README.md

qgis-earthengine-examples

A collection of 270+ Python examples for using Google Earth Engine in QGIS

Contact: Qiusheng Wu (https://wetlands.io)

1. Description

This repository is a collection of 270+ Python examples for the Google Earth Engine plugin for QGIS. I developed these Python examples by converting all the JavaScript examples (except those not yet supported by plugin) from the Google Earth Engine API Documentation. Additionally, some examples were adapted from Gena's examples and the Earth Engine API examples. Kudos to Gennadii Donchyts for developing this amazing Google Earth Engine plugin for QGIS.

2. Usage

• Step 1: Sign up for Google Earth Engine.
• Step 2: Install QGIS.
• Step 3: Install the Google Earth Engine Plugin for QGIS and authenticate Google Earth Engine.
• Step 4: Git clone or download this repository.
• Step 5: Open the Python console in QGIS and load any downloaded Python script into the QGIS Python Editor.
• Step 6: Click the Run script button on the Python Editor to execute the script.
• Step 7: Zoom in/out the QGIS Canvas to inspect the results.

3. Demo

4. Examples

The Table of Contents below mimics the structure of the Google Earth Engine API Documentation. I strongly encourage you to check out the API Documentation if you need an in-depth explanation of each Python example. Please note that the list below does not include all the Python examples contained in this repository. You are welcome to explore the repository and find more examples to suit your needs.

Get Started

• Hello world!
• Adding data to QGIS
• Finding images
• Band math
• Mapping (what to do instead of a for-loop)
• Reducing
• Image statistics
• Masking
• A complete example

Machine Learning

• Supervised Classification Algorithms
  • Classification and Regression Trees (CART) | Support Vector Machine (SVM) | Confusion Matrix
• Unsupervised Classification Algorithms
  • KMeans Clustering

Image

• Image Overview
• Image Visualization
• Image information and metadata
• Mathematical operations
• Relational, conditional and Boolean operations
• Convolutions
• Morphological Operations
• Gradients
• Edge detection
• Spectral transformations
• Texture
• Object-based methods
• Cumulative Cost Mapping
• Registering Images
• Miscellaneous
  • Band statistics (min, max, mean, std) | Image statistics by band | Extract value to points | Rename bands | Clipping | Find image by path and row | Get image resolution | Get image extent | Set image properties | Select bands | Convert bands to ImageCollection | Reclassify | Composite bands | Image smoothing | Download image | Cell statistics | Image patch area | Get image id | Get band name and type | Filtering by calendar range

ImageCollection

• ImageCollection Overview
• ImageCollection Information and Metadata
• Filtering an ImageCollection
• Mapping over an ImageCollection
• Reducing an ImageCollection
• Compositing and Mosaicking
• Miscellaneous
  • Get image centroid | Convert ImageCollection to Image | Sort by cloud and date | Filtering by metadata | Filtering by band names | Select image by index | Creating monthly imagery

Geometry, Feature, FeatureCollection

• Geometry Overview
• Geodesic vs. Planar Geometries
• Geometry Visualization and Information
• Geometric Operations
• Feature Overview
• FeatureCollection Overview
• Feature and FeatureCollection Visualization
• FeatureCollection Information and Metadata
• Filtering a FeatureCollection
• Mapping over a FeatureCollection
• Reducing a FeatureCollection
• Vector to Raster Interpolation
• Miscellaneous
  • Add new attribute | Add area column | Add random value column | Single column statistics | Multiple column statistics | Simplify polygons | Column statistics by group | Select by location | Select by attributes | Select by strings | Vector symbology | Merge FeatureCollection | Search by buffer distance | Select columns | Mimimum bounding geometry | Clipping polygons

Reducer

• Reducer Overview
• ImageCollection Reductions
• Image Reductions
• Statistics of an Image Region
• Statistics of Image Regions
• Statistics of Image Neighborhoods
• Statistics of FeatureCollection Columns
• Raster to Vector Conversion
• Vector to Raster Conversion
• Grouped Reductions and Zonal Statistics
  • Statistics by group | Zonal Statistics
• Weighted Reductions
• Linear Regression

Join

• Simple Joins
• Inverted Joins
• Inner Joins
• Save-All Joins
• Save-Best Joins
• Spatial Joins

Array

• Arrays and Array Images
• Array Transformations
• Eigen Analysis
• Array Sorting and Reducing

Specialized Algorithms

• Landsat Algorithms
  • Radiance | Surface Reflectance | Simple cloud score | Simple composite
• Sentinel-1 Algorithms
• Resampling and Reducing Resolution
  • Resampling | Reducing Resolution
• Linear fit
• Pattern recognition
  • Center-pivot Irrigation Detector

Asset Management

• Exporting Image
• Exporting ImageCollection
• Exporting Vector
• Exporting FeatureCollection
• Exporting CSV
• Exporting Table
• Exporting TimeSeries

How Earth Engine Works

• Client vs. Server
• Deferred Execution
• Projections

Filter

• Filter to metadata equal to the given value
• Filter to metadata not equal to the given value
• Filter on metadata contained in a list
• Filter on metadata that cotains a certain string
• Filter on metadata that starts with a certain string
• Filter on metadata that ends with a certain string
• Filter on metadata that falls within a specified range

Visualization

• RGB composite
• Color palettes
• Color ramp
• Hillshade
• Image stretch
• Image thumbnail
• Rendering categorical maps
• Styled layer descriptors
• Terrain visualization
• Visualizing FeatureCollection
• Visualizing Geometry
• NLCD Land Cover
• US Counties
• Miscellaneous
  • NDVI symbology | NDWI symbology | Landsat symbology | NWI wetlands symbology | Color by attribute | Random color visualizer

Datasets

• Terrain
• Water

Gena's Examples

• Map.addLayer() | Map.centerObject() | Map.setCenter()