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A Year Acquiring and Publishing Drone Aerial Images in Research on Agriculture, Forestry, and Private Urban Gardens

机译:在农业,林业和私人城市花园研究中获取和出版无人机空中形象

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Drone imaging has been shown to have increasing value in monitoring and analysing different kinds of processes related to agriculture and forestry. In long-term monitoring and observation tasks, huge amounts of image data are produced and stored. Environmental drone image datasets may have value beyond the studies that produced the data. A collection of image datasets from multiple data producers can, for example, provide more diverse training input for a machine learning model for vegetation classification, compared with a single dataset limited in time and location. To ensure reproducible research, research data such as image datasets should be published in usable and undegraded form, with sufficient metadata. Timely storage in a stable research data repository is recommended, to avoid loss of data. This work presents research datasets of 2020 drone images acquired from agricultural and forestry research sites of H?me University of Applied Sciences, and from H?meenlinna urban areas. Those images that do not contain personal data are made freely available under a Creative Commons Attribution license. For images containing personal data, such as images of private homes, privacy preserving forms of data sharing may be possible in the future.
机译:无人机成像已被证明在监测和分析与农业和林业有关的不同类型的过程中具有越来越长的价值。在长期监控和观察任务中,产生并存储大量的图像数据。环境无人机图像数据集可能具有超出产生数据的研究的价值。例如,与时间和位置有限的单个数据集有限,可以为多个数据生产者提供来自多个数据生产商的图像数据集的数据集可以为植被分类的机器学习模型提供更多样化的训练输入。为了确保可重复的研究,应以可用和未扩展的形式发布诸如图像数据集的研究数据,具有足够的元数据。建议在稳定的研究数据存储库中及时存储,以避免丢失数据。这项工作提出了从H的农业和林业研究网站获取的2020个无人机图像的研究数据集?Me Applications Sciences大学以及H?Meenlinna市区。这些不包含个人数据的图像是在Creative Commons归因许可证下自由提供的。对于包含个人数据的图像,例如私人家庭的图像,将来可能是可能的保留数据共享形式的隐私。

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