Spatial and Temporal Variation of NDVI in Response to Climate Change and the Implication for Carbon Dynamics in Nepal

B. Baniya,Q. Tang,Zhongwei Huang,Siao Sun,K. Techato

Published 2018 in Forests

ABSTRACT

Nepal is a country of contrast, with varying altitude, climate and vegetation from the top of high mountains to the tropical forest in low lands. The terrestrial vegetation has rapidly been altered by climate change in Nepal. The spatial and temporal evolution of vegetation and its linkage to climatic variables were analyzed using the Normalized Difference Vegetation Index (NDVI) obtained from Advanced Very High Resolution Radiometer (AVHRR) sensors. A linear regression model and Sen’s slope method were used to estimate NDVI trends and the Pearson correlation between NDVI and climatic variable, i.e., temperature and precipitation were calculated to identify the role of climate in vegetation changes. The carbon dynamics were also measured using a biomass carbon density estimation model. Results showed that NDVI experienced an overall increasing trend in Nepal from 1982–2015. The NDVI significantly increased at the rate of 0.0008 year−1 (p 0.05; 0.0007 year−1, p 0.05 in winter, pre-monsoon, monsoon and post-monsoon seasons, respectively. The NDVI relative change ratio (RCR) was 6.29% during last 34 years in Nepal. The correlation between NDVI and temperature was significantly positive (r = 0.36, p = 0.03), but there was a negative correlation with precipitation (r = −0.21, p = 0.28). Altogether, 82.20% of the study areas showed a positive correlation with temperature in which 34.97% was significant and 69.23% of the area had a negative correlation (16.35% significant, p < 0.05) with precipitation. In addition, NDVI-based carbon estimation showed that Nepal’s forest total carbon stock is 685.45 × 106 t C (i.e., an average of 115.392 t C/ha) with an annual carbon sequestration rate of 0.10 t C/ha from 1982–2015. The results suggest that NDVI variation is more sensitive to temperature than precipitation and it is valuable to measure carbon dynamics in Nepal.

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