Synergy of Remote Sensing and Geospatial Technologies to Advance Sustainable Development Goals for Future Coastal Urbanization and Environmental Challenges in a Riverine Megacity

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

I would like to express my sincere gratitude for the opportunity to review the manuscript titled “Synergy of Remote Sensing and Geospatial Technologies to Advance SDGs for Future Coastal Urbanization and Environmental Challenges in a Riverine Megacity.” I hope that my report has made a meaningful contribution to enhancing the quality of this paper.

The paper has utilized multitemporal Landsat imagery and advanced modeling techniques to analyze land use/land cover changes from 1990 to 2020, showing significant urban expansion and a decrease in vegetation and water bodies, which poses increased flood risks. The findings highlight the implications for various Sustainable Development Goals (SDGs) and provide a framework for urban planners to implement adaptive strategies in similarly affected megacities. The paper needs some major improvements to be published in IJGI.

Major comments:

1.      Title:

- Please write the title using the full phrase "Sustainable Development Goals" instead of the acronym "SDGs".

2.      Abstract:

-          I believe that the abstract of a scientific paper should adhere to a problem-solution structure. What specific gap in the existing research does your paper address, and what solution do you propose to fill that gap? Regrettably, I am unable to identify any innovative aspects in your abstract.

 

-          You have utilized the Kappa index to assess land use change maps. However, this index is not an effective measure of accuracy. As highlighted in the well-known article "The Death of Kappa" by Prof. Pontius, it is advisable to use more reliable indicators for evaluating your model. I recommend referring to the following sources for better alternatives.

 

-Pontius Jr, Robert Gilmore, and Marco Millones. "Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment." International journal of remote sensing 32.15 (2011): 4407-4429.

-Ahmadlou, Mohammad, Mohammad Karimi, and Nadhir Al-Ansari. "The use of maximum entropy and ecological niche factor analysis to decrease uncertainties in samples for urban gain models." GIScience & Remote Sensing 60.1 (2023): 2222980.

 

3.      Introduction

-          Lines 49-51: "Megacities... change [1-4].” Please be cautious when using words in your sentences. A megacity is typically defined as... Additionally, the sentence lacks clarity. Are megacities specifically located in coastal zones? Is that a definitive rule? While they can be found in coastal areas, it is not a strict requirement. Therefore, the paper needs substantial improvement in both grammar and clarity.

-          Second sentence also is unclear.

-          Lines 82-84: you should refer to UN not to another one.

-          Lines 94-106: Once again, the specific gap this study intends to address is not clear. Please clearly articulate your objectives.

-          Lines 112-113: GIS and RS are tools?

-          Lines 112-132: I think you should include this paragraph in methodology section.

-          Lines 133-167: This paragraph should be included in the study area section.

-          Lines 145-167: This part should include in last paragraph of Introduction section.

-          Totally the introduction section needs significant enhancement.

 

4.      Materials and Methods

-          Lines 204-206: Why the time intervals are uneven? Why have you selected these times?

-          I can’t see Implementation phase in your figure 2.

-          The MOLUSCE can’t accept other driving factors for land use change? For example, distance to business centers may drive land use change, so can a modeler use this factor in MOLUSCE?

-          I can’t see the name of validation metrics in Figure 2.

-          Again Kappa is not suitable metric to evaluate the performance of land use change models. Please use suitable metrics as I mentioned in my comments at Abstract.

5.      Results

-          The results were well-presented, but lacked adequate validation.

6.      Discussion

The discussion section has been written well. But I would like to see some specific challenges like imbalance problem in land use change modeling. Can your proposed model handle imbalance problem of land use change data? You can refer to below recently published papers:

Ahmadlou, Mohammad, Mohammad Karimi, and Nadhir Al-Ansari. "The use of maximum entropy and ecological niche factor analysis to decrease uncertainties in samples for urban gain models." GIScience & Remote Sensing 60.1 (2023): 2222980.

Ahmadlou, Mohammad, Mohammad Karimi, and Robert Gilmore Pontius Jr. "A new framework to deal with the class imbalance problem in urban gain modeling based on clustering and ensemble models." Geocarto International 37.19 (2022): 5669-5692.

Ahmadlou, Mohammad, et al. "Three novel cost-sensitive machine learning models for urban growth modelling." Geocarto International 39.1 (2024): 2353252.

 

 

Comments for author File: Comments.pdf

Comments on the Quality of English Language

---

Author Response

Response to Reviewer 1

General Comments: I would like to express my sincere gratitude for the opportunity to review the manuscript titled “Synergy of Remote Sensing and Geospatial Technologies to Advance SDGs for Future Coastal Urbanization and Environmental Challenges in a Riverine Megacity.” I hope that my report has made a meaningful contribution to enhancing the quality of this paper.

