Extraction of remote sensing abundance information of typical vegetation in southern China

doi:10.13474/j.cnki.11-2246.2019.0176

Abstract

Abstract:

Aiming at the problem of a large number of mixed pixels in the extraction of typical vegetation abundance in the southern hilly region of remote sensing images, in order to further improve the precision of linear unmixing, the EVI time series curves of typical vegetation (endmember) and mixed pixels in the south of Landsat 8 time series images are constructed by calculating the EVI value of pixels. The vegetation index change curves of various feature types in different growth periods are analyzed, and it is found that different features have their own independent fluctuation rules in the vegetation index time series.By selecting multiple endmembers and their EVI time series curves, the spectral matching method is used to match the EVI time series curve and multiple endmembers, and the purpose of spectral unmixing using different endmember combinations is achieved. The test results show that compared with the traditional method, the precision of broad-leaf forest unmixing is obviously improved, and the precision of coniferous forest unmixing is also improved. The research results can provide strong support for the study of vegetation environment in the southern hilly region.

Key words: southern hills, typical vegetation, broad leaf-conifer mixed forest, mixed pixel unmixing, EVI time series

CLC Number:

P237

GUO Yunkai, LIU Haiyang, JIANG Ming, ZHU Jiaming. Extraction of remote sensing abundance information of typical vegetation in southern China[J]. 测绘通报, 2019, 0(6): 16-18,28.

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