Quantitative identification method of landslide hazard in rare earth mining area based on multi-source data
DAI Meiyi
LI Hengkai
LONG Beiping
WANG Xiuli
Abstract:To identify the potential landslide hazard of ion-adsorption rare earth mining areas in advance,the Lingbei mining area is used as a case study,and a quantitative landslide hazard i-dentification method for rare earth mining areas based on multi-source data was proposed.Based on the Sentinel-1A time series data,the study employed the Small Baseline Subset In-SAR(SBAS-InSAR)technology to identify surface deformation in the study area.Supplemen-ted by multi-source remote sensing data,such as the Digital Elevation Model(DEM)and Landsat 8 Operational Land Imager(OLI),potential landslide points were extracted,and an information value model of landslide hazard in the mining area was constructed.Finally,the potential landslide hazard was identified by combining high-resolution remote sensing images from the same period.The results show that the mining area's average annual surface deforma-tion rate is-20.28~20.08 mm/a and 183 potential landslide points are extracted.The infor-mation value model of landslide hazard in the mining area is feasible and summarizes the opti-mal combination mode of information value for inducing landslides in the study area.Having analyzed the two typical mining sites of Jiazibei and Dakeng,we can find that rare earth mining activities contribute to an increased likelihood of landslides.In addition,the susceptibility to induced landslides remains significantly high,even with post-mining efforts to restore vegeta-tion.
Keywords:landslide identificationrare earth mining areamulti-source dataSBAS-InSAR technologyinformation value model
Publication Date:2024-01-30
Online Publishing Date:2025-08-15(First online date of this platform, not the publication date of the document)
Pages:13( 198-210 )
Journal of China University of Mining & Technology

Journal of China University of Mining & Technology

ISTICPKUEICSCD
ISSN:1000-1964
Year, Vol.(Issue):2024,53(1)