This repository includes the links and information for Zenodo datasets of each ICAERUS Use Case.
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- UC1: Crop Monitoring
- UC2: Drone Spraying
- UC3: Livestock Monitoring
- UC4: Forestry and Biodiversity
- UC5: Rural Logistics
- OCT: AgroTwin
| Dataset | Author | Date | Description |
|---|---|---|---|
| UAV Canyelles Vineyard Dataset 2023-04-21 | Paula Osés, Oriol Arroyo, Aldo Sollazzo, Chirag Rangholia | 2023-04-21 | Crop monitoring dataset that contains RGB images, pointcloud data, an orthomosaic image and the DEM. |
| UAV Canyelles Vineyard Dataset 2023-04-28 | Esther Vera, , Paula Osés, Oriol Arroyo, Aldo Sollazzo, Chirag Rangholia | 2023-04-28 | Crop monitoring dataset that contains RGB images, NIR images, pointcloud data, RGB and NDVI orthomosaic images, DEM and the shape that defines the total vineyard terrain. |
| UAV Canyelles Vineyard Dataset 2023-05-05 | Esther Vera, Oriol Arroyo, Aldo Sollazzo, Chirag Rangholia, Paula Osés | 2023-05-05 | Crop monitoring dataset that contains RGB images, pointcloud data, an orthomosaic image and the DEM. |
| UAV Canyelles Vineyard Dataset 2023-06-09 | Esther Vera, Oriol Arroyo, Aldo Sollazzo, Chirag Rangholia, Paula Osés | 2023-06-09 | Crop monitoring dataset that contains RGB images, NIR images, pointcloud data, RGB and NDVI orthomosaic images, DEM and the shape that defines the total vineyard terrain. |
| UC1 DATA FOLDER GITHUB | Esther Vera, Aldo Sollazzo, Chirag Rangholia | 2024-05-15 | This dataset contains the necessary data to execute the UC1_Crop_Monitoring codes in GitHub. |
| Dataset | Author | Date | Description |
|---|---|---|---|
| UAV Spraying Parameters-Coverage in Vineyards | Vasilis Psiroukis | 2023-12-06 | A set of UAV spraying data collected using WSPs, across different parameter configurations. |
| Dataset | Author | Date | Description |
|---|---|---|---|
| Drone raw images of cattle in french grazing areas | Adrien Lebreton | 2023-08-10 | The dataset encompasses around 900 raw .jpeg drone images of grazing areas where cattle graze collected between June and August 2023. |
| Sheep videos taken from drone at low altitude | Adrien Lebreton, Louise Helary | 2023-12-18 | The dataset encompasses 16 .MP4 videos from drone (DJI mavic 3 Enterprise or Thermal) of around 50 sheep crossing a gate. |
| Drone images and their annotations of grazing cows | Adrien Lebreton, Louise Helary | 2024-04-24 | It contains 1385 images and 4941 bounding boxes of cows to develop cow detection and counting models. |
| Drone videos and their annotations of passing sheep (for counting purpose) | Louise Helary, Kinsey Nnenna, Marta KOLODZIEJCZYK, Jana SCHEWE, Léa Philip, Estelle Nicolas, Adrien Lebreton | 2024-06-18 | The dataset encompasses 4 .MP4 videos from drone (DJI mavic 3 Enterprise or Thermal) of around 50 sheep crossing a gate. |
| Dataset | Author | Date | Description |
|---|---|---|---|
| Forestry and Biodiversity monitoring in Lithuania with hyperspectral camera and UAV | ART21 | 2023-09-11 | Hyperspectral imaging acquired with UAV on different dates of a pine tree forest. |
| Multiple DJI drone flights with thermal camera over Lithuanian forests in winter for wild boar detection | ART21 | 2024-07-15 | The dataset consists of thermal images captured by DJI drones over Lithuanian forests in winter, used for wild boar detection. |
| Dataset | Author | Date | Description |
|---|---|---|---|
| Photogrammetry Orthomosaic and Digital Surface Model (Strumica, North Macedonia) | GEOSENSE, AGFUTURA | 2024-07-26 | A sample dataset from Strumica, North Macedonia, featuring photogrammetric orthomosaics and a Digital Surface Models (DSM). |
| Dataset | Author | Date | Description |
|---|---|---|---|
| UAV AgroTwin Vineyard Dataset 2024 | Simone Kartsiotis, Antonio Donnangelo | 2024-06-19 | The datasets contains RGB images and pointclouds of a vineyard field. |
| Dataset | Author | Date | Description |
|---|---|---|---|
| 3D cloud reconstruction and 2D NDVI index | Taal S.r.l. | 2024-07-26 | The dataset contains 3D pointclouds and 2D NDVI maps of an olive grove. |
| raw drone sensing data - 1 | Taal S.r.l. | 2024-07-26 | It includes RGB and multispectral images collected with the DJI Mavic 3M in an olive grove, along with flight mission files and GIS information, organized by individual drone flights in separate folders. |
| raw drone sensing data - 2 | Taal S.r.l. | 2024-07-26 | It includes RGB and multispectral images collected with the DJI Mavic 3M in an olive grove, along with flight mission files and GIS information, organized by individual drone flights in separate folders. |
| Ground Truth Data | Taal S.r.l. | 2024-07-29 | The dataset features a dataset of labeled RGB and NDVI olive tree images for training classification models, with health statuses detailed in three CSV files. |
| Tree detected | Taal S.r.l. | 2024-07-29 | The repository contains a dataset of labeled olive trees with bounding boxes used for training detection models. |
| Plant Health Status | Taal S.r.l. | 2024-07-30 | This dataset shows the xylella classifier results to identify asymptomatic health status, effectively differentiating it from mild and evident symptomatic conditions in olive trees. |
| Dataset | Author | Date | Description |
|---|---|---|---|
| SHIELD Demonstrations Dataset | Obsidian Innovation Institute - Associação | 2024-06-19 | This dataset contains the NMEA sentences generated during the Secure and High Integrity EGNSS enabled drone (SHIELD) demonstration campaing and concerning the different demonstration scenarios. |
Small introduction (1-2 lines) about what will be found in the dataset and what is the dataset about (classification, detection, segmentation, for building orthomosaics, parameters). This dataset encompasses the following data:
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Folder: description (number of images / subfolders, type of images, size of images, tables, parameters).
- Subfolder: description (number of images, type of images, size of images, tables, parameters).
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Folder: description (number of images, type of images, size of images, tables, parameters).
A paragraph explaining the flight conditions or specifications about how this data was collected in detail. This can include: which drone, camera, resolution, other sensors, altitude, where, time when the data was collected, processing parameters,...
Possible applications: a description of what you could use this dataset for.