Unlocking Solar Potential: Geospatial Mapping of Building-Level Photovoltaic Opportunities in Northern Khyber Pakhtunkhwa’s Tourism Districts, Pakistan

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Authors,

thank you for revising the paper. Most of the issues mentioned in the first round of review have been resolved to a satisfactory level. Some questions remain:

• Is the threshold of 750 kWh appropriate for all building sizes, or just for the smaller ones? Maybe the threshold for bigger ones also needs to be bigger.
• Color labeling in the discussion of Figure 2 is very unusual. For one color two labels are given, e.g. blackberry=deep purple, lilac dust=pale lilac... This is obsolete and confusing.
• Since you propose new methodology in this manuscript, it would be good to verify it. For example compare it with an existing methods to evaluate the solar potential of a region, or prove it reliability by conducting a micro analysis on several buildings. I believe that this would significantly improve the value of the paper.

 

Author Response

Comment 1: Is the threshold of 750 kWh appropriate for all building sizes, or just for the smaller ones? Maybe the threshold for bigger ones also needs to be bigger.

Response 1: We thank the reviewer for this thoughtful and important comment regarding the suitability threshold of 750 kWh/year and its applicability across different building sizes. The 750 kWh threshold was intentionally selected as a minimum viability benchmark rather than as a size-dependent optimization threshold to identify buildings with sufficient solar potential to support economically viable rooftop PV systems, particularly for small- to medium-sized residences, which comprise the majority of the buildings in the study area. While large buildings could generate proportionally more electricity, we maintained a single threshold for analytical simplicity and relative prioritization at the community level. The manuscript clarifies that this threshold is intended to guide policy and planning decisions rather than precise system sizing for all building types.

Because the study is designed as a regional-scale planning and prioritization framework, a uniform threshold ensures comparability across 1.29 million buildings and supports aggregation at the Union Council (UC) level. We have clarified this rationale in Section 2.3 of the revised manuscript and noted that alternative size-dependent thresholds could be explored in future policy-focused or engineering studies.

Comment 2: Colour labelling in the discussion of Figure 2 is very unusual. For one color two labels are given, e.g. blackberry=deep purple, lilac dust=pale lilac... This is obsolete and confusing.

Response 2: We thank the reviewer for this observation. While the figure itself remains unchanged, we have updated the figure description and legend to clarify the color scheme. Each color now corresponds to a single class in a bivariate diverging ramp; shares of purple indicate below-average solar potential (classes 1 -3), light yellow indicates near-average values (class 4) and shared of green indicate above-average potential (classes 5 -6). The percentage of suitable buildings and the number of union councils per class are now provided. This revision eliminates previous duplicates or ambiguous color labels and ensures that readers can clearly interpret areas of low, moderate, and high rooftop solar potential.

Comment 3: Since you propose a new methodology in this manuscript, it would be good to verify it. For example, compare it with an existing methods to evaluate the solar potential of a region, or prove it reliability by conducting a micro analysis on several buildings. I believe that this would significantly improve the value of the paper.

Response 3: We thank the reviewer for this constructive suggestion. We acknowledge the importance of methodological verification. The current study is designed as a scalable, planning-oriented approach using open-data driven framework for large-area prioritization in data-constrained environments, rather than high-precision rooftop engineering estimation. Due to the absence of high-resolution LiDAR/DSM data and building-specific height information for the full study region, a direct micro-level validation against detailed rooftop models was not feasible. Additionally, detailed building-level validation (e.g., using LiDAR or on-site PV measurements) is beyond the scope of this paper. However, we have clarified in the manuscript that the methodology allows for future validation and refinement, including comparisons with local PV installations or higher-resolution DSM data when available. This ensures that the outputs remain robust for policy prioritization and community-level planning.

We appreciate this suggestion, which has helped us better articulate the scope and validation context of the proposed methodology.

Reviewer 2 Report

Comments and Suggestions for Authors

Some comments here:
(1) The study relies on several strong simplifying assumptions, most notably the uniform 5 m building height adjustment, constant 30° tilt angle, and clear-sky solar radiation modeling, yet their cumulative impact on estimation uncertainty is not sufficiently quantified. While these assumptions are acknowledged as limitations, their implications for result robustness remain unclear. Therefore, please explicitly evaluate and discuss uncertainty propagation. A sensitivity analysis or a quantitative comparison among all the factors is needed.

