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

Rautiainen, Miina; Hovi, Aarne; Schraik, Daniel; Hanuš, Jan; Lukeš, Petr; Lhotáková, Zuzana; Homolová, Lucie

doi:https://doi.org/10.5194/essd-2024-154

Preprints

https://doi.org/10.5194/essd-2024-154

Preprints

18 Jun 2024

| 18 Jun 2024

Status: a revised version of this preprint was accepted for the journal ESSD and is expected to appear here in due course.

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

Miina Rautiainen, Aarne Hovi, Daniel Schraik, Jan Hanuš, Petr Lukeš, Zuzana Lhotáková, and Lucie Homolová

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 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), 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).

Received: 30 Apr 2024 – Discussion started: 18 Jun 2024

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.

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Miina Rautiainen, Aarne Hovi, Daniel Schraik, Jan Hanuš, Petr Lukeš, Zuzana Lhotáková, and Lucie Homolová

Status: closed

RC1:
'Comment on essd-2024-154', Anonymous Referee #1, 23 Jun 2024

The development of radiative transfer (RT) models requires comprehensive ground reference data on both the structural and spectral characteristics of forests. However, such kind of data are currently lacking. The dataset introduced in this paper consists detailed structural data from forest inventory measurements, terrestrial and airborne laser scanning, and digital hemispherical photography, and optical properties of tree leaves and needles, forest floor and entire stands. Such data would be valuable for RT modeling and biophysical validation studies. The paper is finely prepared and I recommend its publication in ESSD.

It would be nice if some field measurement pictures can be provided.
Fig. 7. The legend may be put in panel (a).

Citation: https://doi.org/10.5194/essd-2024-154-RC1
- AC1: 'Reply on RC1', Miina Rautiainen, 25 Jul 2024
  
  Thank you for the positive review! We will take your suggestion into account when preparing the final version of the manuscript.
  
  Citation: https://doi.org/10.5194/essd-2024-154-AC1
RC2:
'Comment on essd-2024-154', Anonymous Referee #2, 08 Jul 2024
The study presents a new dataset based on forest inventory measurements with structural and spectral properties of 58 stands in temperate, hemiboreal and boreal European forests. The dataset is specifically designed to develop and validate radiative transfer models for forests but can also be utilized in other remote sensing studies. It includes detailed information on forest structure and spectral properties at multiple scales. The paper is well-written and structured and provides a valuable and comprehensive dataset for advancing RT models and remote sensing of forests, assuring FAIR data principles. However, I would like to ask the author for a few minor corrections:
L. 22: Specify these new satellite missions.

Chapter 3: Does the data set contain information of measurement uncertainty? Please describe it in the manuscript, or give indications of how it can be derived.

L. 448 /Chapter 4: Data availability: Sharing scientific data effectively within the community is crucial, and I particularly appreciate your adherence to FAIR data principles, which greatly facilitates this process. However, FAIR principles are only mentioned and one reference is cited. Could you please give more details on how your data addresses FAIR principles, see also Box2 in Wilkinson et al., 2016 (https://www.nature.com/articles/sdata201618#Sec6)
Citation: https://doi.org/10.5194/essd-2024-154-RC2
- AC2: 'Reply on RC2', Miina Rautiainen, 25 Jul 2024
  
  Thank you for the positive review! We will take your suggestions into account when preparing the final version of the manuscript.
  
  Citation: https://doi.org/10.5194/essd-2024-154-AC2
RC3:
'Comment on essd-2024-154', Anonymous Referee #3, 25 Jul 2024

A spectral-structural characterization of European temperate, hemiboreal and boreal forests
Summary:
This manuscript presents a ground reference dataset of structural and spectral properties of 58 stands in temperate, hemiboreal and boreal European forests with objective to benchmark 3D radiative transfer models. As a radiative transfer model developer, I realize the importance of field measurements that helps the improvement of radiative transfer models and the space mission Cal/Val activities. I appreciate the presented work. Since I am not expert in field measurement, my comments and questions are mainly from a point of view of a modeler.

