Integrated Site Suitability Analysis for Urban Development Using Remote Sensing and GIS Based Multicriteria Evaluation Technique in Wolaita Sodo Town and Surrounding Area, SNNPR, Ethiopia

Urban Land suitability assessment is an important fundamental work in urban land development. Land suitability assessment, in the context of land use planning, is a bridging phase linking land resources assessment to any land use decision-making process. This study demonstrates the use of Geographic Information System (GIS) tools and numerical Multi-Criteria Evaluation (MCE) techniques for selection of suitable sites for urban development of a Sodo Town and surrounding area. Six factors (land use, road proximity, soil type, river proximity, geomorphology and slope) were identified for criteria evaluation. Weights for each criterion are generated by comparing with each other according to their importance. Criteria weights was develop by employing GIS based Multi-Criteria Decision Analysis (MCDA) such as Analytical Hierarchy Process (AHP) for evaluating the suitability of the urban land site selection. Pair wise comparison matrix indicates weights for land use (=0.3729), road proximity (=0.1440), soil type (=0.1826), river proximity (=0.0714), geomorphology (=0.1777) and slope (=0.0514). Consistency Ratio, (CR =0.01) <0.10 indicated a reasonable level of consistency in the pair wise comparisons. After the final suitability analysis map was obtained from weighted overlay in Arc GIS Spatial Analyst Tools; it was found that from the available area 19.234sq km falls under low suitable, 4.579sq. km under moderately suitable and 5.048sq. km under high suitable. The result shows that highly suitable areas for urban development is agricultural land and open forest.


Description of The Study Area
Wolaita Sodo Town, one of the oldest Town in the SNNPR is formed as Town 113 years ago as military center to the south, to make a united one Ethiopia by the Emperor Minlik the secondary of Ethiopia. One of the 22 reform cities in SNNPR & has got a secondary level next to Hawassa. It is the administrative capital of the Wolaita zone. In addition the Town functions as a center for the surrounding agricultural land. It is also a major transportation node, being the center of six national and regional transport router. Trade is the most important lively hood of the resident of the Town. Sodo Town is located 390 km of south 167 km of south west of Addis Ababa and Hawassa respectively. Astronomically the Town is located 6 0 49' N latitude and 37 0 45' E longitude. The Town is divided in to three sub town, 11 kebeles and 99 villages (mender). The Town is established at the foot of mount Damot & from these mountains; its altitude descends to south directions. The highest & lowest altitude of the town range from 2,222-1,600 meters above sea level. The mean annual temperature of the town is 20 o c & the mean annual rainfall is 1,200mm.
Population size of the Town, according to the data from city finance Economic Development office recently the total number of the Town's residents exceed 120,000. However the office says that the number of population is increasing in high level due to continues rural-urban migration. To this end, the annual growth rate of the Town's population is 5.4%. The Town is located in the strategic place for the southern Ethiopia at the center and it has 6 outlets which are connect the north, south, east and west areas.

Materials and Methods
The key principle behind urban land suitability analysis is the cartographic modeling approach in which a set of map operations is performed on input maps of a study area to create a spatial model [4,5]. Suitability analysis can be conducted in GIS by using either a vector data or a raster data model. GIS based urban site suitability is the process of understanding existing site qualities and factors, which will determine the location of a particular activity. The purpose of selecting potential areas for residential development depends upon the relationship of different factors, like location of available sites, extent of the area, accessibility, etc. and site association factors like slope, soil etc. The analysis may also determine how those factors will fit into the design process to evaluate site suitability [13].
The purpose of this chapter is to present fundamental materials and methods applied to obtain the required data from respective sources and a research design describes a procedural adopted to answer the research objectively, accurately. Method includes the following concepts as they relate to a particular discipline or field of inquiry like collection of theories, concepts or ideas, comparative study of different approaches; and critique of the individual. Therefore a research method provide answer for such questions as what techniques will be used to gather the data, what kind of model used to make analysis and presentation of the results.

Materials 3.1.1 Data Sources
Different data source were refereed to analyses the land suitability of the study area because the most important thing in making research is source of data. Data help to reach the final result, which was designed earlier in the objectives. Different types of data were utilized to attain the objectives in this paper.