(2) Although the paper positions itself as a scalable, open-data alternative to LiDAR-based rooftop PV studies, there is limited empirical validation of the results. The absence of benchmarking against existing high-resolution case studies or observed PV installations weakens confidence in the accuracy of the estimates. The authors should include a validation exercise, such as comparing results for a selected sub-area with published LiDAR- or DSM-based studies, cross-checking estimated generation ranges with installed PV systems reported in Pakistan, or validating aggregate outputs against national or provincial solar potential statistics. This would help contextualize accuracy while preserving the study’s large-scale scope.

(3) The manuscript presents a technically sound workflow but currently under-articulates its conceptual contribution to geospatial science. The UC-level prioritization framework is described operationally, yet its novelty relative to existing spatial aggregation or multi-scale planning approaches is not clearly theorized. Please strengthen the conceptual framing by explicitly positioning the UC-level analysis as a planning-oriented spatial abstraction layer. Also, please clarify how this framework bridges technical modeling and governance decision-making within GIS-based energy planning.

Author Response

Comment 1: The study relies on several strong simplifying assumptions, most notably the uniform 5 m building height adjustment, constant 30° tilt angle, and clear-sky solar radiation modeling, yet their cumulative impact on estimation uncertainty is not sufficiently quantified. While these assumptions are acknowledged as limitations, their implications for result robustness remain unclear. Therefore, please explicitly evaluate and discuss uncertainty propagation. A sensitivity analysis or a quantitative comparison among all the factors is needed.

Response 1: We thank the reviewer for highlighting this important and technically valuable point. The methodological assumptions (uniform 5 m height adjustment, constant 30° tilt angle, and clear-sky radiation modelling) were adopted to ensure computational feasibility and regional scalability across more than 1.29 million buildings in a data-constrained environment, ensuring that the relative comparison between buildings and union councils remains robust.

Additionally, because high-resolution data on building heights and rooftop geometries are unavailable for the entire region, a full quantitative sensitivity simulation was not feasible at this scale. However, based on established solar modelling literature¹, the expected magnitude of variation from the assumed height and tilt parameters is moderate relative to spatial variability in radiation driven by terrain and location. We have added it to the limitations section with a reference. We have also clarified in Geospatial Methods that results are intended for policy prioritization and planning purposes rather than precise engineering design, and that the workflow provides a reproducible and transparent approach suitable for large-scale geospatial analysis. Future studies may refine estimates through locally validated building heights, PV orientations, and weather-adjusted solar radiation.

¹Issaq SZ, Talal SK, Azooz AA. Empirical modeling of optimum tilt angle for flat solar collectors and PV panels. Environ Sci Pollut Res Int. 2023 Jul;30(33):81250-81266. doi: 10.1007/s11356-023-28142-3. Epub 2023 Jun 14. PMID: 37314555.

Comment 2: Although the paper positions itself as a scalable, open-data alternative to LiDAR-based rooftop PV studies, there is limited empirical validation of the results. The absence of benchmarking against existing high-resolution case studies or observed PV installations weakens confidence in the accuracy of the estimates. The authors should include a validation exercise, such as comparing results for a selected sub-area with published LiDAR- or DSM-based studies, cross-checking estimated generation ranges with installed PV systems reported in Pakistan, or validating aggregate outputs against national or provincial solar potential statistics. This would help contextualize accuracy while preserving the study’s large-scale scope.

 Response 2: We sincerely thank the reviewer for this important and constructive comment. We agree that contextual validation strengthens methodological credibility. The primary objective of this study is to develop a scalable, open-data-based prioritization framework applicable to large, data-constrained regions, rather than to produce engineering-grade rooftop yield estimates. Unfortunately, high-resolution LiDAR/DSM datasets and detailed rooftop PV installation records are not publicly available for the nine-district study area, which limits the feasibility of direct building-level benchmarking. We clarified in the Methods and Limitations sections that the estimates represent relative solar potential suitable for UC-level planning. Additionally, aggregate solar generation estimates were cross-checked against provincial and national solar statistics, confirming their plausibility and consistency with expected regional values. The workflow also allows for future validation at sub-area or building-level scales when local PV installation or high-resolution DSM/LiDAR data becomes available.

Comment 3: The manuscript presents a technically sound workflow but currently under-articulates its conceptual contribution to geospatial science. The UC-level prioritization framework is described operationally, yet its novelty relative to existing spatial aggregation or multi-scale planning approaches is not clearly theorized. Please strengthen the conceptual framing by explicitly positioning the UC-level analysis as a planning-oriented spatial abstraction layer. Also, please clarify how this framework bridges technical modeling and governance decision-making within GIS-based energy planning.

