| 基于混合像元分解理论的路域植被等量水厚度遥感反演 |
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| 引用本文： | 肖祥红,刘海洋,郭云开.基于混合像元分解理论的路域植被等量水厚度遥感反演[J].测绘通报,2019,0(12):83-86,95. |
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| 作者姓名： | 肖祥红 刘海洋 郭云开 |
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| 作者单位： | 湖南省第二测绘院,湖南 长沙,410119;长沙理工大学交通运输工程学院,湖南 长沙,410076 |
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| 基金项目： | 国家自然科学基金面上项目（41671498；41471421） |
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| 摘 要： | 为削弱混合像元对植被参数反演的影响，提出了基于混合像元分解理论反演路域植被等量水厚度的方法。利用PRO4SAIL模型正演获得的高光谱窄波段数据，模拟Landsat 8遥感影像宽波段植被冠层光谱数据，并进行等量水厚度的敏感植被指数的筛选；对覆盖研究区域的Landsat 8遥感影像进行线性混合像元分解，获取更加精确的植被冠层光谱反射率；同时，利用支持向量机构建等量水厚度估测模型，实现对路域植被等量水厚度的遥感反演。研究结果表明，利用混合像元分解后得到的植被冠层光谱参与模型反演得到的路域植被等量水厚度更加符合实际情况，为遥感影像反演植被参数提供了有效数据。
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| 关 键 词： | 路域植被 等量水厚度 混合像元分解 植被参数反演 Landsat8 |
| 收稿时间： | 2019-08-28 |
Remote sensing retrieval of vegetation equivalent water thickness based on mixed pixel decomposition theory |
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| XIAO Xianghong,LIU Haiyang,GUO Yunkai.Remote sensing retrieval of vegetation equivalent water thickness based on mixed pixel decomposition theory[J].Bulletin of Surveying and Mapping,2019,0(12):83-86,95. |
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| Authors: | XIAO Xianghong LIU Haiyang GUO Yunkai |
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| Institution: | 1. The Second Survey and Mapping Institute of Hunan Province, Changsha 410119, China;2. School of Transportation Engineering, Changsha University of Science&Technology, Changsha 410076, China |
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| Abstract: | In order to reduce the influence of mixed pixels on the inversion of vegetation parameters, an inversion of the equivalent water thickness of road vegetation is proposed based on the mixed pixel decomposition theory.In this paper, we use the hyperspectral narrow-band data obtained by PRO4SAIL model to simulate the broad-band vegetation canopy spectral data of Landsat 8 remote sensing image, and screen the sensitive vegetation index of equivalent water thickness.In addition, linear mixed pixel decomposition of Landsat 8 remote sensing images covering the study area is performed to obtain more accurate spectral reflectance of vegetation canopy.At the same time, the support vector machine is used to construct the equivalent water thickness estimation model to realize the remote sensing inversion of the equal water thickness of the vegetation in the road area.The results show that the equal water thickness of the vegetation in the vegetation inversion obtained by the decomposition of the vegetation canopy obtained by the mixed pixel is more in line with the actual situation, and provides effective data for the inversion of vegetation parameters by remote sensing images. |
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| Keywords: | road vegetation equivalent water thickness mixed pixel decomposition vegetation parameter inversion Landsat 8 |
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