Automated Classification of an Environmental Sensitivity Index

Abstract

Environmental Sensitivity Indices (ESI) composed of many field-data are essential for monitoring and control systems. An ESI of the German Wadden Sea was determined for use by authorities in the beginning of the last decade. It was derived in a still common way by experts semi-manually analyzing an extensive field-data-set. An algorithm is presented here which emulates the expert-decisions on the sensitivity classes. This allows in future the necessary regular updates of ESI-determinations by new field data via automated classifications. After tuning of the parameters of the algorithm it generates identical decisions in about 97% of all locations. In addition the presented algorithm finds as a by-product erroneous or extremely seldom field data.