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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 余化龍,胡明哲 | |
| dc.contributor.author | Kam-Lon Chan | en |
| dc.contributor.author | 陳錦麟 | zh_TW |
| dc.date.accessioned | 2021-05-19T17:45:45Z | - |
| dc.date.available | 2021-08-07 | |
| dc.date.available | 2021-05-19T17:45:45Z | - |
| dc.date.copyright | 2018-08-07 | |
| dc.date.issued | 2018 | |
| dc.date.submitted | 2018-08-03 | |
| dc.identifier.citation | 王志添, & 陳錕山. (2003). 雷達影像多時處理研究. 航測及遙測學刊, 8(1), 47-56.
年佩芬. (2004). 利用合成孔徑雷達差分干涉技術觀測屏東地區地層下陷之研究. (碩士), 臺灣大學. 吳季, 劉浩, 閻敬業, 孫偉英, 張成, & 潘碑. (2009). 干涉式被動微波成像技術. 遙感技術與應用, 24(1), 1-12. 林宜徵. (2011). 應用 MODIS 衛星資料推估地表土壤含水量. 中央大學土木工程學系學位論文, 1-99. 林俐玲, 蔡義誌, & 游韋菁. (2008). 礫石敷蓋與混合對土壤沖蝕影響之研究. 中華水土保持學報, 39(2), 195-206. 邵芸, 廖靜娟, 范湘濤, & 劉浩. (2002). 水稻時域後向散射特性分析: 雷達衛星觀測與模型模擬結果對比. 遥感学报, 6(6), 440-450. 姜壽浩. (2017). 應用 Sentinel-1 合成孔徑雷達影像對舊有崩塌進行再發性評估. 中央大學太空及遙測研究中心. 徐逸祥. (2011). 光學式衛星影像雲層處理之研究. (博士), 國立臺灣大學. 張世駿, 江介倫, 吳進龍, 鄭克聲, & 陳增壽. (2006). 衛星遙測影像應用於地表變遷偵測之研究. 農業工程學報, 52(3), 21-31. 莊麒弘. (2017). 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. 臺灣大學生物環境系統工程學研究所學位論文, 1-76. 陳俊斌. (2016). 應用Sentinel-1A合成孔徑雷達影像於臺灣中部水稻田之判釋. (碩士論文), 國立中央大學. 陳俊愷, 林伯勳, 蕭震洋, 洪寶發, & 鐘啟榮. (2016). 應用合成孔徑雷達干涉技術評估集水區災害規模及治理成效. 中興工程(133), 35-44. 彭炳勳, 謝依達, & 陳朝圳. (2008). 空載光達雷射穿透率指數與柳杉林葉面積指數之關係探討. 臺灣林業科學, 23(S), s63-s73. 游保杉. (2003). 遙測技術應用於集水區水文之研究 (一). 黃孟涵. (2006). 以合成孔徑雷達干涉法研究台灣之地殼變形. 臺灣大學. Available from Airiti AiritiLibrary database. (2006年) 經濟部水利署. (2016). 中華民國105年臺灣水文年報. 經濟部水利署. 蔡博閎, & 林昭宏. 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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/7531 | - |
| dc.description.abstract | 土壤含水量為一在氣象學、水文學、農業生態學等的重要參數，同時也影響全球水循環、植物蒸發散情形等機制運作。在農業中土壤含水量影響著農業配水的分配；在坡地災害中也作為土石流預警的一項重要參考指標。然而土壤含水量的量測常常受到量測儀器的時空間局限性，要浪費大量的人力物力才能取得大範圍及長時間的監測資訊。但若能使用衛星遙測技術的優點來進行土壤含水量的推估，將可取得大範面長時間的監測資訊，這必然會對自然環境有更進一步的了解。
本文將應用歐洲太空總署ESA的哥白尼計畫-Sentinel系列任務之開放衛星資料—Sentinel-1合成孔徑雷達微波波段資料及Sentinel-2多光譜資料來進行土壤含水量的推估。合成孔徑雷達的成像資訊為後向散射係數，而後向散射係散與土壤含水量有直接的關係。因此本文以兩者關係的觀點角度切入，探討台灣地區兩者之間的關係，並以水雲模型來消除植被覆蓋所造成的影響。水雲模型的參數中，葉面積指數及植被含水量無法直接從Sentinel-1影像獲取，需要以Sentinel-2的影像反射率，配合PROSAIL模型反演得出葉面積指數及植被含水量。 本文將以2017年全年的Sentinel-1及Sentinel-2資料，並與中央大學測站的土壤含水量進行比較，進而觀察後向散射係數與不同深度土壤含水量之相關性。結果顯示雷達後向散射係數與中央大學水文氣象測站的深度10公分的土壤含水量有比較好的相關性，相關係數R-square為0.53，並把回歸公式套用到桃園及石門灌區，觀察該區土壤含水量的時間變化，並以石門灌區內的皮寮溪為例作討論。 | zh_TW |
| dc.description.abstract | Soil moisture is one of the important parameters in meteorology, hydrology as well as agricultural, which also affect the operation of the mechanism such as global water cycle and plant evapotranspiration. Soil moisture is one of the factor which affect landslide as well as agriculture. However, the measurement of soil moisture is often limited by the spatial limitations of the observation instrument. If remote sensing data can be used to estimate soil moisture, it can have a large area and time series monitoring of soil moisture and that can increase the efficiency of environmental management and monitoring.
