Regression modelGIS / spatial

Global Remote Sensing Classification

Global 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.

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Sources

  1. Campbell, J. B., & Wynne, R. H. (2011). Introduction to Remote Sensing (5th ed.). Guilford Press. ISBN: 978-1609181765
  2. Turner, W., Rondinini, C., Pettorelli, N., Mora, B., Leidner, A. K., Szantoi, Z., ... & Woodcock, C. (2015). Free and open-access satellite data are key to biodiversity conservation. Biological Conservation, 182, 173-176. DOI: 10.1016/j.biocon.2014.11.048

Related methods

ScholarGateGlobal Remote Sensing Classification (Global Remote Sensing Image Classification). Retrieved 2026-06-04 from https://scholargate.app/en/spatial-analysis/global-remote-sensing-classification