The paper has utilized multitemporal Landsat imagery and advanced modeling techniques to analyze land use/land cover changes from 1990 to 2020, showing significant urban expansion and a decrease in vegetation and water bodies, which poses increased flood risks. The findings highlight the implications for various Sustainable Development Goals (SDGs) and provide a framework for urban planners to implement adaptive strategies in similarly affected megacities. The paper needs some major improvements to be published in IJGI.

Major comments:

Comments 1:  Title: Please write the title using the full phrase "Sustainable Development Goals" instead of the acronym "SDGs".

Response 1: Thank you for your constructive feedback. We have revised the abbreviations to include their full meaning for clarity.

Comments 2:   Abstract: I believe that the abstract of a scientific paper should adhere to a problem-solution structure. What specific gap in the existing research does your paper address, and what solution do you propose to fill that gap? Regrettably, I am unable to identify any innovative aspects in your abstract.

Response 2: Thank you for your constructive feedback regarding the abstract's structure. We appreciate your careful review and understand your concerns about clearly articulating the research gap and innovative aspects. After careful consideration, we have revised the abstract to address these important points while maintaining its scientific rigor and comprehensive coverage of our research findings. The revised abstract now explicitly identifies a critical research gap in understanding the integrated impacts of LULC changes on both ecosystem vulnerability and sustainable development achievements in coastal megacities. While previous research has typically focused on either urban growth patterns or environmental impacts in isolation, our study introduces a novel methodological framework that uniquely combines LULC analysis with quantitative SDG achievement metrics. This integration represents a significant advancement in urban sustainability assessment, particularly for rapidly developing coastal regions. Our innovative approach is demonstrated through several key elements: First, the successful integration of multiple data sources (Landsat imagery, SRTM-DEM, historical maps, and population data) with advanced modeling techniques (MOLUSCE plugin with CA-ANN) provides a robust foundation for both historical analysis and future projections. Second, the achievement of an overall accuracy greater than 97%, with user and producer accuracies above 77%, and a Kappa coefficient approaching validates the reliability of our predictive methodology. Third, and perhaps most significantly, our framework uniquely quantifies the relationship between urban development patterns and SDG achievement potentials, providing concrete metrics for sustainability assessment that can be replicated in other megacities facing similar challenges. The abstract maintains its comprehensive presentation of significant findings while now more clearly emphasizing the innovative aspects of our research approach and its practical implications for urban planning and sustainable development.

Comments 3:  Abstract: You have utilized the Kappa index to assess land use change maps. However, this index is not an effective measure of accuracy. As highlighted in the well-known article "The Death of Kappa" by Prof. Pontius, it is advisable to use more reliable indicators for evaluating your model. I recommend referring to the following sources for better alternatives. -Pontius Jr, Robert Gilmore, and Marco Millones. "Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment." International journal of remote sensing 32.15 (2011): 4407-4429. And -Ahmadlou, Mohammad, Mohammad Karimi, and Nadhir Al-Ansari. "The use of maximum entropy and ecological niche factor analysis to decrease uncertainties in samples for urban gain models." GIScience & Remote Sensing 60.1 (2023): 2222980.

Response 3: Thank you for your valuable feedback. In the initial study, Kappa statistics were used for result validation. However, in the revised version, a confusion matrix has been employed and included in the supplementary materials. To enhance validation robustness, stratified sampling was carefully implemented across different land use categories to calculate Kappa, overall accuracy, producer accuracy, and user accuracy, see lines 320-332 and 417-422. This approach ensures a comprehensive assessment of the model's performance across diverse contexts while minimizing potential biases.

Comments 4:  Introduction: Lines 49-51: "Megacities... change [1-4].” Please be cautious when using words in your sentences. A megacity is typically defined as... Additionally, the sentence lacks clarity. Are megacities specifically located in coastal zones? Is that a definitive rule? While they can be found in coastal areas, it is not a strict requirement. Therefore, the paper needs substantial improvement in both grammar and clarity.

Response 4: Thank you for your insightful comments regarding the definition and geographical context of megacities. We have revised this section to provide greater precision and clarity in our terminology, see lines 50-52. The text has been modified to incorporate a standardized definition of megacities while accurately representing their relationship with coastal zones. According to the United Nations' definition, a megacity is an urban agglomeration with a population exceeding 10 million inhabitants. While our study focuses on coastal megacities due to their unique environmental challenges from both rapid urbanization and climate change impacts, including sea-level rise, storm surges, and altered precipitation patterns, we acknowledge that megacities exist in various geographical contexts.

Comments 5:  Introduction: Second sentence also is unclear.

