台灣中型城市都市熱島效應及相關機制之研究 -以嘉義市為例

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(1)!. ! ! ୯ҥଯ໢εᏢβЕᆶᕉნπำᏢ‫!س‬ ᅺγፕЎ! !. Ѡ᡼ύࠠࠤѱ೿ѱ዗৞ਏᔈϷ࣬ᜢᐒ‫ڋ‬ϐࣴ‫!ز‬ .а჏ကѱࣁ‫!ٯ‬ A Study on Urban Heat Island Effect and Related Mechanism of Medium-sized Cities in Taiwan - A Case study of Chiayi City ! !. ࣴ‫ز‬ғǺЦ៉Ờ ኗ ࡰᏤ௲௤Ǻ஭ඁ໦ റγ ໳ࢋ➌ റγ. ύ๮҇୯΋႟ΖԃϤД.

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(3) ᖴ. ᇞ!. २ӃाӃགᖴ‫ࡰޑך‬Ꮴ௲௤ ஭ඁ໦Դৣ ᆶ ໳ࢋ➌ԴৣǴӧ೭‫ٿ‬ԃ ٰፌፌ௲ᇧǴӢࣁ‫ך‬όࢂҁࣽр‫܌ي‬аԖࡐӭܿՋᔉளόࢂࡐӭǴՠԴ ৣॺ‫ޑ‬ಒЈࡰᏤᆶᕴࢂਔਔᅱ࿎‫ך‬ᡣ‫ך‬ό࡙ආᚷණǴωૈ୼໩ճֹԋ‫ך‬ ‫ޑ‬ፕЎǴΨགᖴԴৣॺᡣ‫ך‬ԋࣁாॺ‫زࣴޑ‬ғǴᡣ‫ך‬Ꮲಞ‫ډ‬஑཰‫ޕ‬᛽Ϸ ࡑΓೀ٣‫ޑ‬ᄊࡋǶ ӆ‫ޣ‬Ǵགᖴα၂‫ہ‬঩৊ਁကԴৣǵᒘ௴ሎԴৣϷ݅௴ฐԴৣǴӧԆ࿛ ύ޸ਔ໔᎙᠐ᆂ‫ޑ‬ፕЎࡕǴ๏ϒ࣬྽ӭ‫ࡌޑ‬᝼ᆶୢᚒǴ٬ளፕЎёаঅ ‫׳ډׯ‬уֹ๓Ƕ ௗ๱གᖴ 413 ࣴ‫ޑ࠻ز‬Ꮲ‫׌‬Ꮲ‫ۂ‬Ǵ‫ڐ‬շ‫ޑך‬೿ѱ዗৞‫ޑ‬ჴෳၗ਑Ǵ ќѦ‫ٿ‬໔ჴᡍ࠻‫ޑ‬ӕᏢᏫ‫ݒ‬ǵ߭᏿Ǵӧ‫ך‬നሡा‫ޑ‬ਔংഉՔ‫ך‬ϷቪፕЎ ‫ޑ‬ၸำύ‫ڐ‬շ‫ࡐך‬ӭǴ‫܌زࣴޑך‬ғఱӢᇡ᛽գॺкᅈ೚ӭҒधӣᏫǶ നࡕགᖴ‫ݿݿޑך‬ǵ༰༰ǵঢঢǵ‫ۊۊ‬Ǵ྽߃،‫ۓ‬ᝩុϲᏢǴ൩Ԗ٤ ೚ᓸΚǴΨӢࣁჴᡍሡाࠄ೽ύ೽ٰӣາǴᡣգॺᏹЈΑǴᗋԖӧ‫ך‬଎ൽ ਔǴԖգॺ๏ϒ‫ޑ‬ཀ‫ـ‬ϷЍ࡭ᆶႴᓰᡣ‫ך‬໩ճֹ่‫܌زࣴ״‬ғࢲǶ.

(4) Ҟ. ᒵ. Ҟ ᒵ .............................................................................................................. I კҞᒵ ............................................................................................................IV ߄Ҟᒵ .......................................................................................................... VII ύЎᄔा ........................................................................................................... 1 मЎᄔा ........................................................................................................... 3 ಃ΋ക!ǵᆣፕ ................................................................................................. 5 1.1 ࣴ‫୏ز‬ᐒ ............................................................................................. 5 1.2 ࣴ‫ز‬Ҟ‫ ޑ‬............................................................................................. 6 1.3 ࣴ‫ز‬Б‫ ݤ‬............................................................................................. 6 1.4 ࣴ‫ࢎز‬ᄬ ............................................................................................. 7 ಃΒക!ǵЎ᝘ӣ៝ ......................................................................................... 8 2.1 ೿ѱ዗৞ਏᔈ ..................................................................................... 8 2.2 ୯ϣѦ೿ѱ዗৞ਏᔈ౜‫ ݩ‬................................................................. 9 2.2.1 ୯Ѧ዗৞ࣴ‫ز‬౜‫ ݩ‬.................................................................. 9 2.2.2 ୯ϣ዗৞ࣴ‫ز‬౜‫ ݩ‬.................................................................. 9 2.3 ೿ѱ዗৞மࡋࡰ኱ ........................................................................... 11 2.4 ౽୏ᢀෳ‫ݤ‬੝‫ ܄‬............................................................................... 12 2.5 ࠤѱ‫ޜ‬໔ჹ዗৞ᜢ߯ ....................................................................... 14 2.5.1 ዗৞ᆶ೿ѱೕኳᆶΓαᜢ߯................................................ 14. I.

(5) 2.5.2 ዗৞ᆶβӦճҔᜢ߯ ............................................................ 14 2.5.3 ዗৞ᆶຉၰࠠᄊ (SVF) ᜢ߯.............................................. 18 2.5.4 ዗৞ᆶΓπ዗ǵኴଯᜢ߯.................................................... 20 ಃΟക!ǵࣴ‫ز‬Б‫ ݤ‬....................................................................................... 22 3.1 ჏ကѱ዗৞౜‫ݩ‬ፓࢗ ....................................................................... 22 3.1.1 ౽୏ᢀෳჴෳБ‫ ݤ‬................................................................ 22 3.1.2 GIS ྕࡋ฻ॶጕϩ‫݋‬Б‫ ݤ‬.................................................... 27 3.2 ࣬ᜢӢηໆϯϩ‫݋‬Б‫ ݤ‬................................................................... 28 3.2.1 εЁࡋ .................................................................................... 28 3.3.1 λЁࡋ .................................................................................... 31 ಃѤക!ǵ჏ကѱ೿ѱ዗৞மࡋፓ่ࢗ݀ ................................................... 39 4.1 ྕࡋਔ໔ਠ҅ ................................................................................... 39 4.2 ዗৞ፓ่ࢗ݀-қϺ ......................................................................... 43 4.4 Ў᝘ፓࢗКၨ ................................................................................... 46 4.51999(2005)ǵ2017(2014)‫ྣޜ‬კКၨ ............................................ 49 ಃϖക!ǵቹៜ዗৞࣬ᜢ‫ޜ‬໔Ӣηፓ่ࢗ݀ ............................................... 55 5.1 ୔ୱЁࡋϩ‫ ่݀݋‬........................................................................... 55 5.1.1 Γαஏࡋ ................................................................................ 55 5.1.2 ᆘᙟ౗ .................................................................................... 57 5.2 ຉ୔Ёࡋϩ‫ ่݀݋‬........................................................................... 62. II.

(6) 5.2.1 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎϺ‫ޜ‬ຎ౗ (SVF) ϩ‫ ่݀݋‬.......... 62 5.2.2 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎ഍ቹϩ‫ ่݀݋‬................................ 65 5.2.3 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎࡌᑐᙟᇂ౗ϩ‫ ่݀݋‬.................... 67 5.2.4 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎ৒ᑈ౗ (֖ኴቫኧ) ϩ‫่݀݋‬...... 69 5.2.5 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎΓπ዗ϩ‫ ่݀݋‬............................ 73 5.2.6 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎᆘϯᙟᇂ౗ϩ‫ ่݀݋‬.................... 77 ಃϤക!ǵ዗৞ਏᔈᆶࡌԋᕉნӢηϐ࣬ᜢ‫܄‬ϩ‫݋‬................................... 80 6.1 ࣬ᜢ‫܄‬ϩ‫ ݋‬....................................................................................... 80 6.2 қϺ዗৞ਏᔈᆶຉ୔ЁࡋࡌԋӢηϩ‫่݀݋‬............................... 80 6.3 ‫ڹ‬໔዗৞ਏᔈᆶຉ୔ЁࡋࡌԋӢηϩ‫่݀݋‬............................... 81 6.4 ᆶၸѐࣴ‫่݀ز‬ϐКၨ(ፎКၨᆶၸѐࣴ‫ ز‬................................. 82 ಃΎക!ǵ่ፕ ............................................................................................... 96 ୖԵЎ᝘ ......................................................................................................... 99 ߕᒵ 1 ჏ကεᏢ਻ຝઠၗ਑Ϸঅ҅ॶ ...................................................... 104 ߕᒵ 2 Ӛෳᗺ‫ڬ‬ᜐ 100m Ϻ‫ޜ‬ຎ౗(SVF)ϩ‫่݀݋‬კ΋ំ߄ ................ 108 ߕᒵ 3 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎ഍ቹკ....................................................... 113 ߕᒵ 4 Ӛෳᗺ‫ڬ‬ᜐ 100m ࡌጨ౗ǵᆘᙟ౗ϩ‫݋‬კ΋ំ߄ ..................... 127 ߕᒵ 5 Ӛෳᗺ‫ڬ‬ᜐ 100m ኴଯϩ‫݋‬კ΋ំ߄.......................................... 133. III.

(7) კҞᒵ კ 2.1 Ϻ‫ޜ‬ຎ౗(SVF)ᆶ೿ѱ዗৞மࡋȐOkeǴ1981ȑ ........................... 18 კ 2.2 ᆵчࣧӦჴෳྕࡋϩѲკ(ύϱ) (ᙁη๔, 2013) ........................... 20 კ 3.1 ϩ୔Ңཀკ ........................................................................................ 22 კ 3.2 Ӛ୔ෳᗺՏ࿼ .................................................................................... 23 კ 3.3 ෳᗺՏ࿼Ңཀკ ................................................................................ 23 კ 3.4 ऍ୯ HOBO MX2301 ᙔУඵૈྕᔸࡋ૶ᒵᏔ............................... 25 კ 3.5 HOBO RX3000 ਻ຝઠ ..................................................................... 25 კ 3.6 GIS ჏ကѱٚࣚკ ........................................................................... 28 კ 3.7 2014 ԃ჏ကѱٚࣚ‫ྣޜ‬კ............................................................... 30 კ 3.8 NVI-met ࡌኳ‫ހ‬य़Ңཀკ ................................................................ 32 კ 3.9 Project Wizard Ңཀკ ....................................................................... 32 კ 3.10 Envimet4 ϩ‫݋‬Ңཀკ ....................................................................... 33 კ 3.11 ჏ကѱӄ୔ࡌᑐኴቫଯࡋ಍ी CAD კ ......................................... 33 კ 3.12 SketchUp ࡌኳ ................................................................................... 33 კ 3.13 ९ຎკϷ҅ຎკ ................................................................................ 34 კ 3.14 ୯βೕჄӦ౛ၗૻკѠ‫ޑ‬ໆෳπ‫ڀ‬Ңཀ ....................................... 35 კ 3.15 ჏ကѱ೿ѱीฝኧॶӦ‫ ׎‬CAD ۭკ(ъ৩ 100m) ........................ 35 კ 3.16 ჏ကѱ೿ѱीฝኧॶӦ‫ ׎‬CAD ۭკ(ъ৩ 100m) ........................ 37 კ 3.17 ᆘϯᅿᜪ ............................................................................................ 38 კ 3.18 Յ༧КфૈҢཀკ ............................................................................ 38 კ 4.1 7 Д 28 В চ‫ࡋྕۈ‬қϺ዗৞ፓ่ࢗ݀ ........................................ 43 კ 4.2 7 Д 28 В ਔ໔ਠ҅ࡕқϺ዗৞ፓ่ࢗ݀ .................................... 44. IV.

(8) კ 4.3 7 Д 29 В চ‫ࡋྕۈ‬қϺ዗৞ፓ่ࢗ݀ ........................................ 44 კ 4.4 7 Д 29 В ਔ໔ਠ҅ࡕқϺ዗৞ፓ่ࢗ݀ .................................... 45 კ 4.5 7 Д 30 В চ‫ࡋྕۈ‬ఁ໔዗৞ፓ่ࢗ݀ ........................................ 45 კ 4.6 7 Д 30 В ਔ໔ਠ҅ྕࡋఁ໔዗৞ፓ่ࢗ݀ ................................ 46 კ 4.7 ഋ߷‫(׊‬2000) 1999/8/16 14Ǻ00.................................................... 47 კ 4.8 2018/7/29 13Ǻ00 ........................................................................... 47 კ 4.9 ഋ߷‫(׊‬2000) 1999/8/16 02Ǻ00.................................................... 48 კ 4.10 2018/7/30 24Ǻ00 ........................................................................... 49 კ 4.11 ჏ကѱ 2005 ԃǵ2014 ԃ‫ྣޜ‬კ 10 ٚΓπय़ᑈቚуК‫ ٯ‬.......... 52 კ 4.12 ჏ကѱ 2005 ԃǵ2014 ԃ‫ྣޜ‬კ..................................................... 53 კ 4.13 ჏ကѱ 2005 ԃǵ2014 ԃΓπय़ᑈቚуК‫ ٯ‬................................ 54 კ 5.1 ჏ကѱӚᎃٚΓαஏࡋԛኧϩଛკ................................................ 56 კ 5.2 ჏ကѱӚٚΓαϩթკ.................................................................... 57 კ 5.3 Ӛٚԛኧϩଛკ(a)ᆘᙟय़ᑈ(b)ᆘᙟ౗ .......................................... 60 კ 5.4 ჏ကѱӚٚᆘӦय़ᑈϩѲკ............................................................ 61 კ 5.5 ჏ကѱӚٚᆘᙟ౗ϩѲკ................................................................ 61 კ 5.6 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎϺ‫ޜ‬ຎ౗(SVF)ԛኧϩଛკ ...................... 62 კ 5.7Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎϺ‫ޜ‬ຎ౗(SVF) (a)‫ޜ‬໔ϩѲ(b)঺᠄Γαஏࡋ ϩѲკ ............................................................................................................. 64 კ 5.8 Ԗ഍ቹϐෳᗺ .................................................................................... 66 კ 5.9 Ӛෳᗺ‫ڬ‬ᜐ 100m ࡌᑐᙟᇂ౗ԛኧϩଛკ .................................... 67 კ 5.10 Ӛෳᗺ‫ڬ‬ᜐ 100m ࡌᑐᙟᇂ౗(a)‫ޜ‬໔ϩѲ(b)঺᠄ΓαஏࡋϩѲკ ............................................................................................................ 69. V.

(9) კ 5.11 Ӛෳᗺ‫ڬ‬ᜐ 100m ৒ᑈ౗ԛኧϩଛკ ............................................ 70 კ 5.12 Ӛෳᗺ‫ڬ‬ᜐ 100m ৒ᑈ౗‫ޜ‬໔ϩѲკ ............................................ 73 კ 5.13 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎΓπ዗ԛኧϩଛკ .................................... 74 კ 5.14 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎΓπ዗ԛኧ‫ޜ‬໔ϩѲკ ............................ 76 კ 5.15 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎᆘϯᙟᇂ౗ԛኧϩଛკ ............................ 77 კ 5.16 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎᆘϯᙟᇂ౗‫ޜ‬໔ϩѲკ ............................ 79. VI.

(10) ߄Ҟᒵ ߄ 2.1 ዗৞ਏᔈቹៜӢη ............................................................................ 11 ߄ 2.2 ዗৞ᝄख़ำࡋຑ՗Б‫(ݤ‬GivonBaruch,1998) .................................. 12 ߄ 2.3 ౽୏ᢀෳБ‫ݤ‬ϐᓬલᗺᆶᔈҔጄൎ(৊ਁက, 2008) ....................... 12 ߄ 2.4 ෳ౽୏ᢀෳБ‫ݤ‬ϐ໨Ҟ(৊ਁက, 2008) ........................................... 13 ߄ 2.5 Ѡύѱ୘཰৒ᑈ౗ᆶྕࡋϐᜢ߯(‫׵‬ሱ᜻, 1999) ........................... 21 ߄ 3.1 ჏ကѱϐύѧ਻ຝֽ߈ϖԃ਻ংచҹ(2014-2018) ....................... 26 ߄ 3.2 ਻ຝઠ೴ਔྕࡋ ................................................................................ 27 ߄ 3.3 ჏ကѱ 107 ԃ 7 ДӚٚϐΓαኧ߄................................................ 29 ߄ 3.4 ҁࣴ‫ز‬჏ကѱҔႝໆᆶኴቫϩᜪ΋ំ߄ ....................................... 36 ߄ 4.1 ч୔ਠ҅ࡕྕࡋ ................................................................................ 40 ߄ 4.2 ࠄ୔ਠ҅ࡕྕࡋ ................................................................................ 41 ߄ 4.3 Ջ୔ਠ҅ࡕྕࡋ ................................................................................ 42 ߄ 4.4 Γπय़ᑈቚуК‫ٯ‬΋ំ߄................................................................ 50 ߄ 5.1 ჏ကѱӚᎃٚΓαஏࡋϩ‫่݀݋‬΋ំ߄ ....................................... 55 ߄ 5.2 Ӛٚᆘᙟय़ᑈϷᆘᙟ౗ϩ‫่݀݋‬΋ំ߄ ....................................... 57 ߄ 5.3 Ӛෳᗺ‫ڬ‬ᜐ 100m Ϻ‫ޜ‬ຎ౗(SVF)ϩ‫่݀݋‬΋ំ߄ ...................... 63 ߄ 5.4 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎ഍ቹԖคϩ‫่݀݋‬΋ឯ߄ ........................ 65 ߄ 5.5 Ӛෳᗺ‫ڬ‬ᜐ 100m ࡌጨ౗ϩ‫่݀݋‬΋ំ߄ .................................... 68 ߄ 5.6 Ӛෳᗺ‫ڬ‬ᜐ 100m ѳ֡ኴଯ่݀ .................................................... 71 ߄ 5.7 Ӛෳᗺ‫ڬ‬ᜐ 100m ৒ᑈ౗่݀ ........................................................ 72 ߄ 5.8 Ӛෳᗺ‫ڬ‬ᜐъ৩ 100m Γπ዗ϩ‫่݀݋‬΋ំ߄ ............................ 75 ߄ 5.9 Ӛෳᗺ‫ڬ‬ᜐ 100m ᆘϯᙟᇂ౗ϩ‫่݀݋‬΋ំ߄ ............................ 78. VII.

