Abstract
Although the growth of cities is a positive phenomenon, but the problem is an uncontrolled and unbalanced growth of cities. In order to control this growth, different policies in different countries have suggested. These policies don’t always have the same content and they can have different effects on the city and its surroundings. Like many developing countries, Iranian cities rapidly growing in terms of population and physically expanding at a high rate. This research investigates the factors that account for urban growth management in Iranian cities. Karaj metropolis has been studied as a case. Karaj has been experiencing significantly higher rates in the total area of urban environments mostly due to its socioeconomic attractions over four decades ago. To evaluate the dimensions of urban growth management in Karaj city, Factor analysis was used in form of classified sampling. Furthermore, in order to describe the variables in the districts of Karaj city, the COPRAS method is used. Finally, differences between urban area and indices of built-up area were analyzed. Results show that five factors effect on urban growth management in Iranian cities; policies and rules factor, physical, economic, social and environmental factors.
This paper is based on the Ph.D dissertation under the title “Explanation and presentation of optimal pattern to urban growth management in Karaj city, Iran”, presented in Faculty of Geography, University of Tehran.
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References
Affisco, J.F., Chanin, M.N.: An empirical investigation of integrated multicriteria group decision models in a simulation/gaming context. Simul. Gaming 21(1), 27–47 (1990). doi:10.1177/1046878190211003
Bouzekri, S., Lasbet, A.A., Lachehab, A.: A new spectral index for extraction of built-up area using Landsat-8 data. J. Indian Soc. Remote Sens. 43(4), 867–873 (2015). doi:10.1007/s12524-015-0460-6
Caves, W.: Encyclopedia of the City. Routledge, NewYork, London (2005)
Chandra Das, M., Sarkar, B., Ray, S.: A framework to measure relative performance of Indian technical institutions using integrated fuzzy AHP and COPRAS methodology. Socio-Econ. Plann. Sci. 46(2012), 230–241 (2012)
Chatterjee, P., Chakraborty, S.: Material selection using preferential ranking methods. Mater. Des. 35, 384–393 (2012). doi:10.1016/j.matdes.2011.09.027
Cho, J.: Urban planning and urban Sprawl in Korea. Urban Pol. Res. 23(2), 203–218 (2005)
Das, M.C., Sarkar, B., Ray, S.: A framework to measure relative performance of Indian technical institutions using integrated fuzzy AHP and COPRAS methodology. Socio-Econ. Plann. Sci. 46(3), 230–241 (2012). doi:10.1016/j.seps.2011.12.001
Dean, J.: Choosing the right type of rotation in PCA and EFA. Shiken JALT Test. Eval. SIG Newsl. 13, 20–25 (2009)
Digman, J.M.: Personality structure: emergence of the five-factor model. Annu. Rev. Psychol. 41, 417–440 (1990). doi:10.1146/annurev.ps.41.020190.002221
Duany, A.A., Plater-Zyberk, E., Speck, J.: The inner city. In: Carmona, M., Tiesdell, S. (eds.) Urban Design Readers. Architectural Press, Oxford (2000)
Friedman, H.S., Schustack, M.W.: Personality: Classic Theories and Modern Research, 5th edn. Allyn & Bacon, Boston (2012). ISBN 0-205-05017-4
Yong, A.G., Pearce, S.: A beginner’s guide to factor analysis: focusing on exploratory factor analysis. Tutor. Quant. Methods Psychol. 9(2), 79–94 (2013)
Ismaeilpour, N., Zare, M., Nasrian, Z.: Urban growth management tools emphasizing to controlling sprawl. National Conference on Geography, Urban Planning and Sustainble Development. University Aviation Industry, Tehran (2014)
Kaklauskas, A., Zavadskas, E.K., Naimaviciene, J., Krutinis, M., Plakys, V., Venskus, D.: Model for a complex analysis of intelligent built environment. Autom. Constr. 19(3), 326–340 (2010). doi:10.1016/j.autcon.2009.12.006
Kaklauskas, A., Zavadskas, E.K., Raslanas, S., Ginevicius, R., Komka, A., Malinauskas, P.: Selection of low-e windows in retrofit of public buildings by applying multiple criteria method COPRAS: a Lithuanian case. Energ. Build. 38(5), 454–462 (2006). doi:10.1016/j.enbuild.2005.08.005
Kanapeckiene, L., Kaklauskas, A., Zavadskas, E.K., Seniut, M.: Integrated knowledge management model and system for construction projects. Eng. Appl. Artif. Intell. 23(7), 1200–1215 (2010). doi:10.1016/j.engappai.2010.01.030
