Detection of Geocryological Conditions in Boreal Landscapes of the Southern Cryolithozone Using Thermal Infrared Remote Sensing Data: A Case Study of the Northern Part of the Yenisei Ridge

Round 1

Reviewer 1 Report

The paper discusses the possible use of infrared remote sensing data to determine geocryological conditions, based on ground observation and satellite remote sensing. This is a interesting task. The approach in this paper might be also used in the identification of the hydrological regime dynamics of soils and trends in permafrost landscape changes. The structure of the paper is clear. However, there are some contents that should be improved, as given below: 

1. Line 70-71: Literature references should according to the order of appearance. The reference sequence should be 10-19, not 10,19.

2. Line 197: some figures need to be improved. For instance, the numbers in axis in the figure 2 is too small, fuzzy, see not too clear, should be perfected. So are figure 3 in Line 207, figure 4 in Line 269. The labels in the vertical axis and horizontal axis are omitted in the figures 2-4.

3. The thermal infrared data from satellite is image brightness which includes the effects of thermal radiations generated by both air and land surface. The method for obtaining near-surfacer temperatures thermal infrared data through should be introduced in the test.

4. There are three or four “temperatures” in the text (near-surface temperature, land temperature and land surface temperature, land surface air temperatures) .Are they different or same?

5. L140: The near-surfacer should be near-surface. Please check it.

6. The basic theory for determining geocryological conditions with infrared remote sensing data is not so clear. If possible, some physical principle are concisely discussed or added in the manuscript. 

Author Response

We thank very much the reviewer for very helpful and constructive comments and recommendations. The manuscript has been revised in accordance with made suggestions to produce an improved version of the article.

Below we present the point by point answer to the reviewer’s comments.

All additions and changes to the manuscript are highlighted in green.

№	Comments of reviewer	Response
1	Literature references should according to the order of appearance. The reference sequence should be 10-19, not 10,19	We corrected the references.
2	Line 197: some figures need to be improved. For instance, the numbers in axis in the figure 2 is too small, fuzzy, see not too clear, should be perfected. So are figure 3 in Line 207, figure 4 in Line 269. The labels in the vertical axis and horizontal axis are omitted in the figures 2-4	We corrected the figures.
3	The thermal infrared data from satellite is image brightness which includes the effects of thermal radiations generated by both air and land surface. The method for obtaining near-surfacer temperatures thermal infrared data through should be introduced in the test.	Section “Research methodology” has been expanded with a description of obtaining LST from Level 2 Landsat data.
4	There are three or four “temperatures” in the text (near-surface temperature, land temperature and land surface temperature, land surface air temperatures) .Are they different or same?	We corrected to a single term «land surface temperature» and/or LST.
5	L140: The near-surfacer should be near-surface. Please check it.	We corrected.
6	The basic theory for determining geocryological conditions with infrared remote sensing data is not so clear. If possible, some physical principle are concisely discussed or added in the manuscript.	We added a diagram illustrating the basic theory to the “Results and Discussion” section (Figure 4).

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Review of the manuscript: “Detection of geocryological conditions in boreal landscapes of

the southern cryolithozone using thermal infrared remote sensing data - a case study of

the northern part of the Yenisei Ridge.”

The manuscript tackles a significantly important problem in the application of thermal

remote sensing for the study of landscapes. The critical issue of detecting characterizing and

analyzing the thermal dynamics of boreal landscapes. This is because the boreal landscapes are

especially sensitive to the impact of currently warming climate. Located at higher latitudes where

the global warming tends to occur faster than at lower latitudes, the application of methodologies

for further understanding boreal landscapes’ thermal behavior and its dynamics become an

essential tool for assessing climate change associated matters. The methodology applied in the

manuscript is very consistent and well founded. The use of transects for extracting thermal profiles

and its further complementary analysis with profiles of vegetation indices is a very appropriate and

well-established analytical method for comparatively studying thermal landscapes of boral forests.

The analysis of satellite remotely sensed data coupled with a systematically conducted quantitative

and qualitative in-situ fieldwork data collection constitute a very robust methodological approach

with a high significant value. Employing fieldwork collected data for supporting the analysis of

satellite observations from earth’s skin surface temperature grants this research with a wellfounded

methodological approach. Therefore, the authors methodological decision of using in-situ

collected fieldwork data is indeed very relevant and supports the studies’ validity.

Furthermore, is notable the profuse advanced knowledge on the boral frost thermal

landscape dynamics, as well as in its characteristics and processes the authors express in the

manuscript. The application of such deep knowledge to support the analytical descriptions

provided largely increase the value of the insights and the discussion of the manuscript. The

manuscripts offer a robust thermal remote sensing-based methodology and firmly supported

research results, both of enormous scientific value.

In addition, the thermal characteristics of these particular type of boreal landscapes have

not been largely studied. The applied methodology permitted extending our knowledge of the

thermal dynamics of these particular types of boral landscapes, the Siberian southern

cryolithozone. The characterization, analytical descriptions and insights provided constitute a novel

valuable knowledge for understanding the northern Siberian landscapes’ thermal behavior.

In conclusion the manuscript constitutes a valuable asset for researchers in the field and it

is indeed a significant contribution to the discipline form both the methodological approach applied

and landscape analysis developed.

However, a particular disclaimer with regards the result’s validity is strongly suggested for

this manuscript. Although the results were well demonstrated for the region of study employing atsensor

brightness temperature for mapping earth surface temperature, while land surface

temperature (LST) was not retrieved from at-sensor brightness temperature, and none

atmospherically corrected top-of-atmosphere (TOA) spectral reflectance data was employed for

calculating the vegetation indices—only radiometric corrections were performed—hence whether

similar results will be achieved employing LST and atmospherically corrected spectral reflectance

still need to be clarified.

As general assessment, given its substantial contribution to the discipline, I think the

manuscript should indeed be published, but only after undergoing the mayor revisions herein

suggested. The suggested revisions and remarks are divided according to each of the sections

constituting the manuscript and explained point-by-point below with further details, including the

line numbers in the manuscript text for each comment or remark. All of them require the attention

of the authors. However, please note that the comments and remarks listed here: Line 70

(Introduction section); From line 148 to line 154 (Research Methodology section); Line 156

(Research Methodology section) are of major importance and it is strongly suggested to be

addressed with especial attention and resolved by the authors.

Comments regarding the Abstract

Line 14: “The paper discusses the possible use of infrared remote sensing data to determine … “

I would suggest to express the first statement assertively meaning instead of expressing

in line 14 “The paper discusses the possible use of…“ to remove the word “possible”, and instead

start the first phrase of the abstract expressing it as: “This paper discuss the use of …”. This is

because in fact the manuscript actually discusses the use of infrared remote sensing data. It is not

a “potential” but an actually an action later performed in the manuscript.

I would even better suggest to the authors to start the abstract’s first phrase with an

expression closer to: “This paper discusses the potential of using …” This last option seems to me

a more appropriate way to present the first phrase of the abstract.

Line 15 and 16: “The study is based on analysis of Landsat TM thermal infrared images and

land surface air temperatures.”

From the text is possible to infer that only Landat-8 images were used since other Landsat

satellites were not mention in the text. It is important to note that the term “Landsat TM” is reserved

for Landsat Thematic Mapper (TM) which correspond to a multispectral scanning radiometer on

boar of Landsat-4 and Landsat-5 with multiple bands covering the visible and Infra-Red regions of

the electromagnetic spectrum with an operating time ranging approximately from July 1982 to June

2013.

I suggest to the authors that in case images from Landsat TM sensor were used, it should

be also described in the Research Methodology section. Otherwise, it is suggested to mention in

the abstract only the sensors corresponding to the satellites that were effectively used in the

research. As far as I understand the authors have only used Landsat-8 data from OLI and TIR

sensors.

I suggest the authors to correct this in the abstract.

In addition, the authors are saying “The study is based on analysis”, maybe the authors

wanted to say “The study is based on the analysis”

I suggest the authors to correct this in the abstract.

In addition, the term “land surface air temperature”, sounds a bit contradictory, since in general the

term used is either “land surface temperature” or LST for referring to earth’s surface temperature

and “air temperature” or Ta for referring to the temperature at a given height from the ground.

In addition, later in the manuscript the term “near-surface temperature” is interchangeably

“land surface temperature”.

I suggest to the authors that for the sake of consistency to use the same term to define the

same concept. This point is explained with details later in this report especially with further

comments in Line 49—please see below.

Comments regarding the Introduction Section

From line 46 to line 51: “Modern remote sensing technologies make it possible to quickly monitor

the geophysical parameters of landscapes’ functioning at various spatial levels. In relation to the

problem considered in this paper, thermal infrared remote sensing data can be processed to derive

near-surface temperature maps. Thermal imaging that utilizes the intensity of infrared radiation

allows identifying different types of forests by their biogeophysical characteristics [2].”

This paragraph is indeed important for the introduction given the relevance of thermal

remote sensing in this study. However, since the main objective of this research seem to me that

is centered in the application of a methodology based upon thermal remote sensing for the

detection and assessment of geocryological conditions in the boreal landscape—for the specific

type of the southern cryolithozine—therefore I suggest to extend a bit more the discussion of

previews research. I suggest to extend the discussion on the use of remote sensing for the analysis

thermal characteristics of boral landscapes, and/or to related general characteristics of boreal

landscapes. Extending a bit more the discussion of previous research that have tackled the same

topic as well as the research advances in the analysis of similar landscapes types, if exists in the

literature, will indeed constitute a significant benefit for the quality of the manuscript.

Line 49: "near-surface temperature":

I have found the use of this term in the literature; it is indeed correct to be used. Although,

it is important to mention to the authors that in thermal remote sensing literature the images

obtained from the preprocessing of thermal infrared (TIR) bands, for instance from Landsat-8 TIR

Sensor data (bands 10 and band 11), for analyzing the temperature values of landscape features

such as vegetation and soil—which constitute part of the earth surface or the skin of earth’s

surface—are rather called "land surface temperature" with its abbreviation LST or in some cease

also just "surface temperature" with its abbreviation ST. For further and more precise expiations in

this regard see my comments bellow in the section Regarding Methodology Section of this

review.

Line 54: “The equation of the heat balance of the Earth’s surface”.

Here I suggest to cite here the bibliographical reference to the equation mentioned.

Line 70: “This approach can be used for mapping permafrost-taiga landscapes [10, 19-24]. This

is most true for the territories of the southern part of the boreal cryolithozone [3, 15, 22], where the

contrast of forest growing conditions is the highest, which is noticeably expressed in the phytomass

stocks of taiga landscapes and in the intensity of their thermal flux.”

Indeed, these phrases are correct and reflect an important standpoint to express in the

introduction.

