A 2001–2015 Archive of Fractional Cover of Photosynthetic and Non-Photosynthetic Vegetation for Beijing and Tianjin Sandstorm Source Region

Xiaosong Li, Zengyuan Li, Cuicui Ji, Hongyan Wang, Bin Sun, Bo Wu and Zhihai Gao
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Xiaosong Li: Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
Zengyuan Li: Institute of Forest Resources Information Technique, Chinese Academy of Forestry, Beijing 100091, China
Cuicui Ji: Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
Hongyan Wang: Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
Bin Sun: Institute of Forest Resources Information Technique, Chinese Academy of Forestry, Beijing 100091, China
Bo Wu: Institute of Desertification Research, Chinese Academy of Forestry, Beijing 100091, China
Zhihai Gao: Institute of Forest Resources Information Technique, Chinese Academy of Forestry, Beijing 100091, China

Data, 2017, vol. 2, issue 3, 1-8

Abstract: Fractional covers of photosynthetic and non-photosynthetic vegetation are key indicators for land degradation surveillance in the dryland of China. However, there are no available, well validated, and multispectral-based products. Aiming for this, we selected the Beijing and Tianjin Sandstorm Source Region as the study area, and utilized the linear spectral mixture model for generating the fractional cover of PV, NPV, and bare soil, with endmember spectra retrieved from the field measured endmember spectral library, based on the MODIS NBAR data from 2001 to 2015. The unmixing results were validated through comparison with the field samples. The results show the method adopted could acquire rational and accurate estimation of fractional cover of photosynthetic vegetation ( R 2 = 0.6297, RMSE = 0.2443) and non-photosynthetic vegetation ( R 2 = 0.3747, RMSE = 0.2568). The dataset could provide key data support for the users in land degradation surveillance fields.

Keywords: non-photosynthetic vegetation; land degradation surveillance; linear spectral mixture model; endmember; MODIS NBAR (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2017
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