{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T15:36:28Z","timestamp":1767108988631,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,10,27]],"date-time":"2024-10-27T00:00:00Z","timestamp":1729987200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Laboratory of Land Satellite Remote Sensing Applications, Ministry of Natural Resources of the People\u2019s Republic of China","award":["KLSMNR-K202210","KLSMNR-G202311","42371408","42101430","2022029","2022PGE006","202110298029Z"],"award-info":[{"award-number":["KLSMNR-K202210","KLSMNR-G202311","42371408","42101430","2022029","2022PGE006","202110298029Z"]}]},{"name":"National Natural Science Foundation of China","award":["KLSMNR-K202210","KLSMNR-G202311","42371408","42101430","2022029","2022PGE006","202110298029Z"],"award-info":[{"award-number":["KLSMNR-K202210","KLSMNR-G202311","42371408","42101430","2022029","2022PGE006","202110298029Z"]}]},{"name":"Science and Technology Plan 2022 of the Natural Resources Department of Jiangsu Province","award":["KLSMNR-K202210","KLSMNR-G202311","42371408","42101430","2022029","2022PGE006","202110298029Z"],"award-info":[{"award-number":["KLSMNR-K202210","KLSMNR-G202311","42371408","42101430","2022029","2022PGE006","202110298029Z"]}]},{"name":"Foundation of Anhui Province Key Laboratory of Physical Geographic Environment","award":["KLSMNR-K202210","KLSMNR-G202311","42371408","42101430","2022029","2022PGE006","202110298029Z"],"award-info":[{"award-number":["KLSMNR-K202210","KLSMNR-G202311","42371408","42101430","2022029","2022PGE006","202110298029Z"]}]},{"name":"Nanjing Forestry University Student Innovation Training Program Project","award":["KLSMNR-K202210","KLSMNR-G202311","42371408","42101430","2022029","2022PGE006","202110298029Z"],"award-info":[{"award-number":["KLSMNR-K202210","KLSMNR-G202311","42371408","42101430","2022029","2022PGE006","202110298029Z"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The traditional process for selecting urban gas station sites often emphasizes economic benefits and return on investment, frequently overlooking mandatory and guiding constraints established by territorial spatial planning regulations. This neglect can compromise the effective layout and future growth of cities, potentially affecting their long-term development. To address this issue, this study develops a systematic framework for urban gas station site selection that integrates both mandatory and guiding constraints. By conducting detailed analyses of feasible construction areas and fuel demand, the framework quantifies relevant indicators and establishes a comprehensive index system for site selection. A multi-objective optimization model employing genetic algorithms was utilized to maximize fuel demand coverage, minimize inter-station redundancy, and achieve optimal site coverage. This framework was applied to the central urban area of Lishui City, China, as a case study. The site selection schemes achieved a coverage rate exceeding 90%, an inter-station redundancy rate around 30%, and a demand coverage rate surpassing 90%, optimizing the key objectives. Compared to traditional methods that often ignore territorial spatial planning constraints, this framework effectively avoids conflicts with urban planning and regulatory requirements. It enhances infrastructure coordination, supports environmental sustainability, and exhibits strong adaptability to diverse urban contexts, thus offering valuable support for practical decision-making.<\/jats:p>","DOI":"10.3390\/ijgi13110375","type":"journal-article","created":{"date-parts":[[2024,10,28]],"date-time":"2024-10-28T07:04:04Z","timestamp":1730099044000},"page":"375","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Multi-Objective Optimization of Urban Gas Station Site Selection Under Territorial Spatial Planning Constraints"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1745-3319","authenticated-orcid":false,"given":"Jie","family":"Zhu","sequence":"first","affiliation":[{"name":"College of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China"},{"name":"Key Laboratory of Virtual Geographic Environment of the Ministry of Education, Nanjing Normal University, Nanjing 210023, China"}]},{"given":"Mengyao","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Li","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Virtual Geographic Environment of the Ministry of Education, Nanjing Normal University, Nanjing 210023, China"}]},{"given":"Li","family":"Luo","sequence":"additional","affiliation":[{"name":"Key Laboratory of Virtual Geographic Environment of the Ministry of Education, Nanjing Normal University, Nanjing 210023, China"}]},{"given":"Weihua","family":"Wang","sequence":"additional","affiliation":[{"name":"Lishui City Land Space Planning and Mapping Research Institute, Lishui Bureau of Natural Resource and Planning, Lishui 323000, China"}]},{"given":"Xueming","family":"Zhu","sequence":"additional","affiliation":[{"name":"Technical Assurance Center for Natural Resources and Planning, Changzhou Xinbei City, Changzhou 213022, China"}]},{"given":"Yizhong","family":"Sun","sequence":"additional","affiliation":[{"name":"Key Laboratory of Virtual Geographic Environment of the Ministry of Education, Nanjing Normal University, Nanjing 210023, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1978782.1978791","article-title":"To fill or not to fill: The gas station problem","volume":"7","author":"Khuller","year":"2011","journal-title":"ACM Trans. Algorithms (TALG)"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1043","DOI":"10.1016\/j.ijhydene.2022.09.195","article-title":"Optimal sites selection of oil-hydrogen combined stations considering the diversity of hydrogen sources","volume":"48","author":"Xu","year":"2023","journal-title":"Int. J. Hydrogen