OpenEOcubes: openEO Compliant Lightweight R Platform for Processing Satellite Image Time Series

The service integrates STAC API (using Rstac package), the OpenEO standardized API, and data cubes concepts (using gdalcubes R package) to be a lightweight platform to enable analysis of time series satellite images via OpenEO Compliant RESTful endpoints using R-Client. It also supports users to run their custom R functions.

Motivation for the platform:

The service tries to improve on the limitations of established EO data management platforms like Google Earth Engine and Sentinel Hub by supporting:

• Reproducibility of Science
• Extensibility
• Infrastructure Replicability
• Open Governance
• No Need for User Management
• User-Defined R Functions
• Flexibility - Custom CRS, and Quick Resampling of Massive EO Data

After processing the data , one can download and explore on open source tools like QGIS, R, Python, etc.

Future developments:

Geospatial Machine Learning APIs for time-series EO Data:

• ML APIs e.g. Random Forest, SVM, XGBoost, etc.
• DL APIs e.g. TempCNN, ResNet, etc.

Currently PoC is being worked on at this reposity on the Open Earth Monitor Cyberinfrastructure EU funded project.

Easy Deployment from DockerHub

Assuming you have Docker installed. This is the easiest approach. You can get a hosted Docker image of the platform on DockerHub https://hub.docker.com/r/brianpondi/openeocubes

Running the container

It is highly recommended to deploy the service on an AWS EC2 machine that is in us-west-2 region (Oregon) as that is the data centre where the Earth Observation(EO) datasets found in AWS STAC search are stored. This enables the processing of EO data from the source so that the network latency between the platform and data is as low as possible hence cheaper. You can expose port 8080 of the EC2 instance to deploy and communicate with the service.

docker run -p 8080:8080  --env AWSHOST=<AWS-IPv4-ADDRESS>  custom/openeocubes

For light tasks and processes you can host the service on pc and therefore you don't need AWS IPv4 Address

docker run -p 8080:8080  custom/openeocubes

Easy Deployment with Docker

If you want to change the source code then this approach is recommended. You first need to clone the repository via this command:

git clone https://github.com/PondiB/openeocubes.git

then you can change to that directory

cd openeocubes

Run it :

docker-compose up

Run in detached mode :

docker-compose up -d

Shutting it down:

docker-compose down

Force restart and rebuild:

docker-compose up --build --force-recreate --no-deps -d

If there are new changes on the images or Dockerfiles:

docker-compose build --no-cache && docker-compose up

Development Notes:

While developing, you can skip rebuilding the docker container everytime. Instead you can run the server locally. Just run "Rscript startLocal.R" inside this directory.

This will compile this Repository as a R Package and start the server.