{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T03:59:52Z","timestamp":1773115192091,"version":"3.50.1"},"reference-count":65,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T00:00:00Z","timestamp":1740182400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52270187"],"award-info":[{"award-number":["52270187"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["W2412162"],"award-info":[{"award-number":["W2412162"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"SDIC Key Project of International (Regional) Cooperation and Exchange Projects of the National Natural Science Foundation of China","award":["52270187"],"award-info":[{"award-number":["52270187"]}]},{"name":"SDIC Key Project of International (Regional) Cooperation and Exchange Projects of the National Natural Science Foundation of China","award":["W2412162"],"award-info":[{"award-number":["W2412162"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Rooftop photovoltaics (RPVs) are crucial in addressing energy shortages and environmental concerns caused by fossil fuel combustion. To promote the optimal deployment of RPVs in Tianjin, a region with abundant solar resources and dense buildings, this study proposes a framework that integrates building vector data with a deep learning model to extract currently installed RPVs from remote sensing images, and further estimate the development potential of RPVs. A total of 86,363 RPV polygons were extracted, covering an area of 10.34 km2. More than 70% of these RPVs are concentrated on large and low-rise buildings, and a similar proportion is found in industrial buildings, as these buildings offer favorable installation conditions. Combining solar radiation and construction land development planning, we further determined the potential deployment zone of RPVs covering about 13% of the Tianjin\u2019s land area, which represents 31.31 TWh per year of power generation potential. In the future, it is recommended to prioritize RPV installation on large and low-rise buildings or industrial buildings in the potential deployment zone, which could provide higher power generation and contribute significantly to environmental emission reduction goals. The proposed research framework can also be applied to other cities.<\/jats:p>","DOI":"10.3390\/ijgi14030101","type":"journal-article","created":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T05:36:47Z","timestamp":1740375407000},"page":"101","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Deep-Learning-Based Evaluation of Rooftop Photovoltaic Deployment in Tianjin, China"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4549-8466","authenticated-orcid":false,"given":"Mei","family":"Shan","sequence":"first","affiliation":[{"name":"School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China"}]},{"given":"Yue","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6274-7087","authenticated-orcid":false,"given":"Yun","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China"}]},{"given":"Yuan","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China"}]},{"given":"Lei","family":"Li","sequence":"additional","affiliation":[{"name":"College of Management and Economics, Tianjin University, Tianjin 300072, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8971-4952","authenticated-orcid":false,"given":"Zhi","family":"Qiao","sequence":"additional","affiliation":[{"name":"School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China"}]},{"given":"Jian","family":"Zuo","sequence":"additional","affiliation":[{"name":"School of Architecture and Civil Engineering, The University of Adelaide, Adelaide 5005, Australia"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"117038","DOI":"10.1016\/j.energy.2020.117038","article-title":"Solar energy potential of urban buildings in 10 cities of China","volume":"196","author":"Cheng","year":"2020","journal-title":"Energy"},{"key":"ref_2","unstructured":"(2024, October 10). Solar Energy. Available online: https:\/\/www.irena.org\/Energy-Transition\/Technology\/Solar-energy."},{"key":"ref_3","unstructured":"(2024, October 09). Global Market Outlook for Solar Power 2023\u20132027. Available online: https:\/\/www.solarpowereurope.org\/insights\/outlooks\/global-market-outlook-for-solar-power-2023-2027."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Pu, Y., Sun, Z., Qian, Z., and Chen, M. (2024). Assessment of rooftop photovoltaic potential considering building functions. Remote Sens., 16.","DOI":"10.3390\/rs16162993"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"130721","DOI":"10.1016\/j.energy.2024.130721","article-title":"Exploring the optimization of rooftop photovoltaic scale and spatial layout under curtailment constraints","volume":"293","author":"Jiang","year":"2024","journal-title":"Energy"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"14545","DOI":"10.1016\/j.egyr.2022.10.396","article-title":"High resolution photovoltaic power generation potential assessments of rooftop in China","volume":"8","author":"Wang","year":"2022","journal-title":"Energy Rep."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"5738","DOI":"10.1038\/s41467-021-25720-2","article-title":"High resolution global spatiotemporal assessment of rooftop solar photovoltaics potential for renewable electricity generation","volume":"12","author":"Joshi","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2347","DOI":"10.1038\/s41467-023-38079-3","article-title":"Carbon mitigation potential afforded by rooftop photovoltaic in China","volume":"14","author":"Zhang","year":"2023","journal-title":"Nat. Commun."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"115705","DOI":"10.1016\/j.apenergy.2020.115705","article-title":"The role of residential rooftop photovoltaic in long-term energy and climate scenarios","volume":"279","author":"Gernaat","year":"2020","journal-title":"Appl. Energy"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"113743","DOI":"10.1016\/j.enbuild.2023.113743","article-title":"Enhancing rooftop solar energy potential evaluation in high-density cities: A Deep Learning and GIS based approach","volume":"309","author":"Ni","year":"2024","journal-title":"Energy Build."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"124172","DOI":"10.1016\/j.apenergy.2024.124172","article-title":"Development assessment of regional rooftop photovoltaics based on remote sensing and deep learning","volume":"375","author":"Qi","year":"2024","journal-title":"Appl. Energy"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"4909","DOI":"10.1109\/JSTARS.2022.3181446","article-title":"Lebanon solar rooftop potential assessment using buildings segmentation from aerial images","volume":"15","author":"Samhat","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_13","unstructured":"(2024, September 09). The Construction of Photovoltaic Power Generation in 2016, Available online: https:\/\/www.nea.gov.cn\/."},{"key":"ref_14","unstructured":"(2024, September 09). The Construction of Photovoltaic Power Generation in 2023, Available online: https:\/\/www.nea.gov.cn\/2024-02\/28\/c_1310765696.htm."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Zech, M., and Ranalli, J. (August, January 15). Predicting PV areas in aerial images with deep learning. Proceedings of the 2020 47th IEEE Photovoltaic Specialists Conference (PVSC), Calgary, AB, Canada.","DOI":"10.1109\/PVSC45281.2020.9300636"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1117\/1.JRS.14.016506","article-title":"Photovoltaic power station identification using refined encoder\u2013decoder network with channel attention and chained residual dilated convolutions","volume":"14","author":"Jie","year":"2020","journal-title":"J. Appl. Remote Sens."},{"key":"ref_17","unstructured":"(2024, September 09). Outline of the 14th Five-Year Plan for Tianjin\u2019s National Economic and Social Development and the Long-Term Goal for 2035, Available online: https:\/\/www.tj.gov.cn\/zwgk\/szfwj\/tjsrmzf\/202102\/t20210208_5353467.html."},{"key":"ref_18","unstructured":"(2024, September 09). Pilot List for County Distributed Photovoltaic Development Projects, Available online: https:\/\/www.gov.cn\/zhengce\/zhengceku\/2021-09\/15\/content_5637323.htm."},{"key":"ref_19","unstructured":"(2024, September 09). Tianjin Urban and Rural Construction Field Carbon Peak Implementation Plan, Available online: https:\/\/zfcxjs.tj.gov.cn\/xxgk_70\/tzgg\/202308\/t20230817_6379811.html."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"113276","DOI":"10.1016\/j.rser.2023.113276","article-title":"Advances and prospects on estimating solar photovoltaic installation capacity and potential based on satellite and aerial images","volume":"179","author":"Mao","year":"2023","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_21","unstructured":"(2024, September 09). Historical Climate Data. Available online: https:\/\/worldclim.org\/data\/worldclim21.html."},{"key":"ref_22","unstructured":"(2024, September 09). General Planning of Land Space of Tianjin (2021\u20132035), Available online: https:\/\/ghhzrzy.tj.gov.cn\/zmhd_143\/jcyjzj\/202109\/t20210923_5608995.html."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"0138","DOI":"10.34133\/remotesensing.0138","article-title":"The last puzzle of global building footprints\u2014Mapping 280 million buildings in East Asia based on VHR images","volume":"4","author":"Shi","year":"2024","journal-title":"J. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3835","DOI":"10.5194\/essd-14-3835-2022","article-title":"A global map of local climate zones to support earth system modelling and urban-scale environmental science","volume":"14","author":"Demuzere","year":"2022","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.scib.2019.12.007","article-title":"Mapping essential urban land use categories in China (EULUC-China): Preliminary results for 2018","volume":"65","author":"Gong","year":"2020","journal-title":"Sci. Bull."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.apenergy.2016.08.191","article-title":"Automatic detection of solar photovoltaic arrays in high resolution aerial imagery","volume":"183","author":"Malof","year":"2016","journal-title":"Appl. Energy"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Malof, J.M., Hou, R., Collins, L.M., Bradbury, K., and Newell, R. (2015, January 22\u201325). Automatic solar photovoltaic panel detection in satellite imagery. Proceedings of the 2015 International Conference on Renewable Energy Research and Applications (ICRERA), Palermo, Italy.","DOI":"10.1109\/ICRERA.2015.7418643"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"604","DOI":"10.1038\/s41586-021-03957-7","article-title":"A global inventory of photovoltaic solar energy generating units","volume":"598","author":"Kruitwagen","year":"2021","journal-title":"Nature"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"114100","DOI":"10.1016\/j.rse.2024.114100","article-title":"Uncovering the rapid expansion of photovoltaic power plants in China from 2010 to 2022 using satellite data and deep learning","volume":"305","author":"Chen","year":"2024","journal-title":"Remote Sens. Environ."},{"key":"ref_30","first-page":"234","article-title":"U-Net: Convolutional networks for biomedical image segmentation","volume":"Volume 9351","author":"Ronneberger","year":"2015","journal-title":"Proceedings of the Medical Image Computing and Computer-Assisted Intervention\u2013MICCAI 2015: 18th International Conference"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Muhammed, E., El-Shazly, A., and Morsy, S. (2023). Building rooftop extraction using machine learning algorithms for solar photovoltaic potential estimation. Sustainability, 15.","DOI":"10.3390\/su151411004"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Joshi, B., Baluyan, H., Hinai, A.A., and Woon, W.L. (2014, January 26\u201328). Automatic rooftop detection using a two-stage classification. Proceedings of the 2014 UKSim-AMSS 16th International Conference on Computer Modelling and Simulation, Cambridge, UK.","DOI":"10.1109\/UKSim.2014.89"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"119025","DOI":"10.1016\/j.apenergy.2022.119025","article-title":"Estimating the spatial distribution of solar photovoltaic power generation potential on different types of rural rooftops using a deep learning network applied to satellite images","volume":"315","author":"Sun","year":"2022","journal-title":"Appl. Energy"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1038\/s41467-020-14386-x","article-title":"Global projections of future urban land expansion under shared socioeconomic pathways","volume":"11","author":"Chen","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_35","unstructured":"(2024, September 09). Solar Photovoltaic Panel Size Guide. Available online: https:\/\/www.abpv360.com\/a\/9599."},{"key":"ref_36","unstructured":"Cebecauer, T., and Suri, M. (2024, September 09). Solar Performance Maps [Dataset]. Solargis. Available online: https:\/\/apps.solargis.com."},{"key":"ref_37","unstructured":"(2024, September 09). Annual Report on China\u2019s Electric Power Industry 2020. Available online: https:\/\/cec.org.cn\/."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"119834","DOI":"10.1016\/j.energy.2021.119834","article-title":"Efficient deployment of solar photovoltaic stations in China: An economic and environmental perspective","volume":"221","author":"Bai","year":"2021","journal-title":"Energy"},{"key":"ref_39","unstructured":"(2024, September 09). China PV Industry Development Roadmap. Available online: https:\/\/www.chinapv.org.cn\/Industry\/resource_1380.html."},{"key":"ref_40","unstructured":"(2024, September 09). Notice on Matters Related to the On-Grid Tariff Policy of PV Power Generation in 2020, Available online: https:\/\/www.ndrc.gov.cn\/xxgk\/zcfb\/tz\/202004\/t20200402_1225031.html."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"12034","DOI":"10.1088\/1742-6596\/1343\/1\/012034","article-title":"Deep learning in the built environment: Automatic detection of rooftop solar panels using convolutional neural networks","volume":"1343","author":"Castello","year":"2019","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Ren, S., Malof, J., Fetter, R., Beach, R., Rineer, J., and Bradbury, K. (2022). Utilizing geospatial data for assessing energy security: Mapping small solar home systems using unmanned aerial vehicles and deep learning. Isprs Int. J. Geo-Inf., 11.","DOI":"10.3390\/ijgi11040222"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"5389","DOI":"10.5194\/essd-13-5389-2021","article-title":"Multi-resolution dataset for photovoltaic panel segmentation from satellite and aerial imagery","volume":"13","author":"Jiang","year":"2021","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"3743","DOI":"10.5194\/essd-14-3743-2022","article-title":"Mapping photovoltaic power plants in China using Landsat, random forest, and Google Earth Engine","volume":"14","author":"Zhang","year":"2022","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"110458","DOI":"10.1016\/j.rser.2020.110458","article-title":"Machine learning approach to understand regional disparity of residential solar adoption in Australia","volume":"136","author":"Lan","year":"2021","journal-title":"Renew. Sust. Energ. Rev."