(11) ߄ 6.1Ӛঁෳᗺਔ໔ਠ҅қϺ਻ྕᆶ‫ڬ‬ᜐ 100m ጄൎӣᘜϩ‫่݀݋‬ᆕӝ΋ ំკ߄ ............................................................................................................. 83 ߄ 6.2Ӛঁෳᗺਔ໔ਠ҅ఁ΢਻ྕᆶ‫ڬ‬ᜐ 100m ጄൎӣᘜϩ‫่݀݋‬ᆕӝ΋ ំკ߄ ............................................................................................................. 84 ߄ 6.3Ӛঁෳᗺਔ໔ਠ҅қϺ਻ྕᆶ‫ڬ‬ᜐ 100m ጄൎ SVF ॶӣᘜϩ‫่݋‬ ݀΋ំ߄ ......................................................................................................... 85 ߄ 6.4 Ӛঁෳᗺਔ໔ਠ҅қϺ਻ྕᆶ‫ڬ‬ᜐ 100m ጄൎᆘϯᙟᇂ౗ӣᘜϩ ‫่݀݋‬΋ំ߄ ................................................................................................. 86 ߄ 6.5Ӛঁෳᗺਔ໔ਠ҅қϺ਻ྕᆶ‫ڬ‬ᜐ 100m ጄൎࡌጨ౗ӣᘜϩ‫่݀݋‬ ΋ំ߄ ............................................................................................................. 87 ߄ 6.6Ӛঁෳᗺਔ໔ਠ҅қϺ਻ྕᆶ‫ڬ‬ᜐ 100m ጄൎ৒ᑈ౗ӣᘜϩ‫่݀݋‬ ΋ំ߄ ............................................................................................................. 88 ߄ 6.7 Ӛঁෳᗺ਻ྕᆶ‫ڬ‬ᜐ 100m ጄൎΓπ዗ӣᘜϩ‫่݀݋‬΋ំ߄ .... 89 ߄ 6.8 Ӛঁෳᗺ਻ྕᆶ‫ڬ‬ᜐ 100m ጄൎࡌԋӢηӣᘜϩ‫݋‬΋ំ߄ ........ 90 ߄ 6.9Ӛঁෳᗺਔ໔ਠ҅‫ڹ‬໔਻ྕᆶ‫ڬ‬ᜐ 100m ጄൎ SVF ॶӣᘜϩ‫่݋‬ ݀΋ំ߄ ......................................................................................................... 91 ߄ 6.10Ӛঁෳᗺਔ໔ਠ҅‫ڹ‬໔਻ྕᆶ‫ڬ‬ᜐ 100m ጄൎᆘᙟ౗ӣᘜϩ‫่݋‬ ݀΋ំ߄ ......................................................................................................... 92 ߄ 6.11Ӛঁෳᗺਔ໔ਠ҅‫ڹ‬໔਻ྕᆶ‫ڬ‬ᜐ 100m ጄൎࡌጨ౗ӣᘜϩ‫่݋‬ ݀΋ំ߄ ......................................................................................................... 93 ߄ 6.12Ӛঁෳᗺਔ໔ਠ҅‫ڹ‬໔਻ྕᆶ‫ڬ‬ᜐ 100m ጄൎ৒ᑈ౗ӣᘜϩ‫่݋‬ ݀΋ំ߄ ......................................................................................................... 94 ߄ 6.13 Ӛঁෳᗺ਻ྕᆶ‫ڬ‬ᜐ 100m ጄൎΓπ዗ӣᘜϩ‫่݀݋‬΋ំ߄ .... 95. VIII.

(12) ߄ 6.14 Ӛঁෳᗺ਻ྕᆶ‫ڬ‬ᜐ 100m ጄൎࡌԋӢηӣᘜϩ‫݋‬΋ំ߄ ........ 95. IX.

(13) Ѡ᡼ύࠠࠤѱ೿ѱ዗৞ਏᔈϷ࣬ᜢᐒ‫ڋ‬ϐࣴ‫ز‬ -а჏ကѱࣁ‫ٯ‬. ࡰᏤ௲௤Ǻ஭ඁ໦ റγǵ໳ࢋ➌ റγ ୯ҥଯ໢εᏢβЕᆶᕉნπำᏢ‫س‬ ୯ҥ჏ကεᏢඳᢀᏢ‫س‬. ᏢғǺЦ៉Ờ ୯ҥଯ໢εᏢβЕᆶᕉნπำᏢ‫س‬. ᄔा ᒿ๱Γα۳೿ѱ໣ύǵβӦ٬Ҕ೿ѱϯϐуቃǴ೿ѱӦ୔ϐ዗৞ਏᔈ В੻ᝄख़Ǵӧ࣬ᜢࣴ‫ز‬ύࣣς᛾ܴ‫ځ‬ᝄख़‫܄‬ᆶ෧጗ϐѸा‫܄‬ǶฅԶǴว৖ ύϐύࠠࠤѱࢂցҭၟᒿεࠠ೿ѱϐᕉნᡂϯဌ‫؁‬Ǵ‫ځ‬೿ѱ዗ᕉნࢂցς ౢғઇᚯǶਥᏵၸѐ 5 ԃ‫਻ޑ‬ຝၗ਑ว౜Ǵ዗஥ύࠠࠤѱ--჏ကѱǴ‫ྕ਻ځ‬ ΢ϲᖿ༈ό٥‫ܭ‬ଯ໢฻዗஥εࠠࠤѱǴฅԶ‫ځ‬೿ѱ዗৞౜‫ݩ‬ᆶ࣬ᜢቹៜᐒ ‫ڋ‬฻ࣴ‫ز‬ፓࢗόӭǶ ӢԜǴҁࣴ‫ز‬а჏ကѱࣁ‫ٯ‬Ǵፓࢗύࠠࠤѱ೿ѱ዗৞ਏᔈ౜‫ݩ‬Ǵ٠௖૸ ೿ѱࡌԋᕉნӢηჹჹ‫ڬځ‬ᜐ዗ᕉნϐቹៜ‫ݩރ‬Ƕࣴ‫ز‬Ӧ୔а჏ကѱӄ୔ ࣁጄൎǴࣴ‫ز‬Б‫ݤ‬௦Ҕᐒً౽୏ᢀෳ‫ݤ‬Ǵ‫ ܭ‬2018 ԃহ‫ۑ‬ჴӦෳໆ჏ကѱ዗ ৞ਏᔈϐ౜‫ݩ‬Ǵ٠ፓࢗ჏ကѱ‫ޑ‬όӕЁࡋ‫ޑ‬೿ѱࡌԋᕉნӢηǴ‫ٯ‬ӵΓα ஏࡋǵᆘϯ‫ݩރ‬ǵϺ‫ޜ‬ёຎࡋ(SVF)ǵࡌጨ౗ǵ৒ᑈ౗ǵΓπ዗ᆶࡌᑐ഍ቹǴ ຾΋‫؁‬ϩ‫݋‬ቹៜ჏ကѱ዗৞ਏᔈ‫ޜޑ‬໔੝ቻǶ٠ճҔ GIS ঺᠄‫ޜ‬໔ᆶ਻ྕ ፓ่ࢗ݀Ǵ௖૸೿ѱࡌԋᕉნӢηჹ዗৞ਏᔈϐቹៜǴ٠ໆϯϩ‫݋‬Ӛෳᗺ ࡌԋᕉნӢηᆶ਻ྕᡂϯϐ࣬ᜢ‫܄‬Ƕ ่݀ว౜ (1)ӧ዗৞ਏᔈ่݀Бय़Ǻ჏ကѱ዗৞ਏᔈқϺਔࢤ዗ྍ೿ӧ ჏ကОًઠߕ߈ϷҬ೯ᕷԆ‫ޑ‬ၡࢤǴఁ໔ਔࢤ዗ᗺӧҬ೯ᕷԆ‫ޑ‬ཥғၡᆶ ۸ֵၡၡαϷࠟླྀၡ୘཰୔ǵࡕОًઠ୘୮୔฻Ƕᆶ 1999 ԃ‫ޑ‬ፓ่ࢗ݀࣬. 1.

(14) КǴқϺനଯྕቚу߈ 3ʚǴ‫ڹ‬໔നଯྕৡ౦ऊቚу 1ʚǵനեྕऊቚу 2ʚǹ ЪқϺ዗୔ϩѲᘉቚԿ჏ကεᏢ݅හਠ୔ǴёૈচӢࣁ၀୔Γπय़ᑈቚу К‫ ٯ‬90 %а΢೷ԋǴհ୔߾ᘉቚԿчෝၡǶ(2)೿ѱࡌԋᕉნӢηϩ‫่݀݋‬ Бय़Ǻӧ୔ୱЁࡋᆶຉ୔Ёࡋ‫ޑ‬ϩ‫݋‬໨Ҟύว౜ǴΓαஏࡋǵࡌᑐᙟᇂ౗ (ε‫ ܭ‬45 % а΢)ǵ৒ᑈ౗(ε‫ ܭ‬200 % а΢)ǵΓπ዗ၨଯ(ε‫ ܭ‬30 ࿤ (ࡋ ԃ/m2) а΢)ଯ‫ޣ‬໣ύӧОًઠࣁύЈ‫୔ޑ‬ୱϩѲǴ٠Ԗᒟ৔‫ރ‬ӛѦሀ෧‫ޑ‬ ᖿ༈ǶᆘӦБय़ǴคፕӧᆘӦय़ᑈ‫܈‬ᆘᙟ౗΢ᆘӦय़ᑈϷᆘϯᙟᇂ౗ၨե ‫(ޣ‬λ‫ ܭ‬30 %)ࣣϩѲ‫ܭ‬ѱύЈǵ۳Ѧൎ߾Ԗၨଯ‫ޑ‬ᖿ༈ϩѲǶ(3)ӧ዗৞ਏ ᔈᆶࡌԋᕉნӢηϐ࣬ᜢ‫܄‬ϩ‫݋‬Бय़Ǻว౜৒ᑈ౗ǵࡌᑐᙟᇂ౗཮٬ྕࡋ ගϲǴԶϺ‫ޜ‬ёຎࡋ(SVF)ǵᆘϯᙟᇂ౗཮٬ྕࡋफ़ྕǴᆶၸѐࣴ‫ز‬Кၨ࣬ ӕǶ. ᜢᗖӷǺ ዗ᕉნǵຉၰǵ౽୏ᢀෳǵӦ౛ၗૻ‫س‬಍. 2.

(15) A Study on Urban Heat Island Effect and Related Mechanism of Medium-sized Cities in Taiwan - A Case study of Chiayi City Advisor(s): Dr. Heui-Yung Chang Institute of Civil and Environmental Engineering National University of Kaohsiung Dr. Jou-Man Huang Institute of Landscape Architecture National Chiayi University Student:Yu-Shu Wang Institute of Civil and Environmental Engineering National University of Kaohsiung ABSTRACT With the intensification of the urbanization of population and land-use, the heat island effect in urban areas has become increasingly serious, and the necessity of its severity and mitigation has been proved in related research. However, whether developing medium-sized cities follow the changing environment of mega-cities, and the urban thermal environment has been damaged. According to the meteorological data of the past five years, the temperature rise of the tropical medium-sized city, Chiayi City, is no less than that of tropical mega-cities such as Kaohsiung. However, the research of the urban heat island effects or related mechanisms about Chiayi City is few. Therefore, this study took Chiayi City as an example to investigate the status of urban heat island effect in medium-sized cities and discusses the influence of urban building environment factors on the surrounding thermal environment. The study area is the whole district of Chiayi City. The research method used the motive-mobile observation method to measure the situation of the heat island effect in Chiayi City, and investigated the urban building environment factors which affect the heat island effect in Chiayi City, such as population density, greening, sky view factor (SVF), building coverage ratio, floor area ratio, artificial heat, and building-shadow. Nesting space and temperature survey results by GIS are used to explore the influence of the building environment factors on the heat island effect and quantitative analysis of the correlation between. 3.

(16) temperature and spatial factors at points. ResultsǺ(1) In the urban heat island effect, Chiayi City's heat island effect during the daytime, heat source is near the Chiayi train station and busy traffic section. In the evening, the hotspots are in the busy traffic area of Xinsheng Road and Zhongxiao Road intersection, and the commercial area of Chuiyang Road and the business district of back-train-station. Comparing with the results of 1999, during the day-time, the maximum temperature increased by nearly 3ʚ, at night, the maximum temperature increased about 1 ʚ and minimum temperature increased about 2ʚ. During the day-time, the heat-area expended to the Chiayi University campus of Linsen, and the increase more than 90% of the artificial area may be the possible reason.The cold-area expended to Beigang Road. (2) In the building environment factors, the higher of population density, building coverage ratio (greater than 45%), floor area ratio (greater than 200%), and artificial heat (more than 300,000 (years/m2) or more) were concentrated in the area of train station and have a tendency to radiate outwards. Regarding the greening, the lowers of the green area and green coverage rate (less than 30%) were distributed in the central city and the highers were in the outer. (3) In the correlation analysis between the heat island effect and building environmental factors, floor area ratio and building coverage ratio could increase the temperature, while the sky view factor (SVF) and green coverage rate could cause the temperature to cool down the same as the past research.. Keywords:Thermal environmentWind, Street, Impervious, Geographic Information System(GIS).. 4.

(17) ಃ΋കǵᆣፕ! 1.1 ࣴ‫୏ز‬ᐒ! ౜Ϟ‫ޑ‬ғࢲᕉნҗ‫ܭ‬Γᜪჹ‫ܭ‬ᕉნ‫ޑ‬ᅿᅿઇᚯ೷ԋ਻ংᡂᎂ฻ᕉნ ୢᚒǴόፕࢂ਻ྕǵफ़ߘǵ॥ೲ฻ϐᡂϯǴ೿٬ளᕉნ๤፾ࡋΠफ़Ǵቹៜ ҇౲ӧЊѦ‫ޑ‬ғࢲࠔ፦Ǵ٠फ़ե҇౲Ѧр‫ޑ‬ཀᜫǴԶӧ೿ѱӦ୔җ‫ܭ‬዗ ৞ਏᔈϐቹៜǴԜᅿୢᚒ‫׳‬ᖿᝄख़Ƕ ᒿ๱Γα۳೿ѱ໣ύǵβӦ٬Ҕ೿ѱϯϐуቃǴ೿ѱӦ୔ϐ዗৞ਏ ᔈВ੻ᝄख़Ǵӧଯࡋ೿ѱϯϐεࠠࠤѱӵܿ٧ǵεٞǵѠч฻ϐ዗৞౜ ຝǴӧ࣬ᜢࣴ‫ز‬ύࣣς᛾ܴ‫ځ‬ᝄख़‫܄‬ᆶ෧጗ϐѸा‫܄‬ǶฅԶǴว৖ύϐύ ࠠࠤѱࢂցҭၟᒿεࠠ೿ѱϐᕉნᡂϯဌ‫؁‬Ǵ‫ځ‬೿ѱ዗ᕉნࢂցςౢғ ઇᚯǴԶઇᚯำࡋΞԖӭϿǴ‫ځ‬ᐒ‫ڋ‬ᆶ෧጗‫ޑ‬ёૈ‫܄‬ΞࣁՖǴ٬ցԖᐒ཮ ග߻Ⴃٛᆶ‫ׯ‬๓ࢂҁࣴ‫ز‬ట௖૸ϐፐᚒǶਥᏵၸѐ 5 ԃ‫਻ޑ‬ຝၗ਑ว౜ ዗஥ύࠠࠤѱ--჏ကѱǴ‫ྕ਻ځ‬΢ϲᖿ༈ό٥‫ܭ‬ଯ໢฻዗஥εࠠࠤѱǴฅ Զ‫ࣁي‬΋ঁύࠠࠤѱ‫ځ‬೿ѱ዗৞౜‫ݩ‬ᆶ࣬ᜢቹៜᐒ‫ڋ‬฻߈ԃࣴ‫ز‬ፓࢗԖ ჏ကѱ‫ޑ‬೿ѱϦ༜ϩѲᆶύλᏢЊѦ‫ޜ‬໔(໳ࢋ➌Ǵ2014ǹ໳ࢋ➌Ǵ2015) Ϸ໦჏ࠄ೿ѱ዗৞(Җ໡‫ޱ‬Ǵ2011)ᆶѠ᡼ύλࠠ೿ѱ዗৞ਏᔈϐᢀෳှ‫݋‬ (ഋ߷‫׊‬Ǵ2000)Ƕ. 5.

