Spatial and Temporal Variation in Vegetation Cover and Its Response to Topography in the Selinco Region of the Qinghai-Tibet Plateau

Abstract

In recent years, the vegetation cover in the Selinco region of the Qinghai-Tibet Plateau has undergone significant changes due to the influence of global warming and intensified human activity. Consequently, comprehending the distribution and change patterns of vegetation in this area has become a crucial scientific concern. To address this concern, the present study employed MODIS-NDVI and elevation data, integrating methodologies such as trend analysis, Hurst exponent analysis, and sequential cluster analysis to explore vegetation cover changes over the past 21 years and predict future trends, while examining their correlation with topographic factors. The study findings indicate a fluctuating upward trend in vegetation cover, with a notable decrease in 2015. Spatially, the overall fractional vegetation cover (FVC) in the study area showed a basic stability with a percentage of 78%. The analysis of future trends in vegetation cover revealed that the majority of areas (68.26%) exhibited an uncertain trend, followed by stable regions at 15.78%. The proportion of areas showing an increase and decrease in vegetation cover accounted for only 9.63% and 5.61%, respectively. Elevation and slope significantly influence vegetation cover, with a trend of decreasing vegetation cover as elevation increases, followed by an increase, and then another decrease. Likewise, as the slope increases, initially, there is a rise in vegetation cover, followed by a subsequent decline. Notably, significant abrupt changes in vegetation cover are observed within the 4800 m elevation band and the 4° slope band in the Selinco region. Moreover, aspect has no significant effect on vegetation cover. These findings offer comprehensive insights into the spatial and temporal variations of vegetation cover in the Selinco region and their association with topographic factors, thus serving as a crucial reference for future research.

An advanced TSMK-FVC approach combined with Landsat 5/8 imagery for assessing the long-term effects of terrain and climate on vegetation growth

“…This phenomenon may be due to the fact that with the increase gradually of slope, soil water and nutrients will be more easily lost, so that the percentage of vegetation decline in the higher slope area will be slightly increased ( Zhang et al., 2013 ). Relevant studies show that vegetative coverage in the TPRR is highest at a slope of 35° ( Wang et al., 2021b ), and have concluded that vegetation in this region is less affected by slope ( Huang et al., 2023 ), which is in agreement with the findings of this research.…”

“…Even within the same geographic unit, there are differences in the response of vegetation to climatic factors such as temperature and precipitation ( Deng et al., 2022b ). However, current vegetation monitoring at high altitudes tends to focus on the entire plateau area, using coarse resolution (>500m) AVHRR or MODIS remote sensing imagery to analyze spatial and temporal changes in vegetation ( Zhang and Jin, 2021 ; Han et al., 2023 ; Huang et al., 2023 ). It was shown that the spatial resolution of remote sensing images may affect the accuracy of FVC estimation, and suitable remote sensing images need to be selected according to the study area ( Zhang et al., 2014 ; Wang et al., 2022 ).…”

Effects of Geomorphic Spatial Differentiation on Vegetation Distribution Based on Remote Sensing and Geomorphic Regionalization

“…Chen et al [61] suggested that elevation, slope, and curvature have the greatest influence on the spatial and temporal evolution of vegetation cover in southwest China. Huan et al [62] proposed that the cover of alpine vegetation shows an increasing and then decreasing trend with increasing altitude and slope. The reason for these differences may be that the indicators selected by different studies vary considerably, and this paper considered the influence of detailed landform types more comprehensively than previous scholars who only considered the influence of topographic factors.…”

Anthropogenic activities dominated the spatial and temporal changes of normalized difference vegetation index (NDVI) in the Hehuang valley in the northeastern Qinghai Province between 2000 and 2020

“…In this study, we used the residual analysis method to separate and quantify the anthropogenic and climatic impacts on NDVI variations at a grid-scale, so as to further identify the main driver of vegetation changes by comparing the residuals between observed NDVI values and predicted NDVI values (Geerken and Ilaiwi, 2004;Sajadi et al, 2021;Lai et al, 2023). We established a multiple regression model between annual NDVI values and corresponding climatic values (precipitation and temperature); the assumption of this model was that the anthropogenic impact on vegetation could be explained by the residual variations derived from the observed values minus the climate-based predicted values (Geerken and Ilaiwi, 2004;Huang et al, 2023). The equations for this calculation are given below.…”