This study takes Guanyinshan Iron mining area, Dongchuan District, Kunming City, Yunnan Province as the research object, and uses remote sensing technology to carry out ore prospecting. Firstly, the information of iron hydroxyl alteration was extracted by Landsat 8 remote sensing image, and the distribution characteristics of iron mineralization were analyzed. Secondly, ASTER remote sensing image was used to extract the distribution of hematite, magnetite and other minerals, and to clarify the mineral composition of iron ore in the region. On this basis, combined with multi-source data, the improved integrated learning method is used to comprehensively analyze the iron ore potential, and delineate the prospecting prospect area. The research shows that the combination of remote sensing technology and geological data can effectively assist the exploration of iron ore resources and provide a scientific basis for future mineral exploration.
References
[1]
Cherai, M., Marzouki, A. and Talbi, F. (2022) Mineralization-Tectonic Relationship in the Jbeltirremi Fluorite Mine (Taourirt Region—Eastern Morocco): Contribution of Remote Sensing for Geological Exploration. Journal of Mines, Metals and Fuels, 70, 251-257. https://doi.org/10.18311/jmmf/2022/28374
[2]
Aryafar, A. and Roshanravan, B. (2020) Improved Index Overlay Mineral Potential Modeling in Brown-and Green-Fields Exploration Using Geochemical, Geological and Remote Sensing Data. Earth Science Informatics, 13, 1275-1291. https://doi.org/10.1007/s12145-020-00509-x
[3]
Kah, E., Innocent, N.M. and Gilles, Z.M. (2020) Combined Methods of Remote Sensing and Fieldwork in Geological and Mineral Exploration in the Mballe Locality, Adamawa Region of Cameroon. Natural Resources, 11, 184-203. https://doi.org/10.4236/nr.2020.114012
[4]
Griffiths, P.S., Curtis, P.A.S., Fadul, S.E.A. and Scholes, P.D. (1987) Reconnaissance Geological Mapping and Mineral Exploration in Northern Sudan Using Satellite Remote Sensing. Geological Journal, 22, 225-249. https://doi.org/10.1002/gj.3350220617
[5]
Han, Y.H., Wang, C.Z., Wu, Z.J., Lu, G.X., Zhang, B.L. and Zhang, Q.P. (2024) Remote Sensing Geological Interpretation, Alteration Information Extraction, and Mineral Prospecting Prediction in the Chaihulanzi Gold Field, Chifeng, Inner Mongolia. Geoscience, 38, 1076-1091
[6]
Malthus, T. (1996) A Review of: “Remote Sensing and Geographic Information Systems—Geological Mapping, Mineral Exploration and Mining”. International journal of geographical information systems, 10, 359-360. https://doi.org/10.1080/02693799608907247
[7]
Jain, R., Bhu, H., Pandey, A.K. and Pour, A.B. (2025) Base-Metal Exploration by Using Remote Sensing, Geological, Geophysical, and Geochemical Datasets with Clues from Ancient Mining: A Comprehensive Review on Aravalli-Delhi Fold Belt, Rajasthan, India. Advances in Space Research, 75, 277-315. https://doi.org/10.1016/j.asr.2024.09.038
[8]
Eskandari, A., Hosseini, M. and Nicotra, E. (2023) Application of Satellite Remote Sensing, UAV-Geological Mapping, and Machine Learning Methods in the Exploration of Podiform Chromite Deposits. Minerals, 13, Article 251. https://doi.org/10.3390/min13020251
[9]
Shayilan, A. and Chen, Y. (2024) A Smotified Extreme Learning Machine for Identifying Mineralization Anomalies from Geochemical Exploration Data: A Case Study from the Yeniugou Area, Xinjiang, China. Earth Science Informatics, 17, 1329-1343. https://doi.org/10.1007/s12145-024-01246-1
[10]
Shirmard, H., Farahbakhsh, E., Müller, R.D. and Chandra, R. (2022) A Review of Machine Learning in Processing Remote Sensing Data for Mineral Exploration. Remote Sensing of Environment, 268, Article ID: 112750. https://doi.org/10.1016/j.rse.2021.112750
[11]
Zhang, S., Tan, S., Sun, Y., Ding, D. and Yang, W. (2024) Risk Mapping of Geological Hazards in Plateau Mountainous Areas Based on Multisource Remote Sensing Data Extraction and Machine Learning (Fuyuan, China). Land, 13, Article 1361. https://doi.org/10.3390/land13091361
[12]
Shereif, A.S., Shebl, A., Mahmoud, A.S. and Csámer, Á. (2024) Enhanced Lithological Mapping in El-Missikat and El-Erediya Areas, Central Eastern Desert, Egypt, Leveraging Remote Sensing Techniques and Machine Learning Algorithms. IEEE Transactions on Geoscience and Remote Sensing, 62, 1-27. https://doi.org/10.1109/tgrs.2024.3471982
[13]
Tucker, C.J. (1979) Red and Photographic Infrared Linear Combinations for Monitoring Vegetation. Remote Sensing of Environment, 8, 127-150. https://doi.org/10.1016/0034-4257(79)90013-0
[14]
Pei, Q.M., Shen, J.L., Wang, S.M., Fang, D.R., Gao, Y.Z., Li, D.A. and Ma, S.B. (2024) Exploring Luorite Veins Using Multi-Source Remote Sensing Astellite Data: A Case Study from the Shuitou Fluorite Deposit in Inner Mongolia, China. Northwestern Geology, 57, 121-134.
[15]
Rowan, L.C. and Mars, J.C. (2003) Lithologic Mapping in the Mountain Pass, California Area Using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Data. Remote Sensing of Environment, 84, 350-366. https://doi.org/10.1016/s0034-4257(02)00127-x
