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Landskabsmønstermålinger×CA-Markov Land-Use Change Model×
FagområdeRumlig analyseRumlig analyse
FamilieProcess / pipelineProcess / pipeline
Oprindelsesår19881997
OphavspersonR. V. O'Neill et al.; McGarigal & Marks (FRAGSTATS)Cellular automata (Clarke) + Markov chain (Muller & Middleton)
TypeQuantitative landscape pattern descriptionSpatio-temporal land-use change simulation
Oprindelig kildeO'Neill, R. V., et al. (1988). Indices of landscape pattern. Landscape Ecology, 1(3), 153–162. DOI ↗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. DOI ↗
Aliasserlandscape pattern indices, FRAGSTATS metrics, fragmentation indices, peyzaj metrikleriCA-Markov model, cellular automata Markov, land-use change simulation, CA-Markov arazi kullanımı modeli
Relaterede33
ResuméLandscape metrics are quantitative indices that describe the composition and spatial configuration of a categorical map — typically land cover — at the patch, class, and whole-landscape levels. Developed in landscape ecology (O'Neill and colleagues, 1988) and made widely usable by the FRAGSTATS software, they turn maps into numbers like patch density, edge density, fragmentation, diversity, and connectivity for ecological, planning, and change analysis.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.
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ScholarGateSammenlign metoder: Landscape Metrics · CA-Markov. Hentet 2026-06-18 fra https://scholargate.app/da/compare