Quantitative Inversion Vegetation Equivalent Water Thickness by Combined Model of PRO4SAIL and the Support Vector Regression

doi:10.13474/j.cnki.11-2246.2017.0253

测绘通报 ›› 2017, Vol. 0 ›› Issue (8): 50-55.doi: 10.13474/j.cnki.11-2246.2017.0253

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Quantitative Inversion Vegetation Equivalent Water Thickness by Combined Model of PRO4SAIL and the Support Vector Regression

LI Danna¹, GUO Yunkai¹, ZHU Shankuan¹, LIU Ning², LIU Lei², JIANG Ming²

1. School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410076, China;
2. Institute of Surveying and Mapping Remote Sensing Application Technology, Changsha University of Science & Technology, Changsha 410076, China

Received:2017-06-12 Online:2017-08-25 Published:2017-08-29

Abstract

Abstract: To monitor the ecological environment of the road vegetation, remote sensing image and the radioactive transfer model are used to estimate vegetation equivalent water thickness. In this paper, a combined model of PRO4SAIL and support vector regression is presented to estimate vegetation equivalent water thickness. We explore the feasibility and accuracy of inversion vegetation parameters of the combined model of PRO4SAIL and support vector regression by the Landsat7 ETM+image and measured data. Research shows that the combined model has good prediction ability, and the accuracy of the equivalent water thickness is high. It also can improve the strong support for support vector machine model applied to remote sensing image inversion of vegetation parameters.

Key words: equivalent water thickness, PRO4SAIL, support vector regression, inversion vegetation parameters

CLC Number:

P237

LI Danna, GUO Yunkai, ZHU Shankuan, LIU Ning, LIU Lei, JIANG Ming. Quantitative Inversion Vegetation Equivalent Water Thickness by Combined Model of PRO4SAIL and the Support Vector Regression[J]. 测绘通报, 2017, 0(8): 50-55.

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Quantitative Inversion Vegetation Equivalent Water Thickness by Combined Model of PRO4SAIL and the Support Vector Regression

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