1. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, CAS, Beijing 100094, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
3. International Centre on Space Technologies for Natural and Cultural Heritage under the Auspices of UNESCO, Beijing 100094, China
Alpine vegetations, whose distribution vary with changing altitudes, are located in inaccessible areas under cold climate condition. This has caused great challenges in terms of quantitatively characterizing the spatial distribution of alpine vegetation. For example, extremely huge time and money costs are the inevitable handicaps in traditional ground transects and quadrat surveys. Moreover, ground transects, and quadrat survey methods may cause some errors when local ecological features are used to characterize the expanded region. Based on the theory that vegetation of different types have different normalized difference vegetation index (NDVI) responses, NDVI analysis in this study was used to quantitatively characterize the spatial distribution of alpine vegetation. Firstly, a DEM-NDVI scatter diagram was plotted based on DEM and NDVI data. Secondly, statistical regression analysis was conducted in combination of ground survey data, high resolution remote sensing images with the DEM-NDVI scatter diagram. The spatial distribution of alpine vegetation was then derived upon the analysis results. We applied the method to a test area, Wolongguangou, Wolong Giant Panda Reserve. The results demonstrated that: (1) NDVI presented a 'Z' pattern as the altitude increased. (2) The DEM-NDVI scatter diagram expressed the NDVI variation of alpine vegetation more completely when compared to a traditional sample-point DEM-NDVI plot. (3) The elevations of alpine vegetation ranged from 3255 m to 4415 m on the northeast slope and 3193 m to 4473 m on the southwest slope, respectively. This finding was favorably consistent with the ground survey results in the respective regions.
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