Vegetation trends and dynamics in Shada Mountain, Saudi Arabia, (1984–2023): insights from Google Earth Engine and R analysis

Hanan F. Al-Harbi, Asma A. Alhuqail, Zubairul Islam, H. Ghrefat
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Abstract

This research analyses the long-term vegetation trends in Shada Mountain across six elevation zones, utilizing Landsat 5, 7, 8, and 9 imageries processed via Google Earth Engine and R. The study managed differences in images resolution through meticulous calibration and image processing techniques. The study is structured around two objectives: examining the relationship between vegetation and its proximity to streams and land surface temperature and analyzing trends in the Normalized Difference Vegetation Index (NDVI). Regression analysis revealed a negative correlation between vegetation and proximity to streams in lower zones (1–3), with no significant effect in higher zones (4–6). NDVI trend analysis indicated an overall increase in vegetation across most zones, with the exception of zone 5, which displayed a negative trend (slope −0.0025). The findings reveal that the decline is particularly pronounced among key tree species such as Ficus cordata subsp. salicifolia and Acacia asak, suggesting potential impacts from climate change and land use alterations. These zone-specific insights deepen our understanding of the dynamic ecological processes in semi-arid environments and guide targeted environmental management and conservation efforts.
沙特阿拉伯沙达山的植被趋势和动态(1984-2023 年):谷歌地球引擎和 R 分析的启示
这项研究利用通过谷歌地球引擎和 R 处理的 Landsat 5、7、8 和 9 图像,分析了沙田山六个海拔区的长期植被趋势。研究围绕两个目标展开:研究植被及其与溪流的距离与地表温度之间的关系,以及分析归一化植被指数(NDVI)的变化趋势。回归分析表明,在较低区域(1-3),植被与靠近溪流的程度呈负相关,而在较高区域(4-6)则无明显影响。NDVI 趋势分析表明,除第 5 区呈现负趋势(斜率为 -0.0025)外,大多数区域的植被总体上都在增加。研究结果表明,主要树种(如榕树亚种和相思树)的植被减少尤为明显,这表明气候变化和土地利用的改变可能会对植被造成影响。这些针对特定地区的见解加深了我们对半干旱环境动态生态过程的理解,并为有针对性的环境管理和保护工作提供了指导。
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