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dc.contributor.authorMpakairi, Kudzai S
dc.contributor.authorDube, Timothy
dc.contributor.authorDondofema, Farai
dc.contributor.authorDalu, Tatenda
dc.date.accessioned2023-06-15T13:53:26Z
dc.date.available2023-06-15T13:53:26Z
dc.date.issued2022
dc.identifier.citationMpakairi, K.S., Dube, T., Dondofema, F. and Dalu, T., 2022. Spatio–temporal variation of vegetation heterogeneity in groundwater dependent ecosystems within arid environments. Ecological Informatics, 69, p.101667.en_US
dc.identifier.urihttps://doi.org/10.1016/j.ecoinf.2022.101667
dc.identifier.urihttp://hdl.handle.net/10566/9104
dc.description.abstractClimate 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).en_US
dc.language.isoenen_US
dc.publisherEcological Informaticsen_US
dc.subjectKhakea–brayen_US
dc.subjectRao’s Qen_US
dc.subjectRandom foresten_US
dc.subjectVegetation heterogeneityen_US
dc.subjectSpectral variation hypothesis (SVH)en_US
dc.titleSpatio–temporal variation of vegetation heterogeneity in groundwater dependent ecosystems within arid environmentsen_US
dc.typeArticleen_US


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