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時空間リモートセンシング分類×リモートセンシング分類×
分野空間分析空間分析
系統Regression modelRegression model
提唱年1980s-2000s1970s–present
提唱者Woodcock, Zhu, and remote sensing communitySwain & Davis (1978); Lillesand & Kiefer (classical textbook treatments)
種類Multi-temporal image classificationSupervised / unsupervised image classification
原典Zhu, 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
別名multi-temporal remote sensing classification, spatio-temporal image classification, temporal remote sensing analysis, STRSCland cover classification, image classification, satellite image classification, spectral classification
関連44
概要Space-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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  3. PUBLISHED

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ScholarGate手法を比較: Space-Time Remote Sensing Classification · Remote Sensing Classification. 2026-06-15に以下より取得 https://scholargate.app/ja/compare