Mapping Seasonal Variations of Grazing Land Above-ground Biomass with Sentinel 2A Satellite Data

Abstract

Abstract Seasonal variations have brought about significant changes in vegetation cover and spatial distribution in the past decade. Globally, grazing lands are experiencing a significant warming and drying process more especially the grazing lands in the Savannah and Sahel regions. This paper reports the study undertaken for mapping changes on the grass above ground biomass (GAB) due to these seasonal changes using Sentinel 2A Multispectral Instrument (MSI) data. Emphasising on the GAB, the main objective of this study is to map and model monthly GAB variations to their corresponding meteorological data. A set of selected widely used vegetation indices were applied to satellite data, and later were further regressed against corresponding in-situ GAB samples and weather data, hence, producing a predictor of GAB from satellite data. Sentinel 2A MSI data were acquired monthly from January to December 2018. Combined with precipitation and temperature data, the GAB variations on monthly scales were analysed. The results indicated that GAB determined and its seasonal variations shown good agreement (r = 0.8, p < 0.001) with corresponding in-situ verifications. Temperature was found inversely proportionally to GAB for the whole grazing calendar. Therefore, it was concluded that mapping GAB seasonal variations is achievable with Sentinel2 MSI, vast potential for input to grazing land management.