تحقیقات کاربردی علوم جغرافیایی

تحقیقات کاربردی علوم جغرافیایی

بررسی کیفیت زندگی شهری با استفاده از سنجش از دور و GIS (مطالعه موردی: مناطق شهری ارومیه)

نویسندگان
1 کارشناس ارشد سنجش از دورو GIS، دانشکده جغرافیا و برنامه‌ریزی، دانشگاه تبریز، تبریز، ایران
2 دانشیار گروه سنجش از دور و GIS، دانشکده برنامه‌ریزی و علوم محیطی دانشگاه تبریز، تبریز، ایران
چکیده
کیفیت زندگی ازجمله مسائل مهمی است که ابتدا با گسترش همه جانبه فناوری و فرآیند صنعتی شدن در کشورهای غربی مورد توجه اندیشمندان قرار گرفت و روزبه روز بر مطالعات در این زمینه افزوده شده و این مهم، به دلیل افزایش روزافزون مطالعات کیفیت زندگی در پایش سیاستهای عمومی است. کیفیت زندگی می تواند به عنوان ابزاری قدرتمند برای نظارت بر برنامه ریزی توسعه اجتماع به کار رود. وجود نابرابری­های فضایی و مکانی در سطح شهر مشکلات عدیده ای ازجمله ضعف منابع در آمدی، مسکن نامناسب، مشکلات و آسیبهای ناشی از نابرابریهای اجتماعی را به وجود آورده و کیفیت زندگی را تحت شعاع قرار داده است. در این تحقیق که از نظر روش، توصیفی-تحلیلی و از نظر هدف، کاربردی می­باشد از آمار بلوک های شهر ارومیه، در سرشماری سال 1395 و داده های سنجش از دور در تلفیق با سیستم اطلاعات جغرافیایی جهت شناخت کیفیت زندگی در مناطق 5 گانه شهر ارومیه استفاده شده است. معیارهای تعریف شده در این تحقیق در 4 بخش: اجتماعی(شامل 9 زیر معیار)، دسترسی به خدمات عمومی(5 زیر معیار)، کالبدی(4 زیر معیار)، طبیعی(4 زیر معیار) می­باشند که با استفاده از تجزیه و تحلیل تصمیم گیری چند معیاره و تلفیق لایه­ها در محیط سیستم اطلاعات جغرافیایی به دست آمده­اند. اوزان به دست آمده برای ابعاد اجتماعی، دسترسی به خدمات عمومی، طبیعی و کالبدی حاصل از مدل تحلیل شبکه به ترتیب برابر با 506/0، 323/0، 116/0 و 055/0 می باشد. نتایج نشان می­دهد که هر چقدر از جنوب غربی به طرق شمال شرقی شهر حرکت کنیم بلوکهایی که کیفیت زندگی مطلوبتری دارند افزایش می­یابند. در بین مناطق شهری منطقه­ای2 کیفیت زندگی مطلوبتری را نسبت به سایر مناطق شهری دارد. نتایج حاصل از اینگونه مطالعات می­تواند به برنامه ریزان شهری در درک بهتر و اولویت بندی مسائل شهری به عنوان یک محیط پویا کمک رسان باشد.
کلیدواژه‌ها

عنوان مقاله English

Assessing urban quality of life using remote sensing and GIS (Case study: Urmia Urban Region)

نویسندگان English

ali khedmatzadeh 1
Bakhtaran Feizizadeh 2
1 MSC remote sensing and GIS, Department of Remote sensing and GIS, University of Tabriz
2 Associated professor in department of remote sensing and GIS, University of Tabriz, Iran
چکیده English

