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Article
Peer-Review Record

Detection of Yunnan Pine Shoot Beetle Stress Using UAV-Based Thermal Imagery and LiDAR

Appl. Sci. 2022, 12(9), 4372; https://doi.org/10.3390/app12094372
by Jingxu Wang 1, Shengwang Meng 2, Qinnan Lin 3, Yangyang Liu 4 and Huaguo Huang 5,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Appl. Sci. 2022, 12(9), 4372; https://doi.org/10.3390/app12094372
Submission received: 17 February 2022 / Revised: 13 April 2022 / Accepted: 20 April 2022 / Published: 26 April 2022
(This article belongs to the Special Issue Advances in Geospatial Techniques on Ecosystem Monitoring)

Round 1

Reviewer 1 Report

Authors use unmanned airborne vehicles (UAV)-based TIR and
light detection and ranging (LiDAR) data to assess the capacity of determine both the potential for using TIR data for determining SDR under different LAI conditions. It is good work, however, some minor comments should be taken into consideration to improve paper 

1-figures should be fixed in the formate of paper

2- what is the difference between Unmanned aerial vehicles and unmanned airborne vehicles. do they are the same 

3- authors should improve paper background with more recently published papers such as Energy-efficient tethered UAV deployment in B5G for smart environments and disaster recovery,A Low-Cost Platform for Environmental Smart Farming Monitoring System Based on IoT and UAVs,Predictive estimation of the optimal signal strength from an unmanned aerial vehicle over the internet of things using ANN. 

4-why did you select Yunnan, not another city, does your work can be applied in Beijing or Shenzhen or any other country

5-authors should highlight the future work of current work by adding two lines at the end of the conclusion section. 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Dear authors thank you very much for your research paper Detection of Yunnan Pine Shoot Beetle Stress Using UAV[1]Based Thermal Imagery and LiDAR.

Major comments

 Please add global challenges about forest deforestation and  further discuss about the restoration   and management process  such as  Grain to Green Program (GTGP) , China; Sub-Saharan Africa, community forest management  and other program in the first paragraph of introduction section.. Following research work may help for review.

https://doi.org/10.1038/srep02846https://doi.org/10.1038/srep02846

https://doi.org/10.3390/rs13204093

UNDESA. The Global Forest Goals Report 2021, Realizing the Importance of Forests in A Changing World; United Nation Department of Economic and Social Affairs: New York, NY, USA, 2021

In the second last paragraph of the manuscript please discuss more about recent application of remote sensing technology  for detection of vegetation  and vegetation health. Review about the application of RS for the evaluation of LAI, NDVI, Canopy Height Model (CHM) and others..

Please include the Materials and Method section in Section 2 and insert 2.1 for study area. After first paragraph of the study area, all text include in sub section ( process).

Please further include the details about the methodology of accuracy of detection including true Positive (TP), false positive (FP), and false negative (FN) classes at pixel level. Further analysis the accuracy assessment result in the first paragraph of result section

Include the limitation of the study and further discuss about the policy and implication in discussion section.

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 3 Report

  1. Why are the studies presented only in 2018? Are there any later ones? How do the results change over time?
  2. On page 5, in the last paragraph, there is a link framed as (Lin, 2019). This is presumably a reference [19]. Needs to be fixed.
  3. If the authors state that "The technical limitations of TIR instruments mean that the resolution of TIR images is coarser than optical and LiDAR data generated from UAV-based sensors" and «using a combination of with different remote sensing data can exploit the advantages of each source and  the different plant information,  they provide to offer a more accurate evaluation of the health status of vegetation. The improved accuracy for monitoring forest infestations via the comprehensive use of multi-source high-resolution remote sensing data may be conducive to limit the spread of the pests» (section 5.1), then it is necessary to propose a methodology (in the form of a block diagram or description of an algorithm) for remote sensing using both optical sensors and TIR and LiDAR instruments.
  4. In the future, it is necessary to calculate the cost of such a multispectral monitoring tool and the economic efficiency of its application. (Wish to the authors)

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Dear Authors

  Thank you very much for the revised version of the manuscript.

Please check all tables and figures caption and include in the text also.

 

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