- What is CREODIAS?
- Computing & Cloud
- Data & Processing
- Pricing Plans
- Fight with COVID-19
- Examples of usage
- EO Data Access (R)evolution
- Land cover classification using remote sensing and AI/ML technology
- AI-based satellite image enhancer and mosaicking tools
- Monitoring air pollution using Sentinel-5P data
- Species classification of forests
- Enabling AI / ML workflows with CREODIAS vGPUs
- Satellite remote sensing analyses of the forest
- Satellite-based Urban Heat Island Mapping on CREODIAS
- Old but gold - historical EO data immediately available and widely used on CREODIAS
- CREODIAS for emergency fire management
- AgroTech project as an example of how CREODIAS can be used for food and environmental research
- Monitoring Air Quality of Germany in Pre vs During COVID Lockdown Period
- EO4UA
- Common Agricultural Policy monitoring with Earth Observation
- Applications of CREODIAS data
- Meteorological data usage on the CREODIAS platform
- Building added value under Horizon Europe with CREODIAS
- CREODIAS: Introduction to SAR Sentinel-1 data
- Land subsidence and landslides monitoring based on satellite data
- Satellite imagery in support of the Common Agriculture Policy (CAP) and crop statistics
- Useful tools for data processing, available on CREODIAS platform
- CREODIAS for hydrological drought modelling
- CREODIAS for managing Urban Heat Islands
- CREODIAS for Digitising Green Spaces
- CREODIAS for Air Quality
- Advanced data processors on CREODIAS
- CREODIAS for your application
- Solutions for agriculture with CREODIAS
- Earth Observation data for Emergency response
- Security Applications with Satellite Data
- Climate Monitoring with Satellite Data
- Water Analysis on CREODIAS
- CREODIAS for land and agriculture monitoring
- Solutions for atmospheric analysis
- Example of tool usage
- Processing EO Data and Serving www services
- Processing and Storing EO
- Embedding OGC WMS Services into Your website
- GPU Use Case
- Using the EO Browser
- EO Data Finder API Manual
- Use of SNAP and QGIS on a CREODIAS Virtual Machine
- Use of WMS Configurator
- DNS as a Service - user documentation
- Use of Sinergise Sentinel Hub on the CREODIAS EO Data Hub
- Load Balancer as a Service
- Jupyter Hub
- Use of CREODIAS Finder for ordering data
- ESRI ArcGIS on CREODIAS
- Use of CEMS data through CREODIAS
- Searching, processing and analysis of Sentinel-5P data on CREODIAS
- ASAR data available on CREODIAS
- Satellite remote sensing analyses of the forest
- EO Data Catalogue API Manual
- Public Reporting Dashboards
- Sentinel Hub Documentation
- Legal Matters
- FAQ
- News
- Partner Services
- About Us
- Forum
- Knowledgebase
Example of usage
Enabling AI / ML workflows with CREODIAS vGPUs
Machine Learning presents an attractive opportunity for supplementing or substituting traditional methods of data processing, including Earth Observation data. Training and tuning ML models are most efficient with a quick feedback loop on the training results. That is where GPUs show their great performance advantage over running the training on regular CPUs.
CREODIAS users working on the WAW3-1 cloud get flexible access to powerful vGPU-enabled machines, along with integrated access to Earth Observation data. This combination enables users to quickly start building and deploying their own AI/ML models.
To get started with AI applications, users can now access new articles about Machine Learning in the knowledge base. These articles provide instructions for installing popular ML libraries TensorFlow and Keras on CREODIAS. They also present a sample deep learning workflow of classifying satellite images that can serve as a reference for further own exploration.
To learn more, see the reference links to the sections below:
- How To Create a New Linux VM With NVIDIA Virtual GPU in the OpenStack Dashboard Horizon on CREODIAS
- Install TensorFlow on WAW3-1 vGPU enabled VM on CREODIAS
- Install TensorFlow on Docker Running on CREODIAS WAW3-1 vGPU Virtual Machine
- Sample Deep Learning workflow using WAW3-1 vGPU and EO DATA on Creodias
- Sample Deep Learning Workflow Using TensorFlow Running on Docker on Creodias WAW3-1 vGPU Virtual Machine
We also encourage users to watch a webinar Using GPU for AI & EO applications, where experts present some practical EO-oriented machine learning scenarios.