- 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
Data & Processing
Sentinel-2: Resolution Enhancer (s2enh)
The products of the Copernicus satellites over the past years have contributed to many projects that have resulted in a significant improvement in the standard of living and have developed a trend in the demand for satellite data.
Sentinel-2 satellite images, or more precisely their resolution, have not always proved to be 100% sufficient for projects that required greater precision.
By leveraging technology based on the latest capabilities such as artificial intelligence and machine learning, as well as experience with satellite imagery, a solution has been achieved. The combination resulted in a hybrid solution, which allows for object enhancement in images for 8 spectral channels with simultaneous preservation of radiometric quality, which is essential for example in natural environment analysis.
The result of the processing is a multilayer geoTIFF file prepared on the basis of the Sentinel-2 L2A product. The usage of the solution gives the possibility to access current and historical data of the Sentinel-2 system in the so far unavailable resolution of 2.5m GSD.
Sentinel-2: Resolution Enhancer solution brings with it many benefits that come from greater detail, which in basic imaging has not been available so far. The solution allows for:
- The ability to identify buildings,
- Clear boundaries between fields,
- Increased precision of environmental analyses,
- Ability to automate analysis of smaller objects e.g. narrow agricultural plots, roads.
The s2enh processor, just like the other processors available on the CREODIAS platform, is accessed via the Finder tool. Each user can easily and quickly use the processor by choosing the area of interest, the time period from which products are needed and then make an order, additionally choosing the location of the results in the form of a private object storage bucket.
The solution based on serverless processing simplifies the form of service and billing to the maximum.
This allows the user to:
- Billing for processing per square kilometer,
- Only the size of the area of interest is calculated and not the whole Sentinel tile,
- It is possible to process a small area continuously based on the Sentinel time series,
- No minimum area order size/value as with commercial satellites
Use the arrows and swipe to compare the image of 10 m and 2.5 m resolutions
