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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 鄭克聲(Ke-Sheng Cheng) | |
dc.contributor.author | Fang-Tzu Kuo | en |
dc.contributor.author | 郭芳慈 | zh_TW |
dc.date.accessioned | 2021-06-13T08:02:21Z | - |
dc.date.available | 2005-07-28 | |
dc.date.copyright | 2005-07-28 | |
dc.date.issued | 2005 | |
dc.date.submitted | 2005-07-22 | |
dc.identifier.citation | 1. 江良印,(1998),紋理特徵應用於遙測影像判釋之理論研究,國立臺灣大學生物環境系統工程研究所碩士論文。
2. 沈 鴻,(1978),生物環境小氣候學,台北市徐氏基金會。 3. 吳淑麗、李選卿、謝振環和陳鈞華,(1995),水田對三生功能效益評估方法之量化研究,曹公農業水利研究發展基金會。 4. 吳富春、沈易徵,(2000),水田微氣候模式之建立與應用,農業工程學報,第四十八卷第一期,第10-23頁。 5. 陳姜琦,(2002),應用衛星遙測於區域蒸發散量之估算,國立成功大學水利及海洋工程研究所碩士論文。 6. 陳鈞華,(2002),水田蒸發散量對區域涼化作用功能效益評估之研究,國立臺灣大學生物環境系統工程研究所博士論文。 7. 曾忠一,(1983),大氣遙測原理與應用,中央研究院物理研究所。 8. 曾忠一,(1988),大氣衛星遙測學,國立編譯館主編。 9. 劉俊志,(2000),克利金空間推估應用於控制點選取與影像幾何校正,國立臺灣大學生物環境系統工程研究所碩士論文。 10. 歐陽鍾裕 譯,(1986),遙感探測學,大中國圖書公司。 11. 鍾譯靚,(2001),利用衛星遙測估算蒸發散量與熱通量之研究,國立台灣大學土木工程研究所碩士論文。 12. 簡文煥,(2004),應用大地衛星於區域地表溫度和緩效能之研究,中華大學土木工程研究所碩士論文。 13. Campbell, Gaylon S. and Norman, John M., 1998. An Introduction to Environmental Biophysics, Springer-Verlag New York, Inc. 14. Conway, Eric D., 1997. An Introduction to satellite image interpretation, The John Hopkins University Press, Baltimore and London. 15. Florio, E.N., Lele, S.R., Chang, Y.Chi, Sterner, R. and Glass, G.E., 2004. Integrating AVHRR Satellite Data and NOAA Ground Observations to Predict Surface Air Temperature: A Statistical approach. International Journal of Remote Sensing, 25(15): 2979-2994. 16. Gallo, K.P., McNab, A.L., Karl, T.R., Brown, J.F., Hood, J.J. and Tarpley, J.D., 1993. The Use NOAA AVHRR Data for Assessment of the Urban Heat Island Effect. Journal of Applied Meteorology, 32(5): 899-908. 17. Lillesand, Thomas M. and Kiefer, Ralph W., 2000, Remote Sensing and Image Interpretation, John Wiley & Sons, Inc. 18. Ottle, C. and Vidal-Madjar, D., 1992. Estimation of Land Surface Temperature with NOAA9 Data. Remote Sensing of Environment, 40: 27-41. 19. Price, John C, 1983. Estimating Surface Temperatures from Satellite Thermal Infrared Data–A Simple Formulation for the Atmospheric Effect. Remote Sensing of Environment, 13: 353-361. 20. Price, John C, 1984. Land Surface Temperature Measurements from The Split Window Channels of The NOAA7 Advanced Very High Resolution Radiometer .Journal of Geophysical Research, 89: 7231-7237. 21. Price, John C, 1990. Using Spatial Context in Satellite Data to Infer Regional Scale Evapotranspiration .IEEE Transactions on Geoscience and Remote Sensing, 28(5): 940-948. 22. Saunders, R.W. and Kriebel, K.T., 1988. An Improved method for Detecting Clear Sky and Cloudy Radiance from AVHRR Data. International Journal of Remote Sensing, 9(1): 123-150. 23. Yokohari, M., Brown, R.D., Kato, Y. and Moriyama, H., 1997. Effects of Paddy Fields on Summertime Air and Surface Temperatures in Urban Fringe Areas of Tokyo, Japan. Landscape and Urban Planning, 38: 1-11. 24. Yokohari, M., Brown, R.D., Kato, Y. and Shori, Y., 2001. The Cooling Effect of Paddy Fields on Summertime Air Temperatures in Residential Tokyo, Japan. Landscape and Urban Planning, 53: 17-27. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/36478 | - |
dc.description.abstract | 水田因湛水,其蒸發散作用旺盛,且熱容量較乾燥地表土壤高,對熱流具有調節作用,能舒緩氣溫、地溫及調節濕度等變異,如日間之涼化作用、日夜溫差縮小。前人應用遙測技術評估水田對周圍環境之涼化作用影響時,僅利用地表溫度進行分析,未考量空氣溫度之變化。因此本研究針對桃園地區進行現地實驗,量測四種地貌類別之地表與空氣溫度,建立其轉換關係式,並結合多時段、多光譜、多空間解析度之衛星影像,評估水田對週邊環境空氣溫度之影響。
研究內容包括:(1)影像處理:NOAA衛星影像之軌道參數校正、幾何校正及濾雲(2)地表地貌分類:利用SPOT多光譜影像,進行最大概似法分類(3)現地實驗:建立地表和空氣溫度之轉換關係式(4)推估四種類別之地表溫度:採用最小平方法推求。 研究結果顯示,利用現地試驗建立地表與空氣溫度之轉換關係式,其 值最高達0.91。當水田百分比增加時,空氣溫度與日夜地表溫差值皆會隨之降低,而水田面積百分比最少和最多時,其空氣溫度差異可達2.83℃,日夜地表溫差值差異可達4.03℃;反之,當建地百分比增加時,其趨勢恰好相反,而建地面積百分比最少和最多時,其空氣溫度差異可達2.04℃,日夜地表溫差值差異可達6.27℃。由此可知,水田面積愈多其涼化作用及縮小日夜溫差之效益愈顯著。 | zh_TW |
