01953nas a2200217   4500008004100000022001400041245012000055210006900175260004200244300000900286490000700295520126700302100002001569700001901589700002101608700001801629700002101647700001801668700001901686856003001705       2021                        eng d  a1927-032100aA Year Acquiring and Publishing Drone Aerial Images in Research on Agriculture, Forestry, and Private Urban Gardens0 aYear Acquiring and Publishing Drone Aerial Images in Research on  aOttawabTalent First Networkc02/2021  a5-160 v113 aDrone 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 Häme University of Applied Sciences, and from Hämeenlinna 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.1 aNiemitalo, Olli1 aKoskinen, Eero1 aHyväluoma, Jari1 aLientola, Esa1 aLindberg, Henrik1 aKoskela, Olli1 aKunttu, Iivari  utimreview.ca/article/1418