9 research outputs found
Joint microwave and infrared studies for soil moisture determination
The feasibility of using a combined microwave-thermal infrared system to determine soil moisture content is addressed. Of particular concern are bare soils. The theoretical basis for microwave emission from soils and the transport of heat and moisture in soils is presented. Also, a description is given of the results of two field experiments held during vernal months in the San Joaquin Valley of California
Geologic application of thermal inertia imaging using HCMM data
Three test sites in the western US were selected to discriminate among surface geologic materials on the basis of their thermal properties as determined from HCMM data. Attempts to determine quantitatively accurate thermal inertia values from HCMM digital data met with only partial success due to the effects of sensor miscalibrations, radiative transfer in the atmosphere, and varying meteorology and elevation across a scene. In most instances, apparent thermal inertia was found to be an excellent qualitative representation of true thermal inertia. Computer processing of digital day and night HCMM data allowed construction of geologically useful images. At some test sites, more information was provided by data than LANDSAT data. Soil moisture effects and differences in spectrally dark materials were more effectively displayed using the thermal data
Evaluation of thermal data for geologic applications
Sensitivity studies using thermal models indicated sources of errors in the determination of thermal inertia from HCMM data. Apparent thermal inertia, with only simple atmospheric radiance corrections to the measured surface temperature, would be sufficient for most operational requirements for surface thermal inertia. Thermal data does have additional information about the nature of surface material that is not available in visible and near infrared reflectance data. Color composites of daytime temperature, nighttime temperature, and albedo were often more useful than thermal inertia images alone for discrimination of lithologic boundaries. A modeling study, using the annual heating cycle, indicated the feasibility of looking for geologic features buried under as much as a meter of alluvial material. The spatial resolution of HCMM data is a major limiting factor in the usefulness of the data for geologic applications. Future thermal infrared satellite sensors should provide spatial resolution comparable to that of the LANDSAT data
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Preface paper to the Semi-Arid Land-Surface-Atmosphere (SALSA) Program special issue
The Semi-Arid Land-Surface-Atmosphere Program (SALSA) is a multi-agency, multi-national research effort that seeks to evaluate the consequences of natural and human-induced environmental change in semi-arid regions. The ultimate goal of SALSA is to advance scientific understanding of the semi-arid portion of the hydrosphere–biosphere interface in order to provide reliable information for environmental decision making. SALSA approaches this goal through a program of long-term, integrated observations, process research, modeling, assessment, and information management that is sustained by cooperation among scientists and information users. In this preface to the SALSA special issue, general program background information and the critical nature of semi-arid regions is presented. A brief description of the Upper San Pedro River Basin, the initial location for focused SALSA research follows. Several overarching research objectives under which much of the interdisciplinary research contained in the special issue was undertaken are discussed. Principal methods, primary research sites and data collection used by numerous investigators during 1997–1999 are then presented. Scientists from about 20 US, five European (four French and one Dutch), and three Mexican agencies and institutions have collaborated closely to make the research leading to this special issue a reality. The SALSA Program has served as a model of interagency cooperation by breaking new ground in the approach to large scale interdisciplinary science with relatively limited resources