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Chen, Y., Liu, Y., Slootweg, M., Hu, M., Tukker, A., and Chen, W. (2024). Unlocking rooftop potential for sustainable cities: A systematic review. Front. Eng. Manag.","DOI":"10.1007\/s42524-024-4053-3"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/j.eneco.2015.08.003","article-title":"Regional distribution of photovoltaic deployment in the UK and its determinants: A spatial econometric approach","volume":"51","author":"Yildirim","year":"2015","journal-title":"Energy Econ."},{"key":"ref_48","unstructured":"(2025, February 07). Tianjin Statistical Yearbook 2024, Available online: https:\/\/stats.tj.gov.cn\/nianjian\/2024nj\/zk\/indexch.htm."},{"key":"ref_49","first-page":"74","article-title":"Where, when and how much solar is available? A provincial-scale solar resource assessment for China. Renew","volume":"85","author":"He","year":"2016","journal-title":"Energy"},{"key":"ref_50","unstructured":"(2025, February 07). Tianjin Renewable Energy Development \u201c14th Five-Year Plan\u201d, Available online: https:\/\/fzgg.tj.gov.cn\/zwgk_47325\/zcfg_47338\/zcwjx\/fgwj\/202201\/t20220127_5791174.html."},{"key":"ref_51","unstructured":"(2025, February 07). Tianjin South 1000 kV Substation Will Be Built Within the Year. Available online: https:\/\/news.bjx.com.cn\/html\/20140422\/505715.shtml."},{"key":"ref_52","unstructured":"(2025, February 06). 2023 Annual Report of State Grid Tianjin Electric Power Company Information Disclosure. Available online: http:\/\/www.tj.sgcc.com.cn\/html\/main\/col2792\/2024-03\/26\/20240326143137466720379_1.html."},{"key":"ref_53","unstructured":"(2025, February 08). ORNL LandScan Viewer-Oak Ridge National Laboratory, Available online: https:\/\/landscan.ornl.gov\/."},{"key":"ref_54","unstructured":"(2025, February 08). OpenStreetMap. Available online: https:\/\/download.geofabrik.de\/."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"106283","DOI":"10.1016\/j.asoc.2020.106283","article-title":"The automatic segmentation of residential solar panels based on satellite images: A cross learning driven U-Net method","volume":"92","author":"Zhuang","year":"2020","journal-title":"Appl. Soft Comput."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"104167","DOI":"10.1016\/j.landurbplan.2021.104167","article-title":"Roofpedia: Automatic mapping of green and solar roofs for an open roofscape registry and evaluation of urban sustainability","volume":"214","author":"Wu","year":"2021","journal-title":"Landsc. Urban Plan."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.joule.2017.07.005","article-title":"100% Clean and renewable wind, water, and sunlight all-sector energy roadmaps for 139 countries of the world","volume":"1","author":"Jacobson","year":"2017","journal-title":"Joule"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Li, J., Wang, C., Guo, J., Xin, Y., Zhang, N., Liu, X., and Feng, K. (2024). Promoting sustainable development goals by optimizing city-level solar photovoltaic deployment in China. Environ. Sci. Technol.","DOI":"10.1021\/acs.est.3c09263"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"115296","DOI":"10.1016\/j.jenvman.2022.115296","article-title":"An integrated technical, economic, and environmental framework for evaluating the rooftop photovoltaic potential of old residential buildings","volume":"317","author":"Wang","year":"2022","journal-title":"J. Environ. Manag."},{"key":"ref_60","unstructured":"Zhang, J. (2015). Assessment of Renewable Energy Potentials Based on GIS and RS, Technische Universit\u00e4t Dortmund."},{"key":"ref_61","first-page":"276","article-title":"Evaluation of energy-oriented utilization potential of main Chinese crop residues based on soil protection functions","volume":"25","author":"Zhu","year":"2017","journal-title":"Chin. J. Eco-Agric."},{"key":"ref_62","unstructured":"(2025, February 07). Introduction of Common Biomass Solid Pellet Fuel Parameters Calorvalue. Available online: http:\/\/www.china-nengyuan.com\/tech\/china-nengyuan_tech_45032.pdf."},{"key":"ref_63","unstructured":"(2025, February 07). Biomass Power Generation Technology Summary and Comparative Analysis of Economic Benefits. Available online: https:\/\/news.bjx.com.cn\/html\/20181102\/938930.shtml."},{"key":"ref_64","unstructured":"(2025, February 07). China County Seat Construction Statistical Yearbook. Available online: https:\/\/navi.cnki.net\/knavi\/detail?p=QRNotohAzjyri1RqHZJaTsF1SQug-eBwO4N_E5_L9nwRVv6AsuhsScJF6v2GXep1m0s1_Cz0ldXfyLtpzI-imXv3gNPIcGzIne0Oq45X_O0=&uniplatform=NZKPT."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"112591","DOI":"10.1016\/j.enbuild.2022.112591","article-title":"The technical and economic potential of urban rooftop photovoltaic systems for power generation in Guangzhou, China","volume":"277","author":"Pan","year":"2022","journal-title":"Energy Build."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/14\/3\/101\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T16:40:31Z","timestamp":1760028031000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/14\/3\/101"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,22]]},"references-count":65,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025,3]]}},"alternative-id":["ijgi14030101"],"URL":"https:\/\/doi.org\/10.3390\/ijgi14030101","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,22]]}}}