cb328232-31f5-4b84-a929-8e1ee551d66a 2023-02-09 GrowliFlower: An image time-series dataset for GROWth analysis of cauLIFLOWER This dataset contains georeferenced, image-based UAV time-series of two monitored cauliflower fields acquired in two years, 2020 and 2021. The proposed dataset contains RGB and multispectral orthophotos with coordinates of approximately 14000 individual cauliflower plants. The coordinates enable extraction of complete and incomplete time-series of image patches showing individual plants. The dataset contains the collected phenotypic traits of 740 plants, including the developmental stage and plant and cauliflower size. The harvestable product is completely covered by leaves, thus, plant IDs and coordinates are provided to extract image pairs of plants pre- and post-defoliation. In addition, to facilitate classification, detection, segmentation, instance segmentation, and other similar computer vision tasks, the proposed dataset contains pixel-accurate leaf and plant instance segmentations, as well as stem annotations. Machine Learning Cauliflower RGB Multispectral UAV Time series Instance Segmentation Defoliation Jana Kierdorf jkierdorf@uni-bonn.de University of Bonn Optimization of cauliflower cultivation using UAVs and machine learning We deal with growth analysis and harvest time prediction of cauliflower. https://phenoroam.phenorob.de:/geonetwork/srv/api/records/cb328232-31f5-4b84-a929-8e1ee551d66a/attachments/data_overview.png https://phenoroam.phenorob.de:/geonetwork/srv/api/records/cb328232-31f5-4b84-a929-8e1ee551d66a/attachments/4405-README.md https://phenoroam.phenorob.de:/geonetwork/srv/api/records/cb328232-31f5-4b84-a929-8e1ee551d66a/attachments/6400-src.zip https://phenoroam.phenorob.de:/geonetwork/srv/api/records/cb328232-31f5-4b84-a929-8e1ee551d66a/attachments/315548-GrowliFlowerD.zip https://phenoroam.phenorob.de:/geonetwork/srv/api/records/cb328232-31f5-4b84-a929-8e1ee551d66a/attachments/711132-GrowliFlowerR.zip https://phenoroam.phenorob.de:/geonetwork/srv/api/records/cb328232-31f5-4b84-a929-8e1ee551d66a/attachments/3472660-GrowliFlowerT.zip https://phenoroam.phenorob.de:/geonetwork/srv/api/records/cb328232-31f5-4b84-a929-8e1ee551d66a/attachments/79798936-GrowliFlowerL.zip https://phenoroam.phenorob.de/file-uploader/download/public/147892741001-GrowliFlowerO.zip https://phenoroam.phenorob.de/file-uploader/download/public/10421830809-GrowliFlowerM.zip DATA PROVISION * All data collected or created within the framework of PhenoRob must be made available to the PhenoRob Database immediately. * The datasets must be sufficiently documented including data format, structure and quality to allow for easy access and use, if possible adhering to existing standards. * Datasets submitted to the PhenoRob Database must be accompanied by metadata. The metadata are open access. DATA USE *Users have to inform the owner of the data of their intended use, and, in case of planned publication, the owner of the data has to be involved. Authorship needs to be negotiated with the owner of the data. * Users agree not to distribute datasets of the PhenoRob Database to others (third persons) without prior consent by the owner of the data. * Users agree to use PhenoRob data only for non-commercial scientific purposes. In case of conflict the PhenoRob Executive Board should mediate. Kierdorf, J., Junker-Frohn, L. V., Delaney, M., Olave, M. D., Burkart, A., Jaenicke, H., Muller, O., Rascher, U., & Roscher, R. (2022). GrowliFlower: An image time series dataset for GROWth analysis of cauLIFLOWER. arXiv preprint arXiv:2204.00294. 6.9742 6.959 50.7743 50.7623