Li Hengkai, Lei Jun, Wu Jiao. Analysis of land damage and recovery process in rare earth mining area based on multi-source sequential NDVI[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2018, 34(1): 232-240. DOI: 10.11975/j.issn.1002-6819.2018.01.032
    Citation: Li Hengkai, Lei Jun, Wu Jiao. Analysis of land damage and recovery process in rare earth mining area based on multi-source sequential NDVI[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2018, 34(1): 232-240. DOI: 10.11975/j.issn.1002-6819.2018.01.032

    Analysis of land damage and recovery process in rare earth mining area based on multi-source sequential NDVI

    • Abstract: The problem of land and ecological environment damage caused by ion mining has attracted more and more attention. Taking the Lingbei rare earth mining area as an example, combined with remote sensing normalized difference vegetation index (NDVI) time sequence analysis method, we used HJ-1B CCD (charge-coupled device), Landsat 5 and Landsat 8 remote sensing data during 1990-2016, and analyzed land distribution and rare earth mining area damage and recovery process. In order to reduce the NDVI error caused by the sensor itself, NDVI conversion equation of HJ-1B CCD and Landsat 5/8 data was constructed by using the regression analysis method, NDVI image of HJ-1B CCD was transformed into the NDVI image corresponding to the years of Landsat 5/8 (the analog image) by using conversion equation, and the root mean square error (RMSE) between the simulated image and the real Landsat 5/8 NDVI image was calculated and the accuracy of the transformation equation was verified. The results showed that the R2 values of NDVI equations from HJ-1B CCD and Landsat 5, HJ-1B CCD and Landsat 8 data were 0.9319 and 0.9552, both more than 0.9, indicating that there is obvious linear positive correlation between the NDVI of HJ-1B CCD and Landsat 5/8. The RMSE values of NDVI imaging between simulation images and real Landsat 5, and simulation images and real Landsat 8 were 0.0293 and 0.040, which were less than 0.05, showing that the obtained conversion equation has high accuracy and can eliminate the influence of different data sources on the NDVI. Combining NDVI threshold of mining and non-mining, and threshold of non-rare earth mining interference and rare earth mining interference, Lingbei rare earth mining area had annual rare earth mining activity from 1990 to 2016, rare earth mining area of which was smaller in 1990, 1991,1995 and 2000, mining area was more than 1 km2 in 2001-2006, and the mining area reached 2.546 1 km2 in 2006; after 2006, to maintain the rare earth mining scale at the lower level, the country began to implement control of rare earth mining, and the spatial distribution of rare earth mining was more dispersed, which not only caused difficulties in supervision and waste of resources, but also increased governance difficulties to a certain extent. Testing the extraction accuracy of land destruction and restoration type, extraction accuracy of various types was found above 85%, most of which reached more than 90%, satisfying the requirement of accuracy. Analysis of land destruction and restoration type showed that the area that was not disturbed was 97.082 1 km2, accounting for 45.41% of the total mining area; anthropogenic disturbance area was 116.709 3 km2, accounting for 54.59% of the total mining area; the area affected by deforestation disturbance was the largest, which was 86.534 1 km2, and the average time length of vegetation restoration was 3 years; the arable land that was not abandoned occupied 5.404 5 km2; cultivated land abandoned for many years and that for returning to forest occupied 9.390 6 km2; orchard development area was 3.148 2 km2, and the average time length of vegetation restoration for 7 years; rare earth mining occupied 11.354 4 km2, whose average recovery time was 11 years, and the recovery of the reclamation area was 5.004 9 km2, so there was still 6.349 5 km2 area with the regional vegetation that did not be recovered, and relevant departments should pay attention to the situation.
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