Landsat satellite derived environmental metric for mapping mosquitoes breeding habitats in the Nkomazi municipality, Mpumalanga Province, South Africa

dc.contributor.authorAdeola, Abiodun Morakinyo
dc.contributor.authorOlwoch, Jane Mukarugwiza
dc.contributor.authorBotai, Joel Ongego
dc.contributor.authorRautenbach, Cornelis Johannes de Wet
dc.contributor.authorKalumba, Ahmed M.
dc.contributor.authorTsela, Philemon Lehlohonolo
dc.contributor.authorAdisa, O.M. (Omolola)
dc.contributor.authorNsubuga, Francis Wasswa Nkugwa
dc.date.accessioned2016-06-20T08:52:16Z
dc.date.issued2017
dc.description.abstractThe advancement, availability and high level of accuracy of satellite data provide a unique opportunity to conduct environmental and epidemiological studies using remotely sensed measurements. In this study, information derived from remote sensing data is used to determine breeding habitats for Anopheles arabiensis which is the prevalent mosquito species over Nkomazi municipality. In particular, we have utilized the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) coupled with land surface temperature (LST) derived from Landsat 5 TM satellite data. NDVI, NDWI and LST are considered as key environmental factors that influence the mosquito habitation. The breeding habitat was derived using multi-criteria evaluation (MCE) within ArcGIS using the derived environmental metric with appropriate weight assigned to them. Additionally, notified malaria cases were analysed and spatial data layers of water bodies, including rivers and dams, were buffered to further illustrate areas at risk of malaria. The output map from the MCE was then classified into three classes which are low, medium and high areas. The resulting malaria risk map depicts that areas of Komatieport, Malelane, Madadeni and Tonga of the district are subjected to high malaria incidence. The time series analysis of environmental metrics and malaria cases can help to provide an adequate mechanism for monitoring, control and early warning for malaria incidence.en_ZA
dc.description.departmentGeography, Geoinformatics and Meteorologyen_ZA
dc.description.embargo2017-12-30
dc.description.librarianhb2016en_ZA
dc.description.sponsorshipThe EU project QWeCI (Quantifying Weather and Climate Impacts on health in developing countries) and the European Commission’s Seventh Framework Research Programme under the [grant number 243964]).en_ZA
dc.description.urihttp://www.tandfonline.com/loi/rsag20en_ZA
dc.identifier.citationA.M. Adeola, J.M. Olwoch, J.O. Botai, C.J. deW Rautenbach, A.M. Kalumba, P.L. Tsela, O.M. Adisa & F.W.N. Nsubuga (2015): Landsat satellite derived environmental metric for mapping mosquitoes breeding habitats in the Nkomazi municipality, Mpumalanga Province, South Africa, South African Geographical Journal, 99(1): 14-28. DOI: 10.1080/03736245.2015.1117012.en_ZA
dc.identifier.issn0373-6245 (print)
dc.identifier.issn2151-2418 (online)
dc.identifier.other10.1080/03736245.2015.1117012
dc.identifier.urihttp://hdl.handle.net/2263/53266
dc.language.isoenen_ZA
dc.publisherRoutledgeen_ZA
dc.rights© 2015 Society of South African Geographers. This is an electronic version of an article published in South African Geographical Journal, vol. 99, no. 1, pp. 14-28, 2017. doi : 10.1080/03736245.2015.1117012. South African Geographical Journal is available online at : http://www.tandfonline.com/loi/rsag20.en_ZA
dc.subjectRemote sensingen_ZA
dc.subjectGeographic information system (GIS)en_ZA
dc.subjectEnvironmentalen_ZA
dc.subjectMalariaen_ZA
dc.subjectNormalized difference vegetation index (NDVI)en_ZA
dc.subjectNormalized difference water index (NDWI)en_ZA
dc.subjectLand surface temperature (LST)en_ZA
dc.subjectMulti-criteria evaluation (MCE)en_ZA
dc.titleLandsat satellite derived environmental metric for mapping mosquitoes breeding habitats in the Nkomazi municipality, Mpumalanga Province, South Africaen_ZA
dc.typePostprint Articleen_ZA

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