title: Understanding vegetation changes in northern China and Mongolia with change vector analysis.
abstract: In recent years, a close link between vegetation change and climate change has been established. Vegetation change can be detected with remotely sensed images, especially with normalized difference vegetation index time series records. We used change vector analysis, especially change vector magnitude (CV magnitude), as an indicator to better understand vegetation change. Twenty-one layers of CV magnitude for each 10-day period from April to October have been acquired. Maxima, range, standard deviation, mean, and minima of CV magnitude were obtained and analyzed, identifying 11 regions with different types of vegetation change during different 10-day periods. In addition, the months of maximum CV magnitude were determined to help predict future vegetation change. The following conclusions were drawn: (a) CV magnitude can serve as an indicator to compare vegetation conditions among different years; (b) 11 typical regions were identified in the study area that show vegetation changes between 1999 and 2006;
authors: Beijing Research Center for Information Technology in Agriculture, Beijing, 100097 China.
authors: Xiaohe
authors: X
authors: Gu
authors: Jiangsu Academy of Agricultural Sciences, Nanjing, 210014 China.
authors: Weiguo
authors: W
authors: Li
authors: Beijing Research Center for Information Technology in Agriculture, Beijing, 100097 China.
authors: Lei
authors: L
authors: Wang
keywords: CV magnitude; Change vector analysis (CVA); NDVI time series; Vegetation dynamic