However, since the objective of this research is to present the application of a methodology

for the detection, assessment and analyses of thermal dynamics of the geocryological conditions

of the boreal landscape—for the specific type of the southern cryolithozine—together with a study

of such area, I strongly recommend to the authors to extend the phrases cited above. Expanding

them from a mere mention of the existence of the previous research on the topic of permafrosttaiga

landscapes mapping to a further step beyond. In this manner, I suggest a strictly brief

literature review with the minimum possible details of the methodological approaches developed

as well as the investigations performed by some of the most significant preceding research that

have tackled the same or very closely similar topics. Giving particular attention to the advantages

and disadvantages such previous investigations might present, and if relevant also briefly report

their achieved results. I found that, although the existing bibliography in the topic is not extremely

profuse, there are some published research related to the permafrost-taiga landscape mapping

and also some of them employing thermal infrared remotely sensed data. Though, in some cases

applying different methodologies to that one proposed in the manuscript while in some others

performed in similar by not exactly the same landscape types. Nevertheless, very briefly describing

such literature can give a context for introducing the methodology employed in the manuscript as

well as the previous investigation performed within the field—i.e., assessing detecting and

analyzing similar types landscapes. In addition, I think that a brief literature review describing

previous research on the topic can largely enrich the introduction by defining a framework, as well

as giving also further justification for the application of the methodology employed and the

development of the study of the specific type of landscapes analyzed. By briefly extending the

introduction with descriptive references to such previous research—literature review in the topic—

together with highlighting the particular advantages of the applied methodology in the manuscript

will serve not only to better familiarize the reader but to give a contextual frame to the manuscript.

Briefly describing current state of the literature on the thermal dynamics of the studied landscape

types or about the aspects treated in relation to this type of landscapes is essential for

strengthening the introduction. This will also serve to highlight the gap existing in the field,

afterwards approached by the methodology and the study developed in the manuscript. In addition,

it will also serve for showing the relevance of the methodology applied in the manuscript in

comparison to other existing once and describing its large contribution to the field of the study

For this purpose, I suggest to the authors to choose the relevant bibliography to be briefly

described in the introduction section. I specially recommend to the authors to choose the

bibliography already mentioned in the manuscript, however not yet described in a brief manner.

The citation numbers to the bibliography mentioned in the manuscript correspond to the citation

numbers [10, 19-24] and [3, 15, 22].

As I have mentioned before, I have found that there is not an abundant bibliography on the

topic, however I have found the bibliography listed below, which might be of some relevance or

usefulness due to its closeness to the topic developed in the manuscript. The bibliography listed

below might not exactly match the research topic treated in the manuscript, but still might constitute

some examples of existing research that has connection with aspects that are treated in the

manuscript and are part of the study described in the manuscript. The references of such

bibliography are provided just in case the authors of the manuscripts would like to consult it.

- Kalinicheva, S., Fedorov, A., & Zhelezniak, M. (2018). Mapping Mountain Permafrost

Landscapes in Siberia Using Landsat Thermal Imagery. Geosciences, 9(1), 4.

https://doi.org/10.3390/geosciences9010004

- Morrissey, L. A., Strong, L., & Card, D. H. (1986). Mapping permafrost in the boreal forest

with thematic mapper satellite data. Photogrammetric Engineering and Remote Sensing,

52, 1513–1520.

- Ranson, K. J., Sun, G., Kharuk, V. I., & Kovacs, K. (2004). Assessing tundra–taiga

boundary with multi-sensor satellite data. Remote Sensing of Environment, 93(3), 283–

295. https://doi.org/10.1016/j.rse.2004.06.019

- Terentieva, I. E., Glagolev, M. V., Lapshina, E. D., Sabrekov, A. F., & Maksyutov, S. (2016).

Mapping of West Siberian taiga wetland complexes using Landsat imagery: implications

for methane emissions. Biogeosciences, 13(16), 4615–4626.

https://doi.org/10.5194/bg-13-4615-2016

- Westermann, S., .stby, T. I., Gisn.s, K., Schuler, T. V., & Etzelmüller, B. (2015). A ground

temperature map of the North Atlantic permafrost region based on remote sensing and

reanalysis data. The Cryosphere, 9(3), 1303–1319. https://doi.org/10.5194/tc-9-1303-2015

- Helbig, M., Wischnewski, K., Kljun, N., Chasmer, L. E., Quinton, W. L., Detto, M., &

Sonnentag, O. (2016). Regional atmospheric cooling and wetting effect of permafrost thawinduced

boreal forest loss. Global Change Biology, 22(12), 4048–4066. Portico.

https://doi.org/10.1111/gcb.13348

- Zakharov, M., Gadal, S., Kamičaitytė, J., Cherosov, M., & Troeva, E. (2022). Distribution

and Structure Analysis of Mountain Permafrost Landscape in Orulgan Ridge (Northeast

Siberia) Using Google Earth Engine. Land, 11(8), 1187.

https://doi.org/10.3390/land11081187

- Bartsch, A., H.fler, A., Kroisleitner, C., & Trofaier, A. (2016). Land Cover Mapping in

Northern High Latitude Permafrost Regions with Satellite Data: Achievements and

Remaining Challenges. Remote Sensing, 8(12), 979. https://doi.org/10.3390/rs8120979

- E. Nyland, K., E. Gunn, G., I. Shiklomanov, N., N. Engstrom, R., & A. Streletskiy, D. (2018).

Land Cover Change in the Lower Yenisei River Using Dense Stacking of Landsat Imagery

in Google Earth Engine. Remote Sensing, 10(8), 1226. https://doi.org/10.3390/rs10081226

- Gido, N. A. A., Bagherbandi, M., Sj.berg, L. E., & Tenzer, R. (2019). Studying permafrost

by integrating satellite and in situ data in the northern high-latitude regions. Acta

Geophysica, 67(2), 721–734. https://doi.org/10.1007/s11600-019-00276-4

- How Can the Dynamics of the Tundra-Taiga Boundary Be Remotely Monitored? Author(s):

Gareth Rees, Ian Brown, Kari Mikkola, Tarmo Virtanen and Ben Werkman Source: Ambio,

Special Report Number 12. Dynamics of the Tundra-Taiga Interface (Aug.,2002), pp. 56-

62Published by: Springer on behalf of Royal Swedish Academy of Sciences Stable URL:

http://www.jstor.org/stable/25094576

Lines 74 and 75:

Before finishing the introduction, I would suggest to the authors to introduce very briefly

the content of the different sections of this manuscript, with an extremely brief summary of one or

two sentences. This will enable the reader to have an introductory view of the structure or

organization of the paper they will be reading.

Comments regarding “Study Subject” Section

Line 76: the title of this section: “Study Subject”

I would suggest to call this section differently maybe something closer to: "Characterization

of Area of Study" or just “The Area of Study” or something similar chosen by the authors. This is

because in this section it is mainly described the area or region of study and its environmental

conditions, such as geocryological condition as well as the properties of the taiga-permafrost

landscape. All of those are features representing environmental ecological aspects and landscape

descriptions of the area or region of study, rather than an expression of the proper "Study subject".

In my opinion, the “Study Subject” is mostly understood as the research's subject matter, the

problem itself to be studied in the research. I see in this section a very good analytical description

of the area or region of study covering its geocyological conditions together with a detailed

description of the of the taiga-permafrost landscape properties. While I assume the subject matter

of this particular study, or its "Study subject" (to put it in the author's worlds), is mores oriented to

the application of thermal remote sensing methodology for mapping detecting and analyzing the

geocryological conditions and characteristics of the forests in taiga-permafrost landscape with a

case study demonstrating the application of such methodological approach.

Figure 1:

I suggest improving the visual quality of the X-Ticks and Y-Ticks of the map coordinates—

probably enlarging the font size or its thickness—to make the map's coordinates easier to read.

In addition, in the capitation of figure 1 it would be a benefit for the reader’s better

understanding of the map to express to which geographical variable the raster values of such a

map correspond. From line 74 of the text is possible to infer that figure 1 corresponds to a terrain

map. Is this correct? If so, I therefore assume the map's pixel values correspond to altitude values

of the terrain. In any case, it would be a benefit for the reader’s understanding of the map to explicit

in the figure's caption the pixels value significance, e.g., terrain altitude, if it is the case.

Moreover, adding a colormap bar of the pixels' values depicted in the map would make the

map more informative to reader for a better understanding the map’s raster values in the region of

study as well as making it possible to distinguish the differences in pixel values (possibly

differences in altitude...?) between the site of study with regards to its surrounding geographical

context.

In the map the text in red color "Under study area" can be located in the figures caption as

part the caption text. In this manner, in the caption of figure 1 a text saying for instance: "the red

rectangle corresponds to the area of study”, can be suitable or a similar text chosen by the authors.

In any case, instead of placing the text inside the map—which can lead unnecessarily to lose

information represented in the map, in my opinion it would be better to locate the text in the caption

of the figure.

The upper left corner of figure 1 indicates global geographical frame of the area of study.

As far as I understand the area of study is located within the Federal District of Siberia, and within

it in the Krasnoyarsk Federal Subject or Krasnoyarsk Krai. However, readers not completely

familiarized with Russian Federation Federal Subjects or the divisions of the Siberian Federal

Districts might not easily acknowledge the general geographical frame where the aera of study is

located in the map by looking at the smaller gray map located at upper left corner of figure 1. In

this respect, it is recommended to the authors to use the gray colored map at the left upper corner

of figure 1 to show a wider geographical region that might enable the reader to easily identify the

general geographical frame where the area of study is located within either the Siberian Federal

Region or alternatively a larger region of the Russian Federation. An example to improve this

aspect of figure 1 can be found in the map on page number 3 of the following paper:

- E. Nyland, K.; E. Gunn, G.; I. Shiklomanov, N.; N. Engstrom, R.; A. Streletskiy, D. Land

Cover Change in the Lower Yenisei River Using Dense Stacking of Landsat Imagery in

Google Earth Engine. Remote Sens. 2018, 10, 1226. https://doi.org/10.3390/rs10081226

Alternatively, for instance, and just as an example (an idea for the authors): gray colored

map at the upper left corner of figure 1 might be more informative if it shows the extent of the whole

Russian Federation, and within it the borders of a polygon defining the Federal Subject of

Krasnoyarsk Krai, and within it another rectangle as a small polygon delimitating the area of study.

It is just an idea. In any case, any possible way the authors find to clarify the general geographical

frame where the study area is located for an easy identification by the reader will be more than

suitable.

From Line 121 to line 125: “Along the transects, test geobotanical sites (100 m2) were

established, where the compositions of stands and ground cover were studied in detail. Tree

species were counted; tree height and diameter (at 1.5 m height) were measured and averaged.

Thus, the phytomass stocks were calculated, which were then compared with the obtained remote

sensing data.”

This part of field work seems to imply a quantitative data collection, analysis of such data

and calculations preformed over such data for obtaining an environmental indicator named

“phytomass stocks”. For a further comparison of such environmental variables with data obtained

from remote sensing.

