News Update

UP42 partners with Hexagon to offer HxGN Content Program aerial imagery on geospatial marketplace

Oct 2020 | No Comment

High-resolution aerial imagery from the HxGN Content Program is now available on the UP42 developer platform for Earth observation data and analytics. UP42 customers may now choose from nearly 11 million square kilometers of 30 cm orthorectified imagery for North America and Europe and over 500,000 sq km of 15 cm data for major U.S. cities in the Hexagon aerial image library.

UP42 gives users direct access to extensive Earth observation data sets and advanced processing algorithms – along with cloud computing power – to create their own geospatial solutions easily and inexpensively. The platform provides all the tools UP42 customers need to develop geospatial workflows, applications, and even commercial products.

Managed by Hexagon, a global leader in sensors, software, and autonomous solutions, the HxGN Content Program has created an archive of cloud-free, four-band (Red, Green, Blue, Near IR) multispectral data acquired in the past two years with Leica ADS100 and DMC III airborne sensors. The data sets have been orthorectified to deliver the highest level of positional accuracy and consistency – regardless of geographic area. The library is updated every two to three years.

With its exceptional positional accuracy, HxGN Content Program data sets are used extensively as GIS base maps and in applications ranging from infrastructure management, agriculture, insurance, real estate, forestry, and many others. The extraordinary data consistency over large areas has made Hexagon’s orthoimages ideal for use as training data sets in machine learning and artificial intelligence projects.

The HxGN Content Program data sets join a broad selection of Earth observation information already on the UP42 marketplace, including Pleiades 1A/B, SPOT 6/7, Landsat-8, TerraSar-X, Sentinel-2, and MODIS satellite imagery, Getmapping U.K. aerial data, and Meteomatics weather and ocean data.

UP42 users may apply more than 50 geospatial analytics processes, including machine learning algorithms, to automatically find features, count objects, detect change, uncover patterns, classify land use, and derive vegetative indices from remote sensing data sets.


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