Knowledge on rangeland condition, productivity patterns and possible thresholds of potential concern, as well as the escalation of risks in the face of climate change and variability over savanna grasslands is essential for wildlife/livestock management purposes. The estimation of leaf area index (LAI) in tropical savanna ecosystems is therefore fundamental for the proper planning and management of this natural capital. In this study, we assess the spatio-temporal seasonal LAI dynamics (dry and wet seasons) as a proxy for rangeland condition and productivity in the Kruger National Park (KNP), South Africa. The 30 m Landsat 8 Operational Land Imager (OLI) spectral bands, derived vegetation indices and a non-parametric approach (i.e., random forest, RF) were used to assess dry and wet season LAI condition and variability in the KNP. The results showed that RF optimization enhanced the model performance in estimating LAI. Moderately high accuracies were observed for the dry season (R-2 of 0.63-0.72 and average RMSE of 0.60 m(2)/m(2)) and wet season (0.62-0.63 and 0.79 m(2)/m(2)). Derived thematic maps demonstrated that the park had high LAI estimates during the wet season when compared to the dry season. On average, LAI estimates ranged between 3 and 7 m(2)/m(2) during the wet season, whereas for the dry season most parts of the park had LAI estimates ranging between 0.00 and 3.5 m(2)/m(2). The findings indicate that Kruger National Park had high levels of productivity during the wet season monitoring period. Overall, this work shows the unique potential of Landsat 8-derived metrics in assessing LAI as a proxy for tropical savanna rangelands productivity. The result is relevant for wildlife management and habitat assessment and monitoring.
1.Univ Western Cape, Dept Earth Sci, Private Bag X17, ZA-7535 Bellville, South Africa 2.Univ Tokyo, Grad Sch Agr & Life Sci, Bunkyo Ku, 1-1-1 Yayoi, Tokyo 1138567, Japan 3.Univ Witwatersrand, Sch Geog Archaeol & Environm Studies, Private Bag 3, ZA-2050 Johannesburg, South Africa 4.South African Natl Pk, POB 787, ZA-0001 Pretoria, South Africa 5.Univ Limpopo, Risk & Vulnerabil Ctr, P Bag X1106, ZA-0727 Sovenga, South Africa 6.Univ Venda, Dept Ecol & Resource Management, Private Bag X5050, ZA-0950 Thohoyandou, South Africa
Recommended Citation:
Dube, Timothy,Pandit, Santa,Shoko, Cletah,et al. Numerical Assessments of Leaf Area Index in Tropical Savanna Rangelands, South Africa Using Landsat 8 OLI Derived Metrics and In-Situ Measurements[J]. REMOTE SENSING,2019-01-01,11(7)