Browsing by Author "Dondofema, Farai"

Now showing 1 - 4 of 4
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    Identification and delineation of groundwater-dependent ecosystems (GDEs) in the Khakea–Bray transboundaryaquifer region using geospatial techniques
    (Taylor and Francis Group, 2023) Rampheri, Mangana B.; Dube, Timothy; Dondofema, Farai
    Identifying and delineating groundwater-dependent ecosystems(GDEs) is critical in understanding their location, distribution andgroundwater allocation. However, this information is inadequatelyunderstood due to limited available data for most areas where theyoccur. Thus, this study aims to address this gap using remotelysensed, analytical hierarchy process (AHP) andin situdata to identifyand delineate GDEs in the Khakea–Bray transboundary aquifer region.The study tested various spatial-explicit GDE indices that integratesenvironmental factors that predict occurrence of GDEs. These includethe normalized difference vegetation index as a proxy for vegetationproductivity and modified normalized difference water index asproxy for moisture availability, land-use and landcover, topographicalfactors such as slope, topographic wetness index,flow accumulationand curvature.
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    Progress in the remote sensing of groundwater-dependent ecosystems in semi-arid environments
    (Elsevier, 2021) Rampheri, Mangana B.; Dube, Timothy; Dondofema, Farai
    Remote sensing of groundwater-dependent ecosystems (GDEs) has increased substantially in recent years. Of significant prominence, is the delineation and mapping of groundwater-dependent vegetation (GDV), species diversity, and water quality in these ecosystems. Groundwater-dependent ecosystems provide several ecological services such as habitat for wildlife fauna, carbon sequestration and water purification. The recent technological advancements and readily accessibility of new satellite sensors with improved sensing characteristics have resulted in numerous state-of-the-art applications for GDEs assessment and monitoring. These studies were done at varying scales, essentially in light of global climate change and variability. In this study, we review and assess the progress on the remote sensing of GDEs in semi-arid environments. We present the key trends in GDEs remote sensing that underpin many of the recent scientific research milestones and application developments. In addition, we observed a considerable shift towards the use of advanced spatial modelling techniques, using high- resolution remotely sensed data to further improve the characterisation and understanding of GDEs. Thus, literature shows the successful use of freely available remotely sensed data in mapping GDEs.
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    Spatial characterisation of vegetation diversity in groundwater-dependent ecosystems using in-situ and sentinel-2 msi satellite data
    (MDPI, 2022) Mpakairi, Kudzai Shaun; Dube, Timothy; Dondofema, Farai
    Groundwater-Dependent Ecosystems (GDEs) are under threat from groundwater overabstraction, which significantly impacts their conservation and sustainable management. Although the socio-economic significance of GDEs is understood, their ecosystem services and ecological significance (e.g., biodiversity hotspots) in arid environments remains understudied. Therefore, under the United Nations Sustainable Development Goal (SDG) 15, characterizing or identifying biodiversity hotspots in GDEs improves their management and conservation. In this study, we present the first attempt towards the spatial characterization of vegetation diversity in GDEs within the Khakea-Bray Transboundary Aquifer. Following the Spectral Variation Hypothesis (SVH), we used multispectral remotely sensed data (i.e., Sentinel-2 MSI) to characterize the vegetation diversity.
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    Spatio–temporal variation of vegetation heterogeneity in groundwater dependent ecosystems within arid environments
    (Ecological Informatics, 2022) Mpakairi, Kudzai S; Dube, Timothy; Dondofema, Farai; Dalu, Tatenda
    Climate change, land cover change and the over–abstraction of groundwater threaten the existence of Groundwater-Dependent Ecosystems (GDE), despite these environments being regarded as biodiversity hotspots. The vegetation heterogeneity in GDEs requires routine monitoring in order to conserve and preserve the ecosystem services in these environments. However, in–situ monitoring of vegetation heterogeneity in extensive, or transboundary, groundwater resources remain a challenge. Inherently, the Spectral Variation Hypothesis (SVH) and remotely-sensed data provide a unique way to monitor the response of GDEs to seasonal or intra–annual environmental stressors, which is the key for achieving the national and regional biodiversity targets. This study presents the first attempt at monitoring the intra–annual, spatio–temporal variations in vegetation heterogeneity in the Khakea–Bray Transboundary Aquifer, which is located between Botswana and South Africa, by using the coefficient of variation derived from the Landsat 8 OLI Operational Land Imager (OLI).