PRELIMINARY STUDY OF URBAN LAND INFORMATION SYSTEM PLANNING

doi:10.6046/gtzyyg.2000.04.12

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Abstract

Land is the material base on which human life and economy development depend. With the growth of population, the contradiction between human and land use becomes more and more sharp. How to use the limited land rationally becomes a serious problem, and it has great effect in human life and social development. ULISis such a system that people can make rational use of land by it and can make the development project accord with land use. There is a basic framework of ULISin this essay, and it is concise and explicit.

Keywords Beijing—Hangzhou Grand Canal Remote sensing Change analysis Industrial pattern

Issue Date: 02 August 2011

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	XIE Bin
	LI Xiang
	YU Le
	SHU Liang
	ZHANG Deng-Rong
	WANG Ji-zhong

Cite this article:

XIE Bin,LI Xiang,YU Le, et al. PRELIMINARY STUDY OF URBAN LAND INFORMATION SYSTEM PLANNING[J]. REMOTE SENSING FOR LAND & RESOURCES, 2000, 12(4): 60-66.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2000.04.12 OR https://www.gtzyyg.com/EN/Y2000/V12/I4/60

[1] 藏淑英,王艳丽,郭少华等.地理信息系统及其在资源管理中的应用【J】.国土与自然资源研究,1997,(4):17.

[2] 陈实.环境管理与环境信息系统【J】.环境监测管理技术,1998,10(1):12.

[3] 张新生,靖学青,唐顺铁.城市地理信息系统的功能和内容【J】.云南地理环境研究,1997,9(1):81.

[4] 王晓栋.地理信息查询外壳的设计【J】.遥感技术与应用,1997,12(3):34～40.

[5] 叶树宁,张虹鸥,黎云.广东省小城市规划管理信息系统的研究【J】.热带地理,1997,17(3):238～242.

[6] 周成虎.洪水灾情评估信息系统研究【J】.地理学报,1993,48(1):11～18.

[7] 张新生,黄瑞红.城市地理信息系统若干问题的理论与技术方法【J】.中山大学学报(自然科学版),1998,37(2):121～123.

[8] 喻光明.UGIS及其在城市发展战略研究中的应用【J】.地理科学,1992,12(3):275～277.

[9] James O Wheeler. Quantitative Analysis and GIS in Urban Geography then and Now 【J】. Urban Geography, 1997, 18(2):95～99.

[10] 王万茂,潘文珠.土地资源管理学【M】.合肥:安徽科学技术出版社,1989.

[11] 陈烈,廖金凤.土地利用总体规划的理论与实践【M】.北京:科学出版社,1995.

[12] 邓良炳,张新生.地图*地理信息系统与规划【M】.广州:广东省地图出版社,1995.

[13] 张超,陈丙咸,邬伦.地理信息系统【M】.北京:高等教育出版社,1995.

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