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Metriken für Landschaftsmuster×CA-Markov Land-Use Change Model×
FachgebietRäumliche AnalyseRäumliche Analyse
FamilieProcess / pipelineProcess / pipeline
Entstehungsjahr19881997
UrheberR. V. O'Neill et al.; McGarigal & Marks (FRAGSTATS)Cellular automata (Clarke) + Markov chain (Muller & Middleton)
TypQuantitative landscape pattern descriptionSpatio-temporal land-use change simulation
Wegweisende QuelleO'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 ↗
Aliasnamenlandscape pattern indices, FRAGSTATS metrics, fragmentation indices, peyzaj metrikleriCA-Markov model, cellular automata Markov, land-use change simulation, CA-Markov arazi kullanımı modeli
Verwandt33
ZusammenfassungLandscape 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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ScholarGateMethoden vergleichen: Landscape Metrics · CA-Markov. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare