EnMAP-Box 3 Logo

General

  • About
  • FAQ & Troubleshooting
  • How to contribute
  • Roadmap
  • Glossary

User Section

  • Installation
  • Getting Started
  • Cookbook
  • User Manual
    • The GUI
    • Spectral Libraries
    • Tools
    • Applications
    • Processing Algorithms
      • Auxilliary
      • Classification
      • Clustering
      • Convolution, morphology and filtering
      • Dataset creation
        • Create classification dataset (from categorized raster layer and feature raster)
        • Create classification dataset (from categorized spectral library)
        • Create classification dataset (from categorized vector layer and feature raster)
        • Create classification dataset (from categorized vector layer with attribute table)
        • Create classification dataset (from Python code)
        • Create classification dataset (from table with categories and feature fields)
        • Create classification dataset (from text files)
        • Create regression dataset (from continuous-valued layer with attribute table)
        • Create regression dataset (from continuous-valued raster layer and feature raster)
        • Create regression dataset (from continuous-valued spectral library)
        • Create regression dataset (from continuous-valued vector layer and feature raster)
        • Create regression dataset (from Python code)
        • Create regression dataset (from table with target and feature fields)
        • Create regression dataset (from text files)
        • Create regression dataset (SynthMix from classification dataset)
        • Create unsupervised dataset (from feature raster)
        • Create unsupervised dataset (from Python code)
        • Create unsupervised dataset (from spectral library)
        • Create unsupervised dataset (from text file)
        • Create unsupervised dataset (from vector layer with attribute table)
        • Merge classification datasets
        • Random samples from classification dataset
        • Random samples from regression dataset
        • Select features from dataset
      • Export data
      • Feature selection
      • Import data
      • Masking
      • Raster analysis
      • Raster conversion
      • Raster miscellaneous
      • Raster projections
      • Regression
      • Spectral resampling
      • Transformation
      • Vector conversion
      • Vector creation
    • Test dataset
  • Application Tutorials
  • Workshop Tutorials

Developer Section

  • Installation
  • EnMAP-Box repository
  • Build and publish the EnMAP-Box
  • Dev Cookbook
  • Create EnMAP-Box Applications
  • RFC list
EnMAP-Box 3
  • Docs »
  • User Manual »
  • Processing Algorithms »
  • Dataset creation
  • Edit on Bitbucket

Dataset creationΒΆ

  • Create classification dataset (from categorized raster layer and feature raster)
  • Create classification dataset (from categorized spectral library)
  • Create classification dataset (from categorized vector layer and feature raster)
  • Create classification dataset (from categorized vector layer with attribute table)
  • Create classification dataset (from Python code)
  • Create classification dataset (from table with categories and feature fields)
  • Create classification dataset (from text files)
  • Create regression dataset (from continuous-valued layer with attribute table)
  • Create regression dataset (from continuous-valued raster layer and feature raster)
  • Create regression dataset (from continuous-valued spectral library)
  • Create regression dataset (from continuous-valued vector layer and feature raster)
  • Create regression dataset (from Python code)
  • Create regression dataset (from table with target and feature fields)
  • Create regression dataset (from text files)
  • Create regression dataset (SynthMix from classification dataset)
  • Create unsupervised dataset (from feature raster)
  • Create unsupervised dataset (from Python code)
  • Create unsupervised dataset (from spectral library)
  • Create unsupervised dataset (from text file)
  • Create unsupervised dataset (from vector layer with attribute table)
  • Merge classification datasets
  • Random samples from classification dataset
  • Random samples from regression dataset
  • Select features from dataset
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© Copyright 2018-2022, Andreas Janz, Benjamin Jakimow, Fabian Thiel, Sebastian van der Linden, Patrick Hostert Revision 09:43:00.

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