پيش بيني رﺷﺪ و ﺗﻮﺳﻌﻪ شهرستان بندرگز ﺑﺎ استفاده از ﻣﺪل اتوماتاي سلوليﻓﺎزى (FCA)

Predicting the growth and development of Bandar-e-Gaz Town Using Fuzzy Cellular Automata (FCA)

ﻣﺪلﻫﺎى ﻣﺒﺘﻨﻰ ﺑﺮ اتوماتاي سلولي(CA) از ﺟﻤﻠﻪ ﻣﺪل‌هاﻳﻰ اﺳﺖ ﻛﻪ در آن‌ها ﻗﻮاﻧﻴﻦ ﺗﺒﺪﻳﻞ در ﺣﺎﻟﺘﻰ ﻏﻴﺮﻣﻨﻌﻄﻒ ﺗﻌﺮﻳﻒ ﻣﻰﮔﺮدﻧﺪ. ﺗﺮﻛﻴﺐ ﻣﻨﻄﻖ ﻓﺎزى ﺑﺎ ﻣﺪل اتوماتاي سلوليﻛﻼﺳﻴﻚ اﻣﻜﺎن مدل‌سازي ﻋﺪم ﻗﻄﻌﻴﺖ ﺣﺎﻛﻢ ﺑﺮ ﻓﺮآﻳﻨﺪ ﺷﺒﻴﻪﺳﺎزى توسعه ﺷﻬﺮى را از ﻃﺮﻳﻖ ﺗﻌﺮﻳﻒ ﻗﻮاﻧﻴﻦ ﺗﺒﺪﻳﻞ ﺑﺎ درﺟﺎت ﻋﻀﻮﻳﺖ ﻓﺎزى ﻓﺮاﻫﻢ ﻣﻰﺳﺎزد. ﭘﮋوﻫﺶ ﺣﺎﺿﺮ ﻣﺪﻟﻰ از ﺗﻮﺳﻌﻪ ﺷﻬﺮى را ﺑﺮ ﻣﺒﻨﺎى اﺻﻮل اتوماتاي سلولي و ﻣﻨﻄﻖ ﻓﺎزى اراﺋﻪ مي‌نمايد. در اﻳﻦ راﺳﺘﺎ اﺑﺘﺪا ﻣﻬﻤﺘﺮﻳﻦ ﺷﺎﺧﺺﻫﺎى ﻣﺆﺛﺮ ﺑﺮ توسعه ﺷﻬﺮى و ﺳﺎﺧﺘﺎر ﺷﺒﻜﻪاى ﺷﺎﺧﺺﻫﺎ ﺑﺎ روش دﻳﻤﺎﺗﻞ به‌دﺳﺖ آﻣﺪ، ﺳﭙﺲ وزن ﻫﺮ ﺷﺎﺧﺺ ﺑﺎ روش ﻓﺮآﻳﻨﺪ ﺗﺤﻠﻴﻞ ﺷﺒﻜﻪ (ANP) ﻣﺤﺎﺳﺒﻪ ﺷﺪ. ﺑﺮاى ﺷﺒﻴﻪ ﺳﺎزى توسعه ﺷﻬﺮى در ﻣﺤﺪوده ﻣﻮرد ﻣﻄﺎﻟﻌﻪ (شهرستان بندرگز) ﺑﺮاى ﺳﺎل2100 از 3 ﺗﺼﻮﻳﺮ ﻣﺎﻫﻮاره‌اى ﻣﺮﺑﻮط ﺑﻪ ﺳﺎلﻫﺎى 2012، 2014 و 2019 اﺳﺘﻔﺎده ﺷﺪ. ﺑﻌﺪ از اﻧﺠﺎم ﻋﻤﻠﻴﺎت ﭘﻴﺶﭘﺮدازش، ﻃﺒﻘﻪﺑﻨﺪى ﺗﺼﺎوﻳﺮ ﺑﺮاى ﻫﺮ ﺳﻪ دوره ﺑﺎ روش ﺣﺪاﻛﺜﺮ ﺷﺒﺎﻫﺖ ﺻﻮرت ﮔﺮﻓت. ﺑﺮاى ﺑﺮرﺳﻰ ﺻﺤﺖ ﻧﻘﺸﻪﻫﺎ در دو ﻣﺮﺣﻠﻪ از ﺷﺎﺧﺺ ﻛﺎﭘﺎ اﺳﺘﻔﺎده ﺷﺪ، اﺑﺘﺪا ﻧﻘﺸﻪﻫﺎى ﺳﺎلﻫﺎى ﻣﺒﺪا ﻃﺒﻘﻪﺑﻨﺪى و ﺻﺤﺖ آن‌ها ﺑﺎ واﻗﻌﻴﺖ ﺑﺮرﺳﻰ ﺷﺪ، سپس ﺑﺮاى ﺷﺒﻴﻪﺳﺎزى ﻧﻘﺸﻪ ﺳﺎلﻫﺎى دﻳﮕﺮ اﻗﺪام ﺷﺪ و ﻣﺠﺪدا ﺻﺤﺖ عمليات مورد ارزيابي قرار گرفت. از آﻧﺠﺎ ﻛﻪ ﻣﻴﺰان ﺻﺤﺖ ﻣﺪل ﺑﺮاى دورهﻫﺎى داراى ﻧﻘﺸﻪ ﻗﺎﺑﻞ ﻗﺒﻮل ارزﻳﺎﺑﻰ ﺷﺪ، ﺑﻨﺎﺑﺮاﻳﻦ ﺑﺮاى ﺷﺒﻴﻪﺳﺎزى توسعه ﺷﻬﺮى ﺳﺎل2100 ﻣﺪل رﮔﺮﺳﻴﻮن ﺧﻄﻰ و ﻣﺎﺗﺮﻳﺲ اﺣﺘﻤﺎﻻت ﺗﺒﺪﻳﻞ ﻣﻮرد اﺳﺘﻔﺎده ﻗﺮار ﮔﺮﻓت. ﻧﺘﺎﻳﺞ ﻧﺸﺎن داد كه ﻣﺪل اراﺋﻪ ﺷﺪه ﻗﺎﺑﻞ ﻗﺒﻮل بوده به‌طوريكه در ﺷﺒﻴﻪﺳﺎزى ﺷﻬﺮى ﻧﺴﺒﺖ ﺑﻪ ﻣﺪل ﻛﻼﺳﻴﻚ CA بهتر عمل مي‌نمايد. همچنين رﺷﺪ و ﺗﻮﺳﻌﻪ شهرستان بندرگز در دورهﻫﺎى ﻣﺨﺘﻠﻒ بيشتر در ﺟﻬﺖهاي شرقي و غربي ﺻﻮرت ﮔﺮﻓﺘﻪ اﺳﺖ.

