Assistant, Department of Environmental science , College of Natural and Computational science, Wolaita Sodo University, Ethiopia, East Africa Wolaita Sodo University
Analyzing urban sprawl in response to land use land cover change dynamics in Areka town and surrounding area: Wolaita Zone, Ethiopia Selemon Thomas Fakana, Elias Bojago, Abebe Alambo Tona, Fekadu Fanjana Falta, Wondimu Elias Worajo, Alefu Chinasho Gujube Environmental and Sustainability Indicators, 2026 Urban sprawl, the uncoordinated and spatially dispersed expansion of urban areas into surrounding rural lands, poses significant challenges to sustainable development, resulting in the loss of agricultural and forest land, habitat degradation, and a weakening of ecosystem services. Using Landsat data for 1995 and 2025, LULC was analyzed for spatiotemporal change in Areka Town and its surrounding area, employing GIS and remote sensing techniques. Training samples were generated by combining multiple bands, and supervised classification was performed using the Support Vector Machine (SVM) algorithm. The resulting classification map was validated using a confusion matrix and the Kappa statistic. The Kappa coefficients of the LULC maps for 1995 and 2025 were 0.8942 and 0.9428, respectively. The findings demonstrate that substantial landscape transformation occurred between 1995 and 2025. Built-up areas and vegetation cover increased by 1,188.83 ha (+492.98%) and 1,291.49 ha (+40.09%), with annual rates of increase of 39.63 ha/year (16.43%) and 43.05 ha/year (1.34%), respectively. However, agricultural and bare land decreased by -1875.8 ha (−47.16%) and -604.9 ha (−23.24%), respectively. Population density analysis revealed that, in 2000, it ranged from 244 to 3264 people/km 2 , whereas in 2020 these values rose to 478 to 4,644 people/km 2 , indicating substantial spatial and temporal intensification accompanied by the outward expansion of the built-up area. Spectral indicators (NDVI and NDBI) provide a quantitative assessment of vegetation dynamics and urban expansion. In 1995, NDVI values ranged from 0.06 to 0.39, whereas in 2025, values had shifted slightly to −0.04 to 0.39, indicating a reduction in vegetation vigor and an increase in impervious surfaces (concrete, asphalt, and buildings). Likewise, the NDBI values, which ranged from −0.24 to 0.19 in 1995 and −0.27 to 0.21 in 2025, reveal a consistent increase in built-up intensity. The gradient directional analysis also demonstrated an asymmetric growth pattern radiating outward from the CBD, along the northern (N), northeastern (NE), and southern (S to SSE) axes, associated with infrastructure development and major roads linking the town with emerging peri-urban settlements. The findings would provide critical insights into the spatial extent and pattern of urban sprawl, helping in sustainable urban planning and land resource management. • GIS and remote sensing analysis using Landsat imagery revealed pronounced urban sprawl • LULC supervised classification using the SVM algorithm achieved plausible accuracy • Built-up expanded (+492.98%), at the expense of agricultural (−47.16%) and bare land (−23.24%) • NDVI and NDBI analysis confirmed declining vegetation vigor and increasing urban sprawl • Directional sprawl analysis showed asymmetric outward expansion along major infrastructure development
Exploring urban solid waste landfill sites for Arba Minch Town, Ethiopia: A suitability analysis employing geospatial technologies for sustainable urban development Alemayehu Abera, Elias Bojago, Mamush Masha, Gemechu Tadila Cleaner Waste Systems, 2026 Geospatial technologies were applied in this study to evaluate potential landfill sites to accommodate solid waste in the fast-growing Arba Minch Town, southern Ethiopia, by integrating multiple criteria, including environmental (slope, land use/land cover types, distance from streams/rivers, and distance from protected areas), social (distance from settlements), and economic factors (distance from road networks). Using several criteria, including land use and land cover, road network, land slope, stream, distance from settlement, and distance from protected areas, the weighted overlay analysis method was used to evaluate suitability. In this process, weights were assigned to the factors based on their significance in determining landfill site suitability. Following the overlay analysis, the weighted aggregation results revealed four levels of suitability for solid waste landfill sites in the study area: unsuitable, less suitable, moderately suitable, and highly suitable. According to this study, the majority of the area (48.6 %) is unsuitable for landfill sites, 24.6 % is less suitable, and 19.8 % is moderately suitable for landfill sites. Only 7 % of the total area is highly suitable for a landfill site, with the most suitable areas located in the northeast of town. In conclusion, this study proposes a practical solution to the problem of solid waste landfill sites using geospatial technology. The AHP-weighted GIS overlay yielded an overall accuracy of ∼8–10 % points better (97.6 % vs. 89.4 %) as well as producer and user accuracies of 97.3 and 97.9 %, respectively (vs. 88.5 and 90.2 % points) to produce more accurate, reliable, and compliant landfill siting. The results of this study show that the implementation of GIS with the analytic hierarchy process (AHP) method has the potential to select appropriate landfill sites for future use in the region. These findings provide geospatial insights for municipal planners and regional authorities to develop resilient solid waste strategies, thereby enhancing environmental sustainability and urban resilience in Arba Minch and similar towns in Ethiopia. • Overall 48.6 % area unsuitable, only 7 % highly suitable are located northeast direction. • Stakeholder cooperation needed for better waste management. • AHP-GIS integration effective for landfill site selection. • Study limited to non-hazardous waste; recommends separate hazardous waste sites. • Community awareness crucial for sustainable waste practices.
