Browsing by Author "Shoko, Cletah"

Now showing 1 - 11 of 11
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    Advancements in the satellite sensing of the impacts of climate and variability on bush encroachment in savannah rangelands
    (Elsevier, 2022) Maphanga, Thabang; Dube, Timothy; Shoko, Cletah
    An increase in shrubs or woody species is likely, directly or indirectly, to significantly affect rural livelihoods, wildlife/livestock productivity and conservation efforts. Poor and inappropriate land use management practices have resulted in rangeland degradation, particularly in semi-arid regions, and this has amplified the bush encroachment rate in many African countries, particularly in key savannah rangelands. The rate of encroachment is also perceived to be connected to other environmental factors, such as climate change, fire and rainfall variability, which may influence the structure and density of the shrubs (woody plants), when compared to uncontrolled grazing. Remote sensing has provided robust data for global studies on both bush encroachment and climate variability over multiple decades, and these data have complemented the local and regional evidence and process studies. This paper thus provides a detailed review of the advancements in the use of remote sensing for the monitoring of bush encroachment on the African continent, which is fuelled by climate variability in the rangeland areas.
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    Advances in satellite remote sensing of the wetland ecosystems in Sub-Saharan Africa
    (Taylor and Francis Group, 2022) Thamaga, Kgabo Humphrey; Dube, Timothy; Shoko, Cletah
    Wetlands are highly productive systems that act as habitats for avariety of fauna andflora. Despite their ecohydrological signifi-cance, wetland ecosystems are severely under threat from globalenvironmental changes as well as pressure from anthropogenicactivities. Such changes results in severe disturbances of plantspecies composition, spatial distribution, productivity, diversity,and their ability to offer critical ecosystem goods and services .However, wetland degradation varies considerably from place toplace with severe degradation in developing countries, especiallyin sub-Saharan Africa due to poor management practices thatleads to underutilization and over reliance on them for liveli-hoods. The lack of monitoring and assessment in this region hastherefore led to the lack of consolidated detailed understandingon the rate of wetland loss.
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    Characterizing the spatio-temporal variations of C3 and C4 dominated grasslands aboveground biomass in the Drakensberg, South Africa
    (Elsevier, 2018) Shoko, Cletah; Mutanga, Onisimo; Dube, Timothy; Slotow, Rob
    C3 and C4 grass species composition, with different physiological, morphological and most importantly phenological characteristics, influence Aboveground Biomass (AGB) and their ability to provide ecosystem goods and services, over space and time. For decades, the lack of appropriate remote sensing data sources compromised C3 and C4 grasses AGB estimation, over space and time. This resulted in uncertainties in understanding their potential and contribution to the provision of services. This study therefore examined the utility of the new multi-temporal Sentinel 2 to estimate and map C3 and C4 grasses AGB over time, using the advanced Sparse Partial Least Squares Regression (SPLSR) model. Overall results have shown the variability in AGB between C3 and C4 grasses, estimation accuracies and the performance of the SPLSR model, over time. Themeda (C4) produced higher AGB from February to April, whereas from May to September, Festuca produced higher AGB. Both species also showed a decrease in AGB in August and September, although this was most apparent for Themeda than its counterpart. Spectral bands information predicted species AGB with lowest accuracies and an improvement was observed when both spectral bands and vegetation indices were applied. For instance, in the month of May, spectral bands predicted species AGB with lowest accuracies for Festuca (R2=0.57; 31.70% of the mean), Themeda (R2=0.59; 24.02% of the mean) and combined species (R2=0.61; 15.64% of the mean); the use of spectral bands and vegetation indices yielded 0.77; (18.64%), 0.75 (14.27%) and 0.73 (16.47%), for Festuca, Themeda and combined species, respectively. The red edge (at 0.705 and 0.74 μm) and derived indices, NIR and SWIR 2 (2.19 μm) were found to contribute more to grass species AGB estimation, over time. Findings have also revealed the potential of the SPLSR model in estimating C3 and C4 grasses AGB using Sentinel 2 images, over time. The AGB spatial variability maps produced in this study can be used to quantify C3 and C4 forage availability or accumulating fuel, as well as for developing operational management strategies.
