Slope ranking and geohazards correlation analysis for combined open-underground mining area
- Published
- Accepted
- Subject Areas
- Spatial and Geographic Information Systems
- Keywords
- Combined Open-Underground Mining area, Slope Ranking, geohazards, correlation analysis
- Copyright
- © 2018 Jin
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2018. Slope ranking and geohazards correlation analysis for combined open-underground mining area. PeerJ Preprints 6:e27070v1 https://doi.org/10.7287/peerj.preprints.27070v1
Abstract
Geohazards in mining areas are mainly ground subsidence, slope landslides and ground cracks, surface cover degradation and environmental ecological pattern destruction. The classification and rank of terrain slope and the feature area extraction of the slope are the important content for the correlation analysis with the geohazards. The slope classification and rank index system for soil and water conservation, land use and man-made ground disasters was analyzed. According to the characteristics of open pit and underground associated mining area, we comprehensively analyzed the spatial correlation between different ground disaster and terrain features and landform types, and propose a new slope ranking index, dividing slope zones and forming slope classification map. Especially slope area of 35-45 degrees and more than 45 degrees was extracted, and the relationship between regional geohazards and slope zone was analyzed. The application of terrestrial laser scanning technology to establish open-pit high precision digital elevation model, extraction of slope, slope type, gully density characteristic factor, topography factor data sets are established, and correlation analysis, to enhance disaster information content.
Author Comment
This is a preprint submission to PeerJ