(18) 1.2 ࣴ‫ز‬Ҟ‫ޑ‬ ୯ϣ‫ޑ‬೿ѱ዗৞ਏᔈࣴ‫ز‬Ӣεӭ೿ࢂ௖૸ࣴ‫ز‬εࠠ೿ѱ‫ޑ‬዗৞ਏᔈǴ Զჹύࠠ೿ѱ዗৞౜ຝ‫ࡐࠅزࣴޑ‬ϿǴ‫܌‬аҁࣴ‫ز‬຾Չ჏ကѱ౜Ӧ዗৞ ჴෳБ‫ݤ‬аྕࡋϩѲ௃‫ٰ࣮׎‬р዗৞மࡋǶ ҁࣴ‫ޑز‬Ҟ‫ޑ‬೸ၸᐒً౽୏ᢀෳ‫ڗݤ‬ள჏ကѱ‫ޑ‬዗৞மࡋᆶྕࡋϩ ѲǴ٠Ъ೸ၸࠤѱ࣬ᜢӢηӵΓαǵᆘᙟ౗ǵᆘϯᙟᇂ౗ǵኴଯǵࡌᑐᙟ ᇂ౗฻Ǵᙖҗ዗৞ਏᔈϐ࣬ᜢӢη‫ޑ‬ໆϯϩ‫݋‬Ϸ଑ᘜϩ‫݋‬БԄ௖૸዗৞ ྕࡋϐ࣬ᜢ‫܄‬Ƕ. 1.3 ࣴ‫ز‬Б‫ݤ‬ ࣴ‫ز‬Б‫ݤ‬௦Ҕᐒً౽୏ᢀෳ‫ݤ‬ჴӦෳໆ჏ကѱ዗৞ਏᔈϐ౜‫ݩ‬Ǵ٠ ፓࢗ჏ကѱຉၰ‫ޜ‬໔ಔԋǴ‫ٯ‬ӵຉၰ‫׎‬ԄǵЁκᆶᆘϯ‫ݩރ‬฻Ǵ຾΋‫؁‬ϩ ‫݋‬ቹៜ჏ကѱ዗৞ਏᔈ‫ޑ‬ຉၰ‫ޜ‬໔੝ቻǴ٠ճҔ GIS ঺᠄‫ޜ‬໔ᆶ਻ྕፓ ่ࢗ݀Ǵ௖૸೿ѱຉၰ੝ቻჹ‫ܭ‬዗৞ਏᔈϐቹៜǶ. 6.

(19) 1.4 ࣴ‫ࢎز‬ᄬ !. ࣴ‫୏ز‬ᐒᆶҞ‫ޑ‬. ! Ў᝘ӣ៝ ! ࣴ‫ز‬Б‫ݤ‬. ! !. ೿ѱࡌԋᕉნӢηፓࢗीฝ!. ౽୏ᢀෳჴෳीฝᔕ‫!ۓ‬. ! ! εЁࡋ! !. 2/Γα! ! 3/ᆘᙟ౗! !HJT ঺᠄ϩ‫!݋‬. ౜Ӧჴෳ຾Չ!. λЁࡋ!. ኧᏵ᏾౛! 2/ຉၰᆘϯໆ)෌ਭǵҖ Ӧ*! 3/ኴଯ)഍ቹǵΓα)Γ π዗**! 4/TWG)഍ቹ*!. ኧᏵਠ҅!. ჴ ෳ Ϸ ࣬ ᜢ Ӣ η ϩ ‫݋‬. ྕࡋ‫ޜ‬໔ϩթϩ. ! ! !. ዗৞ਏᔈᆶࡌԋᕉნ࣬ᜢӢη ϩ‫!݋‬. ! !. ่ፕ!. ! !. 7. ่ ݀ ᆶ ่ ፕ.

(20) ಃΒകǵЎ᝘ӣ៝! 2.1 ೿ѱ዗৞ਏᔈ ዗৞ਏᔈςࢂ೿ѱύ࣬྽දၹ‫ޑ‬౜ຝǶനӃว౜዗৞౜ຝ‫ࢂޑ‬म୯ Ꮲ‫ ޣ‬Luke HowardǴдӧ 1833 ԃр‫ހ‬ϐȨউඩ਻ং ȐThe climate of Londonȑȩ΋ਜջග‫ډ‬Ǵ೿ѱϯ೷ԋ೿ѱྕࡋଯ‫୔॓ܭ‬ȐHoward , 1833ȑ Ƕ ೭ঁ౜ຝ೏ගрࡕǴᒿջԋࣁࣴ‫ز‬ᆶ૸ፕ‫ޑ‬ขᗺǶԿ‫ܭ‬Ȩ೿ѱ዗৞ȩ (Urban Heat Island) ΋ຒǴ߾ࢂᏢ‫ ޣ‬Gordon Manley ӧ 1958 ԃ‫ܭ‬म୯ࣤ ৎ਻ຝᏢ཮р‫ހ‬ϐᏢൔǴ२ԛගр٠‫ۓ‬ကࣁ೿ѱၨໂ‫׸‬Ӧ୔ଯྕϯϐ౜ ຝ (໳฻Ǵ2014)Ƕ ೿ѱ዗৞ਏᔈ‫ޑ‬ᝄख़ำࡋǴ೯தаࠤ॓ϐ໔‫ࡋྕޑ‬ৡ౦നεॶ ȐᶭTu-rȑբࣁຑ՗Ȩ೿ѱ዗৞மࡋ (Urban Heat Island IntensityǴUHIs) ȩ ‫ޑ‬኱ྗǴԶৡॶຫεջж߄೿ѱ࣬ၨ‫ڀ୔॓ܭ‬Ԗຫଯ‫( ࡋྕޑ‬Oke,1988)Ƕ ೿ѱ‫୔॓ک‬നεྕࡋৡ౦ࢂߚதܴᡉЪόೕ߾‫ޑ‬Ƕӧค॥‫ݩރޑ‬ΠǴ‫ڹ‬ ఁ೿ѱ‫ޑ‬༾॥ёаफ़ե዗৞‫ޑ‬ቹៜय़ᑈǹ໩॥‫ޑ‬௃‫ݩ‬ΠǴ॥཮஥๱ྕཪ ‫ޑ‬॥வ೿ѱύЈ۳॓୔ᘉණǶ዗਻ࣗԿёаᘉ৖‫ډ‬ၭ‫׸‬Ӧ୔Ƕ೿ѱϣ೽ ਻იൻᕉ‫ޔࠟޑ‬ຯᚆӧఁ΢೯தѝԖ 2~3 ቫ‫ࡌޑ‬ᑐ‫ޑނ‬ଯࡋǴԶқϺࠅ ёа‫ډ‬ၲ 1 मধǴӢԜ೿ѱ዗৞ቹៜε਻ЬाวғӧқϺ (Duckworth and Sandberg, 1954)Ƕ. 8.

(21) 2.2 ୯ϣѦ೿ѱ዗৞ਏᔈ౜‫ݩ‬ 2.2.1 ୯Ѧ዗৞ࣴ‫ز‬౜‫ݩ‬ ୯ѦමԖࣴ‫ز‬ଞჹ዗஥Ӧ୔ǴаՅӈ੝܎ᆢϻ೿ѱࣁჹຝǴፓࢗᆶ ϩ‫ځ݋‬Ӛঁ‫ۓڰ‬ෳᗺϐ‫؂‬ВനଯྕǵനեྕϷৡຯ (Saaroni, 2000)Ƕ่݀ ว౜ǴқϺੇᜐКѱύЈ‫׳‬հǴԶఁ΢ੇᜐКϣࠤ‫׳‬ཪǴΨ൩ࢂੇᜐࠤѱ ϐѱύЈКᜐጔӦ୔ᗋा዗ (Saaroni, 2000)ǶࡕុԖࣴ‫ز‬ଞჹ዗஥؅ᅃ਻ ং‫ߓޑ‬ᅟϷճ٥‫ޑ‬ᇂᅟၲओ࣪Ǵ௖૸೿ѱຉ‫ޑك‬ଯቨКǵ০ӛǵߚჹᆀǵ ൴ၰǵँрҥय़‫ک‬෌೏Ǵჹ‫ݹ‬዗ଳᔿ਻ং‫࠻ޑ‬Ѧ዗๤፾ϐቹៜ (AliToudert and Mayer, 2006; Ali-Toudert and Mayer, 2007)Ƕ่݀ว౜Ǵӧ΋Ϻ ύวғཱུᆄ዗ᓸΚ‫ޑ‬ਔ໔ᗺ‫ک‬ਔ໔ߏอǴᆶຉၰଯቨК‫ک‬০ӛ࣬ᜢ‫ࡐ܄‬ εǴЪᒿ๱ຉၰଯቨК‫ޑ‬ቚуǴ਻ྕ཮ᇸ༾Ӧ෧ϿǶќѦǴຫεϺ‫ޜ‬໒‫ܫ‬ ‫ޑ܄‬ຉ‫ك‬Ǵ཮೷ԋ‫׳‬ଯ‫ޑ‬዗ᔈΚǴԶ৙‫ك‬዗௃‫཮ݩ‬ᒿ๱΋ঁၨλ‫ޑ‬Ϻ‫ޜ‬ ຎഁԶ‫ׯ‬๓ǴՠΨҗຉၰ০ӛ،‫ۓ‬Ǵ‫܌‬аܿՋӛ৙‫ࢂك‬ന‫ݹ‬዗Ъค‫ݤ‬ӧ ೭ঁ০ӛ‫ׯ‬๓዗௃‫ݩ‬Ƕ. 2.2.2 ୯ϣ዗৞ࣴ‫ز‬౜‫ݩ‬ ୯ϣӧ 2000 ԃ߻ࡕ໒‫ۈ‬Ԗεໆࣴ‫ز‬ଞჹѠ᡼೿ѱ዗৞ਏᔈ຾Չፓࢗ ϩ‫݋‬Ƕ‫ٯ‬ӵǴԐයԖࣴ‫ز‬ଞჹѠчǵѠύǵѠࠄᆶଯ໢Ѥε೿཮୔Ǵ຾Չ ዗৞ਏᔈፓࢗ (‫׵‬ሱ᜻, 1999)Ƕ่݀ว౜ǴѠ᡼೿཮୔ϐ዗৞౜ຝ཮Ӣᗥ ೿ѱ‫ޑ‬Ӧ౛ᆶΓЎచҹόӕԶԖόӕϐ੝ቻǶමԖࣴ‫ز‬ଞჹѠࠄӦ୔Μ ϖঁໂᙼѱǴ຾Չًؓ౽୏ᢀෳϐ೿ѱ዗৞Кჹϩ‫(݋‬৊ਁက, 2003)Ƕ่ ݀ว౜Ǵж߄೿ѱೕኳϐΓαჹኧǴаϷ೿ѱ໒วำࡋ‫ޑ‬Γαஏࡋᆶߚ. 9.

(22) ၭ཰ΓαК‫ٯ‬฻ӢનǴᆶ೿ѱ዗৞மࡋԖᡉ๱‫࣬ޑ‬ᜢ‫܄‬Ƕࡕុࣴ‫ز‬௖૸ ѠࠄӦ୔೿ѱΓαೕኳᆶ೿ѱ዗৞ਏᔈ໔ϐᜢ߯Ǵа౽୏ᢀෳ‫ݤ‬຾Չ΋ ԃ‫ޑ‬ໆෳှ‫݋‬Ǵ٠ᆶ୯ϣѦ‫ځ‬дЎ᝘ࣴ‫ز‬ኧᏵ຾ՉКၨ (݅Ꮶቺ฻, 2005)Ƕ ่݀ว౜Ǵҗ‫ܭ‬ଯᔸࡋᆶեΓπวණ዗ϐ੝‫܄‬ǴѠ᡼ϐ೿ѱ዗৞மࡋܴ ᡉե‫ځܭ‬дྕ஥Ӧ୔‫ޑ‬୯ৎǴԶᆶВҁλࠠ೿ѱᖿ༈࣬߈ǶќѦǴऩஒ೿ ѱीฝΓα೛‫ۓ‬λ‫ ܭ‬10 ࿤ΓǴஒёаԖਏफ़եၸε‫ޑ‬೿ѱ዗৞ਏᔈǶ Ԗࣴ‫ز‬჋၂᏾ӝჴෳኧᏵᆶ਻ং౛ፕǴΨ൩ࢂஒჴෳኧᏵᆶ୷ᘵၗ ਑຾ՉКჹϩ‫݋‬Ǵ௖૸ቹៜ೿ѱ዗৞ϐᜢᗖाન (৊‫݅ک‬฻, 2006) Ƕϩ ‫่݀݋‬ᡉҢǴ਻ྕե‫ޑ‬ϺংచҹΠ೿ѱ዗৞ਏᔈ཮‫׳‬ᡉ๱ǴӢԜࣿ‫܌ۑ‬ ෳளϐനε዗৞மࡋ (ᶭTu-r) ࣁ 3.79ʚǴၨহ‫ۑ‬ෳளϐനε዗৞மࡋ (ᶭTu-r) 2.85ʚଯр೚ӭǴԶӚ‫ۑ‬࿯ѳ֡೿ѱ዗৞மࡋ (ᶭTu-r) ҭаࣿ‫ۑ‬ 2.22ʚനଯǴ‫ځ‬ԛࣁо‫ ۑ‬2.13ʚǵࡾ‫ ۑ‬2.01ʚᆶহ‫ ۑ‬1.47ʚǶќѦǴΓα ኧե‫ܭ‬Ο࿤ΓЪѳ֡Γαஏࡋե‫ᙼࠤޑ‬Ǵ཮ౢғᡉ๱‫ޑ‬೿ѱ዗৞மࡋǶ ΢ॊࣴ‫ز‬೸ၸ SPSS ಍ी೬ᡏ຾Չፄӣᘜϩ‫่݀݋‬ǴаΓαჹኧǵ਻ྕǵ ၭ཰ҔӦК‫ٯ‬ǵߚၭ཰ΓαК‫ࣁٯ‬ႣෳᡂኧǴӅளȨᙁൂԄȩϷȨᆒಒԄȩ ΒԄǴග‫ٮ‬҂ٰႣෳୖԵϐҔǶ ୯ϣԖࣴ‫ز‬ਥᏵኳᔕϩ‫݋‬Ǵ௖૸ຉၰόӕ‫ޑ‬ᎎय़‫׷‬፦ᆶᆘӦ೛࿼‫ޑ‬ ᡂϯǴ‫׎܌‬ԋϐ॥൑੝‫܄‬Ϸྕࡋ‫਻ޜک‬ύ዗֖ໆᡂϯ௃‫ࠔ݅) ݩ‬ሺ, 2010*Ƕ่݀ว౜Ǵᅿ෌෌ਭჹ‫ܭ‬೿ѱफ़ྕ‫ڀ‬Ԗᡉ๱‫ޑ‬ቹៜǴӢࣁ෌ਭ‫ޑ‬ ᇃණբҔёа጗ှ೿ѱଯྕ౜ຝǶќѦԖࣴ‫ز‬а೿ѱЁࡋ௖૸೿ѱβӦ ٬Ҕჹ೿ѱ਻ྕϐቹៜ (݅ᝊ‫ذ‬, 2010) Ƕ่݀ࡰрǴβӦ٬Ҕϩ୔य़ᑈ КᆶѱύЈ਻ྕ࣬ᜢǴԶ྽೿ѱϐߚ೿ѱว৖୔य़ᑈК‫ٯ‬ཇଯǴ߾ѱύ Ј਻ྕཇեǴࡺၭ཰ҔӦКཇεǴѱύЈ਻ྕΨཇեǶКၨന߈ΨԖࣴ‫ز‬. 10.

(23) аᆵчѱࣁ‫ٯ‬Ǵଞჹ‫ځ‬೿ѱ዗৞மࡋᆶЬा࣬ᜢӢη (Γαஏࡋǵࡌጨ౗ǵ ᆘᙟ౗) Ǵ຾Չໆϯϩ‫( ݋‬ᙁη๔, 2013) Ƕ࿶ጕ‫܄‬ӣᘜკ‫׎‬Ϸ࣬ᜢ߯ኧ ள‫ډ‬ӑ᛾Ǵ೿ѱ዗৞மࡋዴᆶΓαஏࡋϷࡌጨ౗և҅࣬ᜢǴԶᆶᆘᙟ౗ ևॄ࣬ᜢǶ. 2.3 ೿ѱ዗৞மࡋࡰ኱ ӵ߄ 2.1Ǵ዗৞ਏᔈቹៜӢηёаϩԋǴ(1) ԾฅᕉნᡂϯǴ(2) ೿ѱ Γࣁ዗ྍǴ(3) ೿ѱ߄य़‫׷‬਑੝‫܄‬Ǵᆶ (4) ೿ѱ෌ਭᆶНᡏǴӅ 4 εᜪǶ Ծฅᕉნᡂϯ߯ࡰ༾਻ংǴхࡴǴВ৔ໆǵྕࡋǵ॥ೲǵ॥ӛǵफ़ߘǵᔸ ࡋǵ໦ໆǵ‫਻ޜ‬షᐜࡋ฻Ƕ೿ѱΓࣁ዗ྍ߾ᆶ೿ѱೕኳᆶΓαǵኴӦ݈ஏ ࡋǵࡌጨ౗ǵ৒ᑈ౗ǵຉၰቨࡋᆶࡌᑐ‫ނ‬ଯࡋ฻Ԗᜢ฻೿ѱ߄य़‫׷‬਑੝‫܄‬ хࡴǴϸ৔౗ǵϸྣ౗ǵ዗໺Ꮴ౗ǵ዗໺೸౗ᆶհࠅ౗฻Ƕ೿ѱ෌ਭᆶН ᡏ߾ቹៜ‫ځ‬ᆘᙟ౗ᆶᇃණ౗Ƕ. Ծฅᕉნᡂϯ ೿ѱΓࣁ዗ྍ ೿ѱ߄य़‫׷‬਑੝‫܄‬ ೿ѱ෌ਭᆶНᡏ. ߄ 2.1ġ ዗৞ਏᔈቹៜӢη ዗৞ਏᔈቹៜӢη ༾਻ং(В৔ໆǵྕࡋǵ॥ೲǵ॥ӛǵफ़ߘǵᔸࡋǵ ໦ໆǵ‫਻ޜ‬షᐜࡋ฻) ೿ѱೕኳᆶΓα ኴӦ݈ஏࡋ ࡌጨ౗ǵ৒ᑈ౗ǵຉၰቨࡋᆶࡌᑐ‫ނ‬ଯࡋ ϸ৔౗ǵϸྣ౗ǵ዗໺Ꮴ౗ǵ዗໺೸౗ǵհࠅ౗ ᆘᙟ౗ǵᇃණ౗. ӵ߄ 2.2ǴΓαೕኳǵຉၰߏቨКǵϺ‫ޜ‬ຎ౗‫ک‬዗๤፾ࡋ฻ࡰ኱Ǵ೏. 11.

