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Colloque International des Utilisateurs de SIG, Taza GIS-Days, 23-24 Mai 2012Recueil des Résumés 468 Optimum locating of urban parks and green space using GIS and TOPSIStechnique (Case study: region six of TEHRAN in IRAN) MOLAEI QELICHI M. (1) , OROJI H. (2) & ASADI S. (3) (1) Geography and Urban Planning, University of Tarbiat Modares, IRAN.
[email protected] (2) Geography and Tourism Planning, University of Tehran, IRAN.
[email protected] (3) Geography and urban Planning, University of Tehran, IRAN.
[email protected] Abstract. Urban parks and green space are important components of urban environments and they can amelioratemicroclimates, reduce air pollution, and alleviate heat island effects, provide comfortable recreational space for residentialand contribute to sustainable urban environments. A number of studies have shown that the location of green space isusually not based on scientific analysis. the purpose of this research is determine the optimum locations and choose thebest place to create parks and green space in the region Six in Tehran city. For this purpose is used TOPSIS model in Arc Gissoftware. Method of research is descriptive-analytical. In this research with evaluation of required criteria for locating of parks and green space, was attempting to create maps and data layers for each of the criteria in the Gis. Then for modelingof each data layer, was assigned a weight based on AHP model. Maps with overlay method combined together and usingthe TOPSIS model that is one of the multi-criteria decision-making (MCDM) techniques, the best place for parks and greenspace in case study area proposed. Results of research show that south of case study area is the best location for parks andgreen space. Keywords: Optimum locating, Parks and Green space, TOPSIS, GIS, Region six of TEHRAN city 1. Introduction. Aspects such as “amount of public green spaces per inhabitant”, “public parks” and “recreation areas” are often mentionedas important factors to make the city live able, pleasant and attractive for its citizen’s [1]. Urban parks and green space areimportant components of urban environments and they can ameliorate microclimates, reduce air pollution, and alleviateheat island effects, provide comfortable recreational space for residential and contribute to sustainable urbanenvironments [2]. Provision of urban green spaces has to be planned and realised together with the planning of other urbanfunctions like housing, transport, infrastructure, etc. The process of urban green planning must be seen as one part of anintegrated overall city planning process where the implementation of the strategy becomes easier because it is acceptedboth by the municipality administration and the citizens [3]. However a number of studies have shown that the location of green space is usually not based on scientific analysis, thus attention to problems of green space and parks providing isnecessary. 2. Methodology Method of research is descriptive-analytical. For collecting data, have been used from library research and field studies, andaccording to the data obtained, the study area in terms of access to educational Centers, residential areas and maincommunication road, also distance to fault and existing green spaces, Has been investigated. For weighting the criteria, isused the AHP model, in the software of Expert choice. Then by using the decision model of TOPSIS in software of Arc Gis9.3, to valuation of criteria within study area and prepare the suitable maps Has been proceeded. Finally, the combinedmap of criteria that shows the best locations for create parks and green space is extracted. 3. Study area Study area is the region 6 in Tehran city. Tehran is thecapital of Iran. Region 6 is one of few central regions of Tehran which perceives activity of a large number of citizensin official and business fields. In other word, specialconditions such as centrality of region in Tehran metropolison one hand, and its traffic and communicational locationbetween northern, southern, eastern, and western regionson the other hand, cause establishment of activities andseveral official-services usages in metropolitan, regional,national and even international scales and eventuallyfunctional centrality of it in Tehran; and transform thisregion to most important part of central core of Tehranfrom type, scale and operation point of view (fig.1)Fig1. Study area International Conference of GIS-Users, Taza GIS-Days, May 23-24, 2012Proceeding Book 469 4. Discussion. 4.1. TOPSIS model TOPSIS (technique for order preference by similarity to an ideal solution) method is presented in Chen and Hwang (1992),with reference to Hwang and Yoon (1981) [4]. The basic principle is that the chosen alternative should have the shortestdistance from the ideal solution and the farthest distance from the negative-ideal solution.The TOPSIS procedure consists of the following steps:(1) Calculate the normalized decision matrix. The normalized value rij is calculated as (1) (2) Calculate the weighted normalized decision matrix. The weighted normalized value v ij is calculated as(2) (3) Determine the ideal and negative-ideal solution.