This study explores application of multi agent system (MAS) to simulate spatial patterns of urban growth in Chandigarh and its surrounding region (India). A numerical simulation model is developed with MAS considering the dynamics of urban and rural population as the principal driver of urban growth. The model utilizes static and dynamic environment variables initialized using a logistic regression model. The logistic regression model uses pixel wise change/no-change information derived using Landsat TM data (1989–1999) as dependent variable and proximity, density, elevation and slope as independent variables. The optimum resolution of 90 m for modelling is decided using fractal analysis of series of transition probability surfaces generated using logistic regression from 30 to 240 m spatial resolution at 30 m interval. The model was finally calibrated using sensitivity analysis and behaviours space experiments with multiple simulation runs. A change to built-up area of 32.55 km2 is observed during 1989–1999 and 113.51 km2 in 1999–2009. The modelling shows a total 14.42 % disagreement between predicted map and reference map for the year 2009. The results were validated using ROC statistics and accuracy estimates with satellite data. The model was further used to predict urban growth for the year 2019. Diversity index was used to determine the potential of the model to capture overall spatial patterns of urban growth.