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    Determining optimal new generation satellite derived metrics for accurate C3 and C4 grass species aboveground biomass estimation in South Africa
    (MDPI, 2018) Shoko, Cletah; Mutanga, Onisimo; Dube, Timothy
    While satellite data has proved to be a powerful tool in estimating C3 and C4 grass species Aboveground Biomass (AGB), finding an appropriate sensor that can accurately characterize the inherent variations remains a challenge. This limitation has hampered the remote sensing community from continuously and precisely monitoring their productivity. This study assessed the potential of a Sentinel 2 MultiSpectral Instrument, Landsat 8 Operational Land Imager, and WorldView-2 sensors, with improved earth imaging characteristics, in estimating C3 and C4 grasses AGB in the Cathedral Peak, South Africa. Overall, all sensors have shown considerable potential in estimating species AGB; with the use of different combinations of the derived spectral bands and vegetation indices producing better accuracies. However,WorldView-2 derived variables yielded better predictive accuracies (R2 ranging between 0.71 and 0.83; RMSEs between 6.92% and 9.84%), followed by Sentinel 2, with R2 between 0.60 and 0.79; and an RMSE 7.66% and 14.66%. Comparatively, Landsat 8 yielded weaker estimates, with R2 ranging between 0.52 and 0.71 and high RMSEs ranging between 9.07% and 19.88%. In addition, spectral bands located within the red edge (e.g., centered at 0.705 and 0.745 m for Sentinel 2), SWIR, and NIR, as well as the derived indices, were found to be very important in predicting C3 and C4 AGB from the three sensors. The competence of these bands, especially of the free-available Landsat 8 and Sentinel 2 dataset, was also confirmed from the fusion of the datasets. Most importantly, the three sensors managed to capture and show the spatial variations in AGB for the target C3 and C4 grassland area. This work therefore provides a new horizon and a fundamental step towards C3 and C4 grass productivity monitoring for carbon accounting, forage mapping, and modelling the influence of environmental changes on their productivity.
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    Evaluating the impact of land use and land cover change on unprotected wetland ecosystems in the arid-tropical areas of South Africa using the Landsat dataset and support vector machine
    (Taylor and Francis Group, 2022) Thamaga, Kgabo Humphrey; Dube, Timothy; Shoko, Cletah
    The study explored the impact of Land Use and Land Cover (LULC) change dynamics in relation to the condition and status of an unprotected wetland located in the arid-tropical parts of the Limpopo Province, South Africa. The long-term Landsat archival data series was used to map and quantify the impacts of LULC change on the wetland over a period of 36 years (1983–2019). A multi-source satellite image analysis was performed, using the support vector machine (SVM) algorithm and advanced spatially- explicit geographic information system tools. Landsat data series covering the entire study area was used to assess, map and monitor LULC change that occurred over-time. Post-classification maps for the Maungani wetland area were analysed to provide a quantitative assessment and a detailed overview of the rate of change. The generated wetland detection maps for four temporal phases (i.e., 1983–1992, 1992–2001, 2002–2010) were analysed.
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    Impacts of climate variability and drought on surface water resources in sub-saharan africa using remote sensing: A review
    (Remote Sensing, 2022) Bhaga, Trisha Deevia; Dube, Timothy; Shekede, Munyaradzi Davis; Shoko, Cletah
    Climate variability and recurrent droughts have caused remarkable strain on water resources in most regions across the globe, with the arid and semi-arid areas being the hardest hit. The impacts have been notable on surface water resources, which are already under threat from massive abstractions due to increased demand, as well as poor conservation and unsustainable land management practices. Drought and climate variability, as well as their associated impacts on water resources, have gained increased attention in recent decades as nations seek to enhance mitigation and adaptation mechanisms. Although the use of satellite technologies has, of late, gained prominence in generating timely and spatially explicit information on drought and climate variability impacts across different regions, they are somewhat hampered by difficulties in detecting drought evolution due to its complex nature, varying scales, the magnitude of its occurrence, and inherent data gaps.