Firstly, given that authors have conducted a significant systematic fieldwork collecting

quantitative data on:

a. count of tree species

b. tree height

c. tree diameter at 1.5 m height

it would be highly valuable and interesting for the reader to have access to at least one or two

examples—a part or price of such data—in an organized from, for instance preferably with a graph

or alternatively with a table. This does not mean is suggested to include in the methodological

section all the collected data obtained in the fieldwork, but it is suggested that would be interesting

and valuable to have visual clue of at least a part of it as one or two examples that characterize

the collected data. For instance, as an example, for a give defined geographically entity such as a

site, area, region or transect etc., where data was collected, a graph or table showing the numerical

values obtained in the fieldwork for each of the different variables can be very informative and

valuable. If the authors would like to include the complete data set collected in the fieldwork, maybe

a graph or table that summarize it would be one of the best options. However, depending on the

format of the data and its length it could be that placing it in a complementary material section

would be a more suitable option.

Secondly, I would suggest to the authors to include in this section the formula or equation

used for calculating the “phytomass stocks”, together with its correspondent citation. This is

because it is a quantitate environmental indicator which its estimation was not described, while it

is part of the methodology employed and it is further used in the analysis. An example of the

calculated phytomass stocks” for the collected data also would be a very valuable information.

Probably a graph or table of the calculated phytomass stocks with its values associated for

instance to the different types of landscapes can also be very informative.

I suggest this because showing to the reader the fieldwork data collected—preferably in a

graph and if not possible alternately as a table—together with the values of the environmental

indicators obtained from it (e.g., phytomass stocks), provide with both higher degree of

understanding and familiarization with the research process, as well as with solid evidence that

can further aid to validate remotely sensed results. This is suggested since the data obtained in

the fieldwork conducted is an important part of this study. To have access to an overview of the

fieldwork data set collected can also provide with a better understanding of the local environmental

condition of the studied area, as well as provide with a greater support for any further analysis of

remotely sensed data performed in the manuscript. Fieldwork data grants research employing

remotely sensed information with a high level of validity.

From line 125 to line 128: “The presence of permafrost was identified using visually pronounced

characteristics and established methods typical of permafrost systems for the studied area [12-

15], some of which are shown in the pictures presented in the sections below.”

This part of the fieldwork seems to imply visual observation techniques corresponding to a

qualitative methodological approach for recording spatial-visual properties of landscapes.

Photographs or pictures of permafrost locations and other landscape features, indeed constitutes

a relevant source of information as well.

From line 128 to line 132: “In general, the impact of permafrost on boreal landscapes of southern

cryolithozone includes increased water content of surface sediments, appreciable peat thickness,

evidence of soil cryoturbation, abundance of cryogenic relief forms, distinct structure and

composition of the vegetation cover (e.g., sparseness and suppression of stands, prevalence of

sphagnum moss and dwarf birch in surface cover).”

This paragraph seems to me more oriented to describe the permafrost properties on boreal

landscapes of the region where the study was performed, the southern cryolithozone. Therefore,

if this paragraph represents information or conclusion derived from observational fieldwork

conducted by the authors at the specific site of study, I suggest to place this paragraph in a more

appropriate section of the manuscript such as section 3. Results and Discussion section. Whereas

if this paragraph contains knowledge on the permafrost properties of boreal landscapes that

corresponds to specific bibliographical sources, I suggest to the authors to add such bibliographical

source and place this paragraph at a more suitable section such as for example the section 2

called by the authors in the manuscript “Study Subject”. If this paragraph corresponds to the

authors’ general knowledge on the topic of boral landscapes properties and has not been taken

from any specific bibliographical source, then I suggest the authors likewise, to place this

paragraph in section 2 now called by the authors “Study Subject”. In any case, this paragraph

contains information that in my option does not correspond to the Research Methodology section.

The methodological section is expected to contain techniques, processes, steps followed,

formulas, equations, software and algorithms, descriptions of models applied among other

methodological procedures.

Lines 132 to 135: “The natural ecosystems within the transects were examined for the evidence

and character of past fires. The thickness of the seasonally thawed layer at the observation points

was estimated with a probe and also visually — in pits and soil cross-sections.”

This fieldwork collected information corresponding to a both qualitative visual observation

with regards to the evidence of past fires and both qualitatively visual observation and quantitative

probe estimation for seasonally thawed layer. These are very relevant sources of information.

Comments regarding the Research Methodology Section

Line 138: “… obtained during the active growing season (July, August) and summer periods with

consistently high air temperatures in 2013, 2016, and 2018, which allowed us to 139 obtain values

for near-surfacer temperatures”

First, I suggest to the authors to pay attention to the spelling of “near-surfacer

temperatures”.

Second, since the temperature of the earth’s surface changes over the hours of the day, I

suggest to the authors to include the time using the local time corresponding to the location where

the images were taken. The metadata file of the Landsat-8 images provides the time when the

satellite took the images. The time at the exact location where the satellite took the image can be

obtained from such metadata file and further converted to the local time corresponding to that of

such location. Alternatively, the time when the image was taken can also be expressed as GMT.

Lines 144-145: “data in two channels — 10 and 11“

Line 146: “Channel 10”

I suggest specifying the wavelength of Landsat-8 TIR bands between brackets with its

units. This will enable the reader rapidly identifying the region of the electromagnetic spectrum in

question. I suggest to use the term “bands” instead of “channels” to follow a more conventional

used terminology in remote sensing literature.

From line 148 to line 154: “Remote sensing data processing was carried out using QGIS in two

stages. Initially, for fragments of the scenes, we calibrated the dimensionless values of the initial

image brightness (Digital Number, DN) in terms of the values of the radiation arriving at the sensor.

Then these values were recalculated into surface temperatures (˚С). Thus, the cartographic

images of the thermal field were created, rendered in the same color scheme. The images were

used to build temperature profiles; the values of near-surface temperatures were derived in the

points of field-descriptions.”

a. With regards to the software used by the authors for processing remote sensing data, I suggest

to cite the software used (QGIS Software) in the bibliography with its explicit version and year.

Similarly for other software used, such as the software used to extract the temperature profiles

from the images.

b. With regards to “near-surface temperature” data/images: preprocessing of Landsat-8 TIR

Sensor data to LST mainly includes several corrections (preprocessing steps) to convert raw

data level 1 in digital numbers (DN) to LST.

Firstly, DN—or level 1 TIR data—need to be converted to top-of-atmosphere (TOA)

spectral radiance. Secondly, such top-of-atmosphere (TOA) spectral radiance needs to be

converted to top of atmosphere brightness temperature (T or BT) also called at-sensor-brightness

temperature. (For conversion steps from Level 1 data see https://www.usgs.gov/landsatmissions/

using-usgs-landsat-level-1-data-product ). Thirdly, BT can be further converted to LST.

This last step is generally needed because, Landsat-8 TIR Sensors’ data depends on surface

parameters such as temperature and emissivity as well as on atmospheric effects. Therefore, in

order to overcome the influences of such atmospheric and ground effects corrections for emissivity

and atmospheric effects are needed. As is further explained in a more rigorous detailed manner at

for instance:

- Li, Z.-L., Tang, B.-H., Wu, H., Ren, H., Yan, G., Wan, Z., Trigo, I. F., & Sobrino, J. A. (2013).

Satellite-derived land surface temperature: Current status and perspectives. Remote

Sensing of Environment, 131, 14–37. https://doi.org/10.1016/j.rse.2012.12.008

Many algorithms have been developed for converting at-sensor-brightness temperature (T

or BT) images to LST images. Such as Radiative Transfer Equation (RTE), Mono-Window

Algorithm (MWA), Split-Window Algorithm (SWA), and Single-Channel Algorithm (SCA) among

several others. For a brief and simple description (in a nutshell description) of the four main

methods for retrieving LST from Landsat-8 TIR Sensor check section 3.2 of the paper below at

pages 4-6:

- Jiang, Y., & Lin, W. (2021). A Comparative Analysis of Retrieval Algorithms of Land Surface

Temperature from Landsat-8 Data: A Case Study of Shanghai, China. International Journal

of Environmental Research and Public Health, 18(11), 5659.

https://doi.org/10.3390/ijerph18115659

Most of these algorithms are not straight forward to apply, demand further complex and

heavy computational processing, while in many cases make use of various types climatological

ancillary data, which are not always available.

However, nowadays, such complex processing needed to retrieve LST from at-sensorbrightness

temperature images—by means of the abovementioned methods—has been largely

overcome by the USGS already preprocessed Landsat-8 TIR Sensor Collection 2 Level 2 data

products. The USGS offers LST data already processes from Landsat TIR bands with its Collection

2 Level 2 data products. In this manner, such a novel uncomplicated solution to the complex

processing required for retrieving LST from BT constitute an advantage for the research

community. (For Landsat Collection 2 Level 2 Surface Temperature see:

https://www.usgs.gov/landsat-missions/landsat-collection-2-surface-temperature ).

For Landsat 8 Collection 2 Level 2 see the bibliography:

- USGS (2021). Landsat Collection 2 Level-2 Science Products. Fact Sheet.

https://doi.org/10.3133/fs20213055

USGS Collection 2 Level 2 Products Guide Downloadable from:

https://www.usgs.gov/media/files/landsat-8-9-collection-2-level-2-science-product-guide

These products are already converted to LST and ready to be download. Landsat-8 LST

data can be downloaded directly either from the USGS Earth Explorer platform (

https://earthexplorer.usgs.gov/ ) or from Google Earth Engine (GEE) platform. However, note that

the application of a scaling factor could be still required to obtain the final LST data. If the authors

are using these already preprocessed LST downloaded either from USGS or GEE, it is suggested

to be further explicitly described in the methodology section of the manuscript together with the

correspondent citation sources.

It is suggested that if the "near-surface temperature" maps the authors are employing in

this study are produced following a different preprocessing to the abovementioned ones for the

Landsat-8 TIR Sensor data, such a preprocessing also be explicitly described in the Research

Methodology section of the manuscript together with the bibliographical sources for the equations

or algorithms applied for the performed data preprocessing.

That said, it is important to note that is indeed incorrect to equate BT to LST or “near

surface-temperature”. Although, there exist several cases of publications that equate BT to LST or

to “near-surface temperature” maps, not retrieving LST from BT and employing directly BT as

surface temperature data, this procedure is considered for most of the case incorrect. It can be

said that, only in some especial cases the use of BT without farther preprocessing is strictly

reserved to be employed in more relative specific studies. If the authors have used at-sensor

brightness temperature (BT) data directly for obtaining “near-surface temperature” data maps from

Landsat-8 TIRS bands without farther corrections, it is necessary to first explicitly justify in the

Research Methodology, why such correction are not necessary to be done. Otherwise, I suggest

to the authors that is necessary to make the correspondent corrections (atmospheric and

emissivity).

