Improving Spatial Soil Moisture Representation through the Integration of SMAP and PROBA-V Products
文献类型： 外文期刊
作者： Fan, Shu-Di 1 ; Hu, Yue-Ming 1 ; Wang, Lu 1 ; Liu, Zhen-Hua 1 ; Shi, Zhou 9 ; Wu, Wen-Bin 10 ; Pan, Yu-Chun 11 ; Wang, Guan 1 ;
作者机构： 1.South China Agr Univ, Coll Nat Resources & Environm, Guangzhou 510642, Guangdong, Peoples R China
2.South China Agr Univ, Key Lab Construct Land Transformat, Minist Land & Resources, Guangzhou 510642, Guangdong, Peoples R China
3.South China Agr Univ, Guangdong Prov Key Lab Land Use & Consolidat, Guangzhou 10642, Guangdong, Peoples R China
4.South China Agr Univ, Guangdong Prov Engn Res Ctr Land Informat Technol, Guangzhou 510642, Guangdong, Peoples R China
5.Univ Elect Sci China, Sch Resources & Environm, Chengdu 610054, Sichuan, Peoples R China
6.SIUC, Dept Geog & Environm Resources, Coll Liberal Arts, Carbondale, IL 62901 USA
7.Hong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Hong Kong 999077, Hong Kong, Peoples R China
8.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA
9.Zhejiang Univ, Inst Agr Remote Sensing & Informat Syst, Hangzhou 310029, Zhejiang, Peoples R China
10.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China
11.Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
关键词： soil moisture; temperature vegetation drought index; downscaling; SMAP; PROBA-V
期刊名称：SUSTAINABILITY （ 影响因子：3.251； 五年影响因子：3.473 ）
ISSN： 2071-1050
年卷期： 2018 年 10 卷 10 期
页码：
收录情况： SCI
摘要： To increase the spatial resolution of Soil Moisture Active Passive (SMAP), this study modifies the downscaling factor model based on the Temperature Vegetation Drought Index (TVDI) using data from the Project for On-Board Autonomy (PROBA-V). In the modified model, TVDI parameters were derived from the temperature-vegetation space and the Enhanced Vegetation Index (EVI). This study was conducted in the north China region using SMAP, PROBA-V, and Moderate Resolution Imaging Spectroradiometer satellite images. The 9-km spatial resolution SMAP data was downscaled to 0.3-km spatial resolution soil moisture using a modified downscaling method. Downscaling accuracies from the original and modified downscaling factor models were compared based on field observations. The results show that both methods generated similar spatial distributions in which soil moisture estimates increased as vegetation coverage increased from built-up areas to forest. However, based on the root mean square error between observations and estimations, the modified model demonstrated an increased estimation accuracy of 4.2% for soil moisture compared to the original method. This study also implies that downscaled soil moisture shows promise as a data source for subsequent watershed scale studies.
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