Title :
Fractional Forest Cover Changes in Northeast China From 1982 to 2011 and Its Relationship With Climatic Variations
Author :
Kun Jia ; Shunlin Liang ; Xiangqin Wei ; Qiangzi Li ; Xin Du ; Bo Jiang ; Yunjun Yao ; Xiang Zhao ; Yuwei Li
Author_Institution :
State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China
Abstract :
Forest cover information is essential for natural resource management and for climate change studies. In this paper, the fractional forest cover (FFC) in Northeast China was estimated using neural networks (NNs) based on the Global Inventory Modeling and Mapping Studies (GIMMS3g) Normalized Difference Vegetation Index (NDVI) data with 8-km resolution from 1982 to 2011. Furthermore, the relationship between FFC and two key climatic parameters (temperature and precipitation) was also analyzed. The validation results indicated a satisfactory performance (R2 = 0.81, RMSE = 11.7%) of the FFC estimation method using NNs and time-series GIMMS3g NDVI data. The temporal and spatial characteristics of FFC changes were analyzed. The forest cover had a slightly decreasing trend during the study period for the entire Northeast China region. However, there were two distinct periods with opposite trends in the FFC change. The FFC had first increased from 1982 to 1998 (0.391% year-1), and then decreased from 1998 to 2011 (-0.667% year-1). The correlation analysis between the FFC and the climatic variations suggested that temperature and precipitation were not the decisive factors on controlling FFC changes in most of the Northeast China regions, and active forest disturbance might be the more important factor for FFC change in Northeast China.
Keywords :
atmospheric precipitation; atmospheric temperature; climatology; neural nets; time series; vegetation; vegetation mapping; AD 1982 to 2011; Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index data; Northeast China region; active forest disturbance; climate change; climatic parameters; climatic variations; correlation analysis; forest cover information; fractional forest cover estimation method; natural resource management; neural networks; precipitation; spatial characteristics; temporal characteristics; time-series GIMMS3g NDVI data; Artificial neural networks; Earth; Estimation; MODIS; Market research; Meteorology; Remote sensing; Climate change; Northeast China; forest; fractional forest cover (FFC); neural networks (NNs);
Journal_Title :
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
DOI :
10.1109/JSTARS.2014.2349007