5079843
doi
10.5281/zenodo.5079843
oai:zenodo.org:5079843
user-eu
Poehls Jeran
Max Plank Institute for Biogeochemistry
Benson Vitus
Max Plank Institute for Biogeochemistry
DeepCube: Africa MiniCubes
Requena-Mesa Christian
Max Plank Institute for Biogeochemistry
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
<p>The <strong>DeepCube Africa Minicubes</strong> dataset has been desinged for prototyping models for forecasting drought impacts in Africa. It pairs high resolution remotely sensed spectral bands with weather observations into sparsely sampled minicubes of 3.84x3.84Km.</p>
<p>Deep Cube Forecasting Drought and Heat Impacts in Africa:</p>
<ul>
<li><strong>Questions to be tackled using this dataset</strong> Can we predict localized impacts of meteorological drought and heat waves in sub-Saharan Africa based on multivariate Earth Observation and meteorological historical data analysis? What are the anticipated long-term effects of drought and heat, i.e. memory and lag effects?</li>
</ul>
<p>The data is shaped into minicubes in order to facilitate the training of deep learning spatio-temporal models that make use of both spatial and temporal dependencies (convolutions and recurrency, e.g., video prediction models).</p>
<p>This release contains 2.859 demonstrator minicubes out of a parent set of 50.000 cubes that have been smart sampled in the African continent.</p>
<p>Find more on <a href="https://deepcube-h2020.eu/data-cubes/ ">DeepCube data cubes</a></p>
Zenodo
2021-06-30
info:eu-repo/semantics/other
5079842
user-eu
v0.1
award_title=EXPLAINABLE AI PIPELINES FOR BIG COPERNICUS DATA; award_number=101004188; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/101004188; funder_id=00k4n6c32; funder_name=European Commission;
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https://zenodo.org/records/5079843/files/africa_minicubes.tar.gz
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