Response 5: Thank you for emphasizing the need for greater clarity in our sentence structure. We recognize that the original sentence required refinement to better convey the spatial distribution and economic significance of coastal megacities. Please refer to lines 56–61: "The global distribution of megacities shows significant presence along coastal zones, with a particularly high concentration in South Asia (Figure 1a). These urban agglomerations function as critical centres of industrial development and economic activity, offering substantial competitive advantages for developing nations through port facilities, international trade connections, and industrial infrastructure networks [5-7]."

Comments 6:  Introduction: Lines 82-84: you should refer to UN not to another one.

Response 6: Thank you for highlighting the importance of proper citation regarding the Sustainable Development Goals (SDGs). We acknowledge the need to directly reference the United Nations as the primary source for this global initiative. Please refer to lines 98–101: "To address these global challenges, the United Nations General Assembly established 17 Sustainable Development Goals (SDGs) in 2015 (UN Resolution A/RES/70/1), encompassing 169 targets that integrate environmental protection, human well-being enhancement, and economic development (United Nations, 2015)."

Comments 7:   Introduction: Lines 94-106: Once again, the specific gap this study intends to address is not clear. Please clearly articulate your objectives.

Response 7: Thank you for highlighting the need to articulate more clearly the research gap and objectives. After a comprehensive review of our study and the current literature, we propose the following revised text to better emphasize our unique contribution, see lines 129–139: "While existing research has made significant advances in spatiotemporal monitoring of LULC dynamics using multispectral satellite imagery across diverse climatic regions [11,15-17], three critical gaps persist in current understanding. First, although studies have examined either urban growth patterns or flood hazards independently, limited research integrates both aspects within a unified analytical framework for coastal megacities. Second, while the importance of SDGs is widely recognized, quantitative methodologies linking LULC changes directly to SDG achievement metrics remain underdeveloped, particularly for economic indicators (SDGs 8 and 9), environmental measures (SDGs 13 and 15), and social benchmarks (SDGs 11 and 6). Third, existing predictive models often lack the integration of hydrological risk assessment with future urban development scenarios, limiting their practical application in sustainable urban planning. This study addresses these gaps through an innovative methodological framework that combines MOLUSCE geospatial predictive modeling with HEC-RAS hydrological simulations. Our approach uniquely quantifies the relationships between urban expansion, environmental degradation, and SDG achievement potential in coastal megacities.”

Our revised objectives are articulated in lines 149–162 as follows: “This research focuses on Karachi, Pakistan, a rapidly expanding coastal megacity facing significant environmental challenges due to unplanned urbanization and climate change impacts. Karachi serves as an ideal case study, exemplifying the complex inter-play between urban growth and environmental degradation in stressed coastal regions. The research aims to: 1. Monitor spatiotemporal LULC changes from 1990 to 2020 to identify primary drivers of land change and associated natural resource degradation. 2. Predict potential LULC alterations for 2025, 2030, and 2035. 3. Investigate shifts in stream channels for the Malir River Basin from 1990 to 2020 to inform hydrological stress prioritization strategies. 4. Simulate flood inundation scenarios for the 2020 torrential rain event using contemporary LULC data and projected maps for 2025–2035. 5. Explore the contributions of the integrated approach outputs to potential positive and negative impacts on SDGs.”

Comments 7:  Introduction: Lines 112-113: GIS and RS are tools?

Response 7: We apologize for the unwilling error. The sentence has been revised as follows (lines 111-114): " Advancements in remote sensing (RS) sensors, combined with Geographic Information Systems (GIS) techniques, have greatly improved the ability to monitor LULC dynamics [8], enabling a deeper understanding and more effective management of urban environmental challenges (Ahmadlou et al., 2023).”

Comments 8:  Introduction: Lines 112-132: I think you should include this paragraph in methodology section.

Response 8: Thank you for your constructive feedback regarding the placement of the methodological content. We agree that much of this text is better suited for the methodology section, as it outlines the specific tools and techniques used in our analysis. However, we believe that a concise overview of the technological approach remains valuable in the introduction to provide context for our research framework. Accordingly, we propose relocating the detailed descriptions of GIS, RS, Landsat, SRTM, and MOLUSCE specifications to the methodology section while retaining a brief summary in the introduction to highlight the innovative technology and its relevance to addressing our research problem.

Comments 9:  Introduction:   Lines 133-167: This paragraph should be included in the study area section.

Response 9: Thank you for your astute observation regarding the placement of the study area description. We fully agree with your suggestion that this detailed characterization of Karachi's geographical and environmental context would be more appropriately positioned within the study area section. We have already implemented this change by relocating the entire description (Lines 133-167) to Section 2.1 (Study Area), where it now provides a more coherent and contextually appropriate overview of Karachi's urban characteristics, environmental challenges, and development patterns.

