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Fjärranalysklassificering tilldelar diskreta tematiska etiketter×Lokala indikatorer för spatial association (LISA)×
ÄmnesområdeRumslig analysRumslig analys
FamiljRegression modelRegression model
Ursprungsår1970s–present1995
UpphovspersonSwain & Davis (1978); Lillesand & Kiefer (classical textbook treatments)Luc Anselin
TypSupervised / unsupervised image classificationLocal spatial statistic
UrsprungskällaLillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2015). Remote Sensing and Image Interpretation (7th ed.). Wiley. ISBN: 978-1118343289Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗
Aliasland cover classification, image classification, satellite image classification, spectral classificationLISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA
Närliggande46
SammanfattningRemote 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.LISA, introduced by Luc Anselin in 1995, decomposes a global spatial autocorrelation index into a location-specific statistic for every observation. It identifies where statistically significant spatial clusters and outliers occur on a map, enabling researchers to move beyond a single global summary and pinpoint the geographic sources of spatial dependence.
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ScholarGateJämför metoder: Remote Sensing Classification · Local Indicators of Spatial Association. Hämtad 2026-06-19 från https://scholargate.app/sv/compare