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@ARTICLE{Sedona:1018223,
author = {Sedona, Rocco and Paris, Claudia and Ebert, Jan and Riedel,
Morris and Cavallaro, Gabriele},
title = {{T}oward the {P}roduction of {S}patiotemporally
{C}onsistent {A}nnual {L}and {C}over {M}aps {U}sing
{S}entinel-2 {T}ime {S}eries},
journal = {IEEE geoscience and remote sensing letters},
volume = {20},
issn = {1545-598X},
address = {New York, NY},
publisher = {IEEE},
reportid = {FZJ-2023-04619},
pages = {1 - 5},
year = {2023},
abstract = {Land cover (LC) maps generated by the classification of
remote-sensing (RS) data allow for monitoring Earth
processes and the dynamics of objects and phenomena. For
accurate LC variability quantification in environmental
monitoring, maps need to be spatiotemporally consistent,
continually updated, and indicate permanent changes.
However, producing frequent and spatiotemporally consistent
LC maps is challenging because it involves balancing the
need for temporal consistency with the risk of missing real
changes. In this work, we propose a scalable and
semiautomatic method for generating annual LC maps with
labels that are consistently applied from one year to the
next. It uses a Transformer deep-learning (DL) model as a
classifier, which is trained on satellite time series (TS)
of images using high performance computing (HPC). The
trained model can generate stable maps by shifting the
prediction window along the temporal direction. The
effectiveness of the proposed approach is tested
qualitatively and quantitatively on a multiannual Sentinel-2
dataset acquired over a three-year period in a study area
located in the southern Italian Alps.},
cin = {JSC},
ddc = {550},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
(SDLs) and Research Groups (POF4-511) / 5112 - Cross-Domain
Algorithms, Tools, Methods Labs (ATMLs) and Research Groups
(POF4-511) / RAISE - Research on AI- and Simulation-Based
Engineering at Exascale (951733) / EUROCC-2 (DEA02266)},
pid = {G:(DE-HGF)POF4-5111 / G:(DE-HGF)POF4-5112 /
G:(EU-Grant)951733 / G:(DE-Juel-1)DEA02266},
typ = {PUB:(DE-HGF)16},
UT = {WOS:001105671500009},
doi = {10.1109/LGRS.2023.3329428},
url = {https://juser.fz-juelich.de/record/1018223},
}