%0 Journal Article %A Alaei Moghadam, Sanaz %A Karimi, Mohammad %T Modeling growth pattern of urban patches using a patch-growing algorithm based on cellular automata in the Tehran megalopolitan area %J Journal of Geospatial Information Technology %V 4 %N 3 %U http://jgit.kntu.ac.ir/article-1-269-en.html %R 10.29252/jgit.4.3.89 %D 2016 %K Urban patches, Urban growth simulation, The megalopolitan area, Spatial index, Cellular automata, %X The megapolis areas are new types of urban settlements created in recent decades along with rapid urbanization. These areas constructed by clusters of small and large urban patches with various growth patterns. Spatial characteristics of urban patches are affected by some driving forces such as closeness to cities Central Business Center CBD and transportation network. The Cellular automata as a most common model for simulating urban growth, is unable in modeling spatial configuration of urban patches because of bottom up procedure and despite of high simulation power at cell level, CA has weaker performance in patch level. So in this study a method is presented for simulation of urban patches growth that is integrated with Logistic CA to modeling urban growth. In this method, on the one hand the growth potential map derived using logistic regression and on the other hand size and growth type of patch in each location is derived using integration of driving forces of growth patterns of urban patches. Finally according to proposed framework, a patch is constructed around selected cell and urban growth map will be prepared. The proposed model is implemented in the Tehran’s megalopolis area in 1379-1385-1391-1397 periods. The overall accuracy and FOM of results is equal to 91/01 and 37/96, respectively that are better than logistic CA model. Also the results of validation of produces urban growth map by using spatial metrics reviled high precision of methodology in simulation of spatial configuration of urban pattern. %> http://jgit.kntu.ac.ir/article-1-269-en.pdf %P 89-106 %& 89 %! %9 Research %L A-11-349-1 %+ K.N.Toosi University of Technology %G eng %@ 2008-9635 %[ 2016