Impacts of Climate Change and Human Activities on NDVI in the Qinghai-Tibet Plateau

Sun, Lu; Li, Hao; Wang, Jia; Chen, Yuhan; Xiong, Nina; Zong, Wang; Wang, Jing; Xu, Jiangqi

doi:10.3390/rs15030587

Cited by 21 publications

(9 citation statements)

References 40 publications

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“…Previous studies have shown that vegetation changes in the Qinghai-Tibet Plateau was mainly influenced by temperature and precipitation [21,22]. However, climate variability also includes climate factors, such as humidity, wind speed, sunlight duration, solar radiation, and so on [78]. Therefore, more climate factors should be used to analyze changes in vegetation changes in the study area for future research.…”

Section: Limitations Of the Current Studymentioning

confidence: 99%

Quantitative Analysis of Climate Variability and Human Activities on Vegetation Variations in the Qilian Mountain National Nature Reserve from 1986 to 2021

Wang,

Zhang,

et al. 2023

Forests

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Rapid climate variability and intense human activities generate obvious impacts on the Qilian Mountains ecosystem. The time series of fractional vegetation coverage (FVC) from 1986 to 2021 were used to quantify the impact of climate variability and human activities on vegetation variations in the Qilian Mountain National Nature Reserve (QMNNR), using 3147 land satellite images based on the Google Earth Engine cloud platform. The contributions of climate variability and human activities to FVC were quantified using multiple regression residual analysis. Partial correlation and correlation methods were used to quantify the impact of temperature, precipitation, and human activity footprints on FVC. The results showed that from 1986 to 2021, the increase rate of FVC was 1.7 × 10−3 y−1, and the high vegetation coverage of the FVC was mainly distributed in the southeastern part of the reserve. In contrast, the low vegetation coverage was mainly distributed in the northwest part of the reserve. The Mann–Kendall mutation test found that the year of 2009 was the year of the mutation. The growth rate of FVC from 2010 to 2021 was greater than that from 1986 to 2009. In addition, climate variability and human activities exhibited a remarkable spatial heterogeneity in FVC changes. Climate variability and human activities contributed 49% and 51% to the increase in FVC in the reserve, respectively, and the contribution of human activities was greater than that of climate variability. The warming and humidification phenomena in the reserve were obvious. However, precipitation was the dominant factor affecting the dynamic changes in FVC. This study improves our understanding of the response of vegetation dynamics to the climate and human activities in the QMNNR.

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Section: Limitations Of the Current Studymentioning

confidence: 99%

Quantitative Analysis of Climate Variability and Human Activities on Vegetation Variations in the Qilian Mountain National Nature Reserve from 1986 to 2021

Wang,

Zhang,

et al. 2023

Forests

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“…The QTP region is rich in various vegetation types, where the main grassland types are alpine meadows, alpine grasslands, and sparse grasslands, but climate change in recent years has led to great uncertainty about the fragile ecosystem on the plateau [22]. In the QTP, the impact of human activities on vegetation is significantly weaker than the effects brought about by climate change, and there are notable regional differences [23,24]. Consequently, in this study, the factor of human activities is disregarded.…”

Section: Study Areamentioning

confidence: 99%

Response of the Normalized Difference Vegetation Index (NDVI) to Snow Cover Changes on the Qinghai–Tibet Plateau

Zhou,

Liu,

Zhang

et al. 2024

Remote Sensing

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The eco-hydrological process related to vegetation on the Qinghai–Tibet Plateau is special, and the impact of snow cover on the growth of vegetation is unique and important. In this study, we analyzed the multi-year variations in the normalized difference vegetation index (NDVI) and snow cover on the Qinghai–Tibet Plateau from spatial and temporal perspectives and determined the relationship between the changes in the NDVI and snow cover. Results showed that in the last 40 years, the rate of change in the snow depth on the plateau was −0.016 mm/a, and the NDVI changed by 0.0005/a. The correlations (|R| values) between the different factors and the NDVI followed the order of precipitation (0.77) > snow depth (0.76) > temperature (0.67) > solar radiation (0.21). The responses of the NDVI to changes in meteorological elements were synchronous, whereas the opposite was found for the snow cover. The snow cover had more significant impacts on vegetation at higher elevations. The NDVI had a lag of about 2 months from the onset of the snow cover, and heavy snow events had negative impacts on the NDVI for more than 3 years. Our findings will facilitate studies of ecological vulnerability and the predictions of changes in vegetation on the plateau.

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“…Notably, given that the basin is located in the core area of the ecological security barrier of the Tibetan Plateau, safeguarding the ecological security of the basin is highly important [3]. In recent years, with the intensification of climate change and human activities, the ecosystem structure and function of the Lhasa River Basin have been Land 2024, 13, 597 2 of 24 affected by glacial and permafrost melting and grassland degradation, seriously impeding the sustainable development of the regional socio-economy [4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Multi-Scenario Prediction of Land-Use Changes and Ecosystem Service Values in the Lhasa River Basin Based on the FLUS-Markov Model

Qi,

Yu,

2024

Land

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The quantitative evaluation and prediction of ecosystem service value (ESV) in the Lhasa River Basin can provide a basis for ecological environment assessment and land-use optimization and adjustment in the future. Previous studies on the ESV in the Lhasa River Basin have focused mainly on static assessment and evolution analysis based on historical data, and have not considered future development trends. Moreover, most of the current driving factors selected in land use and ESV prediction studies are homogeneous, and do not reflect the geographical and cultural characteristics of the study area well. With the Lhasa River Basin as the research focus, 20 driving factors were selected according to the characteristics of the plateau alpine area, and the land-use changes under three developmental orientations, namely, natural evolution, ecological protection, and agricultural development, were predicted for the year 2030 with the FLUS-Markov model. Based on these predictions, the values of ecosystem services were calculated, and their spatiotemporal dynamic characteristics were analyzed. The results show that the model has high accuracy in simulating land-use change in the Lhasa River Basin, with a kappa coefficient of 0.989 and an overall accuracy of 99.33%, indicating a high applicability. The types of land use in the Lhasa River basin are dominated by the existence of grassland, unused land, and forest, with a combined proportion of 94.3%. The change trends of each land-use type in the basin under the three scenarios differ significantly, with grassland, cropland, and building land showing the most significant changes. The area of cropland increased only in the agricultural development scenario; the areas of forest and grassland increased only in the ecological protection scenario; and the expansion of building land was most effectively controlled in the ecological protection scenario. The ESV increased in all three scenarios, and the spatial distribution of the ESV per unit area in the middle and lower reaches was greater than that in the upper reaches. The ESV was the greatest in the ecological protection scenario, with grasslands, forests, and water bodies contributing more to the ESV of the basin. This study provides decision-making references for the effective utilization of land resources, ecological environmental protection planning, and urban construction in the Lhasa River Basin in the future.

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Impacts of Climate Change and Human Activities on NDVI in the Qinghai-Tibet Plateau

Cited by 21 publications

References 40 publications

Quantitative Analysis of Climate Variability and Human Activities on Vegetation Variations in the Qilian Mountain National Nature Reserve from 1986 to 2021

Quantitative Analysis of Climate Variability and Human Activities on Vegetation Variations in the Qilian Mountain National Nature Reserve from 1986 to 2021

Response of the Normalized Difference Vegetation Index (NDVI) to Snow Cover Changes on the Qinghai–Tibet Plateau

Multi-Scenario Prediction of Land-Use Changes and Ecosystem Service Values in the Lhasa River Basin Based on the FLUS-Markov Model

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