To the best of my knowledge, I would suggest that for most of the cases is only correct to

use LST rather than directly BT data for obtaining temperature values of landscape features of the

earth surface such as vegetation and soil. This because the Landsat-8 TIR Sensors—as most of

currently existing satellite TIR data till today—are not unsusceptible to atmosphere and ground

effects influencing the at-sensor brightness temperature (BT). Therefore, I suggest to the authors

of this manuscript the use of LST retrieved from BT for mapping surface temperature moreover for

analyzing landscape properties such as vegetation and soil.

In addition, with regards to the general use of Landsat data I add below some bibliography

that possibly might be of interest.

Further details can be found on preprocessing of Landsat data:

- Young, N. E., Anderson, R. S., Chignell, S. M., Vorster, A. G., Lawrence, R., & Evangelista,

P. H. (2017). A survival guide to Landsat preprocessing. Ecology, 98(4), 920–932. Portico.

https://doi.org/10.1002/ecy.1730

For further details in Landsat-8 data:

- Roy, D. P., Wulder, M. A., Loveland, T. R., C.E., W., Allen, R. G., Anderson, M. C., Helder,

D., Irons, J. R., Johnson, D. M., Kennedy, R., Scambos, T. A., Schaaf, C. B., Schott, J. R.,

Sheng, Y., Vermote, E. F., Belward, A. S., Bindschadler, R., Cohen, W. B., Gao, F., Zhu,

Z. (2014). Landsat-8: Science and product vision for terrestrial global change research.

Remote Sensing of Environment, 145, 154–172. https://doi.org/10.1016/j.rse.2014.02.001

Line 156: with regards to the calculation of the NDVI and the NDMI in both cases the Landsat-8

OLI Sensors spectral reflectance bands used for such calculation should not only be

radiometrically and geographically corrected, but also atmospherically corrected.

As mentioned before, similarly to the suggestions made with regards to the “near-surface

temperature”: if what is being evaluated are landscape features such as vegetation and soil, they

are part of the surface cover of the earth, therefore they constitute part of the earth’s surface skin

and are not unsusceptible to the influence of atmospheric effects. Surface reflectance bands used

for NDVI and NDMI indices require atmospheric correction. Therefore, I suggest to the authors that

in case atmospheric correction was performed it should be explicitly expressed in the Research

Methodology section. If the atmospheric corrections were not performed by the authors before

calculating any index employing Landsat-8 surface reflectance bands it is suggested to the authors

to perform atmospheric corrections of TOA surface reflectance bands before calculating any

spectral index.

Again, preprocessing of Landsat-8 OLI Sensor spectral reflectance bands mainly includes

several corrections (preprocessing steps) to convert raw data level 1 digital numbers (DN) to

surface reflectance that serve to calculate vegetation as well as other spectral indices.

Firstly, DN—or level 1 OLI data—need to be converted to top-of-atmosphere (TOA)

spectral radiance. Secondly, such top-of-atmosphere (TOA) spectral radiance needs to be

converted to top-of atmosphere (TOA) reflectance. (For conversion steps from Level 1 data see

https://www.usgs.gov/landsat-missions/using-usgs-landsat-level-1-data-product ). Thirdly, top-ofatmosphere

(TOA) reflectance needs to be converted to surface reflectance by atmospherically

correcting it to bottom-of-atmosphere or surface reflectance (SR) which is the measure of

reflectance on the surface of the ground. This preprocessing, theoretically based upon atmospheric

radiative transfer is needed to compensate scattering and absorption from radiance by

atmospheric components providing in this way an accurate estimate of the reflectance at earth

surface. Again, several algorithms have been developed for performing this data preprocessing

such as Dark Object Subtraction (DOS), ATCOR2 (Atmospheric Correction for Flat Terrain), COST

(Cosine of the Sun Zenith Angle), FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral

Hypercubes) and 6S (Second Simulation of Satellite Signal in the Solar), LaSRC (Land Surface

Reflectance Code) and Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS)

among others.

As I have mention earlier in this report the complex process of atmospheric correction

nowadays has been largely overcome for the Landsat series data by the USGS Collection 2 Level

2 data products. The USGS offers SR data already processes from Landsat OLI bands with its

Collection 2 Level 2 data products. In this manner, such a novel uncomplicated solution to the

complex processing required for retrieving atmospherically corrected surface reflectance from TOA

reflectance constitute an advantage for the research community. (For Landsat Collection 2 Level

2 Surface Reflectance see: https://www.usgs.gov/landsat-missions/landsat-collection-2-surfacereflectance

). For Landsat 8 Collection 2 Level 2 see the bibliography:

- USGS (2021). Landsat Collection 2 Level-2 Science Products. Fact Sheet.

https://doi.org/10.3133/fs20213055

USGS Collection 2 Level 2 Products Guide Downloadable from:

https://www.usgs.gov/media/files/landsat-8-9-collection-2-level-2-science-product-guide

These products are already converted to SR and ready to be download. Landsat-8 SR data

can be downloaded directly either from the USGS Earth Explorer platform (

https://earthexplorer.usgs.gov/ ) or from Google Earth Engine (GEE) platform. However, note that

the application of a scaling factor might still be required to obtain the final SR.

If the authors are using either these already preprocessed SR downloaded either from

USGS or GEE, it is suggested to be further explicitly described in the methodology section of the

manuscript together with the correspondent citation sources. That said, it is important to note that

if the spectral indices the authors are employing in this study are produced following a different

preprocessing to the abovementioned ones for the Landsat-8 OLI Sensor data, such a

preprocessing also is suggested to be explicitly described in the Research Methodology section of

the manuscript together with the bibliographical sources for the equations or algorithms applied for

the performed data preprocessing.

I would suggest that for most of the cases is better to use atmospherically corrected SR

rather than directly TOA spectral reflectance data for obtaining any spectral index of landscape

features of the earth surface such as vegetation and soil. This because the Landsat-8 OLI Sensors

are not unsusceptible to atmosphere and ground effects influencing the TOA spectral reflectance.

Therefore, I suggest to the authors of this manuscript the use of SR retrieved from TOA spectral

reflectance for calculating any spectral index, moreover for analyzing landscape properties such

as vegetation and soil.

Comments regarding the Results and Discussion Section

Lines 186-186: “[…] which will be demonstrated below with the help of analysis of remote sensing

data coupled with filled observations.”

Figure 2:

I suggest to the authors to specify for each of the tow images to what data they correspond.

I recommend this to be done by first identifying each image either with a letter or number—adding

a letter or a number in a corner of each image—and second, further describing in the caption of

the figure to what data each image correspond using the letter or number as reference. I assume

that the image at the right-hand side of figure 2 corresponds to the "Natural Color Composite" band

combination for Landsat-8, that is the band combination 4-3-2. While the left-hand side image

corresponds to thermal data. Is this assumption correct? If so, I suggest to specify it the caption of

the figure.

In any case, I suggest specifying the content the images represented by inserting a letter

or number to each image and thereafter in the caption of the figure describe to what data the image

with such letter or number corresponds.

For instance, in the case of using letter to identify the images in figure 2. For the left handside

image the text caption would be something like: a. thermal data and for the right-hand side

image: b. Landsat-8 natural color composite image (bands 4-3-2).

In the temperature profile graph X-Ticks labels and Y-Ticks labels are difficult to read.

Maybe either a darker color or a larger font size might improve its readability.

Figure 3:

In all the profile graph X-Ticks labels and Y-Ticks labels are difficult to read. Maybe

either a darker color or a larger font size might improve its readability.

Line 236: “Correspondingly, Pearson correlation coefficient calculated between the values of

vegetation indices and near-surface temperatures for …”

Since here the text starts to explain the Pearson’s correlation coefficient analysis and the

tables 1, 2 and 3 all representing the results of correlation analysis for a better organization of the

text I suggest to start a new paragraph after from the word “Correspondingly” at line 236.

Figure 4:

Same as in Figure 2, for the profile graph X-Ticks labels and Y-Ticks labels are difficult to

read. Maybe either a darker color or a larger size font might improve its readability.

Line 269: “Large-scale map of the distribution of the near-surface temperatures (land surface

temperatures) in the summer season. The ragged line is the “C”-temperature profile.”

In the caption of figure 4 “near-surface temperature” appears to be equated to land surface

temperature. This is the first time in the text I find that both terms are interchangeably used by the

authors. For the sake of consistency, I suggest to choose one of both terms. In my personal opinion

for referring to the earth surface temperature values when obtained from the thermal remote

sensing images processed from Landsat-8 TIR bands the term "land surface temperature"—with

its abbreviation LST—is the most appropriate term to use. As I mentioned before the use of “nearsurface

temperature” is correct although, I suggest to the authors to employ the term land surface

temperature instead which is mostly used in thermal remote sensing literature. It is suggested to

the authors that after the first time the term appears in the text, it will be further called by its

correspondent abbreviation that is “LST”. In any case, it is recommended to the authors to be

consist with the use of the terms all across the text, meaning using always the same term to refer

to the same concept.

From Line 276 to Line 279: “In this respect, our methodology considers the position developed

by M.I. Budyko [17]; it states that the heat balance of land can be expressed as R = LE + P, where

LE is the heat of evaporation (latent heat flux) and P is the turbulent flux of sensible heat from the

underlying surface.”

It is important to consider whether the formula developed by M.I. Budyko is explicitly

applied at any given point by authors for making any quantitative estimation in the research, or is

just brought to express a general viewpoint the authors advocate or follow with no explicit

calculation performed on its bases. If the formula was applied for calculations, then it becomes a

methodological approach employed in the study. Therefore, in such a case I suggest to the authors

to place the whole paragraph from line 276 to line 279 in the Research and Methodology section.

Otherwise, if the formula developed by M.I. Budyko not explicitly applied in any calculation, but is

just used to demonstrate a general approach followed in the analysis and discussion then it is

appropriately placed in the Results and Discussion section of the manuscript, as it is now.

Line 291: “phytomass stocks”

In the section 2—named by the authors “Study subject”—it was mentioned that

“phytomass stocks” was calculated. However, it was not explained how it was calculated.

Line 300:” (Figures 8, 9)”

I could not find figure number 9 in the manuscript, please add figure 9 to the manuscript

or correct the sentence.

Line 293: “The largest phytomass stocks (55-58 t/ha)”

This paragraph describing a type of landscape refers to figures 4 (cited in line 294) and

figure 3 (cited in line 299) which both are figures composed of maps and graphs derived from

remotely sensed data while the paragraph does not refer to or cite any fieldwork-based landscape

picture or photograph as example that enables to identify this specific kind of landscape—

corresponding to phytomass stocks between 55-58 t/h. Therefore, only in the case the authors

have such a photographs or pictures, I suggest it would very informative to include them in the

manuscript and make reference to them or cite them in this paragraph.

I suggest this because for the low phytomass stocks between 38 and 43 t/h (paragraph

starting in line 300), figure 8 (cited in line 301) and figure 6 (cited in line 309) depict for the reader

a clear picture that enables to identify the characteristics of this type of landscape.

