍʭɹʛʠ

31280403:

ެਡఱᅰၸଞ
્āāāāშ

ਡāಔஒമ࡙࠲შ

Npibnnbe!Obtvdib

ɼˋʡʥʏɺ

Vojwfstjuz!pg!
Qfncbohvobo!Kbzb

ਆુ

Epoh!Dibo!Ljn࠴ਡ࠴ਡ‫ۡ୹ࡳߔݨ‬Bejuzb!Sjbej!Hvtnbo

ɼˋʡʥʏɺ

Ljn!Divm!Lj

ఊāშ

ᅰၸᄆโ

312803026ġ
312803029

6/3/ā࣋ۙɈ‫ެޠ‬๧ਂެ ਡ ୸ ෟ Ć‫ ॸ ެ ޠ‬ୌ
્āāშ

ਡāშ

ᅙāოāಪ

ࡖā࠰

ˀʍʭɹʛʠ

ϱɼˋʡʥʏɺ
ϲ਑ৱϱC! ijnbtfob ႨଜĂʨˋʡˋૅଜϲ!੭
! ਑ৱɼˋʡʥʏɺࢼሆਡ
ᆴૢ࠵

31270504ġ
312705021

ϱࢼວॸ࢞൅ਗ
ϲT! znqptjvn!QQJ!Btjb.
Pdfbojb!3127ઞ‫ݡ‬‫ৄྣ܄ۿ‬࿥ࣸĪᅃਗᅅધī

ˀʍʭɹʛʠ

࠴ਡ

Joufsobujpobm!Dpowfoujpo!
Dfoufs!Kfkv

31270502:ġ
312705033

Joufsobujpobm!Tznqptjvn!
po!Sfnpuf!Tfotjoh!3127
ઞ‫ݡ‬࣋‫࢞ॸۋ‬ຑॄྣ

࢏౦ā৘ც

࠴ਡ

Joufsobujpobm!Dpowfoujpo!
Dfoufs!Kfkv

31270502:ġ
312705034

Joufsobujpobm!Tznqptjvn!
po!Sfnpuf!Tfotjoh!3127
ઞ‫ݡ‬

ࠞࣃ H யߔࡍ࿽ࣸ

ˀʍʭɹʛʠ

ɼˋʡʥʏɺ

ϱ Cijnbtfob Ⴈଜϲʐʻˇॻϳʟɻʵʥʌ˅൥ߔ

312705036ġ
31270608ϱϳࢼວॸ࢞൅ਗȵ‫ৄྣ܄ۿ‬࿥ࣸϲॸ࢞ɅबɥʭɻĜ˃ʡ෮ੈ ĪᅃਗᅅધīႨࣕāಫ୽ɼˋʡʥʏɺ

Ⴈ൥઴࠵ĂKJDBĂʴʌĜ˃༔‫ݨ‬൥ߔĂQspwjodjbm!
Bhsjdvmuvsbm!Bhfodz!pg!
Xftu!KbwbĂɾʘʼʢ൥ߔ!

31270702:ġ
312707037

S0EĂN0NĂDSB ຑĂำय़ ି൵ॸ࢞ॄྣ
Ʌ࠲ȳɥ൅ਗȵĪKTUīˀʍʭɹʛʠ

ɼˋʡʥʏɺ

ϱਡᆏਂऋۧහࣟĪMBQBOī 312707032ġ
ϲ Cijnbtfob ʨˋʡˋૅଜ
312707037

ϱϲਗ౰ާ৏˄Ĝʘଌ௠ଌঅɅ࠲ȳɥ෮౲Ă൅ਗȵࢼວॸ࢞ॄྣ
Īʫʶʓʢī

ˀʍʭɹʛʠ

ෂਡ

႘ࢶ Dijob!Obujpobm!
Dpowfoujpo!Dfoufs!

312708023ġ
312708025

3127JFFF!Joufsobujpobm!
Hfptdjfodf!boe!Sfnpuf!
Tfotjoh!TznqptjvnāĪJHBSTT3127īઞ‫ݡ‬Ăཡ࿍࣋‫࢞ॸۋ‬ຑॄྣႨࣕāಫ୽ɼˋʡʥʏɺ

Cpkpohqjdvoh ୈ၃Ă
Qspwjodjbm!Bhsjdvmuvsbm!
Bhfodz!pg!Xftu!Kbwb-!ʴ
ʌĜ˃༔‫ݨ‬൥ߔ -!KJDB

312708024ġ
312708031

ʞʑʠʍɼʠຝੈĂS0EĂ
N0N ำय़Ʌ࠲ȳɥ൅ਗȵି൵ॸ࢞ॄྣ
ĪKTUī― 114 ―

ᅙāāāო

ᅅāāધ

્āāშ

ਡāშ

ᅙāოāಪ

ࡖā࠰

ᅙāāāო

ᅅāāધ

ᅔā‫ڰ‬

ෂਡ

Dijob!Obujpobm!Dpowfoujpo!
Dfousf- ႘ࢶ

312708041ġ
31270907

Btjb!Pdfbojb!Hfptdjfodft!
ି൵ॸ࢞ॄྣ
Tpdjfuz!
ĪBPHTī
!3127Ʌઞ
ĪKBYBī
‫ݡ‬

Ⴈࣕāಫ୽

ɺʹ˂ʃ

Tu/!Mpvjt!Vojpo!Tubujpo!
Ipufm!

312708042ġ
31270906

Uif!24se!Joufsobujpobm!
Dpogfsfodf!po!Qsfdjtjpo!
BhsjdvmuvsfɅઞ‫ݡ‬Ⴈࣕāಫ୽ɼˋʡʥʏɺ

༔ࣞௐĂKJDBĂႨ൥઴࠵!ʴ
ʌĜ˃༔‫ݨ‬൥ߔĂಀʐʻˇୋ
༔౱ࣟĂʴʌĜ˃༔‫ݨ‬൥ߔĂKBTJOEP

31270908ġ
312709024

S0E-!N0N ำय़Ʌ࠲ȳɥບಪၫᅅધࡼĂʅʛʇʂʭʷĜʞɻˋʈĂএණ૗ઍĂN0N ஘შĂ ĪKJDBīບࡼय़‫ݪ‬ၡਠ!

ࣷນāூྷ

ʱʠʢʸ

ʱʠʢʸ‫ߔݨ‬ɺʃʟʷĜۧහࡳ୹ॸ࢞ஒ

31270909ġ
312709022

KTQT ሄဦག઺ૢࣞɅɢɥॸ ି൵ૢࣞॄྣ
࢞ૄຩĪKTQTī

໴৮āల઺

ʂˁˋʘ

Dbcbvx!Pctfswbupsz

31270:06ġ
31270:024ਡ੫ഊ঱྘ߏࠫപଌঅ
ĪDJOEJ.3īɅઞ‫ݡ‬ˀʍʭɹʛʠ

ɼˋʡʥʏɺ

ϱ˅ˋʴʇ๿
31270:02:ġϲਡᆏਂऋۧහࣟĪMBQBOī 31270:035

ϱ MBQBO ଱੓ JTBTU3127
ಪၫᅅધɁਆ‫!ܩ‬ϲ MBQBO ෳࠋɂĪMBQBOīJKKTTɅबɥ஽൒ਆ‫ܩ‬Ɉ෮யߔࡍ࿽ࣸ౲Ă൅Ȼਗɩȵ

樋৏āຼૂ

ʡɼʜ

Ebsntubeu-!Efvutdimboe!
ʘ˃ʸʑʗʐɺʸ

31270:036ġ
312702102

FVNFUTBU!3127!࡜௣‫ܒ‬౳ਡ੫‫ࡼޏ‬Ɂཡ࿍

໴৮āల઺

ʂˁˋʘ

Dbcbvx!Pctfswbupsz

31270:037ġ ਡ੫ഊ঱྘ߏࠫപଌঅ
31270:041
ĪDJOEJ.3īɅઞ‫ݡ‬ၒ஝ࣸຑॄྣ
Īʞʣʽɺʠˁʛʇīˀʍʭɹʛʠ

ɼˋʡʥʏɺ

Cijnbtfob ႨଜĂʨˋʡˋૅ
ଜĂʐʿʈʐʻʃ˃ʗૅଜ!

312702109ġ
3127021027

D ʨˋʡTBS ଌ௠ଌঅĂ൅ਗȵĂਂऋ࡙ߊ໻

‫ৄྣ܄ۿ‬࿥ࣸĪʈ˅Ĝʨ˃ʯ˅ʷ
ʥˋʠī

ߝঈāয়શ

ɺʹ˂ʃ

VTHT!Gpsu!Dpmmjot!Tdjfodf!
Dfoufs-!Sftpvsdf!gps!
Bewbodfe!Npefmjoh!Sppn!

312702209ġ
3127022023

Wfhfubujpo!Joefy!'!
Mboe!Tvsgbdf!Qifopmphz!
Xpsltipq!Ʌ୸ಌ

ି൵ॸ࢞ॄྣ
ĪKBYBī໴৮āల઺ɼˋʡɺ˂ɺʨĜʗ!Bszbcibuub!
Sftfbsdi!Jotujuvuf!pg!
Pctfswbujpobm!Tdjfodft

൥࡜˂ʺĜʠʓˋʏˋʈ࡙
3127022024ġ੮Ɉಡ඲Ăࢼວॸ࢞൅Ȼਗ
3127022029
ɩȵၒ஝ࣸຑॄྣ
Īʞʣʽɺʠˁʛʇī

Ⴈࣕāಫ୽

ɺʹ˂ʃ

ʲˋʏ˃ʱʣɺୋᆏ൥ߔ

3127022024ġ
ॸ࢞൅ਗȵ
3127022028‫ৄྣ܄ۿ‬࿥ࣸĪߔ੩ UE ᅅધīႨࣕāಫ୽ɼˋʡʥʏɺ

ϱQ! spwjodjbm!Bhsjdvmuvsbm!
Bhfodz!pg!Xftu!KbwbĂ
Cpkpohtpboh ୈ၃ϲʴʌĜ˃༔‫ݨ‬൥ߔϳC! bevoh!Ejtusjdu!
Bhsjdvmuvsf!Pggjdf!
ϴɾʘʼʢ൥ߔ

3127022032ġ DSB ำय़Ăॸ࢞Ʌ࠲ȳɥ൅ ି൵ॸ࢞ॄྣ
3127022038
ਗȵĂʞʑʠʍɼʠຝੈ!
ĪKTUī

ᅔā‫ڰ‬

ෂਡ

Cfjkjoh!Dpogfsfodf!Dfousf!

3127༃๱ෂਡࠞࣃ௶ၡࡳ୹
3127022034ġ
ৄᆔ൥‫ޏ‬Ʌઞ‫ݡ‬ȱɀĂ௶ၡ
3127022037
େୠ‫ྣ࢞ॸߔݨ‬ၒ஝ࣸ

Ⴈࣕāಫ୽

ɺʹ˂ʃ

Nptdpof!Dfoufs!

3127023022ġ 3127!BHV!Gbmm!Nffujoh ઞ
3127023028‫ݡ‬Ćཡ࿍!

‫ৄྣ܄ۿ‬࿥ࣸĪʈ˅Ĝʨ˃ʯ˅ʷ
ʥˋʠī

ᅔā‫ڰ‬

ɺʹ˂ʃ

Nptdpof!Dfoufs!

3127023022ġ 3127!BHV!Gbmm!Nffujoh ઞ
3127023029‫ݡ‬Ćཡ࿍!

‫ྣ࢞ॸߔݨ‬ၒ஝ࣸ

ᥓນāஶા

ɺʹ˂ʃ

Nptdpof!Dfoufs!

3127023022ġ 3127!BHV!Gbmm!Nffujoh ઞ
3127023029‫ݡ‬Ćཡ࿍!

ି൵ॸ࢞ॄྣ
ĪKBYBī

ટ๜āც९

ɺʹ˂ʃ

Nptdpof!Dfoufs!

3127023022ġ 3127!BHV!Gbmm!Nffujoh ઞ
3127023029‫ݡ‬Ćཡ࿍!

ି൵ॸ࢞ॄྣ
ĪKBYBī

ɼˋʡʥʏɺ

ϱʓʱˁʑʶ˄ʛʠ൥ߔ
ϲ Cijnbtfob ʨˋʡˋૅଜ!

ϱ!൥
! ߔ࠰ৄᆔࢾฤ࢒ɍྦ਄
‫ৄྣ܄ۿ‬࿥ࣸ
3127023032ġ
ଌঅɅबɥ൅ਗȵĪʈ˅Ĝʨ˃ʯ˅ʷ
31280205
ϲD! ʨˋʡTBS ྦ਄ଌ௠ଌ
ʥˋʠī
অɈ൅ਗȵ

ˀʍʭɹʛʠ

― 115 ―

‫ৄྣ܄ۿ‬࿥ࣸĪߔ੩ UE ᅅધīၒ஝ࣸຑॄྣ
Īʞʣʽɺʠˁʛʇīࢼວॸ࢞ॄྣ
ĪKBYBī

્āāშ

ਡāშ

ᅙāოāಪ

ࡖā࠰

ˀʍʭɹʛʠ

ɼˋʡʥʏɺ

ϱɼˋʡʥʏɺ൥ߔ
ϲ Cijnbtfob ʨˋʡˋૅଜ!
ϳʓʱˁʑʶ˄ʛʠ൥ߔ

312802027ġ
312802033ϱ൅ਗȵ!ϲ D ʨˋʡTBS ྦ ‫ৄྣ܄ۿ‬࿥ࣸ਄ଌ௠ଌঅɈ൅ਗȵ!ϳ൥ߔ Īʈ˅Ĝʨ˃ʯ˅ʷʥˋʠī࠰ৄᆔࢾฤ൅ਗȵႨࣕāಫ୽ɼˋʡʥʏɺ

ϱʴʌĜ˃༔‫ݨ‬൥ߔϲ!ಀ
! ʐʻˇCpkpohtpboh ୈ၃ϳɾʘʼʢ൥ߔ

312802034ġ
312802039

ϱϳॸ࢞൅ਗȵĂϲʞʑʠʍɼʠຝੈି൵ॸ࢞ॄྣ
ĪKTUī

Ⴈࣕāಫ୽

ʑɼʑ

TDPS!Hmpcbm!Qspqfsuz!
boe!Dbtvbmuz!
sfjotvsbodf-Tbsnbq!TBā

312803031ġ
312803036

ॸ࢞൅ਗȵ‫ৄྣ܄ۿ‬࿥ࣸĪߔ੩ UE ᅅધīႨࣕāಫ୽ɼˋʡʥʏɺ

ϱʴʌĜ˃༔‫ݨ‬൥ߔϲɾʘʼʢ൥ߔ࢒ɍୈ၃

312804023ġ
312804029

NpB ஘შĂॸ࢞൅ਗȵି൵ॸ࢞ॄྣ
ĪKTUīˀʍʭɹʛʠ

ɼˋʡʥʏɺ

ϱɼˋʡʥʏɺ฽ඖණࠣᆅࣟ
ϲ Cijnbtfob ʨˋʡˋૅଜ
ϳʓʱˁʑʶ˄ʛʠ൥ߔ
ϴʏɺʇॻෝକ࢒ɍୈ၃

31280402:ġ
31280403:

ϱˇĜʇʏʿʛʯ!ϲ D ʨˋʡTBS ྦ਄ଌঅ൅ਗȵϳਆ‫!ܩ‬ϴॻඪૢɬ࿍ऽၸ
ᄎĂ฽ඖණএණ෮ੈ

‫ৄྣ܄ۿ‬࿥ࣸĪʈ˅Ĝʨ˃ʯ˅ʷʥˋʠī਒࣌ā‫ڟ‬਑ɼˋʡʥʏɺ

ϱɼˋʡʥʏɺ฽ඖණࠣᆅࣟ
ϲʏɺʇॻʏɺʇીୈ၃

31280402:ġ
31280403:

ϱˇĜʇʏʿʛʯ!ϲʏɺʇીୈ၃Ʌɀ฽ඖණএණ෮ੈ

‫ৄྣ܄ۿ‬࿥ࣸĪʈ˅Ĝʨ˃ʯ˅ʷ
ʥˋʠī

樋৏āຼૂ

ɺʹ˂ʃ

OBTB!Bnft ॸ࢞ʓˋʗĜ!
NPGGFUU!GJFME

312804033ġ
312804035!ॸ࢞൅Ȼਗɩȵ!