Response 3: We sincerely thank the reviewer for highlighting the need to clarify the conceptual contribution of our work. In the revised manuscript, we have strengthened the theoretical framing by emphasizing the planning-oriented nature of the union council aggregation. As a result, a spatial abstraction layer was introduced that facilitates community-level prioritization of rooftop PV interventions.  While building-level solar modelling provides high-resolution technical outputs, such granularity is often misaligned with the administrative units through which energy policy, budgeting, and implementation decisions are made. By linking technical modelling outputs to governance and policy decision-making, the framework provides actionable insights for energy planning and resource allocation across administrative units.

Reviewer 3 Report

Comments and Suggestions for Authors

Dear Authors,

 

I have carefully read the manuscript entitled "Unlocking Solar Potential: Geospatial Mapping of Building-Level Photovoltaic Opportunities in Northern Khyber Pakhtunkhwa’s Tourism Districts, Pakistan". This document tackles a pertinent issue and is clearly written; however, it suffers from a fundamental methodological limitation that compromises its scientific validity.

The study asserts that it performs a building-level assessment of rooftop solar potential, but it is based on a 30 m DEM and a synthetic DSM generated by uniformly adding 5 m to building pixels. At this spatial resolution, many rooftops are smaller than a single pixel, making it difficult to estimate solar radiation at the building level and leading to unreliable power generation.  and unreliable power generation. Accordingly, the results and conclusions drawn are not supported by adequate data for the intended scale of analysis.

Despite the effort and clear presentation, this discrepancy represents a critical flaw, and I therefore recommend that the paper be rejected.

 

Kind regards.

Author Response

Comment 1: I have carefully read the manuscript entitled "Unlocking Solar Potential: Geospatial Mapping of Building-Level Photovoltaic Opportunities in Northern Khyber Pakhtunkhwa’s Tourism Districts, Pakistan". This document tackles a pertinent issue and is clearly written; however, it suffers from a fundamental methodological limitation that compromises its scientific validity.

The study asserts that it performs a building-level assessment of rooftop solar potential, but it is based on a 30 m DEM and a synthetic DSM generated by uniformly adding 5 m to building pixels. At this spatial resolution, many rooftops are smaller than a single pixel, making it difficult to estimate solar radiation at the building level and leading to unreliable power generation.  and unreliable power generation. Accordingly, the results and conclusions drawn are not supported by adequate data for the intended scale of analysis.

Despite the effort and clear presentation, this discrepancy represents a critical flaw, and I therefore recommend that the paper be rejected.

Response 1:  We sincerely thank the reviewer for the careful evaluation and for raising this critical concern. We respectfully acknowledge that the study uses a 30 m DEM and a synthetic DSM generated by uniformly adding 5 m to building pixels, which limits the absolute accuracy of rooftop-level solar generation estimates. However, the primary objective of this study is to provide a relative, planning-oriented assessment of solar potential across a large geographic area, rather than precise engineering-level calculations for individual buildings. Additionally,  building-level solar modeling provides high-resolution technical outputs; such granularity is often misaligned with the administrative units through which energy policy, budgeting, and implementation decisions are made.

However, many large-area solar potential assessments globally rely on DEM resolutions of 30 m or coarser for regional screening, particularly in mountainous terrain where slope ^2,3, aspect, and topographic shading are dominant controls. The study’s conclusions are drawn at the Union Council and district scale, where aggregation reduces pixel-level noise and improves robustness.

To address the limitations of the DEM, we applied a fishnet-based allocation method to proportionally assign solar radiation values to building footprints based on the area of intersecting pixels. This approach ensures that while absolute electricity generation values may be influenced by pixel size, building height assumptions and clear-sky conditions, the relative prioritization of building and union councils remains robust.

As described in the Geospatial Methods and in the limitations section (under discussion), the synthetic DSM reflects the predominantly single-story residential structures in northern Khyber Pakhtunkhwa, with a conservative 5 m adjustment to capture rooftop height and minor structural variability. The resulting estimates are intended to inform community-level planning and policy prioritization, rather than detailed system sizing or engineering design.

We believe that with these clarifications, the manuscript now more clearly positions its methodology as a large-scale open-data geospatial assessment framework, bridging technical solar modeling and governance decision-making while transparently acknowledging data and resolution limitations. We respectfully submit that the perceived discrepancy stems primarily from differences in scale interpretation rather than methodological invalidity, and the revised manuscript now explicitly aligns its objectives, methods, and conclusions with the intended regional planning scope. We sincerely appreciate the reviewer’s candid and constructive feedback, which has substantially improved the clarity, conceptual positioning, and scientific rigor of the study.

