@InProceedings{OliveiraPaFeCaBuRoMa:2018:NePaAl,
author = "Oliveira, Savio S. T. de and Pascoal, Luiz M. L. and Ferreira,
Laerte and Cardoso, Marcelo de C. and Bueno, Elivelton and
Rodrigues, Vagner J. S. and Martins, Wellington S.",
affiliation = "{Universidade Federal de Goi{\'a}s (UFG)} and {Universidade
Federal de Goi{\'a}s (UFG)} and {Universidade Federal de
Goi{\'a}s (UFG)} and {Universidade Federal de Goi{\'a}s (UFG)}
and {Universidade Federal de Goi{\'a}s (UFG)} and {Universidade
Federal de Goi{\'a}s (UFG)} and {Universidade Federal de
Goi{\'a}s (UFG)}",
title = "SP-TWDTW: a new parallel algorithm for spatio-temporal analysis of
remote sensing images",
year = "2018",
editor = "Vinhas, L{\'u}bia (INPE) and Campelo, Claudio (UFCG)",
pages = "46--57",
organization = "Simp{\'o}sio Brasileiro de Geoinform{\'a}tica, 19. (GEOINFO)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "In the class of computationally complex problems, the time series
analysis is one of those that has high demand for computational
power. The Time-Weighted Dynamic Time Warping (TWDTW) algorithm
stands out as one of the best solution found in the literature in
this field, but its time complexity of O(n2) makes it unfeasible
for large data sets. To overcome this limitation, this work
proposes a parallel algorithm, named SP-TWDTW (Spatial Parallel
TWDTW), that allows the analysis of large scale time series using
Manycore architectures. The SP-TWDTW considers the temporal axis
and the spatial au- tocorrelation to determine the land use
mapping in a given region. The results show that the SP-TWDTW
algorithm is a promising solution with response time up to 11
times lower.",
conference-location = "Campina Grande",
conference-year = "05-07 dez. 2018",
issn = "2179-4847",
language = "pt",
ibi = "8JMKD3MGPDW34P/3SEUPLL",
url = "http://urlib.net/ibi/8JMKD3MGPDW34P/3SEUPLL",
targetfile = "p5.pdf",
urlaccessdate = "28 abr. 2024"
}