Investigating Urban Heat Islands in Miami, Florida, Utilizing Planet and Landsat Satellite Data

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This study focuses on Miami, Florida, using Planet and Landsat satellite data to explore the urban heat island (UHI) effect. The researchers calculated land surface temperature (LST), generated spectral indices (NDVI, NDRE, VARI), and classified land cover. The results show distinct seasonal variations in LST and UHI intensity. The suitability analysis identified UHI - prone areas. Overall, it provides a valuable reference for understanding and mitigating UHI effects in Miami and other cities. 

1. Abstract

Please reduce the background introduction, increase the description of the research problem, and detail the technical issues solved by high-resolution satellite technology, the research methods, and the research results and findings.

2. Introduction

Emphasize the climate characteristics of Miami and cite local urban heat island literature. In the last paragraph, please add the research gap and the purpose of this study.

3. Methodology

It is recommended to justify the weighted overlay method (40% LST, 20% each index) and cite prior research that used this method. Figure 3 is difficult to read; it is recommended to enhance its readability for the readers.

4. Results

Please verify the data in Figure 8. Is the left side showing winter or summer? Ensure consistent arrangement of all figures. Please comprehensively explain the prominent UHI regions during both summer and winter, as well as areas experiencing UHIs in only one season. Discuss the land use patterns and potential causes of these phenomena.

5. Discussion

Discuss the impact of water bodies on Miami's UHI and compare Miami with other U.S. cities based on existing literature.

6. Conclusions

Emphasize the use of Planet data for fine-scale UHI hotspot detection, which fills a gap in prior Landsat/MODIS studies. Include actionable recommendations based on the findings for policy implications.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The content of the article is current, the issues are presented with relevant references.The article is appropriately structured and written in understandable language.The visual material nicely complements the text and contributes to the comprehensibility of the content (error in the title of figure 12, line 334).

I suggest some additions:

• The abstract outlines the research context well but lacks a clear articulation of the research gap. The key findings of the study that represent a scientific contribution should be highlighted.
• The research questions should be highlighted more clearly, and the objectives of the study could also be defined more explicitly, ideally in a separate paragraph to separate them from the basic information. I also miss the research hypotheses.
• The discussion is well written, but a discussion on the confirmation of the hypotheses and research limitations should be added to this section.
• The discussion and conclusions should more clearly include dynamic approaches to mitigating UHI, which are announced in the abstract as the aim of the study.
• Provide more details about the limitations of the method and its impact on generalizability.
• Clarify the study's contribution.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This study explored the relationship between spectral indices and Land surface Tem-perature for Miami, Florida. However, the paper has several shortcomings:

Most importantly, the relationship between the spectral indices used in this study and LST has been extensively explored in previous research. In particular, NDVI has become one of the essential parameters for calculating LST. This study is based on traditional methods for analysis and research, lacking in innovation and unique contributions.

1. There are many types of spectral indices relating LST, such as vegetation indices, water body indices, and built-up area indices. This study only examined vegetation indices. Even within vegetation indices, there are many indicators, such as RVI, NDVI, and DVI. This study only selected three vegetation indicators—NDVI, NDRE, and VARI—to study LST, which lacks typicality and representativeness and cannot objectively reflect the urban heat island effect in this region.
2. The image quality is low; it is recommended to enhance and standardise the images.
3. The data dates are limited to July and November 2023. The randomness of results from a single year significantly impacts the analysis of relationships.
4. The study uses data with an high cloud cover ratio; additional processing methods are needed.
5. This study has a simple workflow; the methods employed are not complex and lack innovation.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

The article uses high-resolution data from the new Planet satellite sensor to calculate surface indicators and identify surface features in order to investigate the causes of seasonal changes in the urban heat island effect in Miami. In order to further revise and improve the article for publication, the following content needs to be modified.

• The literature review should at least supplement the following two aspects: (1) What are the remote sensing indicators that affect surface temperature? What is the current state of research? (2) In which fields do high-precision remote sensing images have advantages?
• One of the advantages of Planet satellites is their high temporal resolution (a revisit cycle of one day), but the article only obtained data from one day each in winter and summer, thus failing to leverage the advantages of Planet satellites.
• The advantages of the Plnaet satellite's high spatial resolution have not been fully realized in the current research design. The Landsat satellite's 30-meter spatial resolution is sufficient for the task. Additionally, the Landsat satellite features mid-infrared and far-infrared bands, enabling the collection of more detailed surface information.
• In the correlation analysis between LST and surface indices, were the surface indices sampled at the same spatial resolution as the LST images? If not, then such a comparison is inappropriate.
• In comparison, the advantage of Planet satellites is their ability to identify surface features, providing more accurate surface information. Outside of built-up areas and vegetation, the article can identify more types of features, including water bodies. In addition, it is also possible to compare the correlation between the proportion of different features and LST.
• A comparison between remote sensing indices obtained from Landsat satellite imagery and those obtained from Planet satellite imagery can be included to highlight the spatial resolution advantages of Planet satellites.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Thanks for the corrections I suggested in the review.  I have no further comments.

Reviewer 4 Report

Comments and Suggestions for Authors

The article uses higher-resolution Planet satellite data to obtain land cover and vegetation data and analyzes the relationship between various vegetation indices and LST.Within the existing framework, the authors have provided sufficient information and data to support their conclusions. However, we still hope that the authors will make further improvements to optimize and enhance their work.