Using GIS in passive microwave soil moisture mapping and geostatistical analysis

Abstract

Soil moisture is an important hydrologic variable in both natural and agricultural ecosystems. Recent experiments, based on remote sensing data, provided observations of soil moisture distributions at a regional scale. One of the instruments is the Electronically Scanned Thinned Array Radiometer (ESTAR). Deployed on the aircraft, it measures brightness temperature (with the spatial resolution about 400 m) that can be converted into estimates of volumetric soil moisture. The soil moisture retrieval algorithm requires additional data layers (like soil physical temperature, land cover, and soil texture) that come from different sources and have to be combined together in a uniform GIS. The objective of this paper is to report results of the GIS use to map soil surface moisture from passive microwave measurements and to quantify spatial structure of soil moisture distributions. The data were collected across a 10 000 km 2 area in Oklahoma during June and July 1997. The precipitation data and ground measurements from the test sites were also incorporated into GIS. The GIS data layers enable soil moisture distribution analysis with geostatistical tools. Semi-variograms of soil moisture were nested and showed the presence of two scales. Rainfall was the dominant factor influencing soil moisture distribution at the regional scale, whereas soil texture was important at the local scale. Information about soil moisture, obtained with remote sensing techniques over space and time, and organized in a GIS with complementary environmental data layers, can be used in landscape pattern analysis, landscape models, land use assessment and management.