{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T00:27:58Z","timestamp":1767832078658,"version":"3.49.0"},"reference-count":69,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,8,27]],"date-time":"2025-08-27T00:00:00Z","timestamp":1756252800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["72303176"],"award-info":[{"award-number":["72303176"]}]},{"name":"National Natural Science Foundation of China","award":["2024T170709"],"award-info":[{"award-number":["2024T170709"]}]},{"name":"National Natural Science Foundation of China","award":["2025ZC-KJXX-18"],"award-info":[{"award-number":["2025ZC-KJXX-18"]}]},{"name":"National Natural Science Foundation of China","award":["25GL124"],"award-info":[{"award-number":["25GL124"]}]},{"name":"Postdoctoral Science Foundation of China","award":["72303176"],"award-info":[{"award-number":["72303176"]}]},{"name":"Postdoctoral Science Foundation of China","award":["2024T170709"],"award-info":[{"award-number":["2024T170709"]}]},{"name":"Postdoctoral Science Foundation of China","award":["2025ZC-KJXX-18"],"award-info":[{"award-number":["2025ZC-KJXX-18"]}]},{"name":"Postdoctoral Science Foundation of China","award":["25GL124"],"award-info":[{"award-number":["25GL124"]}]},{"name":"Shaanxi Provincial Youth Science and Technology Star Talent Program","award":["72303176"],"award-info":[{"award-number":["72303176"]}]},{"name":"Shaanxi Provincial Youth Science and Technology Star Talent Program","award":["2024T170709"],"award-info":[{"award-number":["2024T170709"]}]},{"name":"Shaanxi Provincial Youth Science and Technology Star Talent Program","award":["2025ZC-KJXX-18"],"award-info":[{"award-number":["2025ZC-KJXX-18"]}]},{"name":"Shaanxi Provincial Youth Science and Technology Star Talent Program","award":["25GL124"],"award-info":[{"award-number":["25GL124"]}]},{"name":"Xi\u2019an Social Science Planning Fund Project","award":["72303176"],"award-info":[{"award-number":["72303176"]}]},{"name":"Xi\u2019an Social Science Planning Fund Project","award":["2024T170709"],"award-info":[{"award-number":["2024T170709"]}]},{"name":"Xi\u2019an Social Science Planning Fund Project","award":["2025ZC-KJXX-18"],"award-info":[{"award-number":["2025ZC-KJXX-18"]}]},{"name":"Xi\u2019an Social Science Planning Fund Project","award":["25GL124"],"award-info":[{"award-number":["25GL124"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>As bike-sharing systems become increasingly integral to sustainable urban mobility, understanding their economic viability requires moving beyond conventional linear models to capture complex operational dynamics. This study develops an interpretable analytical framework to uncover non-linear relationships governing bike-sharing economic performance in Xi\u2019an, China, utilizing one-month operational data across 202 Transportation Analysis Zones (TAZs). Combining spatial analysis with explainable machine learning (XGBoost\u2013SHAP), we systematically examine how operational factors and built environment characteristics interact to influence economic outcomes, achieving superior predictive performance (R2 = 0.847) compared to baseline linear regression models (R2 = 0.652). The SHAP-based interpretation reveals three key findings: (1) bike-sharing performance exhibits pronounced spatial heterogeneity that correlates strongly with urban functional patterns), with commercial districts and transit-adjacent areas demonstrating consistently higher economic returns. (2) Gradual positive relationships emerge across multiple factors\u2014including bike supply density (maximum SHAP contribution +1.0), commercial POI distribution, and transit accessibility\u2014with performance showing consistent but moderate improvements rather than dramatic threshold effects. (3) Significant interaction effects are quantified between key factors, with bike supply density and commercial POI density exhibiting strong synergistic relationships (interaction values 1.5\u20132.0), particularly in areas combining high commercial activity with good transit connectivity. The findings challenge simplistic linear assumptions in bike-sharing management while providing quantitative evidence for spatially differentiated strategies that account for moderate threshold behaviors and factor synergies. Cross-validation results (5-fold, R2 = 0.89 \u00b1 0.018) confirm model robustness, while comprehensive performance metrics demonstrate substantial improvements over traditional approaches (35.1% RMSE reduction, 36.6% MAE improvement). The proposed framework offers urban planners a data-driven tool for evidence-based decision-making in sustainable mobility systems, with broader methodological applicability for similar urban contexts.