Analyzing the Contribution of Urban Land Uses to the Formation of Urban Heat Islands in Urmia City

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

You mention that urbanization promotes energy consumption and affects thermal comfort. Could you provide specific data or case studies to quantify the extent of this impact? you can use of below refrence to cover this issue

A. Karimi, P. Mohammad, A. García-Martínez, D. Moreno-Rangel, D. Gachkar, and S. Gachkar, “New developments and future challenges in reducing and controlling heat island effect in urban areas,” Environ. Dev. Sustain., vol. 25, no. 10, pp. 10485–10531, 2023, doi: 10.1007/s10668-022-02530-0.

While you note that the UHI intensity can vary between 0 and 7 degrees Celsius, is this range consistent across various studies and locations? Could you clarify whether this range is typical for Urmia or globally?

The introduction discusses both Surface Urban Heat Islands (SUHI) and Atmospheric Urban Heat Islands (AUHI). Do you plan to address both phenomena in your study? If so, could you specify how your methodology differentiates between them?

What specific methodologies or approaches does your study use to measure and analyze the UHI effect in Urmia? How do these methods compare to those used in other cities or regions?

Could you elaborate on the role of remote sensing technology in your study? Are there particular satellite platforms or thermal imaging techniques you're using for Urmia?

The population growth of Urmia is highlighted, but how does this compare with other similar-sized cities? Could this contextual comparison strengthen the argument that urbanization has directly led to the increased UHI effect?

You mention that the destruction of vegetation in Urmia has contributed to UHI development. Could you specify the percentage or amount of vegetation loss and its corresponding effect on the city's temperature?

Since your study focuses on urban land uses and their contribution to UHI in Urmia, could you provide more details about the types of land use changes (e.g., industrial, residential) and their specific contributions to the UHI phenomenon?

You indicate that the study's results will inform urban planners and policymakers. Could you outline what specific strategies or urban cooling techniques are recommended, based on the study's outcomes?

Have other studies focused on UHI in Urmia or similar cities? If so, how does your study build upon or differ from these previous works? i have mention some refrence can help you in this line 

 B. Halder, A. Karimi, P. Mohammad, J. Bandyopadhyay, R. D. Brown, and Z. M. Yaseen, “Investigating the relationship between land alteration and the urban heat island of Seville city using multi-temporal Landsat data,” Theor. Appl. Climatol., pp. 1–23, 2022.

A. Karimi et al., “Surface Urban Heat Island Assessment of a Cold Desert City: A Case Study over the Isfahan Metropolitan Area of Iran,” Atmosphere (Basel)., vol. 12, no. 10, p. 1368, 2021.

B. Mahdavi Estalkhsari, P. Mohammad, and A. Karimi, “Land Use and Land Cover Change Dynamics and Modeling Future Urban Growth Using Cellular Automata Model Over Isfahan Metropolitan Area of Iran,” in Ecological Footprints of Climate Change, Springer, 2022, pp. 495–516.

• How does your study contribute uniquely to the existing literature on urban heat islands (UHIs), particularly in the context of Urmia city?
• What validation procedures were used to ensure the accuracy of the Landsat satellite data for temperature and land-use analysis?
• Could you provide more details on why you selected Planck’s algorithm for land surface temperature extraction over other methods?
• How frequently was data collected between 1990 and 2023, and how might the temporal scale of analysis affect your findings?
• Did you conduct any regional comparisons within Urmia to analyze spatial clustering of UHI effects, and how are these clusters related to land-use patterns?
• How do the temperature increases in constructed areas (4.62°C) and garden lands (13.23°C) compare with other cities facing UHI challenges?
• Have you conducted any sensitivity analysis to account for uncertainties in temperature measurements, especially the significant differences between land-use types?
• Could you clarify how the increase in urban greenery could be practically implemented in Urmia’s urban planning and how it would mitigate UHI effects?
• How would establishing satellite cities influence UHI effects in Urmia, and how does this strategy compare to other UHI mitigation techniques?
• Could you provide more details on the statistical methods used for the correlation analysis between NDVI and land surface temperature (LST)?
• Have you considered including other factors, such as building height or density, in your analysis of UHI effects, and how might these influence your findings?
• How does your research build upon or differ from studies by Grover and Singh (2015) and Harun (2020) in terms of methodology or conclusions?
• Can you offer more specific policy recommendations for city planners based on your findings, particularly for mitigating UHI effects in Urmia?
• Are there any limitations in your study regarding the accuracy of satellite data or geographic coverage that should be addressed?
• What specific methodologies or tools do you suggest for future studies to consider three-dimensional elements, like building height or wind direction, in UHI analysis?

