Agri-Hub/Callisto-Dataset-Collection

A list of datasets aiming to enable Artificial Intelligence applications that use Copernicus data.

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Agri-Hub/eoProcessors

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Agri-Hub/agri-hub.github.io

Agri-Hub ressearch group

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Agri-Hub/.github

Research group: AI and Earth observation for sustainable ecosystems

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Agri-Hub/igarss2024

Summer School

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Agri-Hub/Deep-Learning-for-Cloud-Gap-Filling-on-Normalized-Difference-Vegetation-Index

A CNN-RNN based model that identifies correlations between optical and SAR data and exports dense Normalized Difference Vegetation Index (NDVI) time-series of a static 6-day time resolution and can be used for Events Detection tasks

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Agri-Hub/AAAI23-Eval-AgriRecommendations

"Evaluating Digital Agriculture Recommendations with Causal Inference". It was accepted and presented in the special track on Artificial Intelligence for Social Impact, AAAI-23

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Agri-Hub/Space2Ground

A dataset with Space (Sentinel-1/2) and Ground (street-level images) components, annotated with crop-type labels for agriculture monitoring.

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Agri-Hub/datacap

An end-to-end framework for monitoring the CAP, which utilizes Open Data Cube, Sentinel-2 data and Streel-level images.

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Agri-Hub/cotton-phenology-dataset

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Agri-Hub/Mapillary_Annotation

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Agri-Hub/CCAI-NeurIPS22-Personalizing

"Personalizing Sustainable Agriculture with Causal Machine Learning". Best Proposal Paper of "Tackling Climate Change with Machine Learning" Workshop, NeurIPS'22.

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Agri-Hub/rice_map

This dataset includes three paddy rice maps in South Korea for the year 2018. Specifically, the three maps are for the regions of i) Seosan and Dangjin, ii) Haenam and iii) Cheorwon. The paddy rice maps are a product Random Forest predictions and DO NOT represent ground truth information. The predictions were made based on a semi-supervised approach that first generates pseudo-labels using a dynamic k-means algorithm and then trains the Random Forest Classifier. The classifier has been trained on pseudo-labels that stem from the Seosan and Dangjin site (i).

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Agri-Hub/Educational

Educational Scripts related to Geoprocessing with Python

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Agri-Hub/ADC

A Data Cube-based Framework for Utilizing Big Satellite Data for Agriculture Monitoring

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Agri-Hub/Callisto

A Callisto repository that will hold relevant jupyter notebooks and other related work

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Agri-Hub/eshape_phenology

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