The near infrared spectral radiance measurements of snow and cirrus and cumulus cloud backgrounds taken by the Air Force Geophysics Laboratory's flying laboratory are evaluated. From the analysis of the 124 specra obtained, the spectral radiances or reflectance characteristics of snow and cirrus and cumulus clouds between 5500 and 7000/cm (1.82-1.43 micrometers were determined. Snow/cloud discrimination can be made by utilizing a sensor in the 5500 to 7000/ cm spectral region. Based on the analysis of these data, certain snow/cloud design parameters were identified; that is, slope of the spectral radiance, absolute spectral and/or total radiance, and the location and value of the maximum spectral radiance for the snow and cirrus and cumulus cloud backgrounds. Finally, specific recommendations are made for an optimal operational snow/cloud discrimination radiometer. (Author).

This volume outlines the fundamentals and applications of light scattering, absorption and polarization processes involving ice crystals.

Remote sensing has long been used in monitoring and analyzing agricultural activities. Eveyln Pruitt of the U.S. Office of Naval Research (Estes and Jensen 1998) was first coin the term 'remote sensing' in 1958. Scientists used aerial photography for soil and crop surveys associated with agricultural areas (Goodman 1959). Remote Sensing is the science and art of acquiring information (spectral, spatial, and temporal) about material objects, area, or phenomenon, without coming into physical contact with the objects, or area, or phenomenon under investigation. Orbital platforms collect and transmit data from different parts of the electromagnetic spectrum. Remote sensing applications include monitoring deforestation areas, glacial features, and depth sounding of coastal and ocean depths.

Satellite Remote Sensing of Natural Resources offers an introduction to digital remote sensing. This comprehensive text emphasizes the basics, with simple concepts presented in clear, easy-to-understand language. For those who are interested in practical remote sensing but do not have an extensive background in math and statistics, this primer is invaluable. The main topics covered include satellite images, image processing systems, spectral regions, radiometric and geometric corrections, supervised and unsupervised classification, and accuracy assessment. Each chapter concludes with a section of sample problems and list of additional readings.