(24) ຾΋‫؁‬Ҕ‫ܭ‬ຑ՗዗৞ᝄख़ำࡋ (Givon and Baruch, 1998)Ƕ ߄ 2.2ġ ዗৞ᝄख़ำࡋຑ՗Б‫(ݤ‬GivonBaruch,1998) Ӣη ϦԄ ᇥܴ dT=዗৞மࡋ(C)ǹP=Γαೕኳǹ Γαೕኳ! dT=P1/4 /(4U)1/2 U=Ӧ୔॥ೲ(m/s) ຉၰߏቨК! ϦԄύ:H=ࡌՐଯࡋǹW=ࡌᑐ dTmax=7.45+3.971n(H/W) ໔ຯ Ϻ‫ޜ‬ຎ౗(SVF)2 Ǵჹ‫ܭ‬ຎ᝺ค ߔᛖНѳӦ୔Ǵ‫ ځ‬SVF ॶࣁ Ϻ‫ޜ‬ຎ౗! dTmax=15.27-13.88 SVF 1ǹ‫ڬ‬ᜐଯቫࡌᑐஏ໣Ӧ୔Ǵ‫ځ‬ SVF ёૈࣁ 0.1Ƕ ໨Ҟ! ΋૓ ๤፾ ό፾ 0~0.3 m/s 0.3m/s~2.1m/s >5 m/s ՉΓ॥ೲ! ዗๤፾ࡋ 23.0ɴ33.1ʚ )TFU*!. 2.4 ౽୏ᢀෳ‫ݤ‬੝‫܄‬ ୯ϣԋфεᏢ݅Ꮶቺ௲௤வ 1997 ԃ໒‫ۈ‬а౽୏ᢀෳБԄ຾Չ΋‫س‬ӈ ‫ޑ‬೿ѱ዗৞ϐ௖૸Ǵࡕុࣴ‫ز‬຾΋‫؁‬ၮҔᇿෳ‫ܭೌמ‬೿ѱ዗৞ਏᔈࣴ‫ز‬Ǵ ٠ᆶ౽୏ᢀෳ‫ݤ‬຾ՉКၨ (৊ਁက, 2008)Ƕӵ߄ 2.3Ǵ౽୏ෳໆ‫ࢂݤ‬ճҔ ࢎ೛‫ؓܭ‬ᐒً΢‫ࡋྕޑ‬གෳᏔǴՉᎭ‫ܭ‬ଭၡ΢а຾ՉᢀෳǴࡺ‫ڀ‬Ԗᐒ୏ ‫܄‬ଯǵπբᕉნ๤፾ǵࢗਔ໔ϷӦᗺ‫ޑ‬Ծҗ灏ଯ‫ޑ‬ᓬᗺǶӵ߄ 2.4Ǵ౽୏ ෳໆ‫ݤ‬ϐલᗺࢂό‫ڀ‬ӕ‫܄؁‬ᆶܰ‫ڙ‬Ҭ೯ߔ༞‫܌‬ቹៜǶࡺ౽୏ᢀෳ‫ݤ‬ऩૈ ᕭอᢀෳਔ໔Ǵ٠຾Չਔ໔ӕ‫؁‬ϯਠ҅ᆶ኱ྗϯǴ߾ёள‫ࣁ׳ډ‬ᆒዴ‫ޑ‬ ่݀Ƕ ߄ 2.3ġ ౽୏ᢀෳБ‫ݤ‬ϐᓬલᗺᆶᔈҔጄൎ(৊ਁက, 2008) Б‫ݤ‬. ᓬᗺ. લᗺ. 12. ᔈҔጄൎ.

(25) 1. ё ‫ ޔ‬ௗ ‫ ڗ‬ள ‫ྕ ਻ ޜ‬ ࡋၗ਑Ƕ 2. ࣁय़‫ރ‬ၗ਑Ǵёᛤᇙ ྕࡋϩթკǶ 3. ё ᒿ ࣴ ‫ ز‬Ҟ ‫ ޑ‬ፓ ᏾ ౽୏ᢀෳ‫ݤ‬ ෳᗺ໔ຯǴаගଯໆ ෳှ‫ࡋ݋‬Ƕ 4. ค໪೛࿼‫ۓڰ‬း࿼Ǵ ၨ࿶ᔮǶ 5. ၨ ૈ ‫ ڗ‬ள ୔ ୱ ϣ ന ଯྕǵեྕኧᏵǶ. 1. ค ‫ ݤ‬Ծ ୏ ߏ ਔ ໔ ᢀ ෳǶ 2. ό‫ڀ‬ӕ‫܄؁‬Ǵሡ຾Չ ਔ໔ਠ҅Ƕ 3. ‫ ܌‬ᛤ ᇙ ϐ ྕ ࡋ ϩ թ კሡϣѦකीᆉǴҭ ཮़ғᇤৡٰྍǶ 4. ‫ ڙ‬ज़ ‫ ܭ‬ሺ Ꮤ ᆶ Ҭ ೯ π‫ڀ‬Ǵ໻ૈࢎ೛Ͽኧ ሺᏔǶ. ύλЁࡋ ዗ᕉნᆒ ஏჴෳ. ߄ 2.4ġ ෳ౽୏ᢀෳБ‫ݤ‬ϐ໨Ҟ(৊ਁက, 2008) ໨Ҟ ໆෳԾ୏ϯ Ϻংቹៜ ΓΚሡ‫؃‬. ‫ޜ‬໔ှ‫ࡋ݋‬. ᐕўӣྉ‫܄‬. ౽୏ᢀෳ‫ݤ‬ Ծ୏ϯำࡋեǶሡһ ᒘΓΚ຾ՉǶ ຎϺং‫ݩރ‬،‫ࢂۓ‬ ց຾ՉໆෳǶ ΓΚሡ‫؃‬ໆଯǶ‫؂‬ԛ ჴෳ֡ሡा୏঩ε ໆΓΚǶ ౽୏ᢀෳ‫ޜݤ‬໔ှ ‫ࡋ݋‬٩Ᏽࣴ‫ز‬Ҟ‫ޑ‬ ‫ۓु܌‬ϐෳᗺ໔ຯ Զ‫ۓ‬Ǵှ‫ߚࡋ݋‬தᆒ ஏǶ Ԗ຾Չჴෳ ω ཮ Ԗၗ਑ǴӢԜό‫ڀ‬ᐕ ўၗ਑ӣྉ‫܄‬Ƕ. ໨Ҟ ၗ਑ӕ‫؁‬. ၗ਑ό‫ڀ‬ӕ‫܄؁‬Ƕ. ၗ਑ೀ౛. ၗ਑ሡ຾Չਔ໔ਠ҅Ƕ. ᇻᆄໆෳ. ค‫ݤ‬ᇻᆄໆෳǶ. ਔ໔ှ‫ࡋ݋‬. ‫܄ೌמ‬. ߃යሺᏔ೛ ࿼ԋҁ. ໻ሡाҬ೯π‫ڀ‬ચ ॷϷሺᏔ຤ҔǴࡺሺ Ꮤ೛࿼ԋҁၨեǶ. ၮҔቫय़. ࡕයሺᏔᆢ ៈԋҁ. ໻ሡ‫ۓ‬යᆢ ៈ ᔠ ෳሺᏔǴࡺࡕයሺᏔ ᆢៈԋҁၨեǶ. ёҔ‫ܭ‬዗৞ ਏᔈࣴ‫ز‬ϐ ၗ਑ᅿᜪ. 13. ౽୏ᢀෳ‫ݤ‬. ٩Ᏽෳໆᓎ౗Զ‫ۓ‬Ǵӧ ӕ΋Ϻё຾Չኧԛჴ ෳǴёၲȨλਔȩભਔ ໔ှ‫ࡋ݋‬Ƕ ኧᏵ೸ၸ‫ޔ‬ௗໆෳ‫ڗ‬ ளǴ໻ӧਔ໔ਠ҅΢ሡ ाե‫ޑ܄ೌמ‬ၮҔǶ ёၮҔ‫ܭ‬ύ฻Ёࡋཷࡴ ‫܄‬ໆෳǴё‫ڗ‬ளय़‫ރ‬ၗ ਑(х֖Ǻ਻ྕǵᔸࡋǵ ॥ೲ฻)Ƕ ᗨ‫ڙ‬ज़‫ܭ‬ሺᏔࢎ೛‫ܭ‬Ҭ ೯π‫ޜڀ‬໔ୢᚒǴՠϝ ё‫ڗ‬ளኧᅿჴෳୖኧǶ.

(26) 2.5 ࠤѱ‫ޜ‬໔ჹ዗৞ᜢ߯ 2.5.1 ዗৞ᆶ೿ѱೕኳᆶΓαᜢ߯ ୯ϣࣴ‫ࡰز‬рǴऩஒ೿ѱीฝΓα೛‫ۓ‬λ‫ ܭ‬10 ࿤ΓǴஒёаԖਏफ़ եၸε‫ޑ‬೿ѱ዗৞ਏᔈǴ٠Ԗਏ࿯ऊ೿ѱ‫ޜ‬ፓ‫س‬಍઻ႝໆǴаၲ‫ډ‬फ़ե ೿ѱ઻ૈ‫ޑ‬Ҟ኱ (݅฻, 2005)ǶќѦԖࣴ‫ز‬ᡉҢǴѠ᡼Ѥε೿ѱᆶШࣚ೿ ѱ΋ኬǴ‫ڀ‬Ԗ዗৞மࡋᆶΓαჹኧॶևጕ‫࣬҅܄‬ᜢ‫܄ޑ‬፦Ǵՠᆶၨଯጎ ࡋӦ୔КၨǴ࣬ӕΓαచҹΠǴѠ᡼೿ѱ዗৞மࡋၨλǴ‫ځ‬ёૈচӢࢂѠ ᡼ឦੇ৞ࠠ٥዗஥਻ংǴѤຼᕉੇǴ‫ڀ‬Ԗ࣬྽ᛙ‫ۓ‬ϐ਻ྕǵᔸࡋଯ (‫׵‬ሱ ᜻, 1999)Ƕ Ԗࣴ‫ز‬ճҔᐒً౽୏ᢀෳ‫ݤ‬Ϸ‫؁‬ՉБԄǴଞჹѠࠄѱύξϦ༜ᆘ஥ аϷϾቴЎϯ༜୔ϐϦ༜຾ՉፓࢗǴ่݀ᡉҢᆘᙟ౗ᆶྕࡋևॄ࣬ᜢǴ ԶኴӦ݈ஏࡋǵΓαஏࡋǵᎎय़ஏࡋ߾և҅࣬ᜢǴՠϺ‫ޜ‬ຎ౗ (SVF)ǵຉ ၰଯቨКჹ‫ࡋྕܭ‬คᡉ๱࣬ᜢቹៜȐ೾࢙ᠯ, 2000ȑǶ. 2.5.2 ዗৞ᆶβӦճҔᜢ߯ ೿ѱ‫ޜ‬໔‫ނ‬౛่ᄬϐβӦճҔࠠᄊǴჹֽӦ਻ং! (local climate) ᕉ ნ‫ڀ‬Ԗख़ाϐቹៜǶаѠчٰᇥǴӢ‫਻ځ‬ংࣁহ‫ۑ‬ଯྕǵо‫ۑ‬ӭமܿ॥Ǵ ЪࠤѱԖၨଯ‫ࡋྕޑ‬ᆶၨե‫ޑ‬ᔸࡋǴ॥ೲКѠчᑜᗋଯ΋٤Ǵࡺҗ೿ѱ ϣෳઠ໔‫ޑ‬Кၨว౜Ǵ‫ځ‬В໔‫ࡋྕޑ‬ᡂϯനӭǴԶ॥ೲΨܴᡉӦ‫ڬډڙ‬ ൎࡌᑐஏࡋ‫ޑ‬ቹៜ!(໳ࢋ➌, 1999)ǶаѠࠄٰᇥǴ๓Ҕ೿ѱύ॥ǵНǵᆘ Ӧ฻‫ޜ‬໔Ǵ຾Չ፾྽Ӧଛ࿼ᆶ೛ीჹ೿ѱफ़ྕਏཱུ݀‫ڀ‬ወΚǴ٠Ъаβ Ӧ٬Ҕ‫ࡌ܈‬ᑐ‫ޑނ‬ᆅ‫ڋ‬Ћ‫ݤ‬ബ೷೯॥α‫܈‬൴ၰǴӕਔፓ᏾೿ѱύНᡏᆶ. 14.

(27) ᆘӦϩѲаᆢ࡭ੇ॥‫ޑ‬థ౏ࡋǴஒёԖਏ෧጗೿ѱ዗৞ਏᔈ! (໳ࢋ➌, 2014)Ƕ! аΠଞჹβӦճҔǴхࡴǺ෌ਭ೏ᙟǴНᡏ೏ᙟǴᆶΓπᎎय़Ǵᇥܴ ೭٤Ӣηჹ዗৞ਏᔈϐቹៜǺ (1) ෌ਭ೏ᙟ ᆘӦ (෌ਭ) ჹᕉნ‫ޑ‬फ़ྕਏ݀ǴЬाٰԾ෌‫ނ‬ယय़ᇃණϷҁ‫ي‬፿ጨ ฻ᐒ‫܌ڋ‬ౢғ‫ޑ‬ਏᔈǶᇃණբҔӵӕН‫ޑ‬ᇃวǴ෌‫ނ‬೸ၸ਻Ͼ໒ഈᡣН ਻аወ዗ (latent heat) ‫ޑ‬БԄණѨ஥‫و‬዗ૈǶԶ፿ጨբҔЬाҗ‫ܭ‬ယय़֎ ԏǵϸ৔ϼ໚ᒟ৔Ǵ٬‫ځ‬ΠϐӦ߄य़‫ྣڙ‬৔෧ϿԶԖၨե‫߄ޑ‬य़ྕࡋǴӕ ਔҭ٬ள‫ځ‬΢ϐ਻ྕӢԜԶफ़ե (໳ࢋ➌ᆶε‫۝‬ᓪΟǴ2011)ǶਥᏵΓπ ⬏य़ᆶᆘӦ (૛Ӧ) ϐহ‫ۑ‬В໔߄य़ྕࡋࣴ‫ࡰز‬рǴ࢙‫⬏ݨ‬य़ϐӦ߄ྕࡋ ёଯၲ 50-60ʚǴԶᆘӦऊ߾ӧ 33-36ʚѰѓǴ‫ځ‬ЬाӢનջࣁ෌ਭ೸ၸ Нϩᇃණफ़եယय़਻ྕ (Lin et al., 2007ǹKloka et al., 2012ǹMathew et al., 2018)Ƕ ፿ጬբҔБय़෌‫ނ‬ё֎ԏ‫܈‬ϸ৔ϼ໚ᒟ৔Ǵ෧Ͽอ‫ݢ‬ᒟ৔዗(Bradley, 1995)Ƕ྽ϼ໚ᒟ৔ྣ৔ԿယТਔǴ཮‫ډڙ‬ယТϐ፿ᏲԶሀ෧Ǵ٬ᐋ߷ϣ ೽‫ޑ‬Ӏ೸৔ໆᇻλ‫ځܭ‬Ѧ೽ǴЪ೸ၸൂ‫ݍ‬ယТ‫ޑ‬В৔ໆǴҭ཮ᒿ๱ယ፦ όӕԶԖ‫܌‬ৡ౦Ǵऊӧ 10%~30%Ѱѓϐጄൎ(MarshǴ1997)ǹӵ݀೚ӭယ Тख़᠄Ǵ߾೸ၸ‫ޑ‬В৔ໆ൩‫ี׳‬Ͽ(Smardon, 1988)ǶԜѦǴΨԖ೽ϩᒟ৔ ཮வယሜύऀၸ‫ޔ‬৔ԿᐋΠǹऩଷ೛݅Ѧ‫ޑ‬В৔ໆࢂ 100Ǵ߾݅ϣ‫࣬ޑ‬ ჹВ৔ໆ཮٩ᐋЕஏࡋԶ‫ۓ‬Ǵ΋૓ஏࡋ‫ޑ‬ᐋ݅হ‫࣬ۑ‬ჹВ৔ໆࣁ 10~50 (໳ࢋ➌฻Γ, 2011ǹSimpson, 2002)Ƕ Ӣ ࣁ Ӧ ߄ ྕ ࡋ ᆶ த ᄊ ϯ ৡ ౦ ෌ ғ ࡰ ኱ (normalized difference. 15.

