- مراجع
[1] G. Rees, L. Hebryn-Baidy, and C. Good, Estimating the potential for rooftop generation of solar energy in an urban context using high-resolution open access geospatial data: a case study of the city of Tromsø, Norway, ISPRS International Journal of Geo-Information, Vol. 14, No. 3, pp. 123, 2025.
[2] T. Soha, V. Sugár, and B. Hartmann, City-scale analysis of PV potential and visibility in heritage environment using GIS and LiDAR, Energy and Buildings, Vol. 311, pp. 114124, 2024.
[3] N. Malijanska Andreevska, G. Gjorgjiev, and E. Bozhinov, Assessment of solar photovoltaic potential of building rooftops based on multicriteria spatial analysis, Tehnički glasnik, Vol. 18, No. si1, pp. 29-36, 2024.
[4] F. Vecchi and U. Berardi, Solar analysis for an urban context from GIS to block-scale evaluations, Energy Policy, Vol. 184, pp. 113884, 2024.
[5] R. Kassner, W. Koppe, T. Schüttenberg, and G. Bareth, Analysis of the solar potential of roofs by using official LiDAR data, in Proceedings of the International Society for Photogrammetry, Remote Sensing and Spatial Information Sciences, pp. 399-404, 2008.
[6] T. Santos, N. Gomes, M. Brito, S. Freire, A. Fonseca, and J. A. Tenedório, Solar potential analysis in Lisbon using LiDAR data, in Proceedings of the 31st EARSeL Symposium and 35th General Assembly, Remote Sensing and Geoinformation, Prague, Czech Republic: EARSeL, pp. 13-20, 2011.
[7] B. Adams, Mapping Solar Energy Potential Through LiDAR Feature Extraction, Woolpert, Dayton, OH, pp. 1-5, 2012.
[8] Y. Ko, The effect of urban trees on residential solar energy potential, Journal of the Korean Institute of Landscape Architecture, Vol. 42, No. 1, pp. 41-49, 2014.
[9] M. B. Boz, K. Calvert, and J. R. Brownson, An automated model for rooftop PV systems assessment in ArcGIS using LIDAR, AIMS Energy, Vol. 3, No. 3, pp. 401-420, 2015.
[10]S. Akbariyan, H. Arefi, S. M. Ebrahimi, and S. Rahimi, Evaluation of methods for calculating solar potential on building roof surfaces using LiDAR data, in Proceedings of the 2nd International Congress on Earth Sciences and Urban Development, Tabriz, Iran, 2016. (in Persian)
[11] P. B. Dąbek and J. Jurasz, GIS estimated potential of rooftop PVs in urban areas—case study Wrocław (Poland), in E3S Web of Conferences, Vol. 45, pp. 00014, 2018.
[12]I. Prieto, J. L. Izkara, and E. Usobiaga, The application of LiDAR data for the solar potential analysis based on urban 3D model, Remote Sensing, Vol. 11, No. 20, pp. 2348, 2019.
[13]F. Mansouri Kouhestani, J. Byrne, D. Johnson, L. Spencer, P. Hazendonk, and B. Brown, Evaluating solar energy technical and economic potential on rooftops in an urban setting: the city of Lethbridge, Canada, International Journal of Energy and Environmental Engineering, Vol. 10, pp. 13-32, 2019.
[14] Z. Zhang, T. Zhong, M. Chen, Z. Zhou, Y. Wang, and K. Zhang, Estimation of rooftop solar potential using publicly available geodata and deep learning, Proceedings of the Applied Energy Symposium 2020: Low Carbon Cities and Urban Energy Systems (CUE2020), Tokyo, Japan, pp. D128, 2020.
[15]J. E. Fuentes, F. D. Moya, and O. D. Montoya, Method for estimating solar energy potential based on photogrammetry from unmanned aerial vehicles, Electronics, Vol. 9, No. 12, pp. 2144, 2020.
[16]M. Hu, Z. Liu, Y. Huang, M. Wei, and B. Yuan, Estimation of rooftop solar photovoltaic potential based on high-resolution images and digital surface models, Buildings, Vol. 13, No. 11, pp. 2686, 2023.
[17]V. Adjiski, G. Kaplan, and S. Mijalkovski, Assessment of the solar energy potential of rooftops using LiDAR datasets and GIS based approach, International Journal of Engineering and Geosciences, Vol. 8, No. 2, pp. 188-199, 2023.
[18]M. Aslani and S. Seipel, Rooftop segmentation and optimization of photovoltaic panel layouts in digital surface models, Computers, Environment and Urban Systems, Vol. 105, pp. 102026, 2023.
[19]G. Molnár, L. F. Cabeza, S. Chatterjee, and D. Ürge-Vorsatz, Modelling the building-related photovoltaic power production potential in the light of the EU's solar rooftop initiative, Applied Energy, Vol. 360, pp. 122708, 2024.
[20]B. Gui, L. Sam, and A. Bhardwaj, From roofs to renewables: deep learning and geographic information systems insights into a comprehensive urban solar photovoltaic assessment for Stonehaven, Energy 360, Vol. 1, pp. 100006, 2024.
[21]M. Cenky, J. Bendik, P. Janiga, and I. Lazarenko, Urban-scale rooftop photovoltaic potential estimation using open-source software and public GIS datasets, Smart Cities, Vol. 7, No. 6, pp. 3962-3982, 2024.
[22] Y. Chen, Y. Liu, M. Slootweg, M. Hu, A. Tukker, and W.-Q. Chen, Unlocking rooftop potential for sustainable cities: a systematic review, Frontiers of Engineering Management, Vol. 12, pp. 223-237, 2025.
[23] A. Idrovo-Macancela, M. Velecela-Zhindón, A. Barragán-Escandón, E. Zalamea-León, and D. Mejía-Coronel, GIS-based assessment of photovoltaic solar potential on building rooftops in equatorial urban areas, Heliyon, Vol. 11, No. 1, pp. e41425, 2025.
[24] A. Seif and T. Mahmoodi, Lidar sensors and its applications, Scientific-Research Quarterly of Geographical Data (SEPEHR), Vol. 23, No. 89, pp. 72-80, 2014. (in Persian)
[25] L. El Chaar and N. El Zein, Review of photovoltaic technologies, Renewable and Sustainable Energy Reviews, Vol. 15, No. 5, pp. 2165-2175, 2011.
[26] D. N. Aedelia and D. S. Wijayanto, Analysis of monocrystalline and polycrystalline photovoltaic efficiency on dual-axis solar tracker system based on Internet of Things, Mathematical Modelling of Engineering Problems, Vol. 12, No. 9, pp. 2993-3002, 2025.
[27] H. Medi, Feasibility study on site selection for installing a small scale PV plant, Journal of Renewable and New Energy, Vol. 8, No. 1, pp. 102-112, 2021. (in Persian)
[28]National Oceanic and Atmospheric Administration (NOAA), 2013–2014 U.S. Geological Survey CMGP LiDAR: Post Sandy (New York City), Accessed 15 July 2025; https://www.fisheries.noaa.gov/inport/item/49891.
[29] K. Ihsan, A. Sakti, A. Higuchi, H. Takenaka, D. Suwardhi, and K. Wikantika, Comparison of potential energy of solar radiation in rooftop modeling using different building levels of detail, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 48, pp. 115-120, 2023.
[30] A. M. Martín, J. Domínguez, and J. Amador, Applying LIDAR datasets and GIS based model to evaluate solar potential over roofs: a review, AIMS Energy, Vol. 3, No. 3, pp. 326-343, 2015.
[31] A. Chow, 3D Solar Photovoltaic Community Energy Modeling, Ph.D. dissertation, Environmental Applied Science & Management, Ryerson University, Toronto, Canada, 2020.
[32] H. Zhang, Y. Liu, L. Wang, and S. Wang, Regional rooftop PV output potential assessment based on airborne LiDAR for precise consumption analysis, in Proceedings of the 3rd International Conference on Energy and Electrical Power Systems (ICEEPS), IEEE, pp. 348-353, 2024.
[33] Q. Chen, Application of geographic information system in assessing rooftop photovoltaic potential, Highlights in Science, Engineering and Technology, Vol. 69, pp. 361-367, 2023.
[34] M. Schlemminger, D. Bredemeier, A. Mahner, R. Niepelt, M. H. Breitner, and R. Brendel, Rooftop PV potential determined by backward ray tracing: a case study for the German regions of Berlin, Cologne, and Hanover, Progress in Photovoltaics: Research and Applications, Vol. 32, No. 12, pp. 912-929, 2024.
[35] B. O. Sigrin and M. E. Mooney, Rooftop Solar Technical Potential for Low-to-Moderate Income Households in the United States, National Renewable Energy Laboratory, Golden, CO, 2018.
[36] X. Huang, K. Hayashi, T. Matsumoto, L. Tao, Y. Huang, and Y. Tomino, Estimation of rooftop solar power potential by comparing solar radiation data and remote sensing data—a case study in Aichi, Japan, Remote Sensing, Vol. 14, No. 7, pp. 1742, 2022.
[37] X. Song, Y. Huang, C. Zhao, Y. Liu, Y. Lu, Y. Chang, et al., An approach for estimating solar photovoltaic potential based on rooftop retrieval from remote sensing images, Energies, Vol. 11, No. 11, pp. 3172, 2018.
[38] F. Biljecki, G. B. Heuvelink, H. Ledoux, and J. Stoter, Propagation of positional error in 3D GIS: estimation of the solar irradiation of building roofs, International Journal of Geographical Information Science, Vol. 29, No. 12, pp. 2269-2294, 2015.
[39] J. Gooding, H. Edwards, J. Giesekam, and R. Crook, Solar City Indicator: a methodology to predict city level PV installed capacity by combining physical capacity and socio-economic factors, Solar Energy, Vol. 95, pp. 325-335, 2013.
[40] R. Margolis, P. Gagnon, J. Melius, C. Phillips, and R. Elmore, Using GIS-based methods and lidar data to estimate rooftop solar technical potential in US cities, Environmental Research Letters, Vol. 12, No. 7, pp. 074013, 2017.
[41] New York Solar Panel Costs: 2024 Data, Accessed 17 July 2025; https://www.energysage.com/local-data/solar-panel-cost/ny/.
[42] V. Ramasamy, J. Zuboy, E. O’Shaughnessy, D. Feldman, J. Desai, M. Woodhouse, P. Basore, R. Margolis, US Solar Photovoltaic System and Energy Storage Cost Benchmarks, With Minimum Sustainable Price Analysis: Q1 2022, National Renewable Energy Lab. (NREL), Golden, CO (United States), 2022.
[43]NYSERDA, Residential Solar Incentives, Accessed 17 July 2025; https://nysolarmap.com/financing-solar/incentives/residential/.
[44]M. S. Calvo and H. S. Lee, Advanced geospatial analytics and multi-objective optimization framework for national rooftop solar assessment: Cuba case study, Energy Reports, Vol. 14, pp. 254-267, 2025.