Comments 10:  Introduction: Lines 112-113: Lines 145-167: This part should include in last paragraph of Introduction section.

Response 10: Thank you for your constructive feedback regarding the structure of our introduction. We appreciate your attention to detail and agree that the organization of the final paragraphs could be improved. In response to your comment, we have revised the concluding section of the introduction to incorporate the key elements you highlighted. The restructured final paragraph now reads as follows: “This study addresses existing research gaps through an innovative methodological framework that integrates these geospatial approaches with advanced Modules for Land Use Change Evaluation (MOLUSCE) modeling techniques and hydrological simulations. The integration of these diverse analytical methods represents a substantial advancement in predicting environmental degradation and mitigating flood risks in urban environments. Our methodological framework uniquely quantifies the intricate relationships between urban expansion, environmental degradation, and Sustainable Development Goal (SDG) achievement potential in coastal megacities. This research focuses on Karachi, Pakistan, a rapidly expanding coastal megacity facing significant environmental challenges due to unplanned urbanization and climate change impacts. Karachi serves as an ideal case study, exemplifying the complex inter-play between urban growth and environmental degradation in stressed coastal regions.

The research aims to:

1. Monitor spatiotemporal LULC changes from 1990 to 2020 to identify primary drivers of land change and associated natural resource degradation.
2. Predict potential LULC alterations for 2025, 2030, and 2035.
3. Investigate shifts in stream channels for the Malir River Basin from 1990 to 2020 to inform hydrological stress prioritization strategies.
4. Simulate flood inundation scenarios for the 2020 torrential rain event using contemporary LULC data and projected maps for 2025–2035.
5. Explore the contributions of the integrated approach outputs to potential positive and negative impacts on SDGs.

This research plays a pivotal role in advancing land management practices in Kara-chi through systematic monitoring and prediction of LULC changes, encompassing historical analysis, future projections, and flood scenario simulations. Ultimately, this study aims to support informed decision-making processes and promote sustainable development by providing valuable insights for urban planners, policymakers, and environmental managers in Karachi and similar rapidly urbanizing regions, thus contributing to the development of more resilient and sustainable urban environments.”

 

Comments 11:  Introduction: Totally the introduction section needs significant enhancement.

Response 11: Thank you for your valuable assessment regarding the need for significant enhancement of the introduction section. We appreciate your thorough review and have comprehensively addressed all previous comments to improve the introduction's structure and clarity. The revisions include refined definitions of megacities, clearer articulation of research gaps, proper attribution of sources, and better organization of content, with technical details moved to appropriate sections. These changes have strengthened the logical flow of ideas while maintaining scientific rigor, providing a more robust foundation for our research presentation.

Comments 12:  Materials and Methods:  Lines 204-206: Why the time intervals are uneven? Why have you selected these times?

Response 12: Thank you for your insightful feedback. The time intervals selected for this study (1990, 1995, 2000, 2010, 2015, and 2020) were chosen to capture the dynamics of land-use change over time and to identify the key drivers of these shifts. Such five- to ten-year intervals are commonly employed in land-use research to detect significant changes. Data from 2005 and 2007 were excluded due to scan line errors in the Landsat images. While these errors could be corrected, their presence could introduce uncertainties that might compromise the reliability of the results. By excluding these years, we ensure the analysis remains accurate and consistent, minimizing potential concerns related to data interpretation. For further details, please refer to lines 245-255.

Comments 13:  Materials and Methods: I can’t see Implementation phase in your figure 2.

Response 13: Thank you for this valuable comment regarding Figure 2. Based on this constructive feedback, we have thoroughly redesigned Figure 2 to explicitly illustrate the Implementation phase and its integration within the overall workflow. The revised figure now presents a more comprehensive and clearer visualization of our methodological framework. We sincerely hope that this updated workflow diagram meets the expected standards of clarity and thoroughness. We remain open to any additional suggestions for further enhancement.

Comments 14:  Materials and Methods: The MOLUSCE can’t accept other driving factors for land use change? For example, distance to business centers may drive land use change, so can a modeler use this factor in MOLUSCE?

Response 14: Thank you for your insightful feedback. We have added a section on research limitations and future work to the manuscript, as outlined in lines 785-807. Although MOLUSCE can accommodate additional driving factors for land use change, such as distance to business centers, incorporating too many variables may lead to overfitting or unnecessary complexity, potentially compromising the reliability of the model’s predictions. To maintain the model’s focus and manageability, we chose to exclude factors like distance to business centers. This decision is based on the fact that the influence of business centers on land use is often indirectly captured by other variables already included in the model. For example, the distance to the road network and urbanization factors can inherently reflect some of the economic impacts associated with business centers, as the road network is a key indicator of economic development.

