eo-learn
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Contents:
Introduction
Installation
Overview of
eolearn.core
EOTasks
Examples
Land Use and Land Cover
How To: Land-Use-Land-Cover Prediction for Slovenia
Part 1
Part 2
Water Monitor
Measuring the water level of a Theewaterskloof Dam in South Africa
Plot results
IO Examples
Example showcasing IO tasks
Data masks
Example of generation of valid data mask using a predicate
Visualizations
EOPatch visualization
Timelapse
Creating timelapse animations
Package content
Contributing to
eo-learn
eo-learn
Examples
Edit on GitHub
Examples
Land Use and Land Cover
How To: Land-Use-Land-Cover Prediction for Slovenia
Before you start
Requirements
Overview
Part 1:
Part 2:
Part 1
1. Define the Area-of-Interest (AOI):
Get country boundary
Split to smaller tiles and choose a 5x5 area
Visualize the selection
2. - 4. Fill EOPatches with data:
Define some needed custom EOTasks
Define the workflow tasks
Help! I prefer to calculate cloud masks of my own!
Reference map task
Define the workflow
Visualize the patches
Visualize the reference map
Plot the map of valid pixel counts
Spatial mean of NDVI
Temporal mean of NDVI
Plot the average cloud probability
Part 2
5. Prepare the training data
Define EOTasks
Run the EOWorkflow over all EOPatches
6. Model construction and training
Set up and train the model
7. Validation
Plot the standard and transposed Confusion Matrix
ROC curves and AUC metrics
Most important features
8. Visualization of the results
Define EOTasks
Define Tasks and the Workflow
Run the prediction and export to GeoTIFF images
Visualise the prediction
Visual inspection of patches
Water Monitor
Measuring the water level of a Theewaterskloof Dam in South Africa
Imports
Water level extraction EOWorkflow
Load the Polygon of nominal water extent and define a
BBox
Step 1: Intialize (and implement workflow specific) EOTasks
Create an EOPatch and add all EO features (satellite imagery data)
Burn in the nominal water extent
The cloud mask is already provided by Sentinel Hub, we use it to calulcate the valid data mask.
Apply Water Detection
Step 2: Define the EOWorkflow
Step 3: Run the workflow
Plot results
IO Examples
Example showcasing IO tasks
Prerequisites
Sentinel Hub account
Credentials
Request different types of layers and data collections to an eopatch
General parameters
Tasks
Task for Sentinel-2 L1C data
Task for retrieving NDVI index
Task for Digital Elevation Model Data
Task for Sentinel-2 L2A and SCL data
Tasks for saving/outputting the eopatch
Run workflow
Plot results
Sentinel-2 L1C RGB bands
NDVI data
NDWI data
Sentinel-2 L2A RGB bands
Sentinel-2 Scene Classification Layer (from Sen2cor)
Mapzen Digital Elevation Model
Load the saved eopatch from disk
Data masks
Example of generation of valid data mask using a predicate
Workflow to merge the cloud mask with the mask defining where reflectance data is available
Run workflow
Plot results
Visualizations
EOPatch visualization
Basics
Plotting filters and configurations
Types of plots
Timelapse
Creating timelapse animations
1. Define tasks
1.1 Download Task
1.2 Filter Task
2. Create and execute workflow
3. Create animation