Remote sensing retrieval of vegetation equivalent water thickness based on mixed pixel decomposition theory

doi:10.13474/j.cnki.11-2246.2019.0391

Abstract

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.

Key words: road vegetation, equivalent water thickness, mixed pixel decomposition, vegetation parameter inversion, Landsat 8

CLC Number:

P237

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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