- What is CREODIAS?
- Computing & Cloud
- Data & Processing
- Pricing Plans
- Fight with COVID-19
- Examples of usage
- 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
Your Processing Environment
Use of SNAP and QGIS on a CREODIAS Virtual Machine
The CREODIAS platform is designed to be flexible. Satellite data can be downloaded from the platform through a number of services like OGC, NFS, S3 and the CREODIAS Finder API. However, the platform has been designed to minimise the need to download large amounts of satellite data and perform processing and analysis of data on the CREODIAS platform itself. To facilitate this, users of CREODIAS can use a Virtual Machine (VM). Currently, a wide range of VM images are available that can be installed quickly on CREODIAS, currently there are 17 options. For Linux users, there are CentOS, Red Hat, SUSE and Ubuntu images available, as well as OpenVPN and OSGEO images. These are very useful for users that want to access and process large amounts of data. However, for simpler tasks the most commonly used OS, Windows is often more user-friendly.
Once a Windows-based virtual machine is installed, the CREODIAS platform can be accessed via Remote Desktop. From now on, the VM works as if you were working on any Windows PC. Programs such as ESA SNAP or QGIS can be installed by users themselves on request.
Satellite data access
Accessing the satellite data stored on the platform can be done through a mounted network drive in the File Explorer. This shows immediately the advantage of using a VM on the CREODIAS platform, there is no need to download any satellite data to your computer, they are already present and ready to be used for further processing inside the VM. Suitable satellite imagery can be searched in the CREODIAS Finder and be accessed by copying the file path into ESA SNAP, QGIS or any other preferred software and start working on it straightaway.
Through CREODIAS Finder it is also possible to create a task to convert Sentinel-2 L1C data to atmospherically correct L2A data. For this, any L1C image can be selected and ordered by adding the sen2cor processing task. It generates the L2A product directly and will be available within half an hour.
Screenshot of Windows VM environment
Use cases
Sentinel-2 data is often used to estimate health and development of agricultural crops. To achieve this through the VM in CREODIAS, a required Sentinel-2 image can be loaded directly into ESA SNAP and be pre-processed to biophysical parameters like NDVI, fAPAR or LAI. In the screenshot below, biophysical parameter processing of Sentinel-2 data in SNAP is shown, with fAPAR, fCover and LAI parameters shown.
Screenshot of Windows VM environment
Use potential
The use of a VM on CREODIAS offers a safe cloud-based access to large Sentinel and other satellite data sources data, as well as processing and analysis capabilities. This is all possible in a familiar (Windows) environment, without advanced programming and coding skills needed. The VM is highly customisable, it can easily be adapted to the user’s needs and wishes.