An advanced TSMK-FVC approach combined with Landsat 5/8 imagery for assessing the long-term effects of terrain and climate on vegetation growth - Xu, Zhenxian; Shen, Xin; Ge, Sang; Sun, Qinglei; Yang, Ying; Cao, Lin (Frontiers in Plant Science, 2024)
As an exceptional geographical entity, the vegetation of the Qinghai-Tibetan Plateau (QTP) exhibits high sensitivity to climate change. The Baima Snow Mountain National Nature Reserve (BNNR) is located in the south-eastern sector of the QTP, serving as a transition area from sub-tropical evergreen broadleaf forest to highmountain vegetation. However, there has been limited exploration into predicting the temporal and spatial variability of vegetation cover using anti-interference methods to address outliers in long-term historical data. Additionally, the correlation between these variables and environmental factors in natural forests with complex terrain has rarely been analyzed. This study has developed an advanced approach based on TS (Theil-Sen slope estimator) MK (Mann-Kendall test)-FVC (fractional vegetation cover) to accurately evaluate and predict the time and spatial shifts in FVC within the BNNR, utilizing the GEE (Google Earth Engine). The satellite data utilized in this paper consisted of Landsat images spanning from 1986 to2020. By integrating TS and MK methodologies to monitor and assess the FVC trend, the Hurst index was employed to forecast FVC. Furthermore, the association between FVC and topographic factors was evaluated, the partial correlation between FVC and climatic influences was analyzed at the pixel level (30×30m). Here are the results of this research: (1) Overall, the FVC of the BNNR exhibits a growth trend, with the mean FVC value increasing from 59.40% in 1986 to 68.67% in 2020. (2) The results based on the TS-MK algorithm showed that the percentage of the area of the study area with an increasing and decreasing trend was 59.03% (significant increase of 28.04%) and 22.13% (significant decrease of 6.42%), respectively. The coupling of the Hurst exponent with the Theil-Sen slope estimator suggests that the majority of regions within the BNNR are projected to sustain an upward trend in FVC in the future. (3) Overlaying the outcomes of TS-MK with the terrain factors revealed that the FVC changes were notably influenced by elevation. The partial correlation analysis between climate factors and vegetation changes indicated that temperature exerts a significant influence on vegetation cover, demonstrating a high spatial correlation.