Quantifying the Degree-of-Freedom, Degree-of-Sprawl and Degree-of-Goodness of Urban Growth Tehran and Factors Affecting it Using Remote Sensing and Statistical Analyzes

Nowadays, urban sprawl phenomenon have been seen in many of cities in the developing and developed countries. Urban sprawl is considered as a particular kind of urban growth which comes up with a lot of negative effects. The analysis of urban growth using spatial and attribute data of the past and present, is regarded as one of the basic requirements of urban geographical studies, future planning as well as the establishment of political policies for urban development. Various methods have been used to investigate the physical growth of cities up to now. The remote sensing method and geographical information system are the most updated, precise and economical methods used to investigate the physical growth of cities. Since physical expansion occurs in temporal and spatial scale, the built-up land use can be extracted by using remote sensing multi-temporal data. Then, by comparing these data in different time periods by using statistical and spatial analysis of geographical information system, amount, and the ratio of changes were evaluated and its trend was modeled to be used in the urban planning. In this study six temporal satellite images of 44 years interval (1972, 1984, 1992, 2000, 2008 and 2016) have been classified to determine the urban extent and growth of Tehran in 8 different geographical directions within a circular region. So as to analyze data, Pearson’s chi-square statistics, Shannon’s entropy model and degree of goodness index were utilized. Pearson’s chi-square statistical model determines the amount of urban growth difference in various time periods which can be used along with Shannon’s entropy model to determine changes and scattering in the expansion of urban boundaries. The degree of goodness index can be used to investigate the urban growth quality. In the last studies, these models have been used to analyze spatial phenomena of the city such as changes trend in the city structure and shape in order to spatial expansion and land use changes. In this study, the used method of analyzing spatial data completely differs from the literature. In this model, a prediction model of CA-Markov is used to anticipate the urban growth in the year 2024 and also statistical parameters such as Shannon’s entropy and Pearson’s chi-square are used to analyze the way, the amount and the degree of goodness of the urban growth in the past and future. In this way, it was found that the city of Tehran has a high degree-of-freedom, high sprawl, and a negative goodness in urban growth. The total sprawl equals to 4.71 which is dramatically higher than half of value. As a result, it can be generally inferred that the city experienced a high sprawl value during 1972-2016 and this trend would continue to next years. The results indicate that in various time periods the city does not experience a good urban growth. The investigation of the degree of goodness index in various sectors also follows the same trend as various time periods. Nonetheless, different sectors and time periods can be compared to each other. Sectors of North and NorthEast compared to the other sectors, have the best and the worst urban growth, respectively. This study establishes the foundation for an in-depth recognition of urban expansion in Tehran and optimization of future urban planning.