CURRENT DEVELOPMENT SITUATION AND PROSPECTS OF REMOTE SENSING IN THE WESTERN CHINA

doi:10.6046/gtzyyg.2002.04.01

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Abstract

Through more than twenty years' development, an integrated research system of remote sensing application has come into being, which is composed of spaceflight, aerial survey, ground detection and combination with GIS. Remote sensing in western China is an important technology for the investigation and monitoring of resources, environments and hazards. In this paper, the authors first reviewed the experimental research of remote sensing technique in western China, then systemically summarized the current situation of remote sensing application in western China and briefly enumerated parts of results. Combined with the requirements of Western Development, the paper also discussed the future development strategy of remote sensing in western China.

Keywords Hyperspectral remote sensing Independent component analysis(ICA) Kurtosis Unsupervised classification

Issue Date: 02 August 2011

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	LI Na
	ZHAO Hui-Jie

Cite this article:

LI Na,ZHAO Hui-Jie. CURRENT DEVELOPMENT SITUATION AND PROSPECTS OF REMOTE SENSING IN THE WESTERN CHINA[J]. REMOTE SENSING FOR LAND & RESOURCES, 2002, 14(4): 1-6.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2002.04.01 OR https://www.gtzyyg.com/EN/Y2002/V14/I4/1

[1] 蒋承菘.二十一世纪初地质工作的若干思考［J］.中国地质,2001,7(7):1-8.

[2] 寿嘉华.新形势下地质调查工作的责任与任务［J］.中国地质,2001,4(4):1-5.

[3] 童庆喜,郑立中.中国遥感奋进创新二十年大事记［C］. 国家遥感中心,2001.

[4] 李文辉,等.岩溶石山地区石漠化遥感调查技术方法研究［J］. 国土资源遥感 2002,1:34-37.

[5] 崔宏伟.数字地球［M］.北京:中国环境科学出版社,1999.

[6] 中国科学院遥感应用研究所编.遥感知识创新文集［C］. 北京:中国科学技术出版社,1999:7-255.

[7] 肖克炎,等.与GIS平台的矿产资源评价富足系统的研制
[A]. 遥感与新世纪［M］. 北京:气象出版社,1999.

[8] 童庆喜.遥感发展趋势的思考
[A]. 遥感新进展与发展战略［M］.北京:中国科学技术出版社,1996.

[9] 刘燕君,等.遥感图像上的油气晕［J］. 环境遥感,1992:7(1).

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