Geodesy and Geomatics

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Assessment of Vegetation Cover Change in Urban Green Spaces, a Case Study of Addis Ababa, Ethiopia
(Addis Ababa University, 2024-06) Melkamu Tarekegn; Andenet Ashagrie (PhD)
Urban green space (UGS) is crucial for maintaining ecological balance in rapidly urbanizing areas. This study aimed to estimate UGS and quantify oxygen production in Addis Ababa, Ethiopia, for the years 2017 and 2024 using Geographic Information System (GIS) and Remote Sensing (RS) technologies. Sentinel-2A satellite imagery was employed to analyze the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI), assessing changes in vegetation cover and built-up areas. UGS was categorized into dense vegetation, sparse vegetation, and shrub and grassland to estimate oxygen production. The results revealed a significant decline in green spaces and an expansion of built-up areas from 2017 to 2024, indicating rapid urbanization. In 2017, UGS covered 18,818.33 hectares, producing an estimated 33,872.994 tons of oxygen per year. Detailed oxygen production for 2017 included dense vegetation (2,663.39 tons/year), sparse vegetation (2,613.72 tons/year), and shrub and grassland (3,299.22 tons/year). By 2024, UGS reduced to 16,842.17 hectares, with an estimated oxygen production of 30,315.906 tons/year, including dense vegetation (2,862.129 tons/year), sparse vegetation (3,017.96 tons/year), and shrub and grassland (2,402.379 tons/year). Accuracy assessments using Google satellite imagery and ground-collected GPS data validated the classification results. These findings highlight the ecological impact of diminishing green spaces due to urbanization. This research underscores the urgent need for sustainable urban planning and the preservation of green spaces in Addis Ababa to mitigate adverse environmental effects and maintain ecological balance
Assessment of Urbanization and its Impact on Agricultural Land a case of Motta town, Ethiopia
(Addis Ababa University, 2024-06) Muhammed Belale; Andenet Ashagrie (PhD)
Urbanization poses significant challenges to the sustainability of agricultural land, which plays a crucial role in food security and local economies in rapidly urbanizing areas. The study assesses the impact of urbanization on agricultural land in Motta town using Geographic Information System (GIS) and remote sensing techniques. Land use and land cover (LULC) changes from 1992 to 2023 were analysed using Landsat satellite images from the United States Geological Survey (USGS). Both Supervised and unsupervised classification methods of classification were used to classify four land use classes namely built-up area, vegetation, bare land, and agricultural land. The study compared classification algorithms including Support Vector Machine (SVM), Maximum Likelihood Classification (MLC), and unsupervised classification based on their results and accuracy. Additionally, urbanization indices such as New Built-up Index (NBI), Urbanization intensity Index (UII), and Normalized Difference Built-up Index (NDBI) were employed to assess urbanization dynamics. Results indicate a consistent trend of agricultural land loss and built-up area increase. SVM classification shows built-up areas increasing from 323 hectares in 1992 to 607 hectares in 2023, with agricultural land decreasing from 944 hectares to 510 hectares. MLC classification similarly reveals an increase in built-up areas from 534 hectares to 757 hectares and a decrease in agricultural land from 791 hectares to 352 hectares by 2023. Unsupervised classification identifies an increase in built-up areas from 510 hectares to 910 hectares and a decrease in agricultural land from 695 hectares to 346 hectares over the studied period. Accuracy assessments confirm SVM as the most accurate method. The study concludes that urban expansion significantly diminishes agricultural land in Motta town and suggests implementing sustainable land use policies and employing satellite remote sensing for effective monitoring of urban sprawl to mitigate further agricultural land loss
Modelling The Azimuthal Dependence of The Tropospheric Delay on GPS Using Gamit/GLOBK and the Updated Vienna Mapping Function
(Addis Ababa University, 2013-04) Makabayi Brian; Addisu Hunegnaw (PhD)
