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dc.contributor.authorKissa, Sam
dc.date.accessioned2022-06-28T14:48:22Z
dc.date.available2022-06-28T14:48:22Z
dc.date.issued2021-10
dc.identifier.citationKissa, S. (2021) Assessing tree species distribution in Budongo Forest Uganda using GIS and remote sensing (Unpublished master's dissertation). Makerere University, Kampala Ugandaen_US
dc.identifier.urihttp://hdl.handle.net/10570/10641
dc.descriptionA dissertation submitted to the Directorate of Research and Graduate Training for partial fulfillment of the requirement for the award of Master of Science in Geo-Information Science and Technology of Makerere Universityen_US
dc.description.abstractUganda recognizes that forests are central to the three pillars of sustainable development which are economy, society and the environment. Global Forest Resources Assessment (FRA), coordinated by the Food and Agricultural Organization (FAO) of the United Nations, found that the world’s forest area decreased from 31.6 percent of global land area to 30.6 percent between 1990 & 2015. Tropical forests are among the most complex and endangered ecosystems in the world and they cover about 5% of Uganda’s area. Mapping individual tree species through remote sensing has many applications in resource management, biodiversity assessment and conservation. The use of satellite images has not extensively been used to classify tree species in Uganda’s tropical forests. Most of the government decisions to conserve, improve and manage these tropical forests are through manual forest inventories. The objectives of the study were (1) To assess the distribution of tree species using remote sensing and GIS, (2) Compare the results & products developed using traditional forest inventory methods and GIS & Remote sensing. This was achieved by classifying the different tree species from Sentinel-2A satellite imagery and comparing results and products of using remote sensing and forest inventories in tree species classification and mapping. The results indicate that Sentinel-2A satellite imagery can be used to efficiently assess tree species distribution in tropical forests. From the assessment of tree species distribution, results indicate that Cynometra alexandrii occupies 17.4% of the forest and it is dominant in compartments of Siiba 2, Siiba 3, Siiba 4, Siiba 5 and Siiba 6, Khaya anthotheca covers 10.6% of the reserve and present in most compartments of the forest reserve, Albizia zygia covers 7.4% towards the woodland, Cordia millenii covers 5%, Celtis malbreadii covers 3.8%, Chrysophylum albidum covers 2.4%, Maesopsis eminii covers 1.5%, Broussonetia papyrifera covers 2.7% and other species (Grassland and woodland species) covers 45%. Most of the tree species are common in most parts of the forest reserve with different coverages as stated above. From the forest inventory data Celtis malbreadii occupies 44% of the forest while Cynometra Alexandrii occupies 34% of the forest, Khaya Anthotheca covers 6% and the rest of other species maintained their approximate extent close to the coverage from the classified map. With freely available sentinel-2A data, it is recommended that the use of Remote Sensing in classifying and mapping tree species be adopted to boost tropical forest monitoring.en_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectTree speciesen_US
dc.subjectBudongo Foresten_US
dc.subjectRemote sensingen_US
dc.subjectGeographical Information System (GIS)en_US
dc.titleAssessing tree species distribution in Budongo Forest Uganda using GIS and remote sensingen_US
dc.typeThesisen_US


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