Comparar métodos

	Métricas de Patrones del Paisaje	Detección de Comunidades
Campo	Análisis espacial	Análisis de redes
Familia	Process / pipeline	Process / pipeline
Año de origen	1988	2002–2019 (algorithm family)
Autor original	R. V. O'Neill et al.; McGarigal & Marks (FRAGSTATS)	Louvain: Blondel et al. (2008); Leiden: Traag et al. (2019); Girvan-Newman: Girvan & Newman (2002); Infomap: Rosvall & Bergstrom (2008)
Tipo	Quantitative landscape pattern description	Graph-partitioning / clustering algorithm family
Fuente seminal	O'Neill, R. V., et al. (1988). Indices of landscape pattern. Landscape Ecology, 1(3), 153–162.	Blondel, V.D., Guillaume, J.-L., Lambiotte, R. & Lefebvre, E. (2008). Fast Unfolding of Communities in Large Networks. Journal of Statistical Mechanics, 2008(10), P10008.
Alias	landscape pattern indices, FRAGSTATS metrics, fragmentation indices, peyzaj metrikleri	graph clustering, network partitioning, Topluluk Tespiti (Louvain, Girvan-Newman, Leiden)
Relacionados	3	5
Resumen	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.	Community detection is a family of graph-partitioning algorithms that discover densely connected sub-groups — communities — within a network. First formalised through the modularity measure by Girvan and Newman (2002), the field advanced rapidly with the Louvain method (Blondel et al., 2008), the Leiden refinement (Traag et al., 2019), and the information-theoretic Infomap approach. All variants answer the same question: which nodes cluster together more tightly among themselves than with the rest of the network?