Spatial characterisation of vegetation diversity in groundwater-dependent ecosystems using in-situ and sentinel-2 msi satellite data

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dc.contributor.authorMpakairi, Kudzai Shaun
dc.contributor.authorDube, Timothy
dc.contributor.authorDondofema, Farai
dc.date.accessioned2022-10-06T10:39:11Z
dc.date.available2022-10-06T10:39:11Z
dc.date.issued2022
dc.description.abstractGroundwater-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.en_US
dc.identifier.citationMpakairi, K. S. et al. (2022). Spatial characterisation of vegetation diversity in groundwater-dependent ecosystems using in-situ and sentinel-2 msi satellite data. Remote Sensing, 14(13), 2995. https://doi.org/10.3390/rs14132995en_US
dc.identifier.issn2072-4292
dc.identifier.urihttps://doi.org/10.3390/rs14132995
dc.identifier.urihttp://hdl.handle.net/10566/8029
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.subjectGroundwater-Dependent Ecosystems (GDEs)en_US
dc.subjectBiodiversityen_US
dc.subjectVegetation diversityen_US
dc.subjectSustainable Development Goalen_US
dc.subjectTransboundary groundwateren_US
dc.subjectWater qualityen_US
dc.titleSpatial characterisation of vegetation diversity in groundwater-dependent ecosystems using in-situ and sentinel-2 msi satellite dataen_US
dc.typeArticleen_US

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