Retrieval of grassland plant coverage on the Tibetan Plateau based on a multi-scale, multi-sensor and multi-method approach

Plant coverage is a basic indicator of the biomass production in ecosystems. On the Tibetan Plateau, the biomass of grasslands provides major ecosystem services with regard to the predominant transhumance economy. The pastures, however, are threatened by progressive degradation, resulting in a substantial reduction in plant coverage with currently unknown consequences for the hydrological/climate regulation function of the plateau and the major river systems of SE Asia that depend on it and provide water for the adjacent lowlands. Thus, monitoring of changes in plant coverage is of utmost importance, but no reliable tools have been available to date to monitor the changes on the entire plateau. Due to the wide extent and remoteness of the Tibetan Plateau, remote sensing is the only tool that can recurrently provide area-wide data for monitoring purposes. In this study, we develop and present a grassland-cover product based on multi-sensor satellite data that is applicable for monitoring at three spatial resolutions (WorldView type at 2-5 m, Landsat type at 30 m, MODIS at 500 m), where the data of the latter resolution cover the entire plateau. Four different retrieval techniques to derive plant coverage from satellite data in boreal summer (JJA) were tested. The underlying statistical models are derived with the help of field observations of the cover at 640 plots and 14 locations, considering the main grassland vegetation types of the Tibetan Plateau. To provide a product for the entire Tibetan Plateau, plant coverage estimates derived by means of the higher-resolution data were upscaled to MODIS composites acquired between 2011 and 2013. An accuracy assessment of the retrieval methods revealed best results for the retrieval using support vector machine regressions (RMSE: 9.97%, 7.13% and 5.51% from the WorldView to the MODIS scale). The retrieved values coincide well with published coverage data on the different grassland vegetation types.