Softwares for image and data processing
Software used in this study was selected based on the capability to work in achieving the predetermined objectives. ERDAS 2014 was used for image processing activities on satellite images. The factor map development was carried out using ArcGIS10.4.1 Software package. The factors that are input for multi-criteria analysis should be preprocessed in accordance to the criteria set to urban land suitability analysis. So, using spatial Analyst and 3D Analyst extension, some relevant GIS analyses were undertaken to convert the collected shape files. IDRISI 32 was also used for weight module determination.

Methods
In order to conduct the study, a step by step method was followed in this research. The workflow of the research can be shown by figure 2. During the preliminary studies a number of literatures were reviewed and the study area was selected. Based on preliminary studies the requirement analysis was done for setting data requirements and for getting criteria affecting the urban land use suitability analysis. Then, geodatabase was created. The data was collected and was exported into geodatabase. Further literature reviews were done for calculating Eigen Values using AHP methodological operations. The Eigen Values show the degree of priority of the criteria.
Using Eigen Values raster criterion maps were prepared from data available in geodatabase. These criterion maps were overlaid to develop a composite map which later was classified to prepare suitability map. Finally, using the suitability map urban land suitability was suggested.

.1.2 Road Proximity map
The road network plays a very important role in the urban development. The road networks were digitized from the Google earth map. As more settlement develops near the road networks because of the transportation facilities and very easy access to the nearby places and city centers. The five different classes' of proximity regions for road networks were generated, 100m, 200m, 300m, 400m, and 500m proximity respectively. High weightage has been given for 100m class as the development of settlements and multi-story buildings are highly possible near the road networks. Low weightage has been given for 500m proximity class as there are fewer chances for the development of settlements away from road networks.  [12] identified which soil types have high fertility, nutrient deficiency and high water holding capacity and can be used for urban areas. The soil types in the study area are dystric Nitisols, chromic Luvisols and chromic Vertisols.
Nitisols are marked by deep, porous solum, well drained and easy to plough. Moreover, good texture, high organic matter, BS and CEC characterize the Nitisols. Thus they are generally considered as fertile and productive soils. , However, the level of Nitrogen and the imbalances of nutrients need to be corrected to enhance the productivity of the soils. Luvisols are fertile for its high organic matter, available bases and CEC and also intensively cultivated soils. The most constraint of soils, however, is soil acidity [14].
Vertisols soil has good workability, good drainage, and adequate soil depth. The vertisols on the other hand, pose different problems. They are inherently fairly fertile with good moisture holding characteristics, and a welldeveloped structure when dry. However, they have a narrow range of moisture outside of which they are hard when too dry and very sticky when too wet.

Rivers Proximity map
In this study, the rivers have been mapped by digitizing from the Google earth image. The area near the water bodies develops more rapidly than the area which is away from the surface water bodies. Accordingly, analysis tools were used to prepare multiple polygons around each river within the following distances: 100m, 200m, 300m, 400m, and 500m proximity respectively. The proximity map was reclassified into five classes and weights were calculated using data analysis. Accordingly, more weightage was assigned for more suitable areas 100m. Low weightage was given for 500m proximity class.

.1.6 Slope factor map
Slope is one of the basic criteria to be considered in economic terms. It is suggested to select flat areas for development and continuity of the urban growth. The DEM presents in the study area ranging from 1600 -2,222m above sea level. The DEM was used for the generation of the slope map of the area with the help of Arc-GIS tool called Slope, the extension tool of the 3D Analysis tools. Slope has categorized in to 5 classes in degree. Fig 8 below shows the area distribution of the various slope map of the study area.

