Abstract
Environmental analysts and researchers’ time is an expensive and scarce resource that should be used efficiently. Creating analysis products from remote sensing images involves several steps that take time and can be either automatized or centralized. Among all these steps, product’s lineage and reproducibility must be assured. We present CDCol, a geoscience data cube that addresses these concerns and fits the analysis needs of Colombian institutions, the forest and carbon monitoring system.
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Acknowledgments
We thank to Brian Killough from NASA, and Alfredo Delos Santos and Kayla Fox from AMA team, for their support and fruitfully discussions. We also thank to CEOS Australia group for its work and for share it with the world. We thank also to the Environmental Ministry for financial support.
CDCol uses NetCDF format UCAR/Unidata to storage ingested data and results (http://doi.org/10.5065/D6H70CW6).
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Ariza-Porras, C. et al. (2017). CDCol: A Geoscience Data Cube that Meets Colombian Needs. In: Solano, A., Ordoñez, H. (eds) Advances in Computing. CCC 2017. Communications in Computer and Information Science, vol 735. Springer, Cham. https://doi.org/10.1007/978-3-319-66562-7_7
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