An assessment of remote sensing-based drought index over different land cover types in southern Africa

dc.contributor.authorMarumbwa, Farai Maxwell
dc.contributor.authorCho, Moses Azong
dc.contributor.authorChirwa, Paxie W.
dc.date.accessioned2021-01-08T08:59:33Z
dc.date.issued2020
dc.description.abstractAn understanding of drought and land cover interaction plays a crucial role in vegetation vulnerability studies and land use planning. However, there is paucity of information on drought, land cover and land use interaction in southern Africa. We analysed the drought impact on land cover using Globcover land cover data and Vegetation Condition Index (VCI) for the 2015 to 2016 season. The 2015 to 2016 season was chosen because it was the worst drought in southern Africa since the 1980s. We developed a novel land cover ‘social pixels’ or ‘village pixels’ which represents rural communities. The Kruskal–Wallis test was used to evaluate whether there is a significant difference in drought impact among the land cover classes. The response of each land cover to drought impact was calculated by correlating Standardized Precipitation Evapotranspiration Index (SPEI) and Normalized Difference Vegetation Index (NDVI). Our results reveal that the evergreen forests and the flooded vegetation were the most severely affected by the 2015–2016 drought. However, the lowest VCI values were recorded within the village pixels land cover, indicating the vulnerability of rural communities to drought impacts. The vegetation response to drought impact ranged from 2 months (crops) to 8 months (flooded vegetation). With regards to drought recurrence (1998 to 2018), the crop and grassland land cover recorded the highest drought frequency whilst the forest had the least drought frequency.en_ZA
dc.description.departmentPlant Production and Soil Scienceen_ZA
dc.description.embargo2021-07-07
dc.description.librarianhj2020en_ZA
dc.description.sponsorshipThe University of Pretoria Postgraduate Doctoral Bursary.en_ZA
dc.description.urihttp://www.tandfonline.com/loi/tres20en_ZA
dc.identifier.citationFarai Maxwell Marumbwa , Moses Azong Cho & Paxie W Chirwa (2020) An assessment of remote sensing-based drought index over different land cover types in southern Africa, International Journal of Remote Sensing, 41:19, 7368-7382, DOI: 10.1080/01431161.2020.1757783.en_ZA
dc.identifier.issn0143-1161 (print)
dc.identifier.issn1366-5901 (online)
dc.identifier.other10.1080/01431161.2020.1757783
dc.identifier.urihttp://hdl.handle.net/2263/77970
dc.language.isoenen_ZA
dc.publisherTaylor and Francisen_ZA
dc.rights© 2020 Informa UK Limited, trading as Taylor & Francis Group. This is an electronic version of an article published in International Journal of Remote Sensing, vol. 41, no. 19, pp. 7368-7382, 2020. doi : 10.1080/01431161.2020.1757783. International Journal of Remote Sensing is available online at : http://www.tandfonline.com/loi/tres20.en_ZA
dc.subjectDroughten_ZA
dc.subjectLand coveren_ZA
dc.subjectLand useen_ZA
dc.subjectSouthern Africaen_ZA
dc.subjectVegetationen_ZA
dc.subjectVegetation Condition Index (VCI)en_ZA
dc.titleAn assessment of remote sensing-based drought index over different land cover types in southern Africaen_ZA
dc.typePostprint Articleen_ZA

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