DISTSENSING: A NEW PLATFORM FOR TIME SERIES PROCESSING IN A DISTRIBUTED COMPUTING ENVIRONMENT

DISTSENSING: A NEW PLATFORM FOR TIME SERIES PROCESSING IN A DISTRIBUTED COMPUTING ENVIRONMENT

Time series analysis of remote sensing images are indispensable in identifying patterns, trends and changes, and allows the modeling and prediction of events on Earth's surface. For applications with large volumes of data, this analysis should be done in an automated way allowing spatio-tempora...

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Main Authors: Sávio Salvarino Teles de Oliveira, Marcelo de Castro Cardoso, Wisllay dos Santos, Paulo Costa, Vagner José do Sacramento Rodrigues, Wellington Santos Martins
Format: Article
Language:English
Published: Universidade Federal de Uberlândia 2017-05-01
Series:Revista Brasileira de Cartografia
Online Access:http://www.seer.ufu.br/index.php/revistabrasileiracartografia/article/view/44001
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spelling doaj-ca2d89961de746a08e32de74e4e9ae002020-11-25T00:02:54ZengUniversidade Federal de UberlândiaRevista Brasileira de Cartografia0560-46131808-09362017-05-01695DISTSENSING: A NEW PLATFORM FOR TIME SERIES PROCESSING IN A DISTRIBUTED COMPUTING ENVIRONMENTSávio Salvarino Teles de Oliveira0Marcelo de Castro CardosoWisllay dos SantosPaulo CostaVagner José do Sacramento RodriguesWellington Santos Martins1Universidade Federal de Goiás/Instituto de InformáticaUniversidade Federal de Goiás/Instituto de InformáticaTime series analysis of remote sensing images are indispensable in identifying patterns, trends and changes, and allows the modeling and prediction of events on Earth's surface. For applications with large volumes of data, this analysis should be done in an automated way allowing spatio-temporal ï¬ ltering in the image database. This paper proposes a new platform, DistSensing, to process these analysis using spatial and relational distributed indices. The DistSensing platform had better performance than the solutions found in the literature when it is necessary run queries in the database using temporal and spatial ï¬ lters.http://www.seer.ufu.br/index.php/revistabrasileiracartografia/article/view/44001
collection DOAJ
language English
format Article
sources DOAJ
author Sávio Salvarino Teles de Oliveira
Marcelo de Castro Cardoso
Wisllay dos Santos
Paulo Costa
Vagner José do Sacramento Rodrigues
Wellington Santos Martins
spellingShingle Sávio Salvarino Teles de Oliveira
Marcelo de Castro Cardoso
Wisllay dos Santos
Paulo Costa
Vagner José do Sacramento Rodrigues
Wellington Santos Martins
DISTSENSING: A NEW PLATFORM FOR TIME SERIES PROCESSING IN A DISTRIBUTED COMPUTING ENVIRONMENT
Revista Brasileira de Cartografia
author_facet Sávio Salvarino Teles de Oliveira
Marcelo de Castro Cardoso
Wisllay dos Santos
Paulo Costa
Vagner José do Sacramento Rodrigues
Wellington Santos Martins
author_sort Sávio Salvarino Teles de Oliveira
title DISTSENSING: A NEW PLATFORM FOR TIME SERIES PROCESSING IN A DISTRIBUTED COMPUTING ENVIRONMENT
title_short DISTSENSING: A NEW PLATFORM FOR TIME SERIES PROCESSING IN A DISTRIBUTED COMPUTING ENVIRONMENT
title_full DISTSENSING: A NEW PLATFORM FOR TIME SERIES PROCESSING IN A DISTRIBUTED COMPUTING ENVIRONMENT
title_fullStr DISTSENSING: A NEW PLATFORM FOR TIME SERIES PROCESSING IN A DISTRIBUTED COMPUTING ENVIRONMENT
title_full_unstemmed DISTSENSING: A NEW PLATFORM FOR TIME SERIES PROCESSING IN A DISTRIBUTED COMPUTING ENVIRONMENT
title_sort distsensing: a new platform for time series processing in a distributed computing environment
publisher Universidade Federal de Uberlândia
series Revista Brasileira de Cartografia
issn 0560-4613
1808-0936
publishDate 2017-05-01
description Time series analysis of remote sensing images are indispensable in identifying patterns, trends and changes, and allows the modeling and prediction of events on Earth's surface. For applications with large volumes of data, this analysis should be done in an automated way allowing spatio-temporal ï¬ ltering in the image database. This paper proposes a new platform, DistSensing, to process these analysis using spatial and relational distributed indices. The DistSensing platform had better performance than the solutions found in the literature when it is necessary run queries in the database using temporal and spatial ï¬ lters.
url http://www.seer.ufu.br/index.php/revistabrasileiracartografia/article/view/44001
work_keys_str_mv AT saviosalvarinotelesdeoliveira distsensinganewplatformfortimeseriesprocessinginadistributedcomputingenvironment
AT marcelodecastrocardoso distsensinganewplatformfortimeseriesprocessinginadistributedcomputingenvironment
AT wisllaydossantos distsensinganewplatformfortimeseriesprocessinginadistributedcomputingenvironment
AT paulocosta distsensinganewplatformfortimeseriesprocessinginadistributedcomputingenvironment
AT vagnerjosedosacramentorodrigues distsensinganewplatformfortimeseriesprocessinginadistributedcomputingenvironment
AT wellingtonsantosmartins distsensinganewplatformfortimeseriesprocessinginadistributedcomputingenvironment
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