Comments and questions:
(1) Section 2.3: It is hard for readers outside of the domain to understand all the details of measurement. I suggest to add several schemata to present the ideas about the measured quantities and the geometry
(2) Section 2.3.6: The reflection and transmission behaviour of leaves and trunks are usually anisotropic. Is it possible to measure BRDF (bi-directional reflectance distribution factor) and BTDF (bi-directional transmittance distribution factor) instead of DHRF and DHTF ? Also, some leaves have strong specular reflection, is the specular reflection included in DHRF ?
(3) Section 2.3.6: Our radiative transfer model is able to simulate the uncertainty propagation (given the uncertainty of leaf optical properties, our model can compute the uncertainty of the simulated image/BRF), is it possible to get simultaneously the measurement and its uncertainty ? I downloaded the spectral transmittance through the link given by the authors, but I did not find information about uncertainty.
(4) Section 2.4.1: For the atmospheric correction, how do you get the local atmospheric profile ?

Citation: https://doi.org/10.5194/essd-2024-154-RC3
- AC3: 'Reply on RC3', Miina Rautiainen, 21 Aug 2024
  
  Thank you for the positive feedback on our paper! Here are our brief responses to your comments.
  1) Thank you for this suggestion! We will add a schemata that shows the different measurement geometries.
  2) The instruments that were available in this project (i.e., ASD RTS-3ZC integrating spheres) are designed to measure DHRF and DHTF and cannot produce data of the BRDF or BTDF of leaf or needle surfaces (or woody components). Measurements of leaf-level DHRF and DHTF are already rather laborious and slow, and multiangular measurements (BRDF or BTDF) would be even slower to make. In this study, we had a fairly large sample size (1314 leaf samples) and the advantage of this is that we are able to look at inter- and intraspecific variation in leaf-level spectral properties. If the measurements were slower (due to obtaining a multiangular data with another type of instrument), then also the sample size would have been significantly smaller. The answer to the second question is: yes, specular reflection was included in the DHRF.
  3) We are happy to hear that you have already tested our spectral transmittance data. We will add a comment on uncertainties in the revised manuscript.
  4) Parameters used in the atmospheric corrections were retrieved directly from the airborne hyperspectral data. However, for the Hyytiälä site, parameters were specifically retrieved from the on-site Aeronet station (CIMEL sunphotometer). We will include this detail in the revised paper.
  
  Citation: https://doi.org/10.5194/essd-2024-154-AC3
RC4:
'Comment on essd-2024-154', Anonymous Referee #4, 08 Aug 2024

The validation of BRDF models and inversion methods are in urgent need of comprehensive ground reference data of forests, as data measurement is extremely difficult. This manuscript proposes a whole dataset on the structural and spectral properties of 58 stands in temperate, hemi-boreal and boreal European forests. The dataset contains both forest structure data and spectral properties at leaves and needles, tree, forest floor and entire stands scales base on in situ and airborne measurements. This dataset is valuable. But the manuscript can be further improved. I suggest the acceptance after revisions with clarification of minor issues.
1) Line 120, It’s better to describe the exact location of "six fixed locations".
2) Line 127, It’s look like there’s a writing mistake as "it would be 8cm if h > 16m", or maybe can explain why the thresholds were determined as this. This is in conflict with the previous definition of mature stands (Line 122).
3) Line 264, What are the criteria for determining whether a needle is current year or one-year-old needle, according to color?
4) Formula (3), What is the measurement method of S_ref,T？According to the formula, S_ref,T in the formula seems to have the same numerical value as S_ref,R?Please clarify it.
5) Line 419 (Fig. 5.) What is the meaning of n in the picture (Number of trees?) (n=34. n=22)? Same problem also can be found in Line 124 and Fig.6.
6) Fig.7. Why only (c) has a legend?

Citation: https://doi.org/10.5194/essd-2024-154-RC4
- AC4: 'Reply on RC4', Miina Rautiainen, 21 Aug 2024
  
  Thank you for the positive feedback on our paper!
  We will make the corrections you mentioned in your feedback (points #1-2 and #4-6).
  Regarding your question #3 about how needle age classes were determined. Needle age classes were not determined only based on color. The position on a branch, and the color of needles and bark of the shoot are macroscopic criteria that were used to recognize current year shoots and needles. They are usually found in the terminal branch positions in sun-exposed branches. The previous-year shoot can be recognized by the presence of dead and partly shed bud scales at the base of the current year shoot. This rule can be used retrospectively to assess shoot and needle age in regularly growing shoots. More information on the developmental process of forming shoots from various bud categories can be found in e.g., Polák et al. 2007 (DOI 10.1007/s00468-006-0093-z).
  
