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Estimating erosion risk on forest lands using improved methods of discriminant analysis
Author(s) -
Lewis Jack,
Rice Raymond M.
Publication year - 1990
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr026i008p01721
Subject(s) - bootstrapping (finance) , linear discriminant analysis , erosion , statistics , discriminant , population , confidence interval , mathematics , hydrology (agriculture) , environmental science , geology , econometrics , computer science , geotechnical engineering , artificial intelligence , geomorphology , demography , sociology
A population of 638 timber harvest areas in northwestern California was sampled for data related to the occurrence of critical amounts of erosion (>153 m 3 within 0.81 ha). Separate analyses were done for forest roads and logged areas. Linear discriminant functions were computed in each analysis to contrast site conditions at critical plots with randomly selected controls. Bootstrapping was used extensively in the development and testing of the equations, in estimating prediction bias, and in placing confidence limits around parameters and posterior probabilities. The resulting three‐variable equations had classification accuracy, corrected for prediction bias, of 77.7% for road plots and 69.2% for logged area plots. The use of linear discriminant functions facilitates the explicit consideration of erosion risk when planning land‐disturbing activities.