Evaluating Water Turbidity in Small Lakes Within the Taihu Lake Basin, Eastern China, Using Consumer-Grade UAV RGB Cameras

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

In the attached document are some questions and suggestions that I think should be answered and improved in the paper

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

·         The title would be better to refer to the small lakes within the Taihu Lake Basin, eastern China

·         Introduction: Some disadvantages of the UAV approach (if any) would also be discussed

·         Line 49: Replace “effective” with effectiveness

·         Line 122: Why was data collected between June 3^rd and 18^th of 2023? Was a good time to capture turbidity? Justification is needed to make reader clear of why field data was collected at such time.

·         Line 137: Delete “and from the sentence

·         Line 162: What CMOS refers to?

·         Line 230-231: It looks like there was a heavy weight given to train the model. Please justify having 80% of data for model training and only 20% for validation

·         Figure 5 could be presented with better quality

·         Good discussion, but sometimes there were long sentences. Try to shorten sentences to minimize grammatical errors

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This article aims to monitor turbidity using a low-cost airborne platform, the Mavic Air 2 SZ drone, equipped with an RGB camera. The study holds significant relevance for the scientific community as it presents a robust and well-validated methodology for turbidity monitoring through RGB imaging combined with machine learning models. The use of an RGB camera is particularly innovative within this field, which traditionally relies on multispectral or hyperspectral sensors for water quality assessments. By demonstrating the feasibility of RGB cameras, this research introduces a more cost-effective alternative for water quality monitoring, specifically for turbidity. For these reasons, I consider the article suitable for publication in the journal Drones.

Further details will follow.

  

Introduction

Line 52/53: It is important to mention that NIR bands have good correlations with turbidity.

 

Materials and Methods

 

I'd suggest going into more detail about how the R, G and B are separated from the RBG image, which is already composed in true color.

 

Results

 

Table 1: Only the R single band model was tested. Why weren't the G and B single bands tested??

 

 

Discussion

 

Line 388: I do not consider values ranging from 0.4 to 42.4 to represent high turbidity levels

Author Response

Please see the attachment.

Author Response File: Author Response.pdf