A spectral–structural characterization of European temperate, hemiboreal, and boreal forests

Abstract. Radiative transfer models of vegetation play a crucial role in the development of remote sensing methods by providing a theoretical framework to explain how electromagnetic radiation interacts with vegetation in different spectral regions. A limiting factor in model development has been the lack of sufficiently detailed ground reference data on both the structural and spectral characteristics of forests needed for testing and validating the models. In this data description paper, we present a dataset on the structural and spectral properties of 58 stands in temperate, hemiboreal, and boreal European forests. It is specifically designed for the development and validation of radiative transfer models for forests but can also be utilized in other remote sensing studies. It comprises detailed data on forest structure based on forest inventory measurements, terrestrial and airborne laser scanning, and digital hemispherical photography. Furthermore, the data include spectral properties of the same forests at multiple scales: reflectance spectra of tree leaves and needles (based on laboratory measurements), the forest floor (based on in situ measurements), and entire stands (based on airborne measurements), as well as transmittance spectra of tree leaves and needles and entire tree canopies (based on laboratory and in situ measurements, respectively). We anticipate that these data will have wide use in testing and validating radiative transfer models for forests and in the development of remote sensing methods for vegetation. The data can be accessed at Hovi et al. (2024a, https://doi.org/10.23729/9a8d90cd-73e2-438d-9230-94e10e61adc9) (for laboratory and field data) and Hovi et al. (2024b, https://doi.org/10.23729/c6da63dd-f527-4ec9-8401-57c14f77d19f) (for airborne data).

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Publication Details

Journal
Earth system science data
Published
2024-11-05
DOI
https://doi.org/10.5194/essd-16-5069-2024
Citations
1
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.46

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article

A spectral–structural characterization of European temperate, hemiboreal, and boreal forests

Zuzana Lhotáková, Aarne Hovi, Lucie Homolová, Daniel Schraik et al.
1 citations
Earth system science data
Remote Sensing in Agriculture
0.46
article

A spectral–structural characterization of European temperate, hemiboreal, and boreal forests

Zuzana Lhotáková, Aarne Hovi, Lucie Homolová, Daniel Schraik, Miina Rautiainen, Petr Lukeš, Jan Hanuš
article en
1 citations

Abstract

Abstract. Radiative transfer models of vegetation play a crucial role in the development of remote sensing methods by providing a theoretical framework to explain how electromagnetic radiation interacts with vegetation in different spectral regions. A limiting factor in model development has been the lack of sufficiently detailed ground reference data on both the structural and spectral characteristics of forests needed for testing and validating the models. In this data description paper, we present a dataset on the structural and spectral properties of 58 stands in temperate, hemiboreal, and boreal European forests. It is specifically designed for the development and validation of radiative transfer models for forests but can also be utilized in other remote sensing studies. It comprises detailed data on forest structure based on forest inventory measurements, terrestrial and airborne laser scanning, and digital hemispherical photography. Furthermore, the data include spectral properties of the same forests at multiple scales: reflectance spectra of tree leaves and needles (based on laboratory measurements), the forest floor (based on in situ measurements), and entire stands (based on airborne measurements), as well as transmittance spectra of tree leaves and needles and entire tree canopies (based on laboratory and in situ measurements, respectively). We anticipate that these data will have wide use in testing and validating radiative transfer models for forests and in the development of remote sensing methods for vegetation. The data can be accessed at Hovi et al. (2024a, https://doi.org/10.23729/9a8d90cd-73e2-438d-9230-94e10e61adc9) (for laboratory and field data) and Hovi et al. (2024b, https://doi.org/10.23729/c6da63dd-f527-4ec9-8401-57c14f77d19f) (for airborne data).

Earth system science dataVol. 16(11)
Charles University (CZ), Natural Resources Institute Finland (FI), Czech Academy of Sciences, Global Change Research Institute (CZ), Aalto University (FI)
Ministerstvo Školství, Mládeže a Tělovýchovy, H2020 European Research Council
Openalex Percentile: Top 28%
Remote Sensing in Agriculture
0.46
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