Remote Sensing-based estimates of herbaceous aboveground biomass on the Mongolian Plateau

Abstract:

Grasslands comprise most of the land area on the Mongolian Plateau, which includes Mongolia (MG), and the province of Inner Mongolia (IM). Substantial land cover/use change in the recent past, driven by a combination of post-liberalization, socio-economic changes as well as extreme climatic events has resulted in degradation of grasslands in structure and function, for e.g., their carbon sequestration ability. Hence there is a need for precise estimation of above-ground biomass (AGB). In this study, we collected surface reflectance spectra from field radiometry and quadrats and line transects, which include percentage of ground cover, vegetation height, above ground biomass, and species richness, during the growing season, between the periods, 2006-2011 in IM and 2011-2015 in MG. The field sampling was stratified by the dominant vegetation types on the plateau, including the meadow steppe, typical steppe, and the desert steppe. These sampling data were used as training and validation data for developing and testing predictive models for total herbaceous vegetation, and AGB, using Landsat and MODIS-surface reflectance bands and derived vegetation indices optimized for low cover conditions. Our results show that the independent ground sampling data were significantly correlated with remotely sensed estimates. In addition to providing measures of carbon sequestration to the community, these predictive models offer decision makers and rangeland managers the ability to accurately monitor grassland dynamics, control livestock stocking rates in these remote and extensive grasslands.