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Overview

  • Introduction
  • Glossary
  • Changelog

Setup

  • Introduction
  • Digital Earth Australia Sandbox
  • National Computational Infrastructure
  • Jupyter Notebooks

User Guide

  • Beginner’s guide
  • DEA datasets
  • Frequently used code
    • Open and run analysis on multiple polygons
    • Generating animated time series using xr_animation
    • Applying WOfS Bitmasking
    • Calculating band indices
    • Extracting contour lines
    • Detecting seasonality
    • Exporting cloud-optimised GeoTIFF files
    • Exporting data to NetCDF files
    • Integrating external data from a CSV
    • ERA5 Climate Gridded Data
    • Generating composite images
    • Generating geometric median composites (geomedians)
    • Image segmentation
    • Displaying satellite imagery on a web map
    • Machine learning with the Open Data Cube
    • Masking data
    • Opening GeoTIFF and NetCDF files with xarray
    • Pan-sharpening Landsat using the Brovey Transform
    • Polygon drill
    • Polygonising pixel edges
    • Principal component analysis for multi-spectral data
    • Rasterizing vectors & vectorizing rasters
    • Reprojecting datacube and raster data
    • Combining satellite data with tidal modelling using OTPS
    • Using load_ard to load and cloud mask multiple satellite sensors
    • Loading data using virtual products
    • Working with time in Xarray
  • Real-world examples

Index

  • Tags Index
Digital Earth Australia
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  • Frequently used code
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Frequently used code¶

A recipe book of simple code examples demonstrating how to perform common geospatial analysis tasks using DEA and open-source software.

Frequently Used Code

  • Open and run analysis on multiple polygons
  • Generating animated time series using xr_animation
  • Applying WOfS Bitmasking
  • Calculating band indices
  • Extracting contour lines
  • Detecting seasonality
  • Exporting cloud-optimised GeoTIFF files
  • Exporting data to NetCDF files
  • Integrating external data from a CSV
  • ERA5 Climate Gridded Data
  • Generating composite images
  • Generating geometric median composites (geomedians)
  • Image segmentation
  • Displaying satellite imagery on a web map
  • Machine learning with the Open Data Cube
  • Masking data
  • Opening GeoTIFF and NetCDF files with xarray
  • Pan-sharpening Landsat using the Brovey Transform
  • Polygon drill
  • Polygonising pixel edges
  • Principal component analysis for multi-spectral data
  • Rasterizing vectors & vectorizing rasters
  • Reprojecting datacube and raster data
  • Combining satellite data with tidal modelling using OTPS
  • Using load_ard to load and cloud mask multiple satellite sensors
  • Loading data using virtual products
  • Working with time in Xarray
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