Сравнение методов

	Алгебра карт	Метрики ландшафтного паттерна	Анализ наименьшей стоимости пути / анализ стоимости расстояния
Область	Пространственный анализ	Пространственный анализ	Пространственный анализ
Семейство	Process / pipeline	Process / pipeline	Process / pipeline
Год появления	1990	1988	1994
Автор метода	Dana Tomlin	R. V. O'Neill et al.; McGarigal & Marks (FRAGSTATS)	Edsger Dijkstra (shortest path); GIS cost-surface adaptation
Тип	Raster spatial analysis framework	Quantitative landscape pattern description	Raster cost-surface routing
Основополагающий источник	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.
Другие названия	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
Связанные	3	3	3
Сводка	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.