‫ৄྣ܄ۿ‬࿥ࣸĪණ࢝࡜௣ृ WMī― 116 ―

ᅙāāāო

ᅅāāધ

Įǒ^ā࣋‫ߤۋ‬຦
7/2/āਆࡹĪߔငĆ൥ߔۡīš࿱၅࣋‫ۋ‬Ī࣋ᅤ‫ݻ‬าɅഊຎīࠞࣃʋɺĪࠞࣃĆ౺ߤĆ‫ߔݨ‬īĶۧහȥɣɈණ࢝࿍೸ࠫപķĪߝঈī࣋ᅤ๐ާ‫ݨ‬ᄆĪࠞࣃʋɺ࠲ᇦīĶණ࢝ࠞࣃɂ˂ʺĜʠʓˋʏˋʈǍĂǎķĪDFSfT ࣋ۙīࢼฆಮᄑࡊೣ‫ݨ‬ᄆĪဘᆅߔīĶᆵߔ໴ᄑĪǐīķĪႨഽīࢼฆಮᄑࡊೣ‫ݨ‬ᄆĪဘᆅߔīĶ๝૱࡜ߔ໴ᄑ‫୔ܩ‬ĪǏīķĪᥓນīšߔငɈਆࡹĪ߂ߔငɁಮᄑ࣋‫ۋ‬Ɉ‫ێ‬ငɬඐຎīᆅߔငණ࢝‫!ݨߔݨ‬ಮᄑ‫ݨ‬ᄆĶࠞࣃ˂ʺĜʠʓˋʏˋʈ‫ޱ‬ሄǍķĪྼୌ‫ݨ‬ᄆīĪࣷນĆႨࣕīᆅߔငණ࢝‫!ݨߔݨ‬ಮᄑ‫ݨ‬ᄆĶࠞࣃ˂ʺĜʠʓˋʏˋʈ‫ޱ‬ሄǎķĪྼୌ‫ݨ‬ᄆīĪ樋৏Ć໴৮īᆅߔငණ࢝‫!ݨߔݨ‬ಮᄑ‫ݨ‬ᄆĶ൥࡜˂ʺĜʠʓˋʏˋʈķĪ樋৏Ć໴৮īᆅߔငණ࢝‫!ݨߔݨ‬ಮᄑ‫ݨ‬ᄆĶ˂ʺĜʠʓˋʏˋʈ໴ᄑķĪࣷນīᆅߔငණ࢝‫!ݨߔݨ‬ಮᄑ‫ݨ‬ᄆĶ˂ʺĜʠʓˋʏˋʈĆHJT ଌ୔ķĪႨࣕī৙ߔင௶ၡ‫ކ‬ജߔ‫!ݨ‬ಮᄑ‫ݨ‬ᄆĶ๝૱༜ɂ৉ķĪ࢏౦Ć໴৮ī৙ߔင௶ၡ‫ކ‬ജߔ‫!ݨ‬ಮᄑ‫ݨ‬ᄆĶʟĜʗʱĜʑķĪߝঈī৙ߔင௶ၡ‫ކ‬ജߔ‫!ݨ‬ಮᄑ‫ݨ‬ᄆĶ˂ʺĜʠʓˋʏˋʈ৙ߔķĪ࢏౦ĆˀʍʭɹʛʠĆᥓນīš൥ߔۡᆅߔॸ࢞‫ݨ‬Ćණ࢝౺ჩ५‫ߔݨ‬ಮ০ණ࢝‫ߔݨ‬ʋĜʑࠞࣃ˂ʺĜʠʓˋʏˋʈູሄǍĪࣷນĆႨࣕīࠞࣃ˂ʺĜʠʓˋʏˋʈູሄǎĪ樋৏īࠞࣃ˂ʺĜʠʓˋʏˋʈⅠBĪ樋৏īࠞࣃ˂ʺĜʠʓˋʏˋʈⅠCĪࣷນīࠞࣃ˂ʺĜʠʓˋʏˋʈⅡBĪ樋৏īࠞࣃ˂ʺĜʠʓˋʏˋʈⅡCĪႨࣕīࠞࣃ˂ʺĜʠʓˋʏˋʈ်ູਆࡹĪ௄‫܊‬ĆཆĆ樋৏ĆࣷນĆ໴৮īš൥ߔۡᅃਗ‫ݨ࢞ॸߔݨ‬Ć௶ၡ‫ߔݨ‬ಮ০ʶɼʇ˅༜˂ʺĜʠʓˋʏˋʈğག઺೐ࡖĆག઺ষࡖĪˀʍʭɹʛʠĆ‫ۈ‬ഺī˂ʺĜʠʓˋʏˋʈࠞࣃ௶ၡߔⅠğག઺೐ࡖĆག઺ষࡖĪᇑᄄĆ࢏౦Ćᥓນī˂ʺĜʠʓˋʏˋʈࡊೣ௶ၡሄğག઺೐ࡖĆག઺ষࡖĪႨഽĆߝঈīܾᅙ˂ʺĜʠʓˋʏˋʈ৙ߔğག઺೐ࡖĆག઺ষࡖĪ࢏౦ĆߝঈĆ໴৮ī˂ʺĜʠʓˋʏˋʈ৙ߔູሄğག઺೐ࡖĆག઺ষࡖĪႨഽĆˀʍʭɹʛʠĆ‫ۈ‬ഺīĪ࿥ī࿱၅࣋‫࣋ۋ‬ᅤ๐ާ‫ݨ‬ᄆĶණ࢝ࠞࣃɂ˂ʺĜʠʓˋʏˋʈǍĂǎķ‫ێ‬ᅿ
DFSfT ࣋ۙǎʈ˃Ĝʯ౫Ʌɢɥߒ༃ယඐɁȳăႨ༃๱ɉ‫ࡥݚ‬Ɉୂࣞ໘ᅎɁȱȹă
Ī3127༃๱ʏˁʨʑɢɤསౌīŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖ
Ŗ൥࡜ܸಹɂ˂ʺĜʠʓˋʏˋʈĪǏ‫ޑ‬ī໴৮ల઺‫ܒ‬౳˂ʺĜʠʓˋʏˋʈȥɣəȢɀȩɥණ࢝ࡤჹɁɈ൥࡜ܸಹɈএ௻ɂ‫ݻ‬൨ɬ‫ޱ‬ತăɘȹĂȷɈࠫപࡳ୹ɂ
ॳ௠ၫၭȤɢɍளᅰो‫ކ‬ɅȾȞɀɜ௘‫ގ‬ăŖʶɼʇ˅༜˂ʺĜʠʓˋʏˋʈĪǏ‫ޑ‬īˀʍʭɹʛʠĆǰĆʑ˂Ćʑʶˋʠˀ
ʶɼʇ˅༜˂ʺĜʠʓˋʏˋʈɅȤȫɥൣ࿍โɄਗ౰ާ৏˄ĜʘĪTzouifujd! Bqfsuvsf! SbebsĈTBSīɈʏʑʞʸɂ‫ކ‬ജ‫ސ‬಑ɅȾȞɀ‫ސ‬ತȱĂȭɈ TBS Ʌɢɥණ࢝ࠫപɂ႕੠ɄɃɈࠞࣃʺʣʗ˂ˋʈɒɈܾᅙɬ௘‫ގ‬ăŖණ࢝൥࡜Ɉ˂ʺĜʠʓˋʏˋʈĪǏ‫ޑ‬ī࢏౦৘ცණ࢝‫ݗ‬ඤ‫ݛ‬ɞ‫ܸࣃܛ‬ಹɄɃĂ൥࡜ࠞࣃȦଜ‫ޏ‬โɄ෉ᄆɬୠɛɥɄȥĂ൥࡜˂ʺĜʠʓˋʏˋʈɈॸ࢞ȦȭɦɣɈૢ௣ɂɃɈɢȠɅ࠲ɩɥȥɅȾȞɀ‫ޱ‬ತă

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Ŗఆဘɬൎ௣ɂȱȹ˂ʺĜʠʓˋʏˋʈĪǏ‫ޑ‬īߝঈয়શɩȹȱȹȻɈୣࠞࣃɈəɄɣȴĂණ࢝೔ൌɈ࡜েĆࠞࣃɅ୭ᅟɄᄜߠɬɉȹȳఆ౺ɈᅕęɄ௻ൔɬࠫപȳɥఆ౺˂ʺĜʠʓˋʏˋʈɅȾȞɀĂȷɈঈᆅɂ੕ಪ඘Ɉॸ࢞ɅȾȞɀ௘‫ގ‬ăŖ‫܀‬Ćਏ౉ɬəɥ˂ʺĜʠʓˋʏˋʈĪǏ‫ޑ‬ī樋৏ຼૂ໲ęɈ๏࡜Ʌ෸ಞ࠲ɩɥ‫܀‬Ăਏ౉ɬ˂ʺĜʠʓˋʏˋʈɁɃɈɢȠɅəɥɈȥĂȷɈঈᆅĂܾᅙၫၭĂॸ࢞ᇉɬຝɘȢɀತცăŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖ
7/3/āሄဦ൨ᄆ௘‫ގ‬āိ౰39༃๱Ɉ DFSfT ࣋ۙɈૄຩɅɢɥག઺Ɉߔ‫ڮ‬ଲຶଞɉǓშɁȱȹăୌ઺ሄဦ! 24შĂലࣞሄဦ27შɂɂɜɅĂȭȭɁ௘‫ގ‬ȱɘȳăɄȤĂ‫ێ‬ငɈၫɈག઺ሄဦᅟૉɉʣʽĜʑ˄ʗĜိ౰3:༃ǏॢਖĪOp/247īɅऻ੪ȱɀȤɤɘȳă
ĺག઺ሄဦĻ
ߔ౺્შć‫ޠ‬༂อā‫چ‬ᆵၑĪIbjsfuj!Bmjgīሄဦ൨ᄆć!!E fmjofbujpo! pg! efcsjt.dpwfsfe! hmbdjfst! cbtfe! po! b! dpncjobujpo! pg! hfpnpsqipnfusjd!!
qbsbnfufst!boe!Mboetbu!\UJS0
ĪOJS0TXJSī^!cboe!sbujp!
ණवဿౘɂˁˋʡʍʛʠɅɢɥʨˋʡ྘ \UJS0ĪOJS0TXJSī^ Ʌɢɥ࠾ओɁဒɩɦȹ࿉‫ݭ‬Ɉෆ୸ಮāā০ćᆅߔॸ࢞‫ݨ‬ණ࢝౺ჩ५‫ߔݨ‬ಮ০ණ࢝‫ߔݨ‬ʋĜʑߔāā‫ڮ‬ćག઺Īᆅߔīૄຩ࣋ۙćࣷນூྷ
ߔ౺્შćཆā୐ᇥĪYjvmjbo!Cbjīሄဦ൨ᄆć!!Bobmztjt!pg!Eftfsujgjdbujpo!Tjuvbujpo!Vtjoh!Sfnpuf!Tfotjoh!boe!HJT!.B!Dbtf!Tuvez!jo!Pohojve!
Cboofs-!Ipsrjo!Tboez!Mboe-!Dijcb.
!
཰߿ഇ੉ཌྷ‫ݛ‬ණ‫ۊ‬ɅȤȫɥ˂ʺĜʠʓˋʏˋʈɂ HJT ɬᅙȞȹ๲ණᆀᅙĆྡဒဿ‫ݛ‬Ɉ‫ސ‬಑ĝෂਡʳ˃ʙˋ੉ණĂʂˋʣʽʡࡔɅȤȫɥૢᇉॸ࢞ĝಮāā০ćᆅߔॸ࢞‫!ݨ‬ණ࢝౺ჩ५‫ߔݨ‬ಮ০ණ࢝‫ߔݨ‬ʋĜʑߔāā‫ڮ‬ćག઺Īߔ୹īૄຩ࣋ۙćࣷນூྷ
ߔ౺્შćOhvzfo!Wjfu!Mvpoh
ሄဦ൨ᄆć!!Nbqqjoh! pg! Uspqjdbm! Gpsftu! boe! Cjpnbtt! Ftujnbujpo! Vtjoh! Njdspxbwf! boe! Pqujdbm! Sfnpuf!
Tfotjoh!
ʶɼʇ˅༜Ȥɢɍ৉ߔ˂ʺĜʠʓˋʏˋʈɅɢɥ༂൑ᆹɈʶʛʬˋʈɂʨɼʂʶʑైฤɅ࠲ȳɥॸ࢞ಮāā০ćᆅߔॸ࢞‫!ݨ‬ණ࢝౺ჩ५‫ߔݨ‬ಮ০ණ࢝‫ߔݨ‬ʋĜʑߔāā‫ڮ‬ćག઺Īߔ୹īૄຩ࣋ۙćࣷນூྷ
ߔ౺્შć࢔੸ࡦ൥
ሄဦ൨ᄆćழळ‫ܒ‬౳Ʌɢɥ๝ᆋ೸ࠫപɈ‫ܒ‬౳๝‫ڮ‬ဿ຦ᄎ൨ɂ‫ސ‬ड़଴ၭɈอ‫ڨ‬ಮāā০ćᅃਗ‫௶ݨ࢞ॸߔݨ‬ၡ‫ߔݨ‬ಮ০ඪ༑௶ၡʋĜʑߔāā‫ڮ‬ćག઺Ī৙ߔīૄຩ࣋ۙćK/U/ ʑ˂!ʑʶˋʞɻˀ
ߔ౺્შćIvtovm!Lbvtbsjbo
ሄဦ൨ᄆćɼˋʡʥʏɺĆ˃ʩ๿႘င‫࠹ܨ‬ɅȤȫɥʉɼੋယ࿫Ɉණଋʶʛʬˋʈɂ೔ှ༜ਗ౰ާ৏˄Ĝʘ‫ސ‬಑ಮāā০ćᅃਗ‫௶ݨ࢞ॸߔݨ‬ၡ‫ߔݨ‬ಮ০ඪ༑௶ၡʋĜʑߔāā‫ڮ‬ćག઺Ī৙ߔīૄຩ࣋ۙćK/U/ ʑ˂!ʑʶˋʞɻˀ

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ߔ౺્შćNpie![bgsj!Cjo!Cbibsveejoሄဦ൨ᄆć‫ܟ‬ှ༜ਗ౰ާ৏˄ĜʘɈॳບć๝༜ჟࣗଆɁɈʩʛʙɺ˄ɼɺˋʞʢɂઢᅸএ௣Ɉଌঅ
ಮāā০ćᅃਗ‫௶ݨ࢞ॸߔݨ‬ၡ‫ߔݨ‬ಮ০ඪ༑௶ၡʋĜʑߔāā‫ڮ‬ćག઺Ī৙ߔīૄຩ࣋ۙćK/U/ ʑ˂!ʑʶˋʞɻˀ
ߔ౺્შćCbncboh!Tfujbej
ሄဦ൨ᄆćʺʨɼ˃‫ڽ‬ହोધɬᅙȞȹჟఱਂऋ࡙࢒ɍழळ‫ܒ‬౳ʯˁʛʠʭʁĜʸɈʇɼʛʇ˃ʛʇɂ౼დਗ౰ާ
৏˄ĜʘఒਖஐᆅʏʑʞʸɈާཡಮāā০ćᅃਗ‫௶ݨ࢞ॸߔݨ‬ၡ‫ߔݨ‬ಮ০ඪ༑௶ၡʋĜʑߔāā‫ڮ‬ćག઺Ī৙ߔīૄຩ࣋ۙćK/U/ ʑ˂!ʑʶˋʞɻˀ
ĺୌ઺ሄဦĻ
ಫᅝ൥ߔ൥ߔۡᆅߔॸ࢞‫ݨ‬ණ࢝౺ჩ५‫ߔݨ‬ಮ০ණ࢝‫ߔݨ‬ʋĜʑୌᆡ્āშॸ࢞‫ݻ‬൨შ

ߔā‫ڮ‬

ૄຩ࣋ۙ

੧‫ګۈ‬ᆊUSNN ȦനȢȹɺʐɺ‫ۊ‬ɅȤȫɥਏ۫ࣅ๱ɂණवɈ࠲ब

ୌ઺Īᆅߔī 樋৏ຼૂழߚঈಫ਑ા

‫ܒ‬౳ʟĜʗɬᅙȞȹ౉‫ے‬౺દᆲɈණ‫ູۊ‬౯࢒ɍঌେᅟۚɈଌൔ༘‫ڐ‬ୌ઺Īᆅߔī Ⴈࣕಫ୽‫ڤ‬āൗၤ

Bobmz{joh! Tqbujp.Ufnqpsbm! Mboe.Vtf! boe! Mboe.Dpwfs! Dibohf! jo! Tbokjboh!
ୌ઺Īᆅߔī ࣷນூྷQmbjo!up!gjoe!Esjwjoh!Gpsdft鄧āགဦᆱ‫ݭ‬ᆔ‫ۊ‬๲ණྡဒɈ૪ऋ࠰ဿ຦ɂॄ੟ཡ๐ĆࠞࣃဿೋɈ࠲ᇦ

ୌ઺Īᆅߔī ࣷນூྷ৮ᆯ൥‫ބ‬‫چ‬ကजટණழᆔ‫ۊ‬ɅȤȫɥၪଗ౯ဘଋɈ‫ھ‬਄ູ౯ĝဏ๿ॻ‫ڭ‬ൿनರႿ෨ટ௱‫ݎ‬ණࣾழᆔ‫ۊ‬ɬൎ௣ɂȱɀĝୌ઺Īᆅߔī ࣷນூྷ୷ဩఱ‫ڠ‬ఱ‫֭ڠ‬ဏࣣ‫ૂشݪࡄڠش‬༭‫ࢲ୺ڠش‬౶ෝૂ༭΋ȜΑਘၭ્āშॸ࢞‫ݻ‬൨შ

ߔā‫ڮ‬

ૄຩ࣋ۙ

ৡࢀථც

ˁʶˋˁɼʘĜɂණ௫പࡉɅɢɥൎᆔ५ʀɺ˅ʖ˃ɈˁɼʘĜ྘ຩ୸ୌ઺Ī৙ߔī ࢏౦৘ცᄘę޼ᆢ‫ގ‬ਂऋ࡙ࠫപ࢒ɍౘඩʺʟ˃ʟĜʗɬᅙȞȹ HPTBU ‫ܒ‬౳Ɉʹʗˋ༏๱ʟĜʗɈॳ௠‫ސ‬಑

