In case you missed it, we recently added Maxar's WorldView data, USGS's Landsat 8 collection 2, and several Copernicus services collections. You can explore the latter in the EO Browser, our free web application, which we will present in detail in our live webinar tomorrow. The Public Collections Catalogue for discovering and sharing collections has been released and the long-awaited Statistical API is now available in beta. The Expert Judgement Application was featured in our blog post series on Area Monitoring. A new edition of Sentinel Hub Custom Script Contest is in the works. Read all about it and more!
Data collections keep expanding, and you can help as well!
Through our partnership with European Space Imaging, we have finally integrated Maxar’s WorldView data, a new commercial data collection with sub-meter resolution. We've also added the USGS’s Landsat 8 Collection 2, which provides an enhanced surface reflectance product, and the first set of Copernicus services collections - CORINE Land Cover, Global Land Cover, and Water Bodies (additional ones coming soon!). Read our latest blog post for details.
Several of our users expressed their wish to share their collections with the community, which is why we have developed a process to support this. Check out the Public Collections Catalogue to help you discover and share the collections available through Sentinel Hub.
Helping experts with decision making, where machine learning struggles.
Better predictions and decisions are not necessarily made by better and more complex models. Often, greater improvements come from less noisy labels, a better understanding of the data, and where and why models make incorrect predictions. The Expert Judgement app enables all of this and more. We demonstrated how we help operators review thousands of cases in the fastest way possible in our latest blog post from the Area Monitoring series.
All users of the Feature Info Service (FIS) will be happy to hear that we have launched the next version of this API, now called Statistical API. Currently in beta, but much more powerful than the still-supported OGC FIS service you're used to - visit our documentation and examples to see what you can do. To give you an idea - you can now calculate the percentage of cloudy pixels for a given parcel, exclude certain pixels, such as water, from the calculation, split the requested time range into multiple time intervals (e.g. aggregate data by 10 days), and much more. The Statistical API is also included in the Requests Builder, so you can work with a user interface to try new requests.
Three new Copernicus Services data collections have been added to the EO Browser! The first is Corine Land Cover (CLC) with 44 Land Cover and Land Use classes updated every six years so you can compare land cover changes going back to 1990, with the latest update being from 2018. In addition to the Europe-focused CLC, Global Land Cover data starting from 2015 onwards are now available. If you are interested in permanent and seasonal inland waters, take a look at the monthly updated Water Bodies product. All three collections can be found at the data source: Copernicus Services.
Besides the new data, two new languages have also been added. Our ever-growing family of languages is now richer with German and Greek. This means that EO Browser is now closer to more than 850 million people around the world.
Get ready! The new special edition is coming soon!
The next special edition of Sentinel Hub Custom Script Contest – Urban Growth in Africa – focusing on change detection and urban growth will launch in late April / early May 2021. With the help of EO Browser and Euro Data Cube, we aim to demonstrate the power of a deep multi-temporal and multi-resolution data cube over Dakar, Senegal. We have combined open datasets (Sentinel-1, Sentinel-2 and Landsat) to obtain dense time series over a long period of time, and commercial datasets (Pleiades, SPOT, PlanetScope and WorldView) for detailed insights into the area. For more information, visit our official Contest page!
A repository of EO Browser pins - locations of interest - categorized by themes.
Our GitHub Pin Library got a complete redesign to make it more attractive and intuitive. Each pin has a description, an image, a location map, and an EO Browser link. Each theme can be exported and imported into the app, adding the content to the user's pin list. We would love our users to contribute by adding new themes and pins so that it becomes an amazing public repository of remote sensing images and interesting locations for students, researchers and enthusiasts to explore.
Due to the integration of Sentinel Hub with the core Landsat Collection 2 (Level-1 and -2), the old collection (L8L1C) becomes obsolete. We strongly recommend to change your requests to the new one (LOTL1) - the data comes directly from USGS and is therefore more up-to-date and of better quality. Learn how to use both levels in Process API and OGC API here.
The bands and overall settings of L8L1C and LOTL1 are the same, so no change to your EVALSCRIPT is required. If you choose to leave it as is, we will automatically migrate it on June 15, 2021. We don't expect any problems, but it's still better to try it yourself for the specific use-case. Read more.
Join us this Thursday at 14:00 CEST (12:00 UTC) for the Sentinel Hub's live webinar on EO Browser. We'll walk you through all the features, including image download, time-lapse, working with pins, and more! See the agenda and register here!
You can watch recordings of our previous webinars on OGC API with QGIS integration, Sentinel Hub Process API, Commercial Data in Sentinel Hub, Custom Scripts, Multi-Temporal Scripts and Data Fusion, and more. Visit our Youtube Webinar Channel!
A comprehensive article on the OpenEO project has just been published in the MDPI Remote Sensing peer-reviewed journal. The article is titled "The openEO API-Harmonising the Use of Earth Observation Cloud Services Using Virtual Data Cube Functionalities" and was published in the journal's special issue dedicated to Earth observation big data. The article presents the communication strategy and aspects of the data cube model used by the openEO API. Two test cases show the potential and current limitations of processing similar workflows on different cloud platforms and a comparison of the result of a locally running workflow and its openEO-dependent cloud equivalent. The results demonstrate the flexibility of the openEO API in enabling complex scientific analysis of EO data collections on cloud platforms in a homogenized manner.
Read the guest blog post explaining Landsat 8 Clouds Segmentation Script, submitted in the third round of Sentinel Hub Custom Script Contest. The script distinguishes clouds from any type of land in Landsat 8 satellite imagery and is a direct application of a machine learning model obtained using a proprietary Evolutionary Algorithm.
Mark the dates for our presentations at the following events:
We continue to work remotely and meet with you all primarily virtually. Feel free to send us your feedback via the Forum or social media. We look forward to hearing from you.