Kaur, P.: An empirical study on factors affecting faculty retention in Indian business schools, pp. 63–73. Springer, New Delhi (2015). https://doi.org/10.1007/978-81-322-1979-8_5
Konstantinos, D., Patlitzianas, A.P., Psarras, J.: An information decision support system towards the companies’ environment formulation of a modern energy. Renew. Sustain. Energ. Rev. 12(2008), 780–790 (2008)
Kumar Dey, P., Nath Ghosh, D., Chand Mondal, A.: A MCDM approach for evaluating bowlers performance in IPL. J. Emerg. Trends Comput. Inf. Sci. 2, 563–573 (2011)
Keiner, M., Koll-Schretzenmayr, M., Schmid, W.A.: Managing Urban Futures: Sustainability and Urban Growth in Developing Countries. Ashgate, Aldershot (2005)
Loeb, D.: Urban voids: grounds for change reimagining Philadelphia’s vacant lands. Archit. Des. 78(1–2), 68–73 (2008)
Mulliner, E., Smallbone, K., Maliene, V.: An assessment of sustainable housing affordability using a multiple criteria decision making method. Omega 41(2), 270–279 (2013). doi:10.1016/j.omega.2012.05.002
Osborne, J.W.: What is rotating in exploratory factor analysis? Pract. Assess. Res. Eval 20(2) (2015). http://pareonline.net/getvn.asp?v=20&n=2
Pallagst, K.M.: Growth Management in the US, Between Theory and Practice. Ashgate Publishing Limited, England (2007)
Pirasteh, A., Hidarnia, A., Asghari, A., Faghihzadeh, S., Ghofranipour, F.: Development and validation of psychosocial determinants measures of physical activity among Iranian adolescent girls. BMC Pub. Health 8, 150 (2008). doi:10.1186/1471-2458-8-150
Rietveld, T., van Hout, R.: Statistical Techniques for the Study of Language and Language Behaviour. De Gruyter Mouton, Berlin, Boston (1993). doi:10.1515/9783110871609
Rummel, R.J.: Applied Factor Analysis. Northwestern University Press, Evanston (1970)
Sakieh, Y., Amiri, B.J., Danekar, A., Feghhi, J., Dezhkam, S.: Simulating urban expansion and scenario prediction using a cellular automata urban growth model, SLEUTH, through a case study of Karaj City. Iran. J. Hous. Built Environ. 30(4), 591–611 (2014). doi:10.1007/s10901-014-9432-3
Severine, M.: The Influence of Local Political Coalitions on the Effectiveness of Urban Containment Policies: Empirical Evidence from Six U.S. States. Florida State University, New York (2007)
Seifolddini, F., Mansourian, H.: Spatial-temporal pattern of urban growth in Tehran Megapole. J. Geogr. Geol. 6(1), 70–80 (2014). doi:10.5539/jgg.v6n1p70
Sudhira, H.S., Ramachandra, T.V., Raj, K.S., Jagadish, K.S.: Urban growth analysis using spatial and temporal data. J. Indian Soc. Remote Sens. 31(4), 299–311 (2003). doi:10.1007/BF03007350
Tabachnick, B.G., Fidell, L.S.: Using Multivariate Statistics, 3rd edn. Harper Collins, New York (1996)
Triantaphyllou, E.: Encyclopedia of Electrical and Electronics Engineering, vol. 15, pp. 175–186. Wiley, New York (1998). Webster, J.G. (ed.)
Trancik, R.: What is lost space? In: Urban Design Readers. Architectural Press, Oxford (1986)
Waqar, M.M., Mirza, J.F., Mumtaz, R., Hussain, E.: Development of new indices for extraction of built-up area & bare soil from landsat data, vol. 1, p. 136 (2012). doi:10.4172/scientificreports.136
Walters, D., Luise Brown, L.: Design First: Design-based Planning for Communities. Architectural Press, Oxford (2004)
Zavadskas, E.K., Kaklauskas, A., Turskis, Z., Tamošaitienė, J.: Selection of the effective dwelling house walls by applying attributes values determined at intervals (2008). https://doi.org/10.3846/1392-3730.2008.14.3
Zha, Y., Gao, J., Ni, S.: Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. Int. J. Remote Sens. 24(3), 583–594 (2003)
Zhang, Y., Balzter, H., Liu, B., Chen, Y.: Analyzing the impacts of urbanization and seasonal variation on land surface temperature based on subpixel fractional covers using landsat images, vol. 10(4), pp. 1–13 (2016)
Iranian Statistics Center: Karaj statistical yearbook 2012. Tehran, Iran (2012)
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Molaei Qelichi, M., Murgante, B., Farhoudi, R., Zanganeh Shahraki, S., Ziari, K., Pourahmad, A. (2017). Analyzing Effective Factors on Urban Growth Management Focusing on Remote Sensing Indices in Karaj, Iran. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2017. ICCSA 2017. Lecture Notes in Computer Science(), vol 10407. Springer, Cham. https://doi.org/10.1007/978-3-319-62401-3_34
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