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

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dc.contributor.author Marumbwa, Farai Maxwell
dc.contributor.author Cho, Moses Azong
dc.contributor.author Chirwa, Paxie W.
dc.date.accessioned 2021-01-08T08:59:33Z
dc.date.issued 2020
dc.description.abstract An 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.department Plant Production and Soil Science en_ZA
dc.description.embargo 2021-07-07
dc.description.librarian hj2020 en_ZA
dc.description.sponsorship The University of Pretoria Postgraduate Doctoral Bursary. en_ZA
dc.description.uri http://www.tandfonline.com/loi/tres20 en_ZA
dc.identifier.citation Farai 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.issn 0143-1161 (print)
dc.identifier.issn 1366-5901 (online)
dc.identifier.other 10.1080/01431161.2020.1757783
dc.identifier.uri http://hdl.handle.net/2263/77970
dc.language.iso en en_ZA
dc.publisher Taylor and Francis en_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.subject Drought en_ZA
dc.subject Land cover en_ZA
dc.subject Land use en_ZA
dc.subject Southern Africa en_ZA
dc.subject Vegetation en_ZA
dc.subject Vegetation Condition Index (VCI) en_ZA
dc.title An assessment of remote sensing-based drought index over different land cover types in southern Africa en_ZA
dc.type Postprint Article en_ZA


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