Current issue: 54(3)
Under compilation: 54(4)
Despite the importance of spectral properties of woody tree structures, they are seldom represented in research related to forests, remote sensing, and reflectance modeling. This study presents a novel imaging multiangular measurement set-up that utilizes a mobile handheld hyperspectral camera (Specim IQ, 400–1000 nm), and can measure stem bark spectra in a controlled laboratory setting. We measured multiangular reflectance spectra of silver birch (Betula pendula Roth), Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.) stem bark, and demonstrated the potential of using bark spectra in identifying tree species using a Support Vector Machine (SVM) based approach. Intraspecific reflectance variability was the lowest in visible (400–700 nm), and the highest in near-infrared (700–1000 nm) wavelength regions. Interspecific variation was the largest in the red, red-edge and near-infrared spectral bands. Spatial variation of reflectance along the tree height and different sides of the stem (north and south) were found. Both birch and pine had increased reflectance in the forward-scattering directions for visible to near-infrared wavelength regions, whilst spruce displayed the same only for the visible wavelength region. In addition, spruce had increased reflectance in the backward-scattering directions. In spite of the intraspecific variations, SVM could identify tree species with 88.8% overall accuracy when using pixel-specific spectra, and with 97.2% overall accuracy when using mean spectra per image. Based on our results it is possible to identify common boreal tree species based on their stem bark spectra using images from mobile hyperspectral cameras.
Spectral libraries have a fundamental role in the development of interpretation methods for airborne and satellite-borne remote sensing data. This paper presents to-date the largest spectral measurement campaign of boreal tree species. Reflectance and transmittance spectra of over 600 leaf and needle samples from 25 species were measured in the Helsinki area (Finland) using integrating sphere systems attached to an ASD FieldSpec 4 spectroradiometer. Factors influencing the spectra and red edge inflection point (REIP) were quantified using one-way analysis of variance. Tree species differed most in the shortwave-infrared (1500–2500 nm) and least in the visible (400–700 nm) wavelength region. Species belonging to same genera showed similar spectral characteristics. Upper (adaxial) and lower (abaxial) leaf sides differed most in the visible region. Canopy position (sunlit/shaded) had a minor role in explaining spectral variation. For evergreen conifers, current and previous year needles differed in their spectra, current-year needles resembling those of broadleaved and deciduous conifers. Two broadleaved species were monitored throughout the growing season (May–October), and two conifers were measured twice during summer (June, September). Rapid changes were observed in the spectra in early spring and late autumn, whereas seasonal variations during summer months were relatively small for both broadleaved and coniferous species. Based on our results, shortwave-infrared seems promising in separating tree species, although it is to-date least studied. The spectral library reported here (Version 1.0) is publicly available through the SPECCHIO Spectral Information System.