Identifying erosion areas at basin scale using remote sensing data and GIS: a case study in a geologically complex mountain basin in the Spanish Pyrenees

Abstract

Inventory and monitoring of eroded areas at basin scale (Mm2) can be very useful for environmental planning and can help to reduce land degradation and sediment yield to streams. Combined use of remote sensing images and auxiliary geocoded data has been widely used for mapping various environmental features, including surface erosion. Here an example is presented in the Yesa reservoir catchment in the Spanish Pyrenees. Several combinations of radiometric data (a sequence of images from different seasons of the year) and other geocoded information, including topographical (altitude and slope) and geological maps, were compared in their ability to predict previously identified erosive features. Multinomial logistic regression was used as classification method. The datasets were compared in terms of classification error statistics (sensitivity and specificity) using an independent random sample. The incorporation of lithological information improved the discrimination of eroded areas, but the same did not happen in the case of topographical information. Two final maps of eroded areas were obtained applying an equal predicted area rule and an equal error rate rule