Comments 15:  Materials and Methods:  I can’t see the name of validation metrics in Figure 2.

Response 15: We have thoroughly redesigned Figure 2 to clearly depict the Implementation phase and its integration within the overall workflow.

 

Comments 16:  Materials and Methods: Lines 112-113: Again Kappa is not suitable metric to evaluate the performance of land use change models. Please use suitable metrics as I mentioned in my comments at Abstract.

Response 16: Thank you for your valuable feedback. A confusion matrix was utilized and included in the supplementary materials. Random sampling was systematically applied across various land-use categories to validate the LULC maps using performance metrics, including Kappa, overall accuracy, producer accuracy, and user accuracy (refer to lines 321–332 and 418–422). The MOLUSCE plugin was employed to implement the Kappa validation technique for evaluating multiple spatial variable combinations, following previous studies such as Muhammad et al. (2022) and Bol and Randhir (2024). This approach provides insights into the relative significance of these variables in predicting LULC changes, as detailed in Table 5. By adopting this methodology, we ensured a robust assessment of the model’s performance across different contexts while minimizing potential biases (see lines 351–360).

Comments 17:  Results:  The results were well-presented, but lacked adequate validation.

Response 17: Thank you for your constructive feedback. A confusion matrix was utilized and is included in the supplementary materials, using 20% of ROI points from various land-use categories to validate the LULC maps. Performance metrics, including Kappa, overall accuracy, producer accuracy, and user accuracy, were employed for this validation (refer to lines 321–332 and 417–420). The MOLUSCE plugin was used to implement the Kappa validation technique, evaluating multiple spatial variable combinations as demonstrated in previous studies (e.g., Muhammad et al., 2022; Bol and Randhir, 2024). This approach highlights the relative importance of these variables in predicting LULC changes, as summarized in Table 5. By adopting this methodology, we ensured a comprehensive and unbiased assessment of the model’s performance across various contexts (see lines 351–360).

Additionally, field observations in the Malir River watershed were conducted to validate a 30-year shift in the river's course from 1990 to 2020. These observations reveal the effects of LULC changes, including significant erosion and conversion to barelands, and the subsequent impact of this shift on flood extent.

Comments 18:  Discussion: The discussion section has been written well. But I would like to see some specific challenges like imbalance problem in land use change modeling. Can your proposed model handle imbalance problem of land use change data? You can refer to below recently published papers: 1. Ahmadlou, Mohammad, Mohammad Karimi, and Nadhir Al-Ansari. "The use of maximum entropy and ecological niche factor analysis to decrease uncertainties in samples for urban gain models." GIScience & Remote Sensing 60.1 (2023): 2222980. 2. Ahmadlou, Mohammad, Mohammad Karimi, and Robert Gilmore Pontius Jr. "A new framework to deal with the class imbalance problem in urban gain modeling based on clustering and ensemble models." Geocarto International 37.19 (2022): 5669-5692. 3. Ahmadlou, Mohammad, et al. "Three novel cost-sensitive machine learning models for urban growth modelling." Geocarto International 39.1 (2024): 2353252.

Response 17: Thank you for your constructive feedback and for highlighting the need to address specific challenges, such as the imbalance problem in land-use change modeling. We have expanded Section “4.4. Research Limitations and Future Directions” to include a detailed discussion on this issue and its implications for land-use change modeling and flood risk assessment.

 

This study acknowledges several methodological and data-related limitations. A critical challenge is the imbalance in class distribution, which can impact the reliability of predictions and model robustness. Although the ANN-based CA-Markov approach employed in this study demonstrated reliable outcomes with a high Kappa statistic, it faced difficulties in fully capturing the impact of sudden policy changes, economic shocks, or extreme events that could significantly alter land-use patterns. Additionally, the inclusion of excessive variables was avoided to mitigate the risks of overfitting and unnecessary complexity, which can also affect the predictive accuracy of land-use models. To address the imbalance issue, future research will prioritize integrating advanced machine learning techniques specifically designed to handle class imbalance in land-use/land-cover (LULC) data, as highlighted in recent studies (e.g., Hewitt et al., 2022; Ahmadlou et al., 2023). Moreover, incorporating higher temporal resolution imagery and comprehensive validation metrics beyond the Kappa index, coupled with real-time monitoring systems, could further enhance the accuracy of LULC classification and flood risk predictions..

Response to Comments on the Quality of English Language.

Point 1: The English could be improved to more clearly express the research.

Response 1:  Your constructive feedback during the major revision process has been instrumental in refining and enhancing our manuscript. We sincerely appreciate the time and effort you devoted to helping us improve our work for submission to the ISPRS International Journal of Geo-Information.".

