Show simple item record

dc.contributor.authorAgasha, Elizabeth
dc.date.accessioned2024-05-13T07:33:40Z
dc.date.available2024-05-13T07:33:40Z
dc.date.issued2024
dc.identifier.urihttp://hdl.handle.net/20.500.12281/18639
dc.description.abstractThis study focuses on the increasing frequency and intensity of drought globally since the 1970s, with a particular emphasis on Isingiro district. The district has been severely affected by drought for the past 20 years, especially since 2015, largely due to extensive deforestation for charcoal production. Local measures such as intercropping, mulching, water retention trenches, and bottle irrigation have been implemented on a small scale due to their cost-effectiveness. However, these measures have limitations in terms of scale and the types of crops they can support. To address this issue on a larger scale, remote sensing and GIS technologies can provide advanced solutions for prioritizing and implementing large-scale irrigation systems. Agricultural drought is a complex phenomenon that cannot be accurately represented by a single parameter. Various indices derived from remote sensing have been used to monitor drought, but none of them can fully capture agricultural drought alone. Efforts have been made to integrate these indices for drought monitoring; however, composite indices have specific data requirements and applications that may not always be available. In this study, a multi-criteria data analysis (MCDA) technique is employed to assess agricultural drought using three primary parameters: crop water supply, temperature above the crops, and vegetation health represented by the Standardized Precipitation Index (SPI), Temperature Condition Index (TCI), and Normalized Difference Vegetation Index (NDVI) respectively. Drought condition maps for the years 2005, 2010, 2015, and 2020 were generated using this technique, revealing that 2015 experienced the most extreme drought. Furthermore, drought vulnerability maps were created, identifying Masha, Ruggaga, Endinzi, Kashumba, Kabingo, and Ngarama Counties as the most highly vulnerable areas to drought. By utilizing the findings from this study, policymakers and stakeholders can make informed decisions and prioritize appropriate interventions to mitigate the impacts of drought in Isingiro district.en_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectAgricultural droughten_US
dc.subjectNDVI anomalyen_US
dc.subjectRemote sensingen_US
dc.subjectGISen_US
dc.subjectIsingiro Districten_US
dc.subjectMCDA techniqueen_US
dc.subjectDrought monitoringen_US
dc.titleUsing remote sensing and GIS techniques for agricultural drought assessment: A case study of Isingiro Districten_US
dc.typeThesisen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record