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Open AccessArticle

Spatiotemporal Variation of NDVI in the Vegetation Growing Season in the Source Region of the Yellow River, China

by Mingyue Wang 1,2, Jun’e Fu 2,3,*, Zhitao Wu 1 and Zhiguo Pang 2,3
1
Institute of Loess Plateau, Shanxi University, Taiyuan 030006, China
2
China Institute of Water Resources and Hydropower Research, Beijing 100038, China
3
Research Center on Flood & Drought Disaster Reduction of the Ministry of Water Resources, Beijing 100038, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(4), 282; https://doi.org/10.3390/ijgi9040282
Received: 27 February 2020 / Revised: 20 April 2020 / Accepted: 22 April 2020 / Published: 24 April 2020
Research on vegetation variation is an important aspect of global warming studies. The quantification of the relationship between vegetation change and climate change has become a central topic and challenge in current global change studies. The source region of the Yellow River (SRYR) is an appropriate area to study global change because of its unique natural conditions and vulnerable terrestrial ecosystem. Therefore, we chose the SRYR for a case study to determine the driving forces behind vegetation variation under global warming. Using the Normalized Difference Vegetation Index (NDVI) and climate data, we investigated the NDVI variation in the growing season in the region from 1998 to 2016 and its response to climate change based on trend analysis, the Mann–Kendall trend test and partial correlation analysis. Finally, an NDVI–climate mathematical model was built to predict the NDVI trends from 2020 to 2038. The results indicated the following: (1) over the past 19 years, the NDVI showed an increasing trend, with a growth rate of 0.00204/a. There was an upward trend in NDVI over 71.40% of the region. (2) Both the precipitation and temperature in the growing season showed upward trends over the last 19 years. NDVI was positively correlated with precipitation and temperature. The areas with significant relationships with precipitation covered 31.01% of the region, while those with significant relationships with temperature covered 56.40%. The sensitivity of the NDVI to temperature was higher than that to precipitation. Over half (56.58%) of the areas were found to exhibit negative impacts of human activities on the NDVI. (3) According to the simulation, the NDVI will increase slightly over the next 19 years, with a linear tendency of 0.00096/a. From the perspective of spatiotemporal changes, we combined the past and future variations in vegetation, which could adequately reflect the long-term vegetation trends. The results provide a theoretical basis and reference for the sustainable development of the natural environment and a response to vegetation change under the background of climate change in the study area. View Full-Text
Keywords: vegetation; partial correlation analysis; trend prediction; the source region of the Yellow River vegetation; partial correlation analysis; trend prediction; the source region of the Yellow River
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Wang, M.; Fu, J.; Wu, Z.; Pang, Z. Spatiotemporal Variation of NDVI in the Vegetation Growing Season in the Source Region of the Yellow River, China. ISPRS Int. J. Geo-Inf. 2020, 9, 282.

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