Compara mètodes

	Àlgebra de mapes	Mètriques de Patrons del Paisatge	Anàlisi del camí de cost mínim / Distància-cost
Camp	Anàlisi espacial	Anàlisi espacial	Anàlisi espacial
Família	Process / pipeline	Process / pipeline	Process / pipeline
Any d'origen	1990	1988	1994
Autor original	Dana Tomlin	R. V. O'Neill et al.; McGarigal & Marks (FRAGSTATS)	Edsger Dijkstra (shortest path); GIS cost-surface adaptation
Tipus	Raster spatial analysis framework	Quantitative landscape pattern description	Raster cost-surface routing
Font seminal	Tomlin, C. D. (1990). Geographic Information Systems and Cartographic Modeling. Prentice Hall. ISBN: 978-0-13-350927-4	O'Neill, R. V., et al. (1988). Indices of landscape pattern. Landscape Ecology, 1(3), 153–162.	Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269–271.
Àlies	Cartographic Modeling, Raster Algebra, Grid Algebra, Harita Cebiri	landscape pattern indices, FRAGSTATS metrics, fragmentation indices, peyzaj metrikleri	cost-distance analysis, accumulated cost surface, least-cost corridor, en düşük maliyetli yol
Relacionats	3	3	3
Resum	Map Algebra is a rule-based language and computational framework for deriving new raster layers from existing ones by applying arithmetic, logical, or statistical operations cell by cell or across neighborhoods. Formalized by Dana Tomlin in 1990, it is the foundational algebraic system underlying raster GIS analysis and is widely used in environmental science, urban planning, hydrology, and land-use modeling whenever spatially explicit calculations on gridded data are required.	Landscape 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.	Least-cost path analysis finds the route between two locations that minimizes accumulated travel cost across a landscape, rather than minimizing straight-line distance. By encoding terrain, slope, land cover, and other frictions into a cost surface and accumulating cost outward from a source, it identifies optimal corridors for roads, pipelines, trails, power lines, and wildlife movement — a core raster-GIS technique built on Dijkstra's shortest-path logic.