ୌ઺Ī৙ߔī ᥓນஶાழைāഏණ௫ȥɣɈ˂ʺĜʠʓˋʏˋʈɅɢɥ౉௾࡜Ɉܴ෸ʃˁʸᆲĆ਒๱ʯ˅ʭɹɼ
˃ࠫപɈ࿎‫ݟ‬ୌ઺Ī৙ߔī ໴৮ల઺ཝટ౗൥˂ʺĜʠʓˋʏˋʈɅɢɥ໲Ⴈ௫ऋɈʀɺ˅ʖ˃ʠ˄ˋʡ‫ސ‬಑ୌ઺Ī৙ߔī ໴৮ల઺‫ۈ‬௫ाࣝ

ਗ౰ާ৏˄ĜʘɂऋએɅɢɥɼˋʡʥʏɺĆෂငʐʻˇॻɈ৽গߔโණ‫ۊ‬။ীɈ෮ੈୌ઺Ī৙ߔī

K/U/ ʑ˂! ʑʶˋʞɻˀෂഺ‫ိޕ‬

ਂऋ࡙຃੪Ǵʨˋʡ‫ܟ‬ှ༜ਗ౰ާ৏˄Ĝʘᅙʩʛʙɺ˄ĜɺˋʞʢɈާཡɂȷ
Ɉ࿎‫ݟ‬ୌ઺Ī৙ߔī

K/U/ ʑ˂! ʑʶˋʞɻˀ݊Ⴈ‫ވ‬౺

જ૫ই๘दʟĜʗɬᅙȞȹ೔༜व MjEBS ʟĜʗɈ੔এɅ࠲ȳɥॸ࢞ୌ઺Ī৙ߔī

Ⴈഽ‫ݣ‬ც
ߝঈয়શɼˋʡʥʏɺ൥ߔ๝࡜৙ߔಮ০Īʘʮ˃ʟɻʈ˂Ĝʯ˅ʈˁʸīୌᆡ
્āშ
ழટ໘ᅂఱ

ॸ࢞‫ݻ‬൨შ
ழळ‫ܒ‬౳຃੪‫ܟ‬ှ༜ਗ౰ާ৏˄ĜʘᅙɈʶɼʇ˅ʑʠ˂ʛʯɺˋʞʢɈާཡ

― 119 ―

ߔā‫ڮ‬

ૄຩ࣋ۙ

ୌ઺Ī৙ߔī

K/U/ ʑ˂! ʑʶˋʞɻˀĺലࣞሄဦĻಫᅝ൥ߔᆅߔငණ࢝‫ݨߔݨ‬્āშॸ࢞‫ݻ‬൨შ

ߔā‫ڮ‬

ૄຩ࣋ۙ

Ⴅ৮౷ୃ

ಫᅝॻۗᘧைᆔ‫ۊ‬Ɉ඾೧࿹‫ݷ‬ᆲɈ੔ॳບ

ߔ઺Īᆅߔī ࣷນூྷ྅๜౔ୃ‫ݚ‬഍൤ණɬਟɚඇ෿ɅȤȫɥ௑બ౯඾೧Ɉ૪ऋ࠰ယ࿫Ʌ࠲ȳɥॸ࢞ߔ઺Īᆅߔī ࣷນூྷ਒࣌ᄬ஝ʧɼʩĜʑʲʇʠ˃ʟĜʗɬᅙȞȹ౉‫ ے‬Cbdufsjbm!Mfbg!Cmjhiu ࿒Ɉ࿎‫ݟ‬ߔ઺Īᆅߔī Ⴈࣕಫ୽๲ੂ൱ັ

Tfoujofm.2ʟĜʗɬᅙȞȹ౉‫੼ے‬࿥૪ࡖɈ཯်

ߔ઺Īᆅߔī Ⴈࣕಫ୽ஷશāহാိᅖ༂൑‫ۊ‬ɅȤȫɥಀဇှੇȦʀ˃ʣĜʣʿএ௣ɈཡൿɅᅇȢɥ‫ࣗ܆‬ćߔ઺Īᆅߔī ྦྷ৏ຼૂ3125.27༃ɈૢᇉɅȾȞɀ྘‫ݴݣ‬ᇑ

ʭɿĜʒʡɺ˄ɼ࡜௣˄ĜʘɅɢɥൎᆔ౯ਏ౉ʓ˃૵຦ෆ୸य़‫ݪ‬Ɉණ௫ਏ౉Ʌ
ൎȳɥಪ਄౯Ɉູ෡ć3127༃ǔॢǏ໲Ɉႈ഍཰๿ɅȤȫɥૢᇉ‫ސ‬಑ߔ઺Īᆅߔī ྦྷ৏ຼૂಫᅝ൥ߔ৙ߔင௶ၡ‫ކ‬ജߔ‫ݨ‬્āშॸ࢞‫ݻ‬൨შ

ߔā‫ڮ‬

ૄຩ࣋ۙ

ৡࢀৰၓ

ɌɘɩɤǔਖɈ‫ܒ‬౳‫ކ‬ജʟʐʗ˃ඩɅɢɥ൥࡜ʀɺ˅ʖ˃৉ߔโৎȯɈైฤߔ઺Ī৙ߔī ࢏౦৘ცఠ൲୻ࡦණ௫ࠫപക඲ɬᅙȞȹ൥࡜ʀɺ˅ʖ˃Ɉଈ๱Ʌɢɥᆙशဿ‫ݛ‬Ɉ‫ސ‬಑ߔ઺Ī৙ߔī ࢏౦৘ც௄ഺᄲိ‫ܟ‬ှ༜ਗ౰ާ৏˄ĜʘʏʑʞʸᅙฆఒʏʑʞʸɈާཡߔ઺Ī৙ߔī

K/U/ ʑ˂! ʑʶˋ
ʞɻˀ

๧ᵚථᇾā

ਗ౰ާ৏˄ĜʘɅɢɥ‫ے‬Ɉʭɿʦ˅ʐĜࠫപߔ઺Ī৙ߔī

K/U/ ʑ˂! ʑʶˋ
ʞɻˀ

ᄘ๜ਞୃā

ྫယࠍொਗ౰ާ৏˄ĜʘɅɢɥర੠ණ‫ۊ‬Ɉྡޮෆ୸ćछႨණరɒɈܾᅙ

ߔ઺Ī৙ߔī

K/U/ ʑ˂! ʑʶˋ
ʞɻˀ

ழੲణহ

ʨɼʂʶʑ༇ௌɅɢɥ‫ێ‬બ‫ݛ‬ඖ೧࢒ɍ໩બ‫ݛ‬ඖ೧Ɉ൥࡜ෂ༏๱ဿ຦Ɉ‫ސ‬಑ߔ઺Ī৙ߔī ᥓນஶા࠾‫ۈ‬ள‫ێ‬ழळ QD ɬᅙȞȹ൥࡜ࠞࣃࠫപക඲Ɉާཡ

ߔ઺Ī৙ߔī ໴৮ల઺Ⴅྪࢵશಇો࡜௣‫ܒ‬౳ɌɘɩɤǔਖɈ೔๏໲ଗᆲʟĜʗɈॳ௠ߔ઺Ī৙ߔī ໴৮ల઺๜ෂྰ෿ࡢ

TgN ɬᆀᅙȱȹఝᆹ৭ഢ༘‫ڐ‬Ʌ࠲ȳɥॸ࢞ߔ઺Ī৙ߔī

Ⴈഽ‫ݣ‬ც
ߝঈয়શෳ‫஁ۈ‬ఱ

໸‫ࠫڷ‬പʵɼˋʠɅȤȫɥ gBQBS ोപ଴ၭɈอ‫ڨ‬ߔ઺Ī৙ߔī

Ⴈഽ‫ݣ‬ც
ߝঈয়શ

7/4/āိ౰39༃๱ߔ౺ౘ໘ᄟ
ိ౰3:༃ǏॢǍ໲এ੭ലࣞᅅฤଞౘ
Īག઺ߔ‫ڮ‬ଲຶଞ࠸ɚī

੭ಔଞౘ

ਗो

഍āो

ག઺‫ݻ‬า
Ī‫ݚ‬ඦɉᆗߔ౺ī

2

2

3

7

31

37

ୌ઺‫ݻ‬า
Ī‫ݚ‬ඦɉᆗߔ౺ī

21

21

31

3

5

7

ߔင౺
Ī‫ݚ‬ඦɉᆗߔ౺ī

27

1

27

1

1

1

4

4

4

1

2

2

ॸ࢞౺Īᆗߔ౺īୌ઺‫ݻ‬าĪʘʮ˃ʟɻʈ
˂Ĝʯ˅ʈˁʸī2― 120 ―

39
37
27

\Ǔ^āଜ‫ߤۋ࣋ޏ‬຦Ćଜ‫ޏ‬ਇॷ
āāā!Ī౺޲࣋‫ۋ‬Ćଜ‫ޏ‬ਇॷĆެင‫ۙڳ‬ɄɃīĪ࢏౦৘ცīĆ ‫ཾێ‬ଜචၭఱ໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫ޏޏ‬ෳĪ໸ࡖ!3125༃Ǒॢ26໲ġ3127༃Ǒॢ23໲īĆ ৊‫ܗ‬ଜචၭఱोപ૵຦౫সߔ‫ʺ˂ޏ‬Ĝʠʓˋʏˋʈင‫ۙڳޏۙڳ܄ۿޏ‬Ć ˄Ĝʎ˄Ĝʘॸ࢞‫ۙڳ܄ۿޏ‬Ćࠎૢ‫ۙڳޏ‬Ć ੹࣢ॻᆏ࿤຦݊਒ຑߔ৫ TTI ‫ૄ܄ۿ‬ຩ‫ۙڳ‬ĪࣷນூྷīĆ ༔ഺो‫ޏߔކ‬ā࿎ࡼۙĪိ౰37༃ǐॢ23໲ġိ౰41༃ǐॢ഍‫ޏ‬īĆ ‫ཾێ‬ଜචၭఱ໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫ޏ‬ā࿎ࡼۙĪġိ౰39༃๱഍‫ޏ‬ɘɁī!
Ć ౉ဦĆ౉૝঍ߔ‫ޏ‬ā൦25ࡖᆅૢĆဋ‫ޏ‬ෳĪိ౰39༃Ǖॢġိ౰41༃๱഍‫ޏ‬ɘɁī!
Ć ৊‫ܗ‬ଜචၭఱ໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗāൣࡼۙĪණ࢝ఱ࠰५‫ߔݨ‬ʓʇʏʿˋī!
Ć ৊‫ܗ‬ଜචၭఱ໲Ⴈණ࢝ላ౳‫ߔݨ‬ᇦਗāʍɼʀˋʑʴĜʡĪණ࢝ఱ࠰५‫ߔݨ‬ʓʇʏʿˋī!
Ć !໲Ⴈߔ୹‫ !ࡼޏ‬ණ࢝ላ౳‫ ۙڳߔݨ‬JVHH ယ‫ ޏݨ‬JBIT ழ‫ۙڳޏۙڳ‬Īိ౰37༃Ǖॢ41໲ġိ౰3:༃Ǖॢ41໲ɘɁīĆ ໲! Ⴈߔ୹‫ޏۙڳߔࣃࠞ!ࡼޏ‬Ćණ࢝ላ౳‫ۙڳߔݨ‬ਗວ JXE ယ‫ ޏݨ‬HMQ ழ‫ۙڳޏۙڳ‬Īġိ౰3:༃Ǖॢ41໲ɘɁīĆ ಫᅝॻࠞࣃగࡼ‫ޏ‬ā౉ࠞࣃင‫ޏ‬ā‫ۙڳ‬Ćင‫ޏ‬ෳ!
Ć ಫᅝॻࠞࣃగࡼ‫ޏ‬ā‫ݗ‬ಶင‫ޏ‬ā‫!ۙڳ‬Ć ಫᅝॻۗᘧை౉ஃࠞ०೔‫ࡼޏݛ‬ā‫!ۙڳ‬Ć ಫᅝॻࠞࣃ‫ࣗ܆‬࿎‫ޏۙڳݟ‬ā‫!ۙڳ‬Ć ಫᅝॻණଋࠞࣃൎ઄గࡼ‫ޏ‬ā‫ۙڳ‬Īġိ౰41༃21ॢ42໲īĆ ಫᅝॻ೅࣌ી౺ဘഽᅕ౯ණ‫ۊ‬ಱᆒ઄ฤ‫ޏۙڳ‬ā‫ۙڳ‬Ć‫ۙڳ‬ෳĪိ౰38༃ǒॢġණ‫ۊ‬ಱᆒȦ੼౰ȯɦɥɘɁīĆ !ಫᅝॻಫᅝીࠞࣃగࡼ‫ࣃࠞޏ‬။೔ైమो‫ކ‬င‫ޏ‬ණ‫౉ݚ‬။೔ಮᄑ‫ޏۙڳ‬āᆽ૪‫ۙڳ‬Īိ౰38༃22ॢ23໲ġိ౰3:༃ǒॢ41໲īĪˀʍʭɹʛʠ!ʞʠʁʋ!ʑ˂!ʑʶˋʞɻˀīĆ ৊‫ੰܗ‬චၭఱ!ੂນᅣਡ੫யߔੰච!ᆅૢ
Ć Vojwfstjubt! Jtmbn! Sjbv-! U/B/! 3126.3127!Ī Lfqvuvtbo! Sflups! Vojwfstjubt! Jtmbn! Sjbv! Op/1980VJS0
LQUT03127īĈGblvmubt!UflojlĪಮᄑۙīĆ Efqbsunfou! pg! Ufmfdpnnvojdbujpo-! Gbdvmuz! pg! Fohjoffsjoh-! Jotujuvuf! pg! Ufdiopmphz! Cboevoh!ĪJUCī
-!
JoepoftjbĈRvbmjuz!Dpouspm
Ć Dfoufs! gps! Gppe! Bwbjmbcjmjuz! gps! Tvtubjobcmf! Jnqspwfnfou!ĪDGBTJī-! Vebzbob! Vojwfstjuz-! Joepoftjb!
3125!Ľ!qsftfouĈFyqfsu
Ć Ufdiojdbm! Hspvq! po! Tqbdf-! Bfspobvujdbm! boe! Obwjhbujpobm! Fmfduspojt!ĪTBOFī!pg! uif! Jotujuvuf! pg!
Fmfduspojdt-!Jogpsnbujpo!boe!Dpnnvojdbujpo!Fohjoffst!
ĪJFJDFīĪ3121!Ľ!qsftfouī!
ĈಮᄑۙĆ Nfncfs! pg! Bewjtpsz! Cpbse! gps! Fvspqfbo! Dpnnjttjpo! EJGGFSFOU!Ī EJhjubm! cfbn! Gpsnjoh! Gps!
mpx.dptu! nvmuj.tubujd! tqbdF.cpSoF! tzOuifujd! bqfsUvsf! sbebstī-! Dpotpsujvn! Qspkfdu! gpdvtjoh! po!
uif! Efwfmpqnfou! pg! Gvuvsf! Ejhjubm! Cfbngpsnjoh! Tqbdf.Cpsof! Tzoufujd! Bqfsuvsf! Sbebst-! Hsbou!
Bhsffnfou!Op;!717:34-!Efdfncfs!3125!Ľ!Qsftfou
Ć Pvutjef!Fybnjofs!ĪEpdups!Qsphsbnī-!SG!'!Njdspxbwf!Mbcpsbupsz-!Efqbsunfou!pg!Qiztjdt-!Vojwfstjuj!
Qvusb!Nbmbztjb-!Lvbmbmvnqvs-!Nbmbztjb!
Ī3121!Ľ!qsftfouīĪdpoubdu!qfstpo!;!Qspg/![vmljgmz!Bccbtī!
Ć SG!'!Njdspxbwf!Mbcpsbupsz-Efqbsunfou!pg!Qiztjdt-!Vojwfstjuj!Qvusb!Nbmbztjb-!Lvbmbmvnqvs-!Nbmbztjb!
Ī3121!Ľ!qsftfouīĪdpoubdu!qfstpo!;!Qspg/![vmljgmz!Bccbtī!
ĈPvutjef!Fybnjofs!
ĪEpdups!Qsphsbnī― 121 ―