In order to improve the accuracy of point coordinates obtained by the Global Positioning System (GPS), it is important to model the atmospheric delay caused by the Troposphere (Neutral atmosphere). Until now the atmosphere has been considered to be horizontally layered and azimuthally symmetric. Although for most applications this assumption is appropriate, azimuthal asymmetry may introduce significant errors in geodetic measurements where high precision is required. Azimuthal variation of 20% is quite commonly observed in humid areas. The assumption of azimuthal symmetry may cause significant errors when the local troposphere has large lateral temperature, pressure or humidity gradient variations. Recent VLBI studies indicate that azimuth asymmetry effects at 150 Elevation typically produce a Root Mean Square (rms) variation of 7mm, but at times this effect can be as much as 5times. This research investigates the effect of azimuth asymmetry on Tropospheric delay modelling using GPS. The dependence of the Tropospheric Delay on azimuth of the satellites was modelled using GAMIT/GLOBK software and the application of the updated Vienna Mapping Function (VMF1) in Tropospheric Delay modelling was analyzed. A combination of different mapping functions (Vienna Mapping Function (VMF), Niell Mapping Function (NMF) and the Global Mapping Function (GMF)) with the corresponding a priori constraints (U-file (UFL) and Global Pressure Temperature (GPT 50) were used. The combination of VMF and UFL for a different number of gradients estimated per day was done for North America, Europe and Uganda GPS data. The combinations made were evaluated using the Repeatability graphs developed using GLOBK. The results were also presented using tables and line graphs. When the gradients are modelled, the accuracy of fixing the GPS points increases. The accuracy obtained is very low when the gradient is not estimated. The accuracy of the East and North offsets increased more than the up offset in this research since there was no serious storm surge. When the gradient estimated per day is two (2) the accuracy is sufficient for fixing the East and North offsets well as for the up offset, more gradients have to be estimated especially when there is a serious storm surge. VMF1 with GPT50 fix well the East and North offsets well as VMF1 and UFL fix the up offset better. When there is a serious storm surge, gradients more than three should be estimated per day to model the Tropospheric delay well. Different MF/APRIORI combinations should be varied with the number of gradients estimated per day. Meteorological Rinex Files (RNX) should be used as a priori zenith constraints in modelling the Tropospheric delay in the future.
The Use of GIS and Remote Sensing for Land Use/ Land Cover Change Analysis: The case of Dejen Town, Ethiopia
(Addis Ababa University, 2024-06) Abebaw Habtamu; Andenet Ashagrie (PhD)
Technologies like geographic information system (GIS) and Remote Sensing (RS) are used to monitor urbanization, map it, and monitor environmental changes. Since Dejen town is expanding improperly due to growth of population and improper settlers from remote/rural areas to the city, planned development and up-to-date information is needed on the Land Use and Land Cover (LULC) and population of the town to improve the problems. The project's overall goal was to use GIS and remote sensing methods to study LULC classification and analyze trends in Dejen town between 1993 and 2023. The literature review mainly focused on the concepts and definitions of GIS, Remote Sensing, LULC, LULC Mapping, LULC Change detections, and causes for urban expansion in the study area. The Landsat imagery data were used for the research study. Those data were processed using ArcGIS 10.7, and ERDAS (Earth Resource Data Analysis System) software. Accordingly, the satellite images were used to monitor LULC changes from the years 1993-2023 for the five identified LULC classes. The Landsat images were classed into built-up and non-built-up areas to concentrate on urbanization after five distinct kinds of land use and land cover classes were found using supervised classification. The finding of the study showed that, the built up area has increased from 177ha in 1993 to 958ha in 2023, forest area increased from 0.45ha to 107ha, barren land decreased from 334ha to 162ha, agricultural land decreased from 1613ha to 868ha and a slight change occurred in open area decreased from 269ha to 298ha. Built up area has exhibited the most noticeable changes (7.39% to 40.03%) from 1993 to 2023, which come from agricultural land and barren land. The result of the study showed that the most fertile and productive part of the agricultural land has changed to urban land. The study results provide valuable information for the city administration for planning unmanaged urban growth. It also provides useful knowledge for policy relevant land administration for future development related to land use plan associated to urban expansion.
