M
Mbulisi Sibanda
Researcher at University of KwaZulu-Natal
Publications - 85
Citations - 1208
Mbulisi Sibanda is an academic researcher from University of KwaZulu-Natal. The author has contributed to research in topics: Environmental science & Land cover. The author has an hindex of 16, co-authored 70 publications receiving 742 citations. Previous affiliations of Mbulisi Sibanda include University of the Western Cape & Lupane State University.
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Examining the potential of Sentinel-2 MSI spectral resolution in quantifying above ground biomass across different fertilizer treatments
TL;DR: In this article, the authors used hyperspectral data from the recently launched Sentinel 2 Multispectral Imager (MSI) and Landsat 8 OLI for comparison purposes.
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Detection and mapping the spatial distribution of bracken fern weeds using the Landsat 8 OLI new generation sensor
TL;DR: Assessment of the utility of the freely available medium resolution Landsat 8 OLI sensor in the detection and mapping of bracken fern at the Cathedral Peak, South Africa found that the integration of the spectral bands and derived vegetation indices yielded the best overall classification accuracy.
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Delineating the drivers of waning wildlife habitat: The predominance of cotton farming on the fringe of protected areas in the Mid-Zambezi Valley, Zimbabwe
Frédéric Baudron,Marc Corbeels,Jens A. Andersson,Jens A. Andersson,Mbulisi Sibanda,Ken E. Giller +5 more
TL;DR: In this article, the authors quantify the change for the Dande Communal Area, Mbire District, of the Mid-Zambezi Valley and analyse the contribution of three major potential drivers: increase in human population, increase in cattle population, and expansion of cotton farming.
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Exploring the potential of in situ hyperspectral data and multivariate techniques in discriminating different fertilizer treatments in grasslands
TL;DR: In this article, the utility of in situ hyperspectral data and multivariate techniques in distinguishing 12 complex ammonium nitrate, ammonium sulfate, lime, and phosphorus fertilizer combinations on a grassland is assessed.
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Estimating Biomass of Native Grass Grown under Complex Management Treatments Using WorldView-3 Spectral Derivatives
TL;DR: This work sought to explore the robustness of integrating texture metrics and red-edge in predicting the above-ground biomass of grass growing under different levels of mowing and burning in grassland management treatments, and found an optimal prediction accuracy of RMSEP 0.2 kg/m2 across all grass land management treatments.