Ć Uif! 31270Uif! 24ui! Mpvhicpspvhi! Boufoob! '! Qspqbhbujpo! Dpogfsfodf!ĪMBQDī-! 25.26! Opwfncfs!
3127-!Cvsmfjhi!Dpvsu!Joufsobujpobm!Dpogfsfodf!Dfoufs-!Mpvhicpspvhi-!VLĈUQD0Sfwjfxfs
Ć Uif! 26ui! Joufsobujpobm! Dpogfsfodf! po! Rvbmjuz! jo! Sftfbsdi!ĪRjS! 3128ī-! Ovtb! Evb-! Joepoftjb-! 35.38!
Kvmz!3128/ĈJoufsobujpobm!Bewjtpsz!Nfncfs
Ć DFPT!TBS!Dbmjcsbujpo!boe!Wbmjebujpo!Xpsltipq!3127-!Joopwbujwf!TBS!Dpodfqu-!:!Tfqufncfs!3127/Ĉ
Tfttjpo!Dibjs
ĪႨഽ‫ݣ‬ცī
Ć HPTBU0UBOTP!SB ೊฤĆ࿎‫ۙڳޏۙڳݟ‬Ć ۧහਂऋ‫ై୹ࡳߔݨ‬మ‫گ‬൵ྣగੈ࿎‫ޏݟ‬ಮᄑˇĜʅˋʈʈ˃Ĝʯ‫ۙڳ‬Ć ໲Ⴈߔ୹‫ࡼޏ‬ණ࢝ላ౳‫ޏۙڳߔݨ‬ණ࢝Ćላ౳५ယ‫ޏݨ‬ණ࢝ࠫപɈளᅰ৭೻Ʌ࠲ȳɥॳບழ‫ۙڳޏۙڳ‬ĆĶಇો‫ܒ‬౳ʟĜʗᆀᅙࡳ୹਷ඨ‫ޏ‬ķ‫ۙڳ‬ĆĶಇો‫ܒ‬౳ʟĜʗᆀᅙࡳ୹਷ඨ‫ޏ‬ķɌɘɩɤʟĜʗᆀߤᅙɈȹɛɈ੼ࣞʈ˃Ĝʯ‫ۙڳ‬Ć ණ࢝ࠞࣃဿ຦ࠫപʷʛʏʿˋĪHDPNī഍ਗ‫ۙڳޏۙڳ‬Ć ණ࢝ࠞࣃဿ຦ࠫപʷʛʏʿˋĪHDPNīTHMJ ᆀᅙˇĜʅˋʈʈ˃Ĝʯ‫ۙڳޏۙڳ‬āĆ ိ౰39༃๱ NPMJ ॳບ‫ۙڳޏۙڳ‬āĆ ණ࢝ࠞࣃဿ຦ࠫപʷʛʏʿˋĪHDPNī൦ǒ‫࢞ॸޑ‬৊ၕ࿎‫ۙڳޏۙڳݟ‬Ć ိ౰39༃๱൦‫ۧێ‬හࡳ୹ငᄑ໘င࿎‫ޏۙڳݟ‬࿎‫ۙڳݟ‬Ī樋৏ຼૂīĆ ౉ဦĆ౉૝঍ߔ‫ޏ‬āᆅૢĂ഍ო‫ۙڳ‬Ă၂ୠ୸ཹ‫ޏۙڳ‬Ī࠲ຄ৳ఒ‫ܛ‬ʈ˃Ĝʯ˂ĜʘīĆ ໲Ⴈ౉ဦ‫ޏߔݨ‬ā၂ୠ‫ۙڳ‬Ć ໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫ޏ‬ćࡅ‫ۙڳކ‬ĂUG ൎܾʙĜʸဋʙĜʸෳĪɺʃʟʷɺृīĆ ໲Ⴈߔ୹‫ࡼޏ‬āࠞࣃߔ‫ޏۙڳ‬Ćණ࢝ላ౳‫ޏۙڳߔݨ‬ਗວāJHCQĆXDSQ ਗວယ‫ !ޏݨ‬NBIBTSJ!ĪʺˋʑĜˋɺʐɺ౉ဦ࡜েॸ࢞ो‫ކ‬īழ‫ۙڳޏۙڳ‬Ć ࡜௣ෝĶಇો࡜௣‫ܒ‬౳ʟĜʗᆀᅙࡳ୹਷ඨ‫ޏ‬ķɌɘɩɤʟĜʗᆀߤᅙɈȹɛɈ੼ࣞʈ˃Ĝʯ‫ۙڳ‬Ć ਡᆏॸ࢞ާཡၭఱ!ۧහਂऋॸ࢞ާཡ࡙৭!QNN!Īਏ౉ࠫപʷʛʏʿˋī!ᆀᅙॳບ‫!ޏۙڳ‬ষॅʷʛʏʿˋॳບ
ယ‫!ޏݨ‬ᆀᅙైమယ‫ޏݨ‬ā‫ۙڳ‬Ć ਡᆏ൥ߔၭఱ!შগ‫ݎ‬൥ߔ!ۧහණ࢝ࠞࣃॸ࢞ஒ!ࢼວᆀᅙĆࢼວॸ࢞‫ۙڳޏۙڳ‬Ć ਡᆏॸ࢞ާཡၭఱ!௶ၡฆఒॸ࡙࢞৭!ĪOJDUī!ࢾᆵॸ࢞ۙ
ĪႨࣕಫ୽īĆ ဦင‫ߔݨ‬ௐā‫୹ࡳߔݨ‬Ćߔ୹గࡼ‫ޏ‬ಮᄑ‫ۙڳ‬Ć ‫ێ‬ଜī໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫ޏ‬Ćߔ୹‫ۙڳ‬Ī໴৮ల઺īĆ ໲Ⴈ൥࡜‫ޏߔݛ‬ā൥࡜ࠞࣃࠫപॳບ‫ۙڳޏ‬Ć ණ࢝५഍ਗఫඣ‫!ޏۙڳ‬൥࡜ယ‫ۙڳޏݨ‬Ć ۧහȥɣɈ൥࡜ܸಹဘଋࠫപ BQPMMP ʷʛʏʿˋĆVW0Wjtjcmf ˂ĜʘĜĆ ໲Ⴈߔ୹‫ !ޏۙڳߔࣃࠞ !ࡼޏ‬ණ࢝ላ౳‫ޏۙڳߔݨ‬ਗວ JHCQĆXDSQĆEJWFSTJUBT ਗວယ‫ ޏݨ‬JHBD ழ‫ۙڳ‬‫ۙڳޏ‬Ć Joufsobujpobm!TLZOFU!DpnnjuuffĆĶಇો‫ܒ‬౳ʟĜʗᆀᅙࡳ୹਷ඨ‫ޏ‬ķɌɘɩɤʟĜʗᆀߤᅙɈȹɛɈ੼ࣞʈ˃Ĝʯ‫ۙڳ‬Ć ‫ݗ‬ଆৌ‫ݪ‬ʄʑࠫപࡳ୹‫ܒ‬౳ĪȞɐȧīHPTBU0UBOTP!SB ೊฤĆ࿎‫ۙڳޏۙڳݟ‬Ć ࡜েဿ຦ࠫപ‫ܒ‬౳ HDPN.D ʷʛʏʿˋĆ൥࡜ॳ௠˂ĜʘĜ
― 122 ―Ć ໲Ⴈ൥࡜‫ۙڳޏۙڳ܄ۿޏߔݛ‬Ć FbsuiDBSF ‫ۙڳޏۙڳ‬Ć ໲Ⴈණ࢝ላ౳ᇦਗ൥‫!ޏ‬൥࡜‫ߔݛ‬ʓʛʏʿˋ!ൣ࿍ʋˋʫĜʢĜĪᥓນஶાīĆ ໲Ⴈߔ୹‫ޏۙڳߔࣃࠞࡼޏ‬Ćණ࢝ላ౳‫ޏۙڳߔݨ‬ਗວ JHCQĆXDSQĆEJWFSTJUBT ਗວယ‫ ޏݨ‬JHBD ழ‫ۙڳ‬‫ޏ‬ā൦33ࡖ‫ۙڳ‬Ć ࠞࣃௐණ࢝ࠞࣃࣟĆ຾ᆏ਄౱ၭఱۧහਂऋॸ࢞ާཡ࡙৭Ć຾ᆏ਄౱ၭఱਡᆏࠞࣃॸ࢞ஒ! ‫ݗ‬ଆৌ‫ݪ‬ʄʑࠫപࡳ
୹‫ܒ‬౳ĪHPTBUīʍɼʀˋʑʙĜʸĆˇĜʅˋʈʈ˃Ĝʯ‫ۙڳ‬Ć ࠞࣃௐණ࢝ࠞࣃࣟĆ຾ᆏ਄౱ၭఱۧහਂऋॸ࢞ާཡ࡙৭Ć຾ᆏ਄౱ၭఱਡᆏࠞࣃॸ࢞ஒ! ‫ݗ‬ଆৌ‫ݪ‬ʄʑࠫപࡳ
୹‫ܒ‬౳ǎळĪHPTBU.3īʍɼʀˋʑʙĜʸ‫ۙڳ‬― 123 ―

\ǔ^āʓˋʗĜɈ਄ૢ
9/2/āʓˋʗĜ଱੓Ɉʏˋʵʐɾʸ
9/2/2/ā!!DFSfT ਗວʏˋʵʐɾʸ!!
൦35‫ ޑ‬DFSfT ਡ੫ʏˋʵʐɾʸ! !
൦ǐ‫ޑ‬ழळ‫ܒ‬౳ʏˋʵʐɾʸĪTPNJSFT!3127ī! !
Uif!Tznqptjvn!po!Joopwbujwf!Njdspxbwf!Sfnpuf!TfotjohĪಱᆒโ୭๘ॸ࢞ࣅ‫ݛ‬ʯ˅ʈˁʸīိ౰39༃22ॢ32໲ȥɣ35໲ɅȥȫĂǎ༃ɅǍ๱Ɉಫᅝ൥ߔɂɼˋʡʥʏɺɈ൥ߔɂɈࢼວ‫ߔݨ‬ʏˋʵʐɾʸĪJKKTT<! Joepoftjb! Kbqbo! Kpjou! Tdjfoujgjd! TznqptjvnīȦಫᅝ൥ߔɁާ੓ȯɦɘȱȹăȭɈʏˋʵʐɾʸɉᆤਡɈॸ࢞ଞɞ൥ߔۡ౺Ȧৄᆔɬ਄Ƞ࡙‫ޏ‬ɬอࢷȳɥ௲ɁɜȜɤĂ਱‫ޑ‬ɉຎʓˋʗĜɈǏȾɈʏˋʵʐɾʸɬວ૪ާ੓
ȱɘȱȹă߂ʏˋʵʐɾʸਗोɁ3:ɈʓʛʏʿˋȦಡȫɣɦĂ௶ၡฆఒɞ˂ʺĜʠʓˋʏˋʈɬ࠸ɚʓˋʏˋʈĂණ࢝‫ߔݨ‬Ă੠ޮɂঌ੠Ă‫ߔۇ‬ĆᄞߔĂ࣋‫ۋ‬Ăॄ੟ߔĂ఍ᆧɂ౉ɄɃဍঢ়ȞယᄘɅɩȹȽɀ271ࣷȞሄဦɈཡ࿍Ȧȫɞȧ‫࠵ޏ‬ɂఱဦଜ‫ृޏ‬഍ਗॸ࢞ງɁ਄ɩɦɘȱȹăȭɈᅕાɉĂDFSfT ʣʽĜʑ˄ʗĜ3127༃22ॢਖĪOp/243īɁɜ௘‫ގ‬ȱɀȞɘȳăʯ˅ʈˁʸȤɢɍʯ˅ʏĜʟɻˋʈɉĂ‫ ࡥݚ‬DFSfT ɾɿʮʍɼʠɬȮઞ௎ȩȺȯȞă
iuuq;00xxx/ds/dijcb.v/kq0Epdvnfout0tznqptjvnt0tznq31270Qspdffejoht.DFSfT.JoumTznqp35.JKKTT3127/qegଖణāDFSfT ਗວʏˋʵʐɾɈᅕા

9/2/3/ā!!൦2:‫ ޑ‬DFSfT ࠞࣃ˂ʺĜʠʓˋʏˋʈʏˋʵʐɾʸ!

!

ĪʂĜʄʢɼʎĜćDFSfT!ࢼວᆀᅙॸ࢞ైమ‫ޏۙڳ‬ī
ိ౰3:༃ǎॢ31໲ಫᅝ൥ߔȫɞȧ‫࠵ޏ‬ɅȤȞɀĂ
൦2:‫ !ޑ‬DFSfT! ࠞࣃ˂ʺĜʠʓˋʏˋʈʏˋʵʐɾʸɬާ੓ȱɘȱȹăȭɈʏˋʵʐɾʸɉĂࢼວᆀᅙॸ
࢞ཡ࿍‫ޏ‬Ɉ‫ڮ‬඲࿥ȫɁႴ༃ଌૈȱɀȤɤĂʓˋʗĜȦైమȱɀȞɥಪ඘˂ʺĜʠʓˋʏˋʈʯ˅ʈˁʸĂ௶ၡຕਗʯ˅ʈˁʸĂ‫ܒ‬౳ᆀᅙ਒๱‫ݛ‬ʯ˅ʈˁʸɅ࠲ᇦȱȹॸ࢞ཡ࿍Ī৏ຢ27ॣĂʵʑʗĜ39ॣīȦ਄ɩɦĂ77შɈઞ‫ݡ‬ଞɣȦ༂ఘɅࡼሄɬৄɩȱɘȱȹăȭɈᅕાɉĂDFSfT ʣʽĜʑ˄ʗĜ3128༃ǎॢਖĪOp/246īɁɜ௘‫ގ‬ȱɀȞɘȳăɘȹĂຎ໲Ɉཡ࿍൨ᄆȤɢɍʑˁɼʡୠɬĶ൦2:‫ ޑ‬DFSfT!ࠞࣃ˂ʺĜʠʓˋʏˋʈʏˋʵʐɾʸ૝ᆧୠ +ķɂȱɀཡ਄ȱɀȞɘȳăʟʐʗ˃ཹɉ‫ࡥݚ‬ʍɼʠɢɤȮઞ௎ȩȺȯȞăĪ+ ૝ᆧୠćiuuq;00xxx/ds/dijcb.v/kq0Epdvnfout0tznqptjvnt0tznq31250STqsphsbn28.I37/qegī― 124 ―

9/3/āਡ੫ʯ˅ʈˁʸĨGvuvsf!FbsuiĩɒɈଲɤ೨ə
ਡ੫ʯ˅ʈˁʸ Gvuvsf! Fbsui ໲ႨૢოࣟʋˋʕĜʏɺʸɅಫᅝ൥ߔɈ‫ݡ‬ძȦ஻໻ȯɦɘȱȹăਡ੫โɄ‫ߔݨ‬ࡳ୹ɅȤȫɥ൥ȧɄᆔɦɂȱɀĂଜ‫ޏ‬โ‫ݻ‬൨‫ސ‬ड़ɒɈᅟಃĂਡ੫โɄᇦ़ɈైమȦ࢙ɛɣɦɀȞɘȳăȭɈਡ੫ʯ˅ʈˁʸɈ਺ႨɈȜɥɜɈɉĂĶ෰ߔ੫!ĪUsbotejtdjqmjobszīķॸ࢞ɺʯ˅ĜʙɂঘɊɦɥɜɈɁĂߔᄎယᄘɈ࠰Ɉ޼਺ɬฝȩȳɥɂɂɜɅĂȯɣɅߔᄎယᄘĪߔ‫ޢ‬īɈߤ຦ɬଜ‫ޏ‬ɅॆȬɥȭɂɅɢȽɀଜ‫ޏ‬โɄ‫ݻ‬൨Ɉ‫ސ‬ड़ɬᄆૄȳĂɂȞȠɜɈɁȳă໲ႨɁɉ໲Ⴈߔ୹‫ࡼޏ‬ɬෂఘɂȱɀထౘɈ൥ߔɞॸ࡙࢞࠲Ȧઞ‫ݡ‬ȱߤ຦ɬާ઻ȱɘȱȹăಫᅝ൥ߔɅȤȞɀɜຎʓˋʗĜȦෂఘૢოࣟɂɄɤĂ‫ߔ॑ܠ‬ယᄘĂ‫ߔۇ‬ယᄘĂࠡীߔယᄘຑ
ɂɈᇦ़Ɉɜɂ Gvuvsf!Fbsui ʗʑʇʭʁĜʑɬ৭౰ȱĂࠞࣃोപ‫୹ࡳߔݨ‬ɬ߇ɂȱȹĨ఍ɂ०য়Ăȷȱɀࠞࣃĩॸ࢞ɈైమɅଲɤ೨ə઻ɛɘȱȹă
9/3/2/āGvuvsf!Fbsui ၇ࣅ‫ޏ‬
ိ౰39༃ǒॢ41໲Ʌ‫݊ڤ‬ʓˋʗĜෳ଱ຩɈɜɂĂ࣋ఊۙ৐ȫɅ!Gvuvsf!Fbsui!
၇ࣅ‫ޏ‬Ȧ਄ɩɦɘȱȹăɘȴĂGvuvsf! Fbsui ɂɉ‫ݝ‬ȥĂGvuvsf! Fbsui ๐ާɅȤȫɥএ௻Īਡ੫โɅɉĂ໲ႨɁɉĂಫᅝ൥ߔɂȱɀɉīɅȾȞɀ௘‫ގ‬ȦȜɤɘȱȹăȷȱɀĂ૩റ‫ݢ‬༑Ʉණ࢝ଜ‫ޏ‬ɈଌএɬɛȰȳȹɛɅɉĂɃɈɢȠɅ˂ʺĜʠʓˋʏˋʈɈᄜߠɬ‫ڮ‬඲ȿȫĂଜ‫ޏ‬ɅਇॷȳɥɈȥɬߊ໻ȱĂȯɣɅ਱ষɈຎʓ
ˋʗĜɈၫ৐౯ɂȷɈ઴ჩɬ੔ߊ໻ȳɥᄵ‫ࡹڷ‬Ʉ‫ޏ‬ɂɄɤɘȱȹă
9/3/3/āಫᅝ൥ߔ Gvuvsf!Fbsui!ljdl.pgg!ˇĜʇʏʿʛʯ
ိ౰3:༃Ǐॢǎ໲ĂಀಫᅝʅʻˋʩʑɅȤȞɀĶಫᅝ൥ߔ Gvuvsf! FbsuiķɈʅʛʇʂʭˇĜʇʏʿʛʯɬާ੓ȱɘȱȹăယᄘɬ෰Ȣȹᇦ़Ɉɜɂ‫ޑݝ‬ȥ‫ޏ‬ਗɬ୭ɇĂĨ఍ɂ०য়ĂȷȱɀࠞࣃĩɂȞȠࡊႨɂɄɥʞĜʶɬऻȬĂණ‫ۊ‬ɈఱęɬࠆȧਮɭȺಫᅝཡɈ‫ݻ‬൨‫ސ‬ड़Ʌ৐ȫȹॸ࢞ߤ຦Ɉ๐ާɬᄆโɂȱȹߤ຦Ɉࡧ๘ɂɄɥ
ˇĜʇʏʿʛʯɁȳăˇĜʇʏʿʛʯɅಪᆏȻĂȫɞȧ‫࠵ޏ‬ʳĜ˃ɁɈʵʑʗĜʓʛʏʿˋɬ਄ȞĂᇦ़ယᄘɈ߂ॸ࢞‫ݨ‬ɢɤ຾૵Ɉ૗๘Ɂ‫ݻ‬൨‫ސ‬ड़Ʌ৐ȫȹଲɤ೨əၫɬ௘‫ގ‬ȱɘȱȹă঳ষȥɣɈˇĜʇʏʿʛʯɉĂࡊ෮ਆ‫ܩ‬Ăಫᅝ൥ߔ Gvuvsf! Fbsui Ɉ௘‫ގ‬Ăʩʥ˃ʟɻʑʃʛʏʿˋĂɈǏင৭౰ɁĂ਱ষĂGvuvsf! Fbsui! ॸ࢞ɬɃȠइൌ‫ݛ‬ȳɥȥɅȾȞɀĂࡊ෮ਆ‫ܩ‬ଞɂಫᅝ൥ߔ࣋ۙɂɁߤཡɄࡼሄȦৄɩȯɦɘȱȹăȭɦɣɈଲɤ೨əɉĂDFSfT ʣʽĜʑ˄ʗĜ3127༃ǒॢਖĪOp/238īĂȤɢɍ3128༃ǏॢਖĪOp/247īɁɜ௘‫ގ‬ȱɀȞɘȳăɘȹĂȭɈ Gvuvsf! Fbsui ɒɈଲɤ೨əɉĂ૫༃๱‫ڬ‬ਏߔ౺ɒɜȷɈ໻ඪ๱ɬ਒ɛĂ߂૵Ɉॸ࢞ʞĜʶɂ
Gvuvsf! Fbsui โᅟ೧ɬ˂ʺĜʠʓˋʏˋʈɬ߇ɂȱɀɃɈɢȠɅᅃਗȱɀȞȫɥȥɄɃĂ‫ࠓৄॽڷ‬ɬȳɥ௲ɬ૩ȻĂᆅ‫ސ‬ɬఠɛɀȞȩᅅฤɁȳă

