COLLECTION

Digital Rural Landscape Lab

Acronym: DRLL

Description

To support European agricultural and environmental policies, the Digital Rural Landscape Lab uses analytics and novel data capturing methods - combining insights from smartphones, farm sensors, street level cameras, crowdsourcing and satellites. Innovative integration of these data flows will improve farm management and refine rural landscape and biodiversity monitoring. This public collection contains dataset published from the

Digital Rural Landscape Lab.

Contact

Email
Raphael.DANDRIMONT (at) ec.europa.eu

Datasets (9)

DATASET | Last updated:
Flower Detection

Train/Test data for object detection of flowers. This dataset contains 500 images of grassland vegetation patches with all visible flowers annotated using bounding boxes. The data...

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Agri-enviromental semantic segmentation of LUCAS

This dataset contains a semantic segmentation delineation derived from street-level images, focusing on categorizing agricultural and natural landscapes. With 35 distinct classes, ...

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LUCAS Vision

Crop identification using deep learning on LUCAS crop cover photos

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Land Cover Computer Vision LUCAS

Dataset with LUCAS point images and their semantic segmentation masks done with Deeplabv3+ trained on ADE20k dataset

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Spectral Adjustment of Surface reflectance dataset

The data set is composed by three hyperspectral data sets: - From USGS spectral measurements (900 spectra) - From simulated reflectance by the ProSail radiative transfer model (20,...

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AI4boundaries

An open AI-ready dataset to map field boundaries with Sentinel-2 and aerial photography

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EU Crop Diversity

Crop diversity across countries and scales in European Union

DATASET | Last updated:
FlevoVision

Monitoring crop phenology with streer-level imagery using computer vision

Additional information

Published by
European Commission, Joint Research Centre
Created date
2021-09-24
Modified date
2023-02-01