Investigating the impact of Climate Variability on Crop: In Case of Wag Himera, North and South Wello Zones in Amhara Region
(Addis Ababa University, 2024-02) Ayele Tadele; Hamere Yohannes (PhD)
Climate variability like temparture and rainfall is a common characteristic in Ethiopia and it exceedingly affects agricultureparticularly in the northenparts of the country where rainfall is relatively scarce. Hence, understanding the spatio-temporal variability of rainfall is indispensable for planning mitigation measures during high and low rainfall times. This study examined the spatio-temporal variability and trends of rainfall in the WagHimera, North and South Wello Zones in Amhara region Ethiopia. The coefficient of variation (CV) was employed to analyzerainfall variability while Sen’s slop estimator were employed to examine thetrend and magnitude of the rainfall changes, respectively. The association between rainfall, temperature and crop yield was also evaluated by the Pearson correlation coefficient (r) results. The area-averaged minimum and maximum temperature of the region is 26.2mm and 62.9 mm, and it varies from 10.46 to 39.34 mm and 24.06 to76.7 mm respectively. The average annual temperature in the region is about 44.5 mm. The region is characterized by a diverse climate, which ranges from dry and hot lowlands to wet and cold highlands. The area-averaged annual minimum and maximum rainfall of the region is 629.33°C and 855.12°C, and it varies from 313.7°C to 660.7°C and 426.7°C to899.3 °C respectively
Design and Optimization of Geodetic Network: A Case of Ethiopia
(Addis Ababa University, 2023-09) Haileslassie Muluken; Andinet Ashagre (PhD)
The optimization of a geodetic network is to enhance precision and efficiency in surveying practices. Precision involves in controlling the quality of a geodetic network. The research objective is to strategically position control points and minimize errors to improve the overall geodetic network. Finding the optimal design of geodetic network of Ethiopia is the main objective of this thesis by solving the zero order design and first order design problems by applying one of the classical methods that is the trial and error technique using a MATLAB programing language. Zero order design problem was applied to a case study network consists of 30 points and 70 designed distances with a priori deviation equal to 5mm, to determine the best points in the network to consider as control points. The results showed that P18 and P19 having the minimum ellipse of error and considered as control points. These points are therefore chosen as the control points since they have an area of 0.094 and 0.101, respectively, making them the best points. First order design problem was applied on a selected network to be analysed using the objective function, with selected range of movement of 100m to each point in each direction. This first order design problem optimization is done by the trial and error method. By taking P18 and P19 as control points the optimal design of the geodetic network with high precision is developed
Development of Cadastral Information System by using Geographic Information System in Addis Ababa City: a Case Study in Akaki Kality Sub-City, Ethiopia
(Addis Ababa University, 2024-02) Atirsaw Chale; Hamere Yohannes (PhD)
Every developmental effort and human activity depends on land. Therefore, systematic recording of land ownership is essential to ensure the rights of landowners. This paper focuses on the developing a Cadastral Information System (CIS) using Geographic Information System (GIS). Parcel corner data were collected. Sampling data was gathered through key informant interviews, and existing analog (paper-based) attribute data, high-resolution aerial imagery, and Ground Control Point (GCP) data were also utilized. The collected parcel data and aerial imagery were digitized using ArcGIS software. The digitization yielded 126 parcels and 14 roads totally of 140 parcels. Subsequently, topology rule violations were addressed: "Must have no Gaps" and "Must not have overlaps" were fixed for parcels, and "Must not have dangles" was fixed for roads. Finally, the existing analog (paper-based) attribute data was converted to digital format using MS Excel and linked (joined) to the digitized spatial data via a unique id. Parcels were initially identified by using attribute data and existing land use, resulting in 95 registered residential parcels, 18 residential undocumented parcels, 1 sports field, 3 open spaces, 9 cutoff places from parcels, and 14 roads. Secondly, identification by adjudication right showed 71 lease hold, 36 free hold, and 33 unidentified parcels. Further identification by adjudication result revealed 50 parcels with eligible and 90 ineligible parcels. Lastly, ownership type identification categorized the parcels as 21 governments, 118 private, and 1 religious place. Additionally, an attribute data query was applied to quickly access the attribute data.The CIS map of ground data was compared with the CIS map of aerial imagery to assess the accuracy discrepancies between the two. The analysis revealed that the CIS map based on ground data exhibited higher accuracy compared to the map from aerial imagery.Five participants were selected based on their work experience and academic qualifications. They responded to questions based on their perceptions of the CIS in Ethiopia. Notably, more than half of the participants rated the current level of the CIS as low. Finally, these findings verified that the applied cadastral system effectively and efficiently manage land parcels in the study area and we recommend government sector to address concerns regarding CIS not applied area.
Evaluating The Status of Land Use Land Cover Change: A Case Study of East Gojjam Zone Debre Markos Town, Ethiopia
(Addis Ababa University, 2024-02) Dawit Belay; Andenet Ashagrie (PhD)
This research was conducted to evaluate the status of urban land use land cover change. To analyze the LULC change of this study satellite images (Landsat 1986, 2003 and 2020) have been used for retrieving information, adopting image classification method. In addition accuracy analysis has been done by comparing the reference data with the classification results to evaluate the effectiveness of the image classification. The changes between the defined years was evaluated using land use Land cover maps that belongs to different years adopting cross tabulation and overlay analysis methods. The main aim of this study was to evaluate the status of urban land use land cover change in the study area. The result indicates that the main changes in the study area were the transformation of Agricultural Lands 41.62%, 32.60 changes 22.5 % and converted into Built up lands in the study area. Accordingly, around 980 ha of area of Agricultural land were transformed to build up in the last two decades.
