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Study and application of sequential extraction method of ground fissures based on object |
Xinghang ZHANG1,2, Lin ZHU1,2( ), Wei WANG3, Lishan MENG3, Xiaojuan LI1,2, Yingchao REN4 |
1.College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China 2.Laboratory Cultivation Base of Environment Process and Digital Simulation, Beijing 100048, China 3.Laboratory of Non-fossil Energy Minerals,Tianjin Center of China Geological Survey, Tianjin 300170, China 4.The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China |
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Abstract The automatic extraction technology of regional scale ground fissures based on remote sensing images has the problem of low spectral range and low geometric feature, which leads to low extraction precision. Therefore, the sequential step extraction method for ground fissures based on objects is proposed. Firstly, the image is segmented. According to the spectral and geometric characteristics of segmentation object, surface interference factors which are different from the ground fissures are removed by mask. On such a basis, the linear objects are extracted and the surface factors without linear features are removed ultimately. Finally, the fractal characteristics of linear objects are calculated to differentiate between the ground fissures and other linear surface factors and complete the automatic extraction of ground fissures. The method was applied to the extraction of ground fissures in a coal-mining region of northeastern Ordos. The results show that the method is effective in extracting the ground fissures. Its accuracy reaches 85.7%, which is better than the precision of traditional supervised classification method (57.1%) and the precision of knowledge model extraction method (71.4%) . On the basis of extraction results, this paper discusses the distribution characteristics of ground fissures. The respective relations between ground fissures and the location of goafs as well as topography are analyzed. The results show that the number of ground fissures is negatively correlated to the distance of goafs and is not clearly correlated to the topography. The research can provide the necessary technical support for the regional geological environment protection and the rational exploitation of coal resources in the mining area.
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Keywords
GeoEye image
ground fissures
sequential extraction
feature extraction
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Corresponding Authors:
Lin ZHU
E-mail: zhulin@163.com
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Issue Date: 15 March 2019
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