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Using already available data, a backscattering coefficient (so) generator for several types of terrain and measurement conditions is developed. The types of terrain are 1) soils and rocks, 2) trees, 3) grasses, 4) shrubs, 5) short vegetation, 6) roads, 7) urban areas, 8) dry snow, and 9) wet snow. These data sets typically cover incidence angles ranging between 0o and 80o where 0o is normal to the terrain. Measurement conditions are defined by 1) incidence angle, 2) wave polarizations configuration (HH, HV, or VV), and 3) radar band (L, C, S, X, Ku, Ka, or W). The so generator output matches…mehr

Produktbeschreibung
Using already available data, a backscattering coefficient (so) generator for several types of terrain and measurement conditions is developed. The types of terrain are 1) soils and rocks, 2) trees, 3) grasses, 4) shrubs, 5) short vegetation, 6) roads, 7) urban areas, 8) dry snow, and 9) wet snow. These data sets typically cover incidence angles ranging between 0o and 80o where 0o is normal to the terrain. Measurement conditions are defined by 1) incidence angle, 2) wave polarizations configuration (HH, HV, or VV), and 3) radar band (L, C, S, X, Ku, Ka, or W). The so generator output matches very closely the first and second moments of the published data.A modified chi-square goodness of fit test at a 0.05 significance level is introduced to automatically validate the generated output with measured data histograms. Contrary to an ordinary chi-square test previously applied, the modified test rejection rate was consistent with expected behavior of simulated and measured data graphs as the number of source data points (N) increased. The modified test failed to reject the proposed generator as representative of the measured data for an average 72% of all simulated distributions having N greater than or equal to 100. Noted discrepancies can be attributed to sparse so data histograms and model limitations in the 0o less than or equal to q less than or equal to 20o for certain terrain types.