Mapping grass above-ground biomass of grazing-lands using satellite remote sensing

• Main Authors: Isa Muhammad Zumo, Isa Muhammad Zumo, Hashim, Mazlan, Hassan, NoorDyana
• Format: Article
• Published: Taylor and Francis Ltd. 2022
• Subjects: G70.39-70.6 Remote sensing
• Online Access: http://eprints.utm.my/104234/; http://dx.doi.org/10.1080/10106049.2021.1899309

Over the years, global growth in population and changing climate has contributed to shifts in vegetation species composition, and lower production of grass biomass. Several studies have been conducted globally to quantify grassland biomass utilizing satellite data, but rarely in African Savannah, particularly in Jibiro grazing land, Nigeria. In this study, the grass above-ground biomass (GAB) was estimated from Sentinel-2A/2B data using (i) in-situ samplings on GAB and (ii) upscaling the measured GAB to corresponding satellite data. Spectral indices show that the vegetation index number (VIN) is the best suited vegetation index for modelling GAB (R 2 > 0.86, p < 0.001) and is verified (RMSE ±15.99/100 g) with an equally independent assessment set. The result indicated that the grazing reserve has maximum GAB production of 0.76 ton/ha as of September and least GAB of 0.001 ton/ha in January 2018. This study contributes to planning rotational grazing in study area and similar ecosystem.