Estimation and trend analysis of grassland aboveground biomass on the Qinghai-Xizang Plateau based on machine learning
Grassland, as an essential terrestrial ecosystem, plays a vital role in maintaining ecosystem stability, enhancing carbon sequestration, and promoting biodiversity conservation. Accurate estimation of grassland aboveground biomass (AGB) is essential for effective ecosystem management and sustainable...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X25006454 |
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| Summary: | Grassland, as an essential terrestrial ecosystem, plays a vital role in maintaining ecosystem stability, enhancing carbon sequestration, and promoting biodiversity conservation. Accurate estimation of grassland aboveground biomass (AGB) is essential for effective ecosystem management and sustainable development, especially in environmentally sensitive areas like the Qinghai-Xizang Plateau. This study integrated field-measured grassland AGB data (2003–2023) with MODIS remote sensing data and meteorological variables. A comprehensive benchmarking of 25 machine learning (ML) algorithms was conducted to evaluate their performance. The optimal model was identified through an exhaustive comparison and hyperparameter optimization process, and then applied to estimate grassland AGB across the plateau and analyze its spatiotemporal dynamics. The results showed that Ranger performed best (R2 = 0.6541, RMSE = 512.25 kg DW/ha, MAE = 375.91 kg DW/ha), with OSAVI and precipitation-related variables as the key driving factors. Between 2003 and 2023, the spatial distribution of grassland AGB on the Qinghai-Xizang Plateau exhibited significant heterogeneity, with an overall decreasing trend from the southeast to the northwest. From the perspective of interannual variation, 51.41% of the total area remained stable. With respect to persistent change, 64.71% of the area showed uncertain trends, while 35.29% of the area was characterized by persistent trends. The results of this study provide critical data support and a robust scientific foundation for the ecological protection and sustainable management of grassland resources on the plateau. |
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| ISSN: | 1470-160X |