Regression modelGIS / spatial

Remote Sensing Classification

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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Sources

  1. Lillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2015). Remote Sensing and Image Interpretation (7th ed.). Wiley. ISBN: 978-1118343289
  2. Remote sensing. Wikipedia. link

Related methods

Referenced by

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