Most of your image analysis tasks that required ENVI or Erdas Imagine software are now available online thanks to EOS Platform. This new game-changing cloud service launched by EOS Data Analytics provides GIS professionals with a one-stop solution for search, analysis, storing, and visualization of large amounts of geospatial data.
With EOS Platform you get access to an ecosystem of four mutually integrated EOS products, which together provide a powerful toolset for geospatial analysts. Image data is stored in cloud-based EOS Storage and is available for image processing or remote sensing analysis at any time; this can be a raw user file, imagery obtained from LandViewer or an output file from EOS Processing.
A list of EOS Processing workflows that can be filtered by industry, input data type
There are at least two reasons why image processing is the platform’s major asset: the processing of large data amounts runs online and offers as many as 16 workflows with even more coming soon. On top of that, users can get the best cartographic features of EOS Vision for vector data visualization and, as announced for the future, its analysis.
Data agnostic platform
When it comes to raster data, you can work with a variety of satellite and airborne datasets in LandViewer, EOS Processing, and EOS Storage. Users can also upload their own GeoTiff, JPEG, JPEG 2000 files and apply GIS data processing algorithms via API or from the web interface. EOS Vision is your tool for vector data operations with multiple formats support (ESRI Shapefile, GeoJSON, KML, KMZ).
The whole package for image processing
EOS Processing offers a great experience with its sixteen processing workflows, including the popular raster tools (merge, reprojection, pansharpening), remote sensing analytics, photogrammetry, and proprietary feature extraction algorithms that can’t be found anywhere else. Get your data ready for the upcoming LiDAR analysis and 3D modeling as they’ll become available soon.
Such pre-processing tasks as cloud detection or radiometric calibration help you refine raw data for further analysis: you can correct images for atmospheric effects and obtain the real ground radiance or reflectance values.
BEFORE: A high spatial resolution image of a densely built-up area
AFTER: A grayscale image that shows buildings detected using the neural network classification algorithm
Object detection, change detection, and classification
The convolutional neural networks, pre-trained by EOS Data Analytics to extract features from imagery, let you apply state-of-art methods to detect objects and track changes from space.
- Having only a set of multi-temporal images and change detection workflow, you can track how illegal deforestation progresses over time.
- Edge detection can show the exact boundaries of your agricultural lands down to the last pixel.
- It is possible to estimate the parking lot traffic of largest shopping centers with car detection algorithm.
The best of spectral analysis
Products within EOS Platform support almost all remote sensor types, and the user can choose from a long list of spectral indices to calculate on the fly. Aside from the complete set of vegetation indices (NDVI, ReCI, ARVI, SAVI, AVI, etc.), there are also indices to outline landscape features (water, snow, and ice – NDWI, NDSI) and burned areas (NBR). The greatest thing is that here you get the freedom of experimenting with spectral bands and can create custom band combinations that best fit your purposes.
BEFORE: Agricultural lands in Southern Ukraine
AFTER: A raster layer of fields’ edges precisely detected by EOS proprietary algorithm
Customize and analyze
The user-friendly interface of EOS Processing makes it easy to manage processing workflows depending on the user’s business needs. You can set the parameters for processing and repeatedly use such customized workflow to automate high-frequency analytical tasks. The coming updates will add an ability to create custom algorithms from the available data processing operations.
Agriculture, forestry, oil and gas, and more industries
A tandem of EOS products offers a much-needed solution for individuals, businesses, and organizations across numerous industries.
With vegetation indices and crop classification feature, agronomists can continuously monitor crop conditions to detect plant diseases, pests, droughts. Forestry specialists can assess fire damages, monitor forest health, track and enforce logging restrictions.
EOS Platform is a great choice for regional and urban planning, helping users identify land cover classes to generate a vegetation map. It can also make a complete list of urban features like buildings, roads, and other major features in the region.
The platform can tackle disaster management by measuring flood extent and finding fire boundaries. When it comes to oil and gas, it is capable of identifying oil rigs and assessing the environmental impact.
