Using the NDVI to identify variations in, and responses of, vegetation to climate change on the Tibetan Plateau from 1982 to 2012

Pang, Guojin; Wang, Xuejia; Yang, Meixue

doi:10.1016/j.quaint.2016.08.038

Cited by 168 publications

(123 citation statements)

References 57 publications

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“…Compared with the NDVI results of other studies, the annual variation in NDVI is within a narrow range. For instance, the NDVI values increased at a rate of 0.002/a on the Tibetan Plateau from 1982 to 2012 (Pang, Wang, & Yang, ) and increased at a rate of 0.0019/a on the Loess Plateau over the period from 1982 to 2015 (Li et al, ). The standard errors of the MVCs and average NDVIs are 0.0043 and 0.0046, respectively.…”

Section: Resultsmentioning

confidence: 99%

A significant increase in the normalized difference vegetation index during the rapid economic development in the Pearl River Delta of China

Mengmeng

Xia

2018

Land Degrad Dev

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Since 2000, the gross domestic product (GDP) of the Pearl River Delta (PRD) has increased by more than eight‐fold. Experiences throughout the world indicate that the impacts of economic development on vegetation are particularly important. This study analyzed the variations in vegetation coverage in the PRD from 2000 to 2016. Moderate resolution imaging spectroradiometer normalized difference vegetation index (NDVI) data were employed, whereas climate data, GDP, and population were also used as influencing factors. Topographic factors were introduced to explain the spatial vegetation patterns, and the impacts of human activities on vegetation were explored. The results revealed (a) the overall vegetation coverage in the PRD showed an increasing trend, and the overall average NDVI increased by 0.0033/a. (b) The spatial pattern did not change greatly, but the high and low NDVI values moved to low elevations and shallow topographic slopes where human activities were prevalent. This trend resulted in increased NDVI values in 38% of the area of the PRD (p < 0.01). (c) There was a positive correlation between NDVI and economic growth (GDP, population), with correlation coefficients greater than 0.8 (p < 0.01). NDVI is influenced by climate change and human activities (such as afforestation, resident lifestyles, and economic development policies). This study reveals that with good policies, both rapid economic development and vegetation coverage improvements can be simultaneously achieved in a region. The findings of this study are crucial for the sustainable development of the mega‐urban agglomerations of the PRD and Guangdong‐Hong Kong‐Macau Grand Bay.

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Section: Resultsmentioning

confidence: 99%

A significant increase in the normalized difference vegetation index during the rapid economic development in the Pearl River Delta of China

Mengmeng

Xia

2018

Land Degrad Dev

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“…The distribution of summer precipitation closely resembles the annual pattern (Figure (c)). Such precipitation patterns are also seen in a vegetation gradient across the plateau, which varies from forest to grassland and then desert (Liu and Yin, ; Pang et al ., ).…”

Section: Recent Progress Of Precipitation On the Tp From Observationsmentioning

confidence: 97%

“…Precipitation is a critical component of the water balance, and hence its amount relates to the survival of cryosphere elements in the TP. Moreover, precipitation has important implications for local ecological landscapes and ecosystem (Yang et al, 2004b;Chen et al, 2013b;Pang et al, 2016). The rainfall anomalies give rise to floods and droughts in the surrounding area.…”

Section: Introductionmentioning

confidence: 99%

Precipitation over the Tibetan Plateau during recent decades: a review based on observations and simulations

Wang

Pang

Yang

2017

Intl Journal of Climatology

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193

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Schematic diagram of precipitation on the Tibetan Plateau (TP). Precipitation on the TP has a significant influence on climate, water resources, and terrestrial ecosystem. Here, we review recent progresses of precipitation on the TP based on observations (meteorological stations and satellite remote sensing) and simulations (global climate models and downscaling models), and discuss some mechanisms accounting for precipitation changes. Finally, we conclude a strategy for future research to further study the TP precipitation. Such review provides crucial implications for hydrological and precipitation studies over the TP.

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“…This approach has been widely applied to analyze the relationship between NDVI and climatic factors [14,[81][82][83]. The r indicates the linear relationship and the p values indicate the significant correlation level between two variables.…”

Section: Correlation Between Ndvi and Climatic Variablesmentioning

confidence: 99%

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

Baniya

Tang

Huang

et al. 2018

Forests

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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) with seasonal variation of 0.0004 year −1 , p > 0.05; 0.0007 year −1 , p < 0.05; 0.0008 year −1 , p < 0.05 and 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 × 10 6 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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Using the NDVI to identify variations in, and responses of, vegetation to climate change on the Tibetan Plateau from 1982 to 2012

Cited by 168 publications

References 57 publications

A significant increase in the normalized difference vegetation index during the rapid economic development in the Pearl River Delta of China

A significant increase in the normalized difference vegetation index during the rapid economic development in the Pearl River Delta of China

Precipitation over the Tibetan Plateau during recent decades: a review based on observations and simulations

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

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