基于多源时序NDVI的稀土矿区土地毁损与恢复过程分析
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摘要
为分析稀土开采的时空分布及矿区土地毁损与恢复过程,该文以岭北稀土矿区为例,以1990—2016年的HJ-1B CCD、Landsat 5和Landsat 8遥感数据为数据源,结合回归分析法、遥感时序NDVI分析方法,对岭北稀土矿区的稀土开采状况及土地毁损与恢复情况进行分析。为减少不同数据由于传感器自身原因而带来的NDVI误差,采用回归分析法构建HJ-1B CCD、Landsat5/8数据的NDVI转换方程并利用均方根误差对转换方程的精度进行检验。结果表明:HJ-1B CCD、Landsat5/8数据的NDVI影像对应转换方程的R2值均超过0.9以及模拟影像与真实影像之间的均方根误差值均小于0.05,说明HJ-1B CCD、Landsat5/8的NDVI数据之间存在较为显著的线性正相关,所求的转换方程具有较高精度,可以消除数据来源差异对NDVI的影响;稀土开采时空分布分析表明岭北稀土矿区在2001—2004年、2006年的开采面积较大,均超过1 km~2,其中2006的开采面积最大,达到2.546 1 km~2;稀土开采在空间分布上较为分散,不仅增加了监管的困难,造成了资源的浪费,还一定程度上增加了治理困难;土地毁损与恢复分析表明受到人为扰动的区域占矿区总面积的54.59%,其中受森林砍伐扰动影响的面积最大,为86.5341 km~2;稀土开采扰动的土地面积为11.354 4 km~2,其植被恢复的平均加权时长为11年。其中复垦恢复的面积为5.004 9 km~2,仍有6.349 5 km~2的区域植被未恢复,急需治理。该研究能较好的反映稀土干扰下的土地毁损与恢复过程,为岭北稀土矿区的生态环境治理及矿区的可持续发展提供借鉴。
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-1 B 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-1 B CCD and Landsat 5/8 data was constructed by using the regression analysis method, NDVI image of HJ-1 B 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-1 B CCD and Landsat 5, HJ-1 B 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-1 B 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 km~2 in 2001-2006, and the mining area reached 2.546 1 km~2 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 km~2, accounting for 45.41% of the total mining area; anthropogenic disturbance area was 116.709 3 km~2, accounting for 54.59% of the total mining area; the area affected by deforestation disturbance was the largest, which was 86.534 1 km~2, and the average time length of vegetation restoration was 3 years; the arable land that was not abandoned occupied 5.404 5 km~2; cultivated land abandoned for many years and that for returning to forest occupied 9.390 6 km~2; orchard development area was 3.148 2 km~2, and the average time length of vegetation restoration for 7 years; rare earth mining occupied 11.354 4 km~2, whose average recovery time was 11 years, and the recovery of the reclamation area was 5.004 9 km~2, so there was still 6.349 5 km~2 area with the regional vegetation that did not be recovered, and relevant departments should pay attention to the situation.
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-1 B 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-1 B CCD and Landsat 5/8 data was constructed by using the regression analysis method, NDVI image of HJ-1 B 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-1 B CCD and Landsat 5, HJ-1 B 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-1 B 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 km~2 in 2001-2006, and the mining area reached 2.546 1 km~2 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 km~2, accounting for 45.41% of the total mining area; anthropogenic disturbance area was 116.709 3 km~2, accounting for 54.59% of the total mining area; the area affected by deforestation disturbance was the largest, which was 86.534 1 km~2, and the average time length of vegetation restoration was 3 years; the arable land that was not abandoned occupied 5.404 5 km~2; cultivated land abandoned for many years and that for returning to forest occupied 9.390 6 km~2; orchard development area was 3.148 2 km~2, and the average time length of vegetation restoration for 7 years; rare earth mining occupied 11.354 4 km~2, whose average recovery time was 11 years, and the recovery of the reclamation area was 5.004 9 km~2, so there was still 6.349 5 km~2 area with the regional vegetation that did not be recovered, and relevant departments should pay attention to the situation.
