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REMOTE SENSING FOR LAND & RESOURCES    2014, Vol. 26 Issue (2) : 1-4     DOI: 10.6046/gtzyyg.2014.02.01
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Mine remote sensing monitoring and assessment characteristics and the index system
ZHOU Jinsheng, NIU Jianying, ZHANG Xu, YU yanrui
China University of Geosciences(Beijing), Beijing 100083, China
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Abstract  Remote sensing monitoring is used by mine remote sensing monitoring and assessment so as to understand the situation of mineral resources development, mining environment and evaluate mineral resource planning implementation, thus providing the basis for mineral resources planning, mining order rectifying and mine environment governing. The authors analyzed the situation of evaluating the implementation effect of the mine remote sensing monitoring, which is characterized by numerous objects and contents, wide applications and considerable difficulties. In view of such a complex situation, this paper puts forward the index evaluation system for the mineral resources monitoring result, benefit and efficiency, which consists of three primary and nine secondary indexes. According to the experimental evaluation conclusion, some constructive suggestions, such as simplification of the index system and emphasis on the dynamic assessment of continuous monitoring area, have been put forward in this paper.
Keywords Landsat TM      nighttime light data      urban expansion      classification and regression tree      Zhejiang Province     
:  TP79  
Issue Date: 28 March 2014
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CHEN Zheng
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CHEN Zheng,HU Deyong,ZENG Wenhua, et al. Mine remote sensing monitoring and assessment characteristics and the index system[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(2): 1-4.
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[1] 周进生,牛建英,张旭,等.矿山开发遥感调查与监测成果集成与综合研究[R].北京:中国地质大学(北京),2012. Zhou J S,Niu J Y,Zhang X,et al.Research on mine development and remote monitoring results of integration and comprehensive[R].Beijing:China University of Geosciences(Beijing),2012.
[2] 周进生,牛建英,朱瑞兵,等.关于矿山遥感监测实施效果评估的思考[J].资源与产业,2012,14(4):96-100. Zhou J S,Niu J Y,Zhu R B,et al.Views on evaluation of implementation effect of remote sensing monitoring[J].Resources & Industries,2012,14(4):96-100.
[3] 张焜,马世斌,刘丽萍.基于SPOT5数据的盐湖矿产开发及矿山环境遥感监测[J].国土资源遥感,2012,24(3):146-153. Zhang K,Ma S B,Liu L P.Remote sensing monitoring of the mineral resources exploration and mining environment of the salt lake based on SPOT5 data[J].Remote Sensing for Land and Resources, 2012,24(3):146-153.
[4] 赵福岳.全国区域地质环境遥感监测技术体系框架建设研究[J].国土资源遥感,2010,22(增刊):1-3. Zhao F Y.The building of the technical system for national regional geological environment monitoring of remote sensing technology[J]. Remote Sensing for Land and Resources,2010,22(sl):1-3.
[5] 范一大,王磊,夏娟,等.我国低温雨雪冰冻灾害遥感监测评估技术——研究与应用[J].自然灾害学报,2008,17(6):21-25. Fan Y D,Wang L,Xia J,et al.Remote sensing monitoring and assessment techniology for cryogenic ferrzing rain and snow disasters in China:Research and application[J].Journal of Natural Disasters,2008,17(6):21-25.
[6] 翟晶宇.矿产资源规划与可持续发展[J].活力,2006(4):55. Zhai J Y.Planning and sustainable development of mineral resources[J].Vitality,2006(4):55.
[7] 王世军,白聚泊.矿产资源资产的价值管理[J].中国矿业,2004,13(11):13-15. Wang S J,Bai J B.The vaive management of the mineral resources property[J].China Mining Magazine,2004,13(11):13-15.
[8] 闫宗平.地震次生地质灾害特征及发展趋势[J].科技致富向导,2011(9):138. Yan Z P.Earthquake secondary geological disasters characteristics and development trend[J].Guide of Sci-tech Magazine,2011(9):138.
[9] 王逊,陈伟涛.遥感技术在黑龙江省矿山地质环境监测中的应用[J].安全与环境工程,2009,16(6):20-25. Wang X,Chen W T.Monitoring on geoenvironment in mining districts using remote sensing technique in Heilongjiang Province[J].Safety and Environmental Engineering,2009,16(6):20-25.
[10] 周萍,李志忠.空间遥感技术(3S)用于矿山地质环境与生产安全监测[J].中国矿业,2002,11(5):1-3,7. Zhou P,Li Z Z.Spatial remote sensing technology(3S)applied in geological environment and production safety monitoring of mine[J].China Mining Magazine,2002,11(5):1-3,7.
[11] 潘圣明.落实科学发展建设生态文明努力开创矿山自然生态环境保护工作新局面—— 在全省矿山自然生态环境保护与治理工作现场会上的讲话[J].浙江国土资源,2007(12):15-17. Pan S M.Implement the scientific development and construction of ecological civilization and strive to create a new situation in the mine ecological environment-in the province of mine ecological environment protection and management of natural speech at the meeting site[J].Zhejiang Land and Resources,2007(12):15-17.
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