Linganisha mbinu

	Mfumo wa Mabadiliko ya Matumizi ya Ardhi CA-Markov	Uchanganuzi wa Maamuzi wa Vigezo-Nyingi unaotumia GIS (GIS-MCDA)
Nyanja	Uchanganuzi wa Kimaeneo	Uchanganuzi wa Kimaeneo
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	1997	2006
Mwanzilishi	Cellular automata (Clarke) + Markov chain (Muller & Middleton)	Jacek Malczewski (GIS-MCDA synthesis)
Aina	Spatio-temporal land-use change simulation	Spatial multi-criteria suitability/decision analysis
Chanzo asilia	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.	Malczewski, J. (2006). GIS-based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, 20(7), 703–726.
Majina mbadala	CA-Markov model, cellular automata Markov, land-use change simulation, CA-Markov arazi kullanımı modeli	GIS-MCDM, spatial multi-criteria analysis, GIS-AHP, weighted overlay suitability
Zinazohusiana	3	4
Muhtasari	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.	GIS-MCDA combines the map layers of a geographic information system with multi-criteria decision analysis to produce suitability or priority maps — ranking locations by how well they satisfy several weighted criteria at once. It is the standard framework for spatial decisions such as siting hospitals, solar farms, landfills, or evacuation areas, integrating methods like AHP, TOPSIS, and weighted overlay with spatial data.