Classification of coniferous vs. deciduous forests in Ukraine using Sentinel-2 image
EOS Data Analytics uses cloud-based services to address different verticals with a single platform, scientifically proven analytics, scale-ups and it builds products that could add value to remotely sensed data to deliver expert-level results for your business.
Unlock the full potential of Earth observation data with EOS Platform, directly in your browser: link
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Paz is the Spanish word for “peace” and regardless of its meaning the PAZ mission indeed constitutes a flagship mission of the Spanish Space Strategic Plan (Programa Nacional de Observación de la Tierra por Satélite) established between 2007 and 2011. The plan is based on two complementary satellites with PAZ as a radar satellite and the Ingenio satellite covering the optic needs.
The PAZ mission is set-up as dual-use mission serving the civil and military sector. It will be used for applications of earth observation as welll as surveillance purposes. Probably the latter could explain why the satellite was named as “PAZ”. The Paz mission is funded and owned by the Spanish Ministry of Defence and managed by the Spanish communications company Hisdesat. The applicability in the earth observation domain will range from environmental monitoring, protection of natural resources, surface monitoring, city and infrastructure planning, monitoring of natural catastrophes up to high-resolution mapping, while its usage in the intelligence sector will cover military operations, border control and enforcement of international treaties. It will also contribute to the Copernicus Programme of the European Commission.
Constellation
The PAZ satellite is operated in constellation with the SAR fleet of the German TanDEM-X mission (Public Private Partnership (PPP) between the German Aerospace Centre (DLR) and Airbus Defence and Space) with TerraSAR-X and TanDEM-X as its satellites. The constellation was agreed on both sides by Hisdesat and Airbus Defence and Space as the operator of the two German satellites and offers the advantages of an optimized revisit time, increased coverage and improved service. According to Hisdesat “numerous activities that require large quantities of timeous data, like crisis management or the monitoring of surface movements, will benefit from this new constellation.”
When?
With a great delay PAZ finally was launched on 22 February 2018 on board of a Falcon 9 rocket by SpaceX from Vandenberg Airforce Base in California, United States. The original launch was scheduled from the Yasni Launch Base in Russia for 2014, but was cancelled with the geopolitical conflict arising in the Crimea region. At the moment the Paz satellite is in the commission period.
Technical characteristics
Like the TerraSAR-X and TanDEM-X satellite, PAZ was built by Airbus Defence and Space in strong collaboration with Hisdesat. It uses a Synthetic Aperture Radar and operates with X-band at a wavelength of around 3,1 cm in order to be compatible within the two other satellites of the constellation. According to radar technology it records day and night and is weather independent – almost weather independent, as heavy rain clouds reflect the radar wave. With the capability of two polarization modes at the same time the satellite will indeed also be used to detect heavy precipitation occurrences. Planned for a flight time of 5,5 years, PAZ will orbit the Earth 15 times per day and cover an area of 300.000 km² daily up to a resolution of only 25cm. It flies at an altitude of 514km in the same orbit as TerraSAR-X and TanDEM-X. Equipped by an Automatic Indentification System PAZ will simultaneously combine AIS signals from ships and SAR imagery contributing important monitoring capabilities for the maritime domain.
The Spanish Space Strategic Plan constitutes an important support for the development of the Spanish space industry. For the construction of the PAZ satellite, Airbus as main contractor led a team of 18 European companies, whereas Spanish space companies were heavily involved in the development of the active SAR sensor enabling to expand know-how and enhance the competitiveness in the global space market. According to Miguel Ángel Panduro, Head of Hisdesat, “the PAZ programme is already a success story for Spain’s industrial development. It has created hundreds of skilled jobs over the years, and stimulated research, development and innovation activities in Spain.”
Paz satellite as graph. Source: Hisdesat
The city of La Paz carries a part of the satellite’s name, but was probably not responsible for its naming. I assume it comes from the application in the surveillance domain. Source: NDR
