Theses & Dissertations

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Browsing Theses & Dissertations by Subject "Deep Learning,"

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    MONITORING OF TREE SPECIES USING OBJECT BASED TIME SERIES ANALYSIS: -A CASE STUDY OF ACACIA XANTHOPHLOEA SPP IN LAKE NAKURU NATIONAL PARK, KENYA
    (Technical University of Kenya, 2023-08) OSIO, ANNE ACHIENG
    ABSTRACT The significance of wetlands as suppliers of ecosystem services to flora and wildlife in conservation zones is examined in this study. Acacia xanthophloea trees in Kenya's Lake Nakuru National Park are the subject of particular attention since they are in danger of going extinct as a result of repeated floods. This study attempts to detect and quantify the damage to the trees over time in order to comprehend the rate of their deterioration in order to address this issue. To identify and categorize Acacia xanthophloea trees in the Lake Nakuru riparian reserve, the study used an object-based image approach to determine the most efficient model for this task, a variety of spaceborne and aerial sensing technologies were used, including multi-temporal and multi-spatial. The overall goal of the study was to quantify Acacia xanthophloea and related plant species in terms of spectral, spatial, and contextual features in order to determine their degree of deterioration in both space and time. The study shows that the OBIA-Random Forest model and particular training techniques successfully and accurately identified Acacia xanthophloea trees. To identify riparian vegetation before and after floods, various algorithms were used, revealing changes in vegetation coverage brought on by flooding. The health and changes in vegetation degradation were monitored over time using NDVI (Normalized Difference Vegetation Index) maps. Classification of non-degraded forests, degraded forests, and submerged degraded forests was done using temporal profiles based on Landsat time series. The study also tested a variety of data processing methods, including the use of CNN frameworks on datasets based on UAVs and high-resolution Pleiades-1A images. The findings indicated alterations in Acacia xanthophloea coverage throughout various time periods and places, pointing to both gains and losses in tree populations. The importance of wetlands and Acacia xanthophloea trees in providing ecosystem services is highlighted by this study's findings. The study used a range of remote sensing tools and analysis techniques to identify, measure, and monitor the damage done to these trees over time. The results have consequences for conservation initiatives and offer guidance for managing and preserving biodiversity in ecosystems with similar wetlands. In order to stop the extinction of Acacia xanthophloea trees and improve general conservation practices, the technique chosen, incorporating the OBIA approach, provides a useful tool for swift response and management plans.