Airborne Laser Scanning for Large-Scale Forest Carbon Quantification: A Comparison of LiDAR Single-Tree and Field-Based Methods

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript presents a comparison between traditional field-based and ALS-derived carbon quantification methods. While the topic is relevant to forest carbon monitoring, the work lacks methodological novelty and scientific depth. The so-called “novel ALS approach” is not convincingly new and mainly applies existing commercial software (ForestView®) and standard biomass equations. The analysis is descriptive rather than analytical, and the discussion largely repeats known findings from prior LiDAR–biomass studies. I think this manuscript should be rejected.

 

Detailed comments:

1. The workflow is based on standard ALS processing. No methodological novelty is demonstrated.
2. The ALS–field comparison lacks regression modeling, bias correction, or cross-validation.
3. Please list the biomass equations you used in this study.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Major comments:
1. The current title sets very high expectations that the manuscript does not fully meet. What is presented is essentially a site-specific comparison between a conventional plot-based inventory and a single ALS-derived individual tree product at one experimental forest. There is no clear methodological innovation, and the discussion of “challenges and opportunities” remains largely conceptual. At present, the scope of the work is much closer to a technical validation case study than to a broader assessment of LiDAR-based carbon accounting. Either the title and claimed contribution should be narrowed substantially, or the manuscript needs to deliver a much deeper and more generalizable analysis.

2. A central concern is that the digital inventory is treated as a de facto reference over large parts of the analysis. While extensive, the ALS-based dataset is still the output of a complex detection and allometric modeling chain, and it cannot reasonably be considered free of bias. Presenting differences mainly through the lens of whether the plot mean confidence interval overlaps the ALS estimate effectively places all uncertainty on the field side. This inflates the apparent consistency between methods and obscures the true error structure. A more balanced treatment of uncertainty is essential if the results are meant to inform carbon accounting practice.

3. The digital inventory workflow itself remains too opaque for a study that builds its entire argument on its performance. Key practical issues are left unanswered, including how species identity is assigned to individual ALS-detected trees, how dead wood is distinguished from live trees, and how the algorithm behaves in dense or multilayered stands. These details matter directly for interpreting the large pool-specific discrepancies reported later, especially for dead wood. Without a clearer description of these steps and their known limitations, it is difficult to evaluate the reliability of the digital inventory results.

4. The disagreement between the ALS-based inventory and the field inventory for dead wood is striking and, in my view, one of the most informative results in the paper. However, it is currently treated almost as a side observation. Given how problematic dead wood is for any remote sensing approach, the paper would benefit from a more direct discussion of what is driving this mismatch and what it means for practical carbon accounting.

5. Only four figures are used to support the entire analysis, which feels thin for a paper that covers multiple strata, carbon pools, and inventory approaches. Much of the interpretation rests on tables alone, and several results that would clearly benefit from visual inspection remain abstract. Adding more figures would not just improve readability but would also make the analysis feel more substantial.

Minor comments:
1. The abbreviations for the Douglas-fir strata appear to be swapped between the text and the list of abbreviations.
2. There are occasional small language issues that should be cleaned up during revision. For examples, “and it’s conversion into biomass” (should be “its”).
3. It would be useful to provide a bit more information on point density statistics by stratum, not just the overall average pulses per square meter.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Dear authors, congratluation for an interesting and well received scientific article. 

Yourd manuscript presents straighforward and sound empirical up-to-date ALS carbon quantification research. This manuscript is s well written and correctly formulated and prepared according to the requirements of modern scientific papers, and is ready for publication with only two minor improvements noted in the reviewed text version and marked in yellow in line 42 and in line 250f. I suggest to discuss the latter one in the discussion section, two, similar to the discussion about standing deadwood in line 464 as a suggestion. 

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Well done.

Author Response

Comments 1: Well done.

Response 1: The authors kindly thank the reviewer for their review and kind words. We are very appreciative for the opportunity to publish our work here.