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Многокритериальный анализ решений на основе ГИС (GIS-MCDA)×Метрики ландшафтного паттерна×Анализ наименьшей стоимости пути / анализ стоимости расстояния×
ОбластьПространственный анализПространственный анализПространственный анализ
СемействоProcess / pipelineProcess / pipelineProcess / pipeline
Год появления200619881994
Автор методаJacek Malczewski (GIS-MCDA synthesis)R. V. O'Neill et al.; McGarigal & Marks (FRAGSTATS)Edsger Dijkstra (shortest path); GIS cost-surface adaptation
ТипSpatial multi-criteria suitability/decision analysisQuantitative landscape pattern descriptionRaster cost-surface routing
Основополагающий источникMalczewski, J. (2006). GIS-based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, 20(7), 703–726. DOI ↗O'Neill, R. V., et al. (1988). Indices of landscape pattern. Landscape Ecology, 1(3), 153–162. DOI ↗Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269–271. DOI ↗
Другие названияGIS-MCDM, spatial multi-criteria analysis, GIS-AHP, weighted overlay suitabilitylandscape pattern indices, FRAGSTATS metrics, fragmentation indices, peyzaj metriklericost-distance analysis, accumulated cost surface, least-cost corridor, en düşük maliyetli yol
Связанные433
СводкаGIS-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.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.
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ScholarGateСравнение методов: GIS-MCDA · Landscape Metrics · Least-Cost Path. Получено 2026-06-19 из https://scholargate.app/ru/compare