(28) vegetation index, NDVI) և౜ॄ࣬ᜢǴࡺ፾྽ቚу೿ѱᆘϯԖշ‫ܭ‬फ़եӦ ߄ྕࡋǴ຾Զ෧጗೿ѱ዗৞ਏᔈ (৊ਁက฻,2010)Ƕ ୯ϣၸѐࣴ‫ز‬ଞჹѠ᡼Ѥε೿཮୔೿ѱ዗৞຾ՉፓࢗǴว౜Ӧ౛ᕉ ნόӕǴё٬Ӛ೿཮୔‫ڀ‬όӕ‫ޑ‬೿ѱ዗৞੝ቻ (‫׵‬ሱ᜻,1999)Ƕ‫ٯ‬ӵǴѠ чѱЬा‫ډڙ‬εय़ᑈǵଯஏࡋ‫ޑ‬୘཰ࢲ୏‫܌‬ቹៜǴ‫ځ‬೿ѱ዗৞ࠠᄊόႽ Ѡύٗኬ໣ύᆶܴᡉǶќ΋Бय़Ǵ‫؂‬ቚу೿ѱᕉნύ 10 ʝ‫ޑ‬ᆘᙟ౗Ǵ‫ڬ‬ ൎѳ֡਻ྕёफ़ե 0.13~0.28 ʚǹ࣬ჹӦǴ‫؂‬ගଯ 10 ʝ‫ࡌޑ‬ጨ౗Ǵ਻ྕ ऊ΢ܹ 0.14~0.46 ʚǹӕኬӦǴ‫؂‬ගଯ 10 ʝ‫ޑ‬৒ᑈ౗Ǵ਻ྕऊ΢ܹ 0.04~0.10 ʚǶ Ԗࣴ‫ࡰز‬рǴӧВ໔Ǵ෌ਭᆘϯёᛙ‫ۓ‬फ़եෳᗺ‫ڬ‬ൎ‫ྕ਻ޑ‬Ǵऊ 0.6~2.6 ʚǴԶӧ‫ڹ‬໔Ǵ҂٬ҔβӦࠠᄊǵ෌ਭᆘϯࠠᄊϷНୱࠠᄊ೿Ԗ շ‫ܭ‬հࠅෳᗺ‫ڬ‬ൎ‫( ྕ਻ޑ‬ᎄܴϘ,2012)ǶќѦǴଞჹѠࠄѱ೿ѱϦ༜༾ ਻ং຾Չᢀෳှ‫݋‬Ǵ่݀ᡉҢόӕᅿᜪ‫ޑ‬ᎎय़‫׷‬਑ჹ‫ڬ‬ൎ዗ᕉნԖόӕ ำࡋ‫ޑ‬ቹៜ (೾࢙ᠯ, 2000)Ƕ‫؂‬ቚуֽӦ‫ޜ‬໔‫ ޑ‬10%ᆘᙟ౗Ǵёफ़ե၀୔ ୱহ‫ڹۑ‬ఁ 0.17~0.22 ʚ‫ࡋྕޑ‬ǴӧϦ༜Ѥ‫ܴڬ‬ᡉ‫ޑ‬եྕጄൎϣ(ऊ 150 ϦЁѰѓǴኴӦ݈ஏࡋ 1.0~2.0km2/km2 ‫୔ޑ‬ୱ)Ǵহ‫ۑ‬ਔǴ‫ૈځ‬ၲ‫ ډ‬0.2~0.6 ʚ‫ޑ‬फ़ྕਏ݀Ƕ. (2) Нᡏ೏ᙟ Нୱ཮ӢਔࢤϷೕኳόӕԶԖόӕբҔ (݅Ꮶቺ฻,2001) ǶНᡏफ़ ե዗৞ਏᔈ‫ޑ‬ᐒ‫ڋ‬ЬाٰԾ‫ܭ‬Нϩ‫ޑ‬ᇃวբҔᆶၨε‫ޑ‬዗৒ໆǶНϩҗ నᄊᡂԋ਻ᄊǴ೸ၸወ዗ (latent heat) ᇃว‫ ؂‬1 լНё஥‫ و‬540 cal ዗ ໆǶӕਔǴНᡏ࣬ၨ‫ځܭ‬д೿ѱத‫߄ـ‬य़‫׷‬፦‫ڀ‬Ԗၨε‫ޑ‬዗৒ໆ. 16.

(29) (Oke,1987)ǴӢԜ࣬ၨ‫ܭ‬΋૓βᝆ‫ޜ‬ӦϷ࢙‫ݨ‬ၡय़ǴНᡏ߄य़ྕࡋёၨ‫ځ‬ ե 15-20ʚϐӭ (Landsberg,1969ǹDu et al.,2017)Ƕ୯ϣΨԖࣴ‫ز‬ว౜Ǵ ӧВ໔НୱࠠᄊӢηԖ٤೚ණ዗‫ޑ‬ਏ݀ǴԶӧ‫ڹ‬໔Нୱࠠᄊ߾Ԗշ‫ܭ‬հ ࠅෳᗺ‫ڬ‬ൎ‫ྕ਻ޑ‬Ǵ‫܌‬аȨНୱȩࠠᄊӢηჹ਻ྕၨؒԖܴዴ‫ޑ‬ቹៜ (ᎄ ܴϘ,2012)Ƕ. (3) Γπᎎय़ ӧВ໔Ǵࡌᑐ‫ࠠނ‬ᄊӢηᗨฅࢂ֎዗ᡏǴՠ‫܌‬೷ԋ‫ޑ‬഍ቹஒ཮٬‫ڬ‬ ൎ਻ྕၨեǴΓπᎎय़ࠠᄊӢηК‫ٯ‬ຫଯǴஒ཮уೲӦ߄֎዗ԶቚྕǴ҂ ٬ҔβӦࠠᄊᗨߚ֎዗ᡏǴՠ໒ᗡ‫ޜޑ‬໔ஒܰ٬ෳᗺ‫ڬ‬ൎ‫ڙ਻ޜ‬዗ၨ‫ז‬Ƕ ӧ‫ڹ‬໔Ǵࡌᑐ‫ࠠނ‬ᄊϷΓπᎎय़ࠠᄊǴ཮ஒВ໔‫֎܌‬ԏ‫ޑ‬዗ໆᄌᄌวණ Կε਻ϐύǴ‫܌‬аӧࣴ‫่݀ز‬ว౜Ȩࡌᑐ‫ނ‬ȩࠠᄊӢη߾ჹ਻ྕၨؒԖܴ ዴ‫ޑ‬ቹៜǹ ȨΓπᎎय़ȩࠠᄊय़཮ቚу਻ྕऊ 1.8~3.8 ʚǹ Ȩ҂٬ҔβӦȩ ࠠᄊय़ᑈёफ़ե਻ྕऊ 1.8~3.5 ʚნϐख़ाӢનϐ΋ (ᎄܴϘ, 2012)Ƕ Ԗࣴ‫ࡰز‬рǴӦ߄ྕࡋᆶதᄊϯৡ౦෌ғࡰ኱(normalized difference vegetation index, NDVI) ᆶӦ߄ό೸Н౗ǵࡌᑐ‫ނ‬Ϸᎎय़К‫ٯ‬և౜҅࣬ᜢǴ ࡺफ़եӦ߄ό೸౗ǵࡌᑐ‫ނ‬Ϸᎎय़К‫ٯ‬ஒԖշ‫ܭ‬फ़եӦ߄ྕࡋǴ຾Զ෧ ጗೿ѱ዗৞ਏᔈ (৊ਁက฻Γ, 2010) ǶќѦԖࣴ‫ز‬ᡉҢǴ೿ѱϐ೸Нᎎ य़ᆶᆘϯჹफ़ྕ‫ޑ‬ԋਏࢂ࣬ᇶ࣬ԋ‫ޑ‬Ǵՠӧহ‫ۑ‬೸Нჹ‫ڋ׭ܭ‬ଯྕϯਏ ݀Ԗज़ǴӢࣁВ৔‫ޔ‬ௗҗ⬏य़֎ԏǴӆу΢‫ځ‬዗৒ໆεǴ⬏य़εໆ֎ԏᒟ ৔ૈໆǴ٬ளջ٬‫ډ‬Α‫ڹ‬ఁϝค‫ݤ‬फ़ྕ(৪҅݇, 2003)Ƕ !. 17.

(30) 2.5.3 ዗৞ᆶຉၰࠠᄊ (SVF) ᜢ߯ аΠଞჹຉၰࠠᄊǴхࡴǺϺ‫ޜ‬ຎ౗(SVF) Ǵ഍ቹǴ೯॥Ǵᇥܴ೭٤ Ӣηჹ዗৞ਏᔈϐቹៜǺ (1) Ϻ‫ޜ‬ёຎӢη(SVF) ӵკ 2.1ǴਥᏵчऍࢪǵኻࢪǵᐞࢪ‫ڹޑ‬໔೿ѱ዗৞மࡋᆶϺ‫ޜ‬ຎ౗ (SVF) ϐᜢ߯Ǵࡌᑐຫஏ໣‫୔ޑ‬ୱΨ൩ࢂϺ‫ޜ‬ຎ౗ (SVF) ॶຫλȐϺ‫ޜ‬ ‫ࡋـૈޑ‬ຫλȑǴ೿ѱ዗৞ਏᔈΨຫܴᡉȐOke, 1981ȑǶ. კ2.1ġ Ϻ‫ޜ‬ຎ౗(SVF)ᆶ೿ѱ዗৞மࡋȐOkeǴ1981ȑ. ٗࢂӢࣁࡌᑐဂӧқϺ֎ԏεໆ዗ૈǴ‫ڹډ‬ఁਔࡌᑐ‫ނ‬۶Ԝ᎞ளࡐ߈ǵ ዗ૈค‫ݤ‬ԖਏวණԿε਻ύǴӢԜ೿ѱ዗৞ਏᔈ੝ձᡉ๱Ƕ୯ϣΨԖࣴ ‫ࡰز‬рǴຉ❾ϣϐࡌᑐஏࡋǵ௨ӈБԄϷᖏෂ໔ຯࣁ೯॥ᜢᗖǴԶ೿ѱ‫ޜ‬ ໔ᆘϯჹ‫ׯ‬๓೿ѱྕࡋ൑ϐਏ੻‫ؼ‬ӳ )೚Ѷຽ, 2012*Ƕ. 18.

(31) (2) ࡌᑐ‫׎ނ‬ԋϐ഍ቹ ന߈Ԗࣴ‫ࡰز‬рǴВပࡕ෌ਭ഍ቹ୔཮ᆢ࡭ၨեྕǴՠ‫ځ‬д୔ୱқ Ϻᆶఁ΢ϐྕࡋৡ߾ӧ 1 ࡋаϣ (Sun, 2017)Ƕࡌᑐ഍ቹК෌ਭ഍ቹԖफ़ ྕਏ݀ǴӢԜ࣬ӕచҹΠࡌ‫ނ‬Ͽ‫ޑ‬Кࡌ‫ނ‬ӭ‫ࡋྕޑ‬ଯǶԖᆘϯՠคၨ٫ ഍ቹ፿ጨᕉნ‫ޑ‬ᆶԖࡌᑐ‫࣬ޑ‬՟ǴࡺКຉၰύԖࡌᑐ഍ቹϷ෌ਭ഍ቹ‫ޑ‬ ྕࡋଯǶ഍ቹԖफ़եᒟ৔ྕࡋǴԶ෌ਭԖᇃණफ़ྕਏ݀Ƕࡌᑐ഍ቹफ़ྕε ‫ܭ‬Γπ዗ቚྕǶᆕӝа΢ǴΓπ዗ᆶ೯॥คᡉ๱ቹៜǴԶܿՋ‫و‬ӛ‫ޑ‬ຉ ၰǴ‫ځ‬዗ᕉნӢηύа഍ቹࣁ२Ǵ࣬ჹᔸࡋᆶ॥ೲԛϐǶ. (3) ຉၰ೯॥ මԖࣴ‫ز‬௖૸όӕຉၰЁࡋჹᕉნ॥൑ϐቹៜ (ߋ‫ک‬ֆ, 2010) Ƕ൩ ӚຉၰЁࡋϐຉ‫ ك‬1Ȑ॥ೀಃ΋ঁຉ‫ك‬ȑϣࢬ‫ݩ‬ᆶᅁ෮ελԶ‫ق‬ǴຉၰЁ ࡋຫεȐຉၰຫઞȑ Ǵ‫ࣁݩࢬځ‬଑ࢬ୔Ǵҭջ֡ឦѳྖࢬǴӧԜᅿࢬ‫ݩ‬Ȑค ෮ࢬȑచҹΠǴຉ‫ك‬ϣϐ዗ໆค‫ݤ‬໺ᒡԿຉ‫ك‬ѦǴᏤठ೯॥ਏૈό٫Ƕϸ ϐǴຉၰЁࡋຫλȐຉၰຫቨȑ Ǵ‫ܭ‬ຉ‫ك‬ϣ཮ౢᆀ෮ࢬǴёԖਏ‫ޑ‬ஒຉ‫ك‬ ϣ዗ໆǵԦࢉ‫ނ‬໺ᒡԿຉ‫ك‬ѦǴ‫ځ‬೯॥ਏૈҭၨ٫Ƕ ൩೯॥ਏૈຑ՗Զ‫ق‬Ǵόፕ໒ืଯࡋࣁՖǴඤ਻౗ϐᡂϯ֡ᒿ๱ࡌ ᑐ‫ޑނ‬௨ӈᆶ॥ӛᜢ߯Զ‫ڙ‬ቹៜǶӧό‫߻ڙ‬ෂࡌᑐ‫ޑނ‬ቹៜచҹΠȐಃ ΋ෂࡌᑐ‫ނ‬ȑǴӭև౜рᒿ๱ຉၰЁࡋຫεȐջຉၰቨࡋຫઞȑǵኴቫຫ ଯǴ‫ځ‬ඤ਻౗ᒿϐ෧λǶԶ྽‫߻ډڙ‬ෂᆶࡕෂࡌᑐ‫ނ‬ϐచҹΠȐಃΒෂࡌ ᑐ‫ނ‬ȑ ǴନΑຉၰЁࡋ 0.3ǵ0.5 և౜рᒿ๱ຉၰЁࡋຫεǴඤ਻౗ຫଯѦǴ ‫ځ‬Ꭹ֡և౜рຉၰЁࡋຫε߾ඤ਻౗ຫλǴᒿ๱ኴቫຫଯǴ߾ඤ਻౗ຫ λǶӧ໻‫߻ډڙ‬ෂࡌᑐ‫ނ‬ቹៜϐచҹΠȐಃΟෂࡌᑐ‫ނ‬ȑ Ǵεӭև౜ඤ਻. 19.

(32) ౗٠҂ᒿ๱ຉၰЁࡋຫεԶ෧եǴЪᒿ๱ኴቫຫଯǴ‫ځ‬ඤ਻౗ຫλǶ ന߈Ԗࣴ‫ز‬ଞჹ೿ѱ༾਻ং຾Չ௖૸(ߋ฻, 2016) Ƕহ‫ۑ‬዗๤፾ࡰ኱ ӄ୔Γᡏ዗ૈྕࡋ (PET) ኧॶϩѲӧ 32-40 ʚ໔ǹ዗ག‫ัڙ‬༾๤፾ 3034 ʚǴྕཪ 34-38 ʚǴ‫ک‬዗ 38-42 ʚǹғ౛዗ᔈΚག‫ڙ‬ำࡋࣁᇸ༾ǵ፾ ࡋ‫ک‬மਗ਼዗ᔈΚǴෳໆጄൎӭϩѲ‫ܭ‬዗ག‫ྕڙ‬ཪϐ୔ୱǴԶค዗ག‫ڙ‬๤ ፾ϐ୔ୱǴ߾໻Ԗั༾๤፾‫ޑ‬ኧॶǶ ќѦǴຉᄂᆙஏำࡋࡰኧ (CI) 0.1 аΠၨࣁઇ࿗ǴԶ 0.8 а΢ၨό ઇ࿗Ǵՠ዗ག‫ڙڙ‬ᎃ߈‫ݞ‬ο‫ک‬ᆘӦ‫ޜ‬໔ቹៜǴЪࡌ‫ނ‬ၨόᆙஏǴΓᡏ዗ૈ ྕࡋ (PET) ࣬ၨեǴࡺ၀୔হ‫ۑ‬Γᡏ዗ૈྕࡋ(PET) 0-34 ʚ໔Ǵ዗ག‫ڙ‬ ࣁั༾๤፾ǴԶо‫ۑ‬Γᡏ዗ૈྕࡋ(PET)ӧ 14 ʚаΠǴ዗ག‫ߚࣁڙ‬தհǶ ᆙஏำࡋࡰኧ (CI) 0.2 аΠϐ୔ୱǴᡉҢຉᄂၨઇ࿗Ǵܰ೷ԋ๤፾ࡋৡ ౦εǴΓᡏ዗ૈྕࡋ (PET) ϐ዗ག‫཮ڙ‬ၨհ‫܈‬ၨ዗Ƕ. 2.5.4 ዗৞ᆶΓπ዗ǵኴଯᜢ߯ (1) Γπ዗(Anthropogenic heat) Ԗࣴ‫ز‬ፓࢗহ‫ۑ‬ᆵч೿཮୔዗৞ਏᔈǴ่݀ว౜ύϱଯྕ୔ϩѲӧ Ҭ೯࿯ᗺϷΓዊ໣ύᗺǴӵǺًؓ௨‫ܫ‬εໆΓπ዗(ًࢬໆε)ǵΓᜪࢲ୏ εໆණวΓπ዗ (Γዊ໣ύ୔) (ᙁη๔, 2013)Ǵკ 2.2Ƕ. 2012 ԃ 7 Д 4 В. 2012 ԃ 7 Д 11 В. 2012 ԃ 7 Д 13 В. კ2.2ġ ᆵчࣧӦჴෳྕࡋϩѲკ(ύϱ) (ᙁη๔, 2013). 20.

