Satellite-Derived Estimation of Grassland Aboveground Biomass in the Three-River Headwaters Region of China during 1982–2018
Open Access
- 29 July 2021
- journal article
- research article
- Published by MDPI AG in Remote Sensing
- Vol. 13 (15), 2993
- https://doi.org/10.3390/rs13152993
Abstract
The long-term estimation of grassland aboveground biomass (AGB) is important for grassland resource management in the Three-River Headwaters Region (TRHR) of China. Due to the lack of reliable grassland AGB datasets since the 1980s, the long-term spatiotemporal variation in grassland AGB in the TRHR remains unclear. In this study, we estimated AGB in the grassland of 209,897 km2 using advanced very high resolution radiometer (AVHRR), MODerate-resolution Imaging Spectroradiometer (MODIS), meteorological, ancillary data during 1982–2018, and 75 AGB ground observations in the growth period of 2009 in the TRHR. To enhance the spatial representativeness of ground observations, we firstly upscaled the grassland AGB using a gradient boosting regression tree (GBRT) model from ground observations to a 1 km spatial resolution via MODIS normalized difference vegetation index (NDVI), meteorological and ancillary data, and the model produced validation results with a coefficient of determination (R2) equal to 0.76, a relative mean square error (RMSE) equal to 88.8 g C m−2, and a bias equal to −1.6 g C m−2 between the ground-observed and MODIS-derived upscaled AGB. Then, we upscaled grassland AGB using the same model from a 1 km to 5 km spatial resolution via AVHRR NDVI and the same data as previously mentioned with the validation accuracy (R2 = 0.74, RMSE = 57.8 g C m−2, and bias = −0.1 g C m−2) between the MODIS-derived reference and AVHRR-derived upscaled AGB. The annual trend of grassland AGB in the TRHR increased by 0.37 g C m−2 (p < 0.05) on average per year during 1982–2018, which was mainly caused by vegetation greening and increased precipitation. This study provided reliable long-term (1982–2018) grassland AGB datasets to monitor the spatiotemporal variation in grassland AGB in the TRHR.Funding Information
- National Key Research and Development Program of China (2016YFA0600103, 2016YFA0600102)
- National Natural Science Foundation of China (41671331)
This publication has 84 references indexed in Scilit:
- Timing of climate variability and grassland productivityProceedings of the National Academy of Sciences of the United States of America, 2012
- Bootstrapping Lasso EstimatorsJournal of the American Statistical Association, 2011
- Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraintsOecologia, 2010
- On downward shortwave and longwave radiations over high altitude regions: Observation and modeling in the Tibetan PlateauAgricultural and Forest Meteorology, 2010
- Aboveground biomass in Tibetan grasslandsJournal of Arid Environments, 2009
- Carbon storage in the grasslands of China based on field measurements of above- and below-ground biomassClimatic Change, 2007
- Allometric Models for Tree Volume and Total Aboveground Biomass in a Tropical Humid Forest in Costa Rica1Biotropica, 2005
- Overview of the radiometric and biophysical performance of the MODIS vegetation indicesRemote Sensing of Environment, 2002
- Monitoring the grasslands of the Sahel 1984-1985International Journal of Remote Sensing, 1986
- Red and photographic infrared linear combinations for monitoring vegetationRemote Sensing of Environment, 1979