Data for estimating spruce tree health using drone-based RGB and multispectral imagery

Data for estimating spruce tree health using drone-based RGB and multispectral imagery

Description

The dataset contains multispectral and RGB orthomosaics (.tif), and photogrammetric point clouds (.laz) of four study areas (about 25 ha each), where bark beetle-related decline of Norway spruce has been observed in Helsinki, Finland. The filenames refer to Area 1 (Männikkötie), Area 2 (Maunulanmaja), Area 3 (Hakuninmaa), and Area 4 (Paloheinä), described in detail in Junttila et al. 2022. Multispectral Imagery Provides Benefits for Mapping Spruce Tree Decline Due to Bark Beetle Infestation When Acquired Late in the Season, Remote Sensing 14(4), 909: https://doi.org/10.3390/rs14040909 The image data was acquired between 11th and 14th September 2020. RE = Red-Edge M multispectral data RGB = RGB data (Phantom 4 Pro) Altum = Altum multispectral data The ground sampling distances (GSD) were approximately 3 cm, 5 cm, and 8 cm for RGB, Altum, and RedEdge, respectively. The field reference data file contains 556 geolocated trees assessed in the field (between 11.9. and 17.9.2020), of which 203 were dead and 353 were alive. The data is in polygon format, representing the crown delineation done during the data processing. The file includes tree heights estimated from airborne laser scanning data, dbh (for a subset of trees), discoloration, defoliation, resin flow, bark structural damage, and canopy size estimates. More details are in the journal article mentioned above. Key for Field Reference: Z = tree height dbh = diameter-at-breast-height (cm) vari = Discoloration (score 0-5) harsu = Defoliation (score 0-4) pihka = Resin flows (score 0-2) runko = Stem/bark structural damage (score 0-2) latvus = Significantly decreased canopy size (score 0-1)
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Year of publication

2024

Authors

Department of Built Environment

Hannu Hyyppä Orcid -palvelun logo - Contributor

Juha Hyyppä - Contributor

Juha Raisio - Contributor

Markus Holopainen - Contributor

Mikko Vastaranta - Contributor

Mohammad Imangholiloo - Contributor

Ninni Saarinen - Contributor

Päivi Lyytikäinen-Saarenmaa - Contributor

Samuli Junttila Orcid -palvelun logo - Contributor

Eija Honkavaara - Creator

Niko Koivumäki - Creator

Roope Näsi - Creator

Finnish Geospatial Research Institute - Contributor

University of Eastern Finland - Contributor

University of Helsinki - Contributor

Zenodo - Publisher

Other information

Fields of science

Geosciences

Open access

Open

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

Data for estimating spruce tree health using drone-based RGB and multispectral imagery - Research.fi