<\/jats:p>","DOI":"10.3390\/ijgi14090333","type":"journal-article","created":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T07:43:16Z","timestamp":1756366996000},"page":"333","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Economic Optimization of Bike-Sharing Systems via Nonlinear Threshold Effects: An Interpretable Machine Learning Approach in Xi\u2019an, China"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-0678-3610","authenticated-orcid":false,"given":"Haolong","family":"Yang","sequence":"first","affiliation":[{"name":"School of Law, The University of Sydney, Sydney 2006, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chen","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Economics and Finance, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3158-397X","authenticated-orcid":false,"given":"Chao","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Humanities, Chang\u2019an University, Xi\u2019an 710064, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Albuquerque, V., Sales Dias, M., and Bacao, F. (2021). Machine Learning Approaches to Bike-Sharing Systems: A Systematic Literature Review. ISPRS Int. J. Geo-Inf., 10.","DOI":"10.3390\/ijgi10020062"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.jclepro.2014.04.006","article-title":"Sustainable Bike-Sharing Systems: Characteristics and Commonalities across Cases in Urban China","volume":"97","author":"Zhang","year":"2015","journal-title":"J. Clean. Prod."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.jtrangeo.2018.07.006","article-title":"Combining Means of Transport as a Users\u2019 Strategy to Optimize Traveling in an Urban Context: Empirical Results on Intermodal Travel Behavior from a Survey in Berlin","volume":"71","author":"Oostendorp","year":"2018","journal-title":"J. Transp. Geogr."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"113090","DOI":"10.1016\/j.ecolind.2025.113090","article-title":"Research on the Impact of Climate Change on Green and Low-Carbon Development in Agriculture","volume":"170","author":"Cai","year":"2025","journal-title":"Ecol. Indic."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"942","DOI":"10.1016\/j.jclepro.2018.03.323","article-title":"Co-Evolution between Urban Sustainability and Business Ecosystem Innovation: Evidence from the Sharing Mobility Sector in Shanghai","volume":"188","author":"Ma","year":"2018","journal-title":"J. Clean. Prod."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.jtrangeo.2018.11.009","article-title":"Freedom from the Station: Spatial Equity in Access to Dockless Bike Share","volume":"74","author":"Mooney","year":"2019","journal-title":"J. Transp. Geogr."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Qiu, L.-Y., and He, L.-Y. (2018). Bike Sharing and the Economy, the Environment, and Health-Related Externalities. Sustainability, 10.","DOI":"10.3390\/su10041145"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Nikitas, A. (2019). How to Save Bike-Sharing: An Evidence-Based Survival Toolkit for Policy-Makers and Mobility Providers. Sustainability, 11.","DOI":"10.3390\/su11113206"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"101882","DOI":"10.1016\/j.scs.2019.101882","article-title":"A Review on Bike-Sharing: The Factors Affecting Bike-Sharing Demand","volume":"54","author":"Eren","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1007\/s11116-016-9676-8","article-title":"Bicycle Mode Share in China: A City-Level Analysis of Long Term Trends","volume":"44","author":"Li","year":"2017","journal-title":"Transportation"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"102997","DOI":"10.1016\/j.jtrangeo.2021.102997","article-title":"Examining Spatiotemporal Changing Patterns of Bike-Sharing Usage during COVID-19 Pandemic","volume":"91","author":"Hu","year":"2021","journal-title":"J. Transp. Geogr."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/j.trb.2022.12.002","article-title":"A Target-Based Optimization Model for Bike-Sharing Systems: From the Perspective of Service Efficiency and Equity","volume":"167","author":"Chen","year":"2023","journal-title":"Transp. Res. Part B Methodol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"103238","DOI":"10.1016\/j.trd.2022.103238","article-title":"Environmental Impact Assessment of Bike-Sharing Considering the Modal Shift from Public Transit","volume":"105","author":"Saltykova","year":"2022","journal-title":"Transp. Res. Part Transp. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1016\/j.trc.2018.10.011","article-title":"Predicting Station-Level Hourly Demand in a Large-Scale Bike-Sharing Network: A Graph Convolutional Neural Network Approach","volume":"97","author":"Lin","year":"2018","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Jing, Y., Sun, R., and Chen, L. (2022). A Method for Identifying Urban Functional Zones Based on Landscape Types and Human Activities. Sustainability, 14.","DOI":"10.3390\/su14074130"},{"key":"ref_16","first-page":"402","article-title":"Exploration Financial Performance Optimization Strategies on Business Success: A Literature Review","volume":"6","author":"Sugiarto","year":"2023","journal-title":"SEIKO J. Manag. Bus."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"117732","DOI":"10.1016\/j.jclepro.2019.117732","article-title":"Learning about Spatial Inequalities: Capturing the Heterogeneity in the Urban Environment","volume":"237","author":"Giannotti","year":"2019","journal-title":"J. Clean. Prod."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Zhang, J., and Cheng, L. (2019). Threshold Effect of Tourism Development on Economic Growth Following a Disaster Shock: Evidence from the Wenchuan Earthquake, PR China. Sustainability, 11.","DOI":"10.3390\/su11020371"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"124281","DOI":"10.1016\/j.jclepro.2020.124281","article-title":"Identifying the Nonlinear Relationship between Free-Floating Bike Sharing Usage and Built Environment","volume":"280","author":"Chen","year":"2021","journal-title":"J. Clean. Prod."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Mavlutova, I., Atstaja, D., Grasis, J., Kuzmina, J., Uvarova, I., and Roga, D. (2023). Urban Transportation Concept and Sustainable Urban Mobility in Smart Cities: A Review. Energies, 16.","DOI":"10.3390\/en16083585"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"107525","DOI":"10.1016\/j.eneco.2024.107525","article-title":"The Impact of Green Innovation on Carbon Reduction Efficiency in China: Evidence from Machine Learning Validation","volume":"133","author":"Zhao","year":"2024","journal-title":"Energy Econ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"106237","DOI":"10.1016\/j.ecolind.2020.106237","article-title":"Potential Toxic Elements in Sediment of Some Rivers at Giresun, Northeast Turkey: A Preliminary Assessment for Ecotoxicological Status and Health Risk","volume":"113","author":"Ustaoglu","year":"2020","journal-title":"Ecol. Indic."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"103604","DOI":"10.1016\/j.jtrangeo.2023.103604","article-title":"Data-Driven Interpretation on Interactive and Nonlinear Effects of the Correlated Built Environment on Shared Mobility","volume":"110","author":"Gao","year":"2023","journal-title":"J. Transp. Geogr."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.tranpol.2020.05.023","article-title":"On the Possibility of Short-Term Traffic Prediction during Disaster with Machine Learning Approaches: An Exploratory Analysis","volume":"98","author":"Chikaraishi","year":"2020","journal-title":"Transp. Policy"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"106153","DOI":"10.1016\/j.aap.2021.106153","article-title":"The Application of XGBoost and SHAP to Examining the Factors in Freight Truck-Related Crashes: An Exploratory Analysis","volume":"158","author":"Yang","year":"2021","journal-title":"Accid. Anal. Prev."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Wang, L., Zhao, C., Liu, X., Chen, X., Li, C., Wang, T., Wu, J., and Zhang, Y. (2021). Non-Linear Effects of the Built Environment and Social Environment on Bus Use among Older Adults in China: An Application of the XGBoost Model. Int. J. Environ. Res. Public. Health, 18.","DOI":"10.3390\/ijerph18189592"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"105428","DOI":"10.1016\/j.scs.2024.105428","article-title":"Smart Transportation Systems Using Learning Method for Urban Mobility and Management in Modern Cities","volume":"108","author":"Jiang","year":"2024","journal-title":"Sustain. Cities Soc."