| Autor: |
Guangjie Wang, Wenfu Peng, Lindan Zhang, Ji Zhang, Jiayao Xiang |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Global Ecology and Conservation, Vol 45, Iss , Pp e02531- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2351-9894 |
| DOI: |
10.1016/j.gecco.2023.e02531 |
| Popis: |
The research on vegetation changes plays a crucial role in the assessment of ecosystem health, monitoring environmental changes, providing early warnings for natural disasters, and supporting decision-making for sustainable development. However, understanding the nonstationary characteristics of drivers affecting vegetation change remains challenging. This study used Enhanced Vegetation Index (EVI) data obtained through Google Earth Engine (GEE), Theil-Sen, and Mann-Kendall methods to analyze the spatial-temporal patterns and trends of vegetation changes in Sichuan, western China from 2000 to 2020. The Geographical and Temporal Weighted Regression (GTWR) method was applied to deal with spatial and temporal nonstationarity simultaneously. Results showed that vegetation cover in Sichuan was good overall, with medium and high vegetation covering more than 78% of the area. About 72.75% of the area showed an increasing trend in vegetation cover, and areas with extremely significant and significant EVI growth (p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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