GIS-based analysis of urban expansion in Wolaita Sodo, South Ethiopia: implications for sustainable development Mamush Masha, Gemechu Tadila, Elias Bojago Discover Sustainability, 2025 Urbanization and population growth are the major drivers of land use and cover changes in peri-urban areas. This study aimed to analyze urban expansion and land use and land cover (LULC) changes in Wolaita Sodo City, South Ethiopia. Three Landsat (2003, 2013, and 2023) satellite images were used for the study over 20 years. GIS and remote sensing techniques were used to analyze urban expansion and land cover changes in the city. The maximum likelihood algorithm for supervised classification was used to create LULC maps. The satellite image results show that built-up areas increased by 4,654 ha (10.82%), 7914.9 ha (18.4%), and 11681.5 ha (27.2%), respectively, in the first, second, and entire study periods, though the rate was 326.09 ha/year, 376.66 ha/year, and 702.75 ha/year in the first, second, and entire study periods. This rapid growth due to city development has resulted in land grabbing, mainly affecting peri-urban farmers. Managing urban expansion, land use, and agricultural land invasion are crucial for livelihoods. Future studies should integrate innovative techniques with land-use optimization to identify areas that will be covered by future city growth. This will help to balance urban development and environmental conservation.
Monitoring spatio-temporal changes in land use, land cover, and NDVI using MODIS data in Ethiopia’s Gambela region Elias Bojago, Gemechu Tadila, Mamush Masha Discover Applied Sciences, 2025 Understanding spatiotemporal changes in land use, land cover (LULC), and vegetation dynamics is crucial for sustainable environmental management and planning. This study investigated LULC and vegetation changes in the Gambela region of Ethiopia using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data from 2004 to 2024. This study relied on MOD13A3 (NDVI, 1 km, monthly) to track vegetation changes from to 2004–2024, as well as Landsat image classification was used to LULC estimation. The IGBP was refined using a random forest with NDVI thresholding to identify shifts. The accuracy was 87% through Sentinel-2 and ground truth, and NDVI deviations were associated (0.80) with yields. Geospatial and statistical techniques were employed to detect and quantify transitions between land cover classes and fluctuations in greenness in the study area. Six LULC classes, namely forest, agricultural land, grassland, irrigated land, built‑up area, and water bodies, were mapped and analyzed. Between 2004 and 2024, forest cover declined by 2 693.9 km 2 (from 74.2% to 65.3%), agricultural land expanded by 4 618.4 km 2 (from 5.3% to 20.6%), and grasslands contracted by 2 397.8 km 2 (from 19.5% to 11.5%). Irrigated areas more than tripled (0.4% to 1.2%), and built‑up extent grew nearly five‑fold (0.2% to 0.9%), whereas water bodies remained largely stable during this period. NDVI analysis revealed a 12% reduction in high-greenness areas, typically corresponding to NDVI values ≥ 0.6 (often 0.6–0.8), and a mean NDVI drop from 0.62 to 0.59 in non-forest zones, indicating declining vegetation health in converted landscapes. The study found significant LULC changes driven by agricultural expansion, settlement growth, and climate variability, with declining natural vegetation and increasing cultivated and built-up areas in the western and central regions. MODIS data are valuable for environmental monitoring, offering insights into land management and climate adaptation.
