Analysis of watershed landscape pattern change based on TM images

Chongwei Li; Sa Wang; Yongli Zhao

doi:10.1117/12.896388

8 July 2011 Analysis of watershed landscape pattern change based on TM images

Chongwei Li, Sa Wang, Yongli Zhao

Proceedings Volume 8009, Third International Conference on Digital Image Processing (ICDIP 2011); 80090N (2011) https://doi.org/10.1117/12.896388
Event: 3rd International Conference on Digital Image Processing, 2011, Chengdu, China

Abstract

Based on analysis of remote sensing images, statistic data of Yuqiao watershed in Tianjin from 1999 to 2009, and with the technology of Remote Sensing (abbr. RS) and Geographic Information System (abbr. GIS), At the same time, according to Maximum Likelihood Classifier (MLC) , Support Vector Machines (SVM) classifier ,statistical analysis and correlation analysis, we can quantitatively analyze landscape pattern change of Yuqiao watershed by calculating its Landscape diversity index, landscape shape index, Patch density, Edge density and contagion, etc. As a result, significant land-use changes have taken place in the Yuqiao watershed over during the ten years due to urbanization. Farmland has a notable increase. Meanwhile; there is a remarkable decrease in grass and shrub land. The farmland landscape's LSI from 145.72 increased 207.89 from 1999 to 2009, according to the complex and anomalous of farmland, which indicates that the way people cultivate the farmland, not only causes farmland quantity increase, but also makes the shape becomes complex. In the end, some advice will be given that human beings should adjust land-use structure in lake districts. The study of the integration of TM images and GIS technique is an effective approach to analyze the landscape changes in the watershed.

Citation Download Citation

Chongwei Li, Sa Wang, and Yongli Zhao "Analysis of watershed landscape pattern change based on TM images", Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80090N (8 July 2011); https://doi.org/10.1117/12.896388

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