Research on the remote sensing prospecting model for typical uranium mining area along the Sino-Russian economic corridor

Yongfei Che; Fawang Ye

doi:10.1117/12.2521499

12 March 2019 Research on the remote sensing prospecting model for typical uranium mining area along the Sino-Russian economic corridor

Yongfei Che, Fawang Ye

Author Affiliations +

Proceedings Volume 11023, Fifth Symposium on Novel Optoelectronic Detection Technology and Application; 110232O (2019) https://doi.org/10.1117/12.2521499
Event: Fifth Symposium on Novel Optoelectronic Detection Technology and Application, 2018, Xi'an, China

Abstract

By leveraging the remote sensing technology, we have delved into the remote sensing prospecting model for typical uranium mining area along the Sino-Russian Economic Corridor. According to the remote sensing interpretation results of the basic geology along the Sino-Russian Economic Corridor, we have analyzed and summarized the remote sensing geological features of the structure, stratum and rock mass in this area. Moreover, by providing the remote sensing interpretation of basic geology in the Russian Streltsovsky typical hydrothermal uranium mining area based on the data of the domestic GF-1 satellite, we have made conclusive analysis on the characteristics of its ore-controlling elements and preliminarily summarized the remote sensing geological prospecting model for typical volcanic hydrothermal uranium deposits in this area. By using the remote sensing prospecting model, we have delineated three favorable ore-forming sections, which provides an important basis for regional mineralization prediction and the delineation of favorable ore-forming areas, and helps seek such deposits in the same or similar areas.

Citation Download Citation

Yongfei Che and Fawang Ye "Research on the remote sensing prospecting model for typical uranium mining area along the Sino-Russian economic corridor", Proc. SPIE 11023, Fifth Symposium on Novel Optoelectronic Detection Technology and Application, 110232O (12 March 2019); https://doi.org/10.1117/12.2521499

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