Сравнение методов

	Модель изменения землепользования CA-Markov	Клеточные автоматы
Область	Пространственный анализ	Имитационное моделирование
Семейство	Process / pipeline	Process / pipeline
Год появления	1997	1940s–1950s (formalized); 1970 (Conway's Game of Life); 2002 (Wolfram's systematic classification)
Автор метода	Cellular automata (Clarke) + Markov chain (Muller & Middleton)	John von Neumann and Stanislaw Ulam (1940s–1950s); popularized by John Conway (1970) and Stephen Wolfram (1980s–2002)
Тип	Spatio-temporal land-use change simulation	Grid-based computational simulation model
Основополагающий источник	Clarke, K. C., Hoppen, S., & Gaydos, L. (1997). A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B, 24(2), 247–261.	Wolfram, S. (2002). A New Kind of Science. Wolfram Media. ISBN: 978-1579550080
Другие названия	CA-Markov model, cellular automata Markov, land-use change simulation, CA-Markov arazi kullanımı modeli	CA, Hücresel Otomat (Cellular Automata), lattice model, grid-based simulation
Связанные	3	5
Сводка	CA-Markov is a hybrid spatio-temporal model that projects land-use and land-cover change by combining a Markov chain — which predicts how much of each class will change — with cellular automata, which decide where that change happens. Widely used for urban-growth and land-cover forecasting, it answers both the quantity and the location of change, something neither component does well alone.	Cellular automata (CA) is a grid-based computational simulation model, first formalized by John von Neumann and Stanislaw Ulam in the 1940s–1950s and brought to wide attention by John Conway's Game of Life (1970) and Stephen Wolfram's systematic classification (2002), in which a lattice of cells — each holding a finite discrete state — evolves in discrete time steps according to local neighborhood interaction rules, causing complex global patterns to emerge from simple local specifications.