Background: The Ethiopian highlands have experienced intense levels of land use dynamics and forest cover transformations over the past few decades. Multiple socioeconomic , demographic and bio-physical factors have driven such transformations. Nevertheless, recent expansion of urban settlements and infrastructural development could have accelerated the rate at which land cover transformations preceded but little is known about their impacts on land cover transformations in the vicinity of Addis Ababa, Ethiopia. This study, therefore, focuses on detecting long term dynamics of land use/land cover (LULC) change since the 1950s and current state of forest susceptibility to degradation in Northeastern Addis Ababa, Ethiopia. In this study Panchromatic Aerial photographs (1957), MSS (1975), TM (1995) and Sentinel-2 (2017) images were used to generate LULC types. We employed object-based classification techniques to generate LULC types for 1957 aerial photographs and maximum likelihood algorithm for images of 1975, 1995 and 2017. We also generated forest degradation susceptibility map for the study area by employing a multi-criteria approach on the ArcGIS analysis platform. Results: Over the course of 60 years (1957-2017) the extent and direction of LULC have become more dynamic. Agricultural land and forest land showed a comparably equal extent of net change (+ 36.7% and − 37.8%, respectively) but to opposite directions. Forest lost 25.1% and 18.7% of its cover to barren land and agricultural land, respectively. The net change for forest was negative except for the period 1975-1995, with varying rates of deforestation during the four distinct study periods. However, a heightened level of deforestation occurred after the mid-1990s due to rapid urban growth and a change in government economic policy. A 6.2% net change of urban/settlement served as a catalyst for LULC transformations in the last two decades. Our findings also revealed that 97.2% of forests were located at a radius of 1 km distance from urban centers and settlements whereas 92% of them were accessible by road networks of a km radius. Similarly, 71% of forests suffer from edge effects while biophysical factors such as streams as vectors of disturbance and slopes expose about 35% of forests to degradation. Conclusion: Over the last six decades the study area has shown an unprecedented level of LULC change. The main drivers of change were the combination of bio-physical processes especially drought cycles, demographic dynamics (population growth, density and internal migration), urbanization and successive government development policies. The massive conversion of forests to agricultural land and barren land in the study area will have far reaching impact on biodiversity and ecosystem services, land degradation and a change in local hydrological regime.
Rapid conversion of conserved land and cropland to non-agricultural purposes is threatening the ecological areas and dominant agricultural activities that are the main sources of livelihood in urban fringe areas of Addis Ababa City. The combinations of government policy, socioeconomic, demographic dynamics, and biophysical triggers have driven such transformation. However, the recent fast urban expansion and infrastructural development could have accelerated the severity and rate at which urban growth impacts the ecosystem and fertile agricultural land. Yet, little attention is given about their impacts on forest and farming communities in the western fringe areas of Addis Ababa during the recent past. This study, therefore, aimed at quantifying and analyzing the trends of the urban growth and its impacts on flora and agricultural land in Sebeta-Awas town using an integrated GIS tool, remote sensing technique, and Shannon entropy method. Landsat TM of 1986, ETM+ of 2002, and OLI of 2019 were used to produce land use/land cover (LULC) classes. Object-based classification technique was carried out to generate the LULC and to measure the changes in the urban land-use class within the satellite town in the year 1986, 2002, and 2019. Shannon entropy method was applied to model study area’s urban sprawl, growth trend, and spatial change. Over the past three decades (1986–2019), Sebeta-Awas town has experienced severe urban sprawl following lack of proper development control and management. The annual urban growth rates of 1.2, 5.5, and ~15% for the periods of 1986, 2002, and 2019, respectively were obtained mainly at the expenses of agricultural land (25.48%) and forest land (16.6%), catalyzed urban sprawl which finally led to serious deforestation and reduction in rural farmland. The findings indicate that the average of entropy index increased from 0.02 in the year 1986 to 0.996 in the year 2019, indicating more dispersed urban growth to the outskirts, and spatially indicating anticlockwise shifting. In this regard, more than 90.2% of forest loss due to agricultural encroachment, built-up area expansion, and construction was widely observed in Sebeta and Alem Gena areas, of course, Northeast zone in this study. It is concluded that deforestation and continual evacuation of farming communities in the urban fringe areas due to rapid urban expansion in the name of investment and infrastructural development is expected to be worsened in the near future unless strong policy revision and management actions are undertaken.
