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REMOTE SENSING FOR LAND & RESOURCES    2001, Vol. 13 Issue (4) : 13-19,68     DOI: 10.6046/gtzyyg.2001.04.03
Technology Application |
THE APPLICATION OF GIS TO LAND MANAGEMENT——THE CONSTRUCTION OF A MODEL FOR POTENTIAL LANDSLIDE HAZARD EVALUATION
Tzu-how CHU1, Shyh-jeng CHYI2, Nai-yi YANG1, Chiu-ling HSU1
1. Department of Geography, National Taiwan University, Taipei;
2. Department of Geography, National Kaohsiung Normal University, Kaohsiung
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Abstract  

In this paper, a model is constructed for evaluating the potential geological hazards in areas designated as the class C building classification on the slope land. The development of unstable slope land often concurs with dangerous geological hazards. Various mass movement hazards, such as landslide, slump, creep, and mudflow, may be triggered by indiscriminate development activities on slope land with high hazard potential. Government land management administration often lacks both adequate tools and data to assess the potential hazards which are likely to concur with the development of certain areas. It is critical for the land manager to integrate data from various sources within the government agencies, and to use the geographic information system as an able assistant to obtain speedy and proper evaluation results.

Keywords Wetland      Yancheng      Information extraction      Remote sensing monitoring     
Issue Date: 02 August 2011
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ZHAO Yu-Ling
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ZHAO Yu-Ling,YU WAN-Xin,NIE Hong-Feng. THE APPLICATION OF GIS TO LAND MANAGEMENT——THE CONSTRUCTION OF A MODEL FOR POTENTIAL LANDSLIDE HAZARD EVALUATION[J]. REMOTE SENSING FOR LAND & RESOURCES, 2001, 13(4): 13-19,68.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2001.04.03     OR     https://www.gtzyyg.com/EN/Y2001/V13/I4/13


[1] 张石角.山坡地潜在危险之预测及其在环境影响评估之应用[J].中华水土保持学报,1987,18(2):41-62.




[2] 张石角.台湾各地质分区边坡崩塌类型及其预测方法(一)
[Z].行政院农委会委托台大地理学系专题研究,1992.




[3] 高国平.地理信息系统在土地利用规划上之应用-以基隆河集水区为例
[D].台北:台湾大学,1988.




[4] 李丽玲.土地资源数据库之建立与应用-以评估山坡地潜在灾害为例
[D].台北:台湾大学,1995.




[5] 陈紫娥.台湾山坡地工程与地质调查与评估法之比较研究[J].工程环境会刊,1993, 13:26-46.




[6] Dangermand J. Geographic Database System[J]. Geo Processing, 1986, (3): 17-29.




[7] Hansen A. Landslides hazard analysis
[A].in: Brunsden. D. and Prior. D B (ed.) Slope Instability[M].1984, 523-602.




[8] Shirazi M A. Land classification used to select abandoned hazardous waste study sites[J]. Environment Management, 1984, 8(4): 281-286.

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