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بررسی کیفیت زندگی شهری با استفاده از سنجش از دور و Gis مطالعه موردی : مناطق 1 و 2 شهر زاهدان
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نویسنده
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قنبری ابوالفضل ,کریم زاده صدرا ,ترانه صدیقه
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منبع
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اطلاعات جغرافيايي (سپهر) - 1401 - دوره : 31 - شماره : 121 - صفحه:93 -110
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چکیده
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کیفیت زندگی میزان توانمندی محیط برای فراهم آوردن و پاسخگویی به نیازهای مادی و معنوی افراد جامعه می‌باشد. پیامدهای اجتماعی، اقتصادی، سیاسی و فیزیکی شهرنشینی همچنان دانشمندان را در سراسر جهان به چالش می کشاند. راهبردهای برنامه‌ریزی صحیح شهری کلیدهایی برای ایجاد یک محیط زندگی بهتر برای شهروندان است. پژوهش حاضر به بررسی کیفیت زندگی شهری در مناطق 1 و 2 شهر زاهدان با تلفیق دادههای سنجش از دور، تصاویرماهوارهای و دادههای جمعیتی حاصل از سرشماری و شبکه معابر شهری پرداخته است. روش پژوهش به‌کار رفته از نوع توصیفی تحلیلی و روش جمع آوری داده‌ها و اطلاعات، اسنادی و کتابخانه ای بوده است. چهار شاخص اقتصادی، اجتماعی، زیست‌محیطی و دسترسی به خدمات به‌عنوان معیارهای اصلی برای مدل‌سازی کیفیت زندگی انتخاب شده است. همچنین برای استخراج تصاویرماهوارهای از سامانه گوگل ارث انجین و به‌منظور تلفیق و همپوشانی لایه‌ها و شاخص‌ها از نرم‌افزار arcgis استفاده شده است. نتایج نشان می‌دهد که شاخص دسترسی به خدمات بیشترین تاثیر را در بررسی کیفیت زندگی دارد و بخش های شرقی منطقه 2 و بخش‌های مرکزی منطقه 1 از کیفیت زندگی بیشتری برخوردار است. در ادامه نتایج، شاخص خودهمبستگی فضایی موران بر وجود الگوی خوشه ای کیفیت زندگی در محدوده مورد مطالعه تاکید دارد.
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کلیدواژه
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کیفیت زندگی شهری، سیستم اطلاعات جغرافیایی، سنجش از دور، خود همبستگی فضایی، شهر زاهدان
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آدرس
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دانشگاه تبریز, گروه سنجش از دور و سیستم اطلاعات جغرافیایی, ایران, دانشگاه تبریز, گروه سنجش از دور و سیستم اطلاعات جغرافیایی, ایران, دانشگاه تبریز, ایران
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پست الکترونیکی
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sedighe.taraneh@gmail.com
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Evaluating the quality of urban life using remote sensing and GIS Case study: district number 1 and 2 of Zahedan
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Authors
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Ghanbari Abolfazl ,Karimzadeh Sadra ,Taraneh Sedighe
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Abstract
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Extended AbstractIntroductionDespite higher standards of living in urban areas, rapid growth of urbanization has caused some problems such as development of dense and unplanned residential areas, environmental pollution, lack of access to services and amenities, increased gap between social classes and etc. Manifested as severe differences between living standards in different parts of cities, these affect the quality of urban life. Quality of life is considered to be one of the most important dimensions of sustainable urban development. The desire to improve the quality of life in a particular space, for a particular individual or group is one of the main concerns of planners. Failure to identify factors affecting the quality of life in various human settlements will have unexpected and unfortunate consequences. With a decrease in citizens’ life satisfaction, society will gradually lose its productive and capable labour force. The present study primarily seeks to find a way to objectively study and evaluate the quality of life in urban areas using remote sensing technology and GIS. Therefore, it investigates the quality of life in Zahedan and identifies possible factors improving life quality. Methods and MaterialThe present study applies a descriptiveanalytical methodology. Statistical data were collected from census data of Iranian Statistics Center and maps were retrieved from Zahedan detailed planrelated service centers. Satellite images were also used. The present study applies four indicators to study the quality of life: economic, social, and environmental indicators along with access to service providing centers. Cronbach’s alpha method was used in SPSS to determine the reliability of the questionnaire resulting in a coefficient of 0.723 for the previously mentioned indicators which shows high reliability of the instrument. The validity of the questionnaire was also investigated using experts’ opinions. Collected data and factor analysis for economic and social variables were performed using SPSS. Criteria were weighted using Super Decision software and ArcGIS was used to combine and model the layers. Satellite images were retrieved from Google Earth Engine. Results and DiscussionIn order to investigate the socioeconomic inequalities affecting quality of life, 16 parameters were extracted from the available census data and used to assess the socioeconomic situation in the study area. Correlated parameters were combined using factor analysis to represent a single index. A specific name was then assigned to each factor. Indicators were normalized and aligned for the modeling stage. Fuzzy membership functions (Large, Small and Liner) were used to normalize the indicators in ArcGIS. Each index is then multiplied by the weight obtained from ANP method, and integrated using GAMMA fuzzy command. Spatial distribution of urban blocks in the central parts of the first district ranked higher in terms of economic and social indexes of life quality. Environmental indexes and access to service providing centers have a more desirable status in the second district. Parameters such as economic participation rate , housing status, air pollution and health centers had the largest impact on quality of life. Moran’s spatial autocorrelation index shows a cluster pattern for quality of life in the study area. ConclusionFinal results show that access to service providing centers has the largest impact on quality of life. In general, the second district ranks higher than the first district in terms of quality of life. This city faces various economic and social limitations, while having access to many facilities: Recent droughts, universities and higher education institutions, mutual borders with neighboring countries and a large number of immigrants from Afghanistan. It is also facing hot and dry climate, a decrease in vegetation cover and an increase in temperature level. The freeway located in the western part of the study area, urban expansion toward the western parts, increased constructions and increased urban density due to proximity to university centers and finally heavy traffic have caused air pollution. Also, public service centers are not evenly distributed. These are some of the most important causes of low quality of life in the study area.
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Keywords
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