I suggest to the authors for a better organization of the photographs or pictures of

landscapes in manuscript (photographs appearing from page 9 to page 11) in the case that is

possible, to compose with such photographs or pictures a single figure (or two figures) that will

enable the reader to visually compare between landscape types. In this way, figure/s with

photographs or pictures of different landscape types will provide the reader with the possibility of

visually comparing the different landscape types identifying its characteristics and properties (e.g.,

for instance a figure with photographs that enable the comparison between landscapes

corresponding to large pythomass stocks (55 - 58 t/h), and landscapes corresponding to lowest

phytomass stocks (38 - 43 t/h).

Line 330: “Figure 5”

I couldn’t find cited in the text figure 5 (line 330).

I suggest to the authors to make a clear reference or citation in the manuscript’s text of all

the figures shown in manuscript.

Line 348: “(Figure 10)”

I could not find a figure number 10 in the manuscript. Please add figure 10 to the

manuscript or correct the sentence.

Line 348: “Figure 7”

I could not find a figure number 7 in the manuscript. Please add figure 7 to the

manuscript or correct the sentence.

Comments regarding the Conclusions section

Line 368: “thermal fields (surface temperature)”

Here appears a different term for the same concept, “thermal fields” while previously called

“near-surface temperature” and “land surface temperature”. I suggest to authors to use a unique

term to refer to the same concept for the of preserving consistency all along the text. If the authors

what to refer to a different concept a different term can be used. However, I suggest to the authors

that in such a case explicitly define the concept wanted to express.

Line 374: “con-fined”

Maybe the authors wanted to express the word “confined”?

Line 375: “sur-faces”

Maybe the authors wanted to express the word “surfaces”?

Line 376: “are-as”

Maybe the authors wanted to express the word “areas”?

Line 383: “lev-el”

Maybe the authors wanted to express the word “level”?

Line 389: “spo-radic”

Maybe the authors wanted to express the word “sporadic”?

Line 392: “multi-component analysis that included the remote sensing and field data.”

The “multi-component analysis” can be a confusing term, since it is associated to a specific

spectrometric technique used for processing of absorption spectra for samples. If the authors are

not interested in refereeing to this technique, but to the combination of remote sensing and

fieldwork collected data, then I suggest the authors to change this term for a more suitable one,

that reflects the idea wanted to convey.

Line 394: “re-lating”

Maybe the authors wanted to express the word “relating”?

Line: 396: “for-est”

Maybe the authors wanted to express the word “forest”?

Line 397: “research-ers”

Maybe the authors wanted to express the word “researchers”?

Line 398: “cryo-lithozone”

Maybe the authors wanted to express the word “cryolithozone”?

Comments for author File: Comments.pdf

Author Response

Dear Reviewer,

Thank you for the careful reading of our manuscript and the comments to improve it. Please find a table below indicating changes made in the manuscript for each of your concerns/suggestions accompanied by our comments.

All additions and changes to the manuscript are highlighted in green.

