Spatial-temporal evolution of vegetation coverage and its relationship with terrain and human factors in the upper reaches of Ganjiang River Basin, China

Abstract

Vegetation coverage is an important indicator for evaluating regional environmental quality. Based on MODIS NDVI and DEM data collected for the upper reaches of the Ganjiang River Basin, China, this study used trend analysis, coefficient of variation, Hurst index, and linear regression to analyze the temporal and spatial evolution of vegetation coverage and its relationship with terrain factors in the basin during the years 2000–2020. The vegetation coverage in the study area showed a fluctuating increasing trend at a rate of 5%/10y, and an increasing trend with increasing elevation. The maximum vegetation coverage was identified in the elevation zone of 750–1,000 m, with an average of 83.54%. Vegetation coverage also showed an increasing trend with increasing slope. The maximum vegetation coverage was up to 82.22% in the slope zone of ≥25°. There were no significant differences among the distributions of vegetation coverage in different aspects because the terrain in the study area is not rugged enough to form barriers against sunlight. The vegetation coverage was relatively stable in the study area, with an average coefficient of variation of 14.8%. Hurst analysis showed that the anti-sustainability effect of vegetation change was stronger than that of sustainability, and weak anti-sustainability was dominant. The effects of human activities mainly concentrated in the areas of low elevation and small slopes less than 2°where cities and towns are located. The findings can provide a scientific basis for the management of regional ecosystems in the future.

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

“…In addition, the relative contribution of each factor to vegetation change still needs further exploration. Generally, previous studies focusing on the spatial differentiation of landforms and vegetation distribution have mainly used linear correlation methods to describe the relationship between natural variables and vegetation, often ignoring the interaction between vegetation and topographic factors [19,20]. Using the Geodetector model, nonlinear and interactive algorithms can be applied to understand the complex connections between topographic factors and vegetation.…”

Differences in NPP drivers and response mechanisms in typical subtropical mountain ecosystems in China

“…These studies have highlighted the more pronounced and positive impacts of human activities on mountainous areas, particularly in their examination of the relationship between land use change and local policies. Climate factors are recognized as one of the key drivers of ME (Tappeiner et al 2021;Liu et al 2023). Furthermore, variations in topographic gradients in mountainous regions signi cantly affect the uneven distribution of hydrothermal conditions, and the spatial distribution pattern of net primary productivity (NPP) with increasing altitude mirrors that of mountainous formations (Ma et al 2022;Peters et al 2019; Wang et al 2017).…”

Improving Tree Cover Estimation for Sparse Trees Mixed with Herbaceous Vegetation in Drylands Using Texture Features of High-Resolution Imagery

“…The Loess Plateau consists of arid/semi-arid areas [13,14], characterized by sparse mixed forests composed of artificially planted trees and green herbaceous vegetation, which represent typical landscapes in the region [15]. Vegetation coverage serves as an overall ecological indicator for the region [16,17], and it can be further divided into tree cover [18][19][20] and herbaceous vegetation cover, with tree coverage serving as a direct reflection of vegetation restoration. However, the similarity in spectral characteristics between woody vegetation and herbaceous vegetation cover is a key factor affecting the high-precision inversion of tree coverage in tree-grasslands in this region.…”