Modeling urban development patterns is an important technique for understanding complex urban growth processes. In this study, Logistic Regression model was conducted to model urban growth pattern of Gorgan area in North Iran, during the period 1988-2025. To do this, remotely sensed imagery of years 1988, 1998 and 2007 were used to produce land use maps. Also, dependent and independents variables were created to perform urban growth pattern modeling. Then, urban changes were detected during 1988 – 2007 and urban change modelling was achieved using Logistic Regression. After that, future urban grow pattern was predicted. The results indicated that urban areas have increased during study time period. Validation of model results was performed using Pseudo-R2 and ROC values which were more than 0.27and 0.83 respectively. Furthermore, Logistic Regression was applied to predict urban growth patterns for the years of 2016 and 2025. According to the results, appropriate implementations are needed to control land use changes, particularly urban growth, in order to preserve environmental as well as ecological balances of the area. The result could be help the managers to monitor and prevent the unplanned urban development in future. Model’s extracted maps can be used for managing and controlling future urban development.

Evaluation of these and the threat, much reduces costs in the event of crisis and better life with safety and creates security for citizens. On this basis assessment of cities vulnerability during the battles and compile appropriate ways to reduce vulnerability and damages is essential. Therefore this study sought to assess and vulnerability zoning of Kerman city from the perspective of passive defense with an emphasis on land uses and vital infrastructures and possible threats city as well as three indicators of population density, quality of buildings and empty spaces. To achieve this objective the Delphi method and Analytical Hierarchy Process (AHP) is used. Also using the ArcGIS software and it's analyze, Vulnerability maps were developed. Finally, by combining the zoning map the vulnerability of vital infrastructures and population and physical indicators, the final zoning map vulnerabilities in Kerman is achieved. According to the plan a wide range of domestic and central city are as are vulnerable to high and medium. The most vulnerable areas is Zone 3 and Zone4 is the safest area of Kerman city.

Study of changes in the past and the destruction of resources and the feasibility and expected changes in the coming years can be planning and optimal use of resources and controlling non-fundamental changes in the future is an important step. The present study aimed to model the Behbahan using LCM city land use changes and Markov chain was used. In this regard, land use change detection using satellite images Landsat, ASTER and ETM+ (Image 2000) and OLI (Image 2014) was performed. Using logistic regression modeling and 6 variable power transmission, digital elevation models, slope, away from residential areas, the distance of agricultural, away from the road map and Evidence Likelihood was performed. For maps of the distance from residential areas, agricultural lands and away from the road distance analysis Euclidean distance and to evaluate the correlation between the independent variables and the dependent variable Cramer's correlation coefficient was used. The ROC indicator used to assess the validity of the model. Comparison of modeled area map with the map of 2014 shows the residential areas and agricultural land continues to be a growing trend will continue. As the residential area of 3157 hectares, 4180 hectares in 2014 to 15030 hectares to 20778 hectares of agricultural land increased. But the destruction of rangeland has not only not improved, but the intensity is much higher than the last.