Research on quantitative extraction of desertification integrating multisource remote sensing data in large opencast coal mine area

Guangjun Wang; Meichen Fu

doi:10.1117/12.833684

30 October 2009 Research on quantitative extraction of desertification integrating multisource remote sensing data in large opencast coal mine area

Guangjun Wang, Meichen Fu

Author Affiliations +

Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 74982S (2009) https://doi.org/10.1117/12.833684
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Large opencast coal mine area is a complex region which consists of mining area, grassland, farmland, roads, residents and other landscapes, together with the typical characteristics of desertification, agro-pastoral transitional zone, mineral development area and other ecologically fragile areas. As a man-caused disturbance, mining plays an important role in desertification development in this area. The quantitative extraction of desertification integrating multi-source remote sensing data in large opencast coal mine area was studied in this paper. First, the remote sensing data from SPOT 5 and TM were fused to one image based on IHS transformation and Wavelet analysis, then the BP neural network algorithm were used to fusion image to get desertification classification information. The Global Positioning System (GPS) technique was also used to perform verification during the data process. The results of our studies indicate that the severe desertification is always distributing in shape of triangle around the mining land, which has much spatial correlation with the mining land. So the desertification management should be carried out in mining land, the neighbor region of the mining land should not be neglected.

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Guangjun Wang and Meichen Fu "Research on quantitative extraction of desertification integrating multisource remote sensing data in large opencast coal mine area", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74982S (30 October 2009); https://doi.org/10.1117/12.833684

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KEYWORDS

Image fusion

Remote sensing

Mining

Wavelets

Land mines

Spatial resolution

Neural networks

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