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dc.contributor.authorKaggwa, Rogers Jjemba
dc.date.accessioned2022-12-21T09:05:40Z
dc.date.available2022-12-21T09:05:40Z
dc.date.issued2022
dc.identifier.citationKaggwa, R. J. (2022). Investigation of spatial and temporal forest cover change using GEE : a case study of Mabira Forest (Unpublished undergraduate dissertation). Makerere University, Kampala, Uganda.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12281/13794
dc.descriptionA research project submitted to the School of Built Environment as a requirement for partial fulfillment for award of Bachelor of Science in Land Surveying and Geomatics of Makerere University.en_US
dc.description.abstractMabira Forest, a rainforest in Uganda that is situated between Lugazi and Jinja and spans an area of 300 square kilometers (120 square miles) (30,000 hectares (74,000 acres), has been protected since 1932. People have put a lot of strain on the forest over time, which has been linked to the rise in demand for agricultural land and forest products. This study used Google Earth Engine to look at the spatial and temporal changes in the Mabira forest's forest cover. The NDVI was seen to be changing over time using time series and change detection analyses, with the good NDVI (healthy forest cover) being in the early years of 2002 and 2003 and it (NDVI) is gradually decreasing from 2018 and beyond. The Menon and Bawa model and the NDVI approach were used to calculate the deforestation rates for each year during the last 20 years. With 11430 samples, land cover was classified using the Random Forest classifier utilizing the categories of built up, agricultural land, bare ground, and forested land. This was carried out with a training overall accuracy of 87.4753%, and validation was carried out as well.en_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectGoogle Earth Engine (GEE)en_US
dc.subjectRandom Forest Classifieren_US
dc.subjectRemote sensingen_US
dc.subjectTime seriesen_US
dc.subjectMabira Foresten_US
dc.titleInvestigation of spatial and temporal forest cover change using GEE : a case study of Mabira Foresten_US
dc.typeThesisen_US


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