Comparison of applicability of remote sensing estimation model for grassland vegetation coverage

doi:10.13474/j.cnki.11-2246.2019.0311

Abstract

Abstract: Vegetation coverage and its changes have a direct impact on the stability of regional ecosystem, and this kind of effect is more obvious in grassland areas. In order to explore the best remote sensing estimation method of grassland vegetation coverage, this paper compares the estimation accuracy and applicability of binary pixel model, Carlson model and Baret model, and finally optimizes the parameters of Baret model to improve its estimation accuracy in grassland areas. The results of grassland calculation in Hulun Buir region of Inner Mongolia show that pixel dichotomy model overestimates the vegetation coverage, while Carlson model underestimates the vegetation coverage in low vegetation-covered areas and overestimates it in high vegetation-covered areas. And Baret model has the highest estimation accuracy in grassland areas. After parameter optimization of Baret model, the estimation accuracy in high vegetation-covered areas is improved by 4.9%.

Key words: grassland vegetation coverage, photographic method, NDVI, mixed pixel model

CLC Number:

P237

DONG Xiancong, LI Xiaojie. Comparison of applicability of remote sensing estimation model for grassland vegetation coverage[J]. 测绘通报, 2019, 0(10): 17-22.

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