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 (R2 = 0.6297, RMSE = 0.2443) and non-photosynthetic vegetation (R2 = 0.3747, RMSE = 0.2568). The dataset could provide key data support for the users in land degradation surveillance fields.
Highlights
Fractional covers of photosynthetic and non-photosynthetic vegetation are key indicators for land degradation surveillance in the dryland of China
The results show the method adopted could acquire rational and accurate estimation of fractional cover of photosynthetic vegetation (R2 = 0.6297, RMSE = 0.2443) and non-photosynthetic vegetation (R2 = 0.3747, RMSE = 0.2568)
Fractional cover of vegetation plays a key role in resisting wind and water erosion, it has been widely used as the indicator for land degradation monitoring and assessment
Summary
Fractional cover of vegetation plays a key role in resisting wind and water erosion, it has been widely used as the indicator for land degradation monitoring and assessment. Normalized difference senescent vegetation index (NDSVI) [11], a ratio of moderate resolution These methods, based on the hyperspectral sensors, face a great challenge for land imaging spectrometer (MODIS) bands 7 and 6 [1], and the dead fuel index (DFI) [12] —were proposed degradation surveillance due to the shortage of dataisacquisition large regions. This approach area-specific,ability and notfor well validated in other environments. The PV and NPV cover datasets for the BTSSR based on AUTOMCU with MODIS data was produced in order to provide support for land degradation surveillance
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