dc.description.abstract | Because of deep water, the vigorous evapotranspiration and the higher heat capacity are the major characteristics of paddy fields which definitely have the functions of regulating thermal current, easing air and surface temperature, and adjusting humidity and other variations, such as cooling effect of daytime and shortening diurnal difference of temperature. The predecessors assessed the cooling effect of paddy field on ambient environment by remote sensing, it only use surface temperature without considering the change of air temperature. By selecting Taoyuan as the site of field measurement, the research will shows the transformation of four landcovers by measuring their surface and air temperatures. Otherwise, it is expected to assess the effect of paddy on ambient air temperature by combining the satellite images of multi-time, multi-spectrum and multi-space resolution.
The main research contents are: (1) The process of images: It is going to treat geometric correction and detect cloud in NOAA satellite images. (2) Landcover classification: it is expected to use the maximum likelihood classifier to classify by multi-spectrum SPOT images. (3) Field measurement: it is expected to set a transformation between surface and air temperature. (4) Estimating surface temperature of four landcovers: the major method is least square regression. The result of the research shows the value of in the transformation between surface and air temperature by field measurement is near 0.91. With the increasing percentages of paddy fields, air temperature and diurnal difference of surface temperature will decrease. Otherwise, comparing the most and the least percentages of paddy fields, the difference of air temperature could be 2.83℃; the diurnal difference of surface temperature could be 4.03℃. However, the increasing percentages of buildings will show a contrast result since the difference of air temperature could be 2.04℃ and the diurnal difference of surface temperature could be 6.27℃ by comparing the most and the least percentages of buildings. In other words, the cooling effect and shortening the diurnal difference of temperature would be significant with the increasing percentages of paddy fields. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T08:02:21Z (GMT). No. of bitstreams: 1 ntu-94-R92622025-1.pdf: 1004897 bytes, checksum: e5e0257a7b5d04d32f37770294eca4d3 (MD5) Previous issue date: 2005 | en |
dc.description.tableofcontents | 目錄 I
圖目錄 III 表目錄 V 中文摘要 VI Abstract VII 第一章 緒論 1 1-1前言 1 1-2研究目的 2 1-3文獻回顧 3 第二章 研究理論 7 2-1基本遙測原理 7 2-2 地表溫度 11 2-3影像分類原理 14 2-3-1監督式分類 14 2-3-2非監督式分類 19 2-3-3分類之精確度評估 19 2-4水田涼化作用 22 第三章 資料特性 26 3-1氣象衛星之簡介 26 3-1-1氣象衛星系統 26 3-1-2 NOAA氣象衛星 27 3-2 資源衛星之簡介 28 3-3資料之收集 29 第四章 研究內容 32 4-1研究流程 32 4-2研究地區 33 4-3影像處理 33 4-4地表地貌分類 37 4-5現地試驗 37 4-6推估各類別之地表溫度 38 第五章 結果與討論 47 5-1地貌分類結果 47 5-2地表溫度 47 5-3推估各類別地表溫度之結果 48 5-4實地量測結果 49 5-5水田之涼化效益 49 5-6水田具有緩和日夜地表溫差值之效益 50 第六章 結論 65 參考文獻 67 | |
dc.language.iso | zh-TW | |
dc.title | 水田對週邊環境空氣溫度之影響評估 | zh_TW |
dc.title | Assessing the Effect of Paddy on Ambient Air Temperature | en |
dc.type | Thesis | |
dc.date.schoolyear | 93-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 張斐章(Fi-John Chang),游保杉(Pao-Shan Yu),黃文政(Wen-Cheng Huang) | |
dc.subject.keyword | 水田,遙測影像,涼化作用,日夜溫差,NOAA影像, | zh_TW |
dc.subject.keyword | paddy field,satellite image,cooling effect,diurnal difference of temperature,NOAA image, | en |
dc.relation.page | 70 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2005-07-22 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 生物環境系統工程學研究所 | zh_TW |
顯示於系所單位: | 生物環境系統工程學系 |
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