The main grassland plain of Nech Sar National Park (NSNP) is a federally managed protected area in Ethiopia designated to protect endemic and endangered species. However, like other national parks in Ethiopia, the park has experienced significant land cover change over the past few decades. Indeed, the livelihoods of local populations in such developing countries are entirely dependent upon natural resources and, as a result, both direct and indirect anthropogenic pressures have been placed on natural parks. While previous research has looked at land cover change in the region, these studies have not been spatially explicit and, as a result, knowledge gaps in identifying systematic transitions continue to exist. This study seeks to quantify the spatial extent and land cover change trends in NSNP, identify the strong signal transitions, and identify and quantify the location of determinants of change. To this end, the author classifies panchromatic aerial photographs in 1986, multispectral SPOT imagery in 2005, and Sentinel imagery in 2019. The spatial extent and trends of land cover change analysis between these time periods were conducted. The strong signal transitions were systematically identified and quantified. Then, the basic driving forces of the change were identified. The locations of these transitions were also identified and quantified using the spatially explicit statistical model. The analysis revealed that over the past three decades (1986-2019), nearly 52% of the study area experienced clear landscape change, out of which the net change and swap change attributed to 39% and 13%, respectively. The conversion of woody vegetation to grassland (~5%), subsequently grassland-to-open-overgrazed land (28.26%), and restoration of woody vegetation (0.76%) and grassland (0.72%) from riverine forest and open-overgrazed land, respectively, were found to be the fully systematic transitions whereas the rest transitions were recorded either partly systematic or random transitions. The location of these most systematic land cover transitions identified through the spatially explicit statistical modeling showed drivers due to biophysical conditions, accessibility, and urban/market expansions, coupled with successive government policies for biodiversity management, geo-politics, demographic, and socioeconomic factors. These findings provide important insights into biodiversity loss, land degradation, and ecosystem disruption. Therefore, the model for predicted probability generally suggests a 0.75 km and 0.72 km buffers which are likely to protect forest and grassland from conversion to grassland and open-overgrazed land, respectively.
The northeastern part of Ethiopia, particularly Raya area is a pilgrimage site famed for its antique civilization, archaeological sites, and rural landscapes. Despite existing ecotourism potentials, the area has not been utilized for tourism for millennia. While previous work looked at the availability of natural resources, it did not identify and prioritize the resources, so knowledge gaps continue to exist in prioritization of potential ecotourism sites. This study attempted to identify various ecotourism indicators, evaluate and produce maps of suitable ecotourism sites, and prioritize optimum protected areas that are best suited for sustainable ecotourism development of Raya areas. For this analysis, 13 spatial indicators from physical, environmental, archaeological, socio-cultural, and socioeconomic sectors were considered. Analytic Hierarchical Process (AHP) was used to calculate the details of the spatial indicators and class weights. The suitability maps were classified into four classes as Highly Suitable (S1), Moderately Suitable (S2), Marginally Suitable (N1), and Not Suitable (N2). The results revealed 114.37 Km 2 (10.33%), 13.36 Km 2 (1.91%), and 10.39 Km 2 (1.62%) fall under the highly suitable class in Blocks B, A and C, respectively. AHP weights with ultimate criterion and field observations also ranked lake Ashenge, Hugumburda, and Gratkhassu national forest priority areas as 1st, 2nd, and 3rd optimal zones, respectively. The outcomes of this study are crucial for conservation pioneer work in ecological development, and should be used as an ideal blueprint by ecotourism planners and decision-makers for sustainable ecotourism development strategies.
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