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Klasifikacija svemirsko-vremenskih daljinskih istraživanja×Klasifikacija daljinskih istraživanja×
PodručjeProstorna analizaProstorna analiza
ObiteljRegression modelRegression model
Godina nastanka1980s-2000s1970s–present
TvoracWoodcock, Zhu, and remote sensing communitySwain & Davis (1978); Lillesand & Kiefer (classical textbook treatments)
VrstaMulti-temporal image classificationSupervised / unsupervised image classification
Temeljni izvorZhu, Z. (2017). Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications. ISPRS Journal of Photogrammetry and Remote Sensing, 130, 370-384. DOI ↗Lillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2015). Remote Sensing and Image Interpretation (7th ed.). Wiley. ISBN: 978-1118343289
Drugi nazivimulti-temporal remote sensing classification, spatio-temporal image classification, temporal remote sensing analysis, STRSCland cover classification, image classification, satellite image classification, spectral classification
Srodne44
SažetakSpace-Time Remote Sensing Classification extends standard image classification to multi-temporal satellite or aerial imagery, enabling analysts to track land cover change, phenological cycles, and environmental dynamics across both space and time. By incorporating the temporal dimension, classifiers achieve higher accuracy and can detect transitions that a single-date analysis would miss.Remote 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.
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ScholarGateUsporedite metode: Space-Time Remote Sensing Classification · Remote Sensing Classification. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare