تجزیه و تحلیل فقر شهری با تاکید بر شاخص‌های اجتماعی بین سال‌های 1385 و 1395 (مطالعه موردی: شهر اردبیل)

روند شهری شدن در کشورهای درحال‌توسعه با عدم تعادل‌های فضایی، قطبی شدن مناطق و گروه‌های اجتماعی، رشد بی‌قواره شهری و شکل‌گیری گستره‌های فقر در حوزه‌های شهری همراه شده است. فقر شهری افراد را با محدودیت‌های بسیاری ازجمله دسترسی محدود به فرصت‌های شغلی - درآمدی، عدم بهره‌مندی از مسکن و خدمات مناسب، محیط‌های ناسالم و خشن، عدم بهره‌مندی از خدمات اجتماعی، سازوکارهای حمایتی بهداشتی و آموزشی، مواجه می‌سازد. تحلیل فضایی این گستره‌ها، میزان محرومیت نواحی مختلف را مشخص و اولویت اقدامات را برای ارتقای سطح زندگی معلوم می‌نماید. هدف پژوهش حاضر بررسی نابرابری‌های موجود و نشان دادن الگوی فقر در بلوک‌های شهری اردبیل با تاکید بر شاخص‌های اجتماعی طی سال‌های 1385 تا 1395 است. روش پژوهش توصیفی- تحلیلی است. تحلیل فضایی فقر در سطح بلوک‌های شهر اردبیل با استفاده از 21 شاخص اجتماعی و با بهره‌گیری از مدل‌های آمار فضایی، تحلیل لکه‌های داغ و خودهمبستگی فضایی در نرم‌افزار آرک جی‌آی‌اس انجام‌شده است. بر اساس نتایج پژوهش، بلوک‌های شهری اردبیل در هر دوره موردمطالعه در طیف‌های متفاوتی قرار دارند؛ بخش‌های غربی و شمال غربی جز بلوک‌های فقیر، در مقابل شرایط ساکنین بخش‌های جنوبی و بخشی از شمال شرقی شهر به لحاظ اجتماعی بسیار مطلوب می‌باشند. همچنین پژوهش نشان داد که شاخص محاسبه موران برای سال 1385 برابر با 0/100517 و برای سال 1395 برابر با 0/137205 می‌باشد که این نشان‌دهنده خودهمبستگی فضایی داده‌های موردنظر است. الگوی پراکنش فقر در شهر اردبیل از مدل خوشه‌ای تبعیت می‌کند که باعث ایجاد نظام دوقطبی بالاشهری و پایین‌شهری شده است.

investigating the urban poverty with emphasis on social indicators between 2006 and 2016)case study: ardebil city(

introductionurban poverty is a multidimensional problem that faces people with many limitations including limited access to employment and income, lack of adequate housing and services, unhealthy and violent environments, and lack of access to social services and health support mechanisms, and educational. thus, in explaining spatial inequality and urban poverty we cannot simply focus on its economic dimension: because citizen poverty and social poverty are also other dimensions of poverty that are central to the spread all kinds of social harm and deviation. today, the weaknesses of poverty studies and poverty-based approaches in cities are evident to almost everyone. it can be said that a realistic understanding and analysis of poverty in urban areas requires more attention to the social dimensions of this problem. since urban poverty has been the focus of economic attention in most of the cases and few studies have addressed the social aspects affecting urban poverty, therefore, the present study, with emphasis on the effective social aspects in this field, identifies the extent of social poverty and its pattern of spread in ardabil during 2006 to 2016 to provide a platform for policymakers, planners, and urban managers to make decisions about reducing poverty and social deprivation problems in urban areas.methodoloythe purpose of this study is practical and in terms of the nature and method of the research we use descriptive-analytical methods. source of cited indices and quantities used, data and information of statistical blocks of general population census and housing of ardabil city during 2006- 2016 and maps (gis), deputy governor of ardabil planning.the statistical population of the study is the statistical blocks of ardabil city during the period of 2006 to 2016. the arc/gis software has been used to illustrate the poverty situation in this city using the hot spot analysis technique of spatial autocorrelation. moran’s statistic was used to analyze the distribution patterns of urban poverty.results and discussionto study the spatial inequality and determination of urban poverty in ardebil city, we used the data of 2006 and 2016 statistical blocks and in arc / gis software using its capabilities, hot spot analysis are done for all the indices used in ardabil. this analysis calculates the gateway-rd statistic for all the effects in the data. also, with respect to the calculated z score, it can be shown in which blocks the data are clustered with high or low values. according to this analysis, the higher the z score, the higher the values clustered and it make hot spots. in the case of the negative and significant z in terms of statistical, we can say that the smaller the z score, the more severe the clustering of the lower values and indicating cold spots. according to the data obtained, in 2006, out of 5142 urban blocks in ardebil, about 53% were in very deprived and deprived condition, 26% were in moderate condition and about 21% were in good condition. according to 2016 data, these percentages are 46, 23, 33, respectively, among 6439 urban blocks, which also indicates that ardabil city blocks in terms of social indices in 2016 compared to 2006 is in a better position. at this stage, after identifying the cold and hot spots for each of the indices, the maps are combined and finally the final map for both periods 2006 and 2016, according to the morris index is categorized in 5 levels from the most privileged to the most deprived. after classifying ardebil city blocks in 2006 and 2016, arc / gis software and spatial autocorrelation tool have been used to illustrate the pattern of distribution and distribution of this inequality. it is used to analyze patterns of distribution and distribution of effects and phenomena in space and space and is known as the moran statistic.