Retrieval of grassland aboveground biomass across three ecoregions in China during the past two decades using satellite remote sensing technology and machine learning algorithms

• Published in: International journal of applied earth observation and geoinformation Vol. 130; p. 103925
• Main Authors: Wu, Huoqi, An, Shuai, Meng, Bin, Chen, Xiaoqiu, Li, Fangjun, Ren, Shillong
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.06.2024; Elsevier
• Subjects: aboveground biomass; alpine vegetation; carbon sequestration; China; climate change; data collection; ecoregions; Grassland aboveground biomass; Linear trend; Machine learning; satellites; spatial data; Spatiotemporal patterns; Statistical model; steppes; China; Spatiotemporal patterns; Grassland aboveground biomass; Statistical model; Linear trend; Machine learning

[Display omitted] •The high temporal resolution MCD43A4 data is optimal to estimate AGB.•The in situ harvesting AGB data should be strictly screened before the modeling.•The Random Forest model is the optimum method for estimating grassland AGB.•China’s grassland growing season maximum AGB overall i...