A GIS framework for surface-layer soil moisture estimation combining satellite radar measurements and land surface modeling with soil physical property estimation

被引：31
作者：
Tischler, M.
Garcia, M.
Peters-Lidard, C.
Moran, M. S.
Miller, S.
Thoma, D.
Kumar, S.
Geiger, J.
机构：
[1] USDA ARS, Walnut Gulch Expt Watershed, SW Watershed Res Ctr, Tucson, AZ 85719 USA
[2] Univ Wyoming, Dept Renewable Resources, Laramie, WY 82071 USA
[3] NASA, Goddard Space Flight Ctr, Univ Maryland Baltimore Cty, Greenbelt, MD 20771 USA
[4] USA, Corps Engineers, Engn Res & Dev Ctr, Topog Engn Ctr, Alexandria, VA 22312 USA
来源：
ENVIRONMENTAL MODELLING & SOFTWARE | 2007年 / 22卷 / 06期
关键词：
GIS; ARMS; model integration; soil moisture; land information system; parameter estimation;
D O I：
10.1016/j.envsoft.2006.05.022
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
A GIS framework, the Army Remote Moisture System (ARMS), has been developed to link the Land Information System (LIS), a high performance land surface modeling and data assimilation system, with remotely sensed measurements of soil moisture to provide a high resolution estimation of soil moisture in the near surface. ARMS uses available soil (soil texture, porosity, K-sat), land cover (vegetation type, LAI, Fraction of Greenness), and atmospheric data (Albedo) in standardized vector and raster GIS data formats at multiple scales, in addition to climatological forcing data and precipitation. PEST (Parameter EStimation Tool) was integrated into the process to optimize soil porosity and saturated hydraulic conductivity (A(sat)), using the remotely sensed measurements, in order to provide a more accurate estimate of the soil moisture. The modeling process is controlled by the user through a graphical interface developed as part of the ArcMap component of ESRI ArcGIS. Published by Elsevier Ltd.
引用
收藏
页码：891 / 898
页数：8
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