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Spatial and Temporal Patterns of Global NDVI Trends: Correlations with Climate and Human Factors.

Authors :
Ya Liu
Yan Li
Shuangcheng Li
Motesharrei, Safa
Source :
Remote Sensing. Oct2015, Vol. 7 Issue 10, p13233-13250. 18p.
Publication Year :
2015

Abstract

Changes in vegetation activity are driven by multiple natural and anthropogenic factors, which can be reflected by Normalized Difference Vegetation Index (NDVI) derived from satellites. In this paper, NDVI trends from 1982 to 2012 are first estimated by the Theil-Sen median slope method to explore their spatial and temporal patterns. Then, the impact of climate variables and human activity on the observed NDVI trends is analyzed. Our results show that on average, NDVI increased by 0.46 × 10-3 per year from 1982 to 2012 globally with decadal variations. For most regions of the world, a greening (increasing)-browning (decreasing)-greening (G-B-G) trend is observed over the periods 1982-2004, 1995-2004, and 2005-2012, respectively. A positive partial correlation of NDVI and temperature is observed in the first period but it decreases and occasionally becomes negative in the following periods, especially in the Humid Temperate and Dry Domain Regions. This suggests a weakened effect of temperature on vegetation growth. Precipitation, on the other hand, is found to have a positive impact on the NDVI trend. This effect becomes stronger in the third period of 1995-2004, especially in the Dry Domain Region. Anthropogenic effects and human activities, derived here from the Human Footprint Dataset and the associated Human Influence Index (HII), have varied impacts on the magnitude (absolute value) of the NDVI trends across continents. Significant positive effects are found in Asia, Africa, and Europe, suggesting that intensive human activity could accelerate the change in NDVI and vegetation. A more accurate attribution of vegetation change to specific climatic and anthropogenic factors is instrumental to understand vegetation dynamics and requires further research. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
7
Issue :
10
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
110639150
Full Text :
https://doi.org/10.3390/rs71013233