Analysis and Result 4.1 Analytic Hierarchy Process (AHP)
AHP is one of the most popular Multi-Criteria Decision Making Model (MCDM) techniques developed by Saaty (1980). It is used to identify the best one from a set of alternatives with respect to several criteria. The basic principle of AHP is to solve a problem by forming hierarchies. To ensure the credibility of the relative significance used, AHP also provides measures to determine inconsistency of judgments mathematically.
Based on the properties of reciprocal matrices, the consistency ratio (CR) can be calculated. CR < 0.10 indicates that level of consistency in the pair wise comparison is acceptable. Saaty (1980) suggests that if CR is smaller than 0.10, then the degree of consistency is fairly acceptable. But if it is larger than 0.10, then there are inconsistencies in the evaluation process, and AHP method may not yield meaningful results.
The standardized raster layers were weighted using Eigen vector that is important to show the importance of each factor as compared to other in the contribution of urban land suitability analysis. Accordingly, the Eigen vector of the weight of the factors was computed in IDRISI 32 software in analysis menu decision support/ weight module. In this study, a pair of criteria were valued at the same time using the scale of nine points (degrees) ranging from1/9 to 9 as shown in Table 2. The computed Eigen vector, which is an output of the pairwise comparison matrix to produce a best fit set of weight, of Weight Module was: Land use/Land cover 0.3729 Road proximity 0.1440 Soil type 0.1826 Rivers Proximity 0.0714 Geomorphology 0.1777 Slope 0.0514 The critical ratio of the calculated Eigen vector is 0.01 which is acceptable. The computed Eigen vector is used as a coefficient for the respective factor maps to be combined in Weighted Overlay in Arc GIS environment.

Overlaying map layers
Afterward preparation of maps of all features like road buffer, soil type, river buffer and geomorphology were converted to raster files and separate datasets were created using weightage and rank. For different layers having different scores were laid and the scores of each composite class were added. Finally, the suitability map was prepared. Table 3. Factors weightage According to FAO (1993) the suitability classification standard is famous for land suitability analysis. The standard establishes whether a land is highly suitable or not suitable. It is split into five suitability ratings. This case study used three of the important ratings of land suitability ratings to generate the results. The three ratings are high suitability, moderate suitability, and low suitability, as shown in table 4 below. Table 4. Explanation of the land suitability ratings used in the study (Source: FAO, 1993).

Low suitability
Moderate suitability High suitability 1 2 3 Land with limitations so severe that benefits are reduced and/or the inputs needed to sustain production are increased so that this cost is only marginally justified.
Land that is clearly suitable but which has limitations that either reduce productivity or increase the inputs needed to sustain productivity compared with those needed on highly suitable land.
The land can support the land use indefinitely and benefits justify inputs.
In order to have final suitability analysis, six different criteria maps are converted into raster format. A GIS Spatial analysis in which models are represented as a set of spatial processes, such as buffer, classification, and reclassification and overlay techniques. Each of the input themes is assigned a weight influence based on its importance. Figure 9. Final urban land suitability map The procedure for land suitability analysis for the urban development relied on GIS based weighted overlay of the factor maps on this paper. The result indicates that 66.644 percent land is low suitable, 15.866 percent is moderate suitable and 17.490 percent is high suitable for urban development.

Conclusion and Recommendation
This chapter provides the concluding part of this paper. It states the main contribution of this study by relating the findings with the objectives of this study. Finally this chapter suggests further study recommendation.

Conclusion
A suitability map was created based on the approach that was adopted. The study was focused on use of integrated Remote sensing and multi-criteria AHP with GIS to determine the suitability of the urban land deployment of Sodo Town and surrounding area. The result of this study indicated that out of the total area of 13 28.861km 2 , 17.49% (5.048km 2 ) are most suitable for urban development, 15.866% (4.579km 2 ) are moderately suitable for urban development and 66.644% (19.234km 2 ) of the area is least suitable for urban development. Therefore, this study presented the advantages of integrated GIS-based land suitability analysis and a solution for such complicated decisions.

Recommendation
After analysis of the study, certain recommendations can be made. The following can be recommended for suitable urban land development:  The combination of GIS with AHP is powerful tool for land suitability analysis for urban development. The method requires only little computer skills within a GIS environment. Therefore, GIS-based AHP for land suitability has proven to facilitate efficiency from the economic point of view as compared to the traditional methods.  Land-use strategy must take account of land suitability in relation to the expected future needs and the possibility of meeting demands. The critical importance of land for specified uses should be known either physical or economic suitability. This means not only whether it is important that this specific area of land should be used in particular way but also whether a particular area is physically suitable.  An urban development land-use suitability mapping approach has been constructed, based on opportunity and constraint criteria.  In the future study this method can be applied for mapping land suitability of other urban development in the county and across the country with additional and more refined parameters.