Abstract
This paper explored the spatio-temporal patterns of vegetation productivity based on MODIS-NDVI and spatial auto-correlation analysis in the grassland of Inner Mongolia, China during 2011–2013. Two statistics indices, i.e., spatial auto-correlation and semi variance function, were applied in the analysis. The results showed that: (1) at regional scale, the NDVI presented a positive spatial auto-correlation, while at local scope NDVI showed high-high auto-correlation in the eastern part of the study region where the vegetation cover was relatively best. In contrast, NDVI displayed low-low auto-correlation in the western area where the vegetation cover was poor. (2) During 2011 to 2013, the structural factors explained 70 % of the total spatial variations impacting the vegetation cover, and the annual precipitation also played a significant role in the spatial variation of vegetation cover.
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Acknowledgments
This work was Supported by “Key Laboratory for National Geographic State Monitoring of National Administration of Surveying, Mapping and Geoinformation”, the “Strategic Priority Research Program - Climate Change: Carbon Budget and Relevant Issues” of the Chinese Academy of Sciences (No. XDA05050402) and the Natural Science Foundation of China (Grant Nos. 41071249 and 41371371).
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Wang, Z., Li, G., Dai, Y., Wang, Z., Sha, Z. (2016). Assessment of Spatio-Temporal Vegetation Productivity Pattern Based on MODIS-NDVI and Geo-Correlation Analysis. In: Bian, F., Xie, Y. (eds) Geo-Informatics in Resource Management and Sustainable Ecosystem. GRMSE 2015. Communications in Computer and Information Science, vol 569. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49155-3_70
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DOI: https://doi.org/10.1007/978-3-662-49155-3_70
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