Evaluation Of EGM2008 by Means Of GPS/Levelling In Uganda
(Addis Ababa University, 2013-04) Dianah Rose Abeho; Roger Hipkin (PhD)
The global gravity model EGM2008 is evaluated in various regions of the country to assess if it is good enough for geodetic applications. The evaluation method involves comparison of geoid heights computed from the model with those computed at irregularly distributed GPS/levelling stations. For testing the model, a total of seven levelled benchmarks available in Uganda which belong to the New Khartoum datum are used. The spatial positions of these benchmarks were determined at mm accuracy, with respect to ITRF2008. The agreement between the EGM2008 geoid and the geoid undulation derived from GPS/levelling over the seven irregularly distributed benchmark points has a standard deviation of 0.255m, with a mean of -0.859m. The datum offset may be due the choice of Wo (potential of the geoid) and Uo (potential on the surface of the ellipsoid); using GRS80 for the gravitational reference system and WGS84 for the geometrical reference system; some possibly different tidal conventions; but, by using the same method of analysis for Ethiopia and Uganda, these absolute offset effects are eliminated when comparing the two so that the computed difference [0.118 m] in datum offset for the two states does tell us something about the differences in levelling datums. The standard deviation of 26 cm suggests that sparser, irregularly-distributed and inhomogenous gravity data for Uganda was used in the development of EGM2008 not ruling out errors in levelling since there is barely any documentation pertaining the accuracy of results obtained regarding the levelling network in Uganda.
Agricultural Land Suitability Analysis Using GIS and Remote Sensing Techniques: The Case of Mecha Woreda, Amhara, Ethiopia
(Addis Ababa University, 2024-01) Abebe Negussie; Hamere Yohannes (PhD)
Agricultural land suitability study plays a vital role in determining forthcoming agricultural cropping patterns, as well as in the formulation of plans and activities related to agriculture. The assessment of land suitability is a critical endeavor that involves the evaluation of a specific area to ascertain its appropriateness and suitability for a particular use within a given locale. This process encompasses a comprehensive analysis that takes into consideration a multitude of factors, including soil characteristics, climate conditions, topographical features, and the availability of water resources. This analysis on land suitability employs a multi-criteria analytical approach in order to determine the most appropriate land for rain-fed purposes. The results of this analysis demonstrate that a considerable proportion of the region being examined exhibits a high level of suitability for agricultural activities. Approximately 20.92% of the region can be designated as significantly suitable for agricultural practices, and an additional 33.03% can be described as highly suitable. These statistics reveal that around 54% of the entire area possesses a substantial capacity for prosperous farming endeavors. According to the research's discoveries, a substantial segment of the evaluated territory is either highly suitable or very high suitable for irrigation, with a combined total of 82.66%.However, there are also notable areas that are only moderately or low suitable (13.96% combined), while a smaller proportion is not suitable (3.38%) for irrigation purposes In conclusion, the results suggest that a significant proportion of the region being examined exhibits a considerable level of suitability, ranging from high to extremely high, for agricultural purposes.
Developing a Model for Fire Emergency Response Using GIS Based Solution: A Case of Addis Ababa city, Ethiopia
(Addis Ababa University, 2024-01) Assenakew Tsegaw; Hamere Yohannes (PhD)
Emergency services are those that respond to various emergency situations in order to guarantee public safety. For cities, deciding where to put emergency stations is essential. When choosing the best incident location, the most crucial factors to consider are response time reduction, coverage maximization, and overall cost reduction. It is necessary to use Geographic Information Systems (GIS) in order to study on maps. The focus of this work is on developing a model for fire emergency response model based on GIS station; to deliver the fire emergency service in Addis Ababa city, locate the fire incident and the existing fire response station to arrive at the place where the incident occurs. This GIS-based approach followed identified elements such as fire response station, Addis Ababa city parcel, after identified elements then Geo coding existing fire response station and Addis Ababa city resident or parcel and to develop the database for this fire emergency response. To develop the model for the study area, Geo code at visual study code for x y coordinate of fire station and residential with attribute parcel ID. Finally the developed fire emergency response model and database integrate with web GIS. The overlay result indicates that the fire emergency response model and fire emergency database model access to locate a fire incident and timely intervention play a crucial role in managing urban fire, the Addis Ababa city parcel and existing fire response station were based on the inputs, parcel number or ID. The present study suggests GIS based fire emergency response model which helps to located fire incident with the corresponding fire response station location for the city as well as provides fire emergency response Database for the study area.
