Note that "per tile" information is used here, each covering about a 12,000 sq. Pixel is selected from tile with the least cloud coverage metadata Similar to mostRecent but in reverse order In case there are more tiles available with the same timestamp (some tiles are processed by many ground stations, some are reprocessed, etc.), the one, which was downloaded from SciHub later will be used. The pixel will be selected from the tile, which was acquired most recently The tiling is done by ESA for easier distribution. Note that tiles will in most cases come from the same orbit/acquisition. Sets the order of overlapping tiles from which the output result is mosaicked. This chapter will explain the object of the S2L1C process API. This is mandatory and will ensure you get Sentinel-2 L1C data. Use sentinel-2-l1c (previously S2L1C) as the value of the parameter in your API requests. Endpoint Locations Serviceĭifferences in Capabilities Data type identifier: sentinel-2-l1c To see examples of such requests go here, and for an overview of all API parameters see the API Reference. This chapter will help you understand the parameters for S2L1C data. To do this requires setting various parameters which depend on the datasource you are querying. Each POST request can be tailored to get you exactly the data you require. The requested data will be returned as the response to your request. To access data you need to send a POST request to our process API.
Tracing based on Sentinel imagery is allowed for commercial purposes as well.Īcknowledgment or credit: Contains modified Copernicus Sentinel data processed by Sentinel Hub Accessing Sentinel-2 L1C Data See more details on the use of Copernicus Sentinel data and service information
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Land-cover maps, land-change detection maps, vegetation monitoring, monitoring of burned areasĮU law grants free access to Copernicus Sentinel Data and Service Information for the purpose of the following use in so far as it is lawful: a) reproduction b) distribution c) communication to the public d) adaptation, modification and combination with other data and information e) any combination of points a to d. Land and coastal areas between latitudes 56°S and 83°N MultiSpectral Instrument (MSI), 13 bands: 4 visible bands, 6 Near-Infrared bands, and 3 Short-Wave Infrared bands The satellite's multispectral imager provides a versatile set of 13 spectral bands spanning from the visible and near infrared to the shortwave infrared.ġ0 m, 20 m, and 60 m depending on the wavelength Its high-resolution optical images have many applications, including land monitoring, emergency response and security services assistance. SENTINEL-2 is a European wide-swath, high-resolution, multi-spectral imaging mission. Beautiful clouds over Ljubljana, Slovenia.About Sentinel-2 L1C Data Mission information S2cloudless is a machine learning algorithm for computing cloud masks on Sentinel-2 imagery. It has been well received in the community over the last two years, becoming one of the state-of-the-art algorithms for cloud detection.
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Due to the large interest, we announce the availability of pre-computed cloud masks for the entire Sentinel-2 archive via the Sentinel Hub service. This adds great value to the service, opening up fantastic opportunities for everyone to create amazing Earth Observation applications! Sentinel-2 Cloud Detector - s2cloudlessĪ little more than two years have passed since the release of our machine learning-based cloud detection algorithm for Sentinel-2 imagery, and it seems a perfect time to report feedback gathered so far, as well as to share very exciting news regarding its availability through Sentinel Hub. Since the release of the s2cloudless Python package, we have received very positive feedback from many users, in particular regarding the overall accuracy, flexibility of use, and execution speed. Overall, s2cloudless has been downloaded over 47,000 times and is used in dozens of applications.
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