Institute of Geo-Information and Earth Observation

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    Evaluation of land use/cover change and implication for land management of mountainous landscape in Laygaint, North Ethiopia
    (Mekelle University, 2024-01-25) Walelign Zewdie
    Land Use Land Cover Change (LULCC) is one of the major human induced global changes. Information on LULCC, the forces and processes behind such changes are essential for proper understanding of how land was being used in the past, what type of changes have occurred and is expected in the future. This study was carried out to examine land use land cover changes and driving forces behind the changes in Laygaint district, north Ethiopia. The main objective of this thesis is to evaluate the land use/cover with its implication of land management and predictable in the future on mountain landscape. It was conducted using satellite image of Landsat5 TM 1990 and 2000, Landsat7 ETM+ 2010 and Landsat8 OIL/TIROS 2023. In addition, field observations, Key informant interview (KII) and Focus Group Discussion (FGD) were also conducted. ArcGIS 10.5 and QGIS (MOLUSCE 3.0.1), soft wares were used for satellite image processing, map preparation and LULCC prediction respectively. The main finding of this study revealed an expansion of agriculture/crop land as well as bare land and reduction of grass land and dense forest over the last 33 years between 1990 and 2023. Crop land/agriculture and bare land increased by 23700ha and 19800ha, with a corresponding 24000ha and 19600ha decline in the area of grass land and dense forest respectively. If the current rate of LULCC continues, bare land is predicted by 23.9% in 2033. In contrast agriculture/crop land, dense forest and grass land are predicted to shrink 60.81%, 0.61% and 2.88% respectively. LULCC in Laygaint is a result of several proximate and underlying drivers. The major proximate driving forces of LULCC in the study area are agricultural expansion, illegal logging and fuel wood extraction, overgrazing and expansion of illegal and unplanned settlements. Demographic, economic, technological, institution and policy, socio-cultural and biophysical factors constitute the major underlying drivers of LULCC in the study area. Hence, the right policy packages are required to control the expansion of agriculture and bare land at the shrink of grass land and dense forest resources in the study area.
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    INTEGRATED APPLICATION OF GIS AND HEDONIC PRICE MODELING (HPM) FOR PROPERTY VALUATION OF BUILT-UP AREAS IN MEKELLE CITY, TIGRAY, ETHIOPIA
    (Mekelle University, 2025-03-25) SIMONE HAILESLASSIE
    Property valuation plays a crucial role in asset building, environmental resource mobility, and for creation of digital society in the daily life. It significantly contributes to property administration, social equity, and economic stability, while impacts socio-economic, political, cultural, and environmental sustainability. Upon that, accurate and fair property valuation is essential. However, unlike developed countries, property valuation has under numerous challenges in our country. The objective of this study was to identify high property value variations in similar properties through analyzing of existing valuation system. Using a descriptive research design with mixed research data approaches, the study examines factors influenced property values using integrated modeling and mapping for validation and triangulation of the data in social survey. Simple random sampling has used for resident perceptions, while purposive sampling used for expert and official informants through interviews, questionnaires, and group discussions. Additionally, direct field observations conducted. The findings revealed that 99% of respondents are aware of property valuation, with 82% of residents, 33% brokers, and 84% of sectorial respondents involved in property transactions. Residents primarily used transaction 80% for residential houses and 61% for taxation and 20% for remaining listed valuation purposes. While 76% of sector respondents apply scientific valuation methods, only 24% (23% MHSC, 60% Banks, and 13% MMCA & RLRAIB) do so regularly. About 61%, cost approach is predominantly used, 13% income and 27% mixed approaches. For the approved building property nature appraised using 80% of cost approach, shows the valuation practices has not well built. Even through, the value variation in similar properties feedback looks like this 97% HMSC 89% brokers, 56% residents, 52% MMCA & RLRAIB and 26% banks. However, multiple cross validation of overall target group of respondents‟ averagely proven via FGD about 92% have well understood and agreed with the value variation. Economic impacts of value variations range from 36.5% in 1,000,000s to 27% in less than 1,000s, highlighting significant discrepancies. 85% of study results show high valuation and 76% have of these have from 10,000s‟to 1000, 000s‟ price difference roughly. Key informants indicated that the residents done with discrepancies of varied official and actual sales notification. Banks used manuals to prioritizing risk security first, while MMCA & RLRAIB focus on the regulatory system of valuation in higher hierarchy level. Residents‟ dissatisfaction stems from unfairness and lack of transparency. The aim of this study is to address these issues with located the building value using GIS and to model the characteristics property of attribute using HPM to conduct the accurate value with appropriate valuation practices. This have significant role to advance the existed system of property valuation in standardized and comprehensive approach.