The use of quantitative models to simulate the development of cities due to the several factors affecting the urban environment is always accompanied by challenges and uncertainties. Among the most recently used models, automated cell-based models (CAs) are defined in which conversion rules are defined based on two-value logic and in a non-flexible manner. Combining fuzzy logic with the classical cellular automata model makes it possible to model the uncertainty governing the urban development simulation process by defining the transition rules using the degrees of fuzzy membership. This study presented the model of urban expansion based on the fuzzy cellular automata. The most effective indicators were first selected using the DEMATEL method. The weight of each indicator was then obtained using the Analytic Network Process (ANP). Three satellite images from 2012, 2014 and 2019 were used to simulate urban development in the study area (Bandar-e-Gaz Town) for the year 2100.After preprocessing; the images were classified for all three periods by the maximum likelihood method. The Kappa index was used to check the accuracy of the maps in two steps. The images of the base year were first classified and their accuracy was examined, and then the simulation of the images of the other years was performed and their accuracy again was examined. Since the degree of accuracy of the model was considered acceptable, the linear regression model and matrix of transition probabilities were used for simulation. The results of this study showed that the proposed model is acceptable so that it works better in urban simulation than the classical model of CA. Also, the growth and development of Bandar-e-Gaz town in different periods has been more in the eastern and western parts.