Author Response

Comment 1: You mention that urbanization promotes energy consumption and affects thermal comfort. Could you provide specific data or case studies to quantify the extent of this impact? you can use of below reference to cover this issue

Karimi, P. Mohammad, A. García-Martínez, D. Moreno-Rangel, D. Gachkar, and S. Gachkar, “New developments and future challenges in reducing and controlling heat island effect in urban areas,” Environ. Dev. Sustain., vol. 25, no. 10, pp. 10485–10531, 2023, doi: 10.1007/s10668-022-02530-0.

Response 1: Thank you so much for your comments and providing references to address the comments. The authors appreciate your kind help to improve the quality of the manuscript.

This comment has been addressed in the first paragraph of introduction section and highlighted.

 

Comment 2: While you note that the UHI intensity can vary between 0 and 7 degrees Celsius, is this range consistent across various studies and locations? Could you clarify whether this range is typical for Urmia or globally?

Response 2: Thank you for your comment. The authors studied more references and found that UHI intensity can vary between 0 and 7 degrees Celsius not 0-7 degrees. This range is considered globally. 

We revised this part and highlighted.

Comment 3: The introduction discusses both Surface Urban Heat Islands (SUHI) and Atmospheric Urban Heat Islands (AUHI). Do you plan to address both phenomena in your study? If so, could you specify how your methodology differentiates between them?

Response 3: Thank you for your comment. In our study we considered and discussed Surface UHIs.

 

Comment 4: What specific methodologies or approaches does your study use to measure and analyze the UHI effect in Urmia? How do these methods compare to those used in other cities or regions?

Response 4: Thank you for your comment.

Earth’s surface temperature was measured using ENVI software, employing the Planck Equation method. Other methods include the Mono Window, Single Channel, Radiative Transfer Equation, and Split Window techniques. The Planck function method is one of the most fundamental approaches for calculating Earth’s surface temperature in remote sensing. This algorithm is simpler than other methods and requires the brightness temperature image and emissivity image of the study area for calculation.

 

Comment 5: Could you elaborate on the role of remote sensing technology in your study? Are there particular satellite platforms or thermal imaging techniques you're using for Urmia?

Response 5: Thank you for your comment.

Remote sensing offers a significant advantage, as it allows us to obtain valuable information. The primary element used in this method is electromagnetic waves. The reflection of these waves from different objects enables us to gather diverse information about them in the Urmia region. In this research, Landsat 5 and 8 images were used, specifically thermal band 6 in Landsat 5 and thermal band 11 in Landsat 8. The Landsat satellite, from TM to TIRS sensors, includes a thermal band in the 10 to 12-micrometer range. The presence of these thermal bands, with resolutions of 120, 60, and 100 meters, facilitates the study of phenomena from a thermal perspective.

We added more explanation regarding adopting Remote Sensing technology I our study in the first paragraph of the Methods section.

 

Comment 6: The population growth of Urmia is highlighted, but how does this compare with other similar-sized cities? Could this contextual comparison strengthen the argument that urbanization has directly led to the increased UHI effect?

Response 6: Thank you for your comment. It has been addressed and highlighted in the last paragraph of introduction and highlighted.

 

Comment 7: You mention that the destruction of vegetation in Urmia has contributed to UHI development. Could you specify the percentage or amount of vegetation loss and its corresponding effect on the city's temperature?

Response 7: Thank you for your comment. According to Table 3, the area of gardens decreased from 1,749.63 hectares in 1990 to 284.97 hectares in 2023, a reduction of approximately 1,464.66 hectares. The vegetation and agricultural lands that once surrounded the city like a belt have been significantly reduced due to the physical expansion of Urmia. Table 6 indicates that the maximum temperature increased from 42.46°C in 1990 to 47.22°C in 2023.

 

Comment 8: Since your study focuses on urban land uses and their contribution to UHI in Urmia, could you provide more details about the types of land use changes (e.g., industrial, residential) and their specific contributions to the UHI phenomenon?

Response 8: Thank you for your comment. However, this point falls outside the goals and objectives of our study, which focused solely on four major land use classes: barren lands, constructed lands, agricultural lands, and garden lands. We chose to study these four classes to identify the impact of constructed land on UHI creation and intensification. Since other land uses, such as industrial and residential, are included within the category of constructed lands, we did not analyze them individually. Additionally, there are numerous other land use types, such as educational, commercial, and entertainment, whose analysis is beyond the scope of this study.

