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

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 dataRGB = 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 heightdbh = 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)