№	Comments of reviewer	Response
1	I would suggest to express the first statement assertively meaning instead of expressing in line 14 “The paper discusses the possible use of…“ to remove the word “possible” or better suggest to the authors to start the abstract’s first phrase with an expression closer to: “This paper discusses the potential of using …”	We agree, replaced by «This paper discusses the potential of using …”.
2	Line 15 and 16: it is suggested to mention in the abstract only the sensors corresponding to the satellites that were effectively used in the research. ...the authors are saying “The study is based on analysis”, maybe the authors wanted to say “The study is based on the analysis”	We replaced "Landsat TM" with "Landsat-8"; corrected the article.
3	I suggest to the authors that for the sake of consistency to use the same term to define the same concept. (terms “land surface air temperature”, “land surface temperature” or LST…)	We corrected to a single term «land surface temperature» and/or LST.
4	From line 46 to line 51: ... I suggest to extend the discussion on the use of remote sensing for the analysis thermal characteristics of boral landscapes, and/or to related general characteristics of boreal landscapes. Extending a bit more the discussion of previous research that have tackled the same topic as well as the research advances in the analysis of similar landscapes types, if exists in the literature, will indeed constitute a significant benefit for the quality of the manuscript.  ...	Additions have been made to the text (section "introduction").
5	Line 49: "near-surface temperature":	We corrected to a single term «land surface temperature» and/or LST.
6	Line 54: “The equation of the heat balance of the Earth’s surface”.	We added the reference.
7	Line 70: “This approach can be used for mapping permafrost-taiga landscapes [10, 19-24]. This is most true for the territories of the southern part of the boreal cryolithozone [3, 15, 22], where the contrast of forest growing conditions is the highest, which is noticeably expressed in the phytomass stocks of taiga landscapes and in the intensity of their thermal flux.”	Additions have been made to the text (section "introduction").
8	Lines 74 and 75: Before finishing the introduction, I would suggest to the authors to introduce very briefly the content of the different sections of this manuscript, with an extremely brief summary of one or two sentences. This will enable the reader to have an introductory view of the structure or organization of the paper they will be reading.	We added a description of the sections.
9	Line 76: the title of this section: “Study Subject” I would suggest to call this section differently maybe something closer to: "Characterization of Area of Study" or just “The Area of Study” or something similar chosen by the authors.	We agree, replaced “Study Subject” with “Study area”.
10	Figure 1:  I suggest improving the visual quality of the X-Ticks and Y-Ticks of the map coordinates— probably enlarging the font size or its thickness—to make the map's coordinates easier to read.  In addition, in the capitation of figure 1 it would be a benefit for the reader’s better understanding of the map to express to which geographical variable the raster values of such a map correspond. … it is recommended to the authors to use the gray colored map at the left upper corner of figure 1 to show a wider geographical region that might enable the reader to easily identify the general geographical frame where the area of study is located within either the Siberian Federal Region or alternatively a larger region of the Russian Federation.	The figure has been corrected based on the recommendation.
11	From Line 121 to line 125: “Along the transects, test geobotanical sites (100 m2) were established, where the compositions of stands and ground cover were studied in detail. Tree species were counted; tree height and diameter (at 1.5 m height) were measured and averaged. Thus, the phytomass stocks were calculated, which were then compared with the obtained remote sensing data.” This part of field work seems to imply a quantitative data collection, analysis of such data and calculations preformed over such data for obtaining an environmental indicator named “phytomass stocks”. For a further comparison of such environmental variables with data obtained from remote sensing.  Firstly, given that authors have conducted a significant systematic fieldwork collecting quantitative data on:    a.            count of tree species  b.            tree height  c.             tree diameter at 1.5 m height    it would be highly valuable and interesting for the reader to have access to at least one or two examples—a part or price of such data—in an organized from, for instance preferably with a graph or alternatively with a table. ...	We have made several changes in the manuscript: thus “phytomass estimation” was substituted for “stand productivity class characteristics”, which is also the clear indicator of the intensity of biopruductivity processes and characterizes directly quality of forest growth conditions. Then, productivity class was determined using tables from forest mensuration handbooks. According to the productivity class scale accepted in Russia, forest stands on non-permafrost landscapes in the study area were assigned 3 and 4 productive classes, while forest stands on permafrost landscapes were assigned 5 and 5a productivity classes, i.e., the worse in this category. The primary data, if necessary, may be incorporated into the manuscript. However, at this stage, we thought this could overload the manuscript (Table and Graph). Apparently, it is feasible to add a fragment of the Table with contrast values for different landscapes (?)
12	From line 125 to line 128: “The presence of permafrost was identified using visually pronounced characteristics and established methods typical of permafrost systems for the studied area [1215], some of which are shown in the pictures presented in the sections below.” This part of the fieldwork seems to imply visual observation techniques corresponding to a qualitative methodological approach for recording spatial-visual properties of landscapes. Photographs or pictures of permafrost locations and other landscape features, indeed constitutes a relevant source of information as well.	We added links to figures.
13	From line 128 to line 132: “In general, the impact of permafrost on boreal landscapes of southern cryolithozone includes increased water content of surface sediments, appreciable peat thickness, evidence of soil cryoturbation, abundance of cryogenic relief forms, distinct structure and composition of the vegetation cover (e.g., sparseness and suppression of stands, prevalence of sphagnum moss and dwarf birch in surface cover).” This paragraph seems to me more oriented to describe the permafrost properties on boreal landscapes of the region where the study was performed, the southern cryolithozone. Therefore, if this paragraph represents information or conclusion derived from observational fieldwork conducted by the authors at the specific site of study, I suggest to place this paragraph in a more appropriate section of the manuscript such as section 3. Results and Discussion section. Whereas if this paragraph contains knowledge on the permafrost properties of boreal landscapes that corresponds to specific bibliographical sources, I suggest to the authors to add such bibliographical source and place this paragraph at a more suitable section such as for example the section 2 called by the authors in the manuscript “Study Subject”. If this paragraph corresponds to the authors’ general knowledge on the topic of boral landscapes properties and has not been taken from any specific bibliographical source, then I suggest the authors likewise, to place this paragraph in section 2 now called by the authors “Study Subject”. In any case, this paragraph contains information that in my option does not correspond to the Research Methodology section. The methodological section is expected to contain techniques, processes, steps followed, formulas, equations, software and algorithms, descriptions of models applied among other methodological procedures.	Made the necessary adjustments as per your recommendation.
14	Lines 132 to 135: “The natural ecosystems within the transects were examined for the evidence and character of past fires. The thickness of the seasonally thawed layer at the observation points was estimated with a probe and also visually — in pits and soil cross-sections.”   This fieldwork collected information corresponding to a both qualitative visual observation with regards to the evidence of past fires and both qualitatively visual observation and quantitative probe estimation for seasonally thawed layer. These are very relevant sources of information.
15	Line 138: “… obtained during the active growing season (July, August) and summer periods with consistently high air temperatures in 2013, 2016, and 2018, which allowed us to 139 obtain values for near-surfacer temperatures” First, I suggest to the authors to pay attention to the spelling of “near-surfacer temperatures”.  Second, since the temperature of the earth’s surface changes over the hours of the day, I suggest to the authors to include the time using the local time corresponding to the location where the images were taken. The metadata file of the Landsat-8 images provides the time when the satellite took the images. The time at the exact location where the satellite took the image can be obtained from such metadata file and further converted to the local time corresponding to that of such location. Alternatively, the time when the image was taken can also be expressed as GMT.	We corrected to a single term «land surface temperature» and/or LST; We added a table (Table 1) with a description of the date and time of the shooting.
16	Lines 144-145: “data in two channels — 10 and 11“ Line 146: “Channel 10”  I suggest specifying the wavelength of Landsat-8 TIR bands between brackets with its units. This will enable the reader rapidly identifying the region of the electromagnetic spectrum in question. I suggest to use the term “bands” instead of “channels” to follow a more conventional used terminology in remote sensing literature.	We agree, replaced “channels” to “bands”.
17	From line 148 to line 154: “Remote sensing data processing was carried out using QGIS in two stages. Initially, for fragments of the scenes, we calibrated the dimensionless values of the initial image brightness (Digital Number, DN) in terms of the values of the radiation arriving at the sensor. Then these values were recalculated into surface temperatures (˚С). Thus, the cartographic images of the thermal field were created, rendered in the same color scheme. The images were used to build temperature profiles; the values of near-surface temperatures were derived in the points of field-descriptions.”	We have added a link to the software used (QGIS Software) in the bibliography; Taking into account the comments, the Landsat level 2 data was additionally analyzed, the corresponding corrections were made to the figures (3,4,5) and tables (2-4), and the text of the “Research methodology” section was supplemented.
18	Line 156: with regards to the calculation of the NDVI and the NDMI in both cases the Landsat-8 OLI Sensors spectral reflectance bands used for such calculation should not only be radiometrically and geographically corrected, but also atmospherically corrected.	We corrected by adding the use of Landsat-8 2 levels of processing with atmospheric compensation.
19	Figure 2: I suggest to the authors to specify for each of the tow images to what data they correspond. I recommend this to be done by first identifying each image either with a letter or number—adding a letter or a number in a corner of each image—and second, further describing in the caption of the figure to what data each image correspond using the letter or number as reference. I assume that the image at the right-hand side of figure 2 corresponds to the "Natural Color Composite" band combination for Landsat-8, that is the band combination 4-3-2. While the left-hand side image corresponds to thermal data. Is this assumption correct? If so, I suggest to specify it the caption of the figure.  In any case, I suggest specifying the content the images represented by inserting a letter or number to each image and thereafter in the caption of the figure describe to what data the image with such letter or number corresponds.  For instance, in the case of using letter to identify the images in figure 2. For the left handside image the text caption would be something like:  a. thermal data and for the right-hand side image: b. Landsat-8 natural color composite image (bands 4-3-2).  In the temperature profile graph X-Ticks labels and Y-Ticks labels are difficult to read. Maybe either a darker color or a larger font size might improve its readability.	We added letter indexes, changed the caption based on the recommendation, and fixed the X-Ticks labels and Y-Ticks labels.
20	Figure 3: In all the profile graph X-Ticks labels and Y-Ticks labels are difficult to read. Maybe either a darker color or a larger font size might improve its readability.	We added letter indexes and fixed the X-Ticks labels and Y-Ticks labels.
21	Line 236: “Correspondingly, Pearson correlation coefficient calculated between the values of vegetation indices and near-surface temperatures for …”   Since here the text starts to explain the Pearson’s correlation coefficient analysis and the tables 1, 2 and 3 all representing the results of correlation analysis for a better organization of the text I suggest to start a new paragraph after from the word “Correspondingly” at line 236.	We start a new paragraph after from the word “Correspondingly” based on the recommendation.
22	Figure 4: Same as in Figure 2	We fixed the X-Ticks labels and Y-Ticks labels.
23	Line 269: “Large-scale map of the distribution of the near-surface temperatures (land surface temperatures) in the summer season. The ragged line is the “C”-temperature profile.” In the caption of figure 4 “near-surface temperature” appears to be equated to land surface temperature. This is the first time in the text I find that both terms are interchangeably used by the authors. For the sake of consistency, I suggest to choose one of both terms. In my personal opinion for referring to the earth surface temperature values when obtained from the thermal remote sensing images processed from Landsat-8 TIR bands the term "land surface temperature"—with its abbreviation LST—is the most appropriate term to use. As I mentioned before the use of “nearsurface temperature” is correct although, I suggest to the authors to employ the term land surface temperature instead which is mostly used in thermal remote sensing literature. It is suggested to the authors that after the first time the term appears in the text, it will be further called by its correspondent abbreviation that is “LST”. In any case, it is recommended to the authors to be consist with the use of the terms all across the text, meaning using always the same term to refer to the same concept.	We corrected to a single term «land surface temperature» and/or LST.
24	From Line 276 to Line 279: “In this respect, our methodology considers the position developed by M.I. Budyko [17]; it states that the heat balance of land can be expressed as R = LE + P, where LE is the heat of evaporation (latent heat flux) and P is the turbulent flux of sensible heat from the underlying surface.” It is important to consider whether the formula developed by M.I. Budyko is explicitly applied at any given point by authors for making any quantitative estimation in the research, or is just brought to express a general viewpoint the authors advocate or follow with no explicit calculation performed on its bases. If the formula was applied for calculations, then it becomes a methodological approach employed in the study. Therefore, in such a case I suggest to the authors to place the whole paragraph from line 276 to line 279 in the Research and Methodology section. Otherwise, if the formula developed by M.I. Budyko not explicitly applied in any calculation, but is just used to demonstrate a general approach followed in the analysis and discussion then it is appropriately placed in the Results and Discussion section of the manuscript, as it is now.	This formula is a theoretical basis and is not directly used in calculations. We left it as it is as now.
25	Line 291: “phytomass stocks” In the section 2—named by the authors “Study subject”—it was mentioned that “phytomass stocks” was calculated. However, it was not explained how it was calculated.	We have made several changes in the manuscript: thus “phytomass estimation” was substituted for “stand productivity class characteristics”, which is also the clear indicator of the intensity of biopruductivity processes and characterizes directly quality of forest growth conditions. A more detailed answer to this remark is presented in paragraph No. 11.
26	Line 300:” (Figures 8, 9)” I could not find figure number 9 in the manuscript, please add figure 9 to the manuscript or correct the sentence.	We corrected the link to the figures.
27	Line 293: “The largest phytomass stocks (55-58 t/ha)” This paragraph describing a type of landscape refers to figures 4 (cited in line 294) and figure 3 (cited in line 299) which both are figures composed of maps and graphs derived from remotely sensed data while the paragraph does not refer to or cite any fieldwork-based landscape picture or photograph as example that enables to identify this specific kind of landscape— corresponding to phytomass stocks between 55-58 t/h. Therefore, only in the case the authors have such a photographs or pictures, I suggest it would very informative to include them in the manuscript and make reference to them or cite them in this paragraph. I suggest this because for the low phytomass stocks between 38 and 43 t/h (paragraph starting in line 300), figure 8 (cited in line 301) and figure 6 (cited in line 309) depict for the reader a clear picture that enables to identify the characteristics of this type of landscape.  I suggest to the authors for a better organization of the photographs or pictures of landscapes in manuscript (photographs appearing from page 9 to page 11) in the case that is possible, to compose with such photographs or pictures a single figure (or two figures) that will enable the reader to visually compare between landscape types. In this way, figure/s with photographs or pictures of different landscape types will provide the reader with the possibility of visually comparing the different landscape types identifying its characteristics and properties (e.g., for instance a figure with photographs that enable the comparison between landscapes corresponding to large pythomass stocks (55 - 58 t/h), and landscapes corresponding to lowest phytomass stocks (38 - 43 t/h).	We corrected the link to the figures. We added a single figure to compare landscapes with different degrees of permafrost influence.
28	Line 330: “Figure 5” I couldn’t find cited in the text figure 5 (line 330). I suggest to the authors to make a clear reference or citation in the manuscript’s text of all the figures shown in manuscript	We corrected the link to the figures.
29	Line 348: “(Figure 10)”  I could not find a figure number 10 in the manuscript. Please add figure 10 to the manuscript or correct the sentence.	We corrected the link to the figures.
30	Line 348: “Figure 7”  I could not find a figure number 7 in the manuscript. Please add figure 7 to the manuscript or correct the sentence.	We corrected the link to the figures.
31	Line 368: “thermal fields (surface temperature)”	We corrected to a single term «land surface temperature» and/or LST.
32	Line 374, 375, 376, 383, 389, 394, 396, 397,398	We have corrected typos.
33	Line 392: “multi-component analysis that included the remote sensing and field data.”   The “multi-component analysis” can be a confusing term, since it is associated to a specific spectrometric technique used for processing of absorption spectra for samples. If the authors are not interested in refereeing to this technique, but to the combination of remote sensing and fieldwork collected data, then I suggest the authors to change this term for a more suitable one, that reflects the idea wanted to convey.	We replaced «multi-component analysis» with «complex approach».

 

 

 

 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The authors have successfully answered the comments in the revised version. Especially, i appreciate that these figures are improved. So i recommend the manuscript to be published in the present form.

Author Response

We thank very much the reviewer for very helpful and constructive comments and recommendations.

Reviewer 2 Report

Review of the second submission of the manuscript: “Detection of geocryological conditions in boreal landscapes of the southern cryolithozone using thermal infrared remote sensing data - a case study of the northern part of the Yenisei Ridge.”

 

I consider the revised submission of the manuscript has been substantially improved by authors. In this manner considerably boosting the quality of manuscript and setting in it now almost in a suitable condition for publication. I strongly recommend the revised submitted version of manuscript to be accepted for publication however only after undergoing the minor changes I describe below. Therefore, only after the corrections I mention below are performed by the authors, I strongly recommend the revised submitted version of manuscript to be accepted for publication.

 

Line 19 : “forest productivity class estimations”

 

This concept appears in the abstract for the first time in the text, if this concept is mentioned again, then the the full concept together with an abbreviation could be a useful way to summarize such long term, for instance an abbreviation like : “FPCE” can be used. E.g., next time it appears it would be: “forest productivity class estimations (FPCE)”, and thereafter only use the abbreviation FPCE in the text for referring to this concept. However, I could not find the complete term “forest productivity class estimations” in the text in any other place besides the abstract. If the concept is used in this study, I suggest to the authors that it should be defined and explained in the Research Methodology section together with its correspondent citation.

 

Line 49: “land surface temperature (LST) maps.”

 

Once “lands surface temperature” is mentioned for the first time in the text—i.e., in Line 49—together with its correspondent abbreviation LST, between brackets, then for the sake of consistency, it suggested to the authors always to use only the abbreviation LST for singular and LSTs for plural without repeating “land surface temperature” again in the text of the manuscript. It is also recemented not to repeat the text: “land surface temperature (LST)”such as it is in the caption of Table 2 (Line 327), but instead just use LST for singular and LSTs for plural always in all the text. After the first time any concept  appears in the text with its correspondent abbreviation, only its abbreviation should be used. For instance, the concept “lands surface temperature” is repeated in the text very many times, while in Line 49 there is an abbreviation which is LST, therefore I suggest for the sake of consistency, please replace—after Line 49—always “land surface temperature” by LST.

 

Figure 1: “Sentral Siberian Plato”

 

I assume the authors wanted to write in the map “Central Siberian Plateau” instead of “Sentral Siberian Plato”. I suggest correcting the English word from “Sentral” to “Central” and the word “Plato” to “Plateau” for a correct use of the English.

 

Line 188: “This allowed us to assess the forest productivity class in different landscape conditions.”