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    GIS-Based Beekeeping Site Suitability Assessment Using Multi Criteria Decision Analysis in Atsbi-Wemberta District, Ethiopia
    (Mekelle University, 2025-03-25) Hagos Heshe Weldetatiyos
    Beekeeping offers multifaceted benefits that extend beyond economic gains, significantly contributing to pollination services, biodiversity conservation, and maintaining ecosystem balance, and socio economic development. In the Atsbi-Wemberta district, Ethiopia, not all Tabiyas are suitable for beekeeping. Thus, identifying suitable areas for beekeeping is crucial to maximize productivity. Integrating Geographic Information System (GIS) and Multicriteria Decision Analysis (MCDA) offers effective solutions for this decision-making process. Seven key factors influencing beekeeping including Temperature, Rainfall, Land Cover, Distance to River, Distance to Road, Elevation, and Aspect were analyzed. Data was collected from various primary and secondary sources. The weighting was determined using the Analytical Hierarchy Process (AHP), achieving a consistency ratio of 0.040. The study identified fifty-seven bee forage plant species, categorized as 42.1% herbs, 26.3% shrubs, and 31.6% trees. Significant honey sources included Becium grandiflorum, Olea europaea, and Aloe berhana. Three honey-harvesting periods were noted: late October to early December, with additional harvests in April and May. The areas were classified into More Suitable, Suitable, Less Suitable, and Not-Suitable zones, with about 84251.5 hectare (74%) of the land identified as potential for beekeeping from the total area of 113774.88 hectare. Specifically, More Suitable Areas 7318.98 hectare (6.43%), Suitable Areas 60829.36 hectare (53.46%), Less Suitable Areas 16103.15 hectare (14.15%), and not suitable 29523.39 hectare (25.96%) were determined. Validation was conducted using randomly selected 100 existing apiary sites and showed a 78% intersection rate, confirming the model's effectiveness. The socio-economic analysis highlighted challenges such as pests and pesticide use, while opportunities included natural vegetation and established honeybee colonies. This research provides valuable insights fand as a guidance for government agencies, small scale beekeepers, cooperatives, and investors in establishing commercial beekeeping operations. The study recommends Honey production led by agricultural practice should be exercised and conserving existing vegetation to sustain and enhance the area's beekeeping potential.
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    Geospatial Based Suitability Analysis of Urban Green Area Development in Tepi Town South West, Ethiopia Using GIs and RS Techniques
    (Mekelle University, 2025-01-25) Esmael Mohammed
    The main target of this research was to identify suitable locations for events related to urban green area developments in Tepi town, South, Ethiopia using GIs and RS techniques between 2003 and 2023. In order to achieve these, satellite data of Landsat7 for 2003, landsat8 for 2013and landsat9 for 2023 have been obtained and preprocessed using ERDAS Imagine. The Maximum Likelihood Algorithm of Supervised Classification has been used to generate LULC maps. Post classification comparison change detection was employed to determine the gains and losses in LULC between two classified maps. Additionally, socio-economic data assessment was performed by using selected individual’s interview and focused group discussion to identify the driving forces of LULC change in the study area. The study area covers a total area of 2223.23ha. Land suitability analysis has growing importance in identifying suitable land resource for some specific uses. There is a growing demand for land for residential use, commercial, infrastructures and industrial purposes. Improper urban development can bring adverse impact on urban agriculture, urban green area and environmental condition. Due to the dynamic urban growth trends, city administrators and planners are faced with difficulties in amenities like green area. The rate of LULC change with respect to urban green area for the period between 2003 and 2023 was assessed using GIs and RS techniques. The suitability analysis was done using GIS-based multi-criteria analysis steps. The result reveals that since 2003 the green areas, represented by plantations, grassland and cultivated from this plantations and grasslands have been mostly converted into other land uses classes at annual rates of 3.5%, 4.8%, respectively. This has resulted in the reductions of plantations and grassland by 50.7%, 61.7% of the study area total area coverage respectively. In contrary, built-up and cultivated land have been highly expanded with an annual rate of 3.0% and 7.9% and with a total area increase of 80.9% and 38.6% respectively. Based up on GIs based multi-criteria analysis, 1.2 % and 70.4 % of the study area was identified as highly suitable and moderately suitable for green area development respectively. Finally, the sites suitable for certain uses, such as green area development were identified and planned using land suitability studies.
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    Department Of Geo-Informatics