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基于综合高光谱指数的区域土壤盐渍化监测研究
引用本文:丁建丽,伍漫春,刘海霞,李争光. 基于综合高光谱指数的区域土壤盐渍化监测研究[J]. 光谱学与光谱分析, 2012, 32(7): 1918-1922. DOI: 10.3964/j.issn.1000-0593(2012)07-1918-05
作者姓名:丁建丽  伍漫春  刘海霞  李争光
作者单位:1. 新疆大学资源与环境科学学院,新疆 乌鲁木齐 830046
2. 绿洲生态教育部重点实验室,新疆 乌鲁木齐 830046
基金项目:国家国际科技合作项目(2010DFA92720-12);国家自然科学基金项目(40861020,41161063);霍英东教育基金项目(121018);教育部科学研究重点项目;新疆自然科学基金项目(200821128)资助
摘    要:选取新疆塔里木盆地北缘渭干河-库车河三角洲绿洲盐渍化土壤、植被及其光谱反射率为研究对象,对实测土壤、植被高光谱进行包络线、倒数、对数、均方根、一阶微分等各种光谱变换,分析并确定反映盐渍化程度最敏感的波段,结果表明:实测高光谱土壤、植被一阶微分光谱变换对土壤盐渍化响应程度最敏感;基于实测综合光谱指数的盐渍化监测高光谱模型可以准确提取土壤盐渍化信息,明显优于传统遥感方法中单纯利用植被指数或者土壤盐分指数的模型,对土壤盐渍化的高精度遥感监测研究具有较好促进作用。

关 键 词:植被指数  土壤盐分指数  综合高光谱指数  
收稿时间:2011-08-21

Study on the Soil Salinization Monitoring Based on Synthetical Hyperspectral Index
DING Jian-li,WU Man-chun,LIU Hai-xia,LI Zheng-guang. Study on the Soil Salinization Monitoring Based on Synthetical Hyperspectral Index[J]. Spectroscopy and Spectral Analysis, 2012, 32(7): 1918-1922. DOI: 10.3964/j.issn.1000-0593(2012)07-1918-05
Authors:DING Jian-li  WU Man-chun  LIU Hai-xia  LI Zheng-guang
Affiliation:1. College of Resource and Environmental Science, Xinjiang University, Urumqi 830046, China2. Lab for Oasis Ecosystem, Ministry of Education, Urumqi 830046, China
Abstract:The present paper selected the spectral reflectivity of saline soil and vegetation of Weigan-Kuqa River Delta Oasis in the northern margin of the Tarim Basin in Xinjiang as objects,and used various spectral transforms to process the data with continum removed methods, derivate spectra, reciprocal, first order differential and root mean square etc, then analyzed the spectrum features and decided the most sensitive band ranges most relevant to salinization, and used field hyperspectral vegetation index, soil salinity index and measured synthetical spectral index to respectively establish hyperspectral quantitative models which could evaluate the soil salinization degrees. By comparing various spectral transformations of hyperspectral data the result showed that the first derivative of measured soil and vegetation hyperspectral were most sensitive to soil salinization degrees. The hyperspectral quantitative model based on measured synthetical spectral index could monitor soil salinization accurately and was better than the models simply based on vegetation index or soil salinity index. The research provided some scientific basis with soil salinization detection.
Keywords:Vegetation index  Soil salinity index  Synthetical spectral index   
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