 

            I assume this is the estimation the authors refer in the abstract Line 19 [“forest productivity class estimations”] and only mention it but not describe it in the Research Methodology section in Line 188 [“forest productivity class”], and also mentioned in the Conclusion Section in Line 453 [“forest productivity class”]; as well as the same procedure the authors described in Point 11 of the author’s Cover Letter, that is, how the different productivity classes are assessed. As expressed by the authors in the Cover Letter: “Then, productivity class was determined using tables from forest mensuration handbooks. According to the productivity class scale accepted in Russia, forest stands on non-permafrost landscapes in the study area were assigned 3 and 4 productive classes, while forest stands on permafrost landscapes were assigned 5 and 5a productivity classes, i.e., the worse in this category.”

 

I haven’t seen this concepts’ [ “forest productivity class estimations”]  formal description, and its correspondent citation explicitly expressed in the Research Methodology section. If there is a formula or a procedure (or consulted tables in a specific handbook, etc.,) that the authors have employed for landscapes descriptions and characterization, then it is part of the Research Methodology section. Therefore, if formulas or estimations, or other procedure were employed by the authors, I suggest that all those should be at least briefly described rather than only mentioned in the Research Methodology section with its correspondent citation.  

 

Line 197: “ in QGIS”

 

I suggest to the authors to write instead something similar to :”employing QGIS software.”

 

Line 199: “atmospheric compensation”

 

            Although the term “compensation” is used, I suggest to the authors to use the term “atmospheric correction” which is mostly used in the remote sensing literature, this might better orient the reader.

 

Line 208 and 209: “The use of these data allows avoiding additional atmospheric correction, as is necessary when working with level 1 data”

 

However, it is true that the use of the Level 2 data avoids “additional atmospheric correction” it is because the atmospheric correction was already performed by NASA team according to the algorithms cited in the bibliographical sources referred in my previous review of this manuscript.

I would suggest to the authors rephrasing the sentence, not saying that it “allows avoiding additional atmospheric correction” but that Collection 2 Level 2 data products correspond to already atmospherically corrected data. In the case the authors want to go a step further and explicitly describe which specific algorithm was used by NASA team to retrieve LST from brightness temperature (TIR bands) and surface reflectance (SR) from spectral radiance (OLI bands)  as well as citate the source, then I suggest to the authors to check the bibliography bellow from my previous review of this manuscript, there the complete names both algorithms used by NASA team are explicitly mentioned. Here below I cite the correspondent sources again:

 

For TIR bands retrieving LST from brightness temperature:

retrieving LST from BT for Landsat Collection 2 Level 2 Surface Temperature see:

https://www.usgs.gov/landsat-missions/landsat-collection-2-surface-temperature ).

For Landsat 8 Collection 2 Level 2 see the bibliography:

- USGS (2021). Landsat Collection 2 Level-2 Science Products. Fact Sheet.

https://doi.org/10.3133/fs20213055

USGS Collection 2 Level 2 Products Guide Downloadable from:

https://www.usgs.gov/media/files/landsat-8-9-collection-2-level-2-science-product-guide

 

For OLI bands retrieving ST from spectral radiance:

For Landsat Collection 2 Level 2 Surface Reflectance see: https://www.usgs.gov/landsat-missions/landsat-collection-2-surfacereflectance

). For Landsat 8 Collection 2 Level 2 see the bibliography:

- USGS (2021). Landsat Collection 2 Level-2 Science Products. Fact Sheet.

https://doi.org/10.3133/fs20213055

USGS Collection 2 Level 2 Products Guide Downloadable from:

https://www.usgs.gov/media/files/landsat-8-9-collection-2-level-2-science-product-guide

 

Line 210 to 215: “It should be noted that for the study area and the selected images, land surface temperatures were also preliminarily calculated without atmospheric correction, and these data qualitatively almost completely coincide with those adjusted. However, after the correction, all values shifted several degrees (Figure 2) and are more differentiated. Subsequently, the corrected data were used in the analysis. The adjustment process is described in more detail in [36, 37].”

 

It is indeed valuable that the authors show the preliminarily calculation with Level 1 data and further compere between Level 1 data (none atmospherically corrected data) and Level 2 data (atmospherically corrected data). Also, citations 36 and 37 are important and valuable information brought by the authors.

However, I my opinion such a comparison between Landsat Level 1 data and Level 2 data  is out of the scope this manuscript as well as out of the scope of the main methodological goal of the manuscript. Besides it is a whole subfield in (thermal) remote sensing the analysis of deviations between algorithms and the comparison of their results, for obtaining the more accurate atmospheric correction. In addition, it is a whole subfield in remote sensing the algorithms development for that purpose. Therefore, I suggest to the authors to avoid tackling this highly specific and complex issue, which is also relevant to a different subfield in remote sensing to that treated  in the manuscript. That said, I suggest to the authors to remove from the manuscript the text going from line 210 to line 215 together with figure 2.

In the case the authors insist to include such information—from line 210 to line 215 and the correspondent figure 2—I might suggest it could be included as an additional informative experiment made by the authors through the research process and place it for instance at the Complementary Material section and refer in the main manuscript to the Complementary Material Section where such comparative analysis is shown or alternatively to place it in a correspondent appendix.

 

Line 230 : NDVI theoretical range goes from -1 to +1. If the authors are specifically using a subrange of the NDVI’s complete theoretical range, or the authors are using the obtained range of the processed images, or the authors want to highlight a specific subrange such as for instance for dense vegetation from 0.6 to 0.9 or the specific range from 0 to 1 due to some especial reason, then, I suggest to the authors to explain it in the text. I suggest such reasons should be specified in the text. Otherwise, the theoretical range of the NDVI goes from -1- to +1.

 

For a very brief explanation of NDVI’s range (in a nutshell) please consult:

https://www.usgs.gov/special-topics/remote-sensing-phenology/science/ndvi-foundation-remote-sensing-phenology

 

For a more precise explanation consult the following bibliography in page 3 under the subtitle NDVI calculation:

 

Huang, S., Tang, L., Hupy, J. P., Wang, Y., & Shao, G. (2020). A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing. Journal of Forestry Research, 32(1), 1–6. https://doi.org/10.1007/s11676-020-01155-1

 

Line 265 to 270: “In general, the impact of permafrost on boreal landscapes of southern cryolithozone includes increased water content of surface sediments, appreciable peat thickness, evidence of soil cryoturbation, abundance of cryogenic relief forms, distinct structure and composition of the vegetation cover (e.g., sparseness and suppression of stands, prevalence of sphagnum moss and dwarf birch in surface cover) (Figure 4).”

 

Since figure 4 lacks a detailed explanation in the text and it  is referenced to this particular paragraph in the text, I suggest to the authors to extend a bit more this paragraph using it to further explain with a little bit more of details the complex process represented in figure 4. This is to give a better understanding of the complex process depicted in figure 4 to the reader. Or alternatively to cite figure 4 again where more detailed explanations about figure 4 might exist in the text. The objective is to make a good referencing in the text of the complex content represented in figure 4, to have it explained in the text for the reader’s understanding. The process represented in figure 4 has a certain degree of complexity and uses several concepts, therefore I suggest to authors to make sure the content of figure 4 is well explained to the reader in the text and cited accordingly. Of course, if figure 4 was created by the authors it does not need citations, otherwise I suggest to the authors to make the correspondent citation in the caption of figure 4.

 

Lines 375 to 397:

As far as I have seen in the manuscript, it is strongly expressed from the line 375 to line 397, that NDVI defined by qualitatively ranges as “highest ” and “lowest” was used. Although no specific NDVI numerical range is expressed for each of both types of landscapes features described in (1) and (2). Here I suggest that only if it is possible, to use at least an approximate numerical range of NDVI obtained for both qualitative ranges namely “highest ” and “lowest”. The use of an approximate numerical range of NDVI will defiantly be more informative to the reader than just qualitative ranges.

 

In the Cover Letter Point 11: “We have made several changes in the manuscript: thus “phytomass estimation” was substituted for “stand productivity class characteristics”, which is also the clear indicator of the intensity of biopruductivity processes and characterizes directly quality of forest growth conditions. Then, productivity class was determined using tables from forest mensuration handbooks. According to the productivity class scale accepted in Russia, forest stands on non-permafrost landscapes in the study area were assigned 3 and 4 productive classes, while forest stands on permafrost landscapes were assigned 5 and 5a productivity classes, i.e., the worse in this category. The primary data, if necessary, may be incorporated into the manuscript. However, at this stage, we thought this could overload the manuscript (Table and Graph). Apparently, it is feasible to add a fragment of the Table with contrast values for different landscapes (?).“

 

This explanation could be a little bit confusing!

 

Here the authors refer to an estimation procedure called “stand productivity class characteristics” which functions as a representative indicator of biopruductivity intensity and capable of characterizing the quality of forest growth conditions, instead of the previously used  “phytomass estimation”.  In my opinion this corresponds to the Research Methodology section. I assume the concept “stand productivity class characteristics” refers to the concept  “forest productivity class estimations” found in Line 19 in the abstract, is this correct?

If “stand productivity class characteristics” refers to the same concept as “forest productivity class estimations” I suggest that only one of both concepts  should be chosen to be used in the manuscript’s text. This will reduce potential confusions.   

If such concept or measure is actually estimated, calculated or employed in any manner by the authors for classification or characterization of landscapes in the manuscript, then I suggest it should be at least briefly explained with it correspondent citation in the Research Methodology section. It is suggested to the authors to specify in the text the correspondent explanation given in Point 11 of the Cover Letter with the correspondent citations to the bibliography mentioned—i.e.  tables from forest mensuration handbooks (?)—with a very brief description of  the procedure applied with respect to the data used. If none of this data and calculation procedures were actually employed for the classification or characterization of landscapes in the manuscript, there is no need to mention it in the manuscript neither to cite the correspondent bibliography. If such procedures were applied and performed to classify or characterize landscapes, then without overloading the manuscript with tables and graphs, I suggest to the authors to add a very brief explanation of the procedure applied, and as mentioned by the authors, to “add a fragment of the Table with contrast values for different landscapes” explaining that such fragment of a Table is a representative example for the classification method employed.

