Dynamic Monitoring of Vegetation Coverage in Daliuta Mine Based on ENVI and GIS Technology

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Abstract:

Researching dynamic variation of vegetation coverage has positive significance for vegetation restoration and ecological reconstruction. Landsat TM/ETM+ remote sensing data of the 2002, 2005, 2007, 2009 and 2011 was analyzed by ENVI and GIS technology, divided the vegetation coverage into 6 grades based on dimidiate pixel model, concluded the variation of ecological environment based on transfer matrix method, taked the Daliuta Mine as a case. The results indicated that average vegetation coverage in Daliuta Mine has increased integrally, and vegetation coverage changed from low, medium low and medium to medium and medium high, the vegetation coverage has somewhat. The dynamic monitoring of vegetation coverage can effectively reflect the variation of ecological environment in Daliuta Mine. This study provided a theoretical basis for the ecological reconstruction and sustainable development of Daliuta Mine.

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Periodical:

Advanced Materials Research (Volumes 1010-1012)

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377-380

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August 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Z.Q. Hu, W. Xiao. New idea and technology of Mine Land reclaimation: Concurrent Mining and Reclamation [J]. Coal Science and Technology, 2013, 41(9): 178-181.

Google Scholar

[2] Y. Jia. Analysis of the evolution trend of He-Bao-Pian Mining Area FVC and the driving force [D]. Shanxi University, (2012).

Google Scholar

[3] L.C. Li, L. Deng, Y. Cao. Vegetation dynamic monitoring in mining area based on NDVI serial images and dimidiate pixel model [J]. Journal of Central South University of Forestry and Technology, 2012, 32(6): 18-23.

Google Scholar

[4] X.C. Liu. Remote Sensing Dynamic Monitoring of vegetation coverage based on the mountains of northern Beijing TM images [J]. Science and Technology of West China, 2013, 12(11): 43-45.

Google Scholar

[5] S.T. Fu, Y. Zhou. Studies of the NDVI algorithm based on the sensing image [J]. Jiangxi Surveying and Mapping, 2010, 84(3): 31-32, 15.

Google Scholar

[6] S.G. Lei. Monitoring and analyzing the mining impacts on key environmental elements in desert area [J]. Journal of China Coal Society, 2010, 35(9): 1587-1588.

Google Scholar