Forest Fire Risk Estimation and Modeling Using GIS and Remote Sensing Techniques: The Case Of Asebot Monastery, Oromia, Ethiopia
(Addis Ababa University, 2024-02) Birhanu Melkam; Hamere Yohannes (PhD)
Forest fires are a major threat to the environment, human health, and property. The Asebot forest area is particularly vulnerable to forest fires due to its unique geographical and environmental characteristics. To mitigate the risk of forest fires in this region, it is essential to identify the influential factors of forest fire risks and estimate post-fire degradation. This was achieved by using post-fire satellite images of 2021 and modeling the location of potential fire susceptibility in the Asebot forest area. Forest fires are a major threat to ecosystems and human populations, and early detection and monitoring are crucial for effective fire management. In this study, the weighted overlay analysis technique is being used for multi-criteria decision-making. The goal is to estimate the post-fire and model forest fire risk susceptibility. To perform this analysis, each data set is converted to raster format and reclassified to a common scale using ArcGIS spatial analysis. Pair-wise comparisons of factor layers are conducted to determine their relative importance or weight. Remote sensing techniques have become increasingly important for detecting and monitoring forest fires, as they offer a cost-effective and efficient way to gather data over large areas. In this study, the two commonly used remote sensing techniques are employed to estimate fire severity: Normalized Difference Vegetation Index (NDVI) and Burn Severity Index (NBR). The study found that approximately 38.419% of the area had very high and high burn severity, as classified by the Normalized Burn Ratio (NBR) index whereas, burn severity concerning NDVI, which is very high and high burn severity covered 52.277% of the study area. The findings of the study indicate that the area under consideration has varying levels of forest fire risk. The model produced in this study reveals that a substantial portion of the area is classified as having a high to very high risk of forest fires, with over 22% falling into these categories
Landslide Hazard Zonation by Using Geospatial Based Multi-Criteria Decision Analysis Techniques: The Case of Worra Jarso District, Central Ethiopia
(Addis Ababa University, 2024-02) Adisu Mersha; Hamere Yohannes (PhD)
The present study area is located in the Northern Shewa Zone of the Oromia Region, Worra Jarso District, Central Ethiopia, which is far 186km from Addis Ababa. Landslide is among mega geo-hazard that pose a significant damage to civil infrastructure, property, and loss of life. It can be induced by natural phenomena like heavy rainfall, earthquakes and volcanoes. As well, by human action such as deep excavation for mining, road network, building, urbanization, deforestation, unscientific slope cutting and improper agricultural practice. Therefore, the main aim of this study was to delineate landslide hazard-zones using Geospatial based Multi-Criteria Decision Analysis methods. To achieve the stated objective, the eight causative factors were identified namely; elevation, slope, aspect, curvature, soil type, lithology, land use/land cover and drainage density. These factors were identified and the weights were assigned based on the Expert opinion, literature review and nature of the study area. Accordingly, the assigned weights were computed using pair wise comparison matrix of Analytic Hierarchy Process (AHP) method. The spatial distribution of landslide was mainly influenced by slope angle >450, limestone lithological unit, high drainage density, shallowness of leptosoil, expansion of agricultural land on steep slope, falling of elevation class in between 1575m-2100m, concave slope curvature and northwest facing of slope aspect. Later, the landslide hazard zone map was produced by using Analytic Hierarchy Process and Weighted Linear Combination in Geographic Information System (GIS) weighted overlay analysis environment. The produced landslide Hazard Zone map shows that 0.001% (0.014km2)area fall within low hazard zone, 46.66% (555.25km2) of the area fall within moderate hazard zone, 50.02% (595.13km2) and 3.32% (39.48km2) of the area falls into high hazard and very high hazard zones respectively. Moreover, validation of landslide hazard zone map with 49 past landslide inventory data reveals that 85.7% of the known landslide events were falls in very high hazard and high hazard zone. Thus, the landslide hazard map produced by Geospatial based Multi-Criteria Decision Analysis Approaches with careful identified factors proved to be valuable tool for providing fundamental information about hazard assessment, land use planning, infrastructure development and disaster preparedness of the area.
