MODELLING CARRYING CAPACITY FOR THE THANDA PRIVATE GAME RESERVE, SOUTH AFRICA USING LANDSAT 8 MULTISPECTRAL DATA

Abstract

Abstract. Rangelands which consist of grasslands, shrublands and savannahs are used by wildlife for habitat and are the main source of forage for livestock. The assessment and monitoring of rangeland condition is one of the most important factors for rangeland scientists in order to calculate the carrying capacity of livestock with consideration for coexisting wildlife. This study assessed the potential of Landsat 8 multispectral bands and broadband vegetation indices to model woody vegetation parameters such as tree equivalents (TE) and total leaf mass (LMASS) for the Thanda Private Game Reserve using partial least squares regression (PLSR). The PLSR model predicted TE with an R2 value of 0.76 and a root mean square error (RMSE) of 1411 TE/ha using an independent test dataset. LMASS was predicted with an R2 value of 0.67 and a RMSE of 853 kg/ha on an independent test dataset. The predictive models were then inverted to map TE and LMASS over the study area. The modelled TE and LMASS layers were integrated with conventional grazing and browse capacity models to map carrying capacity for the Game Reserve. The study indicates the potential of Landsat 8 multispectral data in carrying capacity modelling. The result is significant for rangeland monitoring in Southern Africa using remote sensing technologies.