  Citation: https://doi.org/10.5194/essd-2024-154-AC4

Status: closed

RC1:
'Comment on essd-2024-154', Anonymous Referee #1, 23 Jun 2024

The development of radiative transfer (RT) models requires comprehensive ground reference data on both the structural and spectral characteristics of forests. However, such kind of data are currently lacking. The dataset introduced in this paper consists detailed structural data from forest inventory measurements, terrestrial and airborne laser scanning, and digital hemispherical photography, and optical properties of tree leaves and needles, forest floor and entire stands. Such data would be valuable for RT modeling and biophysical validation studies. The paper is finely prepared and I recommend its publication in ESSD.

It would be nice if some field measurement pictures can be provided.
Fig. 7. The legend may be put in panel (a).

Citation: https://doi.org/10.5194/essd-2024-154-RC1
- AC1: 'Reply on RC1', Miina Rautiainen, 25 Jul 2024
  
  Thank you for the positive review! We will take your suggestion into account when preparing the final version of the manuscript.
  
  Citation: https://doi.org/10.5194/essd-2024-154-AC1
RC2:
'Comment on essd-2024-154', Anonymous Referee #2, 08 Jul 2024
The study presents a new dataset based on forest inventory measurements with structural and spectral properties of 58 stands in temperate, hemiboreal and boreal European forests. The dataset is specifically designed to develop and validate radiative transfer models for forests but can also be utilized in other remote sensing studies. It includes detailed information on forest structure and spectral properties at multiple scales. The paper is well-written and structured and provides a valuable and comprehensive dataset for advancing RT models and remote sensing of forests, assuring FAIR data principles. However, I would like to ask the author for a few minor corrections:
L. 22: Specify these new satellite missions.

Chapter 3: Does the data set contain information of measurement uncertainty? Please describe it in the manuscript, or give indications of how it can be derived.

L. 448 /Chapter 4: Data availability: Sharing scientific data effectively within the community is crucial, and I particularly appreciate your adherence to FAIR data principles, which greatly facilitates this process. However, FAIR principles are only mentioned and one reference is cited. Could you please give more details on how your data addresses FAIR principles, see also Box2 in Wilkinson et al., 2016 (https://www.nature.com/articles/sdata201618#Sec6)
Citation: https://doi.org/10.5194/essd-2024-154-RC2
- AC2: 'Reply on RC2', Miina Rautiainen, 25 Jul 2024
  
  Thank you for the positive review! We will take your suggestions into account when preparing the final version of the manuscript.
  
  Citation: https://doi.org/10.5194/essd-2024-154-AC2
RC3:
'Comment on essd-2024-154', Anonymous Referee #3, 25 Jul 2024

A spectral-structural characterization of European temperate, hemiboreal and boreal forests
Summary:
This manuscript presents a ground reference dataset of structural and spectral properties of 58 stands in temperate, hemiboreal and boreal European forests with objective to benchmark 3D radiative transfer models. As a radiative transfer model developer, I realize the importance of field measurements that helps the improvement of radiative transfer models and the space mission Cal/Val activities. I appreciate the presented work. Since I am not expert in field measurement, my comments and questions are mainly from a point of view of a modeler.

Comments and questions:
(1) Section 2.3: It is hard for readers outside of the domain to understand all the details of measurement. I suggest to add several schemata to present the ideas about the measured quantities and the geometry
(2) Section 2.3.6: The reflection and transmission behaviour of leaves and trunks are usually anisotropic. Is it possible to measure BRDF (bi-directional reflectance distribution factor) and BTDF (bi-directional transmittance distribution factor) instead of DHRF and DHTF ? Also, some leaves have strong specular reflection, is the specular reflection included in DHRF ?
(3) Section 2.3.6: Our radiative transfer model is able to simulate the uncertainty propagation (given the uncertainty of leaf optical properties, our model can compute the uncertainty of the simulated image/BRF), is it possible to get simultaneously the measurement and its uncertainty ? I downloaded the spectral transmittance through the link given by the authors, but I did not find information about uncertainty.
(4) Section 2.4.1: For the atmospheric correction, how do you get the local atmospheric profile ?