Determining Ground Surface Deformation at Erta Ale Volcano and Assessing Lava Lake Reservoir Northern Afar, Ethiopia
(Addis Ababa University, 2024-02) Tilaye Sewnet; Andenet Ashgrie (PhD)
This research endeavors to ground surface deformation analysis using Persistent scatter interferometry at Erta Ale volcano and assessing its Lava Lake reservoirs in northern Afar Ethiopia spanning the period from 2017 to 2022, using Sentinel-1A data. Erta Ale is an active volcano located tectonically at the triple divergent junction of the Arabian, Nubian, and Somalian divergent plates. Geological setting of Erta Ale is highly extended and thin crust layer which is additional factor to Era Ale volvcanic activity. Studying the ground deformation of actively erupted volcanoes at the local level is one way of monitoring the continental refits. In this study, 26 sentinel-1A descending single look complex (SLC) SAR data are the main input for the study. SAR data covers large areas that enables to generate densified Ground control points to assess surface displacement at active volcano area. The latest InSAR processing method, PS-InSAR, is used to process SAR data. The commercial software SARPROZ used to process and analyze data in PS-InSAR techniques. Atmospheric phase error are removed by the amplitude-phase scattering (APS) method in this method. In the subsidence area, maximum horizontal and vertical displacement are~143±1.2674 mm and~91.89mm, respectively. Areas including Bora Ale and areas in the NW of the north pits are continuously subsiding. In the Northeast, the deforming rate of subsidence is 13.76mm per year, resulting in ~12mm of ground contraction and vertical deflation ~40m. Between Ali Bagu and Boral areas, there are some boreholes and temporary cracking that cause depression of the earth’s surface. uplifting area is ~60.23 ±1.2674 and ~93.04 mm, respectively, in the SW direction, resulting in horizontal extension of PSC ~12cm. North pit Lava Lake magma has decreased in area from the February2017 to December 2022 is ~0.061723km2 to ~0.036983km2.
Spatiotemporal Analysis of Land Use/Land Cover Change and Urban Sprawl using GIS and Remote Sensing: The Case of Bahir Dar City, Ethiopia
(Addis Ababa University, 2024-01) Habtamu Hulgizie; Hamere Yohannes(PhD)
Spatiotemporal analysis is a method used in Geographic Information Systems (GIS) and Remote Sensing to analyze changes in land use and land cover over specific time. This study was conducted to produce maps of the spatiotemporal changes over the study area from 2002 to 2022, quantify gain and losses of land use/land cover (LULC) classes, examine land use transitions, assess spatial trends of changes, and analyze the extent and patterns of urban sprawl over the study area. The LULC classes include Bare Land, Crop Land, Vegetation Area, Water Body, and Buildup Area. According to the analysis, the area of built-up land was increased time to time from 2002 to 2022, more than doubling in size, which increased from 1253.951 ha to 5519.19 ha. This indicates substantial urbanization and infrastructure development during the study period. With decrease in cropland and bare land but significant growth in built-up areas. To some extent, there was an increment of Vegetation area but water bodies remained relatively the amount of coverage area decrease in the first three consecutive period. Overall, the study highlights significant shifts in land use land cover over the 20-year timeframe. Moreover, the urban expansion intensity index analysis reveals fluctuations in the rate of urban expansion over the years, with periods of limited growth followed by accelerated expansion and then a slowdown. The urban expansion rates for the periods 2002-2007, 2002-2012, 2002-2017, and 2002-2022 were 4.204%, 10.763%, 7.332%, and 7.632%, respectively, these rates indicate fluctuations in urban growth within the region over the years.