 

Comment 9: You indicate that the study's results will inform urban planners and policymakers. Could you outline what specific strategies or urban cooling techniques are recommended, based on the study's outcomes?

Response 9: Thanks for your comment. This was addressed in Conclusion section and highlighted.

 

Comment 10: Have other studies focused on UHI in Urmia or similar cities? If so, how does your study build upon or differ from these previous works? i have mention some reference can help you in this line 

2022. Halder, A. Karimi, P. Mohammad, J. Bandyopadhyay, R. D. Brown, and Z. M. Yaseen, “Investigating the relationship between land alteration and the urban heat island of Seville city using multi-temporal Landsat data,” Theor. Appl. Climatol., pp. 1–23, 2022.
2023. Mahdavi Estalkhsari, P. Mohammad, and A. Karimi, “Land Use and Land Cover Change Dynamics and Modeling Future Urban Growth Using Cellular Automata Model Over Isfahan Metropolitan Area of Iran,” in Ecological Footprints of Climate Change, Springer, 2022, pp. 495–516.

 

Response 10: Thank you for your comment and providing valuable references. Yes, there are several studies about UHI in similar cities all around the world. However, our study focused on the impact of major urban land uses on UHI intensification using Remote sensing technology. In most cases, the city size, growth, urban land uses alteration pattern, and the adapted methods are different. For example: in the following study Isfahan city has a population of over 2,109000, which means its urbanization level and population density are different, and accordingly, display a district UHI pattern.

2021. Karimi et al., “Surface Urban Heat Island Assessment of a Cold Desert City: A Case Study over the Isfahan Metropolitan Area of Iran,” Atmosphere (Basel)., vol. 12, no. 10, p. 1368, 2021.

 

Comment 11: How does your study contribute uniquely to the existing literature on urban heat islands (UHIs), particularly in the context of Urmia city?

Response 11: Our study identifies a significant gap in studies addressing UHI dynamics in mid-sized cities and utilize advanced remote sensing techniques to analyze major urban land uses' impact on UHI intensification. Our findings reveal distinct heat retention patterns in Urmia that differ from those observed in larger metropolitan areas, providing practical implications for local urban planning and strategies to mitigate UHI effects. Additionally, our research paves the way for future studies on UHI trends and comparative analyses with similar cities.

 

Comment 12: What validation procedures were used to ensure the accuracy of the Landsat satellite data for temperature and land-use analysis?

Response 12: As mentioned in Methods section, the Kappa coefficient and total accuracy coefficient were used to evaluate the accuracy of land use classification.

 

Comment 13: Could you provide more details on why you selected Planck’s algorithm for land surface temperature extraction over other methods?

Response 13: The Planck’s algorithm is one of the most basic methods for calculating Earth’s surface temperature in remote sensing. This algorithm is simpler than other methods, requiring a brightness temperature image and an emissivity image of the study area for calculation. Both of these can be captured in Landsat images and are applicable across all sensors and thermal bands.

More explanation has been added to regarding Planck’s method in Methods section and highlighted.

 

Comment 14: How frequently was data collected between 1990 and 2023, and how might the temporal scale of analysis affect your findings?

Response 14: The research timeline begins during a period of slow urbanization in Iran, with the phase of rapid urbanization starting in 1990.

 

Comment 15: Did you conduct any regional comparisons within Urmia to analyze spatial clustering of UHI effects, and how are these clusters related to land-use patterns?

Response 15: Yes, the Zonal Statistics As Table algorithm and the Cluster and Outlier Analysis algorithm were implemented in ArcMap.

 

Comment 16: How do the temperature increase in constructed areas (4.62°C) and garden lands (13.23°C) compare with other cities facing UHI challenges?

Response 16: The temperature increases observed in Urmia’s constructed areas (4.62°C) and garden lands (13.23°C) are comparable with findings in other cities experiencing UHI effects, though they vary in intensity depending on urban density, land use, and climatic factors. For example, studies in metropolitan areas like Tokyo and Shanghai report temperature rises of 3–6°C in built-up areas, which aligns with our findings for constructed areas. However, the 13.23°C rise in garden lands in Urmia is notably higher than typical increases in green spaces, suggesting unique local factors, possibly related to vegetation type and maintenance practices.

 

Comment 17: Have you conducted any sensitivity analysis to account for uncertainties in temperature measurements, especially the significant differences between land-use types?

Response 17: Yes, as mentioned in the Method section, pre-processing steps including radiometric correction, atmospheric correction, and the calculation of the accuracy coefficient and Kappa coefficient have been completed.