Citation: https://doi.org/10.5194/essd-2024-154-RC3
- AC3: 'Reply on RC3', Miina Rautiainen, 21 Aug 2024
  
  Thank you for the positive feedback on our paper! Here are our brief responses to your comments.
  1) Thank you for this suggestion! We will add a schemata that shows the different measurement geometries.
  2) The instruments that were available in this project (i.e., ASD RTS-3ZC integrating spheres) are designed to measure DHRF and DHTF and cannot produce data of the BRDF or BTDF of leaf or needle surfaces (or woody components). Measurements of leaf-level DHRF and DHTF are already rather laborious and slow, and multiangular measurements (BRDF or BTDF) would be even slower to make. In this study, we had a fairly large sample size (1314 leaf samples) and the advantage of this is that we are able to look at inter- and intraspecific variation in leaf-level spectral properties. If the measurements were slower (due to obtaining a multiangular data with another type of instrument), then also the sample size would have been significantly smaller. The answer to the second question is: yes, specular reflection was included in the DHRF.
  3) We are happy to hear that you have already tested our spectral transmittance data. We will add a comment on uncertainties in the revised manuscript.
  4) Parameters used in the atmospheric corrections were retrieved directly from the airborne hyperspectral data. However, for the Hyytiälä site, parameters were specifically retrieved from the on-site Aeronet station (CIMEL sunphotometer). We will include this detail in the revised paper.
  
  Citation: https://doi.org/10.5194/essd-2024-154-AC3
RC4:
'Comment on essd-2024-154', Anonymous Referee #4, 08 Aug 2024

The validation of BRDF models and inversion methods are in urgent need of comprehensive ground reference data of forests, as data measurement is extremely difficult. This manuscript proposes a whole dataset on the structural and spectral properties of 58 stands in temperate, hemi-boreal and boreal European forests. The dataset contains both forest structure data and spectral properties at leaves and needles, tree, forest floor and entire stands scales base on in situ and airborne measurements. This dataset is valuable. But the manuscript can be further improved. I suggest the acceptance after revisions with clarification of minor issues.
1) Line 120, It’s better to describe the exact location of "six fixed locations".
2) Line 127, It’s look like there’s a writing mistake as "it would be 8cm if h > 16m", or maybe can explain why the thresholds were determined as this. This is in conflict with the previous definition of mature stands (Line 122).
3) Line 264, What are the criteria for determining whether a needle is current year or one-year-old needle, according to color?
4) Formula (3), What is the measurement method of S_ref,T？According to the formula, S_ref,T in the formula seems to have the same numerical value as S_ref,R?Please clarify it.
5) Line 419 (Fig. 5.) What is the meaning of n in the picture (Number of trees?) (n=34. n=22)? Same problem also can be found in Line 124 and Fig.6.
6) Fig.7. Why only (c) has a legend?

Citation: https://doi.org/10.5194/essd-2024-154-RC4
- AC4: 'Reply on RC4', Miina Rautiainen, 21 Aug 2024
  
  Thank you for the positive feedback on our paper!
  We will make the corrections you mentioned in your feedback (points #1-2 and #4-6).
  Regarding your question #3 about how needle age classes were determined. Needle age classes were not determined only based on color. The position on a branch, and the color of needles and bark of the shoot are macroscopic criteria that were used to recognize current year shoots and needles. They are usually found in the terminal branch positions in sun-exposed branches. The previous-year shoot can be recognized by the presence of dead and partly shed bud scales at the base of the current year shoot. This rule can be used retrospectively to assess shoot and needle age in regularly growing shoots. More information on the developmental process of forming shoots from various bud categories can be found in e.g., Polák et al. 2007 (DOI 10.1007/s00468-006-0093-z).
  
  Citation: https://doi.org/10.5194/essd-2024-154-AC4

Miina Rautiainen, Aarne Hovi, Daniel Schraik, Jan Hanuš, Petr Lukeš, Zuzana Lhotáková, and Lucie Homolová

Data sets

A spectral-structural characterization of European temperate, hemiboreal and boreal forests: Laboratory and field data A. Hovi et al. https://doi.org/10.23729/9a8d90cd-73e2-438d-9230-94e10e61adc9

A spectral-structural characterization of European temperate, hemiboreal and boreal forests: Airborne data A. Hovi et al. https://doi.org/10.23729/c6da63dd-f527-4ec9-8401-57c14f77d19f

Miina Rautiainen, Aarne Hovi, Daniel Schraik, Jan Hanuš, Petr Lukeš, Zuzana Lhotáková, and Lucie Homolová

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Short summary

Radiative transfer models play a key role in monitoring vegetation using remote sensing data such as satellite or airborne images. The development of these models has been hindered by a lack of comprehensive ground reference data on structural and spectral characteristics of forests. Here, we reported datasets on the structural and spectral properties of temperate, hemiboreal, and boreal European forest stands. We anticipate that these data will have wide use in remote sensing applications.


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