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Peer review report 2 On “Spatial quantification of leafless canopy structure in a boreal birch forest”
Agricultural and Forest Meteorology 201S (2015) 116
Contents lists available at ScienceDirect
Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet
Peer Review Report
Peer review report 2 On “Spatial quantification of leafless canopy structure in a boreal birch forest”
Original Submission Recommendation Major Revision Comments to Author: The main objective of this study was to examine the ability of aerial LiDAR to map canopy sky fraction. Though the research of this paper would be of interest to the readers of AGRFORMET, I would not recommend the paper in its current form for publication in AGRFORMET for the following main reasons: 1. The findings of this study heavily rely on aerial LiDAR derived canopy height estimates. To derive canopy heights from aerial LiDAR data, the authors binned returns within 4 × 4 meter areas to then derive canopy height estimates for each 4 × 4 meter area by subtracting the mean of all first return heights from the mean of all final return heights within the 4 × 4 meter areas. By using this approach, the authors do not take full advantage of the 1 meter spatial resolution of the aerial lidar data that should allow fitting a more accurate bare earth model (DTM) and canopy model (DSM) when compared to the approach the authors have
DOI of published article: http://dx.doi.org/10.1016/j.agrformet.2013.12.005. 0168-1923/$ – see front matter http://dx.doi.org/10.1016/j.agrformet.2015.07.029
taken. Having a more accurate DTM and DSM should result in more accurate canopy height estimates which might strongly affect the results shown in this study. Hence, I strongly suggest the authors should reanalyze their data by taking full advantage of the 1 meter spatial resolution of the aerial LiDAR dataset. 2. There is a time gap of 6 years between the aerial LiDAR data acquisition (collected in 2005) and the terrestrial LiDAR acquisition (collected in 2011) as well as the aerial LiDAR data acquisition (collected in 2005) and the manual measurements. This big time gap appears to have a considerable effect on the results shown in this study. For example, aerial LiDAR (collected in 2005) shows to underestimate canopy height when compared to terrestrial laser scanner derived canopy height (TLS data was collected in 2011). This result makes sense given that there is a 6 year time gap between the aerial and TLS data acquisition. However, it raises the question how this time gap might have confounded some of the results shown in this study which ultimately challenges some of the findings and conclusion of this work. Anonymous Available online 6 August 2015
Contents lists available at ScienceDirect
Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet
Peer Review Report
Peer review report 2 On “Spatial quantification of leafless canopy structure in a boreal birch forest”
Original Submission Recommendation Major Revision Comments to Author: The main objective of this study was to examine the ability of aerial LiDAR to map canopy sky fraction. Though the research of this paper would be of interest to the readers of AGRFORMET, I would not recommend the paper in its current form for publication in AGRFORMET for the following main reasons: 1. The findings of this study heavily rely on aerial LiDAR derived canopy height estimates. To derive canopy heights from aerial LiDAR data, the authors binned returns within 4 × 4 meter areas to then derive canopy height estimates for each 4 × 4 meter area by subtracting the mean of all first return heights from the mean of all final return heights within the 4 × 4 meter areas. By using this approach, the authors do not take full advantage of the 1 meter spatial resolution of the aerial lidar data that should allow fitting a more accurate bare earth model (DTM) and canopy model (DSM) when compared to the approach the authors have
DOI of published article: http://dx.doi.org/10.1016/j.agrformet.2013.12.005. 0168-1923/$ – see front matter http://dx.doi.org/10.1016/j.agrformet.2015.07.029
taken. Having a more accurate DTM and DSM should result in more accurate canopy height estimates which might strongly affect the results shown in this study. Hence, I strongly suggest the authors should reanalyze their data by taking full advantage of the 1 meter spatial resolution of the aerial LiDAR dataset. 2. There is a time gap of 6 years between the aerial LiDAR data acquisition (collected in 2005) and the terrestrial LiDAR acquisition (collected in 2011) as well as the aerial LiDAR data acquisition (collected in 2005) and the manual measurements. This big time gap appears to have a considerable effect on the results shown in this study. For example, aerial LiDAR (collected in 2005) shows to underestimate canopy height when compared to terrestrial laser scanner derived canopy height (TLS data was collected in 2011). This result makes sense given that there is a 6 year time gap between the aerial and TLS data acquisition. However, it raises the question how this time gap might have confounded some of the results shown in this study which ultimately challenges some of the findings and conclusion of this work. Anonymous Available online 6 August 2015