Abstract
Vegetation coverage is an important biophysical parameter of terrestrial ecosystems. In this study, MODIS data were used to estimate sparse vegetation coverage using an improved dimidiate pixel model in northern China. Specifically, Normalized Difference Vegetation Index (NDVI), Fraction of Photosynthetically Active Radiation (FPAR) and Leaf Area Index (LAI) products acquired from MOD09A1 and MOD15A2 were selected to acquire the sparse vegetation coverage in northern China. When 1 < LAI < 3, the no-dense model was used and dense model was used under other conditions. The sparse vegetation coverage results from 2001 to 2015 were used to analyze the spatiotemporal change in this area. In this region, vegetation degradation, vegetation non-alteration and vegetation restoration cover 19.18%, 37.91% and 42.91%, respectively. In recent 5 years, vegetation situation is deteriorated, especially in local area. Although vegetation situation is improved on a long time and large scale, we should pay much attention to vegetation degradation in recent years and local areas.
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Acknowledgements
This work was funded by Foundation of Hebei Educational Committee (QN2018054, BJ2018043), Humanities and Social Sciences Fund of Ministry of Education (18YJCZH257), Forestry Public Benefit Scientific Research Special Project of PR China (201504420) and National Natural Science Foundation of China (31670706, 31600585).
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Feng, L., Jia, Z., Li, Q. et al. Spatiotemporal Change of Sparse Vegetation Coverage in Northern China. J Indian Soc Remote Sens 47, 359–366 (2019). https://doi.org/10.1007/s12524-018-0912-x
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DOI: https://doi.org/10.1007/s12524-018-0912-x