Reviewer 2 Report

Comments and Suggestions for Authors

Hello, dear authors of the Manuscript ID ijgi-3339027,

The current manuscript is well written and illustrates the ongoing and rapid urbanization in the context of coastal megacities under changing land cover conditions and associated SDGs. The comprehensive review shows some minor suggestions and comments as follows.

1. The introduction section is well written, but case building is poor. I suggest adding some recent data regarding LULC-led urbanization and its drivers. See the recent publications of http://dx.doi.org/10.3389/fevo.2023.1115074 and http://dx.doi.org/10.1016/j.eiar.2023.107396. These studies will also be added to the discussion sections. If possible, include the discussion section by adding more recent literature.

2. Figures 1 need some clarification. Use only solid lines, not dashed ones. Also, download the most recent geopolitical boundary data from the official sources. Ensure all the legends are clear and the text and symbology in the figures are readable.

3. Add references where needed in the last section of the discussion while discussing the SDGs. 

Best Regards

Author Response

Response to Reviewer 2

General Comments: Hello, dear authors of the Manuscript ID ijgi-3339027.

The current manuscript is well written and illustrates the ongoing and rapid urbanization in the context of coastal megacities under changing land cover conditions and associated SDGs. The comprehensive review shows some minor suggestions and comments as follows:

Comments 1: The introduction section is well written, but case building is poor. I suggest adding some recent data regarding LULC-led urbanization and its drivers. See the recent publications of http://dx.doi.org/10.3389/fevo.2023.1115074 and http://dx.doi.org/10.1016/j.eiar.2023.107396. These studies will also be added to the discussion sections. If possible, include the discussion section by adding more recent literature.

Response 1: We sincerely thank you for your constructive feedback regarding the introduction section. Following your valuable suggestion, we have substantially enhanced both the introduction and discussion sections by incorporating the recommended recent publications (Waleed et al., 2023; Mehmood et al., 2023) along with additional contemporary literature. The revised manuscript now includes more recent data regarding LULC-led urbanization and its drivers, providing stronger case building and a more comprehensive theoretical foundation. The discussion section has also been enriched with current literature to better contextualize our findings within the latest research developments in this field. These additions have significantly strengthened our argument about the significance of LULC changes in urban contexts and their environmental implications in Pakistan.

Comments 2:   Figures 1 need some clarification. Use only solid lines, not dashed ones. Also, download the most recent geopolitical boundary data from the official sources. Ensure all the legends are clear and the text and symbology in the figures are readable.

Response 2: "We have revised Figure 1 by incorporating clearer symbols and improved color schemes to enhance readability and accuracy.

Comments 3:   Add references where needed in the last section of the discussion while discussing the SDGs.

Response 3: Thank you for your careful attention to the discussion section and the valuable suggestion regarding SDG references. We have thoroughly revised the last section of the discussion to include appropriate citations that support our analysis of SDG achievements. Each SDG discussion point is now backed by relevant contemporary literature that demonstrates the linkages between urban development, environmental changes, and sustainable development goals. This addition strengthens the scientific foundation of our SDG analysis and provides readers with access to further research on specific SDG implementation challenges and opportunities in rapidly urbanizing regions.

Response to Comments on the Quality of English Language.

Point 1: The quality of English does not limit my understanding of the research..

Response 1:  Your constructive feedback during the major revision process has been invaluable. We sincerely appreciate the time and effort you dedicated to helping us improve our work for submission to the ISPRS International Journal of Geo-Information.

 

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript research investigated the impact of rapid urbanisation and climate change in Karachi, Pakistan, on the environment using GIS tools and complex statistical analysis. According to the results, the area of the city increased significantly, while vegetation and water surface decreased, which increased the risk of flooding. The manuscript points out that sustainable urban planning is key for cities facing similar problems.

 

The choice of topic of the manuscript is actual and relevant, and the complex research approach and applied research methods should be appreciated, I think. However, I think the manuscript needs major changes on some points.

 

The manuscript currently contains hardly any research limitation notes (see my three detailed remarks below). These need to be written briefly at the end of the manuscript and mentioned in more detail in earlier parts of the manuscript.

 

The time horizon of manuscript research spans three decades, but collecting data at five-year intervals may omit some potential important intermediate changes. For this reason, it would be worthwhile for the authors to investigate, or at least address, the problem of how denser temporal sampling would affect the results.

 

The accuracy and reliability of satellite images and other spatial data used by the authors for complex statistical analysis are important from a scientific point of view. For this reason, authors should analyse in more detail how accurate the data they use are and what the margins of error are, as the accuracy and reliability of data from different sources and available may vary. For example, combining World Bank and OSM data and validating it using Google Earth may not produce fully accurate maps.

