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dc.contributor.authorAmanya, Saphra
dc.date.accessioned2022-05-17T11:52:07Z
dc.date.available2022-05-17T11:52:07Z
dc.date.issued2022-12-23
dc.identifier.citationAmanya, Saphra. (2022). Flood mapping using analytical hierarchy process and fuzzy logic. (Unpublished undergraduate dissertation) Makerere University; Kampala, Uganda.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12281/12617
dc.descriptionA final year project report submitted to the department of Geomatics and Land Management in partial fulfillment of the requirements for an award of a Bachelors degree of Bachelor of Science Land Surveying and Geomatics of Makerere University.en_US
dc.description.abstractKampala city has experienced floods on a number of occasions after a downpour, causing damage to people’s homes, water pollution, disruption of traffic and economic activities. This study aims at flood susceptibility mapping using analytical hierarchy process, fuzzy criteria and a combination of two algorithms AHP and fuzzy in Kampala city Uganda. Flood maps are generated based on six flood influencing factors (rainfall intensity, LULC, soil moisture index, soil type and drainage density). Thematic maps for each of the six flood conditioning factors were generated, and the generated thematic maps were used to develop flood maps using AHP, fuzzy criteria and a combination of both algorithms AHP and fuzzy. Using AHP the weight derived for the factors were Rainfall 59%, Slope 7.514%, Drainage density 14.291%, Soil type 5.243%, LULC 11.002%, Soil moisture 2.95%. The generated flood susceptible maps were assessed based on the area under the curve as shown by the receiver operating curve, AHP had an accuracy of 56.16%, fuzzy criteria had an accuracy of 81.42% and the combination of both algorithms had an accuracy of 71.98%.en_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectFloodsen_US
dc.subjectMapping floodsen_US
dc.titleFlood mapping using analytical hierarchy process and fuzzy logic.en_US
dc.typeThesisen_US


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