9/4/ā൦27‫ ޑ‬TBS ‫ކ‬ജఒਖஐᆅĆಫᅝ൥ߔ Tvnnfs!Tdippm!po!Njdspxbwf!Sfnpuf!Tfotjoh
3127༃ǔॢǍ໲ġǏ໲Ʌಫᅝ൥ߔూங࠵ɂࠞࣃ˂ʺĜʠʓˋʏˋʈॸ࢞ʓˋʗĜʹʟɻɺ˃ĜʸɅɀĂ൦27‫ ޑ‬TBS ‫ކ‬ജఒਖஐᆅĆಫᅝ൥ߔ Tvnnfs!Tdippm!po!Njdspxbwf!Sfnpuf!Tfotjoh ɬާ੓ȱɘȱȹăȭɈߤ຦Ʌ໲ႨɬɉȲɛĂɼˋʡʥʏɺĂʀʐʯʠĂʶ˄ĜʏɺĂʄˋʢĜĂෂਡĂ࠴ਡĂʩʅʑʗˋĂʺˋʌ˃ɄɃȥɣ
66შɜɈॸ࢞ۙɂߔ౺Ȧઞ‫ݡ‬ȱɘȱȹăȭɈߤ຦Ɂɉਗ౰ާ৏˄ĜʘĪTBSīɈಡोɬɉȲɛĂላ౳එੈɈᇘ
ષĂ‫ކ‬ജఒਖஐᆅĂTBS ʓˋʍɈູ౯ɂȷɈܾᅙɄɃɬ௘‫ގ‬ȱɘȱȹă

― 125 ―

― 126 ―\Ǖ^ā଱ᅟॸ࢞ಡྩ
:/2/ā‫ܒ‬౳ʟĜʗିఒʏʑʞʸĪ଱ඐຎć樋৏ຼૂī
DFSfT! ɁିఒĆஐᆅȳɥ‫ܒ‬౳ĆʓˋʍɉĂɺˋʞʢɅɢɥ෸ಞିఒɁɉ! OPBB0BWISS ʏ˂ĜʒĂෂਡಇો࡜௣‫ܒ‬౳ GZ ʏ˂ĜʒĂˁˋʡˁɼˋଲຶĪɼˋʗĜʥʛʠଲຶīɁɉ໲ႨɈಇો࡜௣‫ܒ‬౳ NUTBU ʏ˂ĜʒĪɌɘɩɤǔਖಜɤൖȢষɜ NUTBU ঱ࠓʟĜʗɬଲຶĆஐᆅīĂɌɘɩɤǔਖĂɺ‫ܒ‬౳຃੪Ɉ NPEJT ɁȜɥăOPBB0BWISS ɉ DFSfT ཡഫষຩ໴ȱȹିఒĆஐᆅʏʑʞʸɬຝ୙ȱĂ౺ʟĜʗିఒġʯ˅ʘʇʠ౺౰ġ৊ާʍĜʨɒɈ๖ഗɬ਄ȽɀȞȹȦĂ3121༃21ॢɈ๘ॳพ๝ষɅିఒˇĜʇʑʞĜʏʿˋȦঠ௩Ăିఒ࿤‫ݢ‬༑ɂɄȽȹăວ༃๱ჂɅൣൖஐᆅʍĜʨɬߔ໘੩ᆲॄྣɁຩ໴Ăʯ˅ʘʇʠ౺౰ɘɁ੔ާȱȹăȱȥȱĂɺˋʞʢʺĜʗɈॄ༃ᇚ‫ݛ‬Ʌɢɥିఒ‫ކ‬ജɈଋᇚ‫ݛ‬ĂିఒʏĜˋౘɈ൥ဍঌவĂBWISS ʏ˂ĜʒɈଌଋโɄ୒᠅ĂɌɘɩɤǔਖɈ๨௲ຑɅɢɤĂ࣋ۙ‫ࡼޏ‬ɈࡼɅɢɤ BWISS ିఒૢࣞɬ3127༃๱ঔɤɁ୒ᆡȳɥȭɂɬड़ฤĂ3128
༃ǏॢɅɺˋʞʢക඲‫ૺێ‬Ɉ้ࢦ৙ૢɬ਄ȽȹăɄȤĂ‫ࢦݿ‬Ɉ BWISS ିఒʟĜʗɅ࠲ȱɀɉȭɦɘɁฆɤ৊ާ
ɉॅറȳɥă
ĆOPBB0BWISS ʏ˂Ĝʒ! Ī2::8༃ǐॢ26໲ିఒާ઻Ă3128༃Ǐॢ24໲ିఒക඲้ࢦīĆNUTBU ʏ˂Ĝʒāāā! Ī3116༃ǒॢɢɤɺĜʃɼʮާ઻īĆɌɘɩɤǔਖ!

Ī3126༃Ǔॢɢɤ౷ૺ‫ۿ‬ᅙާ઻Ă‫ڬ‬೐ɈʞʑʠʟĜʗɜେሃȱɀȞɥȦĂᆀᅙɉ!
ঔɣɦɥīĆGZĪC0D0E0Fīʏ˂Ĝʒ!Ī2::9༃ǐॢɢɤ GZ3.C ౘˎॢିఒĂ3118༃๱Ʌ GZ3.D ȥɣିఒĂ৊ާާ઻īĆHPFT.FĂ.X ʏ˂Ĝʒ!

Ī2::9༃ယɢɤɺĜʃɼʮȜɤīĆNPEJT!

Ī3115༃ǔॢɢɤ!
KBYB ିఒယɺĜʃɼʮާ઻Ă೔࢝࠲ᇦʯ˅ʘʇʠɉ UfssbĂ
Brvb ާ઻૪ɢɤɺĜʃɼʮᄵɤ

:/3/ā๝༜ჟࣗଆ!Ī଱ඐຎćK/U/!ʑ˂!ʑʶˋʞɻˀī
ိ౰31༃ǎॢ26໲Ʌࠞࣃ˂ʺĜʠʓˋʏˋʈॸ࢞ʓˋ
ʗĜʶɼʇ˅༜˂ʺĜʠʓˋʏˋʈॸ࢞ଆĪˀʍʭɹʛʠ
ॸ࢞ଆīɅࠊ౰ȱȹಡྩɉୈ༜ౘǍHI{ ȥɣ51HI{ ɘɁ઴ᅙ‫ݢ‬༑ɁĂਗ౰ާ৏˄ĜʘĪTBSīɬɉȲɛĂʶɼʇ˅༜
Ɉ๝༜๙ུɂઢᅸɈଌঅɄɃɅܾᅙȱɀȞɥăȭɈಡྩɈ
౥ၭɉဍ5/1n Ŀͽෳ7/7n Ŀͽ਒3/5n ɁĂɘȹ࢓େູ౯ɉ46!
eC ‫ڬ‬௫ɁȜɥăʶɼʇ˅༜˂ʺĜʠʓˋʏˋʈɅȤȫɥᅕęɄଌঅɬૅ
‫ܧ‬ȳɥȹɛɅĂʥʛʠˇĜʇɺʢˁɼʎĂʶɼʇ˅༜‫ޑ‬ᇭĆࡊྲྀ‫ݡ‬৙ക඲Ă਒౼๱‫ޑ‬๖൤ɄɃɜ౲ྩȱĂਗ౰ާ৏˄Ĝ

ూ:/3/ā!๝
! ༜ჟࣗଆ໘ɅȤȫɥழळ‫ܒ‬౳ɈപฤȱȹᅕાʘɈާཡɅྼᅟ࿤‫ݢ‬ज़Ʉʶɼʇ˅༜‫ޑ‬ᇭɂɺˋʞʢɬާཡ
ȳɥȹɛɅĂʺĜʹˋʠၭĪNpNīĂᄵঔᅟ೧ၭĪGFNīɄɃɬ઴ᅙȱȹ਒ୈ༜‫ޑ‬ᇭĆɺˋʞʢಡोᅙɈʕʭʠ
ɾɿɺɜ౲ྩȱɀȞɥăȭɦɣɈಡྩɉএ੭ྦ਄࡙Īჟఱྦ਄࡙ VBW ɬ࠸ɚīɂʶɼʇ˅‫ܒ‬౳຃੪ᅙɈਗ౰ާ৏˄ĜʘɈާཡɅ઴ᅙ
ȱɀȤɤĂɘȹĂຎʓˋʗĜɈ೔ਡࢼວᆀᅙࢼວॸ࢞ૈಡɁɜഽȞɅߤᅙȱĂ೔ਡɈॸ࢞ଞɂࢼວȱɀĂழळ‫ܒ‬౳ɬɉȲɛĂਗ౰ާ৏˄ĜʘĂʶɼʇ˅༜ၪଗोĆઢᅸोĂັᇭ๸य़ࠠ૗ʓˋʍɄɃɁȜɥʶɼʇ˅༜ɅȤȫɥᅕęɄʓˋʍɈާཡɅ઴ᅙȱɀȞɥă

― 127 ―

:/4/ā൥࡜ʟĜʗଲຶˁɼʘĜക඲Ī଱ඐຎć࢏౦৘ცīˁɼʘĜ!Īmjebsī!ɉĂ൥࡜ෂɅʩ˃ʑ˄ĜʎĜ৉ɬ௎ଗȱĂ൥࡜ෂɈઢᅸൌɁȜɥʀɺ˅ʖ˃ɞ‫܀‬ȥɣɈઢᅸ৉ɬႊܳࣖɁି৉ȱɀઢᅸൌɈ৉ߔູ౯ɞऋ࠰ယ࿫ɬोപȳɥക඲ɁȜɤĂ൥࡜ɬൎ௣ɂȳɥ˂ʺĜʠʓˋʏˋ
ʈɅȤȞɀࡊႨโɄोപക඲ɂɄȽɀȞɥăDFSfT ɁɉĂ൥࡜ࠞࣃယᄘɞ࡜௣ယᄘɄɃ࠲ᇦȳɥȯɘȰɘɄࢼວᆀᅙॸ࢞ଞɈᅟႊɅܾȢɣɦɥɢȠĂ੕ಪ඘ɈोപȦ‫ݢ‬༑ɁĂȥȾܾᅙཱྀ‫ڱ‬Ɉঢ়ȞˁɼʘĜȤɢɍȷɈ৫౷ᅙʏʑʞʸɬိ౰33༃๱ɅઌఛȱȹăȭɦɅɢɤĂDFSfT ɈǏȾɈෂ߇โɄॸ࢞ʯ˅ʈˁʸɈȠȻɈ‫ێ‬ȾɁȜɥĶಪ඘โ˂ʺĜʠʓˋʏˋʈʯ˅ʈˁʸķɅȤȞɀĂࢼວᆀᅙĆࢼວॸ࢞Ɉ਒๱‫ݛ‬Ȧɢɤ‫ݢ‬༑ɅɄȽȹă൥࡜ʟĜʗଲຶˁɼʘĜക඲!ĪBunptqifsjd!Ebub!Dpmmfdujpo!Mjebs-!BEDMīɈ!ക඲৭౰ɉĂઢᅸൌɈव௻ယ
࿫Ȧोപ‫ݢ‬༑Ʉഽ༜ෳोപക඲ɂĂჶโĆᆏൌโɄोപȦ‫ݢ‬༑Ʉ QQJ!
ĪQQJ ɉ Qmbo!Qptjujpo!Joejdbups ɈᆒīʺĜʡोപക඲ȦෂఘɂɄȽɀȞɥĪూ:/4/ ઞ௎īă‫ུݢ‬౯ɜ৽ᆞȱȹഽ༜ෳ৭౰ɈʋˋʵĜʥˋʠ‫ݛ‬ɬూɤĂ˄ĜʎĜക඲ɂႊܳࣖȦ‫ێ‬ൌ!Īʺʦʑʗʞɻʛʇī!Ȥɢɍᆋɦȹ!Īʨɼʑʗʞɻʛʇī! ༯඲ɄɃĂഽᅕɄʣĜʒɅൎܾ‫ݢ‬༑Ʉʏʑʞʸ৭౰ɬੜᅙȱɀȞɥăວ૪ɅĂഽ༜ෳʥʭɿ˅ʹĜʗɄɃණ௫Ɉૅ‫ܧ‬പࡉɅɢɥණ௫ोപʟĜʗɈେୠɬ਄ȽɀĂฤᆲโȥȾఒᅲ౯Ɉ਒ȞˁɼʘĜఒਖ‫ސ‬಑ɬଌএȳɥȭɂȦ‫ݢ‬༑ɄʏʑʞʸɂɄȽɀȞɥă

ూ:/4/ā!!൥࡜ʟĜʗଲຶˁɼʘĜക඲!ĪBEDMīćĪbī!ഽ༜ෳˁɼʘĜʾʣʛʠĂĪcī!ഽ༜ෳˁɼʘĜʾʣʛʠɈ৭౰ూĂ
Īdī!ණ௫ʀɺ˅ʖ˃ोപക඲ĂĪeī!QQJ ക඲Ɉ৭౰ూɂଖణ

BEDM Ɉණ௫പࡉငʟĜʗɉĂ‫ࡥݚ‬Ɉ VSM ȥɣઞ௎‫ݢ‬༑ɁȜɥăĪʟĜʗɬߔ‫ޏ‬ཡ࿍ɞሄဦɄɃɅ઴ᅙȯɦɥ௲ਗĂ࢏౦ॸ࢞ଆȜɀȮᇦᅵȩȺȯȞăī
iuuq;00xxx/ds/dijcb.v/kq0lv{f.mbc0npojups0npojups/qiq!
iuuq;00xxx/ds/dijcb.v/kq0lv{f.mbc0npojups0bedm/qiq!

