Assessing the Contributions and Thresholds of Multi-Source Remote Sensing Informatiuon in Vegetation Aboveground Biomass Estimation Under Optical Saturation
Year: 2026
Type: article
Abstract: Aboveground biomass (AGB) is an important indicator for monitoring ecosystem carbon stocks and vegetation productivity. However, optical-remote-sensing-based AGB estimation is prone to saturation effects. Multi-source remote sensing fusion provides an important means of alleviating optical saturation. Although the optimal estimation result can currently be obtained directly on the basis of overall model accuracy, the contribution mechanisms and effective ranges of different information sources after optical saturation, as well as their dependence on topographic background, remain difficult to explain. Accordingly, this study used Dongzhai National Nature Reserve in Luoshan County, Henan Province, China, as the study area and 90 field-measured AGB values as the target variable; integrated GEDI L2A/L2B, Landsat 9, Sentinel-2, GF-2, GF-5B hyperspectral, Sentinel-1, topographic, and climatic data; constructed four feature sets comprising optical information Sp, structural information St, microwave scattering information Se, and topographic and climatic information En; designed eight ablation experiments using a random forest model; and analyzed the contribution mechanisms and response thresholds of multi-source remote sensing information for AGB estimation under optical saturation. The results showed that: (1) St was the core information source for improving AGB estimation accuracy in the reserve, and adding only structural information to optical information increased the model OOF R2 from 0.169 to 0.433, and the high-AGB interval (64.18–129.456 Mg ha−1) was the primary source of model estimation error; (2) under the full-sample sliding-window framework of this study, the predictive response of Sp gradually weakened with increasing AGB and eventually entered a stable saturation state. Thereafter, St provided sustained and stable compensation for RMSE and MAE, whereas the improvements from Se and En were mainly concentrated in the transition stage from weakening optical response to stable saturation, and only when both were simultaneously incorporated in the presence of St; (3) multi-source remote sensing fusion is not necessarily more effective with more information sources. The key lies in whether different information sources can provide effective information under specific ecological backgrounds and observation conditions.
Source: Remote Sensing
DOI: 10.3390/rs18183113
Authors: Shuhan Huo, Jiangbo Liu, Ruiqing Niu
Institution: China University of Geosciences
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
SDGs: Climate action, Life on land
Open Access status: gold
Estimated APC paid: $3,258
OpenAlex ID: W7212138255