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Unlabeled Sentinel 2 time series dataset (training, T31TDL): Self-Supervised Spatio-Temporal Representation Learning of Satellite Image Time Series

Authors: Dumeur, Iris; Valero, Silvia; Inglada, Jordi;

Unlabeled Sentinel 2 time series dataset (training, T31TDL): Self-Supervised Spatio-Temporal Representation Learning of Satellite Image Time Series

Abstract

This is a part of the unlabeled Sentinel 2 (S2) L2A dataset composed of patch time series acquired over France used to pretrain U-BARN. For further details, see section IV.A of the pre-print article "Self-Supervised Spatio-Temporal Representation Learning Of Satellite Image Time Series" available here. Each patch is constituted of the 10 bands [B2,B3,B4,B5,B6,B7,B8,B8A,B11,B12] and the three masks ['CLM_R1', 'EDG_R1', 'SAT_R1']. The global dataset is composed of two disjoint datasets: training (9 tiles) and validation dataset (4 tiles). In this repo, only data from the S2 tile T31TDL are available. To download the full pretraining dataset, see: 10.5281/zenodo.7891924 Global unlabeled dataset description Dataset name S2 tiles ROI size Temporal extent Train T30TXT,T30TYQ,T30TYS,T30UVU, T31TDJ,T31TDL,T31TFN,T31TGJ,T31UEP 1024*1024 2018-2020 Val T30TYR,T30UWU,T31TEK,T31UER 256*256 2016-2019

Keywords

Unlabeled dataset, Satellite Image Time Series, Sentinel 2, Unlabeled Dataset, France

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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