Distribution and Variation of Forests in China from 2001 to 2011: A Study Based on Remotely Sensed Data
AbstractForests are one of the most important components of the global biosphere and have critical influences on the Earth’s ecological balance. Regularly updated forest cover information is necessary for various forest management applications as well as climate modeling studies. However, map products are not widely updated at continental or national scales because the current land cover products have overly coarse spatial resolution or insufficiently large training data sets. This study presents the results of forests distribution and variation information over China using Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series data with the first layer of MODIS Land Cover Type product (MODIS LC-1). The NDVI time series histogram characteristic curves for forestland were estimated from MODIS LC-1 and MODIS NDVI time series data. Based on the differences of histograms among different forests, we obtained the 2001–2011 forests distribution for China at a spatial resolution of 500-m × 500-m. The overall accuracy of validation was 80.4%, an increase of 12.8% relative to that obtained using MODIS LC-1 data. The 2001–2011 forestland pure and mixed pixels of China accounted for an average of 33.72% of all pixels. There is a gradual increase in China’s forestland coverage during 2001–2011; however, the relationship is not statistically significant. View Full-Text
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Zhao, X.; Xu, P.; Zhou, T.; Li, Q.; Wu, D. Distribution and Variation of Forests in China from 2001 to 2011: A Study Based on Remotely Sensed Data. Forests 2013, 4, 632-649.
Zhao X, Xu P, Zhou T, Li Q, Wu D. Distribution and Variation of Forests in China from 2001 to 2011: A Study Based on Remotely Sensed Data. Forests. 2013; 4(3):632-649.Chicago/Turabian Style
Zhao, Xiang; Xu, Peipei; Zhou, Tao; Li, Qing; Wu, Donghai. 2013. "Distribution and Variation of Forests in China from 2001 to 2011: A Study Based on Remotely Sensed Data." Forests 4, no. 3: 632-649.