Get our prerendered Sentinel-2 cloudless as map cache or create your own layer using our mapping optimized source mosaics for web maps or desktop GIS tools.
Sentinel-2 cloudless 2018 single-file
Viewing Ready - Get the prerendered map used at s2maps.eu (mosaic combined with bathymetry and ocean mask) both as GeoPackage and MapCache SQLite file for self-hosting or offline usage.
Sentinel-2 cloudless 2016 single-file
Sentinel-2 cloudless 2018 GeoTIFFs
Get off-the-shelf multispectral mosaic data from Sentinel-2 or define a custom mosaic tailored for your needs for further analysis and processing.
EOxCloudless Sentinel-2 2018 8bit
Exploitation Starter - Get the global mosaic as a 4 band (RGB + NIR) GeoTIFF tile dataset for basic analysis.
EOxCloudless Sentinel-2 2018 16bit
Refined satellite data
EOxCloudless preprocesses raw satellite imagery to cloudless and seamless satellite data coverage. No more manual preselection of good scenes. No more unnecessary fetching of unusable data. No more data stitching. Just define time of interest and let us do the work.
Every use case has its specific requirements. To be able to meet these requirements we developed a couple of different methods to extract the optimum pixels from image stacks to get the best data coverage for you.
From regional to global mosaics at full resolution: Our platform is designed for cloud computing and scales with your needs.
Original Metadata, full traceability
By retaining original metadata, our products enable tracing back to individual input satellite images on a per-pixel basis.
Multiple sensors, countless applications
We accommodate processing of both optical and radar data. Complementing our Sentinel-2 dataset with Sentinel-1 on-demand processing, we offer unprecedented possibilities for monitoring applications.
The world is in constant change - our products allow comparing different points in time, enabling analysis and monitoring of natural and man-made development.
EOxCloudless enables continuous agricultural monitoring of spatial areas of any size by using higher level optical data or even a combination of optical and radar data together with optimized time intervals.