(33) а‫ޜ‬ፓౢғ‫ޑ‬዗ໆܿՋ‫و‬ӛଯྕ໣ύӧՋ೽Ϸܿࠄ೽ӢՋ೽Տ‫ܭ‬Π ॥୔Ǵܿࠄ೽Ӣࡌ‫ނ‬ӭԶණ዗ᆶ೯॥ৡǶණ዗ໆ 40 W ቚуԿ 120 W ਔǴ ᏾ᡏྕࡋৡቚуԿ 6K 4 ঁਔ໔നࣁৡ౦ǺԐ΢ 11-12ǵΠϱ 2-3ǵ5-6ǵఁ ΢ 8-9Ƕ. (2) ࡌᑐ‫ނ‬ኴଯ මԖࣴ‫ز‬аъ৩ 1000 m ‫ޑ‬Ёࡋϩ‫݋‬Ѡύѱ୘཰৒ᑈ౗ᆶྕࡋϐᜢ ߯Ǵ่݀ว౜ӧϱ‫࣬ڹ‬ᜢ‫܄‬നεǴЪ୘཰৒ᑈ౗‫؂‬ගଯ 50 %ǴѠύѱϱ ‫ڹ‬ਔࢤྕࡋऊቚу 0.5 ʚǴԶύϱӢѓ੝ਸ‫ޑ‬೿ѱհ৞౜ຝǴ‫܌‬а୘཰ ৒ᑈ౗ᆶύϱਔࢤ೿ѱ਻ংև౜ॄ࣬ᜢ่݀ (‫׵‬ሱ᜻, 1999)Ǵ߄ 2.5Ƕ ߄ 2.5ġ Ѡύѱ୘཰৒ᑈ౗ᆶྕࡋϐᜢ߯(‫׵‬ሱ᜻, 1999) ύϱ ఁ΢ ϱ‫ڹ‬ ъ৩ a b R a b R a b Ѡ 500m 34.58 0.27 0.07 31.02 ύ 1000m 34.64 -0.58 0.17 30.98 ѱ 1500m 34.58 -0.41 0.17 31.12. 21. R. 0.69. 0.33. 28.66. 0.52. 0.31. 0.87. 0.45. 28.59. 1.18. 0.64. -0.10. 0.08. 28.63. 0.93. 0.60.

(34) ಃΟകǵࣴ‫ز‬Б‫!ݤ‬ 3.1 ჏ကѱ዗৞౜‫ݩ‬ፓࢗ 3.1.1 ౽୏ᢀෳჴෳБ‫ݤ‬ 3.1.1.1 ᢀჸጄൎ ҁࣴ‫ز‬ፓࢗа჏ကѱࣁჹຝǴ௖૸჏ကѱϐ዗৞ਏᔈϷ‫ځ‬ᝄख़‫܄‬Ǵ ٠ϩ‫݋‬๤፾ࡋ࣬ᜢቹៜǴᢀෳጄൎ఼ᇂ೿ѱϐѱ୔ᆶ॓୔Ƕ. 3.1.1.2 ၡጕ ӵკ 3.1Ǵҁࣴ‫ز‬ፓࢗ‫ע‬჏ကѱϩࣁՋ୔ǵч୔ǵࠄ୔ϐ 3 ୔ǴԶ 3 చፓࢗၡጕӵკ 3.2Ǵᒧ᏷ϐჴෳၡጕࣁЬा༸ၰǴԶෳᗺӼ௨аၡαࣁ ЬǶ. კ3.1ġ ϩ୔Ңཀკ. 22.

(35) !. (a)ч୔ෳᗺՏ࿼. !. (b)Ջ୔ෳᗺՏ࿼. !. (c)ࠄ୔ෳᗺՏ࿼ კ3.2ġ Ӛ୔ෳᗺՏ࿼. 3.1.1.3 ෳᗺ ӵკ 3.3Ǵҁࣴ‫ز‬ፓࢗᕴӅԖ 87 ঁෳᗺǴԶ‫ঁ؂‬ၡጕӼ௨ऊ 30 ঁෳ ᗺǴаӧ΋λਔϣֹԋෳໆǶ. კ3.3ġ ෳᗺՏ࿼Ңཀკ. 23.

(36) 3.1.1.4 ፓࢗБ‫ݤ‬ ፓࢗ຾Չ‫ޑ‬БԄࢂа 2 Γ΋ಔ᚛ᐒً‫ۓډ‬ᗺ૶ᒵᐒᏔኧᏵǶ٬Ҕ‫ޑ‬ ፓࢗҔ‫ڀ‬хࡴǺፓࢗკǵ૶ᒵ‫ހ‬ǵЎ‫ڀ‬Ƕፓࢗჴࡼਔ໔ᒧ᏷ӧহ‫ۑ‬නਟค ߘ‫ޑ‬ВηǴ‫ܭ‬ӕ΋Ϻ΢ϱ 10Ǻ30 ‫ډ‬Πϱ 2Ǻ30ǴϷఁ΢ 10Ǻ30 ‫ډ‬ঐః 2Ǻ30Ǵ຾Չ 2 ԛ౜Ӧᢀෳϐ዗৞ჴᡍǶӢࣁύϱࣁ΋ϺϺ਻ന‫ݹ‬዗‫ޑ‬ਔ ࢤǴӢԜࢎ೛ሺᏔᢀෳΨаԜਔࢤࣁ٫Ƕ ᆕӝа΢Ǵҁࣴ‫҇ܭز‬୯ 107 ԃ 7 Д 28 ВԿ 8 Д 1 Вය໔Ǵ຾Չࣁ ය 3 ВϐෳໆჴᡍǶӧ౜Ӧෳໆ߻΋ຼǴჹΓ঩຾ՉՉ߻௲‫૽ػ‬ግǶෳ ໆ‫܌‬ሡ 3 ಔȐ6 ঁΓȑ ǵ3 ѠᐒًᆶෳໆሺᏔǴӧ߻΋λਔջा‫ۓډ؃‬ᗺǶ. 3.1.1.5 ჴᡍ௓‫ڋ‬ Ӣ೿ѱ዗৞தаѱ୔ࣁ༝Ј۳ѱ॓բ৩ӛว৖Ǵࡺҁࣴ‫ز‬ೕჄϐፓ ࢗၡ৩εठаѱ୔ύЈࣁচᗺǵև౜‫ܫ‬৔‫ރ‬ᄊǴа఼ᇂ᏾ঁᢀෳጄൎǶӧ ຾Չ౽୏ᢀෳύ೛‫ۓ‬а 2 ࣾࣁ໔႖Ǵೱុ૶ᒵྕᔸࡋϷਔ໔Ƕ ‫؂‬ಔሡ૶ᒵᢀෳᗺ‫ޑ‬ਔ໔ǴЪ‫؂‬ಔӚၡጕ࿶ၸෳᗺਔሡ‫ۓ‬ᗺଶ੮ 15 ࣾǶෳᗺ‫ޑ‬೛‫ۓ‬аѱ୔ၨஏǵѱ॓ၨ౧ࣁচ߾Ǵ٠Ꮓёૈᒧ᏷ၡα‫ޑ‬Տ ࿼ǴБߡӧӦკ΢ஒෳᗺբ‫ۓ‬ՏǴаճ‫ុࡕܭ‬Ӧკᆶႝတკᔞϐ০኱ᙯ ඤբ཰Ƕ ࣁΑᡣӚಔໆෳၗ਑ᆶ૶ᒵਔ໔ӕ‫؁‬ǴӚಔ‫ޑ‬Ծ୏૶ᒵᏔᆶໆෳ‫ޣ‬ ‫૶ޑ‬ᒵᏔ‫܌‬௦Ҕ‫ޑ‬Չ୏ᔈҔ೬ᡏሡӧෳໆ߻֡຾Չਔ໔ӕ‫؁‬ਠ҅Ƕ‫؂‬ಔ ‫ॄ܌‬ೢ૶ᒵϐᢀෳᗺऊ 30 ঁǴᕴᢀෳਔ໔௓‫ڋ‬ӧ 1 ঁλਔϣǶ. 24.

(37) 3.1.1.6 ෳໆሺᏔᇥܴ ҁࣴ‫ز‬௦Ҕᐒًᢀෳ‫ݤ‬຾ՉჴᡍǴԶሺᏔࢎ೛೽ϩࣁஒྕྒྷࡋइᒵ Ꮤ‫ܭۓڰ‬ᐒًࡕྣ᜔Ѝࢎ΢คҺՖ፿ጨ٠य़ӛ߻БǴӵკ 3.4Ƕҁࣴ‫ز‬௦ ҔϐჴբෳໆሺᏔࢂऍ୯ HOBO MX2301 ϐЊѦࠠྕᔸࡋ૶ᒵᏔǶྕࡋ ᆶᔸࡋࣁϣ೽໺གᏔǴ‫ځ‬ໆෳྕࡋጄൎ- 40 ʚ ~ 70 ʚǴ࣬ჹᔸࡋጄൎ 0 ~ 100% RHǴໆෳᆒࡋྕࡋࣁ² 0.2 ʚϷ࣬ჹᔸࡋࣁ² 2.5% RH Ǵ૶ᒵ໔ ႖ёа೛‫ ۓ‬1 ࣾ‫ ډ‬18 㚚λ㟭Ǵҁࣴ‫ز‬௦‫ ؂ڗ‬2 ࣾࣁ૶ᒵਔ໔႖Ƕ ӵკ 3.5Ǵ‫ۓڰ‬ਠ҅ઠϐ਻ຝઠሺᏔ௦Ҕ Onset Ϧљрౢ‫ ޑ‬HOBO RX3000Ǵࢂ‫ڀ‬Ԗᇿൔфૈ‫૶ޑ‬ᒵᏔǴ፾Ҕ‫ܭ‬ӚᅿൾӍᕉნёаམଛӚԄ ਻ຝགෳᏔϷᜪКᒡрགෳᏔǴёаᅱ䬲໨ҞԖǺ‫ࡋྕ਻ޜ‬ǵᔸࡋǴफ़ߘ ໆǴε਻ᓸΚǴ॥ӛǴ॥ೲ฻Ǵҁࣴ‫ز‬௦Ҕ 5 ϩដࣁ૶ᒵ໔႖Ǵइᒵਔ໔ ࣁ 24 λਔǶ. კ3.4ġ ऍ୯ HOBO MX2301 ᙔУ ඵૈྕᔸࡋ૶ᒵᏔ. კ3.5ġ HOBO RX3000 ਻ຝઠ. 25.

(38) 3.1.1.7 ਻ຝచҹ ٩Ᏽύѧ਻ຝֽၗ਑ϐ਻ຝచҹѳ֡ॶǴ߄ 3.1 ჏ကѱϐύѧ਻ຝֽ ߈ϖԃ਻ংచҹ(2014-2018)࿶ीᆉள‫ޕ‬ᐕԃ 7 Дҽѳ֡ྕࡋࣁ 29 ʚǴВ നଯྕѳ֡ࣁ 35.93 ʚǴВനեྕѳ֡ࣁ 23.67 ʚǴ॥ೲѳ֡ 2.04 m/sǴ ໦ໆѳ֡ 6.58 ΜϩໆǶ ߄ 3.1ġ ჏ကѱϐύѧ਻ຝֽ߈ϖԃ਻ংచҹ(2014-2018) ྕࡋ(ʚ). ߘໆ. ॥ೲ/॥ӛ. ਔ໔. ѳ ֡. നଯ/В ය. നե/В ය. డԯ. നεΜ ϩដ॥. 2014/7 2015/7 2016/7 2017/7 2018/7 2014/8 2015/8 2016/8 2017/8 2018/8. 30.1 29.2 29.5 28.9 29.0 28.9 28.1 29.0 29.8 28.3. 37.0,7/19 35.8,7/1 36.7,7/29 36.0,7/1 36.5,7/18 35.1,8/1 34.9,8/11 36.2,8/10 35.8,8/26 35.3,8/5. 24.7,7/19 23.5,7/27 24.3,7/30 23.5,7/31 23.7,7/8 23.4,8/21 23.2,8/8 23.7,8/19 23.9,8/28 22.8,8/23. 203.7 245.6 208.7 663.2 377.9 253.0 560.5 189.4 198.6 858.5. 2.4/250 2.4/250 2.2/260 1.8/60 1.9/240 2.0/200 2.3/210 1.4/250 2.0/250 2.0/170. നε ᕓ໔ ॥ 20.0 16.0 20.3 17.5 13.8 17.1 33.8 13.2 23.8 18.8. ࣬ჹ ྒྷࡋ (%) ѳ֡. Вྣ ਔኧ. 73 75 77 80 79 80 80 81 76 78. 236.2 199.1 232.1 192.2 173.3 209.4 146.7 179.8 214.3 144.1. ᕴ ໦ ໆ 6.2 7.1 5.8 6.8 7.0 6.2 7.3 7.0 6.2 7.7. ҁࣴ‫ز‬ϩ‫ ݋‬7 Д 28 Вᆶ 7 Д 29 Вਔ໔ 10 ᗺԿ 14 ᗺ‫਻ޑ‬ຝઠ೴ਔ ྕࡋइᒵǴӵ߄ 3.2Ƕ่݀ว౜Ǵ7 Д 28 В໦ໆ೿ӧ 6-8Ǵ॥ೲΨၨ১Ǵ Զ 7 Д 29 В‫ ޑ‬14 ᗺϷ 30 В‫ ޑ‬12 ᗺ໦ໆࣁ 6Ǵ॥ೲऊࣁ 4Ƕ࿶೴ਔྕࡋ Кၨ 7 Д 29 Вࣁന٫ࡼෳВයǶ. 26.

(39) ߄ 3.2ġ ਻ຝઠ೴ਔྕࡋ 7 Д 28 В 10 ᗺ 11 ᗺ 12 ᗺ 13 ᗺ ྕࡋ(℃) 32.3 32.5 33.8 34.0 ॥ೲ(m/s) 2.1 0.9 1.1 2.0 ໦ໆ(0~10) 6.0 8.0 7.0 7.0 ᒟ৔ໆ(MJ/ʤ) 2.21 1.90 1.82 2.43 ߘໆ(mm) 0.0 0.0 0.0 0.0 7 Д 30 В ୖ ኧ 10 ᗺ 11 ᗺ 12 ᗺ 13 ᗺ ྕࡋ(℃) 32.8 33.1 33.5 34.7 ॥ೲ(m/s) 0.8 3.0 1.7 3.7 ໦ໆ(0~10) 4.0 4.0 6.0 2.0 ᒟ৔ໆ(MJ/ʤ) 2.66 2.73 2.32 3.11 ߘໆ(mm) 0.0 0.0 0.0 0.0 ୖ ኧ. 14 ᗺ 34.0 3.1 7.0 2.49 0.0 14 ᗺ 34.7 4.2 2.0 3.00 0.0. 7 Д 29 В 10 ᗺ 11 ᗺ 12 ᗺ 13 ᗺ 14 ᗺ 33.0 33.5 34.1 35.0 34.8 1.4 1.3 2.5 1.6 4.6 3.0 3.0 3.0 3.0 6.0 2.51 3.00 3.02 3.32 2.52 0.0 0.0 0.0 0.0 0.0 7 Д 30 В 7 Д 31 В 23 ᗺ 24 ᗺ 1ᗺ 2ᗺ 28.7 1.1 -0.0 0.0. 28.4 0.7 -0.0 0.0. 28.1 0.9 -0.0 0.0. 27.1 0.4 -0.0 0.0. 3.1.2 GIS ྕࡋ฻ॶጕϩ‫݋‬Б‫ݤ‬ ҁࣴ‫ز‬ϐྕࡋ฻ॶጕࢂа Excel ‫ע‬ჴෳྕࡋ࿶ၸਔ໔ӕ‫؁‬ਠ҅ࡕǴ ள‫ډ‬ჴෳΟϺѤঁਔࢤനಖਠ҅ྕࡋॶǴӆஒനಖਠ҅ྕࡋॶᆶ࣬ჹ‫ޑ‬ ෳᗺ຾Չӝ‫ٳ‬Ǵ٠࿼Ε AREGIS ೬ᡏύ‫ڗ‬ளྕࡋ฻ॶጕკǶAREGIS ೬ ᡏග‫ޑٮ‬ϣකБ‫ݤ‬Ԗ IDWǵKrigingǵNatural NeighborǵSplineǵTopo to Rwaster ฻Ǵҁࣴ‫ز‬࿶ၸ၂ᇤว౜ IDW ϣක‫ݤ‬നࣁௗ߈ჴሞ‫ݩރ‬Ǵ‫܌‬а ჴෳྕࡋ฻ॶጕკջ௦Ҕ IDW ϣක‫ݤ‬π‫ڀ‬Ƕ. 27.

(40) 3.2 ࣬ᜢӢηໆϯϩ‫݋‬Б‫!ݤ‬ 3.2.1 εЁࡋ 3.2.1.1 ჏ကѱΓαϩ‫݋‬Б‫ݤ‬ Γαஏࡋ೸ၸΓαஏࡋϦԄ (1) ၮҔ Excel ीᆉǴϩձࡌҥࣴ‫୔ز‬ ୱ‫ޑ‬ЊᝤΓαஏࡋӦ౛ၗૻ‫س‬಍Ƕ. D=P/A……(1). DǺӚٚΓαஏࡋ(Γαኧ/ѳБϦٚ) PǺӚٚΓαኧ AǺӚٚय़ᑈ !. Ӛٚय़ᑈ (A)Ǵӵკ 3.6Ǵёҗࡹ۬ၗ਑໒‫ܫ‬ѳѠ‫ڗ‬ளǶӚٚΓαኧ (P)Ǵӵ߄ 3.3Ǵࣁ჏ကѱܿǵՋ୔Њࡹ٣୍‫܌‬ϐ಍ीၗ਑Ƕ !. კ3.6ġ GIS ჏ကѱٚࣚკ. 28. !.