 

The details of the validation process used by the authors and the reliability of their methods used are important factors from a scientific point of view. Therefore, it would be useful for the authors to analyse in more detail how representative their validation is and what alternative validation techniques may be used, I suggest.

 

 

The manuscript maps themselves are basically high-quality, but they have a low resolution, which makes them difficult to interpret. This should be improved.

Author Response

Response to Reviewer 3

General Comments: The manuscript research investigated the impact of rapid urbanisation and climate change in Karachi, Pakistan, on the environment using GIS tools and complex statistical analysis. According to the results, the area of the city increased significantly, while vegetation and water surface decreased, which increased the risk of flooding. The manuscript points out that sustainable urban planning is key for cities facing similar problems.

The choice of topic of the manuscript is actual and relevant, and the complex research approach and applied research methods should be appreciated, I think. However, I think the manuscript needs major changes on some points

Comments 1: The manuscript currently contains hardly any research limitation notes (see my three detailed remarks below). These need to be written briefly at the end of the manuscript and mentioned in more detail in earlier parts of the manuscript.

Response 1: Thank you for this important observation regarding research limitations. Following this valuable suggestion, a comprehensive new section titled "Research Limitations and Future Directions" has been added to the manuscript. This section thoroughly addresses the methodological constraints, data uncertainties, land use changes imbalance, and analytical challenges encountered during the research process. The discussion encompasses limitations related to data accuracy, temporal resolution of satellite imagery, uncertainties in land use classification, and challenges in validation processes. Additionally, relevant aspects of these limitations have been integrated within earlier sections of the manuscript where appropriate, providing readers with important context for interpreting the results. The section also outlines future research directions that could address these limitations, including recommendations for improved data collection methods, advanced modeling techniques, and potential integration of additional environmental parameters.

Comments 2:  The time horizon of manuscript research spans three decades, but collecting data at five-year intervals may omit some potential important intermediate changes. For this reason, it would be worthwhile for the authors to investigate, or at least address, the problem of how denser temporal sampling would affect the results.

Response 2: Thank you for your insightful feedback. The time intervals selected for this study (1990, 1995, 2000, 2010, 2015, and 2020) were chosen to capture the dynamics of land-use change over time and to identify the key drivers of these shifts. Such five- to ten-year intervals are commonly employed in land-use research to detect significant changes. Data from 2005 and 2007 were excluded due to scan line errors in the Landsat images. While these errors could be corrected, their presence could introduce uncertainties that might compromise the reliability of the results. By excluding these years, we ensure the analysis remains accurate and consistent, minimizing potential concerns related to data interpretation. For further details, please refer to lines 245-255.

Comments 3: The accuracy and reliability of satellite images and other spatial data used by the authors for complex statistical analysis are important from a scientific point of view. For this reason, authors should analyse in more detail how accurate the data they use are and what the margins of error are, as the accuracy and reliability of data from different sources and available may vary. For example, combining World Bank and OSM data and validating it using Google Earth may not produce fully accurate maps.

Response 3: Thank you for your valuable feedback. To minimize any differences and evaluate the degree of agreement across the various data sources, we specifically used kappa statistics to validate the data. We were able to measure the precision of our land use classification using this statistical technique, as well as the degree of agreement between the satellite imagery, World Bank, OSM data, and Google Earth validation. We also compared our findings with previously published research that classified land use and performed spatial analysis using comparable data sources. By confirming that our results are consistent with previous studies, this comparison gave us an additional degree of validation and assisted us in confirming the accuracy of our findings.

Comments 4: The details of the validation process used by the authors and the reliability of their methods used are important factors from a scientific point of view. Therefore, it would be useful for the authors to analyse in more detail how representative their validation is and what alternative validation techniques may be used, I suggest.

Response 4: Thank you for your valuable feedback. A confusion matrix was utilized and included in the supplementary materials. Random sampling was systematically applied across various land-use categories to validate the LULC maps using performance metrics, including Kappa, overall accuracy, producer accuracy, and user accuracy (refer to lines 321–332 and 417–420). The MOLUSCE plugin was employed to implement the Kappa validation technique for evaluating multiple spatial variable combinations, following previous studies such as Muhammad et al. (2022) and Bol and Randhir (2024). This approach provides insights into the relative significance of these variables in predicting LULC changes, as detailed in Table 5. By adopting this methodology, we ensured a robust assessment of the model’s performance across different contexts while minimizing potential biases (see lines 351–360).

Comments 5: The manuscript maps themselves are basically high-quality, but they have a low resolution, which makes them difficult to interpret. This should be improved

Response 5: We have revised all Figures by incorporating clearer symbols and improved color schemes to enhance readability and accuracy.

