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

Abstract

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 (R² > 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.

Keywords:

• Grass above-ground biomass
• grazing land
• mapping
• satellite remote sensing

Acknowledgements

Acknowledgements of research facilities utilized at Geoscience & Digital Earth Centre (INSTeG), Universiti Teknologi Malaysia. We also acknowledged the Nigerian federal government for providing financial intervention to the first author via Tertiary Education Trust Fund.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was partially funded by the Ministry of Education Malaysia using FRGS grant (Ref: Vote no. 5F211 – Remote Sensing-Based Seagrass Ecosystem Services), as offset test of grass allometry models.