Quality of life is one of the important issues that was first brought to the attention of scholars by the extensive development of technology and industrialization process in the Western countries, and it is increasingly being studied in this field, and this is important due to the increasing increase in quality of life studies in public policy monitoring. Quality of life can be used as a powerful tool for monitoring community development planning. The existence of spatial and spatial inequalities in the city has caused many problems, including the weakness of resources, inappropriate housing, the problems and damage caused by social inequalities, and undermined the quality of life. In this research, that of terms methodological, descriptive-analytic and in terms of purpose, it is functional used the statistics blocks of Urmia, in the census of 1395, and remote sensing data in combination with GIS have been to understand the quality of life in the 5 regions of Urmia. The criteria defined in this research are in 4 sections: social (including 9 sub-criteria), access to public services (5 sub-criteria), physical (4 sub-criteria), natural (4 sub-criteria), which are based on decision analysis Multi-criteria and integration of layers in the GIS environment. Weights obtained for social dimensions, access to public, natural and physical services derived from network analysis model are respectively 0.506, 0.323, 0.116 and 0.055. The results show that as far as the southwest is moving along the northeastern part of the city, blocks that have a better quality of life are rising. In the urban regions of the region 2, quality of life is more favorable than other urban regions. The results of such studies can help urban planners to better understand and prioritize urban issues as a dynamic environment.

