A Comparison and Selection of the Methods for Mine Geological Environment Assessment Based on GIS and RS

doi:10.6046/gtzyyg.2010.03.19

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Abstract

The Huludao mining area in Liaoning Province was chosen as the study area. In this paper, grid method, vector polygon method and buffer method were used to conduct the assessment of mine geological environment in Huludao. Results of the assessment were comparatively analyzed, and the vector polygon method yielded the best result. It is thus held that the vector polygon method can be used to perform mine geological environment assessment in this area.

Keywords SAR Internal wave depth Internal wave amplitude

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	TP 79

Issue Date: 20 September 2010

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	YANG Jin-song
	HUANG Wei-gen
	ZHOU Cheng-hu
	ZHOU Chang-bao
	XU Ming-guang
	XIAO Qing-mei

Cite this article:

YANG Jin-song,HUANG Wei-gen,ZHOU Cheng-hu, et al. A Comparison and Selection of the Methods for Mine Geological Environment Assessment Based on GIS and RS[J]. REMOTE SENSING FOR LAND & RESOURCES, 2010, 22(3): 92-96.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2010.03.19 OR https://www.gtzyyg.com/EN/Y2010/V22/I3/92

［1］DZ/T 223-2007.矿山环境保护与综合治理方案编制规范［S］.

［2］中华人民共和国国土资源部令第44号.矿山地质环境保护规定［Z］.

［3］乔晓英,王文科.基于GIS的冯家山灌区地质环境评价研究［J］.西安工程学院学报,2002,24(1):39-42.

［4］武健强,于军,余勤.苏锡常地区地质环境信息系统设计与实践［J］.地质与勘探,2002,38(6):66-69.

［5］武健强,余勤,等.基于GIS的苏锡常地区地质环境现状评价［J］.水文地质工程地质,2002(3):63-67.

［6］赵法锁,宋飞,等.基于GIS的略阳县地质环境质量评价［J］.地球科学与环境学报,2006,28(1):88-91.

［7］鲁明星,孙金华,吴班.基于GIS的唐山市区环境地质模糊评价分析［J］.地震工程与工程振动,2006,26(3):34-36.

［8］李娜,高德政.基于GIS的地质环境评价研究［J］.四川地质学报,2007,27(4):292-295.

［9］李娜,高德.基于GIS的嘉陵江上游地质环境评价［J］.资源与产业,2007,9(6):32-35.

［10］DD 2004-02.区域环境地质调查总则(试行)［S］.

［11］彭慧,徐利淼.缓冲区分析与生态环境影响评价［J］.天津师范大学学报(自然科学版),2004,24(2):34-37.

［12］李凤海.基于GIS的矿区生态环境评价［J］.金属矿山,2007,(7):70-72.

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