引文
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[3]卞正富.矿区开采沉陷农用土地质量空间变化研究[J].中国矿业大学学报,2004,33(2):213-218.Bian Zhengfu.Change of agricultural land quality due to mining subsidence[J].Journal of China University of Mining&Technology,2004,33(2):213-218.(in Chinese with English abstract)
[4]王杨扬,赵中秋,原野,等.黄土区露天煤矿不同复垦模式对土壤水稳性团聚体稳定性的影响[J].农业环境科学学报,2017,36(5):966-973.Wang Yangyang,Zhao Zhongqiu,Yuan Ye,et al.Effects of different reclamation patterns on the stability of soil water-stable aggregates of an opencast mine in Loess area[J].Journal of Agro-Environment Science,2017,36(5):966-973.(in Chinese with English abstract)
[5]张紫昭,郭瑞清,周天生,等.新疆煤矿土地复垦为草地的适宜性评价方法与应用[J].农业工程学报,2015,31(11):278-286.Zhang Zizhao,Guo Ruiqing,Zhou Tiansheng,et al.Suitability evaluation method and application for land reclamation to grassland in Xinjiang coal mines[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(11):278-286.(in Chinese with English abstract)
[6]Areendran G,Rao P,Raj K,et al.Land use/land cover change dynamics analysis in mining areas of Singrauli district in Madhya Pradesh,India[J].Tropical Ecology,2013,54(2):239-250.
[7]Brom J,Nedbal V,Procházka J,et al.Changes in vegetation cover,moisture properties and surface temperature of a brown coal dump from 1984 to 2009 using satellite data analysis[J].Ecological Engineering,2012,43(7):45-52.
[8]Bodlák L,K?ovákováK,Nedbal V,et al.Assessment of landscape functionality changes as one aspect of reclamation quality-the case of Velkápodkru?nohorskádump,Czech Republic[J].Ecological Engineering,2012,43:19-25.
[9]彭文甫,王广杰,周介铭,等.基于多时相Landsat5/8影像的岷江汶川-都江堰段植被覆盖动态监测[J].生态学报,2016,36(7):1975-1988.Peng Wefu,Wang Guangjie,Zhou Jieming,et al.Dynamic monitoring of fractional vegetation cover along Minjiang River from Wenchuan County to Dujiangyan City using multi-temporal landsat 5 and 8 images[J].Acta Ecologica Sinica,2016,36(7).(in Chinese with English abstract)
[10]殷守敬,吴传庆,王桥,等.多时相遥感影像变化检测方法研究进展综述[J].光谱学与光谱分析,2013,33(12):3339-3342.Yin Shoujing,Wu Chuanqing,Wang Qiao,et al.Review of change detection methods using multi-temporal remotely sensed images[J].Spectroscopy and Spectral Analysis,2013,33(12):3339-3342.(in Chinese with English abstract)
[11]张扬建,范春捆,黄珂,等.遥感在生态系统生态学上应用的机遇与挑战[J].生态学杂志,2017,36(3):809-823.Zhang Yangjian,Fan Chunkun,Huang Ke,et al.Opportunities and challenges in remote sensing applications to ecosystem ecology[J].Chinese Journal of Ecology,2017,36(3):809-823.(in Chinese with English abstract)
[12]朴英超,关燕宁,张春燕,等.基于小波变换的卧龙国家级自然保护区植被时空变化分析[J].生态学报,2015,36(9):2656-2668.Piao Yingchao,Guan Yanning,Zhang Chunyan,et al.Analysis of temporal and spatial changes in vegetation cover using wavelet transform method in Wolong Natural Reserve[J].Acta Ecologica Sinica,2016,36(9):2656-2668.(in Chinese with English abstract)
[13]贾铎,牟守国,赵华.基于SSA-Mann Kendall的草原露天矿区NDVI时间序列分析[J].地球信息科学学报,2016,18(8):1110-1122.Jia Duo,Mu Shou guo,Zhao Hua.Analysis of NDVI time series in grassland open-cast coal mines based on SSA-Mann Kendall[J].Journal of Geo-Information Science,2016,18(8):1110-1122.(in Chinese with English abstract)
[14]Li A,Huang C,Sun G,et al.Modeling the height of young forests regenerating from recent disturbances in Mississippi using Landsat and ICESat data[J].Remote Sensing of Environment,2011,115(8):1837-1849.
[15]杨辰,沈润平,郁达威,等.利用遥感指数时间序列轨迹监测森林扰动[J].遥感学报,2013,17(05):1246-1263.Yang Chen,Shen Runping,Yu Dawei,et al.Forest disturbance monitoring based on the time-series trajectory of remote sensing index[J].Journal of Remote Sensing,2013,17(5):1246-1263.(in Chinese with English abstract)
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