Browsing by Author "Opedes, Hosea"

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    The damage caused by landslides in socio-economic spheres within the Kigezi highlands of South Western Uganda
    (Environmental & Socio-economic Studies, 2021) Nseka, Denis; Mugagga, Frank; Opedes, Hosea; Ayesiga, Patience; Wasswa, Hannington; Mugume, Isaac; Nimusiima, Alex; Nalwanga, Faridah
    An assessment of the socio-economic implications of landslide occurrence in the Kigezi highlands of South Western Uganda was conducted. Landslide occurrence is on the increase and threatens community livelihoods in these highlands. Detailed field investigations were undertaken with the help of local communities between June 2018 and May 2020 to identify and map recent and visible landslide scars in Rukiga uplands of Kigezi highlands. In the course of field inventories, 85 visible landslide scars were identified and mapped using handheld GPS receivers to produce a landslide distribution map for the study area. A socio-economic analysis was conducted to establish the effects of landslide damage on people’s livelihoods as well as their existing coping and adaptation mechanisms. The assessment was administered through field observations and surveying, focus group discussions, key informants and household interviews as well as the use of Local Government Environmental Reports. The study established an increase in the spatial-temporal distribution of landslides over the Kigezi highlands in the past 40 years. The landslides have resulted in a reduction in the quality of land, loss of lives, destruction of transport infrastructures, settlements, farmlands, crops and other socio-economic infrastructures. Therefore, it is important to look for reliable and sustainable measures to prevent landslide hazards. Total landscape reforestation with deep-rooted trees can possibly reduce the landslide risk. It is also important to undertake policy implementation for preparedness and mitigation plans against landslides in this region and in the country at large. Proper soil and water conservation measures could help in enhancing soil strength against landslide hazards.
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    Land Cover Change Detection and Subsistence Farming Dynamics in the Fringes of Mount Elgon National Park, Uganda from 1978–2020
    (Remote Sens, 2022) Opedes, Hosea; Mücher, Sander; Baartman, Jantiene E. M.; Nedala, Shafiq; Mugagga, Frank
    Analyzing the dominant forms and extent of land cover changes in the Mount Elgon region is important for tracking conservation efforts and sustainable land management. Mount Elgon’s rugged terrain limits the monitoring of these changes over large areas. This study used multitemporal satellite imagery to analyze and quantify the land cover changes in the upper Manafwa watershed of Mount Elgon, for 42 years covering an area of 320 km2. The study employed remote sensing techniques, geographic information systems, and software to map land cover changes over four decades (1978, 1988, 2001, 2010, and 2020). The maximum likelihood classifier and post-classification comparison technique were used in land cover classification and change detection analysis. The results showed a positive percentage change (gain) in planted forest (3966%), built-up (890%), agriculture (186%), and tropical high forest low-stocked (119%) and a negative percentage change (loss) in shrubs (􀀀81%), bushland (􀀀68%), tropical high forest well-stocked (􀀀50%), grassland (􀀀44%), and bare and sparsely vegetated surfaces (􀀀14%) in the period of 1978–2020. The observed changes were concentrated mainly at the peripheries of the Mount Elgon National Park. The increase in population and rising demand for agricultural land were major driving factors. However, regreening as a restoration effort has led to an increase in land area for planted forests, attributed to an improvement in conservation-related activities jointly implemented by the concerned stakeholders and native communities. These findings revealed the spatial and temporal land cover changes in the upper Manafwa watershed. The results could enhance restoration and conservation efforts when coupled with studies on associated drivers of these changes and the use of very-high-resolution remote sensing on areas where encroachment is visible in the park.
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    Monitoring land cover changes and farming dynamics in the fringes of Mount Elgon National Park, Uganda.
    (Copernicus Meetings, 2022) Opedes, Hosea; Baartman, Jantiene; Mücher, Sander; Mugagga, Frank
    Analyzing the dominant forms and extent of land cover changes in the Mount Elgon region is important for tracking conservation efforts and sustainable land management. Mount Elgon's rugged terrain limits monitoring these changes over large areas. With conducive climatic conditions, highly fertile and productive soils; Elgon is one of the densely populated rural mountainous regions in East Africa. The demand for more agricultural land and space for settlement has led to continued vegetation clearance and encroachment of the park. These pressures combined with the loss of vegetation cover have led to the continued occurrence of natural hazards, especially landslides and soil erosion events. Recent studies have given focus to these hazards and coping strategies. However, monitoring changes in land cover and associated driving factors are fundamental towards the improvement of land use, land restoration, and vegetation recovery in Mount Elgon. This study used multitemporal satellite imagery, aerial photographs, field surveys, and expert interviews to analyze and quantify the land cover flows in the upper Manafwa watershed of Mount Elgon, for 42 years covering an area of 319.73km2. The study employed remote sensing techniques and geographic information system and software to map land cover changes for four stages (1978-1988, 1988-2001, 2001-2010, and 2010-2020). The study considered nine land cover classes; tropical high forest well-stocked, grassland, shrubs, bushland, bare & sparsely vegetated surfaces, tropical high forest low-stocked, agriculture, planted forest, and built-up. The maximum likelihood classifier of supervised classification and postclassification comparison technique was used in land cover classification and change detection analysis.