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خانوادهRegression modelRegression model
سال پیدایش1970s–1980s (pixel-based global classifiers); global land-cover products 1990s–2000s1950
پدیدآورRosenfeld & Kak; Jensen; Campbell & Wynne (textbook codifications)P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
نوعSupervised / unsupervised image classificationSpatial statistic / exploratory spatial data analysis
منبع بنیادینCampbell, J. B., & Wynne, R. H. (2011). Introduction to Remote Sensing (5th ed.). Guilford Press. ISBN: 978-1609181765Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗
نام‌های دیگرglobal pixel-based classification, global image classification, wall-to-wall remote sensing classification, global land cover classificationspatial dependence, geographic autocorrelation, spatial clustering measure, SA
مرتبط35
خلاصهGlobal Remote Sensing Classification assigns every pixel across an entire image or worldwide dataset to a discrete land-cover or thematic class. Treating the scene uniformly — rather than adapting to local subregions — this wall-to-wall approach underpins continental and global land-cover products such as GlobCover, FROM-GLC, and ESA CCI Land Cover.Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations.
ScholarGateمجموعه‌داده
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  3. PUBLISHED

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ScholarGateمقایسهٔ روش‌ها: Global Remote Sensing Classification · Spatial Autocorrelation. بازیابی‌شده در 2026-06-17 از https://scholargate.app/fa/compare