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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 余化龍(Hwa-Lung Yu) | |
dc.contributor.author | Chi-Hung Chuang | en |
dc.contributor.author | 莊麒弘 | zh_TW |
dc.date.accessioned | 2021-06-17T02:28:21Z | - |
dc.date.available | 2019-08-24 | |
dc.date.copyright | 2017-08-24 | |
dc.date.issued | 2017 | |
dc.date.submitted | 2017-08-18 | |
dc.identifier.citation | Allard, D., et al. (2011). 'An efficient maximum entropy approach for categorical variable prediction.' European Journal of Soil Science 62(3): 381-393.
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68634 | - |
dc.description.abstract | 土壤含水量為一在氣象、水文及農業上的重要參數之一,影響了地表水循環、植物蒸發散情形等機制的運作,且降雨臨前土壤含水量於坡地災害的預警上為一重要參考指標。然而土壤含水量的量測常受限於觀測儀器的空間侷限性,若能利用衛星遙測技術所取得的影像資訊,來推估取得土壤含水量,將可取得大範圍面積之土壤含水量資訊,進而對自然環境能有更完善的了解與掌握。
本文將應用美國太空總署的中尺度影像光譜儀計畫─MODIS (Moderate Resolution Imaging Spectroradiometer)的開放衛星資料來進行土壤含水量的推估。土壤含水量的推估演算部分,本文將由蒸發散的觀點角度來切入,進行蒸發散比率的計算。蒸發散比率為實際蒸發散量與潛勢蒸發散的比值,可藉由地表能量平衡方程式的關係來求得,演算法部分使用地表能量平衡演算法─SEBAL(Surface Energy Balance Algorithm for Land),並結合地表溫度與植生指標所建立之二維空間關係來進行SEBAL演算法的極端值選取,以此進行蒸發散比率之演算,進而推估土壤含水量情形。 本文將以MODIS每八天合成之衛星資料進行2015年全台灣之蒸發散比率演算,並與水土保持局土石流觀測站的土壤含水量觀測值做比較,進而觀察此二參數間之相關性。結果顯示衛星遙測推估之蒸發散比率能表現出土壤含水量的變化趨勢,兩者之間存在一自然對數之關係,相關係數R^2表現因不同水保局實地觀測站情形有所不同,介於0.3至0.7之間。 | zh_TW |
dc.description.abstract | Soil water content is one of the important parameters in meteorology, hydrology and agriculture, which affects the operation of the mechanism such as surface water circulation and plant evapotranspiration, and the soil moisture before rainfall is an important reference index on slope disaster. However, the measurement of soil water content is often limited by the spatial limitations of the observation instrument. If the image information obtained by satellite remote sensing technology can be used to estimate the soil water content, the soil moisture content of large area can be obtained.
This paper will use the satellite data from the MODIS (Moderate Resolution Imaging Spectroradiometer) to estimate the soil water content. The calculation part of the estimation of soil water content, this paper will use the point of view of evaporation, the calculation of the evaporative fraction. The ratio of actual evapotranspiration and the potential evapotranspiration can be obtained by the relationship of the surface energy balance equation, and the surface energy balance algorithm, SEBAL (Surface Energy Balance Algorithm for Land), is used. Combined with the two-dimensional relationship between the surface temperature and the vegetation index to select the extreme value of the SEBAL algorithm to calculate the evaporative fraction, and then estimate the soil water content. In this paper, we will use the satellite data of MODIS every eight days to calculate the evapotranspiration ratio of Taiwan in 2015 and compare it with the soil moisture content of the soil and water conservation bureau and soil and water conservation station, and then observe the correlation between the two parameters. The results show that the evapotranspiration ratio estimated by satellite telemetry can show the trend of soil water content, and there is a natural logarithm relationship between the two. The correlation coefficient R-square is different due to the different situation of the site of the Soil and Water Conservation Bureau, Between 0.3 and 0.7. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T02:28:21Z (GMT). No. of bitstreams: 1 ntu-106-R04622032-1.pdf: 4434316 bytes, checksum: 38a1ae4f79ad01780ac77aa8002e59b3 (MD5) Previous issue date: 2017 | en |
dc.description.tableofcontents | 誌謝 i
中文摘要 ii 英文摘要 iii 第一章 前言 1 第二章 文獻回顧 4 2.1 被動式微波感測器 5 2.2 主動式微波感測器 6 2.3 被動光學式感測器 7 2.4 土壤含水量指標─TVDI(Temperature Vegetation Dryness Index) 8 2.5 土壤含水量指標─CWSI(Crop Water Stress Index) 10 2.6 蒸發散比率─EF(Evaporative Fraction) 11 第三章 研究材料 14 3.1 衛星遙測資料─MODIS 14 3.1.1 MODIS產品─MCD12Q1 16 3.1.2 MODIS產品─MCD43B3 17 3.1.3 MODIS產品─MOD11A2 17 3.1.4 MODIS產品─MOD13A2 17 3.1.5 MODIS衛星影像處理 18 3.2 中央氣象局資料 21 3.2.1 氣溫資料推估 22 3.2.2 風速資料推估 23 3.3 水保局土壤含水量資料 24 第四章 研究方法 26 4.1 SEBAL 26 4.1.1 淨輻射能量(Net Radiation, Rn) 27 4.1.2 土壤熱通量(Soil Heat flux, G) 29 4.1.3 可感熱通量(Sensible Heat flux, H) 29 4.2 T-SEBAL 34 第五章 結果與討論 36 5.1 Ts-EVI空間冷熱點選取結果 36 5.2 EF指標與水保局土石流觀測站土壤含水率資料比較 37 5.2.1 九份二山土石流觀測站 37 5.2.2 豐丘土石流觀測站 38 5.2.3 神木土石流觀測站 39 5.2.4 羌黃坑土石流觀測站 40 5.2.5 集來土石流觀測站 41 5.2.6 來義土石流觀測站 42 5.2.7 大鳥土石流觀測站 43 5.3 討論 44 第六章 結論與建議 63 附錄一 MODIS產品分層基本資料 70 附錄二 Hellman coefficient與地表覆蓋種類對照表 75 附錄三 中央氣象局局屬測站基本資料 76 | |
dc.language.iso | zh-TW | |
dc.title | 應用MODIS衛星資料演算蒸發散比率推估台灣土壤含水量情形 | zh_TW |
dc.title | Using MODIS Data to estimate Taiwan Soil Moisture by Evaporative Fraction | en |
dc.type | Thesis | |
dc.date.schoolyear | 105-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 謝正義(Cheng-Yi Hsieh),許少瑜(Shao-Yu Hsu),黃倬英(Cho-Ying Huang),陳主惠(Chu-Hui Chen) | |
dc.subject.keyword | 土壤含水量,衛星遙測,MODIS影像,蒸發散比率,台灣地區, | zh_TW |
dc.subject.keyword | soil moisture,satellite remote sensing,MODIS,evaporative fraction,Taiwan, | en |
dc.relation.page | 76 | |
dc.identifier.doi | 10.6342/NTU201703745 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2017-08-18 | |
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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