Inversion of aboveground biomass of grassland on the eastern margin of the Qinghai-Tibet Plateau combined with Sentinel-1 and Sentinel-2 data

The aim of this study was to explore the application potential of collaborative active and passive remote sensing in aboveground biomass (AGB) estimation of grassland. In this study, Hongyuan County, Aba Tibetan and Qiang Autonomous Prefecture, on the eastern edge of the Qinghai-Tibetan Plateau was used as the study area. We investigated the ability to retrieval grass AGB by combining Sentinel-1 and Sentinel-2 data, using multiple linear regression, stepwise regression, and semi-empirical physical modeling, with Sentinel-1 synthetic aperture radar data and Sentinel-2 multispectral images as the data sources. The results showed that the cooperative inversion accuracy was better than the inversion accuracy of the Sentinel-2 single-data source (the accuracy, R², of the multiple linear regression model increased from 0.74 to 0.83). In addition, combining Sentinel-1 and Sentinel-2 data with stepwise regression, the AGB model accuracy (R²) was 0.78, and the semi-empirical physical model accuracy (R²) was 0.77. In general, the Sentinel-1 influence factor improved the accuracy of the inversion model to some extent, and the final inverse AGB results from multiple modeling approaches were consistent with the measured grassland AGB. The results of this study provide a scientific basis for the accurate estimation of AGB in the study area and even the eastern edge grassland of the whole Qinghai-Tibet Plateau.