IEEE Xplore | Rendered paper | Rendered presentation
@inproceedings{dubrovinRemoteSensingEvidence2022,
title = {Remote {{Sensing Evidence}} for the {{Harmful Algal Bloom Explanation}} of the {{Ecological Situation}} in {{Kamchatka}} in {{Autumn}} of 2020},
booktitle = {{{IGARSS}} 2022 - 2022 {{IEEE International Geoscience}} and {{Remote Sensing Symposium}}},
author = {Dubrovin, Ivan and Ivanov, Anton},
date = {2022-07-17},
pages = {6764--6767},
publisher = {{IEEE}},
location = {{Kuala Lumpur, Malaysia}},
doi = {10.1109/IGARSS46834.2022.9884841},
eventtitle = {{{IGARSS}} 2022 - 2022 {{IEEE International Geoscience}} and {{Remote Sensing Symposium}}},
isbn = {978-1-66542-792-0}
}
Data/: lists of used products for raw and simple READMEs that preserve the directory structure for generated data.Python/: Python scripts that wrap SNAP GPT to process Sentinel images.Qmd/: Quarto source for the paper and the presentation + auxillary files.R/: R scripts that define functions used in the pipeline._targets.R: the pipeline definition.
The dependencies are contained within virtual environments: renv for R and Pipenv for Python.
The whole workflow is contained within a targets pipeline.
I don't know how to include data retrieval into the pipeline. I include the lists of used products in the folders that are supposed to contain them. Offline Sentinel-2 MSI products can be downloaded from the Copernicus Hub without problems. There is even a great API to automate that. Offline Sentinel-3 ocean data (older than one year), however, as far as I know, can only be accessed via EUMETSAT archive. It has no API and is, in general, quite a chore to use. The EUMETSAT team is working on better alternatives, but at the moment, it's the only option.
I would put the data on public file sharing, but it's too big for any free service. I will be keeping a copy of all products for some time, so if you need the data, you can suggest a way to share it here in the discussions or by reaching me at Ivan.Dubrovin@skoltech.ru.