Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2025, Vol. 22, No. 2, pp. 335-342
Archive of information products on surface type observation frequency based on Sentinel-2 data and its possible applications
A.V. Kashnitskii
1 , E.A. Loupian
1 1 Space Research Institute RAS, Moscow, Russia
Accepted: 20.03.2025
DOI: 10.21046/2070-7401-2025-22-2-335-342
This paper presents a dataset of detection frequency data for various types of Earth surface obtained from the MSI instrument on board Sentinel-2 satellites, along with the technology used for its creation. The dataset is published on the resources of the IKI-Monitoring Center for Collective Use and is available for solving various scientific tasks. Among other sites, the possibility of working with these products is organized within the unique Vega-Science scientific service (http://sci-vega.ru/). It includes multiple data products based on classifications derived from the Sen2Cor and Dynamic World algorithms. The technology is based on assigning a specific surface type to each pixel of each scene over a specified time period. For the Sen2Cor-based products, the classes used are water surface, vegetation, non-vegetation, dark objects, and snow. For the Dynamic World-based products, the classes include water, trees, grass, flooded vegetation, crops, shrub and scrub, built, bare ground, and snow and ice. The developed technology calculates the absolute number of assignments to each class for each pixel over a period, as well as the percentage of such assignments relative to all cloud-free measurements. Additionally, it determines the most frequently occurring value for that period and the total number of cloud-free measurements. The described products have been generated from 2016 to the present, continuously covering several periods each year. They have been created for a large area of interest in Northern Eurasia spanning over 18 million square kilometers.
Keywords: Sentinel-2, surface type, data set, IKI-Monitoring CCU, landcover, cloud-free data, remote sensing, observation frequency, Sen2Cor, Dynamic World
Full textReferences:
- Kashnitskii A. V., Loupian E. A., Monthly and seasonal data products from Sentinel-2 series satellites in the archives of the IKI-Monitoring Center: Current status, creation technology and access possibilities, Materialy 22-i Mezhdunarodnoi konferentsii “Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa” (Proc. 22nd Intern. Conf. “Current Problems in Remote Sensing of the Earth from Space”), Moscow: IKI RAS, 2024, p. 105 (in Russian), DOI: 10.21046/22DZZconf-2024a.
- Kashnitskii A. V., Burtsev M. A., Proshin A. A., Technology to create cloud-free composites from Sentinel-2 satellite data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, V. 19, No. 5, pp. 76–85 (in Russian), DOI: 10.21046/2070-7401-2022-19-5-76-85.
- Loupian E. A., Proshin A. A., Bourtsev M. A. et al., Experience of development and operation of the IKI-Monitoring center for collective use of systems for archiving, processing and analyzing satellite data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, V. 16, No. 3, pp. 151–170 (in Russian), DOI: 10.21046/2070-7401-2019-16-3-151-170.
- Proshin A. A., Loupian E. A., Balashov I. V. et al., Unified satellite data archive management platform for remote monitoring systems development, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2016, V. 13, No. 3, pp. 9–27 (in Russian), DOI: 10.21046/2070-7401-2016-13-3-9-27.
- Proshin A. A., Kashnitskii A. V., Burtsev M. A., Bril A. A., Organization of receiving, processing and providing data from Sentinel-2 satellites in the IKI-Monitoring shared use center, Materialy 17-i Vserossiiskoi otkrytoi konferentsii “Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa” (Proc. 17th All-Russia Open Conf. “Current Problems in Remote Sensing of the Earth from Space”), Moscow: IKI RAS, 2019, p. 117 (in Russian).
- Baetens L., Desjardins C., Hagolle O., Validation of Copernicus Sentinel-2 cloud masks obtained from MAJA, Sen2Cor, and FMask processors using reference cloud masks generated with a supervised active learning procedure, Remote Sensing, 2019, V. 11, No. 4, Article 433, DOI: 10.3390/rs11040433.
- Brown C. F., Brumby S. P., Guzder-Williams B. et al., Dynamic World, near real-time global 10 m land use land cover mapping, Scientific Data, 2022, V. 9, Article 251, DOI: 10.1038/s41597-022-01307-4.
- Gorelick N., Hancher M., Dixon M. et al., Google Earth Engine: Planetary-scale geospatial analysis for everyone, Remote Sensing of Environment, 2017, V. 202, pp. 18–27, DOI: 10.1016/j.rse.2017.06.031.
- Louis J., Debaecker V., Pflug B., Main-Knorn M., Bieniarz J., Mueller-Wilm U., Cadau E., Gascon F., Sentinel-2 Sen2Cor: L2A processor for users, Proc. “Living Planet Symp. 2016”, Prague, Czech Republic, 2016, ESA SP-740, 8 p.
- Loupian E. A., Bourtsev M. A., Proshin A. A. et al., Usage experience and capabilities of the VEGA-Science system, Remote Sensing, 2022, V. 14, No. 1, Article 77, DOI: 10.3390/rs14010077.
- Main-Knorn M., Pflug B., Louis J. et al., Sen2Cor for Sentinel-2, Proc. SPIE. Image and Signal Processing for Remote Sensing XXIII, 2017, V. 10427, pp. 37–48, DOI: 10.1117/12.2278218.
- Venter Z. S., Barton D. N., Chakraborty T. et al., Global 10 m land use land cover datasets: A comparison of Dynamic World, World Cover and Esri Land Cover, Remote Sensing, 2022, V. 14, No. 16, Article 4101, DOI: 10.3390/rs14164101.
- Xu P., Tsendbazar N.-E., Herold M. et al., Comparative validation of recent 10 m-resolution global land cover maps, Remote Sensing of Environment, 2024, V. 311, Article 114316, DOI: 10.1016/j.rse.2024.114316.