Improving Forest Aboveground Biomass (AGB) Estimation by Incorporating Crown Density and Using Landsat 8 OLI Images of a Subtropical Forest in Western Hunan in Central China
Gen Takao
Round 1
Reviewer 1 Report
Overall:
1. It is an interesting analysis that demonstrated the importance of the canopy density as a variable in AGB estimation models using optical satellite images.
2. Given the canopy density is a key variable, however, you have derived it not by remote sensing but by in situ measurement. It means you should have prior knowledge on the canopy density along with the forest types before the image analysis. I’d like to know how you expect to combine such knowledge with your method to apply to the forest monitoring and/or forestry in the Greater Xiangxi region.
3. Since R2s of the model 1 are very low (Table 5), contribution of the satellite data to your model is questionable. Significance of the overall model and each of the independent variables should be evaluated for each of models 1-3. Scattergrams of the in situ AGB vs. modeled AGB, labelled with the canopy density, would also help the readers understand it.
4. Characters in the figures are too small.
L117 ‘pine forests,’ ‘Chinese fir forests’, 'mixed forests': Are they planted or natural stands? Describe the scientific names of the species and the structure of each forest type.
L119 ‘hm2’: Is it equivalent to ‘ha?’ If so, ‘ha’ might be more popular thus more appropriate. Otherwise, use a more appropriate alternative.
L120 ‘tree volume’: How was it measured?
L132 ‘the first seven bands’: For image texture variables, finer resolution images probably have more information. Why did not you use OLI Band 8?
L151 ‘considered as a categorical variable’: Crown density is by its nature a continuous variable, thus it seems more natural if it is used as a continuous independent variable, transformed appropriately if necessary. Why did you transfer it to a categorical variable? How did you decide the number of classes and the thresholds?
L156-157 ‘a linear regression model (model 1), … (model 3)’: explicitly describe like ‘a linear regression model without the crown density (model 1)’ and so on.
L180 ‘RMSE’: Cross validation is more appropriate for estimating the prediction error. Consider one-leave-out cross validation.
Eq. 3 Square?
L193-197 Since it is a description of the samples and an important hypothesis of your statistic models, this paragraph along with Figure 3 & Table 3 might be located in Section 2.2 instead of 3. Figure 3 can be removed and instead explained in the text.
Table 3 Number of samples for each vegetation type X crown density class are required.
L205-206 ‘the spectral variables as the independent variable (Table 4)’: There is no description on the process and results of selecting the variables on Table 4. Do you mean that the variables in Table 4 were chosen for Model 1 and also used for Models 2 & 3?
L206-210 ‘Model 1 was … AGB estimation.’: This part is a repeat of L156-157 thus redundant.
L254-255 ‘only significantly different from 0 in the thin and medium crown density plots for the fir forest,’: -> ‘significantly different from 0 only in the thin and medium crown density plots for the fir forest,’ ???
Figure 5 What are 'AA' and 'B' in the plots? For Bias% plots, X axis line (Bias% = 0) is required. For RMSE% plots, X axis line (RMSE% = 0) is also recommended. For each of the two types of plot, it's highly recommended to use the same range and ticks along the Y axis throughout the forest types. Reconsider the figure explanation and the labelling (A1, A2, B1, …).
L283-293 Explanation is not clear.
Figure 8 Where?
L295-369 In relation to the above-mentioned comments (Overall-2 & 3),
- It is highly recommended to describe the implication of the study to the forestry or forest management of the region in the Discussion
- More in-depth examination of the satellite image variables is required so as to satisfy a doubt that satellite image might be no use for AGB estimation if canopy density information is delivered from somewhere else
Author Response
Dear editor and reviewers,
Thank you very much for having our paper entitled " Improving Forest Aboveground Biomass (AGB) Estimation by Incorporating Crown Density and Using Landsat 8 OLI Images of a Subtropical Forest in Western Hunan in Central China" reviewed and sending us a bunch of comments, which are quite helpful for us to improve the manuscript. We have carefully revised the manuscript in accordance with the comments raised in the peer-review process, and the original comments are presented in black and our corresponding point-by-point replies are presented in red. Additionally, we have checked the entire sections of the manuscript including main text, figures, tables and references to ensure its compliance with the style or format of Forests. All modifications according to reviewers’ comments are marked in blue ink in the revised version. The itemized response to each comment is provided as follows.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The manuscript is original and presents an interesting approach to estimate forest AGB. A large number of variables have been included in the analysis but they are not well described and it is not clear how they affect the performance of the models specifically which single bands, vegetation indices or transform algorithm and texture measurements are the most effective. These need to be presented in a separate table in the results section and discussed in the text. In addition, the authors should discuss why the performance of the model is not considerably better than previous efforts despite the fact that a newer sensor, new models and many more variables are used. Also In Discussion, the authors should quantitatively compare their results with those from previous research using e.g. Landsat data for AGB estimation.
Some minor comments:
- Abstract needs to be augmented by adding quantitative results and avoiding terms like “better” and the like.
- In Materials and Methods section why the authors selected data in December for their analysis and why they didn’t use surface reflectance products available.
- Limit the number of significant digits in tables.
- Define variables and abbreviations presented in Table 2.
- Figure 3 is hard to understand. Please explain more in the text how it should be interpreted.
Author Response
Dear editor and reviewers, Thank you very much for having our paper entitled " Improving Forest Aboveground Biomass (AGB) Estimation by Incorporating Crown Density and Using Landsat 8 OLI Images of a Subtropical Forest in Western Hunan in Central China" reviewed and sending us a bunch of comments, which are quite helpful for us to improve the manuscript. We have carefully revised the manuscript in accordance with the comments raised in the peer-review process, and the original comments are presented in black and our corresponding point-by-point replies are presented in red. Additionally, we have checked the entire sections of the manuscript including main text, figures, tables and references to ensure its compliance with the style or format of Forests. All modifications according to reviewers’ comments are marked in blue ink in the revised version.
Author Response File: 
Author Response.docx
Round 2
Reviewer 2 Report
The manuscript has been improved and the authors have addressed most of the comments. There are still a few concerns that need to be addressed.
The authors must add a paragraph before Table 2 to explain the types of biophysical information that are used in the study and what they represent. For example, what biophyiscal characteristics texture variables and vegetation indices represent?
I understand that cloud-free images were not available before December but December seems to be too late in the growing season. The authors must better justify the choice of imagery dates and how this affects spectral vegetation indices and texture variables especially for mixed forest land cover.
Finally, these additions must be reflected in the conclusion section as well.
Author Response
Dear editor and reviewers,
Thank you very much for having our paper entitled " Improving Forest Aboveground Biomass (AGB) Estimation by Incorporating Crown Density and Using Landsat 8 OLI Images of a Subtropical Forest in Western Hunan in Central China" reviewed and sending us a bunch of comments, which are quite helpful for us to improve the manuscript. We have carefully revised the manuscript in accordance with the comments raised in the peer-review process, and the original comments are presented in black and our corresponding point-by-point replies are presented in red. Additionally, we have checked the entire sections of the manuscript including main text, figures, tables and references to ensure its compliance with the style or format of Forests. All modifications according to reviewers’ comments are marked in red ink in the revised version.
Author Response File: Author Response.docx
