Genemo Berisa & K.V. Surya ( 4 th Esri Eastern Africa Education - PowerPoint PPT Presentation

GIS Based Urban Sprawl Susceptibility Analysis: The Case of Shashamane T own, Oromia Region Genemo Berisa & K.V. Surya ( 4 th Esri Eastern Africa Education GIS User Conference) (23 - 24 September, 2016 | UNECA, Africa Hall ) Addis Ababa, Ethiopia

Presentation Outlines  Introduction  Urban Sprawl & GIS Application  Study Approaches  Results & Discussion  Conclusion & Ways Forward

Introduction  Urban areas become the most dynamic places in the history of the Earth surfaces change.  Urban areas tend to grow horizontally outward to accommodate the ever growing population pressure on the limited land resources.  Despite their regional economic importance, urban growth has a considerable impact on the surrounding ecosystem (Yuan et al ., 2005)  Urban development in Ethiopia has been boosting with a remarkable rate as the result of increased rural-urban migration and population growth.

Introduction …  Urban sprawl has become very common in Ethiopia where towns are expanding well out of order, to marginal areas without consent of both city and rural administrators.  Sprawl is the process of outwards expansion of town to accommodate the ever growing population pressure.  Urban sprawl is a complex phenomenon which has environmental and social impacts (Barnes et al. 2001) manifested in the:  loss of productive agricultural land and open green spaces,  depletion of surface water bodies and ground water  water and air pollutions due to increased solid waste and noise.

Urban Sprawl and GIS Application  The following are a few of operational GIS applications for Sprawl study but not restricted to:  Make depiction of spatial extent of urban sprawl and the sprawling tendencies of an area effectively and efficiently.  Detect, map and analyze the physical features and patterns of sprawling on a landscape ( Barnes, 2001 ).  Help providing information about sprawl rate and natural resources vulnerable to sprawling on the exurban environment.  This information would further help authorities of both urban and rural areas to take informed decision around urban planning and growth monitoring.

Study Approaches Study Area  Located at 250 km to the southeast of Addis,  Spread over 12, 868 ha territory with 102, 062 population (CSA, 2007).  Average elevation ranges from 1826-2107 meters  Geographic location 7 o 8 ′ 50 ″ N to 7 o 18 ′ 17 ″ N latitude and 38 o 32 ′ 43 ″ E to 38 o 40 ′ 58 ″ E longitude. o Mean annual rainfall 1200 mm with average max and min temperature of 24.3 °C & 7.5 °C respectively.

Study Approaches…, Methods  Five input parameters were integrated to develop urban sprawl susceptibility index using GIS techniques.  The parameters were derived from three urban sprawl criteria: Criteria Parameters Physical/Natural T opographical condition (slope) Distance from river Social Distance from road arteries Population density Land use Land use/cover types  All parameters were projected into the same coordinate system of WGS 1984 UTM Zone 37N in ArcGIS platform to maintain spatial consistency.

Case Study Approaches Methods … ,  Then after, all parameters were undertaken the following geospatial processes :  Vector to raster conversion,  Resampling to common spatial resolution, (using DEM 30 m)  Reclassify for standardization of internal criteria,  Multi Criteria Evaluation (MCE) for weighting & ranking using AHP  Finally, weighted overlay to develop urban sprawl susceptibility index.

Study Approaches…, Methods … , Flowchart Data Sources Basic data sources Remote sensing dataset GIS datasets (Digital) CSA Landsat ETM+ Population Deriving processes SRTM DEM 30 m Ethio-Roads Ethio-River Surface Classification Extraction Interpolation Extraction Derived parameters Road artery River map Slope Pop Density LULC map Standardization Process Reclassify Integration process Weighted Overlay Outcome index Sprawl susceptibility index

Study Approaches…, Parameters’ Map with different units (Unstandardized) …………………….. the same units (Standardization)

Study Approaches…, Weighting and Ranking of parameters  Pair-wise comparison matrix of parameters was generated randomly with the rank of 1/5 (the least important) to 5 (the most important) after Saaty’s 1977 analytical hierarchy process (AHP) .  Weightage was given to the parameters based on their relative influence of contributing urban sprawl susceptibility. Ranking the parameters of urban sprawl using Saay AHP Parameter Land Roads Stream Slope Pop. AHP use Artery Density Weights Land use 1 0.25 Roads Artery 1 1 0.37 Stream 1/3 1/3 1 0.08 Slope 1/3 1/5 1 1 0.07 Pop. Density 1 1/3 3 5 1 0.23 1.00 Pair-wise comparison matrix with CR of 0.04

Study Approaches…, Weighting and Ranking of parameters … , Parameter Weights ClassValue Susceptibility Susceptibility level level value class name Stream buffer zone 8 % <50 m 1 Restricted >50 m 5 Highly susceptible Existing Land use 25 % Agriculture 5 Highly susceptible Vegetated 4 Moderately susceptible Built up 1 Restricted Bare land 3 Marginally susceptible Population density 23 % 5 - 15 5 Highly susceptible 15 - 25 4 Moderately susceptible 25 - 35 3 Marginally susceptible > 35 2 Currently not susceptible Distance from road 37 % <50 m 5 Highly susceptible artery 50 -500 m 4 Moderately susceptible 500 -1500 m 3 Marginally susceptible >1500 m 2 Currently not susceptible Slope of the region 7 % 0 - 3 5 Highly susceptible 3 - 11 4 Moderately susceptible 11 - 15 3 Marginally susceptible >15 2 Currently not susceptible

Study Approaches…,  Integration of the weighted parameters in MCE decision rule was yielding sprawl susceptibility index using the formula: Where, S is Susceptibility index (score), W i is weight of i th parameter; F i is rank of i th parameter and n is number of parameter.  Then, the overlay algorithm runs the product summation parameters in the ArcGIS platform using expression that follows.

Results and Discussion Spatial extent of sprawling Susceptibility class Area Area (ha) (%) Highly susceptible 1023 8 Moderately susceptible 5270 41 Marginally susceptible 394 3 Currently unsusceptible 4310 33 No data 1971 15 Study Area 12868 100  Results show spatial variations of prospective urban sprawl susceptibility of Shashamane town with vicinities dominated by: agricultural lands and nearby the road arteries and spread over a gentle slope were identified as  highly susceptible,  huge agricultural lands that are away from major streams were moderately susceptible,  inaccessible topography and already sprawled were marginally and currently not susceptible, respectively.

Conclusion and Ways Forward  Agro-rural setup in the town vicinity has been facing serious urban sprawl challenges with a high loss of fertile agriculture land to built up areas.  The situation has been threatening the livelihoods of the dwellers around the town unless it is checked.  Haphazard expansion of the town without planning and consent of judicious authority will also hamper the legitimate urban development patterns over several years in the future.  GIS providing effective information that help authorities to take preemptive measures based on indicators such as the urban sprawl susceptibility index.  This would lie a foundation to identify areas where environmental and natural resources are critically threatened and suggest the likely future directions and patterns of urban growth.

Conclusion and Ways Forward…,  GIS is proved to be a powerful technique to characterize urban sprawl and make the spatial depiction of sprawl susceptibility both quickly and user friendly.  However, the major challenges hampering widespread use of GIS technology, especially in developing nations: shortage of spatial data, lack of proper hardware and software, insufficient user support and unreachability of GIS professionals are  Therefore, realizing a web-based GIS database is of paramount importance to improve access to the GIS data.  The hands-on training and networking among GIS professionals would also further encourage the sharing of high quality spatial data.

Sprawling along road artery

Stream side sprawling

Plain areas urban sprawling

sprawl encroachment on farmland

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