Fernerkundung und Landschaftsmaße - Untersuchungen zur raumstrukturellen Analyse urbaner Regionen

Abstract

The analysis and monitoring of land use for decision support in planning and management of urban regions is a major application of remote sensing technology. The ability to derive land use data with high geometric and thematic accuracy is generally limited by the availability of adequate remote sensing data and digital image analysis techniques. This study introduces a new approach to using image data spatial structure information (in the form of landscape metrics) derived from digitally classified remote sensing data to describe structures and changes in urban land use. The results show a useful separation between urban and non-urban land cover categories as well as between three inner urban land use types: commercial development, high-density residential and low-density residential. Several important structural land cover features were identified for this study. These were: the dominant general land cover (built-up or vegetation), the housing density, the mean structure and plot size, as well as the spatial aggregation of the built-up areas. Furthermore it is shown that changes in urban environment (urban growth), or as the case may be their effects on the spatial land use structure, can be described and characterized using the landscape metric information. In order to produce more accurate discriminations between the three land cover types of interest, the landscape metrics were further refined into what are termed Landscape Metric Signatures (LMS) for the land use categories.