**2. Short background: GIS-based land-use suitability studies**

While factor and objectives are spatial, a GIS interface is necessary to analyze geographic da‐ ta, and it requires a combination of multi-criteria methods with a GIS interface [21, 22]. In the literature, there are many land-use decision studies using GIS and other spatial informa‐ tion science, such as RS. Malczewski [22] completed a detailed study on the survey of the GIS-based MCE techniques. Results showed that this method is used widely (top three sub‐ jects) and orderly in environment and ecology, transportation, and urban-rural planning studies. In addition, these techniques are used in waste management, agriculture and forest‐ ry, facility area suitability, rangeland management, recreation and tourism, natural hazard studies, hydrological studies, and real estate-housing studies. Some techniques, data, and criteria used for land-use suitability analyses are found in **Table 1**.

there are some non-linear ideal data-dependent techniques, such as ANN, logistic regres‐

Expert-based technique is preferred by those who have not any ideal point data, because, in this technique, all factors are evaluated by the experts, applying a survey that includes ques‐ tions about the priority of the factors. Analytical hierarchical process (AHP) can be used be‐ cause of pairwise comparison abilities to detect the weights of factors after the expert's decisions. Pairwise comparison matrix is defined as weights using binary priority definition ability [16, 17]. Although expert-based weighting is easy, all experts may be given various answers to the same question. Thus, the subjectivity of this method is high. However, this

Literature-based weighting is another approach to define factor weights. It is completely based on similar studies in the literature and factor weights are adapted to the new research from previous studies. This method is easy for weight definition; however, regional environ‐ mental and social differences are ignored in this approach, so the reliability of the technique

Ideal data-based weighting is the most reliable approach in MCE studies. The problem in this technique is that what is the ideal data. For example, in a crop-based agricultural landuse suitability detection study, crop productivity can be used to define ideal crop suitability areas and all factors can be weighted relating to high productive areas to find potential suit‐ able areas. Crop productivity data can be obtained from farmer surveys or using RS [13]. There is another technique using ideal point for weighting called the weight of evidence (WOE). This approach is also effective to define factor weights in land-use suitability or en‐

This chapter discusses land-use suitability for urban growth using ideal point-based techni‐ que. Ideal urban sprawl is defined using urban growth dynamics from past to current. In this extent, Van City, which is located in eastern Turkey, was modeled by applying three different scenarios: economic, ecological, and sustainable. Distance from road and central city area, elevation, slope, hillshade, land-use ability (LUA), and land-use cover (LUC) were used as factors in the study. Weights were defined according to urban change and were used in all scenarios. On the contrary, restriction areas and fuzzy suitability degrees of LUC

While factor and objectives are spatial, a GIS interface is necessary to analyze geographic da‐ ta, and it requires a combination of multi-criteria methods with a GIS interface [21, 22]. In the literature, there are many land-use decision studies using GIS and other spatial informa‐ tion science, such as RS. Malczewski [22] completed a detailed study on the survey of the GIS-based MCE techniques. Results showed that this method is used widely (top three sub‐

sion, ant colony algorithm, and regression tree.

vironmental hazard probability studies [19, 20].

and LUA data were modified separately for the scenarios.

**2. Short background: GIS-based land-use suitability studies**

method is still used widely [18].

is a question.

208 Sustainable Urbanization



EC, electrical conductivity; GDD, growing degree days; NDVI, normalized difference vegetation index.

**Table 1.** Sample techniques and factors used in land-use suitability studies.

According to **Table 1**, even if the suitability target is same, there might be small differences between factors. Some of the important essential factors are the same in agricultural suitability studies, such as soil depth, slope, and soil texture. However, there are different factors: erosion rate, soil nutrients, and crop productivity. Data accessibility, database availability, and method can be affected factors despite the same purpose. Also, these factors may be changed with respect to regional differences. If there is flood risk in an area, we have to assess flood risk rate in land-use suitability analyses.