GIS-Based Urban Land Property Valuation for Taxation Purpose: The Case of Akaki Kality sub city, Addis Ababa, Ethiopia
(Addis Ababa University, 2024-01) Tadilo Alemu; Hamere Yohannes (PhD)
Land valuation is the process of assessing the characteristics of a given piece of land grounded on experience and judgment, for different purposes like for transaction, mortgage, taxation, insurance, and so on. In this case the study concentrated on land property valuation for taxation purpose. It is considered that an owner should be able to pay taxes to the government in connection with his ownership, in terms of the government services he receives and the infrastructure provided to him. That is, a property owner who lives in an area with better infrastructure and government services will be taxed higher or vice versa. In the current situation, the land ownership registration and information agency of Addis Ababa city administration and land development management institutions in connection with land property valuation, especially the land property valuation service used for tax rate purposes follows the calculation method based on income capitalization and based on the current land property transaction value which, might not indicate whether the land property right holder is situated on well-developed infrastructures or not. That makes the system unfair, which does not follow the multiple requirements or parameters that affect a land property value. Therefore, this study will address and show the direction of the land and land-related valuation system especially for laving taxes, observed in the city administration specifically Akaki Kality sub city, for the study using multi-faceted criteria’s to develop land property valuation model and parcel data were integrated using ArcGIS to developed property valuation attribute table. The result indicated that the majority (35.16% and 28.88% respectively) of the total land area falls under the categories of very high land value and high land value. This indicated that these areas have high potential for development, so that should rate high tax. Whereas 15.37% of the study area are moderately offers some potential for development. The low value (12%) has limited development opportunities or undesirable locations, following to this property owner on this category should pay lower rate of tax. The remaining 8.59% of the area has the lowest development opportunity and infrastructures. In conclusion, the significant proportion of land falling under the very high and high categories have nice development opportunities for various purposes such as residential, commercial, or industrial projects. Developers and investors can focus their efforts on acquiring and utilizing these lands to capitalize on the high development opportunities associated with these areas. Additionally, the distribution of land across different categories provides valuable understanding for urban planners and policymakers relating to taxation. Following to this study concerned parties may elongate it throughout the city and gives coefficients to each categories’ of land values. This knowledge also allows decision-makers to prioritize areas with higher potential for growth and allocate resources accordingly.
Spatiotemporal Modeling of Urban Expansion: In a case of Robe Towen Using Remote sensing and GIS Techniques
(Addis Ababa University, 2023-07) Olana Adere; Asnake Mekuriaw (PhD)
Urbanization is the most powerful and visible force that has fundamental changes Land Use Land Cover around globe. This study was conducted in Robe town to model spatio-temporal of expansion during 2006–2021. SPOT image for 2006 and 2016 as well as Sentinel 2A for image were used for this study. Three different land-cover maps produced at different intervals between 2006 and 2021 were used to evaluate and analyze urban expansion visually and quantitatively. The satellite images were classified and land-use/land-cover maps were produced using Object Based Image Classification using KNN classification method using Envi 5.3 and predict Expansion of Robe Town using CA-Markov model. The classification process was checked by overall accuracy and Kappa statistic accuracy assessments from confusion metrics. Results show acceptable agreement between the classified maps and reference data with overall accuracy value 91% for 2006, 88% for2016 and 93% for 2021. Kappa accuracy value 0.89, 0.85 and 0.91 for classified satellite image of 2006, 2016 and 2021 respectively. Post classification change detection analysis and selected spatial metric indices calculation were made to detect, assess pattern of urban expansion in the study area. Change detection analysis indicated that Robe town is growing rapidly with an average growth rate of 7.8% year during2006–2021. The builtup area was 854 hectare, 1067hectare and 1740 hectare, respectively in 2006, 2016 and 2021, with annual growth rates of 2% and 7.8% in the two study phases respectively during the periods 2006-2016 and 2016-2021. From spatial metrics analysis, largest patch index of built-up area was 7%, 10% and 15% for the years 2006, 2016 and 2021. The increase in the number of largest patch index all through the study periods shows the rapid urban growth process in the study area.CA-Markov model used for modeling and validating kappa statistic is moderate and acceptable to predict for future (2050).Therefore, it is time for policy makers, city managers and urban planners to plan and cope up with the pace of Robe town urban expansion depending on with proper implementation.
Land Use Land Cover Prediction Using Cellular Automata-Markov Model in Kulfo River Watershed
(Addis Ababa University, 2023-05) Seble Gezahegn; Degefie Tibebe (PhD)
Land use land cover change is created principally by human activities, activities manipulating the Earth’s surface for some purpose such as agricultural, industrial and residential etc. Mapping and predicting of LULC is important to identify and evaluate the magnitude and the change within the watershed to ensure best future planning and management. This study was mainly focusing on predicting land use cover change in kulfo river watershed through remote sensing, geographic information system integrated with IDRISI selva software and CA-Markov chain model. Cellular automata coupling with Markova model was used to predicting and modeling land use cover change for the year 2036 and 2051. Land use map of 2000, 2011 and 2021 were generated from Landsat satellite images. Analyzing the pixel based image classification method. The land use cover maps were computed using Maximum Likelihood algorithm of supervised classification technique, in ENVI 5.3 and GIS 10.8. Predicted LULC is developed using IDRISI Selva Software, and calibrated and validated using classified 2021 LULC maps. Hence the quality and location coefficient were calculated based on compassion of the predicted LULC for 2021 with the actual 2021 for first scenarios. The outcome demonstrate that bare land that was 14.5 % in 2021 decrease to 13.3% and change to 12.5% in 2051, forest land will decline from 18.3 % in 2021 to 17.7% in 2036 and also 18.5 % in 2051, water body that was 0.9% in 2021 to 0.6% in 2031 and change to 0.4 % in 2051.In general, the forecast result shows that except for built up area and cultivated land all land use type decreased per year respectively. Hence the observed LULC changes were generated by the increase of population, this lead to the demand for cultivated land, rural settlement and the extraction of forest for fuel and other construction materials.