(3)(4) Calculate the separation measures, using the n -dimensional Euclidean distance. The separation of each alternative fromthe ideal solution is given as (4) Similarly, the separation from the negative-ideal solution is given as(5)(5) Calculate the relative closeness to the ideal solution. The relative closeness of the alternative a j with respect to A * isdefined as (6)(6) Rank the preference order. 4.2. Operational steps of TOPSIS technique in Arc Gis After the defining of effective criteria in locating of urban parks and green space, data layers of criteria entered in Gis. Thefirst step of TOPSIS is normalizing criteria that each of criterion based on their effect (positive or negative) normalized.After normalizing of layers, obtained weights from the AHP model in Expert Choice software, through command of RasterCalculator was multiplied in normalized layers and each of the criterion was weighted normalized. For example threecriterions in this research showed in fig.2, 3, and 4.Fig.2 main road Fig.3 fault Fig.4 educational center Blue pixels are closest to the ideal and vice versa, whatever we are close to the yellow color represents the ideal is negative. Colloque International des Utilisateurs de SIG, Taza GIS-Days, 23-24 Mai 2012Recueil des Résumés 470 For weighting of criteria we used AHP model in Expert Choice software. AHP is one of weighting method that formulatingthe problem as a hierarchical. AHP based on 1. Hierarchy construction, 2. Pairwise comparison, 3. Relative-weightcomputation, 4. Consistency ratio, and finally aggregation of relative weights [5]. In this research we used the Expert Choicesoftware that is compute the weight of each criteria according to AHP model (fig.5). Consistency ratio of pairwisecomparison is 0.01 that is acceptable, because less than 0.1.Fig5. Weighting of criteria in Expert ChoiceIn table 1, see obtained weights from the AHP model.Table 1. Weights of criteriaIn the next step, the positive ideal and negative ideal for each of the criteria was determined. The best values for positivecriteria is largest pixels and for negative indicators is the smallest pixels and the worst values for positive indicators issmallest pixels and for negative indicators is the largest pixels.next step is calculating of distances of pixels from the ideal and negative ideal. in fig.6 and 7, pixels distances to ideal andnegative-ideal solution for criterion of educational centers has been shown.Fig.6 ideal solution (educational centers) Fig.7 negative ideal solution (educational centers)After calculating of pixels distances from the ideal and negative ideal, each of criterion is collected together and its squareroot Through command of Raster Calculator was obtained (calculation of separation measures). This action is repeated forthe negative ideal. The obtained maps will be including D j+ and D j- that fig 8 and 9 has been shown. criterion Access tomain roadAccess toresidential areaDistance togreen spaceand parksDistance tofaultAccess toeducationalcenters Total of WeightsWeight 0.183 0.298 0.121 0.101 0.298 1 International Conference of GIS-Users, Taza GIS-Days, May 23-24, 2012Proceeding Book 471 Fig.8 separation measures of ideal solution Fig.9 separation measures of negative ideal solutionIn final step, the maps obtained in previous step according to the formula (Cj=Dj-/( Dj-+ Dj-)) combined together andoptimum locations for green spaces and parks Is obtained (fig.10).Bleu pixels are optimum locations and vice versa, whatever we are close to the yellow color represents the non-optimumlocations.Fig 10. Final map 5. Conclusions. One of the most important factors in the create of green space is a location, therefore, to determine the optimum location,maximizing efficiency of green spaces and better services for users offers. Thus, considering the fact that green spacesshould be switching to a fellow professional in the city where it seems necessary. In this research, to provide optimal spatialpattern of green spaces in the region 6 of Tehran with TOPSIS model in Arc Gis software was discussed. with combine andoverlying of data layers, the final map was obtained and was determined thatsouth (east south) of area study is the bestlocation for parks and green space. References [1] A. Chiesura, “The role of urban parks for the sustainable city” Landscape and Urban Planning Vol.68, 2004, (pp. 129–138)[2] C.Y.Jim, S.S.Chen, “Comprehensive green space planning based on landscape ecology principles in compact Nanjingcity, China, ”Landscape Urban Plan, vol.65, 2003, (pp.95–116)[3] R. Coles, N. Grayson, “Improving the Quality of Life in Urban Regions Through Urban Greening Initiatives”, Proceedingof Open Space: People Space Conference, Edinburgh, UK, 2004[4] Y-M Wang, M.S. Elhag, “Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment”,Expert Systems with Applications 31, 2006, (pp. 309-319)[5] A. Shapira, M. Simcha, “AHP-Based Weighting of Factors Affecting Safety on Construction Sites with Tower Cranes”,Journal of Construction Engineering and Management, Vol,135, 2009, (pp.307-318)