Agroforestry practices, adoption factors, and livelihood contributions among smallholder farmers in Didu district, southwestern Ethiopia Alemayehu Abera, Elias Bojago, Mamush Masha, Teshome Lidatu Journal of Agriculture and Food Research, 2025 Agroforestry (AF) has the potential to deliver for rural livelihoods, environmental sustainability, and climate change adaptation and mitigation. Little attention has been paid to smallholder farmers’ perceptions, adoption levels with barriers, and influencing factors. This study examines how adoption is determined and the livelihood contribution of AF practices among smallholder farmers in Didu District, Southwestern Ethiopia. This study employed a mixed-method cross-sectional design. Using a multi-stage sampling procedure, 296 respondents (174 adopters and 122 non-adopters) were selected. The collected data were analyzed using thematic, descriptive, and inferential methods. Farmers adopted various AF practices in different home gardens (36%), scattered trees in croplands (29.71%), boundary tree planting (16%), and hedgerows (2.29%). The major barriers to AF adoption were the lack of extension services (98.3%), limited land (97%), and inaccessible markets (94%). A binary logistic regression analysis was adopted, and it was positively influenced by wealth level (p<0.01), level of education, size of the farm, slope of the farmland, extension relations, and farming experiences (p<0.05) and negatively by distance from home to farmland (p<0.05). Analysis of the net profit margin also showed that practice adopters had higher profitability rates than non-adopters (16.54% vs. 9%), and the AF reported economic benefits to smallholder farmers in the study area. The results showed that the diversified nature of smallholder farmers’ livelihoods in the area was largely supported by AF practices. Through AF practices, society has experienced diminished poverty levels together with enhanced food accessibility, and farmers have achieved better earnings and living conditions. This study proposes strategies to enhance AF as a base for enduring socioeconomic progress and supervision of natural resources.
Diversity of Spice Plants, Their Use and Function as Additive in Traditional Ethiopian Gastronomies and Culinary Recipes Pakistan Journal of Scientific and Industrial Research Series B Biological Sciences, 2025
Spatio-temporal rainfall variability and trends using a Kriging-interpolation and Innovative trend analysis approach: the case of Wolaita zone, south Ethiopia Elias Bojago Discover Sustainability, 2024 Climate change is one of the worst environmental issues, with a negative impact on most developing countries across the globe and in some regions, including Ethiopia. This study seeks to establish the temporal and spatial changes in rainfall for the period 1987–2021. In this study, ordinary statistical measures, such as the mean and coefficient of variation, precipitation concentration index (PCI), and standardized anomaly index (SAI), were applied to investigate the rainfall variation. Concerning the estimation of the spatiotemporal distribution and magnitude of changes in, non-parametric Mann-Kendall (MK) tests, Sen’s slope estimator, and innovative trend analysis (ITA) were also conducted in ArcGIS 10.8 environment and XLSTAT/R. The study showed significant fluctuations in rainfall in the Wolaita zone, with minimum mean annual rainfall in 1997 and maximum rainfall in 2003. All but the Belg season had more negative seasonal anomalies than positive ones. The annual rainfall for each of the AEZs in different parts of the country ranged from one another; it was 969.03 mm in a southeast lowland AEZ and 1648.75 mm in the northwest highland AEZ. Rainfall was not uniformly distributed throughout the year and study area; the highland AEZs received more rainfall in the Belg and Kermit seasons than in the lowland seasons. In the ordinary kriging results, the extent of variability in the CV of the mean annual rainfall for each zone was identifiable. The southwest lowland AEZ produced a CV of 24.22% with a decrease in rainfall amounts, and the northeast highland AEZ produced a CV of 31.63% of the rainfall distribution amounts. This area includes lowland and highland AEZs of the northeastern part of the study area’s rainfall, which is moderately distributed by PCI. This information is helpful when attempting to associate development and cropping systems with temporal and spatial climatic patterns with respect to rainfall for agro-climatological activities and projects or flood regulatory measures.