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基于实测端元光谱的多光谱图像光谱模拟研究
  • 期刊名称:光谱学与光谱分析
  • 时间:0
  • 页码:2889-2893
  • 语言:中文
  • 分类:P237[天文地球—摄影测量与遥感;天文地球—测绘科学与技术]
  • 作者机构:[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, [3]中国科学院绿洲生态与荒漠环境重点实验室,新疆乌鲁木齐830011
  • 相关基金:国家自然科学基金项目(40861020); 中国科学院绿洲生态与荒漠环境重点实验室开放基金项目; 测绘遥感信息工程国家重点实验室开放基金项目(09R03); 教育部科学研究重点项目; 新疆自然科学基金项目(200821128)资助
  • 相关项目:新疆绿洲土壤电导率遥感建模研究
中文摘要:

地物光谱特性是遥感应用的基础。然而,在基于野外实测端元光谱的遥感应用中,由于测量尺度不同,导致同一地物光谱形态和反射率值存在很大差异,为遥感信息的定量反演带来困难。文章以新疆塔里木盆地北缘渭干河-库车河绿洲为研究区,选取裸土、植被两类地物作为研究对象,首先通过AVNIR-2传感器的光谱响应函数,实现了将野外实测端元光谱拟合为多光谱离散光谱,通过实例数据表明,拟和的多光谱与AVNIR-2像元光谱具有很好的相关性,在此基础上,采用线性算法建立端元光谱与遥感图像像元光谱的转换模型,实现了从实测端元光谱尺度向遥感多光谱像元尺度的定量光谱转换,为遥感定量分析奠定了一定基础。

英文摘要:

The characteristic of landscape spectrum is the basic of application of remote sensing and plays an important role in quantitative analysis of remote sensing.However,in spectrum-based application of remote sensing,because the difference of measuring scale and instrument resolution yield serious error in spectral curve and reflectance for the same landscape,there exists difficulty in quantitative retrieval of special information extraction of remote sensing.Firstly,the imaging simulation principles of the optics image was described and proposed A method using field measured endmember spectrum with higher spectrum resolutions to simulate spectrum of Multi-spectrum images with lower spectrum resolution was proposed.In the present paper,the authors take the delta oasis of Weigan and Kuqa rivers ocated in the North of Tarim Basin as study area,and choose vegetation and soil as study object.At first,we accomplished the simulation from field measured endmember for multi-spectrum by using the spectral response function of AVNIR-2,and found the large correlation between simulated multi-spectrum and pixel spectrum of AVNIR-2 by using the statistical analyse.Finally,the authors set up the linear model to accomplish the quantitative transformation from edmember scale to pixel scale.The result of this study has the realistic meaning for the quantitative application of remote sensing.

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