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Klasifikace dálkového průzkumu Země×Síťová prostorová analýza×
OborProstorová analýzaProstorová analýza
RodinaRegression modelRegression model
Rok vzniku1970s–present1990s–2000s
TvůrceSwain & Davis (1978); Lillesand & Kiefer (classical textbook treatments)Atsuyuki Okabe and colleagues
TypSupervised / unsupervised image classificationSpatial network model
Původní zdrojLillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2015). Remote Sensing and Image Interpretation (7th ed.). Wiley. ISBN: 978-1118343289Okabe, A., Satoh, T., Furuta, T., Sugihara, K., & Okano, K. (2006). Generalized network Voronoi diagrams: Concepts, computational methods, and applications. International Journal of Geographical Information Science, 22(9), 965–994. DOI ↗
Další názvyland cover classification, image classification, satellite image classification, spectral classificationnetwork spatial analysis, network-constrained spatial analysis, spatial network analysis, NBSA
Příbuzné43
ShrnutíRemote sensing classification assigns discrete thematic labels — such as forest, urban, water, or cropland — to pixels in a satellite or aerial image based on their spectral, spatial, and temporal properties. It underpins land-use/land-cover mapping, change detection, environmental monitoring, and disaster response at local to global scales.Network-based spatial analysis (NBSA) analyzes the distribution and interaction of spatial phenomena constrained to a network structure — such as roads, railways, or rivers — using network distance rather than straight-line (Euclidean) distance. It is the appropriate framework whenever movement, proximity, or risk is governed by the underlying network topology rather than open space.
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ScholarGatePorovnat metody: Remote Sensing Classification · Network-Based Spatial Analysis. Získáno 2026-06-15 z https://scholargate.app/cs/compare