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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| Autores principales: | , |
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| Formato: | Artículo revista |
| Lenguaje: | Español |
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Facultad de Ciencias Agropecuarias
2019
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| Acceso en línea: | https://revistas.unc.edu.ar/index.php/agris/article/view/23410 |
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| Sumario: | 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. |
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