Landscape pattern recognition on water quality protection in an urbanizing delta using remote sensing and GIS techniques

Abstract

Quantitative relationships between land-use pattern and the water quality of river nets in the delta plains where the megacities lie need to be clarified. We selected Qingpu District of Shanghai City located in Yangtze Delta as a case study. Because the water flows in this area are almost static, the bad water quality might result from adjacent land uses. We calculated spatial patterns of urban, agricultural, and forest land uses related to the water quality in this area. In our method, remotely sensed large data were first registered into the same spatial resolution and radioactive level. Then, data were clipped via the boundary of study area. We used supervised classification algorithm (support vector machine) to obtain land-use classes with promising accuracy, followed by calculation of land-use pattern metrics. We correlated the water quality parameters with pattern metrics. The results showed that both the proportions of land use and the configurations of urban, agricultural, and forest areas were closely associated with the water quality. It is suggested that an appropriate land-use plan for this kind of region should be undominated regular simple shapes of urban or built-up zonings, aggregated agricultural fields, and large connected forests with complex edges.