― 128 ―

:/5/āၪଗࠫപʥʛʠˇĜʇૈಡĪTLZOFUīĪ଱ඐຎć໴৮ల઺īණ࢝࡜েɈဿ຦ɬᆅ‫ސ‬ȳɥȹɛĂʀɺ˅ʖ˃ɂʀɺ˅ʖ˃ɬ߇ɂȱɀ౰ෳȳɥ‫܀‬ɈࠫപʟĜʗɈଲຶɂ‫ސ‬಑ɉज़ȥȵɄȞăႨʓˋʗĜɁɉĂಇો࡜௣‫ܒ‬౳ɄɃ߂ହɈණ࢝ࠫപ‫ܒ‬౳ȥɣຶɣɦɥ‫܀‬Ăʀɺ˅ʖ˃௶ၡɈණ௫ॳ
௠ૈಡɂȱɀĂ໲Ⴈɬ࠸ɚຄɺʐɺɬෂఘɅ TLZOFU ࠫപᄀĪಫᅝĂဏ৮๿Ă‫݋‬໢၃টგĂ࢔গ๿ĂෂਡਗྠĂʗɼĂʬʶɼ഼īɬ‫܄ۿ‬ȱĂȷɈʟĜʗ‫ސ‬಑ɬ਄ȽɀȞɥăȷɈ߇ɂɄɥ࡙੮ɉ! tlz! sbejpnfufsĪ๏ऋɈၪଗ
ࡩ๱ယ࿫ɈोപīɁȜɤĂȭɈʟĜʗȥɣʀɺ˅ʖ˃Ɉ৉ߔʩˁʹĜʗĪ৉ߔโৎȯĂඍ‫ێ‬ઢᅸɺ˃ʱʡ഼īȦైฤɁȧɥăTLZOFU ɉĂਡ໘ެɈ࠲ᇦॸ࢞Ʌ࿤‫ݢ‬ज़Ʉණ௫ोപʟĜʗɬอࢷȱɀȤɤĂȷɈ‫ۿ‬ᅙɅȜȹȽɀɉ࠲ᇦॸ࢞ଞɂɈˇĜʇʏʿʛʯɞʏˋʵʐɾʸɬฤࡖโɅާ੓ȱɀȞɥă௫ćTLZOFU ɅȤȫɥၪଗࠫപക඲द
੆ć!!TLZOFU ࠫപᄀĪಫᅝĂဏ৮๿Ă‫݋‬໢၃টგĂ࢔গ๿ĂෂਡਗྠĂʗɼĂʬʶɼ഼ī:/6/āȷɈ഼ोപക඲ĂʕʭʠɾʀɺĪ࢏౦ॸ࢞ଆĆࣷນॸ࢞ଆĆˀʍʭɹʛʠॸ࢞ଆĆႨࣕॸ࢞ଆīĆ૓ެĂ‫ݢ‬૗Ăࣷಘެယ৉৉๱ोɂཱଗപฤക඲
ĆʧɼʩĜʑʲʇʠ˃ʃʹˁ
Ćʶɼʇ˅༜๙ུപฤʏʑʞʸĆ਒ୈ༜‫ޑ‬ᇭಡोʕʭʠ IGTTĆ਒ୈ༜‫ޑ‬ᇭಡोʕʭʠ JF4E
Ć਒ୈ༜‫ޑ‬ᇭಡोʕʭʠ Botpgu!EftjhofsĆऋ࠰௶ၡ‫ސ‬಑ʕʭʠ BsdHJTĆ‫ܒ‬౳‫ކ‬ജ‫ސ‬಑ FS!NbqqfsĂFOWJĂFSEBTĂQDJ ɄɃ― 129 ―

\21^āိ౰39༃๱ोધ࡙ʟĜʗʱĜʑ଱ᅟࣞო
21/2/ā‫ޱ‬ᅟāိ౰39Ī3127ī༃๱ɉȭɦɘɁɈʟĜʗʱĜʑ৊ާࣞოɈॅറȦ଱Ʉߤ຦ɁȜɥă
21/3/āိ౰39Ī3127ī༃๱ोધ࡙ʟĜʗʱĜʑȤɢɍʟĜʗࠣᆅૅ‫ܧ‬ଆ଱ᅟࣞო
āฆ௵ࣞოĪǍშൌ౫īঢ়ၡࣞოĪૅ‫ܧ‬ଆɢɤǍშīŜ‫ިێ‬ʍĜʨଆĂD4ĂD5ʍĜʨᇆɈ௻ൔࠣᆅĂၡਠĂʀɺʋˋʭɻ˃ʗĂ‫ݗ‬๱ࠣᆅĂ࡙ࡉʏ˂ɺ˃ʢˋʨࠣᆅ

Ŝ‫ݎ‬௫ɺˋʞʢĪGZ.3EĂF ିఒɺˋʞʢīʙɿʛʇŜ߂ହʟĜʗʘɾˋ˅Ĝʡ௻࣍ʙɿʛʇĂज़ᅶʟĜʗɈ੔ஐᆅĂʟĜʗᆲɈʙɿʛʇ
Nfufptbu8ĂNTH2Ī3128༃ǎॢɢɤī଴຦ʘɾˋ˅ĜʡĂʯ˅ʘʇʠ੼౰ĂNTH3ĂǏʟĜʗɈʞĜʯ຿Ŝ !

ə୸ȱĂ။ശʞĜʯɈࠆȧᄋȱ੼ࣞŜʞĜʯʨʛʇɺʛʯĂMUP5ȥɣ MUP7ɒɈʟĜʗ‫ھ‬຦ŜࠞࣃॸȥɣɈǐȉȉʞĜʯĪbwiss ʟĜʗīɈ຿ə୸ȱʙɿʛʇŜʹĜ˃ʍĜʨࠣᆅĂॸ࢞ଆ NM ৩ఛĂఛࡤ NM ੼౰ĂɼˋʠˁʥʛʠࠣᆅŜ

XXX ʍĜʨʋˋʞˋʜɈ৩ఛ

Ŝॸ࢞ଆʕʭʠɾɿɺࠣᆅ൤ො੼౰

Ŝ༃ၡĂʣʽĜʑ˄ʗĜ੼౰ૅ‫ܧ‬Ăʭɿɼʑʮʛʇ߄୤ĂʾĜʙʽĜʮঢ়ၡĂૅ‫ܧ‬ଆɈʥʛʠˇĜʇ௩ޮ௶ၡࠣᆅ
࿍21/2/āိ౰39Ī3127ī༃๱௩ޮຑၡਠ༃āॢā໲௩ޮĆൎܾૢਐ

3127015032

BWISSćɺˋʞʢʺĜʗ෮౲Ī໲Ⴈཉᅙī

3127015039

BWISSćɺˋʞʢʺĜʗ෮౲Ī໲Ⴈཉᅙī‫ޜ‬೑əɣɦȴăĪǐॢʟĜʗ௻࣍ī HPFT.FBTUćɈʟĜʗঌவĂ3:໲ɾɼ˃ʑࠐಹɅɢɥʥʛʠଡඣȜɤăʕĜˁĜɈʟĜʗɈ‫ھ‬຦พોĂ୽ࡠാᅣ৉ႄޮෂ
312701601:‫ިێ‬ʍĜʨଆʍĜʅʽ˄Ĝʗঠ௩Ăৄࠓ

3127016037

NPEJTć༬ჶɈ‫ݗ‬๱௫ீĂ˄ɼʡ‫௵ڽ‬
INXS93:itćĪʯˁɼʱĜʠʥʛʠˇĜʇृīʥʛʠˇĜʇඣೀȜɤ

3127016038

NPEJTć༬ჶɈ‫ݗ‬๱௫ீĂ˄ɼʡ‫௵ڽ‬
INXS93:itćĪ2:3ृīʥʛʠˇĜʇඣೀȜɤ

3127017017

UBQF3ʃĜʥ˃ʩʣʛʇ

3127017025

GZćିఒพો

3127017028

ʍĜʨଆʀɺʋˋঠ௩

3127017031

GZć˄ʏĜʨɬʫʐʿˋʞʛʇɅഗ࿥Ăୌᆅ

312701802:

UBQFā0wbs!211œ

3127018037

HBJBć˄ɼʡȥɣ्ਠ‫ݙ‬

3127018038

GZ ˄ɼʡ‫௵ڽ‬റȩ!Ũ!຃੪ȯɦȹ IEE ȦʋˋʏʽĜʶ৐ȫɁූ๱വȽɀୁჩɬ॒ȢɥɈȦܳۚăȺɘȱȺɘȱ‫ۿ‬ᅙ

3127018039

BWISS ๝঍ʾʣʛʠ‫௵ڽ‬Ăৄࠓ

3127019016

HPFTć˄ɼʡ TESBN ʀˁĜ

3127019019

GZćtmpu3ʹʟɻɺʀˁĜ

3127019033

HBJBćพો

312701:027

OPBSFDĪBWISS ିఒஐ඲ക඲īćିఒౘॗঌ

312701:03:

GZćtmpu:ʹʟɻɺʀˁĜĪǕॢʟĜʗ௻࣍ī ୑ࡠാᅣ৉ႄޮෂ
3127021014

INXS93:it ˄ɼʡ‫௵ڽ‬

3127021015

UBQF3ĂHBJB ˄ɼʡ‫௵ڽ‬― 130 ―

༃āॢā໲

௩ޮĆൎܾૢਐ

3127021022

XXX ʭɹˋ‫௵ڽ‬

3127021027

ो‫ކ‬พ๝ൎܾ

3127021018

HQ15ćDQV ‫௵ڽ‬Ă઴ᅙพો

3127022018

HQ15ʍĜʨĜʘɾˋ

3127022034

NPEJT ˄ɼʡ‫௵ڽ‬Ă੔ࡧ຦Ɂൎܾ

3127022039

INXS93:hsć˄ɼʡ‫௵ڽ‬

3127023016

NPEJTć˄ɼʡ೔ʟɻʑʇಘˁˋʯĂ੔ࡧ຦Ɂൎܾ

3127023019

໴৮ॸʍĜʨ‫௵ڽ‬ĂHFPJOGP ˄ɼʡ‫௵ڽ‬

3127023023

HFPJOGPćʀˁĜ‫ݙ‬
HPFTćTESBN ‫௵ڽ‬

3127023027

INXS93:itćPT ໴ɦൖȢɅɢɤĂ‫˅ࢦݿ‬ʈ௉଄Ă˅ʈ‫ڮ‬඲ဿ৩
INXS93:hsćPT ໴ɦൖȢɅɢɤĂ˅ʈܑাȥɣ໲ႨাɅဿ৩

3128012021

໴৮ॸʍĜʨঠ௩GZćVQT ʨʛʞ˂Ĝৄࠓ

3128012022

GZćWU Ʌ૪ਟਗɩȵ‫گ‬ᅲ

3128012041

GZćtmpu22ʀˁĜ

3128013013

BWISSćTmpu222ʹʟɻɺʀˁĜ

3128013017

BWISSćTmpu22-!tmpu8ʹʟɻɺʀˁĜ

3128013025

NPEJT ˄ɼʡ‫௵ڽ‬

3128013026

XXX.IE ʭɹˋ‫ݙ௵ڽ‬

3128013029

ʞĜʯʍĜʨʨʛʞ˂ĜʺĜʡ

31280130

INXS93:hsćʥʛʠ࿤෮ɅɢɤĂʈ˂ʛʡʟĜʗ੼౰࿤ᆯĂ‫ࢦݿ‬Ɉज़ᅶʟĜʗɈʙɿʛʇɂ੔ஐᆅ

3128014015

GZćtmpu4ʹʟɻɺʀˁĜ

3128014017

ʍĜʨଆʀɺʋˋঠ௩

3128014026‫ݎ‬௫ bwiss ɺˋʞʢ้ࢦ৙ૢ

3128014034

GZćtmpu22ʀˁĜ

21/4/āိ౰39Ī3127ī༃๱ʟĜʗʘɾˋ˅Ĝʡଌಕ
ā3127༃ ๱ ʟ Ĝ ʗ ʘ ɾ ˋ ˅ Ĝ ʡ ଌ ಕ ɉ ‫ ݚ ڬ‬Ɉ ฆ ɤ Ɂ Ȝ ɥă3127༃ ๱ ɉ Ɍ ɘ ɩ ɤ ǔ ਖ ೔ ࢝ĪGEī!hsjeefe!
qspevdu ৊ާɜާ઻ȱȹȭɂɜȜɤĂஏ෮Ʌഝ‫ݡ‬ȱɀȞɥăູɅߔެȥɣɈᆀᅙഝ൥Ȧ൥ȧȩĂɌɘɩɤǔਖʟĜʗ৊ާɬฆȲĂ഼ɈʟĜʗʓʛʠ৊ާɅȾȞɀɜඪɥȧȽȥȫɬຶȹʾĜʎȦഝȢȹɈȥɜȱɦɄȞă
࿍21/3/ā3127༃๱ʟĜʗʘɾˋ˅Ĝʡଌಕ‫ܒ‬౳ğʓˋʍĜშߔ໘ʘɾˋ˅Ĝʡߔެʘɾˋ˅Ĝʡ

OPBB0BWISS

44-778285-3121/5802/:5439

5:-86:

1/1101/49

Ufssb!Brvb0NPEJT

઀༃྘!ߔ໘ğߔެ

HNT6-!HPFT:

49-55384-8::

1/8:01/28

NUTBU

77:-955

3-441-821

2/3202/19

GZ3

275-483362-87:

1/6202/38

Nfufptbu-!NTH

2:1-766319

368701/97

HPFT.F-!.X

2-513-386

51-8362/2902/24

ණᆅ௶ၡຑ

3-989-:67

2-47:-49:

1/9:05/51

USNN-!B.Usbjo

357-376562-875

2/6505/2:

ၪଗʯ˅ʘʇʠ

2-994-8:1:-767-849

2/9103/24

Ɍɘɩɤǔਖ

49-233-613

25-9:1-398

2/2203/99

഍ो56-742-1:7

3:-39:-45:

2/2203/33― 131 ―

\22^āိ౰39༃๱ DFSfT ʣʽĜʒ˄ʗĜʰʛʡˁɼˋȤɢɍʣʽĜʑ˂˂ĜʑāāāāĪiuuq;00xxx/ds/dijcb.v/kq0kbqboftf0ofxt/iunmī
ş!Ofxtmfuufs!Op/236Īཡ਄3127༃ǐॢīʓˋʗĜෳ୊໸ɈȮ‫ډ‬઎Ī‫݊ڤ‬೑ဦఛʓˋʗĜෳɢɤī
Joufsobujpobm!Tznqptjvn!po!Sfnpuf!Tfotjoh!
ĪJTSTī!3127
ɺʃʟʷʛʇĆ˂ˋʇĆɾɻĜʇࡅ‫!ކ‬ġĶɌɘɩɤǔਖȦ჏ȵɥ!ʭ˃ʃˁĜɈ౦‫ޢ‬ķġ
Joufsobujpobm!ujft!pg!DFSfT!ĝ!Xibuħ
t!vq-!hsbevbuft@ġʏ˂ĜʒāDFSfT!ୌᆡɈᆗߔ౺!౦‫ޢ‬ɁߤᄠĊĪʉʣɺ၂ī!ġ
ş!Ofxtmfuufs!Op/237Īཡ਄3127༃ǑॢīႨࣕஂ࣋ୂĂTBUSFQT ੜ൰ड़ฤĊ
Ĳି௤ၡਠĳ໲Ⴈ˂ʺĜʠʓˋʏˋʈߔ‫ޏ‬ᄭ୐ሄဦཡ࿍௤
Ɍɘɩɤǔਖʈ˂ʛʡʟĜʗ৊ާ
ş!Ofxtmfuufs!Op/238Īཡ਄3127༃ǒॢī൦21‫ ޑ‬WM ਆ୔‫ާޏ‬੓ȱɘȳĪǕॢ31໲ġ32໲īġ໲ႨɈණ࢝ࠫപ‫ܒ‬౳ɬඪɧȠġ
3127༃๱൦Ǎ‫௶ޑ‬ၡʓʅʽ˂ʞɻਆ୔‫ޏ‬ଌૈ
Gvuvsf!Fbsui ၇ࣅ‫!ޏ‬ġ૩റ‫ݢ‬༑Ʉණ࢝ଜ‫ޏ‬ɬɛȰȱɀġ࣋ఊۙ෇఍‫!ޏ‬ġ೔ۙୠਗĊġ
ş!Ofxtmfuufs!Op/239Īཡ਄3127༃Ǔॢīိ౰39༃๱ࢼວᆀᅙॸ࢞ੜ൰‫ݻ‬൨ड़ฤ!ġိ౰39༃๱൦Ǎ‫ࢪޑ‬๘‫ާޏۙڳ܄ۿ‬੓ġႨࣕಫ୽ஂ࣋ୂĂȜȥɤɭɺˇĜǓॢɼʱˋʠɅ๨௲!ġಫᅝ൥Ɉ౦‫ޢ‬โॸ࢞ʏ˂Ĝʒ!൦Ǎ‫ޑ‬ġ
UFJ.DFSfT!Bunptqifsjd!Sftfbsdi!Nffujoh Ɉާ੓ၡਠ
ိ౰39༃๱ఛఱ॒࠙‫ާޏ‬੓
ş!Ofxtmfuufs!Op/23:Īཡ਄3127༃ǔॢī
DFSfT ʣʽĜʑ˂˂ĜʑɅɀॸ࢞ၡਠ!ġʏ˂Ĝʒ!DFSfT Ɉॸ࢞ߤ຦၆ɤĪ߂ॸ࢞ଆȥɣī!ġ
Joufsobujpobm!ujft!pg!DFSfT!ĝ!Xibuħ
t!vq-!hsbevbuft@ġʏ˂ĜʒāDFSfT!ୌᆡɈᆗߔ౺!౦‫ޢ‬ɁߤᄠĊĪʨˋʈˁʟɻʛʏʽ၂ī!ġ
DFSfT ɢɤȤඪɣȵĪJKKTT3127ާ੓ī
ş!Ofxtmfuufs!Op/241Īཡ਄3127༃Ǖॢī൦21‫ ޑ‬WM ਆ୔‫ާޏ‬੓ĪǕॢ31໲ġ32໲īġ໲ႨɈණ࢝ࠫപ‫ܒ‬౳ɬඪɧȠġɌɘɩɤǔਖʗɼɺʛʯࡅ‫ކ‬ᇦ੪୒ᆡ
ş!Ofxtmfuufs!Op/242Īཡ਄3127༃21ॢīബၡĊ൥ߔۡ࣋‫ۋ‬Ʌ˂ʺĜʠʓˋʏˋʈʋĜʑඞ౺!ġိ౰3:༃ǐॢĂᅃਗᆅ৙ߔ࿬ಡ඲ɒġ
Uif!27ui!Xpsltipq!po!TBS!Jnbhf!Qspdfttjoh
ġ Dijcb!Vojwfstjuz!Tvnnfs!Tdippm!po!Njdspxbwf!Sfnpuf!Tfotjoh ġဦင‫ߔݨ‬ௐਡᆏ൥ߔၭఱૅ‫ݻܧ‬ෳ!૗ઍ
ෂਡĂʠ˃ʋĂʺˋʌ˃Ɉ൥ߔ‫ێ‬਄Ȧ DFSfT ॽߔ
Yjokjboh!VojwfstjuzĂBolbsb!VojwfstjuzĂJtqbsub!VojwfstjuzĂNpohpmjbo!Bdbefnz!pg!Tdjfodf― 132 ―