(41) ٚ ቅছٚ ً۫ٚ ᅽ҇ٚ Ӏၡٚ ỿᛯٚ ෫ϣٚ ϼѳٚ ཥছٚ ᅽӼٚ Ԯൎٚ ߥғٚ ཥ۫ٚ ӥᓐٚ ᅽӄٚ ࡕᤞٚ ᑫ‫׸‬ٚ Ў໡ٚ ऍྍٚ ߥᅽٚ ᑫϘٚ ᑄ䚀ٚ ࡕ෫ٚ ‫ޱ‬૛ٚ ෝ‫ڳ‬ٚ ύᤞٚ Ջѳٚ ߥӼٚ Ϙကٚ ч෫ٚ ߏԮٚ က௲ٚ ྰηٚ ݅හٚ Ӽቧٚ ഗቧٚ. ߄ 3.3ġ Γαኧ 8113 7378 7026 6342 5653 5412 5298 5149 5113 5109 5087 4987 4958 4861 4764 4718 4542 4495 4424 4402 4251 4224 4207 4147 3953 3952 3865 3541 3486 3446 3397 3395 3294 3166 2974. ჏ကѱ 107 ԃ 7 ДӚٚϐΓαኧ߄ ٚ Γαኧ Area_km2 Area_km2 ύѧٚ 13.23508454 2601 1.955988995 ၸྎٚ 3.913254318 2573 1.468951939 ើ዇ٚ 5.422535107 2560 21.72797959 ࡕᡌٚ 5.192744115 2557 3.630164606 ෫ᜐٚ 18.49507421 2533 2.208736681 ‫ޱ‬Ӽٚ 23.65264364 2529 2.266260644 Ўϯٚ 5.908816348 2525 1.577288108 ཥՋٚ 2.969681703 2502 1.775757116 εྛٚ 6.142125202 2495 30.0930883 ख़ᑫٚ 4.526834663 2424 1.81547091 ර໚ٚ 4.405928012 2375 1.370767077 ๮ࠄٚ 7.263533989 2342 2.696140929 ཥ໒ٚ 9.792158762 2337 3.751252077 ҉‫ک‬ٚ 5.102160775 2308 1.375423893 ࠟླྀٚ 21.27464064 2307 1.571674013 ਜଣٚ 6.385565711 2268 2.384484299 ᐽছٚ 3.932788505 2244 40.68007409 Ӽ཰ٚ 7.17596621 2234 4.584676622 ύξٚ 2.855558016 2208 2.371893262 ठᇻٚ 4.692908021 2175 0.613043871 ‫ػ‬मٚ 4.114573674 2165 1.807633839 ᓐෝٚ 19.53832678 2158 26.02729892 ܿᑫٚ 4.506436046 2135 2.105870452 ҇௼ٚ 12.486388 2128 1.570173487 ܿοٚ 3.458774044 2123 6.315573557 आґٚ 8.343549005 2066 8.086630001 Ծமٚ 2.878310628 2001 1.211566878 ୻ϡٚ 2.597403402 1967 0.825710306 ཥ൤ٚ 24.61641235 1934 1.362443588 ቼӼٚ 13.61891345 1906 0.928796968 ᑫࠄٚ 2.389511138 1882 1.546216368 Ꮴܴٚ 1.456207973 1845 1.258998857 Π୶ٚ 3.176845704 1825 14.95491011 ᆧۡٚ 2.738462102 1701 0.486766056 พ‫ޗ‬ٚ 2.576821186 1614 1.700991312. 29.

(42) ᑫӼٚ чᄪٚ ЦҖٚ อԮٚ чߐٚ Ջᄪٚ ഗᤞٚ. 2791 2734 2695 2657 2647 2634 2630. ࠹ߞٚ ୯๮ٚ ᙦԃٚ Ԯ‫׸‬ٚ чཥٚ ജቧٚ ३෫ٚ. 7.616013995 1.519175141 5.31939192 4.214522367 3.995949727 1.424136239 6.348351938. 1572 1564 1527 1338 1324 1242 942. 0.911682332 1.966809264 1.571356352 19.76281054 21.51210235 41.74951451 8.364209077. ၗ਑ٰྍǺ჏ကѱܿ୔Њࡹ٣୍‫܌‬ǵ჏ကѱՋ୔Њࡹ٣୍‫!܌‬ !. 3.2.1.2 ჏ကѱᆘᙟ౗ϩ‫݋‬Б‫ݤ‬ ӵკ 3.7Ǵ჏ကѱٚࣚ‫ྣޜ‬კ߯җ჏ကѱ೿ѱीฝၗ਑ᆛ္‫ޑ‬ႝηӦ კύ 2014 ԃ჏ကѱ‫ྣޜ‬კϷ჏ကѱٚࣚጕკǴа Photoshop ᠄კࡕ‫܌‬ளǶ. კ3.7ġ 2014 ԃ჏ကѱٚࣚ‫ྣޜ‬კ ၗ਑ٰྍǺhttps://landuse.chiayi.gov.tw/chyiweb/. 30.

(43) Ӛٚᆘᙟय़ᑈ٩Ᏽ჏ကѱٚࣚ‫ྣޜ‬კǴճҔ Photoshop ϩ‫݋‬ளрӚٚ ϣᆘᙟय़ᑈႽનǴ஥ΕϦԄ (2) ीᆉрӚٚᆘᙟय़ᑈኧᏵǶ. G= A*g/a……(2). GǺӚٚϣᆘᙟय़ᑈ AǺӚٚय़ᑈ gǺӚٚϣᆘᙟय़ᑈႽન aǺӚٚय़ᑈႽન. 3.3.1 λЁࡋ 3.3.1.1 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎϺ‫ޜ‬ຎ౗(SVF)ϩ‫݋‬Б‫ݤ‬ ҁࣴ‫ز‬а SVF ϩ‫݋‬ຉၰቨࡋᆶࡌ‫܌ނ‬ౢғϐ഍ቹǴჹ೿ѱྕࡋࢂց Ԗ࣬ჹ‫ޑ‬ቹៜǶ‫ڀ‬ᡏԶ‫ق‬Ǵҁࣴ‫ز‬а CAD Ϸ ENVI-met ೬ᡏ຾ՉࡌኳϷ SVF ϩ‫݋‬ǴΨ൩ࢂճҔ჏ကѱ೿ѱीฝኧॶӦ‫׎‬კ‫܌‬ග‫ٮ‬ϐ჏ကѱࡌᑐ ኴଯ CAD კǴཥቚෳᗺ٠ᘏ‫ڗ‬ෳᗺ‫ڬ‬ൎǴӈӑࡕෳໆ٠኱ຏၰၡЁκϷ ࡌᑐኴଯЁκǴӵკ 3.8ǴӆճҔ ENVI-met ࡌኳǶ‫ঁ؂‬ෳᗺၰၡࡌᑐࡌ ҥ ENVI-met ኳࠠࡕǴӆа Project Wizar Ϸ Envimet4 π‫ঁ؂עڀ‬ኳࠠ຾ Չ SVF ϩ‫݋‬Ǵ‫פ‬рຉ୔‫ޜ‬໔ࠠᄊᜪࠠ‫ޑ‬዗ᕉნϩѲ੝ቻǴӵკ 3.9 ᆶკ 3.10ǶӵԜ‫פ‬рӚෳᗺ‫؂‬ъ৩ 10 m ‫ޑ‬༝ϐ SVF ѳ֡ॶࡕǴӆஒ ENVImet ϩ‫݋‬рϐ SVF ༊рԋ Excel ᔞǴ٠‫؃‬ръ৩ 10 m ጄൎϣϐѳ֡ॶǶ. 3.3.1.2 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎ഍ቹϩ‫݋‬Б‫ݤ‬ ӵკ 3.11Ǵ഍ቹϩ‫݋‬ӕኬࢂа჏ကѱ೿ѱीฝኧॶӦ‫׎‬კ‫܌‬ග‫ٮ‬ϐ ჏ကѱӄ୔ࡌᑐኴቫଯࡋ಍ी CAD კࣁ୷ᘵǴ‫ঁ؂ע‬ෳᗺᛤᇙраъ৩ 100m ༝٠ᄒკǴӆ༊ΕԿ SketchUp ճҔᛤკϷጓᒠπ‫ࡌڀ‬ኳǴӵკ 3.12Ǵ. 31.

(44) ӆ‫ࡌډ‬ኳၗૻϣ೛‫ۓ‬Ӧ౛Տ࿼ᆶ഍ቹπ‫ڀ‬ϣ೛‫ۓ‬ჴෳ྽ВϐВයϷਔ໔Ǵ നࡕҔ᜔ᓐπ‫ٰڀ‬ᘏ‫ڗ‬ຎ‫ف‬კǴӵკ 3.13Ȑ၁ߕᒵ 3ȑǶ. კ3.8ġ NVI-met ࡌኳ‫ހ‬य़Ңཀკ. კ3.9ġ Project Wizard Ңཀკ. 32.

(45) კ3.10ġ Envimet4 ϩ‫݋‬Ңཀკ. კ3.11ġ ჏ကѱӄ୔ࡌᑐኴቫଯࡋ಍ी CAD კ. კ3.12ġ SketchUp ࡌኳ. 33.

(46) (a)९ຎკ. (b)ୁຎკ კ3.13ġ ९ຎკϷ҅ຎკ. 3.3.1.3 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎࡌᑐᙟᇂ౗ϩ‫݋‬Б‫ݤ‬ ӵკ 3.14ǴλЁࡋϐࡌᑐᙟᇂ౗ࢂ೸ၸ୯βೕჄӦ౛ၗૻკѠ‫ޑ‬ໆ ෳπ‫ڀ‬ǴаෳᗺࣁύЈฝръ৩ 100m ϐ༝୮ǴаԜࣁጄൎ٠ᘏ‫ڗ‬კᔞǴ ӆ༊Ε‫ ډ‬Photoshop ᒧ‫ࡌڗ‬ጨ߄य़а‫؃‬рࡌጨय़ᑈႽનǶϐࡕǴճҔϦԄ )4*а EXCEL ीᆉр 87 ঁෳᗺϐӚෳᗺ‫ڬ‬ᜐ 100 m ጄൎϐࡌᑐᙟᇂ౗ Ȑ၁ߕᒵ 4ȑ Ƕ C=Ca/Fr*100……(3). CǺࡌᑐᙟᇂ౗ CaǺъ৩ 100M ጄൎϣࡌጨय़ᑈႽન FrǺъ৩ 100M ӄጄൎႽનॶ. 3.3.1.4 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎ৒ᑈ(֖ኴଯ)౗ϩ‫݋‬Б‫ݤ‬ ӵკ 3.15Ǵኴଯၗ਑ӕኬࢂа჏ကѱ೿ѱीฝኧॶӦ‫׎‬კ‫܌‬ග‫ٮ‬ϐ CAD ۭკࣁ୷ᘵǴаෳᗺࣁύЈᛤраъ৩ 100m ϐጄൎࡕǴӆаΓπ ಍ीБԄ‫؃‬рǶѳ֡ኴབᆶ৒ᑈ౗ϐኧॶࢂճҔ Excel ਥᏵϦԄ(4)ᆶ(5) Ƕ ीᆉǴ‫؃‬р 87 ঁෳᗺ‫ঁ؂ޑ‬ෳᗺ‫ڬ‬ᜐ 100m ጄൎϐ৒ᑈ౗Ȑ၁ߕᒵ 5ȑ. 34.

(47) Af=F/B……(4). AfǺѳ֡ኴଯ FǺᕴಕᑈኴଯኧ BǺෂኧ. Fa=C/Af……(5). FaǺ৒ᑈ౗ CǺࡌᑐᙟᇂ౗ AfǺѳ֡ኴଯ. კ3.14ġ ୯βೕჄӦ౛ၗૻკѠ‫ޑ‬ໆෳπ‫ڀ‬Ңཀ. კ3.15ġ ჏ကѱ೿ѱीฝኧॶӦ‫ ׎‬CAD ۭკ(ъ৩ 100m). 35.

(48) 3.3.1.5 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎΓπ዗ϩ‫݋‬Б‫ݤ‬ аϣࡹ೽ᔼࡌ࿿ࠤໂว৖ϩ࿿୯βೕჄϩಔΕαᆛ‫ޑ‬ӄ୯βӦ٬Ҕ ϩ୔ၗ਑ࢗ၌‫س‬಍ፓࢗϩᜪӚෳᗺ‫ڬ‬ᜐ 100m ጄൎࣁ୘཰୔ᗋࢂՐӻ୔Ƕ ஒ჏ကѱࡹ۬‫ޑ‬჏ကѱ೿ѱीฝኧॶӦ‫׎‬კග‫ٮ‬ϐ჏ကѱӄ୔ࡌᑐ ኴቫଯࡋ಍ी CAD(კ 3-16)аෳᗺࣁύЈᛤраъ৩ 100m ϐጄൎǴ٠ ीᆉъ৩ 100m ጄൎϣϐӚኴቫᕴय़ᑈॶǶ ҁࣴ‫ز‬Γπ዗а؇ӵᓪ(92)೿ѱՐӻ୔ຉᄂҔႝໆፓࢗύ࿯ᒵՐ୘ ٬Ҕ‫ޑ‬ѳ֡ҔႝໆǴԶ჏ကѱຉၰ 1F-2F ӭࣁ୘۫ 3F а΢ࣁՐӻǴ‫܌‬а ҁࣴ‫ز‬ஒ୘཰୔аషӝՐӻࣁЬǶ߄ 3.4 ࣁ‫ॺך‬ीᆉҔϐႝໆǴ୘཰୔‫ޑ‬ 1F-2F а୘཰୔Ҕႝໆ 3F а΢аՐӻ୔ҔႝໆǴՐӻ୔аՐӻӚኴቫҔ ႝໆǶаϦԄ(6)(7)ٰीᆉрᕴҔႝໆǶ ࣻ = Fn * Fe * Ga……(6). ࣻǺӚෂҔႝໆ FnǺኴቫኧ FeǺ‫؂‬ቫҔႝໆ GaǺय़ᑈ. A=σ௡ࣻୀଵ ‫(……ࣻܧ‬7). AǺᕴҔႝໆ ࣻǺӚෂҔႝໆ ࣻǺෂኧ. ߄ 3.4ġ ҁࣴ‫ز‬჏ကѱҔႝໆᆶኴቫϩᜪ΋ំ߄ ୘཰୔ Րӻ୔ ४΢‫ޑ‬Ҕႝໆ ४΢‫ޑ‬Ҕႝໆ ኴቫϩᜪ ኴቫϩᜪ 2 (ࡋ/ԃ/m ) (ࡋ/ԃ/m2) 1F-2 Fġ 127.13 1 F -2 Fġ 35.47 3 F -6 F 30.53 3 F -4 F 31.42 7 F а΢ 5 F а΢ 22.91 22.91 ၗ਑ٰྍǺ؇ӵᓪ(92)೿ѱՐӻ୔ຉᄂҔႝໆፓࢗ. 36.

(49) კ3.16ġ ჏ကѱ೿ѱीฝኧॶӦ‫ ׎‬CAD ۭკ(ъ৩ 100m). 3.3.1.6 Ӛෳᗺ‫ڬ‬ᜐ 100m ጄൎຉၰᆘϯᙟᇂ౗ϩ‫݋‬Б‫ݤ‬ ࣁ௖૸ຉၰᆘϯໆϐӭჲჹ೿ѱྕࡋϐቹៜǴҁࣴ‫ز‬ϩ‫݋‬჏ကѱຉ ၰϐᆘϯᙟᇂ౗Ƕϩ‫݋‬Б‫ݤ‬ӃਥᏵଯှ‫ࡋ݋‬ϐ჏ကѱ‫ྣޜ‬კǴаෳᗺࣁ ύЈъ৩ 10M ϐ༝୮ࣁጄൎǴᘏ‫ڗ‬კႽࡕа Photoshop ϐՅ༧Кфૈ࣮ ෌‫ނ‬Յ༧ϐႽનǶϐࡕǴճҔ EXCEL ीᆉ 87 ঁෳᗺϐ෌‫ނ‬ՅႽનǴӵ ϦԄ(8)Ƕ G=Pg/Fr*100……(8). GǺᆘϯᙟᇂ౗ PgǺъ৩ 100M ෌‫ނ‬ՅႽન FrǺъ৩ 100M ӄጄൎႽનॶ. ᆘϯᙟᇂ౗Ȑ%ȑ=Ȑӄ೽ᆘϯᅿ෌ࠟ‫׫ޔ‬ቹय़ᑈ/ᕴҔӦԶᑈȑØ100% ᆘϯᙟᇂ౗ࢂࡰᆘϯࠟ‫׫ޔ‬ቹय़ᑈϐ‫ک‬λ୔ҔӦ‫ޑ‬К౗Ƕᐋ‫ޑ‬ቹηǵ ៛Ϻଶً൑ёаύ໔ᅿ૛‫ޑ‬Бᑄ೿ёᆉΕᆘϯᙟᇂ౗ǴӢԜࢌ٤௃‫ݩ‬Π ᆘϯᙟᇂ౗ёૈຬၸ 60%Ƕ. 37.

(50) ! კ3.17ġ ᆘϯᅿᜪ !. (a)ᒧ‫ڗ‬ъ৩ 100M ༝ϐՅ༧Ⴝન. (b)ᒧ‫ڗ‬ъ৩ 100M ༝ϣᆘᙟϐՅ༧Ⴝન კ3.18ġ Յ༧КфૈҢཀკ. 38. !.