Positional Accuracy Validation of Base Map and Investigating its Impact on Road Projects: A Case of Addis Ababa City, Ethiopia
(Addis Ababa University, 2023-06) Solomon Woldeyesus; Tulu Besha (PhD)
Positional accuracy is a topic that of renewed interest and concerns not only the distance between the geographic object and its actual or real location on the earth surface but also the accuracy with which map features are located. Collecting the highest quality independent ground-based data is a key factor in validating the useful location accuracy of digital geospatial data. This information simplifies geographic analysis and promotes better judgment. In this research the accuracy of the horizontal position of an orthophoto/line map had been investigated. The global positioning system and total station survey had been employed to access the accuracy of the horizontal coordinate of the line map. The horizontal coordinates of the terrestrial position of the points are observed using Sokkia Atlas GR5+ Differential Global Positioning System (GPS) device and the row data are post-processed using various processing tools such as Leica Geo-Office and Topcon Tools v.8.2.3 reference with to local GNSS reference stations. In this study, we evaluated the 2D positional accuracy of the line map by matching its horizontal coordinates with the associated ground control point observed as in-suit data. Comparing the digital line map coordinates to the corresponding in-situ ground control points, RMSE between the digital line map and the GPS/total station position of the twenty-five reference points is 0.813 m in x and 0.903m in y respectively. Furthermore, in comparison to GNSS/Total Station data acquired through LGO processing, the digital line map exhibited a horizontal precision of 2.103 m at a 95% confidence interval. This inaccuracy can potentially impact the drainage line or buildings that are constructed parallel to the road center line. Specifically, for the Saris site, it results in a 1.398 m deviation from the road design center line. This discrepancy has had a discernible effect on ground surveys and the design of road projects in Addis Ababa city, necessitating repeated right-of-way surveys and redesign efforts. Consequently, the precision of digital line maps falls short of the national error budget requirement (30cm) for Standard Mapping tasks under all circumstances. However, it may be suitable for imagining and small demanding tasks. In its current status, it is applicable to projects like master plans and general economic development plans.
GEOID QUASI-GEOID Separation Computation Using the Grace And GOCE Global Geopotential Model in Semien Mountains, Ethiopia
(Addis Ababa University, 2023-08) Tadege Getie; Tulu Basha (PhD)
Different reference systems are used to determine height,which are quasi-geoids and geoids. The definition of the geoid and telluroid (or, more generally, the quasi-geoid) is connected to these height systems. The optimal technique for computing orthometric heights has been a topic of discussion for more than a century. In mountainous regions, it is challenging to determine geoid and quasi-geoid features using GPS technology. The highest point of a mountain in Ethiopia's highlands is known as Ras Dashen. To tackle boundary issues for mountainous places such as the Ethiopian Semein plateau, a satellite data model is required to ascertain the distinction between geoid and quasi-geoid. We have written this research article to support this investigation. For individuals working in this field, determining the distance between the two references is quite helpful. Calculating the distance between them is important to transform what we receive from one to another.Although there are other ways to determine this gap, we employed satellite earth models created using satellite data for this work. There are three different kinds of models: models created only using GRACE satellite data, models created only using GOCE satellite data, and models created using both GRACE and GOCE data. Our search for the model reference height type was based on E Topo. As a result, Sjoberg's exact formula was used to calculate it in this study using the geoid-quasi-geoid separation model. Using the ETOPO 1 and TC programs from the GRAVSOFT package, the gravity anomaly in the case area was determined. This study investigated variations in the results of the order factor in the application of gravity in addition to the type of data. Models from the International Center for Global Earth Models, including SGG-UGM-2, IGGT_R1C, GO_CONS_GCF_2_TIM_R6, and ITSG-Grace2018, were used in this determination of Geoid-Qusigeoid separation.With the help of these models, we searched for various gravitational field functions, but primarily we searched for the separation between the geoid and quasi-geoid separation in all four models, and we discovered that the minimum and maximum results are, respectively, 0.388, 0.356, 0.365, 0.360 and 4.730,3.798,3.755,and 3.760 meter.

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