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Article

Spatiotemporal Variation of Vegetation on the Qinghai–Tibet Plateau and the Influence of Climatic Factors and Human Activities on Vegetation Trend (2000–2019)

Institute of Desertification Studies, Chinese Academy of Forestry, Beijing 100091, China
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Remote Sens. 2020, 12(19), 3150; https://doi.org/10.3390/rs12193150
Received: 31 August 2020 / Revised: 18 September 2020 / Accepted: 22 September 2020 / Published: 25 September 2020
(This article belongs to the Special Issue Remote Sensing of Vegetation Dynamics and Resilience)
Vegetation is the terrestrial ecosystem component most sensitive to climate change. The Qinghai–Tibet Plateau (QTP), characterized by a cold climate and vulnerable ecosystems, has experienced significant warming in previous decades. Identifying the variation in vegetation coverage and elucidating its main driving factors are critical for ecological protection on the QTP. In this study, MOD13A2 Normalized Difference Vegetation Index (NDVI) data in the growing season (May to September) was used to represent QTP vegetation coverage during 2000–2019. The univariate linear regression, partial correlation analysis, residual analysis, and the Hurst exponent were used to detect the vegetation spatiotemporal dynamic, analyze the relationship between the vegetation and main driving factors, and predict the future vegetation dynamic. The growing season NDVI (GNDVI) of the QTP showed an extremely significant rate of increase (0.0011/a) during the study period, and 79.29% of the vegetated areas showed a greening trend. Over the past 20 years, the northeast, mid-east, and western edges of the plateau have been cooling and wetting, while the southwest, mid-west, and southeast have been warming and drying. Different climatic conditions lead to spatial differences in the response of plateau vegetation to climatic factors with generally 1–4 months lag time. The vegetation in the north of the plateau was mainly positively correlated with moisture, and negatively correlated with temperature, while the southern part showed positive correlation with temperature and negative correlation with moisture. Due to the enhancement of cooling and wetting trend in the last decade (2010–2019), especially in the south of the plateau, the greening trend of the plateau vegetation slowed down appreciably and even degraded in some areas. Human activities were mainly concentrated in the eastern part of the plateau—and its positive effect on vegetation was gradually increasing in most areas during study period, especially in the northeastern part. However, vegetation degradation caused by human activities in the southeast of the plateau should not be ignored. The future vegetation dynamic based on the Hurst exponent showed that the plateau faces a higher risk of vegetation degradation, which deserves more attention. This study explored the effect of climatic factors and human activities on vegetation of the QTP, thereby providing some guidance for the study of vegetation dynamic in the alpine areas. View Full-Text
Keywords: NDVI; vegetation dynamic; Hurst exponent; temperature; moisture; human activities; the Qinghai–Tibet Plateau NDVI; vegetation dynamic; Hurst exponent; temperature; moisture; human activities; the Qinghai–Tibet Plateau
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MDPI and ACS Style

Chen, J.; Yan, F.; Lu, Q. Spatiotemporal Variation of Vegetation on the Qinghai–Tibet Plateau and the Influence of Climatic Factors and Human Activities on Vegetation Trend (2000–2019). Remote Sens. 2020, 12, 3150. https://doi.org/10.3390/rs12193150

AMA Style

Chen J, Yan F, Lu Q. Spatiotemporal Variation of Vegetation on the Qinghai–Tibet Plateau and the Influence of Climatic Factors and Human Activities on Vegetation Trend (2000–2019). Remote Sensing. 2020; 12(19):3150. https://doi.org/10.3390/rs12193150

Chicago/Turabian Style

Chen, Junhan, Feng Yan, and Qi Lu. 2020. "Spatiotemporal Variation of Vegetation on the Qinghai–Tibet Plateau and the Influence of Climatic Factors and Human Activities on Vegetation Trend (2000–2019)" Remote Sensing 12, no. 19: 3150. https://doi.org/10.3390/rs12193150

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