Quantative inversion based on hyperspectral data for soil salinization in the ecological corridor of tarim river, xinjiang,china

CORC > 新疆生态与地理研究所 > 中国科学院新疆生态与地理研究所 > 中国科学院新疆生态与地理研究所(2010年以前数据)

	Quantative inversion based on hyperspectral data for soil salinization in the ecological corridor of tarim river, xinjiang,china
	Cun ; Chang1 ; 2 ; Xi ; Chen1 ; Anming ; Bao1 ; Geping ; Luo1
	2008
会议名称	2008 IEEE International Geoscience and Remote Sensing Symposium
会议日期	2008
会议地点	Boston, MA, United states
关键词	Differential equations - Inverse problems - Problem solving - Regression analysis - Remote sensing - Rivers - Salinity measurement - Soils - Field sampling - Field test - Hyperion - HyperSpectral - Hyperspectral Data - Hyperspectral remote sensing - Key factors - Regression model - Sampling methods - Soil salinity - Soil salinization - Spectral estimation - Surface soil - Tarim river - Xinjiang
页码	III1075-III1078
中文摘要	Soil salinization is regarded as the key factor that limits the growth of local vegetation at the lower reaches of the Tarim River. In order to Inverse the salinization level of surface soil, this paper attempts to adopt the following measures: soil salinization field sampling, soil salinization field hyperspectral sampling, and hyperspectral Remote sensing analysis, Finally,we used the regression model of soil salinity to develop the map of soil salinity concentration the lower reaches area of the Tarim River, with EO -1Hyperion data. the field test has validated this method's validity and feasibility. the result shows that we would solve that problem.©2008 IEEE. (13 refs.)
收录类别	EI
会议录	2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
ISBN号	13:9781424428083
内容类型	会议论文
源URL	[http://ir.xjlas.org/handle/365004/10794]
专题	新疆生态与地理研究所_中国科学院新疆生态与地理研究所(2010年以前数据)
推荐引用方式 GB/T 7714	Cun,Chang1,2,et al. Quantative inversion based on hyperspectral data for soil salinization in the ecological corridor of tarim river, xinjiang,china[C]. 见:2008 IEEE International Geoscience and Remote Sensing Symposium. Boston, MA, United states. 2008.