Paper
21 October 2004 Environmental impact classification with fuzzy sets for urban land cover from satellite remote sensing data
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Proceedings Volume 5581, ROMOPTO 2003: Seventh Conference on Optics; (2004) https://doi.org/10.1117/12.583060
Event: ROMOPTO 2003: Seventh Conference on Optics, 2003, Constanta, Romania
Abstract
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.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Maria A. Zoran, Doina Nicoleta Nicolae, and Camelia Talianu "Environmental impact classification with fuzzy sets for urban land cover from satellite remote sensing data", Proc. SPIE 5581, ROMOPTO 2003: Seventh Conference on Optics, (21 October 2004); https://doi.org/10.1117/12.583060
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KEYWORDS
Fuzzy logic

Satellites

Earth observing sensors

Remote sensing

Landsat

Reflectivity

Satellite imaging

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