ş!Ofxtmfuufs!Op/243Īཡ਄3127༃22ॢī൦Ǔ‫ ޑ‬Joepoftjb!Kbqbo!Kpjou!Tdjfoujgjd!TznqptjvnĪJKKTTīާ੓ġǎ༃ɅǍ๱ɈɼˋʡʥʏɺĆ໲Ⴈࢼວ‫ߔݨ‬ʏˋʵʐɾʸĂ਱༃ɉಫᅝ൥ߔɁġ˂ɺɾĆɼʑˁʸ൥ߔĂʏɺʇॻɂɈৄᆔࢾฤȦำय़SFTFBSDI!USJQ!UP!JOEJB!ġʑʃɼʥʛʠĂɼˋʡʍɼʠާಡɅ৐ȫɀġ൥ߔ೔ൌɁɈࠞࣃɒɈଲɤ೨ə!ġ JTP ໘ငࠠੈय़‫ݪ‬ၡਠġ
ş!Ofxtmfuufs!Op/244Īཡ਄3127༃23ॢī൦33‫ޑ‬Ķఛદࣞ೯౺ʯ˅ʟʽĜʑߤ຦ķ˂ʺĜʠʓˋʏˋʈɈ੕೐ೀ!ġ‫ܒ‬౳ȥɣʡ˅ĜˋɘɁġ‫ݴ‬ဢʏĜʒˋຖᅰĂൎ઄ɉ჈೔Ɂȳȥĉ!ġɾɿʎĜʣʽĜʒଜɂɈࢼວॸ࢞ɢɤĪႨࣕॸ࢞ଆīġఛ໸ఊۙɈ௘‫ގ‬ćʘʷɺĜʣāɺ˄ʛʍˋʡ˅āູ໸஝࣋
ş!Ofxtmfuufs!Op/245Īཡ਄3128༃ǍॢīɼˋʡɁɈණ௫˂ʺĜʠʓˋʏˋʈࠫപɈ஑ࡖय़‫!ݪ‬ġʏ˂Ĝʒ!DFSfT Ɉॸ࢞ߤ຦၆ɤĪ໴৮ॸ࢞ଆīġĶGvuvsf!Fbsui!ʅʛʇʂʭ!ˇĜʇʏʿʛʯķާ੓ȱɘȳġ఍Ć०য়ĆࠞࣃĂɬʅĜˇĜʡɅĂಫᅝ൥ߔ Gvuvsf!Fbsui Ɉ੭ɤၫɬ৽ȢɥġࣅȞࠂ࡜୙ᅰĂ໲Ⴈ‫ޠ‬തɁɉ൥ಥറȩĂშগ‫ݎ‬Ɂɜಓಥ!ġ DFSfT!ZpvUvcf ৊ૺʙʻˋʥ˃ɢɤġ
ş!Ofxtmfuufs!Op/246Īཡ਄3128༃ǎॢī൦2:‫ʺ˂ࣃࠞޑ‬Ĝʠʓˋʏˋʈʏˋʵʐɾʸާ੓ʧɼˁʞɻȯɭĂି௤ȤɛɁɂȠȮȰȞɘȳ!ġෂਡఱᆗߔ౺ॸ࢞யᇋ௤ġ෵ଲɁࡥሃโɄ൥ಥ!ġ DFSfT!ZpvUvcf ৊ૺʙʻˋʥ˃ɢɤġ
ş!Ofxtmfuufs!Op/247Īཡ਄3128༃Ǐॢīಫᅝ൥ߔ Gvuvsf!Fbsui!ljdl.pgg ˇĜʇʏʿʛʯާ੓ၡਠ
ߔ‫ڮ‬ଲຶȤɛɁɂȠȮȰȞɘȳ
DFSfT ɢɤȤඪɣȵĪOPBB0BWISS ିఒʏʑʞʸ୒ᆡīŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖŖ
ş!Ofxtsfmfbtf!Op/!4Īཡ਄3127༃Ǐॢī໲ႨɈ‫ݗ‬ଆৌ‫ݪ‬ʄʑࠫപࡳ୹‫ܒ‬౳ĶȞɐȧķɅɢɥ௫ऋɈ໩બ‫ݛ‬ඖ೧༏๱Ɉࠫപ
ġఱ৙‫ܒ‬౳Ɂ௫ऋɈ໩બ‫ݛ‬ඖ೧༏๱ɬɃɦȩɣȞ౷ߊɅപɦɥȥĉġĪᥓນஶા஝࣋ॸ࢞ʈ˃Ĝʯī

ş!Ofxtsfmfbtf!Op/!5Īཡ਄3127༃ǑॢīĶɌɘɩɤǔਖķ౼დࡐ‫ݝ‬ၒ౷੟ʈ˂ʛʡʟĜʗ৊ާġĶɌɘɩɤǔਖķɈȳȮȯɬȜɄȹɜଌ੫ɈʟĜʗ‫ސ‬಑ɁൌঅɁȧɘȳġĪ樋৏ຼૂஂ࣋ୂĆඹෂ‫܉‬௃ࢊۙஂ࣋ୂĆၹ຀৹‫ູێ‬໸ॸ࢞ۙī― 133 ―

ş!Ofxtsfmfbtf!Op/!6Īཡ਄3127༃ǓॢīĶຄɺʐɺɈ൥࡜ෂ OP3ܸಹ˄ʱ˃ĂǑ༃೐Ɉ˄ʱ˃Ʌ‫ޑ‬ဌȱɀȞȹĊķġ଱ɅෂਡɁ‫ޑ‬ဌĂ໲ႨĆ࠴ਡɁɉɞɞ‫ݛڏ‬Ɉभ৐ġ!Ī˂ʺĜʠʓˋʏˋʈɅɢɥബၡīĪ໴৮ॸ࢞ଆī

ş!Ofxtsfmfbtf!Op/!7Īཡ਄3127༃ǔॢī‫ܒ‬౳ࠫപȥɣఝᆹɈᆹယ৭ഢȦ੔এ‫ݢ‬༑ɅĊġᆏᄄდ๱ɂୃ਒ɅࡊȿȞȹᆹယ৭ഢʺʟ˃ɈާཡġĪᅔ‫ູڰ‬໸஝࣋ī

ş!Ofxtsfmfbtf!Op/!8Īཡ਄3127༃21ॢī೔࢝ఆ౺ʨɼʂʶʑɈ༘‫ڐ‬ɬᄆૄȱɀ
ġ HDPN.DĪණ࢝ࠞࣃဿ຦ࠫപʷʛʏʿˋɈ‫ܒ‬౳īĂ3129༃൅Ȼ௫ȬᅅฤġĪႨഽ‫ݣ‬ცஂ࣋ୂī― 134 ―

Į23įā೨ఉĆ‫܄ۿ‬ĆఱૢĆᅅધ
23/2/āʓˋʗĜɈ৭౰Īိ౰3:༃Ǐॢএ੭īʓˋʗĜෳāāā‫݊ڤ‬ā೑ဦ˂ʺĜʠʓˋʏˋʈࡊྉॸ࢞ᆴ‫ۊ‬˂ʺĜʠʓˋʏˋʈထਗॸ࢞ᆴ‫ۊ‬࣋āୂāāāKptbqibu!Ufuvlp!TsjāāāāāāTvnbouzpஂ࣋ୂāāāႨഽā‫ݣ‬ცஂ࣋ୂāāā໴৮āల઺ਆāુāāāߝঈāয়શ࣋āୂāāā࢏౦ā৘ც࣋āୂāāāࣷນāூྷஂ࣋ୂāāāႨࣕāಫ୽‫ܒ‬౳ʟĜʗஐᆅଆଆෳĆஂ࣋ୂāāā樋৏āຼૂ஝࣋āāāāāāāᥓນāஶા

23/3/āఊۙშၛĪိ౰3:༃Ǐॢএ੭ī
࣋ۙ೨ఉ
ఊāშ

+

્āშ

ྩā৽

ູ໸࣋ୂ

‫݊ڤ‬ā೑ဦ

ʓˋʗĜෳ

࣋ୂ

࢏౦ā৘ც

ဋʓˋʗĜෳ

࣋ୂ

ࣷນāூྷ

ā

࣋ୂ

Kptbqibu!Ufuvlp!Tsj!Tvnbouzp

ā

ஂ࣋ୂ

໴৮āల઺

ā

ஂ࣋ୂ

樋৏āຼૂ

ā

ஂ࣋ୂ

Ⴈࣕāಫ୽

ā

ஂ࣋ୂ

Ⴈഽā‫ݣ‬ც

ā

ਆુ

ߝঈāয়શ

ā

஝࣋

ᥓນāஶા

ā

࣋ୂ

+

൩ᄘā࿢ც

৙ߔॸ࢞‫ݨ‬

࣋ୂ

+

ટ੸āဦᅂ

৙ߔॸ࢞‫ݨ‬

࣋ୂ

+

ဎငāਞა

ᆅߔॸ࢞‫ݨ‬஝࣋+‫ݡ‬ນā঄

‫ݨ࢞ॸߔ॑ܠ‬

ູ໸஝࣋

ᅔā‫ڰ‬

ā

ູ໸஝࣋

ᤁાā෸ৠ

ā

ູ໸஝࣋

ટ๜āც९

ā

ູ໸஝࣋

‫ۈ‬ഺāఒࡹ

āູ໸஝࣋

Divb!Njoh!Zbn

ູ໸஝࣋

Bmfttboesp!Ebnjbojູ໸ॸ࢞ۙၹ຀ā৹‫ێ‬

ູ໸ॸ࢞ۙ

݊Ⴈāৰ

ā

ູ໸ॸ࢞ۙ

࣌Ⴈā୻ூ

ā

ࢊۙ࣋ୂ

༣ဓāሆᅂ

ਡᆏࠞࣃॸ࢞ஒ

ྥ௵ࣦਆુĪࢊۙஂ࣋ୂī๜ෂāॿ૭ࢶ๬൥ߔ႕੠ॸ࢞ஒ

ྥ௵ࣦਆુĪࢊۙஂ࣋ୂīඹෂā‫܉‬௃ۧහਂऋॸ࢞ާཡ࡙৭

ྥ௵ࣦਆુĪࢊۙॸ࢞ۙīTibsnb!Sbn!DiboesbāਆુĪॸ࡙࢞࠲ॸ࢞ۙīഷā玫āਆુĪॸ࡙࢞࠲ॸ࢞ۙī਒࣌ā‫ڟ‬਑

ā

ā

ɉ१ო࣋ۙ

― 135 ―

ૢო೨ఉ
ఊāშ

્āშ

ྩā৽

ૢოʓˋʗĜෳ๲‫ݎ‬ā౷஧

৙ߔृૢოʓˋʗĜ

ಮᄑۙ

ሆ๜āਔ

৙ߔृૢოʓˋʗĜ‫ཾێ‬ఊۙ

ද๜āႊ৙ߔृૢოʓˋʗĜૢოၒੂۙࡈഽā‫ݤ‬ા

ā

ૢოၒੂۙ

ಫᅝāణ࢕

ā

ૢოၒੂۙ

࣌Ⴈā‫ྰݠ‬ૢოၒੂۙ௄ঈā໖෿ા

āૢოၒੂۙ௄Ⴈāषᆅાāૢოၒੂۙ‫ڭ‬ນā‫ݠ‬ા

ૢოၒੂۙ

छರāᄡൣ

ā

ૢოၒੂۙ

ကతāሆા

ā

ૢოၒੂۙ

෿๜ā‫ݠ‬ા

ā

ૢოၒੂۙ

࢔Ⴈāಫഁ

ࡳ୹ၒੂۙĪॸ࢞ૅ‫ైܧ‬మۙīಆᄄāੂषા

ࡳ୹ၒੂۙ

ۧ๜āᄙ౺

ࡳ୹ၒੂۙ

஧ငāਛ

ࡳ୹ၒੂۙ

‫ݡ‬ນā௕ા

ࡳ୹ၒੂۙ

ᆏಒāਗ਼

ࡳ୹ၒੂۙ

ိᄘāəȯ

ā

23/4/āࢪ๘‫ޏۙڳ܄ۿ‬ိ౰39༃๱āಫᅝ൥ߔࠞࣃ˂ʺĜʠʓˋʏˋʈॸ࢞ʓˋʗĜࢪ๘‫ۙڳޏۙڳ܄ۿ‬შၛ
ိ౰3:༃Ǐॢ42໲এ੭
ᄜāఊ

્āშ

ஒമĆఊშ

‫ۙڳ‬ෳ

ਥ࠾āᤁ঵!

൥ߔۡᅃਗ‫ݨ࢞ॸߔݨ‬Ī࣋ୂī

‫ڳ‬āۙ

ટႨāಇ࿧

ۧහਂऋॸ࢞ާཡ࡙৭Īᆅૢī

‫ڳ‬āۙ

ෳඇರāࣧ

ਡ๲࠵൥ߔဦߔငණᆅĆࠞࣃಮ০Ī࣋ୂī

‫ڳ‬āۙ

௫๜āག

შগ‫ݎ‬൥ߔĪშᅈ࣋ୂī

‫ڳ‬āۙ

༳ࠍᄘā২

ၪഗ൥ߔĪ࣋ୂī

‫ڳ‬āۙ

྅ഺā২!