کلیدواژه‌ها English

quality of life
Urmia city
Spatial analysis
GIS
FANP
Blomquist, G. C., Berger, M. C., & Hoehn, J. P. (1988). New estimates of quality of life in urban areas. The American Economic Review, 89-107.
Boyer, R, Savageau, D. (1981). Places Rated Almanac Rand McNelly Chicago.
Campbell, A, Philip E. C, and Willard L. R(1976). The quality of American life: Perceptions, evaluations, and satisfactions. Russell Sage Foundation.
Chen J, Yang Y. 2011. A fuzzy ANP-based approach to evaluate region agricultural drought risk. Procedia Eng.23:822–827.
Das, D. (2008). Urban quality of life: A case study of Guwahati. Social Indicators Research, 88(2), 297-310.
Feizizadeh B, Ghorbanzadeh O. (2017). GIS-based interval pairwise comparison matrices as a Novel approach for optimizing an analytical hierarchy process and multiple criteria weighting. GI_Forum. 1:27–35.
Foo, T,S. (2000)"Subjective assessment of urban quality of life in Singapore (1997–1998)." Habitat International 24, no. 1: 31-49.
Garcia-Melon, Monica, Javier Ferris-Onate, Jeronimo Aznar-Bellver , Pablo Aragonés-Beltran, and Rocio PovedaBautista (2008), Farmland appraisal based on the analytic network Process, Journal of Global Optimization, Vol.42, pp.143-155.
Huang, J.J., Tzeng, G.H., and Liu, H.H. (2009). A Revised VIKOR Model for Multiple CriteriaDecision Making -The Perspective of Regret Theory. MCDM, CCIS, 35:761-768.
Jensen, J.R. (2005). Introductory digital image processing. Upper Saddle River: Pearson: Prentice Hall.
Jimenez-Munoz, J.C., Sobrino, J.A., Skokovic, D., Mattar, C., and Cristobal, J. (2014). Land surface temperature retrieval methods from Landsat-8 thermal infrared sensor data.Geoscience and Remote SensingLetters, IEEE, 11(10): 1840-1843.
Jun, B. W. (2006). Urban quality of life assessment using satellite image and socioeconomic data in GIS. Korean Journal of Remote Sensing, 22(5), 325-335.
Klee, P. (2011). The core of GIScience: a process-based approach. Enschede, the etherlands: ITC.
Lee, J., Je, H., Koo, B, (2008). A Study on the Direction of Remodeling for Super High-Rise Housing through Survey with Experts.
Li, G. and Weng, Q., (2007), Measuring the Quality of Life in City of Indianapolis by Integration of Remote Sensing and Census Data, International Journal of Remote Sensing, 28(2), 249-267.
LI, G., and Weng, Q. (2007). Measuring the quality of life in city of Indianapolis by integration of remote sensing and census data. International Journal of Remote Sensing, 28:249–267.
Liu, B,C.(1976). "Quality of Life Indicators in US Metropolitan Areas A Statistical Analysis". Praeger, New York.
Lo, C. P. (1997). Application of Landsat TM data for quality of life assessment in an urban environment. Computers, Environment and Urban Systems, 21(3-4), 259-276.
Lo, C. P., & Faber, B. J. (1997). Integration of Landsat Thematic Mapper and census data for quality of life assessment. Remote sensing of environment, 62(2), 143-157.
McGillivray, M. (2007). Human well-being: Issues, concepts and measures Human wellbeing(pp. 1-22): Springer.
Moro, M., Brereton, F., Ferreira, S., & Clinch, J.P. (2008). Ranking quality of life using subjective well-being data. Ecological Economics, 65(3), 448-460
Murray-Rust, D., Rieser, V., Robinson, D. T., Miličič, V., Rounsevell, M., 2013. Agent-based modelling of land use dynamics and residential quality of life for future scenarios. Environmental modelling & software, 46, 75-89.
Pal, A. K., & Kumar, U. C. (2005). Quality of Life (QoL) concept for the evaluation of societal development of rural community in West Bangal, India. Asia-Pacific Journal of Rural Development, 15(2), 83-93.
Pearl, D.C. (2011), “Mapping the Quality of life experience in Alfama”, Unpublished Master Degree dissertation, Portugal New University of Lisbon, Portugal.
Rahman, M. R., Shi, Z. H., Chongfa, C., (2014). Assessing regional environmental quality by integrated use of remote sensing, GIS, and spatial multi-criteria evaluation for prioritization of environmental restoration. Environmental monitoring and assessment, 186(11), 6993-7009.
Saaty TL. (1996). Decision making with dependence and feedback: the analytic network process. Vol. 4922, Pittsburgh (PA): RWS publications;
Saaty TL.( 1990). How to make a decision: the analytic hierarchy process. Eur J Oper Res. 48(1):9–26.
Saaty TL.( 1996). The analytic network process. Pittsburgh (PA): RWS Publications.
Saaty, T. L. (1999), "Fundamentals of the Analytic Network Process", Proceedings of ISAHP 1999, Kobe, Japan
Saaty, T. L. (1999), "Fundamentals of the Analytic Network Process", Proceedings of ISAHP 1999, Kobe, Japan.
Sadeghi, B., and Khalajmasoumi, M. (2015). A futuristic review for evaluation of geothermal potentials using fuzzy logic and binary index overlay in GIS environment. Renewable and Sustainable Energy Reviews, 43:818-831.
Sarmah, Tanaya, and Sutapa Das. "Earthquake Vulnerability Assessment for RCC Buildings of Guwahati City using Rapid Visual Screening." Procedia engineering 212 (2018): 214-221.
Shamsuddin, S; Abu Hassanb,N; Bilyamin, S(2012) Walkable Environment in Increasing the Liveability of a City, ASEAN Conference on EnvironmentBehaviour Studies .Bangkok, Thailand, 16-18 July 2012, Procedia - Social and Behavioral Sciences 50 ( 2012 ) 167 – 178.
Shen, L., Peng, Y., Zhang, X., & Wu, Y. (2012). An alternative model for evaluating sustainable urbanization. Cities, 29(1), 32-39.
Smith, C., & Levermore, G. (2008). Designing urban spaces and buildings to improve sustainability and quality of life in a warmer world. Energy policy, 36(12), 4558-4562.
Stover, M. E., & Leven, C. L. (1992). Methodological issues in the determination of the quality of life in urban areas. Urban Studies, 29(5), 737-754.
Sufian, A,J,M. (1993). A multivariate analysis of the determinants of urban quality of life in the world's largest metropolitan areas. Urban Studies, 30(8), 1319-1329.
Susanti, R., Soetomo, S., Buchori, I., & Brotosunaryo, P. M. (2016). Smart Growth, Smart City and Density: In Search of The Appropriate Indicator for Residential Density in Indonesia. Procedia - Social and Behavioral Sciences, 227(November 2015), 194–201.
Yuksel, Ihsan & Metin, Dagdeviren (2007). Using the analytic network process (ANP) in a SWOT analysis – A case study for a textile firm, Information Sciences 177.