Regional-scale soil moisture monitoring using NOAA/AVHRR data

Regional-scale soil moisture is important information in the areas of agriculture, hydrology, climatic modeling, and global environmental change. The problems with conventional techniques, such as field surveys and meteorological methods, for monitoring soil moisture include the inability to detect subtle differences in surface wetness across geographic space and the lack of moisture data in a timely fashion. The purpose of the research was to develop a means of measuring the regional-scale root-zone soil moisture content using remote-sensing techniques. To accomplish this goal, a methodology was established and software was developed which make use of both thermal and visible channels of NOAA/AVHRR data in conjunction with the ground meteorological data to infer the regional-scale root-zone soil moisture content and other moisture-related surface physical quantities. The software development occurred within the context of a Geographic Information System (GIS). The research results indicated that AVHRR data can be used to detect and measure both temporal and spatial changes in root-zone soil moisture and certain other surface physical quantities such as daily evapotranspiration, canopy temperature, diurnal heat capacity, and net radiation, and that this can be done on a regional scale in an operational mode. In addition, the research concluded that, theoretically, the Normalized Vegetation Index (NVI or NDVI) is equal to the foilage shielding factor, and that NVI is not a spatially extendable indicator of soil moisture condition. The research demonstrated that only a thermal image, either day or night, is necessary to obtain soil moisture information. The work also suggested that, with a given ground meteorological condition, soil moisture information is functionally related to the day or night surface temperature, foliage shielding factor, and incoming solar radiation. A second order regression model was used to describe the relationship. The Palmer Drought Severity Index (PDSI) correlated well with daily evapotranspiration, while the Crop Moisture Index (CMI) varied with both the root-zone moisture content and canopy temperature