Analysis of changing trends in NDVI and their driving forces in the Tuojiang River basin based on an improved BFAST model

ZHONG Xuzhen; WU Ruijuan

doi:10.6046/zrzyyg.2023216

2025 Vol. 37, No. 1

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ZHONG Xuzhen, WU Ruijuan. 2025. Analysis of changing trends in NDVI and their driving forces in the Tuojiang River basin based on an improved BFAST model. Remote Sensing for Natural Resources, 37(1): 131-141. doi: 10.6046/zrzyyg.2023216

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ZHONG Xuzhen, WU Ruijuan. 2025. Analysis of changing trends in NDVI and their driving forces in the Tuojiang River basin based on an improved BFAST model. Remote Sensing for Natural Resources, 37(1): 131-141. doi: 10.6046/zrzyyg.2023216

Analysis of changing trends in NDVI and their driving forces in the Tuojiang River basin based on an improved BFAST model

ZHONG Xuzhen^1,2,3,
WU Ruijuan^1,4,

1. School of Geography and Resource Science, Neijiang Normal University, Neijiang 641100, China;
2. Faculty of Geography, Yunnan Normal University, Kunming 650500, China;
3. Southwest United Graduate School, Yunnan Normal University, Kunming 650500, China;
4. State Key Laboratory of Resources and Environmental Information System, Beijing 100101, China

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Corresponding author: WU Ruijuan

Received Date: 20 July 2023

Revised Date: 20 November 2023

Abstract

Abstract

Vegetation, the main body of a terrestrial ecosystem, serves as an important indicator of environmental changes in a regional ecosystem. The Tuojiang River basin is an economically and industrially developed area in Sichuan. Dynamic vegetation monitoring and the analysis of factors driving its changes hold great significance for ecological change assessment and ecological protection. This study investigated the Tuojiang River basin. Based on MODIS data of normalized difference vegetation index (NDVI) from 2000 to 2021, this study detected, analyzed, and compared linear and nonlinear characteristics of the data, including mutation types and years, using linear regression Slope and an improved BFAST01 model. Additionally, this study explored the factors influencing the NDVI using the Optimal Parameters-based Geographic Detector (OPGD) model. The results indicate that more than 95% of the Tuojiang River basin exhibited NDVI values exceeding 0.6. The linear regression analysis for NDVI trends revealed that regions with significantly improved and significantly degraded vegetation coverage accounted for 18.07% and 10.60%, respectively, of the total area of the river basin, as indicated by image pixels. The BFAST01 nonlinear mutation analysis showed that the NDVI trends in the Tuojiang River basin over the 22 years can be categorized into eight mutation types, with the proportion of regions exhibiting improved vegetation coverage (58.62%) exceeding that of regions with degraded vegetation coverage (41.38%). These findings were consistent with the linear regression analysis, suggesting that the vegetation in the river basin was well protected in the 22 years. Mutations were concentrated between 2002 and 2018, with “interruption-+” and “reversal+-” representing the most common mutation types, accounting for 14.83% and 13.19%, respectively. In contrast, other mutation types exhibited a relatively even distribution across different stages. The results of the OPGD model revealed slight variations in the factors influencing NDVI across different years. Generally, the most influential factors included land use/land cover (LULC), elevation, and terrain and landforms, followed by meteorological factors such as temperature and precipitation. In contrast, other factors produced relatively minor impacts. Overall, despite some impacts, human factors like population and GDP exerted less influence on vegetation than natural factors in the Tuojiang River basin. Therefore, vegetation protection and restoration should consider the combined effects of both natural factors and anthropogenic activities.
- NDVI /
- nonlinear trend /
- BFAST improved model /
- OPGD /
- Tuojiang River basin

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References

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