Global assessment of vegetation patterns along topographic gradients

The complex topography in mountainous regions, exemplified by factors like slope aspect, leads to noticeable variations in vegetation patterns, which are fundamental for understanding mountain ecosystems. However, a consistent global-scale quantification of topography's influence on vegetation patterns is still lacking. Here, we utilize two phenological metrics as proxies for vegetation-maximum vegetation greenness and seasonal greenness amplitude-computed from Sentinel-2 images, to quantify differences across three topographic factors: slope aspect, steepness, and elevation within each 0.15°×0.15° mountain grid. Our mapping reveals clear geographic patterns indicating that topography strongly influences vegetation in arid and polar ecosystems, with an influence approximately 1.9 times higher than in temperate ecosystems. Topography is also important in humid regions, as demonstrated by diverse vegetation types growing on different slope aspects, steepness levels, and elevations. Additionally, the impacts of slope aspect, steepness, and elevation vary within the same region. In 25.9% of mountain grids, slope aspect causes the largest difference in vegetation patterns, while elevation and steepness account for 43.1% and 31%, respectively. Our study highlights the hotspot areas where topographic effects on vegetation patterns are most pronounced, enabling researchers to focus on these regions for better parameterization of Earth system models.

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Publication Details

Journal
International Journal of Digital Earth
Published
2024-09-19
DOI
https://doi.org/10.1080/17538947.2024.2404232
Citations
17
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
7.80

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article

Global assessment of vegetation patterns along topographic gradients

Torbern Tagesson, Rasmus Fensholt, Linqing Zou, Sabine B. Rumpf et al.
17 citations
International Journal of Digital Earth
Remote Sensing in Agriculture
7.80
article

Global assessment of vegetation patterns along topographic gradients

Torbern Tagesson, Rasmus Fensholt, Linqing Zou, Sabine B. Rumpf, Shunlin Liang, Tianchen Liang, Tian Feng, Hongxiao Jin, Tao He
article en
17 citations

Abstract

The complex topography in mountainous regions, exemplified by factors like slope aspect, leads to noticeable variations in vegetation patterns, which are fundamental for understanding mountain ecosystems. However, a consistent global-scale quantification of topography's influence on vegetation patterns is still lacking. Here, we utilize two phenological metrics as proxies for vegetation-maximum vegetation greenness and seasonal greenness amplitude-computed from Sentinel-2 images, to quantify differences across three topographic factors: slope aspect, steepness, and elevation within each 0.15°×0.15° mountain grid. Our mapping reveals clear geographic patterns indicating that topography strongly influences vegetation in arid and polar ecosystems, with an influence approximately 1.9 times higher than in temperate ecosystems. Topography is also important in humid regions, as demonstrated by diverse vegetation types growing on different slope aspects, steepness levels, and elevations. Additionally, the impacts of slope aspect, steepness, and elevation vary within the same region. In 25.9% of mountain grids, slope aspect causes the largest difference in vegetation patterns, while elevation and steepness account for 43.1% and 31%, respectively. Our study highlights the hotspot areas where topographic effects on vegetation patterns are most pronounced, enabling researchers to focus on these regions for better parameterization of Earth system models.

International Journal of Digital EarthVol. 17(1)
University of Copenhagen (DK), University of Basel (CH), Lund University (SE), Wuhan University (CN), Hong Kong Jockey Club (HK), University of Hong Kong (HK)
National Natural Science Foundation of China, Swedish National Space Agency, Svenska Forskningsrådet Formas, National Key Research and Development Program of China
Climate action
Openalex Percentile: Top 2%
Remote Sensing in Agriculture
7.80
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