Energy"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1274","DOI":"10.1016\/j.ijhydene.2023.09.168","article-title":"Two-stage site selection of hydrogen refueling stations coupled with gas stations considering cooperative effects based on the CRITIC-ITFAHP-MABAC method: A case study in Beijing","volume":"49","author":"Shi","year":"2024","journal-title":"Int. J. Hydrogen Energy"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.energy.2017.08.041","article-title":"Decision-making of compressed natural gas station siting for public transportation: Integration of multi-objective optimization, fuzzy evaluating, and radar charting","volume":"140","author":"Li","year":"2017","journal-title":"Energy"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.habitatint.2018.10.002","article-title":"Urban sustainable transportation planning strategies for livable City\u2019s quality of life","volume":"82","author":"Wey","year":"2018","journal-title":"Habitat Int."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"105288","DOI":"10.1016\/j.landusepol.2021.105288","article-title":"Territory spatial planning and national governance system in China","volume":"102","author":"Liu","year":"2021","journal-title":"Land Use Policy"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Tan, X., Zhang, P., Wang, J., and Hong, J. (2019). Research on Urban Bearing Capacity of Gas Supply Stations. Sustainability, 11.","DOI":"10.3390\/su11246971"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Garcia-Ramirez, K.A., Llacza-Lizarraga, A.W., Ninaquispe-Soto, M., Riega-Vir\u00fa, Y., and Riojas-Ca\u00f1ari, A. (2023). Simulation of a Queuing System in the Customer Service Area of a Gas Station, Lima, Peru. International Conference on WorldS4, Springer Nature.","DOI":"10.1007\/978-981-99-7886-1_46"},{"key":"ref_9","first-page":"27","article-title":"The effect of facilities and service quality on customer satisfaction of gas station in setu bekasi, west java","volume":"1","author":"Riseetyawan","year":"2022","journal-title":"J. Manag. Account. Gen. Financ. Int. Econ. Issues"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/j.tranpol.2022.09.015","article-title":"Framework for planning of EV charging infrastructure: Where should cities start?","volume":"128","author":"Torkey","year":"2022","journal-title":"Transp. Policy"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1108\/09590559710160355","article-title":"Towards a contemporary perspective of retail location","volume":"25","author":"Clarke","year":"1997","journal-title":"Int. J. Retail. Distrib. Manag."},{"key":"ref_12","unstructured":"Berman, B. (2004). Retail Management: A Strategic Approach, Pearson Education India."},{"key":"ref_13","first-page":"12","article-title":"A multi-criteria factor evaluation model for gas station site selection","volume":"2","author":"Semih","year":"2011","journal-title":"Evaluation"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.trd.2014.09.003","article-title":"Siting public electric vehicle charging stations in Beijing using big-data informed travel patterns of the taxi fleet","volume":"33","author":"Cai","year":"2014","journal-title":"Transp. Res. Part D Transp. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Yang, W., and Ai, T. (2018). POI information enhancement using crowdsourcing vehicle trace data and social media data: A case study of gas station. ISPRS Int. J. Geo-Inf., 7.","DOI":"10.3390\/ijgi7050178"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"40138","DOI":"10.1016\/j.ijhydene.2022.08.068","article-title":"Multi-period planning of hydrogen refuelling stations using flow data: A case study for Istanbul","volume":"47","year":"2022","journal-title":"Int. J. Hydrogen Energy"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"31305","DOI":"10.1016\/j.ijhydene.2023.04.210","article-title":"Hydrogen station allocation based on equilibrium traffic flow","volume":"48","author":"Xu","year":"2023","journal-title":"Int. J. Hydrogen Energy"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1431","DOI":"10.1016\/j.compchemeng.2011.03.018","article-title":"An optimization framework for cost effective design of refueling station infrastructure for alternative fuel vehicles","volume":"35","author":"Shukla","year":"2011","journal-title":"Comput. Chem. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"103426","DOI":"10.1016\/j.trc.2021.103426","article-title":"Location selection for hydrogen fuel stations under emerging provider competition","volume":"133","author":"Minner","year":"2021","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"112923","DOI":"10.1016\/j.rser.2022.112923","article-title":"Ground-mounted photovoltaic power station site selection and economic analysis based on a hybrid fuzzy best-worst method and geographic information system: A case study Guilan province","volume":"169","author":"Fard","year":"2022","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"10270","DOI":"10.1016\/j.ijhydene.2019.10.069","article-title":"Hydrogen station location optimization based on multiple data sources","volume":"45","author":"Lin","year":"2020","journal-title":"Int. J. Hydrogen Energy"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"102999","DOI":"10.1016\/j.trb.2024.102999","article-title":"Mathematical formulations for the multi-period alternative fuel refueling station location problem with routing under decision-dependent flow dynamics","volume":"186","author":"Yaman","year":"2024","journal-title":"Transp. Res. Part B Methodol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.rser.2015.10.133","article-title":"Energy management and planning in smart cities","volume":"55","author":"Calvillo","year":"2016","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_24","first-page":"1361","article-title":"Site selection for small gas stations using GIS","volume":"6","author":"Aslani","year":"2011","journal-title":"Sci. Res. Essays"},{"key":"ref_25","first-page":"158","article-title":"Suitability analysis for siting oil and gas filling stations using multi-criteria decision analysis and GIS approach\u2014A case study in Tarkwa and its environs","volume":"12","author":"Peprah","year":"2018","journal-title":"J. Geomat."