Response to Comments on the Quality of English Language.

Point 1: The quality of English does not limit my understanding of the research.

Response 1:  We sincerely appreciate the time and effort you dedicated to helping us improve our work for submission to the ISPRS International Journal of Geo-Information.

 

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I believe the authors have addressed all of my comments. The paper is now suitable for publication.

Author Response

General Comments : I believe the authors have addressed all of my comments. The paper is now suitable for publication.

Response 17: Your constructive feedback during the major revision process has been instrumental in refining and enhancing our manuscript. We sincerely appreciate the time and effort you devoted to helping us improve our work for submission to the ISPRS International Journal of Geo-Information..

Response to Comments on the Quality of English Language.

Point 1: The quality of English does not limit my understanding of the research..

Response 1:  We sincerely appreciate the time and effort you devoted to helping us improve our work for submission to the ISPRS International Journal of Geo-Information.

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript has been improved. I consider minor changes in content and form to be necessary.

 

Concerning my previously mentioned time-interval sampling density aspect, I think that the authors do not mention potential alternative ways to reduce related data loss over time (e.g. interpolation, or possibly including other datasets if such datasets exist).

 

The "Research Limitations and Future Directions" section still does not cover enough methodological limitations and uncertainties in the results. For example, the sensitivity of models to input variables is not discussed. In this context, I suggest that the authors need to address here a little more the uncertainty arising from the sources of the data they select, such as the accuracy of the combination of World Bank and OSM data.

 

I suppose that the "Research Limitations and Future Directions" section contains somewhat general proposals, but more specific proposals should be made instead. And the authors could elaborate a little more on how the results could be applied more directly to city management or policymaking.

 

The manuscript maps still have a low resolution, which makes them difficult to interpret. This should be further improved.

Author Response

Response to Reviewer 3

General Comments: The manuscript has been improved. I consider minor changes in content and form to be necessary.

Comments 1: Concerning my previously mentioned time-interval sampling density aspect, I think that the authors do not mention potential alternative ways to reduce related data loss over time (e.g. interpolation, or possibly including other datasets if such datasets exist).

Response 1: Thank you for this important observation regarding temporal sampling density. We have addressed this limitation in the "Research Limitations and Future Directions" section by explicitly discussing the potential use of interpolation techniques and complementary datasets to reduce temporal data loss. The revised section now includes specific recommendations for future research to implement higher temporal resolution analysis methods while acknowledging current methodological constraints.

Comments 2:  The "Research Limitations and Future Directions" section still does not cover enough methodological limitations and uncertainties in the results. For example, the sensitivity of models to input variables is not discussed. In this context, I suggest that the authors need to address here a little more the uncertainty arising from the sources of the data they select, such as the accuracy of the combination of World Bank and OSM data.

Response 2: Thank you for this important observation regarding methodological limitations and uncertainties. We have significantly expanded our discussion of model sensitivity and data uncertainties in the "Research Limitations and Future Directions" section. Specifically, While detailed uncertainty quantification was beyond the scope of this study, these findings lay the groundwork for refining sensitivity analyses in future research. The integration of World Bank road network data with OpenStreetMap (OSM) data introduced additional uncertainties due to discrepancies in temporal and spatial resolutions, despite validation efforts using Google Earth's time series engine. Moreover, differences in spatial resolutions between Landsat imagery (30 m) and OSM data introduced scaling uncertainties, particularly in rapidly changing urban fringe areas. These factors highlight the need for enhanced data harmonization and sensitivity analyses in future studies to improve the accuracy of LULC change and flood risk assessments. These additions provide a more comprehensive and transparent assessment of our methodology's limitations and their potential impacts on our results.

Comments 3: I suppose that the "Research Limitations and Future Directions" section contains somewhat general proposals, but more specific proposals should be made instead. And the authors could elaborate a little more on how the results could be applied more directly to city management or policymaking.

Response 3: Thank you for your constructive feedback regarding the need for more specific proposals and practical applications. We have substantially restructured the "Research Limitations and Future Directions" section to present clear, actionable recommendations organized into distinct categories: research approaches, implementation priorities, and policy recommendations. This revised structure provides a more systematic framework for translating our research findings into practical urban management applications.

Comments 4: The manuscript maps still have a low resolution, which makes them difficult to interpret. This should be further improved.

Response 4: Thank you for your valuable feedback. We have revised the majority of low-quality figures to improve their clarity and readability.

Response to Comments on the Quality of English Language.

Point 1: The quality of English does not limit my understanding of the research..

Response 1:  We sincerely appreciate the time and effort you dedicated to helping us improve our work for submission to the ISPRS International Journal of Geo-Information.