博碩士論文 993202093 完整後設資料紀錄

DC 欄位 語言
DC.contributor土木工程學系zh_TW
DC.creator袁培堯zh_TW
DC.creatorPei-yao Yuanen_US
dc.date.accessioned2012-7-30T07:39:07Z
dc.date.available2012-7-30T07:39:07Z
dc.date.issued2012
dc.identifier.urihttp://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=993202093
dc.contributor.department土木工程學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract土壤含水量在地表水循環中扮演關鍵角色,其含量是用來推估水循環之重要機制,如地表蒸發、植物蒸散以及區域降雨變率等能量交換作用,也影響當地之農業條件、環境保育與氣候變遷等議題。利用遙測技術可以大量而廣泛的獲得地表土壤含水量資訊,以進行長時期的地表含水量監測,目前遙測衛星AMSR-E(Advanced Microwave Scanning Radiometer for EOS)提供的全球土壤含水量產品影像,空間解析度為25公里,是最便捷的土壤含水量資訊,但解析度較差而無法滿足農業規劃或乾旱監測等需求。而使用MODIS(Moderate-resolution Imaging Spectroradiometer)衛星影像產生乾旱指數(Drought Index)以評估土壤溼度的方法已被證實可行,其空間解析度較高,但乾旱指數不具有物理單位,只能得到土壤相對溼度情形。 本研究是以MODIS衛星影像推估中美洲地區2010年與2011年的乾季土壤含水量。使用1公里解析度的MODIS多光譜影像,以近紅外光波段(Near Infrared, NIR)及短波紅外光波段(Short Wave Infrared, SWIR)計算常態化多波段乾旱指數(Normalized Multi-band Drought Index, NMDI),再以統計方法將NMDI指數與AMSR-E土壤含水量產品迴歸分析至1公里解析度,推估具有高空間解析度及物理單位的土壤含水量,以期能增加資料的應用層面與價值。 研究成果顯示,在植被密度較低的區域,NMDI指數與AMSR-E土壤含水量資料間具有明顯的相關性。利用NMDI指數估計土壤含水量時,成果與AMSR-E土壤含水量資料相比,其殘差在空間中具有規律分布,且殘差之RMSE大於AMSR-E資料本身的RMSE平均值,因此本研究利用最小二乘配置法的概念,利用Kriging方法計算局部系統誤差,成果顯示此方法可以有效降低檢核點的土壤含水量估計誤差,將誤差降至AMSR-E資料本身的最小誤差。而高解析度的土壤含水量推估成果與AMSR-E土壤含水量資料的乾溼分布情形非常相似,但仍需其他來源或地面監測站的資料才能進一步分析驗證。 zh_TW
dc.description.abstractSoil moisture is an important factor for the exchange of water between the land surface and plant transpiration. It has tremendous effects on agriculture, the environment and climate. It is hard to evaluate long term land surface dryness by field investigation or ground survey. Using remote sensing technology can get soil moisture information extensively. The Advanced Microwave Scanning Radiometer for EOS (AMSR-E) provide global soil moisture product, the spatial resolution is 25km. The spatial resolution is not good enough to satisfy the demand for agricultural planning or drought monitoring. In the literary, using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite image to observe land surface water content is feasible. A land surface drought index called Normalized Multi-Band Drought Index (NMDI) based on two short wave infrared (SWIR) channel in MODIS as the soil moisture sensitive band, is used for estimating land surface soil moisture, and the spatial resolution is up to 1km. The main objective of this study is to estimate soil moisture conditions of the Central American region using MODIS and AMSR-E data in 2010 and 2011 dry season. en_US
DC.subject土壤含水量zh_TW
DC.subjectMODIS影像zh_TW
DC.subjectAMSR-Ezh_TW
DC.subjectNMDI指數zh_TW
DC.subjectNMDIen_US
DC.subjectMODISen_US
DC.subjectAMSR-Een_US
DC.subjectSoil moistureen_US
DC.title利用MODIS與AMSR-E衛星資料推估地表土壤含水量zh_TW
dc.language.isozh-TWzh-TW
DC.titleUsing MODIS and AMSR-E Satellite Data to Estimate Land Surface Soil Moistureen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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