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Klasyfikacja obrazów teledetekcyjnych×Analiza Gorących Punktów (Getis-Ord Gi*)×
DziedzinaAnaliza przestrzennaAnaliza przestrzenna
RodzinaRegression modelRegression model
Rok powstania1970s–present1992
TwórcaSwain & Davis (1978); Lillesand & Kiefer (classical textbook treatments)Arthur Getis and J. Keith Ord
TypSupervised / unsupervised image classificationLocal spatial statistic
Źródło pierwotneLillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2015). Remote Sensing and Image Interpretation (7th ed.). Wiley. ISBN: 978-1118343289Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206. DOI ↗
Inne nazwyland cover classification, image classification, satellite image classification, spectral classificationGetis-Ord Gi* statistic, spatial hot spot detection, cluster and outlier analysis, HSA
Pokrewne45
PodsumowanieRemote 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.Hot Spot Analysis uses the Getis-Ord Gi* local spatial statistic to identify geographic locations where high or low attribute values cluster together to a degree that is statistically significant. Each feature is evaluated in relation to its neighbours, producing a z-score that flags genuine spatial hot spots and cold spots against a background of random variation.
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  3. PUBLISHED

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ScholarGatePorównaj metody: Remote Sensing Classification · Hot Spot Analysis. Pobrano 2026-06-17 z https://scholargate.app/pl/compare