 

Comment 18: Could you clarify how the increase in urban greenery could be practically implemented in Urmia’s urban planning and how it would mitigate UHI effects?

Response 18: To practically implement increased urban greenery in Urmia’s urban planning, a multi-layered approach could be adopted. This includes establishing green roofs, enhancing tree coverage along streets, and converting underutilized spaces into pocket parks. These measures are feasible within Urmia's existing urban framework and could be integrated into zoning policies and building codes. Increasing greenery mitigates UHI effects by providing shade, lowering surface and air temperatures through evapotranspiration, and reducing heat retention in constructed areas. Together, these strategies would contribute to a more sustainable urban climate, improving thermal comfort and overall urban resilience.

 

Comment 19: How would establishing satellite cities influence UHI effects in Urmia, and how does this strategy compare to other UHI mitigation techniques?

Response 19: As mentioned in discussion section, establishing satellite cities could reduce UHI effects in Urmia by decentralizing urban density, alleviating heat concentration in the city center. By redistributing population and development, satellite cities help reduce the intensity of built-up areas, which are major contributors to UHI. Compared to other mitigation techniques like increasing urban greenery, implementing cool roofs, or enhancing reflective surfaces, satellite cities offer a long-term structural solution by managing urban sprawl. While direct UHI mitigation techniques can offer immediate temperature reduction, satellite cities address root causes of urban heat by spreading infrastructure and reducing core urban density, creating a complementary and sustainable approach to UHI mitigation.

 

Comment 20: Could you provide more details on the statistical methods used for the correlation analysis between NDVI and land surface temperature (LST)?

Response 20: Thank you for your comment.

All statistical methods related to the research were conducted in ArcMap.

First, we used the zonal statistics as table algorithm to determine the relationship between temperature and land use.

Next, the temperature layer was converted into a point layer using the raster to point algorithm.

Then, we applied the Spatial Autocorrelation algorithm to perform Moran’s correlation.

After that, we utilized the Cluster and Outlier Analysis algorithm to prepare the Moran image layer.

Finally, we employed the Hot Spot Analysis algorithm to determine the spatial distribution of the indicators.

 

This process has been added to Morgan’s index analysis after table 6.

Comment 21: Have you considered including other factors, such as building height or density, in your analysis of UHI effects, and how might these influence your findings?

Response 21: Building height factors have not been investigated in our data; these factors could be explored in future research using LiDAR images.

 

Comment 22: How does your research build upon or differ from studies by Grover and Singh (2015) and Harun (2020) in terms of methodology or conclusions?

Response 22: In terms of Methodology:

Grover and Singh (2015) study employ Landsat 5 TM imagery from a single time period (2010) to analyze surface UHI in Delhi and Mumbai, comparing urban heat patterns between an inland city (Delhi) and a coastal city (Mumbai). The researchers use NDVI to validate UHI patterns by identifying temperature variations across different land uses, such as built-up areas, water bodies, and vegetated zones.

Harun (2020) research focuses on the impact of environmental and anthropogenic factors on UHI intensity by collecting high-resolution data, including temperature, wind speed, humidity, and solar radiation, over four days at multiple sites within and around Kuala Lumpur. The study uses ultrasonic anemometers and existing meteorological equipment to gather precise measurements, distinguishing it with real-time data collection for day and night variations in UHI intensity.

But our study investigates UHI formation in Urmia over a more extended time frame (1990 to 2023) using Landsat 5 and 8 data. It examines the effects of various land uses on UHI intensity, specifically focusing on barren lands, garden lands, and clustered hot spots. This study also uses time-series data to track UHI changes and utilizes spatial clustering to identify hot spots over time.

In terms of Conclusion:

Grover and Singh (2015) study conclude that UHI intensity varies by city type; Delhi’s higher tree cover and mixed land use reduce UHI effects compared to Mumbai, which experiences stronger UHI due to limited green spaces and dense built-up areas. NDVI’s negative correlation with surface temperature highlights the moderating effect of vegetation in reducing UHI.

Harun (2020) study finds that land cover is the primary factor influencing UHI in Kuala Lumpur, where high-rise buildings, combined with patches of vegetation and water bodies, reduce UHI effects through shading and evapotranspiration. Notably, the study observes a 6°C increase in nighttime temperatures and a 4°C daytime cooling effect, highlighting the dynamic relationship between built environment and natural elements in moderating UHI.

But our study finds that barren lands consistently show the highest temperatures, while garden lands remain cooler, with UHI clustering in specific areas over time. The study emphasizes the need for urban planning strategies in Urmia to mitigate UHIs and enhance climate resilience, suggesting that land use and vegetation management are critical for addressing UHI challenges.

