Spatio-temporal data managment of satellite imagery
The management of long time series data of Normalized Difference Vegetation Index (NDVI) over large territories demands efficient use of computational resources. This paper discusses and illustrates strategies for the construction and statistical processing of massive spatio-temporal databases from...
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Facultad de Ciencias Agropecuarias.
2019
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I10-R10-article-234102020-03-30T15:07:23Z Spatio-temporal data managment of satellite imagery Gestión de datos espacio-temporales de imágenes satelitales Castillo Moine, Matías Alejandro Balzarini, Mónica Graciela GIS MODIS satellite image time series, divide-apply-combine, data management protocol parallel processing SIG MODIS Series de tiempo de imágenes satelitales dividir-aplicar-combinar procesamiento en paralelo protocolo The management of long time series data of Normalized Difference Vegetation Index (NDVI) over large territories demands efficient use of computational resources. This paper discusses and illustrates strategies for the construction and statistical processing of massive spatio-temporal databases from satellite images. The implementation of a data management protocol in the R software is detailed, with implementation of parallel computations. The results show that the concept divide-apply-combine was adequate to filter and classify long time series of NDVI territorially distributed at a regional scale. El manejo de datos de largas series temporales del índice de vegetación de diferencia normalizada (NDVI) en territorios extensos demanda un uso eficiente del recurso computacional. En este trabajo se discuten e ilustran estrategias para la construcción y procesamiento estadístico de bases de datos masivos espacio-temporales provenientes de imágenes satelitales. Se detalla la implementación de un protocolo de manejo de datos en el software R, con implementación de cómputos paralelizada. Los resultados muestran que el concepto dividir-aplicar-combinar resultó adecuado para filtrar y clasificar largas series de tiempo de NDVI distribuidas territorialmente a escala regional. Facultad de Ciencias Agropecuarias. 2019-12-24 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf text/html https://revistas.unc.edu.ar/index.php/agris/article/view/23410 AgriScientia; Vol. 36 No. 2 (2019); 67-80 AgriScientia; Vol. 36 Núm. 2 (2019); 67-80 1668-298X 10.31047/1668.298x.v36.n2 spa https://revistas.unc.edu.ar/index.php/agris/article/view/23410/28846 https://revistas.unc.edu.ar/index.php/agris/article/view/23410/29280 |
institution |
Universidad Nacional de Córdoba |
institution_str |
I-10 |
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R-10 |
container_title_str |
Revistas de la UNC |
language |
Español |
format |
Artículo revista |
topic |
GIS MODIS satellite image time series, divide-apply-combine, data management protocol parallel processing SIG MODIS Series de tiempo de imágenes satelitales dividir-aplicar-combinar procesamiento en paralelo protocolo |
spellingShingle |
GIS MODIS satellite image time series, divide-apply-combine, data management protocol parallel processing SIG MODIS Series de tiempo de imágenes satelitales dividir-aplicar-combinar procesamiento en paralelo protocolo Castillo Moine, Matías Alejandro Balzarini, Mónica Graciela Spatio-temporal data managment of satellite imagery |
topic_facet |
GIS MODIS satellite image time series, divide-apply-combine, data management protocol parallel processing SIG MODIS Series de tiempo de imágenes satelitales dividir-aplicar-combinar procesamiento en paralelo protocolo |
author |
Castillo Moine, Matías Alejandro Balzarini, Mónica Graciela |
author_facet |
Castillo Moine, Matías Alejandro Balzarini, Mónica Graciela |
author_sort |
Castillo Moine, Matías Alejandro |
title |
Spatio-temporal data managment of satellite imagery |
title_short |
Spatio-temporal data managment of satellite imagery |
title_full |
Spatio-temporal data managment of satellite imagery |
title_fullStr |
Spatio-temporal data managment of satellite imagery |
title_full_unstemmed |
Spatio-temporal data managment of satellite imagery |
title_sort |
spatio-temporal data managment of satellite imagery |
description |
The management of long time series data of Normalized Difference Vegetation Index (NDVI) over large territories demands efficient use of computational resources. This paper discusses and illustrates strategies for the construction and statistical processing of massive spatio-temporal databases from satellite images. The implementation of a data management protocol in the R software is detailed, with implementation of parallel computations. The results show that the concept divide-apply-combine was adequate to filter and classify long time series of NDVI territorially distributed at a regional scale. |
publisher |
Facultad de Ciencias Agropecuarias. |
publishDate |
2019 |
url |
https://revistas.unc.edu.ar/index.php/agris/article/view/23410 |
work_keys_str_mv |
AT castillomoinematiasalejandro spatiotemporaldatamanagmentofsatelliteimagery AT balzarinimonicagraciela spatiotemporaldatamanagmentofsatelliteimagery AT castillomoinematiasalejandro gestiondedatosespaciotemporalesdeimagenessatelitales AT balzarinimonicagraciela gestiondedatosespaciotemporalesdeimagenessatelitales |
first_indexed |
2022-08-20T01:01:41Z |
last_indexed |
2022-08-20T01:01:41Z |
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