ಫᅝॻࠞࣃॸ࢞ʓˋʗĜĪ଱໸௫ಌॸ࢞ۙī

‫ڳ‬āۙ

ୣāც౷

ਡᆏࠞࣃॸ࢞ஒĪᆅૢෳī

‫ڳ‬āۙ

ဎငāਞა

൥ߔۡᆅߔॸ࢞‫ݨ‬Ī࣋ୂī‫ڳ‬āۙ‫݊ڤ‬ā೑ဦ

ࠞࣃ˂ʺĜʠʓˋʏˋʈāॸ࢞ʓˋʗĜĪʓˋʗĜෳī

‫ڳ‬āۙ

࢏౦ā৘ც

ࠞࣃ˂ʺĜʠʓˋʏˋʈāॸ࢞ʓˋʗĜĪဋʓˋʗĜෳī

‫ڳ‬āۙ

ࣷນāூྷ

ࠞࣃ˂ʺĜʠʓˋʏˋʈāॸ࢞ʓˋʗĜĪ࣋ୂī― 136 ―

23/5/āߔ໘߂ହ‫ۙڳޏۙڳ‬ȤɢɍʓˋʗĜ໘‫ޏۙڳ‬ိ౰39༃๱āߔ໘߂ହ‫ۙڳޏۙڳ‬‫ޏۙڳ‬ຑშ

‫ۙڳ‬ఊშ

્āშ႕੠ࡇ࡙ൎ઄ଆ

ଆۙࣷນāூྷਡ੫ಱᆒႨငāਡ੫ಱᆒଆ

ଆۙˀʍʭɹʛʠ

ߔ୹ॸ࢞ైమ࡙৭āॸ࢞ૅ‫ކࡅܧ‬င‫ޏ‬

৭౰ۙ

ࣷນāூྷ

ঢ়ၡಱᆒଆāঢ়ၡైమಮᄑင‫ޏ‬

৭౰ۙ

໴৮āల઺

ߔ୹ॸ࢞ైమ࡙৭āଭ଴ॸ࢞ଞ‫ۋ‬౰ငᄑ৭౰ۙʞʣʽɺʠˁʛʇగੈĆ࿎‫ݟ‬င‫ޏ‬࢏౦ā৘ც

ࠞࣃ JTP ଌ਄‫ޏۙڳ‬

‫ۙڳ‬

ᥓນāஶા

ʾʣʛʠࠞࣃಗ໸ଞĪॸ࢞ງīᥓນāஶાʾʣʛʠࠞࣃಗ໸ଞĪࢼວງĆଌঅງīˀʍʭɹʛʠ

ʾʣʛʠࠞࣃಗ໸ଞĪ৙ߔृ഍ਗງǔGī ࣷນāூྷௐʀʥ˂ĜʘĜ‫ࡼޏ‬ௐʀʥ˂ĜʘĜߝঈāয়શʧˁʑʹˋʠ

ʧˁʑʹˋʠഊඨۙ

Ⴈࣕāಫ୽௶ၡ။ীࠣᆅಗ໸ଞ

‫݊ڤ‬ā೑ဦ

௶ၡ။ীࠣᆅଞ

࢏౦ā৘ცʋˋʯˁɼɺˋʑైమಗ໸ଞ

‫݊ڤ‬ā೑ဦ

ʋˋʯˁɼɺˋʑైమဋಗ໸ଞ

࢏౦ā৘ცॸ࢞ᆷᆅ࣋‫ۋ‬ಗ໸ଞ‫݊ڤ‬ā೑ဦ

௶ၡ‫ڤ‬೔ࠣᆅൌ౫

ʋˋʯˁɼɺˋʑࠣᆅ
ॸ࢞ᆷᆅ࣋‫ۋ‬ိ౰39༃๱āʓˋʗĜ໘ā‫ޏۙڳ‬შ࢒ɍ‫ۙڳ‬შ‫ޏۙڳ‬შ

‫ۙڳ‬ෳ

‫ڳ‬āۙ

ᅅધ‫ޏۙڳ‬࢏౦ā৘ცࣷນāூྷĂKptbqibu!Ufuvlp!Tsj!TvnbouzpĂ樋৏āຼૂࢼວᆀᅙॸ࢞ైమ‫ޏۙڳ‬Ⴈࣕāಫ୽Ⴈഽā‫ݣ‬ცĂKptbqibu!Ufuvlp!Tsj!Tvnbouzpঢ়ၡ‫ޏۙڳ‬Kptbqibu! Ufuvlp!
ᥓນāஶાĂ໴৮āల઺
Tsj!Tvnbouzpૈಡ‫ޏۙڳ‬ࣷນāூྷႨഽā‫ݣ‬ცĂᥓນāஶાोધ࡙࢒ɍʟĜʗʱĜʑ‫ޏۙڳ‬樋৏āຼૂࣷນāூྷĂߝঈāয়શĂᥓນāஶા࣋‫ޏۙڳۋ‬ࣷນāூྷߝঈāয়શĂKptbqibu!Ufuvlp!Tsj!TvnbouzpĂ樋৏āຼૂෂࡖो‫ైކ‬మ‫ޏۙڳ‬‫݊ڤ‬ā೑ဦ

ಮ໸࣋ۙ૵জ๘ॳ ¦ ࿎‫ޏۙڳݟ‬‫݊ڤ‬ā೑ဦ

ಮ໸࣋ۙļૢოʓˋʗĜෳߔ୹ైమࡅ‫ކ‬ழ‫ޏۙڳ‬ࣷນāூྷʓˋʗĜෳ!Ăᅅધ‫ۙڳ‬ෳĂঢ়ၡ‫ۙڳ‬ෳĂʓˋʗĜૅ‫ܧ‬ʈ˃Ĝʯʈ˃Ĝʯ˂ĜʘĜ

― 137 ―

23/6/āᅅધိ౰39༃๱ā੕୒ᅅધૢāਐ‫ৄྣ܄ۿ‬࿥ࣸᅅધߗĪ‫ܟ‬īྩā৽

24:-691-656

࣋‫ྣॄ࢞ॸۋ‬96-834-656

ʈ˅Ĝʨ˃ʯ˅ʷʥˋʠॸ࢞ࡊࠎ

21-361-111

೔ਡࢼວᆀᅙĆࢼວଌૈ37-868-111

ၭఱ‫ߤ܄ۿ‬౯‫ྣॄܧૅݛ‬611-111ߔෳ੩ᆲॄྣ
ެင૝ࣸ

27-461-111
325-8:8-781‫ྣ࢞ॸߔݨ‬ၒ஝ࣸ

22-35:-757 ೐༃๱ट‫ܛ‬ယɬ࠸ɚି൵ॸ࢞ॄྣ

66-9:3-393 ੔‫ڳ‬൵ယɬ࠸ɚ

ࢼວॸ࢞ॄྣ

:-577-687

ି൵ૢࣞॄྣ

25-:25-719

ࡍ࿽ࣸॄྣ25-589-737 ೐༃๱ट‫ܛ‬ယɬ࠸ɚၒ஝ࣸຑॄྣ

:9-867-384

ॸ࢞࠲ᇦॄྣ

9-44:-76:ॸ࢞࠲ᇦॄྣĪ೔ߔࢼฆຑॄྣī2-811-111

ૈಡಡྩྣၒ஝ࣸૢࣞॄྣຑ
ਗāो1
465-489-326

Ŧಮ໸࣋ۙĂ௵ࣦૢოఊۙɈఱॣྣĂ࢒ɍ൥ߔႨငૅ‫ܧ‬ɈఱॣྣĪʟĜʗɺĜʃɼʮāࣞოɅबɥູ໸ယīɉ࠸ɘɄȞă― 138 ―

23/7/āެင૝ࣸ‫ێ‬ᅿĪ࠰ಞॄྣ࠸ɚ༃๱ඍ‫ڮ‬Ɉ༯ယĆऴᄝߗĂȹȺȱயߔࡍ࿽ࣸĂၒ஝ࣸຑɉྥऻ੪ī
ॸ࢞ହᄆ

ॸ࢞ʞĜʶ

ି໴࣋ۙ

ࣸߗ

‫ྣ࢞ॸߔݨ‬ၒ஝ࣸࡊྉॸ࢞ĪǟīāĪఛࡤīɌɘɩɤǔਖʀɺ˅ʖ˃ʟĜʗɈਡ੫ණ௫˂ʺĜʠʓˋʏ ໴৮āల઺ˋʈࠫപᄀɅɢɥ਒ߊ๱ॳ௠

2-7:1-111!

෣ಱโၴ‫࢞ॸވ‬āĪॅറī ʧɼʩĜʑʲʇʠ˃ɼʹĜʐˋʈɅɢɥ൥࡜ܸಹ࡜ൌɈ‫ ݢ‬ᤁાā෸ৠ૗‫ݛ‬

Ī!!೐༃๱ट‫ܛ‬Ȝɤīఛߔ୹ᆴ‫࢞ॸۊ‬Īယඐଞī ౉Ć๲ੋ‫ھ‬຦Ʌ཮Ƞၪଗ౯ဘଋɈ‫ھ‬਄‫ݿ‬าɈᆅ‫ސ‬Īॅറīāॸ࢞ൣ࿍ଞć‫ݖ‬๜ᄽ‫ێ‬Īය༜൥ߔīࣷນāூྷ

891-111ࡊྉॸ࢞ĪǯīĪယඐଞī ഽ༜ෳˁɼʘĜɂ‫ߔݛ‬ᄪഗʺʟ˃ɬຕਗȱȹʀɺ˅ʖ˃Ǒ ໴৮āల઺Īॅറī૫ইວ‫ݛ‬Ʌ࠲ȳɥಪຩโॸ࢞
āॸ࢞ൣ࿍ଞćۭᄘ‫ڭ‬෿ૂĪࣻୋ൥ߔī2-:61-111ࡊྉॸ࢞ĪǝīĪယඐଞī ࢳᇆཽఇ࡙৭Ʌ࢒ɖȳණ࢝‫ݗ‬ඤ‫ݛ‬Ć࡜েဿ຦‫ࣗ܆‬Ɉഁࡖ् ࣷນāூྷĪॅറī‫ૄޚ‬࿈Ɉ৭භɅ৐ȫɀāॸ࢞ൣ࿍ଞćʑʠ˃ʑʶˋ!D/B/Īຄࢶ‫ޠ‬ᅖ൥ߔī

891-111ࡊྉॸ࢞ĪǝīĪယඐଞī ʀɺ˅ʖ˃ණ௫˂ʺĜʠʓˋʏˋʈࠫപᄀɅɢɥౘඩʺʟ ໴৮āల઺Īॅറī˃Ɉ࡜েဿ຦ᅅപɈ਒๱‫ݛ‬āॸ࢞ൣ࿍ଞćඹഺ୻ྷĪࣻୋ൥ߔī3-217-111ࡊྉॸ࢞ĪǞīĪယඐଞī ‫ܒ‬౳຃੪ɺʇʞɻʮĆʩʛʏʮʓˋʍĜʟĜʗɈထਗᆀᅙ ໴৮āల઺ĪॅറīɅɢɥ೔࢝ʀɺ˅ʖ˃‫ސ‬಑āॸ࢞ൣ࿍ଞćಀ៛ථცĪਡᆏࠞࣃॸ࢞ஒī2-281-111ࡊྉॸ࢞ĪǞīĪယඐଞī ࡜েဿ຦࢒ɍଜ‫ॄޏ‬੟ʏʢ˂ʂɬ৽ᆞȱȹঢ়‫ݭۊ‬ರཷᅼ˂ ࣷນāூྷĪॅറīʑʇᅅപʺʟ˃ާཡ
āॸ࢞ൣ࿍ଞćߐā‫܉‬ସĪ๲ᄄॸ࢞ஒī2-385-111ࡊྉॸ࢞ĪǞīĪယඐଞī Ǐ૫ইఝᆹ৭ഢɅॊ৉ယ࿫௶ၡɬ࿥‫ݡ‬ȱȹఛȱȞ৉ࠞࣃĝ ᅔā‫ڰ‬৉ਗ౰ʺʐʽĜ˃Ɉާཡāॸ࢞ൣ࿍ଞćழᆹ୐ୃĪ‫ޠ‬ᅖॸ࢞ާཡ࡙৭ī2-151-111ࡊྉॸ࢞ĪǟīĪယඐଞī ౺ߤࠞࣃ५ɅȤȫɥ DP3༏๱Ɉණ‫ۊ‬౯ɅශᄆȱȹఛȹɄᆶ ࢏౦ā৘ცණ࿎‫ૄݟ‬࿈Ɉอ‫ڨ‬āॸ࢞ൣ࿍ଞćठঈāᄼષĪ‫ۓ‬௱൥ߔī

2-216-111

ି൵ॸ࢞
KTUāDSFTUFNT ɈȹɛɈ໲ଗʟĜʗিੇ࿎‫ݟ‬ණ௫ʏʑʞʸɈ৭භ໴৮āల઺

9-549-411

KBYBāHDPN!SB൥࡜ၒ౷੟əᆌ‫ཱۊ‬ଗᆎॳ௠ၫၭɈާཡĂ࢒ɍĂᅝჶಓૄ Ⴈഽā‫ݣ‬ცౘĆ৉ਗ౰ᄵৌၪଗ࢓େᆎైฤɺ˃ʌ˂ʒʸɈާཡ

9-831-111

KBYBāHDPN!SBʈ˅Ĝʨ˃ණ௫ʨɼʂʶʑైฤĂఆ౺ˁʭʥʑૄౘȤɢɍ ߝঈāয়શ౉ʑʠ˄ʑभ৐ૄౘɺ˃ʌ˂ʒʸɈާཡɂॳ௠

9-611-111!

ဦင‫ߔݨ‬ௐāۧහਂऋ‫ ݨ‬ණ࢝ࠫപ‫ܒ‬౳ʟĜʗɈණ௫ॳ௠ߤ຦Ʌɢɥଌ೉โఱ੮‫ۋ‬౰ Ⴈഽā‫ݣ‬ცߔࡳ୹ైమ‫ڳ‬൵ྣʑʅĜʸɈ৭භ

7-684-44:!

KBYBāHPTBU

22-111-111!

༂ಘެယ৉ʟĜʗɅɢɥ໩બ‫ݛ‬ඖ೧Ȥɢɍʹʗˋຩ୸ɺ˃ ᥓນāஶાʌ˂ʒʸɈ਒๱‫ݛ‬ĪȷɈǍīৠ೐൥ߔğࠞࣃௐĆ഍ਗ ‫ܒ‬౳Ć੔‫ސ‬಑ʟĜʗɬ઴ᅙȱȹɺ˃ʌ˂ʒʸ‫ޜ‬ᆯණ࢝ࠞࣃߔॸ࢞ஒ੔‫ڳ‬൵樋৏āຼૂ

9-:12-111

KTU!!TBUSFQT఍ᆧ‫ڤ‬೔။௩ɬᄆૄȱȹ࡜েဿ຦ไܾ઄ɂȱɀɈ༔ࣞ။ঃ Ⴈࣕāಫ୽ɅȤȫɥഹޮ࿎‫ݟ‬଴ၭɈ৭භɂଜ‫ޏ‬ଌക

7-5::-851!

KBYB

HDPN.D0THMJ ࡐ‫ݝ‬࿈ฤஐᆅĂ࢒ɍʂ˃ʕၒ౷ɺ˃ʌ˂ʒ Ⴈഽā‫ݣ‬ცʸɈ‫ڿ‬૩‫ีޜ‬:43-182

KBNTUFD0KBYB ੔‫ڳ‬൵

HDPN.D2ᅝ ჶ ಓ ૄ ౘĆ ৉ ਗ ౰ ᄵ ৌ ၪ ଗ ࢓ େ ᆎĪMBJ0 ᅔā‫ڰ‬
GBQBSīɂ஋‫ێ‬૫౺દᆲĪOQQīʯ˅ʘʇʠɺ˃ʌ˂ʒʸɈ৭භĪॸ࢞ʯ˅ʘʇʠī711-111KBYB

ိ౰39༃๱āఆ౺ˁɼʘĜࠫപჹࡴଌঅᅙਂऋ࡙຃੪ଌ Ⴈഽā‫ݣ‬ცঅɈॳ௠ʟĜʗɈଲຶ:::-881ဦင‫ߔݨ‬ௐಇો࡜௣‫ܒ‬౳दɢɤຩ୸ȯɦȹാᅣၪଗĆാᅣ৉ཡ๝ᆲై 樋৏āຼૂฤɈ౦‫ޢ‬๐ާ4-:88-391!

― 139 ―

ࢼວॸ࢞
KBYB

TLZOFU ණ௫˂ʺĜʠʓˋʏˋʈࠫപᄀɅɢɥ HDPN.D ໴৮āల઺൥࡜ʯ˅ʘʇʠɈॳ௠

໲Ⴈჟೀ߰ૺ‫ޏ‬ଜ‫ܒ‬౳Ă˄ĜʘĂණ௫ࠫപɅɢɥൎᆔ‫܀‬ཡ౺Ɉࠫപ

ɼˋʡʥʏɺۧහਂऋࣟ

ᅃਗණ࢝ࠞࣃఫඣॸ࢞ʯ˅ʈˁʸĝழळ‫ܒ‬౳दɅɢɥ൥ᆌ ˀʍʭɹʛʠ
ࡤჹණ߈ဿ຦Ɉࠫപĝ

1!

KBYB

ఆ౺ˁɼʘĜࡳ୹ଌ௠ɈȹɛɈᄘެଌঅ

Ⴈഽā‫ݣ‬ც

1!

KBYB

ಇો࡜௣‫ܒ‬౳दɬᅙȞȹ਒૪࠰ယ‫ސ‬༑ਏ౉࠲ᇦᅟ೧Ɉෆ୸ 樋৏āຼૂȤɢɍ HTNbQ ɒɈไᅙ4-:38-537!

໲Ⴈჟೀ߰ૺ‫ޏ‬ଜਗ౰ާ৏˄ĜʘĪTBSīʏʑʞʸĆTBS ‫ކ‬ജఒਖஐᆅʕ ˀʍʭɹʛʠ
ʭʠɈާཡɂȷɈܾᅙ

531-111!

ɼˋʡʥʏɺāʫʶʓʢଜ

Efwfmpqnfou! pg! D! Cboe! Tzouifujd! Bqfsuvsf! Sbebs! ˀʍʭɹʛʠ
ĪDC.TBSīgps!Vonboofe!Bfsjbm!Wfijdmf!Qmbugpsn

3-829-419

જྐྵ๝࡙Ī߰ī௶ၡࡳ୹഍ਗॸ࢞ஒ

ഁࡖਛ۫ᅅപࡳ୹

࢏౦ā৘ც

2-111-111!

Īਡīঈાᆵॸ࢞ާཡ࡙৭ ˄ĜʎĜ৉Ɉઢᅸɬᆀᅙȱȹၪଗ༑ᆲोപࡳ୹Ʌ࠲ȳɥॸ࢞ ࢏౦ā৘ც

Ľ!

樋৏āຼૂ

3-226-111!
531-111!

ି൵ૢࣞ
൥ᅣ໲બ

˄ĜʎĜယ৉Ʌɢɥວ‫ڮ‬ൌယ಑Ȥɢɍ˄Ĝʎ৉Ɉ਒ৌᆎ௎ ࢏౦ā৘ცଗၫၭɅ࠲ȳɥࡳ୹โૄຩ

൤ሕਡ‫ۧݦ‬හʓˋʗĜĪOTQPī

൤ሕਡ‫ۧݦ‬හʓˋʗĜĪOTQPīᅙਂऋ࡙຃੪ǟʨˋʡਗ ˀʍʭɹʛʠ 39-384-211
౰ާ৏˄ĜʘĪDC.TBSīɈާཡ― 140 ―

611-111千葉大学環境リモートセンシング研究センター
平成 28（2016）年度 年報（第 22 号）

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