Measurement of soil moisture using remote sensing multisensor radiation techniques

Theoretical modeling as well as laboratory and field measurement were coupled with analysis of aircraft data obtained from controlled sites in an effort to enhance understanding of the microwave response due to soil moisture so as to specify sensor parameters and develop inversion algorithms. Models to predict the complex dielectric constant were produced which led to the interpretation of the results in terms of a matrix potential rather than simply moisture content. Similar advances were made in the development of coherent and incoherent radiative transfer models and rough surface scattering models

Inversion algorithms for the microwave remote sensing of soil moisture. Experiments with swept frequency microwaves

Two experiments were performed employing swept frequency microwaves for the purpose of investigating the reflectivity from soil volumes containing both discontinuous and continuous changes in subsurface soil moisture content. Discontinuous moisture profiles were artificially created in the laboratory while continuous moisture profiles were induced into the soil of test plots by the environment of an agricultural field. The reflectivity for both the laboratory and field experiments was measured using bi-static reflectometers operated over the frequency ranges of 1.0 to 2.0 GHz and 4.0 to 8.0 GHz. Reflectivity models that considered the discontinuous and continuous moisture profiles within the soil volume were developed and compared with the results of the experiments. This comparison shows good agreement between the smooth surface models and the measurements. In particular the comparison of the smooth surface multi-layer model for continuous moisture profiles and the yield experiment measurements points out the sensitivity of the specular component of the scattered electromagnetic energy to the movement of moisture in the soil

Data documentation for the bare soil experiment at the University of Arkansas

The reflectivities of several controlled moisture test plots were investigated. These test plots were of a similar soil texture which was clay loam and were prepared to give a desired initial soil moisture and density profile. Measurements were conducted on the plots as the soil water redistributed for both long term and diurnal cycles. These measurements included reflectivity, gravimetric and volumetric soil moisture, soil moisture potential, and soil temperature

A study of image quality for radar image processing

Methods developed for image quality metrics are reviewed with focus on basic interpretation or recognition elements including: tone or color; shape; pattern; size; shadow; texture; site; association or context; and resolution. Seven metrics are believed to show promise as a way of characterizing the quality of an image: (1) the dynamic range of intensities in the displayed image; (2) the system signal-to-noise ratio; (3) the system spatial bandwidth or bandpass; (4) the system resolution or acutance; (5) the normalized-mean-square-error as a measure of geometric fidelity; (6) the perceptual mean square error; and (7) the radar threshold quality factor. Selective levels of degradation are being applied to simulated synthetic radar images to test the validity of these metrics

Evaluation of SIR-A space radar for geologic interpretation: United States, Panama, Colombia, and New Guinea

Comparisons between LANDSAT MSS imagery, and aircraft and space radar imagery from different geologic environments in the United States, Panama, Colombia, and New Guinea demonstrate the interdependence of radar system geometry and terrain configuration for optimum retrieval of geologic information. Illustrations suggest that in the case of space radars (SIR-A in particular), the ability to acquire multiple look-angle/look-direction radar images of a given area is more valuable for landform mapping than further improvements in spatial resolution. Radar look-angle is concluded to be one of the most important system parameters of a space radar designed to be used for geologic reconnaissance mapping. The optimum set of system parameters must be determined for imaging different classes of landform features and tailoring the look-angle to local topography

Use of Orbital Radars for Geoscience Investigations

Studies sponsored by NASA at the University of Kansas in cooperation with several other universities and government research agencies are substantiating the applicability of remote sensing by radar to many fields within the earth sciences, agriculture, and oceanography. 1 The purpose of this paper is to show how the properties of the radar return are used to provide geoscience information

Broad Spectrum Microwave Systems for Remotely Measuring Soil Moisture Content

A theoretical and experimental study of the microwave reflectivity of soils with varying moisture content was conducted. A system was developed to measure reflectivity over a continuous frequency range of 4 to 26.5 GHz, at incidence angles from 10° to 70°, and with both horizontal and vertical polarization. The measurements were found to be extremely accurate for smooth homogeneous surfaces, however, the effects of surface roughness were found to be more severe than predicted due to the discontinuous nature of naturally occurring rough surfaces. An algorithm was developed which used the frequency dependence of the reflectivity to estimate the effective roughness of the surface and permit correction to an equivalent smooth surface reflectivity which in turn could be related to dielectric constant or percent moisture content. For the frequency range of investigation the maximum mean square height deviation that could be accomodated was approximately one inch. From this it may be concluded that operational airborne or spacecraft sensors must operate in the 500 MHz to 1 GHz range. Even at this reduced frequency it will be impossible to neglect the effects of roughness and a diversity technique such as developed here is essential if an absolute measure of soil moisture is to be made

Evaluation of Skylab (EREP) data for forest and rangeland surveys

The author has identified the following significant results. Four widely separated sites (near Augusta, Georgia; Lead, South Dakota; Manitou, Colorado; and Redding, California) were selected as typical sites for forest inventory, forest stress, rangeland inventory, and atmospheric and solar measurements, respectively. Results indicated that Skylab S190B color photography is good for classification of Level 1 forest and nonforest land (90 to 95 percent correct) and could be used as a data base for sampling by small and medium scale photography using regression techniques. The accuracy of Level 2 forest and nonforest classes, however, varied from fair to poor. Results of plant community classification tests indicate that both visual and microdensitometric techniques can separate deciduous, conifirous, and grassland classes to the region level in the Ecoclass hierarchical classification system. There was no consistency in classifying tree categories at the series level by visual photointerpretation. The relationship between ground measurements and large scale photo measurements of foliar cover had a correlation coefficient of greater than 0.75. Some of the relationships, however, were site dependent