Gestión de datos espacio-temporales de imágenes satelitales

Q4 Agricultural and Biological Sciences
Matías Alejandro Castillo Moine, M. Balzarini
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引用次数: 0

Abstract

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.
卫星图像的时空数据管理
大范围归一化植被指数(NDVI)长时间序列数据的管理需要有效利用计算资源。本文讨论并阐述了基于卫星影像的海量时空数据库的构建和统计处理策略。详细介绍了数据管理协议在R软件中的实现,并实现了并行计算。结果表明,“划分-应用-组合”概念能够较好地过滤和分类区域尺度上的NDVI长时间序列。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
AgriScientia
AgriScientia Agricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
0.30
自引率
0.00%
发文量
0
审稿时长
22 weeks
期刊介绍: AgriScientia es una revista de acceso abierto, de carácter científico-académico, gestionada por el Área de Difusión Científica de la Facultad de Ciencias Agropecuarias de la Universidad Nacional de Córdoba, Argentina. La revista recibe artículos en los idiomas español e inglés. El objetivo de esta publicación es la difusión de los resultados de investigaciones de carácter agronómico. Está destinada a investigadores, estudiantes de pregrado, grado y posgrado, profesionales en el área de las ciencias agropecuarias y público en general interesado en las temáticas relacionadas. Su periodicidad es semestral. Los artículos se reciben durante todo el año. Los tipos de documentos que se publican son artículos científicos, comunicaciones y revisiones.
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