Data Catalog

Through the OpenOrbit end-to-end mission management scheme, Open Cosmos has developed a number of Earth Observation satellites, offering a range of in-orbit capabilities to meet diverse remote sensing needs.

Each of these platforms offers tasking opportunities, allowing you to request high resolution, multispectral and hyperspectral imagery of a specific location on Earth.

Access the archive of existing observations through the DataCosmos platform, and begin to explore the multiple applications that these data offer.

Data Products

The capabilities of the Open Constellation satellite fleet are outlined below. Follow the links for detailed descriptions of each product, their payloads, and the various data products they provide.

Hyper-500

Hyper-500 is provided by Hammer and Acc1.

HAMMER, which stands for Hyperspectral AI for Marine Monitoring and Emergency Response was built through key technical features with capabilities to monitor the Atlantic and help mitigate illegal fishing with near real-time data.

Acc1 is a hyperspectral Earth observation CubeSat mission developed in partnership with Open Cosmos. The satellite is designed to capture high-resolution hyperspectral imagery for various applications, including environmental monitoring, energy, agriculture, and resource management.

Hyperspectral insights
The Hyperspectral Imager captures images across dozens of narrow spectral bands, offering detailed information about the composition of objects or scenes enabling applications for environmental monitoring.

Multi-500

Multi-500 is a product generated by satellites such as Menut and Platero.

Menut is the second satellite of Catalonia’s NewSpace Strategy. Promoted by the Government of Catalonia and the Institut d’Estudis Espacials de Catalunya (IEEC). MENUT is a six-unit CubeSat weighing less than 10 kg, with a mission to observe Earth in order to improve spatial planning and help understand the effects of the climate crisis.

Platero Commissioned by the Junta de Andalucia through AGAPA and co-financed by FEDER in the SmartFood project, the PLATERO satellite integrates Earth Observation, IoT, and AI on-board processing. Part of LifeWatch ERIC, it monitors biodiversity, desertification, emergencies, and farming effects to inform environmental policies and promote sustainable farming in the region.

The satellites can take images at 4.75m ground sampling distance at any location around the world.

VNIR-250

VNIR-250 is provided by the Mantis satellite.

MANTIS, which stands for Mission Agile Nanosatellite for Terrestrial Imagery Services, is the first satellite launched as part of ESA InCubed, the co-funding programme run by the ESA Φ-lab which focuses on commercial development activities across the entire Earth observation (EO) value chain.

AI On-board
MANTIS hosts an innovative multispectral, high-resolution optical payload for EO and a secondary payload, a high-performance and reconfigurable processing unit aimed at exploiting the power of Artificial Intelligence to derive insights onboard.

SWIR-5000

ALISIO-1 is a 6U satellite built by Open Cosmos for IACTEC-Espacio. The satellite is used to monitor the global environment and provide data for a variety of applications, including agriculture, forestry, and disaster management.

Unleashing Global Connectivity
ALISIO-1 is equipped with a DRAGO-2 infrared camera and a CubeLCT laser communications terminal. The DRAGO-2 camera provides high-resolution images of the Earth's surface in the infrared spectrum. The laser communications terminal allows the satellite to transmit data at high speeds to ground stations.

Phisat 2

Phisat 2 uses the same payload as Platero and Menut, but the delivery strategy is different.

Image processing level

Image processing levels refer to the stages of data processing from raw sensor measurements to refined, usable products.

Image processing level descriptions may vary between satellite data providers, this description is meant as a broad overview of Open Constellation satellites.

Level 0 (L0)

• Raw image converted from binary - limited image processing

Level 1A (L1A)

The Level 1A processor's primary function is to unpack the raw payload binaries, generate raster data (separated bands) in COG format (Cloud Optimized GeoTIFF), and retrieve radiometric coefficients. The processor also attaches a coarse affine geotransform solely based in platform ancillary data, without altering the sensor geometry of the data.

1. Data Unpacking: The raw payload binaries are unpacked to extract image data into COG format and payload metadata
2. Coarse Georeferencing: A preliminary camera model, based on the platform ancillary data (position and attitude), is used to project the 4 corners of the stripe from the image space to the object space, and determine an affine transformation. The data is still stored in sensor geometry.
3. Radiometric Coefficients Computation: Radiometric coefficients are computed and appended to the data images as additional metadata. Their computation requires access to the imaging parameters (number of TDI stages, exposure time) and metadata (temperatures during acquisition).
4. Radiometric Correction: The processor applies the following radiometric corrections:
   1. Dark count correction: Subtract the dark level for each pixel. This is done determining the acquisition temperature for each line, and using it to evaluate a linear model and retrieve the column dark level.
   2. Pixel non-uniformity correction: Equalize using a per-column correction (same for all rows of the linescan capture).
   3. Absolute coefficients calibration: Evaluate a linear model using the DNs to retrieve the radiance value.
   4. Defective pixel identification and interpolation.

Level 1B (L1B)

The Level 1B processor applies radiometric correction to provide calibrated ToA radiances in sensor geometry. The data is stored in unsigned integer format with associated metadata per band to convert to ToA radiance. It also performs geometric correction and calibration by coregistering all bands to a common reference, generating an initial solution for RPCs using the camera model, extracting ground control points from a reference raster (GRI), and refining the RPCs.

1. Band Alignment: Define a reference band, define a grid over it, and find the best matching feature between reference and candidate band. A 2D deformation map is generated, so that the band can be warped into the reference to minimize band misalignment.
2. Initialize RPCs: Define a 3D grid over the scene space and use the camera model and a DEM to get a dense set of Image(line,column)-Scene (X,Y,Z) points. Then, find the coefficients that minimize the RPC residuals.
3. Extract GCPs: Determine the approximate overlap of the scene with a reference image using the coarse geotransform. Define a grid and try to find matching points for each cell. Filter the candidate GCPs to remove outliers.
4. Refine RPCs: Use the GCPs to refine the initial RPCs so that the final geoaccuracy meets the target value.

Level 1C (L1C)

The Level 1C processor is responsible for converting ToA radiances to ToA reflectances and applying the geometric model with terrain correction and projection in cartographic geometry.

1. ToA Radiance to Reflectance Conversion: ToA radiances are converted to ToA reflectances, taking into account the acquisition geometry (sun and sensor relative position with respect to the scene). The data is stored in unsigned integer where reflectance is scaled between 0 and 10,000.
2. Geometric Model Application (orthorectification): The geometric model (RPC) is applied to image data, using a Digital Elevation Model (DEM). In a nutshell, a grid with the desired spatial resolution is defined across the XY scene space, and the corresponding Z is obtained from the DEM. Then, the radiometric value for each of these XYZ points is retrieved by locating the associated line-column coordinate and performing interpolation.

For MANTIS, Orthorectification happens at L1D processing level.

Level 2A water (L2Aw)

The level 2Aw applies atmospheric correction to the level L1C reflectances to retrieve surface reflectances over water bodies. The atmospheric correction algorithm is applied using the Acolite model for aquatic applications.

Summary

Summary of Image processing levels available for Open Constellation satellites.

(✔) Available (✳) Coming soon (✶) Processed by customer

Glossary