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Environmental impact classification with fuzzy sets for urban land cover from satellite remote sensing data

Urban area is a mosaic of complex, interacting ecosystems, rich natural resources and socio-economic activity. Dramatic changes in urban's land cover are due to natural and anthropogenic causes. A scientific management system for protection, conservation and restoration must be based on reliable information on bio-geophysical and geomorphologic, dynamics processes, and climatic change effects. Synergetic use of quasi-simultaneously acquired multi-sensor data may therefore allow for a better approach of change detection and environmental impact classification and assessment in urban area. It is difficult to quantify the environmental impacts of human and industrial activities in urban areas. There are often many different indicators than can conflict with each other, frequently important observations are lacking, and potentially valuable information may non-quantitative in nature. Fuzzy set theory offers a modern methodology for dealing with these problems and provides useful approach to difficult classification problems for satellite remote sensing data. This paper describes how fuzzy logic can be applied to analysis of environmental impacts for urban land cover. Based on classified Landsat TM, SPOT images and SAR ERS-1 for Bucharest area, Romania, it was performed a land cover classification and subsequent environmental impact analysis.