(51) ಃѤകǵ჏ကѱ೿ѱ዗৞மࡋፓ่ࢗ݀! 4.1 ྕࡋਔ໔ਠ҅ ࣴ‫ز‬ፓࢗа჏ကεᏢ਻ຝઠࣁ‫ۓڰ‬ઠǴճҔԜ‫ۓڰ‬ਠ҅ઠ‫ޑ‬ਔ໔ϐ ྕࡋᇤৡॶǴ‫؃‬рΟঁၡጕӚᢀෳᗺ‫ࡋྕޑ‬ᇤৡঅ҅ॶǴаዴߥӚᢀෳ ᗺ‫ڀॶࡋྕޑ‬Ԗӕ‫؁‬ෳໆϐᆒࡋǶӚᢀෳᗺ‫ࡋྕޑ‬ᆶਔ໔ӵаΠਠ҅Ǻ 1. ‫ۓڰ‬ਠ҅ઠ೽ϩ ‫؂ځڗ‬λਔਔ໔္‫ޑ‬ύ໔ਔ໔բࣁਠ҅୷ྗਔ໔ᗺǴ‫ٯ‬ӵ 1Ǻ00 ‫ ډ‬2Ǻ00 ‫ޑ‬ය໔ջа 1Ǻ30 ‫ॶྕ਻ޑ‬നࣁ೭ਔය‫ޑ‬ਠ҅୷ྗǴӧ ೭୔໔ϣ‫ঁ؂‬ਔ໔ᗺᆶԜਠ҅୷ྗਔ໔‫ࡋྕޑ‬ৡॶջࣁჴෳਔ ໔౽୏ઠϐਔ໔অ҅ॶǶ(ߕᒵ 1) 2. ჴෳਔ໔ਠ҅೽ϩ Ӣࣁҁࣴ‫܌ز‬Ҕϐ‫ۓڰ‬ਠ҅ઠྕࡋॶа 5 ϩដ΋฽ၗ਑Ǵ‫ॺך‬΋ ঁᗺѝԖ 2 ϩដѳ֡ၗ਑ॶǴ‫܌‬аค‫ݤ‬খӳᆶ‫ۓڰ‬ઠ‫ޑ‬ၗ਑ਔ໔ ᗺֹӄ಄ӝǴࡺаേʹ ϩដࣁ΋ঁ୔ୱǹ‫ٯ‬ӵǴঅ҅ॶϐਔ໔ࣁ 10Ǻ 32 Ϸ 10Ǻ37ǴԶჴෳਔ໔ࣁ 10Ǻ34Ǵ߾ᒧ᏷ਔ໔ࣁ 10Ǻ32 ‫ޑ‬অ ҅ॶǶ 3. ҁࣴ‫ࣁز‬Α‫ޕ‬ၰሺᏔϐ໔ࢂցԖྕࡋᇤৡǴ‫܌‬аᒧӧ 8 Д 2 В຾ Չჴෳനࡕ᛾ჴคሺᏔྕࡋᇤৡǴ‫܌‬аӧਠ҅೽ҽؒԖ٠คሺᏔ ਠ҅Ƕ. ٩ྣ΢ॊ‫؁‬ᡯਠ҅ࡕϐΟঁ୔ୱӚෳᗺ‫ࡋྕޑ‬Ǵӵ߄ 4.1-4.3Ƕ. 39.

(52) ߄ 4.1ġ ч୔ਠ҅ࡕྕࡋ ෳᗺ. ၡӜ. X. Y. ਔ໔. ྕࡋ ਠ҅ॶ ਠ҅ࡕ. N1 ҇௼ၡǵϘངၡ. 120.4422 23.47531 2018/7/28 10:25. 37.03. -0.84. 37.87. N2 ҇௼ၡǵ҇ғчၡ. 120.4466 23.4757 2018/7/28 10:27. 36.42. -0.84. 37.26. 120.45 23.47601 2018/7/28 10:29. 35.73. -0.84. 36.57. N4 ҇௼ၡǵֆስчၡ. 120.4536 23.47631 2018/7/28 10:30. 35.14. -0.84. 35.98. N5 ҇௼ၡǵᑼ‫ک‬ຉ. 120.4595 23.47686 2018/7/28 10:32. 35.02 -0.485. 35.51. N6 ε໡ၡ 2 ࢤǵߎᓪຉ. 120.4673 23.47725 2018/7/28 10:36. 35.37 -0.485. 35.86. N7 ε໡ၡ 1 ࢤǵ҇៾ܿၡ. 120.4826 23.48005 2018/7/28 10:39. 33.8. -0.84. 34.64. N8 ε໡ၡ 1 ࢤǵЎ໡ຉ. 120.4897 23.48122 2018/7/28 10:40. 33.04. -0.84. 33.88. N9 ҇៾ၡǵѠ᡼ԾٰНިҽ 120.4768 23.48387 2018/7/28 10:45. 33.09. 0.298. 32.8. N10 ҇៾ၡǵ༝ᅽຉ. 120.4645 23.48425 2018/7/28 10:48. 32.73. 0.613. 32.12. N11 ҇៾ၡǵཥғၡ. 120.4609 23.48386 2018/7/28 10:49. 33.01. 0.613. 32.4. N12 ҇៾ၡǵ‫ک‬ѳၡ. 120.456 23.48329 2018/7/28 10:51. 34.42. 0.613. 33.81. N13 ҇៾ၡǵֆስчၡ. 120.4524 23.48301 2018/7/28 10:53. 35.62. 0. 35.62. N14 ߏᄪຉǵЎϯၡ. 120.4489 23.48313 2018/7/28 10:54. 35.64. 0. 35.64. N15 ߏᄪຉǵ҇ғчၡ. 120.4459 23.48259 2018/7/28 10:56. 35.14. 0.768. 34.38. N16 ݅හܿၡǵ۸ֵၡ. 120.4535 23.48607 2018/7/28 11:00. 33.92. 0. 33.92. N17 ݅හܿၡǵᆢཥၡ. 120.4582 23.48701 2018/7/28 11:02. 34.34. 0. 34.34. N18 ݅හܿၡǵറܿၡ. 120.4636 23.48882 2018/7/28 11:09. 34.93. 0.229. 34.71. N19 ݅හܿၡǵᐽကၡ. 120.482 23.49458 2018/7/28 11:13. 34.43 -0.417. 34.85. N3 ҇௼ၡǵЎϯၡ. N20 റܿၡǵཥғၡ. 120.4588 23.49069 2018/7/28 11:18. 35.37. 0.485. 34.89. N21 റܿၡǵ۸ֵၡ. 120.4533 23.49018 2018/7/28 11:20. 35.59. 0.485. 35.11. N22 Ѡ݅ຉǵཥғၡ. 120.4549 23.4956 2018/7/28 11:23. 35.53. 0.485. 35.05. N23 ۸ֵၡǵཥғၡ. 120.4524 23.49603 2018/7/28 11:25. 35.97. 0.485. 35.49. 120.45 23.50135 2018/7/28 11:27. 35.49 -0.935. 36.43. 120.4445 23.51236 2018/7/28 11:30. 35.32 -0.935. 36.26. N24 ۸ֵၡǵӳѱӭ Costco N25 ۸ֵၡǵߥ۸ 1 ຉ. ! ! ! ! !. !. 40.

(53) ߄ 4.2ġ ෳᗺ. ၡӜ. ࠄ୔ਠ҅ࡕྕࡋ. X. Y. ਔ໔. ྕࡋ অ҅ॶ ਠ҅ࡕ. S1 ϶۸ၡǵଯ៓εၰ. 120.433346 23.476264 2018/7/28 10:30 33.34. -0.84. 34.18. S2 ϶۸ၡǵчෝၡ. 120.434445 23.477514 2018/7/28 10:32 33.35 -0.485. 33.84. S3 ᑫၲၡǵЎϯၡ. 120.443252 23.489094 2018/7/28 10:36 34.32 -0.485. 34.81. S4 റངၡ 1 ࢤǵԾҗၡ. 120.441893 23.484461 2018/7/28 10:38 34.89. -0.84. 35.73. S5 റངၡ 2 ࢤǵύᑫၡ. 120.438819 23.480729 2018/7/28 10:39 35.32. -0.84. 36.16. S6 റངၡ 2 ࢤǵ҇௼ၡ. 120.434516 23.475682 2018/7/28 10:41 35.08. -0.84. 35.92. 120.439425 23.472769 2018/7/28 10:43 34.76 0.298. 34.47. 120.444753 23.473295 2018/7/28 10:44. 34.8 0.298. 34.51. 120.44914 23.473683 2018/7/28 10:46 34.87 0.298. 34.58. 120.453805 23.474105 2018/7/28 10:47 35.45 0.613. 34.84. S11 ࠟླྀၡǵ‫ک‬ѳၡ. 120.45782 23.474469 2018/7/28 10:48 35.87 0.613. 35.26. S12 ࠟླྀၡǵᔆߒၡ. 120.461705 23.474876 2018/7/28 10:50 35.89 0.613. 35.28. S13 ᔆߒၡǵҥϘၡ. 120.467265 23.466098 2018/7/28 10:53 34.91. 0. 34.91. S14 ᔆߒၡǵᑫ཰ܿၡ. 120.464733 23.470835 2018/7/28 10:54 34.42. 0. 34.42. S15 ᑫ཰ܿၡǵᡏ‫ػ‬ၡ. 120.461017 23.469968 2018/7/28 10:55 34.16. 0. 34.16. S16 ᑫ཰ܿၡǵ࠹ߞຉ. 120.459376 23.469826 2018/7/28 10:56 34.19. 0. 34.19. S17 ᑫ཰ܿၡǵ୯๮ຉ. 120.449661 23.468653 2018/7/28 10:58 34.31 0.768. 33.55. S18 ᑫ཰ܿၡǵ҇ғࠄၡ. 120.446711 23.468611 2018/7/28 10:59 34.11 0.768. 33.35. 120.443 23.468225 2018/7/28 11:00 33.97 0.768. 33.21. 7. ࠟླྀၡǵཥ҇ၡ. S8 ࠟླྀၡǵཥᄪၡ S9 ࠟླྀၡǵ୯๮ຉ S10 ࠟླྀၡǵֆስࠄၡ. S19 ᑫ཰ՋၡǵϘངၡ S20 ཥ҇ၡǵख़ቼၡ. 120.44016 23.46575 2018/7/28 11:02 34.01. 0. 34.01. S21 ࠄ٧ၡǵᑫ཰Ջၡ. 120.435865 23.467517 2018/7/28 11:04 33.74. 0. 33.74. S22 Ш፣ 3 ࢤ଑ᙯၰ. 120.428647 23.464832 2018/7/28 11:06 33.66 0.229. 33.44. S23 Ш፣ 3 ࢤǵख़ቼၡ. 120.430719 23.462327 2018/7/28 11:09 34.12 0.229. 33.9. S24 Ш፣ 3 ࢤǵࠄ٧ၡ. 120.436571 23.460984 2018/7/28 11:11. 33.8 0.229. 33.58. S25 Ш፣ 3 ࢤǵཥ҇ၡ. 120.440752 23.461305 2018/7/28 11:12 33.52 -0.417. 33.94. S26 ཥ҇ၡǵࠄ٧ၡ. 120.438061 23.457888 2018/7/28 11:13 33.19 -0.417. 33.61. S27 ҇ғࠄၡǵШ፣ 4 ࢤ. 120.444085 23.461867 2018/7/28 11:21. 33.4 0.485. 32.92. 120.44862 23.462562 2018/7/28 11:22 33.66 0.485. 33.18. S28 Ш፣ 4 ࢤǵᑫӼຉ. S29 Ш፣ 4 ࢤǵε཰ຉ 172 ࡅ 120.450995. 23.4643 2018/7/28 11:23 33.78 0.485. 33.3. S30 Ш፣ 4 ࢤǵֆስࠄၡ. 120.454648 23.466087 2018/7/28 11:24 33.64 0.485. 33.16. S31 Ш፣ 4 ࢤǵҥϘၡ. 120.456469 23.462219 2018/7/28 11:29 33.38 -0.935. 34.32. S32 Ш፣ 4 ࢤǵᑫऍၡ. 120.457738 23.459561 2018/7/28 11:32 33.92 -0.935. 34.86. !. !. 41.

(54) ߄ 4.3ġ ෳᗺ. ၡӜ. X. Ջ୔ਠ҅ࡕྕࡋ ਔ໔. Y. চ‫ ࡋྕۈ‬অ҅ॶ ਠ҅ࡕ. W1 ύᑫၡǵҏξၡ. 120.4291 23.47269 2018/7/28 10:30. 34.32 -0.485. 34.81. W2 ߎξၡǵҏξၡ. 120.4246 23.47172 2018/7/28 10:31. 34.27 -0.485. 34.76. W3 ε๮ၡǵߎξၡ. 120.424 23.47405 2018/7/28 10:32. 34.05 -0.485. 34.54. W4 ύᑫၡǵε๮ၡ. 120.428 23.47498 2018/7/28 10:33. 33.98 -0.485. 34.47. W5 ύᑫၡǵεӕၡ. 120.4279 23.47719 2018/7/28 10:34. 33.91 -0.485. 34.4. W6 ύᑫၡǵчෝၡ. 120.4299 23.48018 2018/7/28 10:35. 33.71 -0.485. 34.2. W7 ύᑫၡǵΖቺၡ. 120.4311 23.48201 2018/7/28 10:36. 33.74. -0.84. 34.58. W8 ύᑫၡǵ϶ངၡ. 120.4339 23.48222 2018/7/28 10:37. 33.89. -0.84. 34.73. W9 ύᑫၡǵࡌ୯ၡ. 120.4363 23.48244 2018/7/28 10:38. 34.04. -0.84. 34.88. W10 ᑫၲၡǵԾҗၡ. 120.4379 23.48758 2018/7/28 10:41. 34. -0.84. 34.84. W11 ߥӼΒၡǵ϶ངၡ. 120.4387 23.49123 2018/7/28 10:43. 33.8 0.298. 33.51. W12 ϶ངၡǵЎϯၡ. 120.4451 23.49179 2018/7/28 10:44. 33.77 0.298. 33.48. W13 Ш፣ 1 ࢤǵЎϯၡ. 120.4438 23.49508 2018/7/28 10:48. 34.61 0.613. 34. W14 Ш፣ 1 ࢤǵԾҗၡ. 120.4308. 23.4931 2018/7/28 10:51. 34.38. 0. 34.38. W15 ϶ངၡǵчᑫຉ. 120.4338 23.48791 2018/7/28 10:53. 34.22. 0. 34.22. W16 чӼၡǵΖቺၡ. 120.4304 23.48866 2018/7/28 10:55. 34.08. 0. 34.08. W17 ᑫၲၡǵѤᆢၡ. 120.4279 23.48487 2018/7/28 10:58. 34.35 0.768. 33.59. W18 ѤᆢၡǵШ፣ 1 ࢤ. 120.4268 23.48875 2018/7/28 10:59. 34.27 0.768. 33.51. W19 чෝၡǵШ፣ 1 ࢤ. 120.4224 23.48454 2018/7/28 11:00. 34.29 0.768. 33.53. W20 чෝၡǵߥᅽၡ. 120.4066 23.48942 2018/7/28 11:03. 34.76. 0. 34.76. W21 чෝၡǵߥᅽ 1 ၡ. 120.4046 23.48996 2018/7/28 11:04. 34.8. 0. 34.8. W22 чෝၡǵ୶Ԯၡ. 120.3979. 34.81. 0. 34.81. W23 ଯ៓εၰǵ୶Ԯၡ. 120.3958 23.48927 2018/7/28 11:07. 35.01 0.229. 34.79. W24 ଯ៓εၰǵεྛၡ. 120.4125 23.48409 2018/7/28 11:10. 35.46 0.229. 35.24. W25 ଯ៓εၰǵШ፣ 2 ࢤ. 120.4208 23.48165 2018/7/28 11:12. 35.41 -0.417. 35.83. W26 ଯ៓εၰǵѤᆢၡ. 120.4249. 23.4793 2018/7/28 11:13. 35.3 -0.417. 35.72. W27 Ѥᆢၡǵεӕၡ. 120.4254. 23.4767 2018/7/28 11:14. 35.03 -0.417. 35.45. W28 εӕၡǵШ፣ 2 ࢤ. 120.4206 23.47563 2018/7/28 11:14. 34.79 -0.417. 35.21. 120.426 23.46601 2018/7/28 11:18. 34.7 0.485. 34.22. 120.4248 23.46449 2018/7/28 11:18. 34.75 0.485. 34.27. W29 Ш፣ 2 ࢤǵറངၡ 2 ࢤ W30 റངၡ 2 ࢤǵԾமຉ. 23.492 2018/7/28 11:06. 42.

(55) 4.2 ዗৞ፓ่ࢗ݀-қϺ 7 Д 28 ВқϺ዗৞ፓࢗϐচ‫ࡋྕۈ‬ᆶঅ่҅݀᏾౛‫ܭ‬კ 4.1 ᆶ 4.2 Ƕ ፓ่ࢗ݀ᡉҢǴ྽Ϻ 10 ᗺ዗ᗺࣁΟ୔ǴОًઠጄߕ߈Ϸ҇௼ၡǵ۸ֵၡ ԿറངၡҬ೯ᕷԆ‫ޑ‬ၡࢤǴ11 ᗺ዗ᗺࣁОًઠጄൎǵറངΒࢤǵЎϯ୘ ୮Ǵ12 ᗺࣁၨ዗ਔࢤԶ዗୔ࣁОًઠጄൎϷ҇௼ၡǵࠟླྀၡǵ๮ࠄଯ୘ ୔Ǵ13 ᗺ዗৞౜ຝ཮ၨܴᡉǴว౜ࠟླྀ୯λ୔ѰᜐԿࠟླྀଯࢎᐏǵ҇៾ ၡ༝ᕉԿ჏ကϦ༜ၡࢤǵύᑫၡǴԶើ዇୔ԖНୱ ϷၨӭᐋЕϷ჏ကଯ ύߕ߈ӢԖ჏ကѱϦ༜ᆶΒΒΖϦ༜‫܌‬аྕࡋၨեǶ7 Д 29 ВқϺ዗৞ ፓࢗϐচ‫ࡋྕۈ‬ᆶঅ่҅݀᏾౛‫ܭ‬კ 4.3 ᆶ 4.4 Ƕፓ่ࢗ݀ᡉҢǴ྽Ϻ዗ ᗺ 10 ᗺӧчෝၡШ፣ၡΒࢤၡαǴ11 ᗺӧύᑫၡԿЎϯၡ‫ޑ‬റངΒࢤǵ ҏξၡǴ12 ᗺӧֆስࠄၡǵ۸ֵၡԿറܿၡǵҏξၡǵчෝၡ΢ϐу‫ݨ‬ ઠǴ13 ᗺӧШ፣ၡ 3ǵ4 ࢤǵύᑫၡǵύᑫၡԿЎϯၡ‫ޑ‬റངΒࢤǵᆒ۸ ୯λߕ߈ǵ჏ကεᏢྕࡋଯǶ. კ4.1ġ 7 Д 28 В চ‫ࡋྕۈ‬қϺ዗৞ፓ่ࢗ݀. 43.