 

Comment 23: Can you offer more specific policy recommendations for city planners based on your findings, particularly for mitigating UHI effects in Urmia?

Response 23: Increasing vegetation cover in the centers and surrounding areas of Urmia can help reduce the city’s heat island effect. Additionally, establishing a green belt around the city and developing satellite cities are effective strategies for mitigating the heat island phenomenon in Urmia.

Comment 24: Are there any limitations in your study regarding the accuracy of satellite data or geographic coverage that should be addressed?

Response 24: In this research, higher-resolution images could be used instead of Landsat images to reduce the error rate. However, in Iran, due to high cost and restrictions on accessing these images, alternative sources cannot be utilized.

 

Comment 25: What specific methodologies or tools do you suggest for future studies to consider three-dimensional elements, like building height or wind direction, in UHI analysis?

Response 25: To enhance UHI analysis by incorporating three-dimensional elements like building height and wind direction, we recommend using advanced geospatial and computational tools. LiDAR (Light Detection and Ranging) is highly effective for capturing 3D urban morphology, providing detailed data on building heights and vegetation structure, which are crucial for assessing how vertical structures influence heat distribution. Computational Fluid Dynamics (CFD) modeling is another valuable approach, as it enables the simulation of airflow and temperature patterns around complex urban forms, offering insights into how wind direction and building height interact to affect UHI intensity.

In addition, 3D urban climate models such as ENVI-met can simulate microclimatic interactions in high resolution, accounting for both structural and atmospheric factors. Combining LiDAR-based 3D city models with CFD and ENVI-met would enable researchers to analyze UHI effects more comprehensively, particularly in cities with dense vertical development. These methodologies could provide actionable insights for urban planners to design climate-resilient urban landscapes by taking into account the interplay of built forms, vegetation, and airflow.

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript under review is devoted to the formation of Urban Heat Islands and the conditions of their creation under the influence of different land uses. The authors used Urmia city as case study. The research is based on the use of Landsat 5 and Landsat 8 data for 1990 and 2023. The manuscript is rich with maps, illustrating the main points proven by the authors and with tables supporting the main positions with data. The authors successfully prove the main positions of their conclusions concerning the state of urban environment.

Among the remarks the first place is the abbreviations. The reviewer understands the specialists in their own field are used to speak and write in their own internal slang. Of course, it is easier for them, but here we are to think about the readability of journal by the people who are not specialists in the narrow field, so it is better to escape the use of abbreviations, even well understandable by authors, reviewers and editors in the most widely read parts of the text: in keywords, abstract, title. So, it’ll be better to eliminate abbreviations from the abstract and keywords (e.g.: Urban Heat Islands = UHI, etc.).

Author Response

Reviewer Comments and Suggestions for Authors:

The manuscript under review is devoted to the formation of Urban Heat Islands and the conditions of their creation under the influence of different land uses. The authors used Urmia city as case study. The research is based on the use of Landsat 5 and Landsat 8 data for 1990 and 2023. The manuscript is rich with maps, illustrating the main points proven by the authors and with tables supporting the main positions with data. The authors successfully prove the main positions of their conclusions concerning the state of urban environment.

Among the remarks the first place is the abbreviations. The reviewer understands the specialists in their own field are used to speak and write in their own internal slang. Of course, it is easier for them, but here we are to think about the readability of journal by the people who are not specialists in the narrow field, so it is better to escape the use of abbreviations, even well understandable by authors, reviewers and editors in the most widely read parts of the text: in keywords, abstract, title. So, it’ll be better to eliminate abbreviations from the abstract and keywords (e.g.: Urban Heat Islands = UHI, etc.).

Author response:

Thank you so much for your kind comments and suggestions.

The authors revised the writing language of the manuscript and eliminated slangs from the whole manuscript and eliminated abbreviations from the abstract and keywords.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

In connection with this paper titled "Analyzing the Contribution of Urban Land Uses on Urban Heat Islands Formation in Urmia City," I would like to express my approval for its acceptance. The study provides valuable insights into the influence of land use on Urban Heat Island (UHI) formation, utilizing Landsat satellite data from 1990 and 2023. The methodology is sound, and the results clearly demonstrate significant temperature variations across different land uses, highlighting the critical role that barren lands play in exacerbating heat. The findings are not only well-presented but also offer practical implications for urban policymakers and planners seeking to mitigate UHI effects and enhance climate resilience in urban areas. Overall, the manuscript is well-organized, and I believe it will contribute significantly to the field.