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In this paper, methods for mapping land use changes and vegetation parameters using remote sensing data are presented in the context of hydrological studies. In the first part, a land use and land cover classification system (RUB-LUGS: Ruhr University Bochum-Land Use and Land Cover Classification System) is developed for providing distributed information for hydrological modelling and for detection of distributed land use changes. Applying this system to Landsat data, land use time series is created for hydrological modelling of effects of man-made changes in the Sauer River Basin. In the second part, equations are established for estimating leaf area indices using vegetation indices calculated from remote sensing data and a two stream approximation model for estimating leaf area indices is applied to the Sauer River Basin. Combining the two approaches, a method has been found for calculating leaf area indices for mesoscale river basins using remote sensing data.
Zhongbo Su (Sat,) studied this question.