An analysis of urban land development using multi-criteria decision model and geographical information system (a case study of Babolsar city).

Author:Lotfi, Sedigheh
 
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INTRODUCTION

The physical expansion of the cities is a dynamic process which changes the physical space of the city in a vertical or horizontal direction. If this process takes place in an unplanned manner, the physical balance of urban areas would be challenged and soon urban system is not able to function properly. Many of small and intermediate cities of the country have developed on the margins of their limits where the urban incompatible land uses created many problems (1).

The unplanned physical growth is one the most challenging problems in the developing countries which impose many socio-economic and environmental constrain. So, the physical growth of cities should be guide and control by considering the different parameters which influence the city expansion. Managing a city needs a large amount of data and information which the traditional methods are not able to do deal with them. The complexity of the urban land uses and their functions could be managed and perceived only by using a powerful tool such as GIS. One of the models which can decrease the cost and has a high potential for spatial decision making is Multi-criteria Decision Model Analysis (MCDA).

Babolsar town is one of the northern cities of the Mazandaran province in the southern coast of the Caspian Sea. The town is located in the middle of agricultural fertile lands. Iran as arid and semi arid region has a limited area of cultivable land which is mainly scratched in the north. The central policy of the Iranian government is to save agricultural land for the cultivation of rice as strategic crop. But the unprecedented urban physical growth has threatened the most of the periphery areas of the city in the region. So this study tries by using an efficient model for appropriate urban development in the area.

MATERIALS AND METHODS

Multi model decision making refers to a process of valuing different alternatives which are investigated by several criteria. The multi criteria decision making could be divided into the two broad classes: multi-attribute and multi-objective decision making.

If the investigated case is a confined set of alternatives for selecting of the best one according to the weight of each alternative characteristic, this case would be a Multi-attribute decision making. The multi-objective decision making selects the best alternatives on the base of much incompatible objectives (2). The multi-objective models are used for design while multi objective models are applied for selecting the best alternative (3).

The Multi Criteria Decision Making (MCDM) is a set of techniques (e.g., sum of weights or conversion analysis) which is able to weight and score a range of criteria and then the scores are ranked by the expertise and other related interested groups (3).

Statistics reveal that more than 80 percent of information relates to space and situation in the daily life of human being (4).

The MCDA techniques are spatial in much degree. In fact, criteria are different among the number of decision in space (5) However, despite the potential of MCDA model for integration to deal with spatial units problems, it gained attention only in a certain period of times in some practical researches and managerial limits (6) Urban planners used the strategy of MCDA integration for dealing with spatial issues from 1990s (7) A city system can not be studied only by considering the simple concepts like land use or traffic. Now planners need to develop and deepen their understanding about a city system by analyzing a various socio-economic and political indicators. The issues which need to be dealt at same times create a condition which many alternatives should be tested and integrated to improve (8).

So, using an analyzing tool for the huge volume of data is quite necessary to optimize the MCDA models. GIS can provide an appropriate context for data analysis which is useful tool integration with into MCD methods. Therefore, using MCDA and GIS has a high efficiency for solving spatial problems in urbanism; as in one hand this method could provide an organized framework for consider the effective criteria on spatial issues and weighting them through multi criteria decision strategy and in the other GIS can analysis the large data to determine the most appropriate decisions. Carver and Openshaw stated four main benefits for using integrated MCDA and GIS:

* This method has the ability to perform the complex analysis of many different criteria.

* This model uses factor weighting to integrate the analysis for value judgments.

* It creates a systematic framework of analysis.

* It has all of the advantages of the GIS data base (9).

The AHP approach, developed by (10) is one of the more extensively used MCDM methods. The AHP has been applied to a wide variety of decisions and the human judgment process (11). This technique is one of the MCDA methods with many capabilities which is used in different scientific disciplines. The previous researches show that the technique of MCDA which is...

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