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Prostorno-vremenska klasifikacija daljinskog osmatranja×Prostorno-vremenska prostorna autokorelacija×
OblastProstorna analizaProstorna analiza
PorodicaRegression modelRegression model
Godina nastanka1980s-2000s1981–1992
TvoracWoodcock, Zhu, and remote sensing communityCliff & Ord; extended by Anselin and others
TipMulti-temporal image classificationSpatial autocorrelation statistic
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 ↗Clifford, P., Richardson, S., & Hemon, D. (1989). Assessing the significance of the correlation between two spatial processes. Biometrics, 45(1), 123–134. DOI ↗
Drugi nazivimulti-temporal remote sensing classification, spatio-temporal image classification, temporal remote sensing analysis, STRSCSTSA, spatiotemporal autocorrelation, space-time Moran's I, temporal spatial dependence
Srodne45
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.Space-Time Spatial Autocorrelation extends classic spatial autocorrelation measures — most notably Moran's I — to data that vary across both geographic units and time periods. It detects whether nearby locations that are also temporally close tend to share similar attribute values, revealing clusters, trends, or anomalies that purely spatial or purely temporal analyses would miss.
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ScholarGateUporedite metode: Space-Time Remote Sensing Classification · Space-Time Spatial Autocorrelation. Preuzeto 2026-06-17 sa https://scholargate.app/sr/compare