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Method for extraction of ferric contamination anomaly from high-resolution remote sensing data and its applications |
| JIN Moushun1, WANG Hui1, ZHANG Wei2, WANG Xue3 |
1. Remote Sensing Application Institute of ARSC, Xi'an 710054, China;
2. China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing 100083, China;
3. China University of Geosciences(Beijing), Beijing 100083, China |
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Abstract The utilization of multi-spectral remote sensing data to extract anomalies in western China is a fast and economical method, but the spatial resolution of the data available is low and the ferric contamination anomaly appears as mixed pixels so that the accuracy of extraction for ferric contamination anomaly is poor. In view of the deficiency of extraction for ferric contamination anomaly with low resolution remote sensing data, the authors, through analyzing the geological basis and spectral features of ferric contamination anomaly, determined the wave bands of high resolution remote sensing data, such as WorldView2 and IKONOS, and used principal component analysis to extract ferric contamination anomaly. A large-sized iron ore belt in Heiqia of Western Kunlun Mountains was found, and the ferric contamination anomalies coincident with the magnetite mineralization in Laobing of Western Kunlun Mountains were extracted. The results show that the accuracy of extracting ferric contamination anomaly with high resolution remote sensing data is satisfactory.
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| Keywords
mountain resources
spatial analysis
Model Builder
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Issue Date: 23 July 2015
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2015,
Vol. 27