Comments for author File: Comments.pdf

Author Response

Dear Reviewer, Thank you for the careful reading of our manuscript and the comments to improve it. Please find a table below indicating changes made in the manuscript for each of your concerns/suggestions accompanied by our comments.   All additions and changes to the manuscript are highlighted in purple.
№	Comments of reviewer	Response
1	Line 19 : “forest productivity class estimations”   This concept appears in the abstract for the first time in the text, if this concept is mentioned again, then the the full concept together with an abbreviation could be a useful way to summarize such long term, for instance an abbreviation like : “FPCE” can be used. E.g., next time it appears it would be: “forest productivity class estimations (FPCE)”, and thereafter only use the abbreviation FPCE in the text for referring to this concept. However, I could not find the complete term “forest productivity class estimations” in the text in any other place besides the abstract. If the concept is used in this study, I suggest to the authors that it should be defined and explained in the Research Methodology section together with its correspondent citation.	We decided to return the original version of "phytomass estimations". We will follow this further in the text.
2	Line 49: “land surface temperature (LST) maps.”   Once “lands surface temperature” is mentioned for the first time in the text—i.e., in Line 49—together with its correspondent abbreviation LST, between brackets, then for the sake of consistency, it suggested to the authors always to use only the abbreviation LST for singular and LSTs for plural without repeating “land surface temperature” again in the text of the manuscript. It is also recemented not to repeat the text: “land surface temperature (LST)”such as it is in the caption of Table 2 (Line 327), but instead just use LST for singular and LSTs for plural always in all the text. After the first time any concept appears in the text with its correspondent abbreviation, only its abbreviation should be used. For instance, the concept “lands surface temperature” is repeated in the text very many times, while in Line 49 there is an abbreviation which is LST, therefore I suggest for the sake of consistency, please replace—after Line 49—always “land surface temperature” by LST.	We have replaced “lands surface temperature” with an abbreviation LST.
3	Figure 1: “Sentral Siberian Plato”   I assume the authors wanted to write in the map “Central Siberian Plateau” instead of “Sentral Siberian Plato”. I suggest correcting the English word from “Sentral” to “Central” and the word “Plato” to “Plateau” for a correct use of the English.	We have corrected the inaccuracies in the figure.
4	Line 188: “This allowed us to assess the forest productivity class in different landscape conditions.”   I assume this is the estimation the authors refer in the abstract Line 19 [“forest productivity class estimations”] and only mention it but not describe it in the Research Methodology section in Line 188 [“forest productivity class”], and also mentioned in the Conclusion Section in Line 453 [“forest productivity class”]; as well as the same procedure the authors described in Point 11 of the author’s Cover Letter, that is, how the different productivity classes are assessed. As expressed by the authors in the Cover Letter: “Then, productivity class was determined using tables from forest mensuration handbooks. According to the productivity class scale accepted in Russia, forest stands on non-permafrost landscapes in the study area were assigned 3 and 4 productive classes, while forest stands on permafrost landscapes were assigned 5 and 5a productivity classes, i.e., the worse in this category.”   I haven’t seen this concepts’ [ “forest productivity class estimations”] formal description, and its correspondent citation explicitly expressed in the Research Methodology section. If there is a formula or a procedure (or consulted tables in a specific handbook, etc.,) that the authors have employed for landscapes descriptions and characterization, then it is part of the Research Methodology section. Therefore, if formulas or estimations, or other procedure were employed by the authors, I suggest that all those should be at least briefly described rather than only mentioned in the Research Methodology section with its correspondent citation.
5	Line 197: “ in QGIS”   I suggest to the authors to write instead something similar to :”employing QGIS software.”	We have corrected the sentence according to the recommendation.
6	Line 199: “atmospheric compensation”   Although the term “compensation” is used, I suggest to the authors to use the term “atmospheric correction” which is mostly used in the remote sensing literature, this might better orient the reader.	We have changed the term «compensation» to «correction».
7	Line 208 and 209: “The use of these data allows avoiding additional atmospheric correction, as is necessary when working with level 1 data”   However, it is true that the use of the Level 2 data avoids “additional atmospheric correction” it is because the atmospheric correction was already performed by NASA team according to the algorithms cited in the bibliographical sources referred in my previous review of this manuscript. I would suggest to the authors rephrasing the sentence, not saying that it “allows avoiding additional atmospheric correction” but that Collection 2 Level 2 data products correspond to already atmospherically corrected data. In the case the authors want to go a step further and explicitly describe which specific algorithm was used by NASA team to retrieve LST from brightness temperature (TIR bands) and surface reflectance (SR) from spectral radiance (OLI bands) as well as citate the source, then I suggest to the authors to check the bibliography bellow from my previous review of this manuscript, there the complete names both algorithms used by NASA team are explicitly mentioned.	We have rephrased these sentences and added a mention of the atmospheric correction algorithms used by the USGS.
8	Line 210 to 215: “It should be noted that for the study area and the selected images, land surface temperatures were also preliminarily calculated without atmospheric correction, and these data qualitatively almost completely coincide with those adjusted. However, after the correction, all values shifted several degrees (Figure 2) and are more differentiated. Subsequently, the corrected data were used in the analysis. The adjustment process is described in more detail in [36, 37].”   It is indeed valuable that the authors show the preliminarily calculation with Level 1 data and further compere between Level 1 data (none atmospherically corrected data) and Level 2 data (atmospherically corrected data). Also, citations 36 and 37 are important and valuable information brought by the authors. However, I my opinion such a comparison between Landsat Level 1 data and Level 2 data is out of the scope this manuscript as well as out of the scope of the main methodological goal of the manuscript. Besides it is a whole subfield in (thermal) remote sensing the analysis of deviations between algorithms and the comparison of their results, for obtaining the more accurate atmospheric correction. In addition, it is a whole subfield in remote sensing the algorithms development for that purpose. Therefore, I suggest to the authors to avoid tackling this highly specific and complex issue, which is also relevant to a different subfield in remote sensing to that treated in the manuscript. That said, I suggest to the authors to remove from the manuscript the text going from line 210 to line 215 together with figure 2. In the case the authors insist to include such information—from line 210 to line 215 and the correspondent figure 2—I might suggest it could be included as an additional informative experiment made by the authors through the research process and place it for instance at the Complementary Material section and refer in the main manuscript to the Complementary Material Section where such comparative analysis is shown or alternatively to place it in a correspondent appendix.	We agree that this information is superfluous in this study. We have deleted this paragraph and figure.
9	Line 230 : NDVI theoretical range goes from -1 to +1. If the authors are specifically using a subrange of the NDVI’s complete theoretical range, or the authors are using the obtained range of the processed images, or the authors want to highlight a specific subrange such as for instance for dense vegetation from 0.6 to 0.9 or the specific range from 0 to 1 due to some especial reason, then, I suggest to the authors to explain it in the text. I suggest such reasons should be specified in the text. Otherwise, the theoretical range of the NDVI goes from -1- to +1.	There was an accidental mistake in the text. NDVI theoretical range goes from -1 to +1.
10	Line 265 to 270: “In general, the impact of permafrost on boreal landscapes of southern cryolithozone includes increased water content of surface sediments, appreciable peat thickness, evidence of soil cryoturbation, abundance of cryogenic relief forms, distinct structure and composition of the vegetation cover (e.g., sparseness and suppression of stands, prevalence of sphagnum moss and dwarf birch in surface cover) (Figure 4).”   Since figure 4 lacks a detailed explanation in the text and it is referenced to this particular paragraph in the text, I suggest to the authors to extend a bit more this paragraph using it to further explain with a little bit more of details the complex process represented in figure 4. This is to give a better understanding of the complex process depicted in figure 4 to the reader. Or alternatively to cite figure 4 again where more detailed explanations about figure 4 might exist in the text. The objective is to make a good referencing in the text of the complex content represented in figure 4, to have it explained in the text for the reader’s understanding. The process represented in figure 4 has a certain degree of complexity and uses several concepts, therefore I suggest to authors to make sure the content of figure 4 is well explained to the reader in the text and cited accordingly. Of course, if figure 4 was created by the authors it does not need citations, otherwise I suggest to the authors to make the correspondent citation in the caption of figure 4.	Appropriate additions have been made, briefly describing the mechanism of connections in the permafrost-taiga landscape, illustrated in fig. 4. Figure 4 was created by the authors of the article, so there is no need to use a link.
11	Lines 375 to 397: As far as I have seen in the manuscript, it is strongly expressed from the line 375 to line 397, that NDVI defined by qualitatively ranges as “highest ” and “lowest” was used. Although no specific NDVI numerical range is expressed for each of both types of landscapes features described in (1) and (2). Here I suggest that only if it is possible, to use at least an approximate numerical range of NDVI obtained for both qualitative ranges namely “highest ” and “lowest”. The use of an approximate numerical range of NDVI will defiantly be more informative to the reader than just qualitative ranges.	We have indicated approximate NDVI values, adding that these values may differ for other territories.
	In the Cover Letter Point 11: “We have made several changes in the manuscript: thus “phytomass estimation” was substituted for “stand productivity class characteristics”, which is also the clear indicator of the intensity of biopruductivity processes and characterizes directly quality of forest growth conditions. Then, productivity class was determined using tables from forest mensuration handbooks. According to the productivity class scale accepted in Russia, forest stands on non- permafrost landscapes in the study area were assigned 3 and 4 productive classes, while forest stands on permafrost landscapes were assigned 5 and 5a productivity classes, i.e., the worse in this category. The primary data, if necessary, may be incorporated into the manuscript. However, at this stage, we thought this could overload the manuscript (Table and Graph). Apparently, it is feasible to add a fragment of the Table with contrast values for different landscapes (?).“   This explanation could be a little bit confusing!   Here the authors refer to an estimation procedure called “stand productivity class characteristics” which functions as a representative indicator of biopruductivity intensity and capable of characterizing the quality of forest growth conditions, instead of the previously used “phytomass estimation”. In my opinion this corresponds to the Research Methodology section. I assume the concept “stand productivity class characteristics” refers to the concept “forest productivity class estimations” found in Line 19 in the abstract, is this correct? If “stand productivity class characteristics” refers to the same concept as “forest productivity class estimations” I suggest that only one of both concepts should be chosen to be used in the manuscript’s text. This will reduce potential confusions. If such concept or measure is actually estimated, calculated or employed in any manner by the authors for classification or characterization of landscapes in the manuscript, then I suggest it should be at least briefly explained with it correspondent citation in the Research Methodology section. It is suggested to the authors to specify in the text the correspondent explanation given in Point 11 of the Cover Letter with the correspondent citations to the bibliography mentioned—i.e. tables from forest mensuration handbooks (?)—with a very brief description of the procedure applied with respect to the data used. If none of this data and calculation procedures were actually employed for the classification or characterization of landscapes in the manuscript, there is no need to mention it in the manuscript neither to cite the correspondent bibliography. If such procedures were applied and performed to classify or characterize landscapes, then without overloading the manuscript with tables and graphs, I suggest to the authors to add a very brief explanation of the procedure applied, and as mentioned by the authors, to “add a fragment of the Table with contrast values for different landscapes” explaining that such fragment of a Table is a representative example for the classification method employed.	We returned to the variant with the calculation of phytomass stocks based on the collected data. We agree that this will make the article more accessible to the reader and avoid confusion. A fragment of the table with the calculation of phytomass reserves based on the collected data has been added to the methodological section.

 

Author Response File: Author Response.pdf

Round 3

Reviewer 2 Report

I think the significant improvements made by the authors to the latest revised version of the manuscripts have greatly boosted its quality, setting in it now in an entirely  suitable condition for publication. Therefore, I highly recommend the latest revised version of the manuscript to be accepted for publication without any further changes.