He et al. (2026) Combined active-passive remote sensing inversion of grassland aboveground biomass on the Qinghai-Tibet plateaus and exploration of its driving mechanisms with optical-radar-meteorological systems

Identification

• Journal: Ecological Indicators
• Year: 2026
• Date: 2026-09-10
• Authors: Xu He, Rui Zhang, Age Shama, Ruikai Hong, Hang Jiang, Guobing Wang, Hang Yao, Guoxiang Liu
• DOI: 10.1016/j.ecolind.2026.115349

Research Groups

• Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 611756, China
• College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541006, China

Short Summary

This study integrates active-passive remote sensing inversion to estimate grassland aboveground biomass (AGB) on the Qinghai-Tibet Plateau and explores its driving mechanisms with optical-radar-meteorological systems. The results indicate that GBDT exhibited the strongest inversion performance, with average RMSE values 4.105–16.357 g/m2 lower and R2 values 0.036–0.169 higher than those of SVM and RF.

Objective

• Investigate the feasibility of high-resolution biomass estimation using active-passive remote sensing data on the Qinghai-Tibet Plateau.
• Explore the driving mechanisms linking environmental systems and grassland AGB.

Study Configuration

• Spatial Scale: The study area covers approximately 2.5 million square kilometers, spanning around 26% of China's entire land area.
• Temporal Scale: The study period spans from December 2018 to December 2024, with a total of 73 months.

Methodology and Data

• Models used: GBDT (Gradient Boosting Decision Trees), RF (Random Forest), SVM (Support Vector Machines)
• Data sources:
  • Sentinel-1/2 imagery from December 2018 to December 2024
  • ERA5-Land Monthly Aggregated data for meteorological variables
  • Ground survey data from seven regions on the Qinghai-Tibet Plateau

Main Results

• The GBDT algorithm demonstrated the highest inversion accuracy (R2 = 0.797, RMSE = 50.635 g/m2) with an average RMSE 4.105–16.357 g/m2 lower and an average R2 0.036–0.169 higher than the other two algorithms.
• The inclusion of SAR features improved the inversion accuracy of grassland AGB.

Contributions

• This study provides a framework for assessing grassland productivity and ecological responses to environmental variability on the Qinghai-Tibet Plateau.
• The results demonstrate that GBDT-Scheme 3 not only achieves the highest point estimate accuracy but also maintains a relatively low estimation error.

Funding

• Not specified in the provided text.

Citation

@article{He2026Combined,
  author = {He, Xu and Zhang, Rui and Shama, Age and Hong, Ruikai and Jiang, Hang and Wang, Guobing and Yao, Hang and Liu, Guoxiang},
  title = {Combined active-passive remote sensing inversion of grassland aboveground biomass on the Qinghai-Tibet plateaus and exploration of its driving mechanisms with optical-radar-meteorological systems},
  journal = {Ecological Indicators},
  year = {2026},
  doi = {10.1016/j.ecolind.2026.115349},
  url = {https://doi.org/10.1016/j.ecolind.2026.115349}
}