The use of RAPID GIS for gold mineralization prediction on the basis of satellite data

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Space Geoinformatics and Geodesy
1Busygin, BS, 1Nikulin, SL, 2Boyko, VO
1National Mining University, Dnipropetrovsk, Ukraine
2Private Joint-Stock Company «Scientific-Production Enterprise» Orbita, Dnipropetrovsk, Ukraine
Kosm. nauka tehnol. 2007, 13 ;(Supplement1):047-054
https://doi.org/10.15407/knit2007.01s.047
Publication Language: Russian
Abstract: 
Current state of space images usage problem in the geological study of the Earth's surface is considered. The principal information on the specialized geoinformation system RAPID and its SEGMENT module dedicated to image processing, analysis and interpretation are presented. We describe some methods for ore-gold mineralization prediction in an open mountain Uzbekistan region using lineament analysis of SPOT-4 satellite images. The prediction results obtained from satellite images are compared with geological and geophysical data.
Keywords: geological and geophysical data, prediction, satellite images
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References: 
1. Busygin B. S., Miroshnichenko L. V. Pattern recognition under geological and geophysical forecasting, 168 p. (DGU, Dnepropetrovsk, 1991) [in Russian].
2. Busygin B. S., Nikulin S. L., Boyko V. A. GIS-technology for gold prospecting in Western Uzbekistan. Geoinformatyka, No. 1, 44—49 (2006) [in Russian].
3. Busygin B. S., Nikulin S. L., Zalesskiy V. V. Computer Technology for Gold Search Within South-West Downhill of the Ukrainian Shield. Nauka ta innovacii', 2 (3), 80—91 (2006) [in Russian].
4. Busygin B. S., Nikulin S. L., Zalesskiy V. V. Forecasting of gold mineralization in the Sorokinsky greenstone structure. Nauk. visnyk NGU, No. 3, 68—72 (2006) [in Russian].
5. Koronovskii N. V., Zlatopol’skii A. A., Ivanchenko G. N. Automated interpretation of space images for structural analysis. Issled. Zemli Kosmosa, No. 1, 111 — 118 (1986) [in Russian].
6. Pratt W. Digital image processing, 3ed., 366 p. (Wiley, 2001).

7. Zlatopolsky A. A. Texture orientation description of remote sensing data using LESSA (Lineament Extraction and Stripe Statistical Analysis). Computers and Geosciences, 23 (1), 45—62 (1997).
https://doi.org/10.1016/S0098-3004(96)00053-2