Uncertainty Analysis for Remote Sensing Classification in the Context of Disaster Studies in Shanghai

Zhane Yin 1+, Jiahong Wen 1 and Shiyuan Xu 2
Geography Department of Shanghai Normal University, 100 Guilin Road, Shanghai, 200234, China
2 Geography Department of East China Normal University, 3663 North Zhongshan Road, Shanghai, China

Abstract. Our study applies the object-oriented technology to extract urban green automatically, which could increase accuracy through evaluating and analyzing  the quality of disaster spatial data by measuring the disfigurement points and disfigurement rate in disaster GIS based on error analysis. The study shows that
for high resolution remote sensing images that the accuracy may increase about 20% based on object-oriented technology using  remote sensing image processing software eCognition than based on traditional supervised classification method using software ERDAS.

Keywords: accuracy, remote sensing data, rate of disfigurement in GIS, Shanghai

In: Wan, Y. et al. (eds) Proceeding of the 8th international symposium on spatial accuracy assessment in natural resources and environmental sciences, World Academic Union (Press).

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