This paper will use the Sentinel-1 C band SAR & Sentinel-2 multi-spectrum satellite data which come from Copernicus Programme of ESA (European Space Agency) to estimate soil moisture. The imaging principle of SAR is backscatter, which is directly related to soil moisture. Therefore, this paper will use the point of view of their relationship to estimate their situation in Taiwan region. Water-cloud model is used to reduce the vegetation cover affect. In water-cloud model, there are two parameters: LAI and canopy water content cannot be obtained directly from Sentinel-1 satellite. That’s why Sentinel-2 satellite reflectance data are used to do inverse calculation of LAI and canopy water content using PROSAIL. In this paper, Sentinel-1 & Sentinel-2 satellite data for the whole year 2017 are used and compare with the in situ soil moisture data which come from surface hydrology laboratory in National Central University, as to observe their relationship. Results show that C band radar backscatter coefficient the depth of 10cm soil moisture have a good correlation, the correlation coefficient R-square is 0.53. Therefore, apply their relationship to Taoyuan & Shihmen irrigation area, observe the time series change in 2017 of the area, and use Piliao river as a case study for discussion. | en |
| dc.description.provenance | Made available in DSpace on 2021-05-19T17:45:45Z (GMT). No. of bitstreams: 1 ntu-107-R05622033-1.pdf: 40667699 bytes, checksum: 47feca52fe90822afca6745078dba842 (MD5) Previous issue date: 2018 | en |
| dc.description.tableofcontents | 誌謝 ii
摘要 iii Abstract iv 目錄 v 圖目錄 vii 表目錄 ix 第一章 前言 1 第二章 文獻回顧 3 2.1 被動式光學雷達推估土壤含水量 3 2.2 主動式微波雷達 4 2.2.1 合成孔徑雷達原理 5 2.2.2 影響合成孔徑雷達成像之因素 6 2.2.3 主動式合成孔徑雷達推估土壤含水量 7 2.3 被動式微波雷達 10 2.4 葉面積指數(Leaf Area Index, LAI) 10 第三章 研究區域及材料 12 3.1 研究區域 12 3.2 衛星遙測資料 – Sentinel-1 13 3.2.1 Sentinel-1產品介紹 13 3.2.2 Sentinel-1衛星影像擷取 14 3.2.3 Sentinel-1衛星資料處理 15 3.3 衛星遙測資料 – Sentinel-2 17 3.3.1 Sentinel-2產品介紹 17 3.3.2 Sentinel-2衛星影像擷取 18 3.3.3 Sentinel-2衛星資料處理 19 3.3.4 雲遮蔽的影響 21 3.4 中央大學水文氣象測站土壤含水量資料 22 第四章 研究方法及流程 24 4.1 研究流程 24 4.2 Water-Cloud Model水雲模型 24 4.3 PROSAIL輻射傳輸模型 26 第五章 結果與討論 29 5.1 中央大學水文氣象測站土壤含水量資料與後向散射係數作比較 29 5.2 桃園石門灌區 31 5.3 討論 39 第六章 結論及建議 51 第七章 參考文獻 53 | |
| dc.language.iso | zh-TW | |
| dc.title | 利用Sentinel-1 & 2遙測影像推估土壤含水量空間分佈－以桃園石門灌區為例 | zh_TW |
| dc.title | Using Sentinel-1 & 2 data to estimate spatial distribution of soil moisture – A case study of Taoyuan and Shimen Irrigation area | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳主惠,黃倬英 | |
| dc.subject.keyword | 土壤含水量,合成孔徑雷達,衛星遙測,水雲模型,PROSAIL輻射傳輸模型, | zh_TW |
| dc.subject.keyword | soil moisture,synthetic aperture radar,remote sensing,water-cloud model,PROSAIL, | en |
| dc.relation.page | 57 | |
| dc.identifier.doi | 10.6342/NTU201802444 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2018-08-03 | |
| 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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