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Detailed point cloud data on stem size and shape of Scots pine trees

Saarinen, N.; Kankare, V.; Yrttimaa, T.; Viljanen, N.; Honkavaara, E.; Holopainen, M.; Hyyppa, J.; Huuskonen, S.; Hynynen, J.; Vastaranta, M.

2020-03-10 ecology
10.1101/2020.03.09.983973 bioRxiv
Show abstract

Quantitative assessment of the effects of forest management on tree size and shape has been challenging as there has been a lack of methodologies for characterizing differences and possible changes comprehensively in space and time. Terrestrial laser scanning (TLS) and photogrammetric point clouds provide three-dimensional (3D) information on tree stem reconstructions required for characterizing differences between stem shapes and growth allocation. This data set includes 3D reconstructions of stems of Scots pine (Pinus sylvestris L.) trees from sample plots with different thinning treatments. The thinning treatments include two intensities of thinning, three thinning types as well as control (i.e. no thinning treatment since the establishment). The data set can be used in developing point clouds processing algorithms for single tree stem reconstruction and for investigating variation in stem size and shape of Scots pine trees. Additionally, it offers possibilities in characterizing the effects of various thinning treatments on stem size and shape of Scots pine trees from boreal forests. Data setZenodo https://zenodo.org/record/3701271 Data set licenseAttribution 4.0 International (CC BY 4.0)

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.