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Effects of precipitation intensity and temperature on NDVI-based grass change over Northern China during the period from 1982 to 2011

(2015) REMOTE SENSING. 7(8). p.10164-10183
Author
Organization
Abstract
The knowledge about impacts of changes in precipitation regimes on terrestrial ecosystems is fundamental to improve our understanding of global environment change, particularly in the context that heavy precipitation is expected to increase according to the 5th Intergovernmental Panel on Climate Change (IPCC) assessment. Based on observed climate data and the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) satellite-derived normalized difference vegetation index (NDVI), here we analyzed the spatio-temporal changes in grassland NDVI, covering 1.64 x 10(6) km(2), in northern China and their linkages to changes in precipitation and temperature during the period 1982-2011. We found that mean growing season (April-October) grass NDVI is more sensitive to heavy precipitation than to moderate or light precipitation in both relatively arid areas (RAA) and relatively humid areas (RHA), whereas the sensitivities of grass NDVI to temperature are comparable to total precipitation in RHA. Heavy precipitation showed the strongest impacts in more than half of northern China (56%), whereas impacts of light precipitation on grass NDVI were stronger in some areas (21%), mainly distributed in northwestern China, a typical arid and semi-arid area. Our findings suggest that responses of grasslands are divergent with respect to changes in precipitation intensities.
Keywords
NET PRIMARY PRODUCTION, CENTRAL GREAT-PLAINS, CLIMATE-CHANGE, PRIMARY PRODUCTIVITY, VEGETATION GROWTH, INNER-MONGOLIA, ECOSYSTEM PRODUCTIVITY, RAINFALL RELATIONSHIP, NORTHWESTERN CHINA, MODELING ANALYSIS

Citation

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MLA
Yuan, Xiuliang et al. “Effects of Precipitation Intensity and Temperature on NDVI-based Grass Change over Northern China During the Period from 1982 to 2011.” REMOTE SENSING 7.8 (2015): 10164–10183. Print.
APA
Yuan, X., Li, L., Chen, X., & Shi, H. (2015). Effects of precipitation intensity and temperature on NDVI-based grass change over Northern China during the period from 1982 to 2011. REMOTE SENSING, 7(8), 10164–10183.
Chicago author-date
Yuan, Xiuliang, Longhui Li, Xi Chen, and Hao Shi. 2015. “Effects of Precipitation Intensity and Temperature on NDVI-based Grass Change over Northern China During the Period from 1982 to 2011.” Remote Sensing 7 (8): 10164–10183.
Chicago author-date (all authors)
Yuan, Xiuliang, Longhui Li, Xi Chen, and Hao Shi. 2015. “Effects of Precipitation Intensity and Temperature on NDVI-based Grass Change over Northern China During the Period from 1982 to 2011.” Remote Sensing 7 (8): 10164–10183.
Vancouver
1.
Yuan X, Li L, Chen X, Shi H. Effects of precipitation intensity and temperature on NDVI-based grass change over Northern China during the period from 1982 to 2011. REMOTE SENSING. 2015;7(8):10164–83.
IEEE
[1]
X. Yuan, L. Li, X. Chen, and H. Shi, “Effects of precipitation intensity and temperature on NDVI-based grass change over Northern China during the period from 1982 to 2011,” REMOTE SENSING, vol. 7, no. 8, pp. 10164–10183, 2015.
@article{8534486,
  abstract     = {The knowledge about impacts of changes in precipitation regimes on terrestrial ecosystems is fundamental to improve our understanding of global environment change, particularly in the context that heavy precipitation is expected to increase according to the 5th Intergovernmental Panel on Climate Change (IPCC) assessment. Based on observed climate data and the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) satellite-derived normalized difference vegetation index (NDVI), here we analyzed the spatio-temporal changes in grassland NDVI, covering 1.64 x 10(6) km(2), in northern China and their linkages to changes in precipitation and temperature during the period 1982-2011. We found that mean growing season (April-October) grass NDVI is more sensitive to heavy precipitation than to moderate or light precipitation in both relatively arid areas (RAA) and relatively humid areas (RHA), whereas the sensitivities of grass NDVI to temperature are comparable to total precipitation in RHA. Heavy precipitation showed the strongest impacts in more than half of northern China (56%), whereas impacts of light precipitation on grass NDVI were stronger in some areas (21%), mainly distributed in northwestern China, a typical arid and semi-arid area. Our findings suggest that responses of grasslands are divergent with respect to changes in precipitation intensities.},
  author       = {Yuan, Xiuliang and Li, Longhui and Chen, Xi and Shi, Hao},
  issn         = {2072-4292},
  journal      = {REMOTE SENSING},
  keywords     = {NET PRIMARY PRODUCTION,CENTRAL GREAT-PLAINS,CLIMATE-CHANGE,PRIMARY PRODUCTIVITY,VEGETATION GROWTH,INNER-MONGOLIA,ECOSYSTEM PRODUCTIVITY,RAINFALL RELATIONSHIP,NORTHWESTERN CHINA,MODELING ANALYSIS},
  language     = {eng},
  number       = {8},
  pages        = {10164--10183},
  title        = {Effects of precipitation intensity and temperature on NDVI-based grass change over Northern China during the period from 1982 to 2011},
  url          = {http://dx.doi.org/10.3390/rs70810164},
  volume       = {7},
  year         = {2015},
}

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