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3136","DOI":"10.1016\/j.camwa.2011.03.104","article-title":"A new fuzzy weighted average (FWA) method based on left and right scores: An application for determining a suitable location for a gas oil station","volume":"61","author":"Mokhtarian","year":"2011","journal-title":"Comput. Math. Appl."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"24","DOI":"10.55670\/fpll.futech.2.4.3","article-title":"Potential measurement and spatial priorities determination for gas station construction using WLC and GIS","volume":"2","author":"Estelaji","year":"2023","journal-title":"Future Technol."},{"key":"ref_28","first-page":"1","article-title":"Geospatial Analysis of Fuel and Gas Station Distribution: Evaluating the Compliance and Impact of Station Siting on Public Health and Safety in Kumasi, Ghana","volume":"10","author":"Antwi","year":"2024","journal-title":"Comput. Res. Prog. Appl. Sci. Eng. CRPASE Trans. Civ. Environ. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.jtrangeo.2016.08.019","article-title":"A threshold covering flow-based location model to build a critical mass of alternative-fuel stations","volume":"56","author":"Hong","year":"2016","journal-title":"J. Transp. Geogr."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"3335","DOI":"10.1016\/j.ijhydene.2016.12.137","article-title":"Refueling station location problem with traffic deviation considering route choice and demand uncertainty","volume":"42","author":"Miralinaghi","year":"2017","journal-title":"Int. J. Hydrogen Energy"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"103339","DOI":"10.1016\/j.trc.2021.103339","article-title":"Predicting traffic demand during hurricane evacuation using Real-time data from transportation systems and social media","volume":"131","author":"Roy","year":"2021","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Yoon, S., and Park, M. (2023). Prediction of gasoline orders at gas stations in South Korea using VAE-based machine learning model to address data asymmetry. Appl. Sci., 13.","DOI":"10.3390\/app132011124"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1916","DOI":"10.1016\/j.cor.2008.06.005","article-title":"Optimization of natural gas pipeline transportation using ant colony optimization","volume":"36","author":"Chebouba","year":"2009","journal-title":"Comput. Oper. Res."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1007\/s10586-017-1305-6","article-title":"Expected value model of bus gas station site layout problem with fuzzy demand in supplementary fuel using genetic algorithm","volume":"22","author":"Wei","year":"2019","journal-title":"Clust. Comput."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"844","DOI":"10.1016\/j.energy.2018.12.062","article-title":"GIS-based multi-objective particle swarm optimization of charging stations for electric vehicles","volume":"169","author":"Zhang","year":"2019","journal-title":"Energy"},{"key":"ref_36","first-page":"293","article-title":"A multi-objective site selection of electric vehicle charging station based on NSGA-II","volume":"15","author":"Zhang","year":"2024","journal-title":"Int. J. Ind. Eng. Comput."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"118645","DOI":"10.1016\/j.enconman.2024.118645","article-title":"Driving towards net-zero from the energy sector: Leveraging machine intelligence for robust optimization of coal and combined cycle gas power stations","volume":"314","author":"Ashraf","year":"2024","journal-title":"Energy Convers. Manag."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"106462","DOI":"10.1016\/j.landusepol.2022.106462","article-title":"Territorial spatial planning for regional high-quality development\u2013An analytical framework for the identification, mediation and transmission of potential land utilization conflicts in the Yellow River Delta","volume":"125","author":"Qu","year":"2023","journal-title":"Land Use Policy"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"111816","DOI":"10.1016\/j.ecolind.2024.111816","article-title":"Aligning territorial spatial planning with sustainable development goals: A comprehensive analysis of production, living, and ecological spaces in China","volume":"160","author":"Song","year":"2024","journal-title":"Ecol. Indic."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"04024074","DOI":"10.1061\/JTEPBS.TEENG-8539","article-title":"Real-Time Traffic Flow Uncertainty Quantification Based on Nonparametric Probability Density Function Estimation","volume":"150","author":"Li","year":"2024","journal-title":"J. Transp. Eng. Part A Syst."},{"key":"ref_41","unstructured":"(1995). Code for Urban road Traffic Planning and Design (Standard No. GB 50220-95)."},{"key":"ref_42","first-page":"100779","article-title":"The ideal isochrone: Assessing the efficiency of transport systems","volume":"46","author":"Olszewski","year":"2023","journal-title":"Res. Transp. Bus. Manag."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/13\/11\/375\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:21:31Z","timestamp":1760113291000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/13\/11\/375"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,27]]},"references-count":42,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2024,11]]}},"alternative-id":["ijgi13110375"],"URL":"https:\/\/doi.org\/10.3390\/ijgi13110375","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2024,10,27]]}}}