Atmospheric modeling related to Thematic Mapper scan geometry

A simulation study was carried out to characterize atmospheric effects in LANDSAT-D Thematic Mapper data. In particular, the objective was to determine if any differences would result from using a linear vs. a conical scanning geometry. Insight also was gained about the overall effect of the atmosphere on Thematic Mapper signals, together with the effects of time of day. An added analysis was made of the geometric potential for direct specular reflections (sun glint). The ERIM multispectral system simulation model was used to compute inband Thematic Mapper radiances, taking into account sensor, atmospheric, and surface characteristics. Separate analyses were carried out for the thermal band and seven bands defined in the reflective spectral region. Reflective-region radiances were computed for 40 deg N, 0 deg, and 40 deg S latitudes; June, Mar., and Dec. days; and 9:30 and 11:00 AM solar times for both linear and conical scan modes. Also, accurate simulations of solar and viewing geometries throughout Thematic Mapper orbits were made. It is shown that the atmosphere plays an important role in determining Thematic Mapper radiances, with atmospheric path radiance being the major component of total radiances for short wavelengths and decreasing in importance as wavelength increases. Path radiance is shown to depend heavily on the direct radiation scattering angle and on haze content. Scan-angle-dependent variations were shown to be substantial, especially for the short-wavelength bands

Development, implementation and evaluation of satellite-aided agricultural monitoring systems

Research activities in support of AgRISTARS Inventory Technology Development Project in the use of aerospace remote sensing for agricultural inventory described include: (1) corn and soybean crop spectral temporal signature characterization; (2) efficient area estimation techniques development; and (3) advanced satellite and sensor system definition. Studies include a statistical evaluation of the impact of cultural and environmental factors on crop spectral profiles, the development and evaluation of an automatic crop area estimation procedure, and the joint use of SEASAT-SAR and LANDSAT MSS for crop inventory

Wheat signature modeling and analysis for improved training statistics: Supplement. Simulated LANDSAT wheat radiances and radiance components

Simulated scanner system data values generated in support of LACIE (Large Area Crop Inventory Experiment) research and development efforts are presented. Synthetic inband (LANDSAT) wheat radiances and radiance components were computed and are presented for various wheat canopy and atmospheric conditions and scanner view geometries. Values include: (1) inband bidirectional reflectances for seven stages of wheat crop growth; (2) inband atmospheric features; and (3) inband radiances corresponding to the various combinations of wheat canopy and atmospheric conditions. Analyses of these data values are presented in the main report

Development, implementation and evaluation of satellite-aided agricultural monitoring systems

Research supporting the use of remote sensing for inventory and assessment of agricultural commodities is summarized. Three task areas are described: (1) corn and soybean crop spectral/temporal signature characterization; (2) efficient area estimation technology development; and (3) advanced satellite and sensor system definition. Studies include an assessment of alternative green measures from MSS variables; the evaluation of alternative methods for identifying, labeling or classification targets in an automobile procedural context; a comparison of MSS, the advanced very high resolution radiometer and the coastal zone color scanner, as well as a critical assessment of thematic mapper dimensionally and spectral structure

Multispectral system analysis through modeling and simulation

The design and development of multispectral remote sensor systems and associated information extraction techniques should be optimized under the physical and economic constraints encountered and yet be effective over a wide range of scene and environmental conditions. Direct measurement of the full range of conditions to be encountered can be difficult, time consuming, and costly. Simulation of multispectral data by modeling scene, atmosphere, sensor, and data classifier characteristics is set forth as a viable alternative, particularly when coupled with limited sets of empirical measurements. A multispectral system modeling capability is described. Use of the model is illustrated for several applications - interpretation of remotely sensed data from agricultural and forest scenes, evaluating atmospheric effects in LANDSAT data, examining system design and operational configuration, and development of information extraction techniques

Investigation of spatial misregistration effects in multispectral scanner data

The author has identified the following significant results. A model for estimating the expected proportion of multiclass pixels in a scene was generalized and extended to include misregistration effects. Another substantial effort was the development of a simulation model to generate signatures to represent the distributions of signals from misregistered multiclass pixels, based on single class signatures. Spatial misregistration causes an increase in the proportion of multiclass pixels in a scene and a decorrelation between signals in misregistered data channels. The multiclass pixel proportion estimation model indicated that this proportion is strongly dependent on the pixel perimeter and on the ratio of the total perimeter of the fields in the scene to the area of the scene. Test results indicated that expected values computed with this model were similar to empirical measurements made of this proportion in four LACIE data segments

Wheat signature modeling and analysis for improved training statistics

The author has identified the following significant results. The spectral, spatial, and temporal characteristics of wheat and other signatures in LANDSAT multispectral scanner data were examined through empirical analysis and simulation. Irrigation patterns varied widely within Kansas; 88 percent of wheat acreage in Finney was irrigated and 24 percent in Morton, as opposed to less than 3 percent for western 2/3's of the State. The irrigation practice was definitely correlated with the observed spectral response; wheat variety differences produced observable spectral differences due to leaf coloration and different dates of maturation. Between-field differences were generally greater than within-field differences, and boundary pixels produced spectral features distinct from those within field centers. Multiclass boundary pixels contributed much of the observed bias in proportion estimates. The variability between signatures obtained by different draws of training data decreased as the sample size became larger; also, the resulting signatures became more robust and the particular decision threshold value became less important

Understanding and utilization of Thematic Mapper and other remotely sensed data for vegetation monitoring

The TM Tasseled Cap transformation, which provides both a 50% reduction in data volume with little or no loss of important information and spectral features with direct physical association, is presented and discussed. Using both simulated and actual TM data, some important characteristics of vegetation and soils in this feature space are described, as are the effects of solar elevation angle and atmospheric haze. A preliminary spectral haze diagnostic feature, based on only simulated data, is also examined. The characteristics of the TM thermal band are discussed, as is a demonstration of the use of TM data in energy balance studies. Some characteristics of AVHRR data are described, as are the sensitivities to scene content of several LANDSAT-MSS preprocessing techniques