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    Impacts of groundwater and climate variability on terrestrial groundwater dependent ecosystems: A review of geospatial assessment approaches and challenges and possible future research directions
    (Taylor and Francis Group, 2022) Chiloane, Chantel; Dube, Timothy; Shoko, Cletah
    Terrestrial groundwater dependent vegetation (TGDV) are crucialecosystems which provide important goods and services such ascarbon sequestration, habitat, water purification and aestheticbenefits in semi-arid environments. Global climate change andanthropogenic impacts on surface water resources have led toincreased competing claims on groundwater resources to meetan exponential water demand for environmental needs, agricul-tural and developmental needs. This has led to the unsustainableexploitation of groundwater resources, resulting in groundwatertable declines, threatening the sustainability of TGDV. It is on thispremise that the review aims to provide a detailed overview onthe progress in remote sensing of TGDV.
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    Local community attitudes and perceptions towards benefits and challenges associated with biodiversity conservation in Blouberg Nature Reserve, South Africa
    (Journal of Ecology, 2022) Dube, Timothy; Rampheri, Mangana B; Shoko, Cletah; Marambanyika, Thomas; Dhau, Inos
    This study assessed the benefits and challenges associated with local community involvement in biodiversity conservation in the Blouberg Nature Reserve (BNR) of South Africa. To achieve this, a descriptive research design was used in the study. Three hundred and thirty-five households from four villages scattered around the nature reserve were selected using a stratified systematic sampling procedure to participate in a household questionnaire survey. The BNR Manager was purposefully selected for an in- depth structured interview so that an overview of socio-economic benefits and challenges to the community from the park's perspective could be known. Field data collection was conducted during the month of June 2019.
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    Multispectral remote sensing of potential groundwater dependent vegetation in the greater Floristic region of the Western Cape, South Africa
    (Taylor and Francis Group, 2023) Chiloane, Chantel; Dube, Timothy; Shoko, Cletah
    Groundwater dependent vegetation (GDV) is increasingly threa-tened by the transformation of the natural environment. An under-standing of the nature of GDV at the appropriate scale helps environmental managers make suitable decisions. This study assesses the potential for mapping the distribution of GDV within the Heuningnes Catchment using multispectral remotely sensed data (i.e., Landsat 8 (L8) and Sentinel 2 (S2)), the derived vegetation indices (Normalised Difference Vegetation Index (NDVI) and the Soil-Adjusted Vegetation Index (SAVI)) and in-situ data. The GDV distribution maps were produced by integrating vegetation pro-ductivity, landcover, and topographic layers as GDV indicators.
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    Remote sensing of land use-land cover change and climate variability on hydrological processes in Sub-Saharan Africa: Key scientific strides and challenges
    (Taylor and Francis Group, 2022) Govender, Tanushri; Dube, Timothy; Shoko, Cletah
    The impact of land use land cover (LULC) change and climatevariability on water resources poses as a major threat in semi-aridenvironments, especially in the sub-Saharan Africa. Countries insub-Saharan Africa are vulnerable to water scarcity. Hence, thereis an urgent need for understanding the various methods forLULC change and climate variability assessment, to aid in waterresources management at various scales. Various studies havemodelled and assessed the effect of LULC change and climatevariability on hydrological responses, using different approaches.In this regard, this paper provides a detailed review on the pro-gress of various remote sensing techniques in modelling andassessing the effect of LULC change and climate variability onhydrological processes.
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    Remotely sensed data for estimating chlorophyll-a concentration in wetlands located in the Limpopo Transboundary River Basin, South Africa
    (Physics and Chemistry of the Earth, 2022) Dzurume, Tatenda; Dube, Timothy; Shoko, Cletah
    Wetlands in semi-arid regions are highly productive and biologically diverse ecosystems that contribute significantly to livelihood and economic development and play a substantial role in sustaining rural livelihoods. These ecosystems are not only rich in biodiversity, but also predominantly valuable in terms of the services they provide to people, including water security, hydrological regulation, and other services. Chlorophyll-a concentrations and associated dynamics in two tropical wetland systems were estimated in the Makuleke and Nylsvlei wetlands. The Makuleke and Nylsvlei wetlands are in the Limpopo Transboundary River Basin, South Africa. Moderate-resolution Landsat 8 images for September 2018 and June 2019 and in situ field measurements were used to estimate and map chlorophyll-a concentration from the two wetlands. Landsat-derived chlorophyll-a concentrations were validated using field-derived chlorophyll-a measurements. Validation was implemented to assess the consistency of the remotely sensed chlorophyll-a estimates.