Title: A global cloud free pixel- based image composite from Sentinel-2 data
Authors: CORBAN CHRISTINAPOLITIS PANAGIOTISKEMPENEERS PIETERSIMONETTI DARIOSOILLE PIERREBURGER ARMINPESARESI MARTINOSABO FILIPSYRRIS VASILEIOSKEMPER THOMAS
Citation: DATA IN BRIEF vol. 31 p. 105737
Publisher: ELSEVIER
Publication Year: 2020
JRC N°: JRC120356
ISSN: 2352-3409 (online)
URI: https://www.sciencedirect.com/science/article/pii/S2352340920306314?via%3Dihub#sec0006
https://publications.jrc.ec.europa.eu/repository/handle/JRC120356
DOI: 10.1016/j.dib.2020.105737
Type: Articles in periodicals and books
Abstract: Large-scale land cover classification from satellite imagery is still a challenge due to the big volume of data to be processed, to persistent cloud-cover in cloud-prone areas as well as seasonal artefacts that affect spatial homogeneity. Sentinel-2 times series from Copernicus Earth Observation program offer a great potential for fine scale land cover mapping thanks to high spatial and temporal resolutions, with a decametric resolution and five-day repeat time. However, the selection of best available scenes, their download together with the requirements in terms of storage and computing resources pose restrictions for large-scale land cover mapping. The dataset presented in this paper corresponds to global cloud-free pixel based composite created from the Sentinel-2 data archive (Level L1C) available in Google Earth Engine for the period January 2017- December 2018. The methodology used for generating the image composite is described and the metadata associated with the 10 m resolution dataset is presented. The data with a total volume of 10 TB is stored on the Big Data platform of the Joint Research Centre. It can be downloaded per UTM grid zone, loaded into GIS clients and displayed easily thanks to pre-computed overviews.
JRC Directorate:Space, Security and Migration

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