期刊
ECOLOGICAL INDICATORS
卷 112, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.ecolind.2020.106108
关键词
Net primary productivity; Inner Mongolia; Remote sensing; Spatial autocorrelation
资金
- National Key R&D Program of China [2016YFD0300201]
- National Science Foundation of China [41801078]
Monitoring variations in vegetation net primary productivity (NPP) contributes greatly to the evaluation of terrestrial ecosystem structure and function. Current research has focused on the trend changes of vegetation productivity but has largely ignored spatial correlation. This study selected MOD17A3 NPP data in Inner Mongolia to explore the spatiotemporal variations of NPP using spatial autocorrelation indices (Global Moran's I, Getis-Ord General G, Getis-Ord G(i)*, and Anselin Local Moran's I). This is helpful to examine whether NPP in Inner Mongolia has exhibited significant spatial cluster based on temporal variations and spatial patterns. NPP in Inner Mongolia has shown significant spatial cluster in high-value areas from 2000 to 2014 and demonstrated a polarized distribution. Although the east part of the study area generally showed a high NPP pattern, the northeast turned to low NPP pattern in 2001, 2004, 2007, and 2010 and the southeast turned to low NPP pattern in 2009 and 2013. The former variations were primarily affected by precipitation, while the latter variations were affected by both hydrothermal conditions and human activities. These results are useful to analyze spatial correlations and local abnormalities of NPP and provide references for integrated ecosystem management in Inner Mongolia.
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