Remote sensing monitoring and analysis of the spatiotemporal evolution of ecological environment in Lengshuijiang mining area, Hunan
Vegetation, as the most sensitive component of the natural geographical environment, can reveal the degree of pollution in the ecological environment of mining areas. Long-term antimony mining has led to severe environmental degradation in Lengshuijiang, Hunan Province. In this study, multi-year Landsat satellite images were utilized, based on the pixel binary model, to estimate vegetation coverage using the Normalized Difference Vegetation Index (NDVI). Through temporal and spatial comparative analysis, the evolving characteristics of the impact of antimony mining on the ecological environment were revealed. Results indicate that vegetation coverage gradually decreases with the increase in pollution level, namely: vegetation coverage in heavily polluted areas < moderately polluted areas < lightly polluted areas < clean areas. Moreover, from a temporal perspective, overall vegetation coverage was poor during 2006-2009, especially in heavily polluted areas, which experienced a very low level of vegetation coverage due to the pollution from mining activities. After 2009, with the implementation of mining restoration projects, overall vegetation coverage gradually returned to the level of 1990. This outcome aligns with previous field studies but at a reduced cost. This method offers valuable insights for monitoring pollution, assessing ecological restoration effectiveness, land management, and future planning in Lengshuijiang and similar mining regions.
Authors
- Yonggang Nie (ORCID: https://orcid.org/0000-0002-7554-979X)
- Meng Xi (ORCID: https://orcid.org/0000-0001-8207-3921)
- Qiao Wang (ORCID: https://orcid.org/0000-0001-6604-0003)
- Yuan Sun (ORCID: https://orcid.org/0000-0002-4595-9237)
- De Li Liu (ORCID: https://orcid.org/0000-0003-2574-1908)
- Jiaguo Li (ORCID: https://orcid.org/0000-0001-8617-3284)
- Yanping Wang (ORCID: https://orcid.org/0000-0002-2918-147X)
- haixiao qin
Institutions
- Institute of Disaster Prevention (CN)
- National Satellite Ocean Application Service (CN)
- Aerospace Information Research Institute (CN)
Publication Details
- Published
- 2024-11-27
- DOI
- https://doi.org/10.1117/12.3049133
- Primary Topic
- Remote Sensing and Land Use
- Type
- article
- Field-Weighted Citation Impact
- 0.00