Application of Markov chain & cellular automata based model for prediction of Urban transitions

A Review of Simulation Urban Growth Model

“…The result of integration between CA model and other models shows high results, both in projection, simulation accuracy, and prediction as well as in determining an urban planning that will be used as government decision making and policy in managing urban growth. [3,44] Local historical data as a search for factors affecting land change.…”

“…In Table 1 is written what are the causes of urban growth, as well as a compact growth in terms of growth that affect the growth of the city with a wide scope. Basically, simulation techniques are used to test theories about spatial location as well as fundamental interactions on urban models especially land use and urban growth activities [3]. Spatial changes in urban growth especially land use have become a problem as well as one of the interesting concerns to be understood by researchers based on urbanization and development [4].…”

“…Where P is the matrix transition, the probabilities Pij are called transition probabilities, and n = the transition probability matrix P. is the probability of change from land use type i to j calculated on a cell-by-cell basis, and the sum of each row always equals to 1 [24]. The basic premise of the Markov chain model is that land use at some point in the future (t+ 1) can be determined as a function of current land use (t), or mathematically (3) where X represents t + 1 which is the ending time of the simulation, t represents land use at the beginning time, Xt represents land use at time t and f is the transition rule [25].…”

“…In determining the proper simulation of urban growth, spatial modeling becomes a serious challenge in urban development [2]. Because, with spatial modeling, it can show the extent to which urban land changes are caused by urban growth, which can later provide information on the investigation of urban ecosystem management [3]. With the urbanization process in urban areas has caused changes in the urban landscape.…”

Modelagem das mudanças espaço-temporais de áreas úmidas: estudo de caso da Região Administrativa de Abitibi-Témiscamingue – Québec, Canadá

“…Por sua vez, os estados têm um valor em cada etapa de tempo, o que determinará as relações entre um pixel e os pixels vizinhos, formando a vizinhança (Chen et al, 2008). As regras determinarão os estados de cada pixel na próxima etapa de tempo (Kumar et al, 2016).…”