Monitoring Total Suspended Sediment Concentration in Spatiotemporal Domain over Teluk Lipat Utilizing Landsat 8 (OLI)
Round 1
Reviewer 1 Report
This is an interesting application needed to estimate spatially continuos sediment distribution along river mouth and coastal area.
However I think the manuscript must be improved in data presentation and clarity. My main concerns are related on some data presentation that is missing. In particular:
- A map with the positions of the lab samples used to calibrate the algorithm is needed.
It would be useful also to classify the sample points with a color scale representing the TSS concentration.
- Show what are the validation points.
- Why TSS concentration maps for 28/3/2018 and 16/4/ 2019 are not shown? I think must be shown displaying the calibration and validation points on the maps of the spatial distribution of TSS derived with the algorithm application and using the same TSS scale.
Please improve the discussion on the calibration and validation points compared with the relative TSS concentration maps
Author Response
Thank you for your comment, the answer to your comments is, because there are so many clouds on the images, we only choose x points and y points from each sample can comply. because of that, we do not use the image to create a TSS map. hope you can accept our explanation. thank you very much, sir.
Reviewer 2 Report
The manuscript examines some empirical models for estimation of total suspended sediment (TSS) from Landsat-8 imagery. There is no novelty from the methodological point of view. I recommend restructuring the paper as a case study. The introduction is shallow and missing the main concepts. The methods employed are not based on state-of-the-art models. The writing (English) of the paper also needs major improvements. Here are my detailed comments:
Major comments:
From the title and the abstract, it sounds that a new algorithm is going to be proposed for retrieving total suspended sediment (TSS). However, there is no novelty from the methodological point of view. Empirical methods (regression-based models) are widely used for the estimation of water quality parameters. This manuscript presents only a case study. This should be clarified throughout the paper and the contribution and objectives of the research should be revised.
The introduction is very shallow in terms of summarizing the remote sensing methods for estimation of TSS from optical imagery. There are physics-based methods rather than regression-based models that should be addressed in the introduction. For instance, water color simulator (WASI) provides a physics-based inversion with no need for in-situ samples for training. You can refer to several recent publications in MDPI Remote Sensing journal which are based on WASI physics-based modeling. This is an example and there are other models as well.
Table 1: the regression-based models are not limited only to the band ratio models. There are other spectral features like those derived from the transformation of color space, spectral derivatives, etc. You can refer to the following studies:
Novel spectra-derived features for empirical retrieval of water quality parameters: Demonstrations for OLI, MSI, and OLCI Sensors
A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques
Lines 107-108: utilization of three bands can not be considered as a novelty. There are several studies based on three bands and the selection of band combinations can be done automatically by considering all the possible band combinations to find the optimal one.
The quality of atmospheric correction should be demonstrated. There are several atmospheric correction methods that are specifically developed for aquatic applications (e.g., C2RCC, iCOR, etc). It is not clear why none of these methods are used. Also, there are surface reflectance products from Landsat-8 for aquatic applications that can be freely downloaded.
I suggest considering parameters like Bias also in the accuracy metrics to have a better understanding of the performance of the TSS retrieval method.
State-of-the-art methods like machine learning approaches are not considered and the contribution of the paper is vague.
The availability of data should be clarified. I recommend publishing the in-situ TSS along with the associated spectral data derived from Landsat imagery.
Minor comments:
Line 35: “during” is repeated. Revise the sentence. The English writing of the paper needs some improvements as well.
Author Response
We have revised our manuscript based on your generous comment, so we make some changes to our manuscript regarding your comment.
Abstract:
This study aims to monitor spatiotemporal TSS concentration over Teluk Lipat, Malaysia. To date, there are two commonly used to monitor TSS concentration over wide water regions. Firstly, field sampling is known very expensive and time-consuming method. Secondly, the remote sensing technology that can monitor spatiotemporal TSS concentration freely. Although remote sensing technology could overcome these problems, universal empirical or semiempirical algorithms still not available. Most of the developed algorithms are on a regional basis.
Introduction (we make some changes to the direction of our study)
This study aims to monitor spatial and temporal TSS concentration over Teluk Lipat, Malaysia. The remote sensing technique is used in this study. To fulfill the aim, three objectives were set up. The first objective is to develop and validate the regional TSS algorithm utilizing Landsat 8 (OLI) dataset. The second objective is to develop a TSS concentration map for the study area. The third objective is to analyze and investigate the TSS concentration in the space and time domain. To achieve the above-mentioned objective, two fields trip was conducted in the study area. The water sample is then processed in the lab to obtained measured TSS. The relation between the measured TSS and Landsat surface reflectance was determined by using a regression technique. The algorithm was developed empirically by using three Landsat 8 (OLI) bands which are band 3 (Green, l = 0.53-0.59 µm), band 5 (near Infrared, l = 0.85-0.88 µm), and band 6 (short-wave infrared, l = 1.57-1.65 µm). A TSS map was then created by applying the developed algorithm. The map is then analyzed to extract the required information. Since the algorithm is only validated with the data acquired over the study area, the application of the developed algorithm is only limited over Teluk Lipat Malaysia.
We also include summarized the flowchart of the data processing scheme of this study
Conclusion:
The main intention of this study monitors spatiotemporal TSS concentration over Teluk Lipat Malaysia utilizing Landsat 8 datasets. Three objectives stated earlier were successfully achieved. In this study, the regional TSS algorithm with regression coefficient, R2 =0.79 utilizing three Landsat 8 channels (Green, NIR, and SWIR) was successfully developed and validated. The regression statistics model between laboratory-derived in-situ value and model-fitted TSS concentration value of the validation points revealed a strong correlation with R2 = 0.8406, RMSE of 1.50mg/L MRE=9.14%. The TSS map is constructed using the developed algorithm. Analyses of the map suggested that most of the suspended sediment was distributed along the coastal line and over the river mouth. It is suggested that the TSS in this area are mostly transported by the river and induced by the wave. Others identified suspended induced factors are sand dredging activities and embarkment projects. This study succeeded determined the direction of sediment transport clearly.
I hope you can accept our explanation and we make major changes to our manuscript regarding your comment to improve our manuscript. TQVM for your time revised our manuscript. Thanks, sir
Author Response File: 
Author Response.docx
Round 2
Reviewer 1 Report
Author answer are fine for me.
Author Response
Thank you very much for your feedback and comments.
Reviewer 2 Report
The replies of the authors are not satisfactory and they haven't considered my comments. The replies are just like "We already make some changes to our manuscript", which are not acceptable. Thus, I couldn't get any clear reply to my comments. They are vague and not on the point.
Author Response
Please refer to the attachment
Author Response File: Author Response.docx
Round 3
Reviewer 2 Report
The authors have now changed the focus of the manuscript from method development to a case study or TSS retrieval. This sounds more reasonable as there is no methodological novelty. The paper sound to be now suitable for the readers of Applied Sceinces.
