بررسی نقش و عملکرد شهرها درنظام طبقات شهری استان مازندران با استفاده از منطق فازی

در تحلیل مناسبات، روابط و عملکرد فی مابین شهرها توجه به ویژگیهای جغرافیایی، جمعیتی، اقتصادی وارتباطی از اهمیت ویزه ای برخوردار می باشد. شکل گیری سکونتگاهها و نظام شبکه شهری مازندران به تبعیت از ناهمواریها و جهت قرارگیری (رشته کوه البرز)، منابع آب (رودخانه های دایمی، فصلی، چشمه ها) و شبکه ارتباطی در جلگه و ارتفاعات می باشد. پژوهش حاضر از نظر هدف کاربردی و از نظر ماهیت توصیفی تحلیلی بوده وشیوه گردآوری داده ها اسنادی و میدانی و نیز در تحلیل داده ها (شدت عملکرد و نقش شهرها) از منطق فازی استفاده شده است. ضمن آنکه ترسیم نقشه های عملکردی شهرهای استان در محیط arc gis صورت پذیرفته است. نتایج حاصله از مجموع شاخصهای جمعیت، مسافت(کیلومتر،زمان)، مرکزیت درمنطق فازی گویای آن است که توزیع طبقات جمعیتی شهرهای استان به تبعیت از روند کنونی نظام طبقات شهری در سطح ملی می باشد.(کانون شهر)های استان گرچه از برتری عددی برخوردار می باشند لیکن سهم ناچیزی در جمعیت شهری استان دارند. وجود رابطه معکوس و متقارن بین تعداد شهرها و جمعیت شهری با حرکت از طبقه پایین (کانون شهر، روستاشهر) به (مراکزخرده ناحیه ای، متروپل ناحیه ای) همچون: ساری بابل، آمل، قائمشهرو بالعکس در نظام شهری استان محسوس می باشد با توجه به مجموع شاخصهای جدول نظام طبقات شهری استان، صعود پلکانی (کانون شهر، روستاشهرها) ازعملکرد ضعیف به عملکرد متوسط و خوب در(شهرکوچک،متوسط) و از عملکرد خوب به (مراکزخرده ناحیه ای، متروپل ناحیه ای) با عملکرد برجسته مشهود می باشد.بر این اساس (متروپل ناحیه ای) ساری و بابل دارای عملکرد برجسته و (مراکزخرده ناحیه ای) آمل و قائمشهراز عملکرد خوبی برخوردار می باشند. حدود 41 درصد از مجموع 58 شهر استان که شامل(کانونهای شهری) و(روستاشهر) می باشند دارای عملکرد ضعیف بوده اند که بیشترین سهم را شهرهای واقع در بخش غربی و ارتفاعات استان به خود اختصاص داده اند.

A Study on the Role and Function of Cities in Mazandaran Province’s Urban Levels System by using Fuzzy Logic

In analyzing functions of cities, it is important to notice geographical, population, economic and communicative characteristics. Formation of settlements and urban networks in Mazandaran follows Alborz mountains, water resources (permanent and seasonal rivers and springs), and communication networks in heights and plains. The purpose of this study is applied; its nature is descriptiveanalytical and its method of data collection focuses around documents and field data. For data analysis (intensity of function and role of cities), this study relies on fuzzy logic. Drawing provincial cities function map was accomplished in Arc GIS. Results obtained from various population, distance (Km, time), centrality in fuzzy logic indexes suggest that distribution of population levels follows the current trend in national urban levels system. Although centers of the cities enjoy numerical supremacy, they have negligible shares of the province’s urban population. The reverse and symmetrical relationship between the number of cities and urban population is perceivable by moving from lower levels (city center, ruralcity) to (subregional centers, metropolitan regions) such as: Sari, Babol, Amol, Qaemshahr. According to the indexes of provincial urban levels system table, stairwise ascent (city center, ruralcity) from weak to medium and good function in (small, medium cities) and from good (subregional centers, metropolitan regions) to prominent function is observed. Thus, (reginal metropolitan) Sari and Babol have prominent functions and (subregional centers) Amol and Qaemshahr show good functions. Around 41% of 58 provincial cities including (urban centers and ruralcities) demonstrate weak function with Western and high altitude cities having the greatest share. Keywords: urban systems, population levels,, regional metropolis, urban function, fuzzy logic Research Paper               Extended Abstract Introduction:In order to identify urban systems, it is vital to consider the external relationships of cities and the significance and role of each connection. Thus, accurate understanding of the nature of space and its forming forces and subsequently, identification of space organization methods in the region, requires identification of various relationships among cities (Mohammadi et al., 2017, p. 91). Urban network patterns are affected by different factors including natural, morphological, population, centrality of amenities and political, economic, social services, space and time distances from central or influential cities and other similar variables. Accordingly, based on distances and city size, that by themselves conceptualize associated region  toward each other, recognize intensity and degree of connections and the function of cities in the realm of land (Shahosseini, 2017, p. 9). Understanding the relationships among urban and rural settlements and the functions that they perform as to one another, constitute living patterns in various regions to a large extent. Additionally, the role of each city on the basis of social, populationoriented, economic, servicebased and political components in defining functional associations in urban network of the land, plays a crucial role. Therefore, the current study aims to investigate the role and function of cities in urban levels system of Mazandaran by using Fuzzy logic in order to determine the position and status of each city. Methodology:       The present study is applied in terms of purpose, and is descriptiveanalytical in terms of nature. Data collection method was based on documents and field study and instruments of data collection included library sources and authors’ field observation and studying. To measure and analyze the data (intensity of relationships and functions in the urban network of Mazandaran) fuzzy logic was employed with emphasis on four variables of population, centrality (political, social, cultural, medical, economic), distance (time and place) and the sum of indexes by which function and relationships among cities ranged from prominent (0.751), good (0.50.75), medium (0.250.5), weak (00.25). This scale was actively used to determine the amount of influence and malleability of urban levels system in each of the cities under investigation. Moreover, drawing provincial maps (of role and function of urban networks) by using Arc GIS was accomplished too. Findings:        Results of the study indicate that distribution of population levels in the cities of the province follows a similar trend as the national urban levels system. besides, urban centers of the province, although having a numerical advantage (51%) in comparison to other levels, possess a meager share  (8%) of provincial urban population. The reverse and symmetrical relationship between the number of cities and their population is obvious by moving from the bottom level (city center, ruralcity) toward (subregional centers, regional metropolis) such as Sari, Babol, Amol, Qaemshahr, (52 percent of the urban population) in the urban system of the province  Conclusion:     The present study suggest that, as shown in the indexes of provincial urban levels system table, stairway ascent (city center, ruralcity) from weak to medium and good function in (small, medium cities) and from good (subregional centers, metropolitan regions) to prominent function is observed. Kiakola, Sorkhrood, Hadishahr, Emamzadeh Abdollah, Daboodasht, are among city centers that although possess less population and have their centrality in rural areas, demonstrate good functions in urban levels system because of their proximity to and little distance from subregional centers of Amol, Babol, and Sari. Jouybar, Nowshahr, Nour, Amirkola, Babolsar (small and medium cities) contain more population compared to the previous level and boast political and economic centrality, thus being among cities with good function in the urban system of the province. The (regional metropolis) of Sari and Babol share and compete on a prominent status and function in the provincial urban network and outperform other rival cities.