²M. Šúri, T.A. Huld, E.D. Dunlop, H.A. Ossenbrink, Potential of solar electricity generation in the european union member states and candidate countries, Sol Energy, 81 (10) (2007), pp. 1295-1305

³Ruiz‐Arias, J. A., Tovar‐Pescador, J., Pozo‐Vázquez, D., & Alsamamra, H. (2009). A comparative analysis of DEM‐based models to estimate the solar radiation in mountainous terrain. International Journal of Geographical Information Science, 23(8), 1049–1076. https://doi.org/10.1080/13658810802022806

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Authors,

thank you for providing the revised version of the manuscript. It has now been improved in certain aspects. However, the core issue and my main concern remain. Since you use a methodology that has not been used in other studies, some type of verification is needed. I proposed that you verify it by comparing the results of your analysis with results of already established method, but you state that this would not be appropriate. I respect that, nevertheless, in that case you need to provide some other proof that verifies that the results you obtained are correct. 

Author Response

We thank the reviewer for this important and constructive comment and fully agree that some form of validation is necessary to support confidence in the proposed methodology.

Given the absence of directly comparable large-scale studies in the same geographic and data context, we have incorporated indirect verification and consistency checks to verify the robustness of our results:

1. Consistency with established solar radiation ranges

Our results are consistent with the established solar ranges from global and regional datasets, including the World Bank Global Solar Atlas (Aqsa et al., 2024; ESMAP, 2020; M. Khan et al., 2024). These sources report average Global Horizontal Irradiance (GHI) values of approximately 1640–2000 kWh/m²/year for Northern Pakistan. The mean solar radiation obtained in our study (~1700–1900 kWh/m²/year) falls within this range, with differences generally within ±10–15%, consistent with regional-scale solar assessments. Published studies indicate that Pakistan lies within a high solar insolation belt (~1600–2100 kWh/m²/year), with site-specific estimates (e.g., Multan, ~30°N) around 1860 kWh/m²/year (ESMAP, 2020; Khan, Ahmad, Tariq, Anjum, & Shafi, 2024).

2. Comparison with regional GIS-based studies

Previous research using PVGIS-based modeling in Khyber Pakhtunkhwa (the same province as our study area) reports comparable magnitudes of solar irradiation and PV potential (Tajbar et al., 2020). This provides additional confidence that our results are consistent not only with global datasets but also within the same regional and climatic context.

3. Methodological grounding and consistency checks

To assess the robustness and reliability of the estimated solar radiation outputs, a verification and consistency assessment approach was applied. The solar radiation estimates are based on the Area Solar Radiation algorithm (Fu & Rich, 2002), which is widely used in GIS -based analyses. Internal consistency checks were conducted to en-sure spatial patterns followed expected physical principles, such as values in valleys and higher values in elevated, unobstructed areas, Estimated Global Horizontal Irradiance (GHI) values were also compared with published datasets and studies, including the Global Solar Atlas and related literature ((Aqsa et al., 2024; ESMAP, 2020; M. Khan et al., 2024), and results were further assessed against independent studies using alternative approaches, such as PVGIS-based estimates in similar regions (Tajbar, Rafiq, Bıbı, & Saıdullah, 2020). This multi-level approach is appropriate for regional-scale assessments where ground-based validation data are not available.

In response to this comment, we have:

• Added a Verification and Consistency Checks paragraph in the Methods Section and also referred to in the Discussion section, describing these consistency checks with citations.
• Added the paragraph (second) in the Discussion section, providing consistency with established solar radiation ranges with citations.
• Added the Methodological grounding and scope in the Limitations section with citations.
• Included citations to established literature and regional studies.

These additions demonstrate that the modeled solar potential values are consistent with established datasets, regional studies, and physical expectations, thereby providing reasonable and scientifically grounded verification of the methodology within the scope of this research.

Reviewer 2 Report

Comments and Suggestions for Authors

I think the authors have addressed all my concerns.

Author Response

We sincerely thank the reviewers for their time, constructive feedback, and thoughtful suggestions throughout the review process. Their comments have significantly helped us improve the clarity, rigour, and overall quality of the manuscript. We  appreciate their support and are glad that the revisions have addressed their concerns.

Reviewer 3 Report

Comments and Suggestions for Authors

Dear authors,

 

I think you have conducted some critical issues and clarified some points. Thus, I consider the paper is ready to be accepted.

 

Kind regards.

Author Response

We sincerely thank the reviewers for their time, constructive feedback, and thoughtful suggestions throughout the review process. Their comments have significantly helped us improve the clarity, rigour, and overall quality of the manuscript. We  appreciate their support and are glad that the revisions have addressed their concerns.

Round 3

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Authors,

thank you for working on improving the quality of the paper. I noticed one typo in table 2.