基于环境一号HSI高光谱数据提取叶绿素a浓度的混合光谱分解模型研究
发布时间：2018-10-30 08:02
【摘要】：随着遥感技术的应用推广以及对研究精度的要求提高,越来越多的研究注意到混合像元的问题。在水质遥感监测中传感器探测的水体辐射亮度值是纯水和各种水质参数辐射亮度值的叠加,混合像元问题严重影响了水质定量遥感反演的准确性。基于环境一号HSI高光谱数据,首先分析了混合光谱分解模型的物理基础,然后基于采样点浓度大小和PPI(纯净像元指数)方法在遥感影像上提取纯水和叶绿素a的端元波谱,并利用线性光谱分解方法得到叶绿素a的丰度值找丰度值与叶绿素a浓度值之间的统计关系,建立了叶绿素a浓度反演的混合光谱分解模型,且反演精度较高。本文为水质定量遥感提供了一种新的思路。
[Abstract]:With the application of remote sensing technology and the improvement of research precision, more and more researchers pay attention to the problem of mixed pixel. In water quality remote sensing monitoring, the radiance value of water detected by sensor is the superposition of pure water and various water quality parameters. The mixed pixel problem seriously affects the accuracy of water quality quantitative remote sensing inversion. Based on environment 1 HSI hyperspectral data, the physical basis of the mixed spectral decomposition model was first analyzed, and then the end-component spectra of pure water and chlorophyll a were extracted from remote sensing images based on the concentration of sampling points and the PPI (pure pixel index) method. The statistical relationship between the abundance of chlorophyll a and the concentration of chlorophyll a is obtained by using the linear spectral decomposition method. The mixed spectral decomposition model for inversion of chlorophyll a concentration is established, and the inversion accuracy is high. This paper provides a new idea for quantitative remote sensing of water quality.
【作者单位】： 云南师范大学信息学院和西部资源环境地理信息技术教育部工程研究中心;
【基金】：国家科技支撑计划(2013BAJ07B00) 云南省科技计划(2012CA024) 高等学校博士学科点专项科研基金(20115314110005)资助
【分类号】：TP79
[Abstract]:With the application of remote sensing technology and the improvement of research precision, more and more researchers pay attention to the problem of mixed pixel. In water quality remote sensing monitoring, the radiance value of water detected by sensor is the superposition of pure water and various water quality parameters. The mixed pixel problem seriously affects the accuracy of water quality quantitative remote sensing inversion. Based on environment 1 HSI hyperspectral data, the physical basis of the mixed spectral decomposition model was first analyzed, and then the end-component spectra of pure water and chlorophyll a were extracted from remote sensing images based on the concentration of sampling points and the PPI (pure pixel index) method. The statistical relationship between the abundance of chlorophyll a and the concentration of chlorophyll a is obtained by using the linear spectral decomposition method. The mixed spectral decomposition model for inversion of chlorophyll a concentration is established, and the inversion accuracy is high. This paper provides a new idea for quantitative remote sensing of water quality.
【作者单位】： 云南师范大学信息学院和西部资源环境地理信息技术教育部工程研究中心;
【基金】：国家科技支撑计划(2013BAJ07B00) 云南省科技计划(2012CA024) 高等学校博士学科点专项科研基金(20115314110005)资助
【分类号】：TP79
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