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Wu, P., Zhang, Z., Peng, X., and Wang, R. (2024). Deep Learning Solutions for Smart City Challenges in Urban Development. Sci. Rep., 14.","DOI":"10.1038\/s41598-024-55928-3"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"106090","DOI":"10.1016\/j.scs.2024.106090","article-title":"Exploring the Nuanced Correlation between Built Environment and the Integrated Travel of Dockless Bike-Sharing and Metro at Origin-Route-Destination Level","volume":"119","author":"Shen","year":"2025","journal-title":"Sustain. Cities Soc."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Lai, X., and Gao, C. (2023). Spatiotemporal Patterns Evolution of Residential Areas and Transportation Facilities Based on Multi-Source Data: A Case Study of Xi\u2019an, China. ISPRS Int. J. Geo-Inf., 12.","DOI":"10.3390\/ijgi12060233"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Zhang, X., Wang, J., Long, X., and Li, W. (2021). Understanding the Intention to Use Bike-Sharing System: A Case Study in Xi\u2019an, China. PLoS ONE, 16.","DOI":"10.1371\/journal.pone.0258790"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.tra.2020.12.009","article-title":"Quantifying Economic Benefits from Free-Floating Bike-Sharing Systems: A Trip-Level Inference Approach and City-Scale Analysis","volume":"144","author":"Gao","year":"2021","journal-title":"Transp. Res. Part Policy Pract."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.1468-2427.2010.00982.x","article-title":"Cities in a World of Cities: The Comparative Gesture","volume":"35","author":"Robinson","year":"2010","journal-title":"Int. J. Urban Reg. Res."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"103008","DOI":"10.1016\/j.trd.2021.103008","article-title":"An Economic Analysis of Integrating Bike Sharing Service with Metro Systems","volume":"99","author":"Zhang","year":"2021","journal-title":"Transp. Res. Part Transp. Environ."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Storme, T., Casier, C., Azadi, H., and Witlox, F. (2021). Impact Assessments of New Mobility Services: A Critical Review. Sustainability, 13.","DOI":"10.3390\/su13063074"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1080\/01441647.2018.1450307","article-title":"The Implications of the Sharing Economy for Transport","volume":"39","author":"Standing","year":"2019","journal-title":"Transp. Rev."},{"key":"ref_37","first-page":"28","article-title":"Bike Sharing: A Review of Evidence on Impacts and Processes of Implementation and Operation","volume":"15","author":"Ricci","year":"2015","journal-title":"Res. Transp. Bus. Manag."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Lan, J., Ma, Y., Zhu, D., Mangalagiu, D., and Thornton, T.F. (2017). Enabling Value Co-Creation in the Sharing Economy: The Case of Mobike. Sustainability, 9.","DOI":"10.3390\/su9091504"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.envint.2016.08.019","article-title":"A Systematic Review of the Relationship between Objective Measurements of the Urban Environment and Psychological Distress","volume":"96","author":"Gong","year":"2016","journal-title":"Environ. Int."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"127991","DOI":"10.1016\/j.physa.2022.127991","article-title":"Large-Scale Dockless Bike Sharing Repositioning Considering Future Usage and Workload Balance","volume":"605","author":"Hua","year":"2022","journal-title":"Phys.-Stat. Mech. ITS Appl."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"105323","DOI":"10.1016\/j.scs.2024.105323","article-title":"Revealing the Driving Factors and Mobility Patterns of Bike-Sharing Commuting Demands for Integrated Public Transport Systems","volume":"104","author":"Zhu","year":"2024","journal-title":"Sustain. Cities Soc."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"103527","DOI":"10.1016\/j.trc.2021.103527","article-title":"Dynamic Incentive Schemes for Managing Dockless Bike-Sharing Systems","volume":"136","author":"Jin","year":"2022","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Guo, Y., Yang, L., and Chen, Y. (2022). Bike Share Usage and the Built Environment: A Review. Front. Public Health, 10.","DOI":"10.3389\/fpubh.2022.848169"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"103880","DOI":"10.1016\/j.scs.2022.103880","article-title":"The Impact of Energy Efficiency on Carbon Emissions: Evidence from the Transportation Sector in Chinese 30 Provinces","volume":"82","author":"Li","year":"2022","journal-title":"Sustain. Cities Soc."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.tra.2021.03.021","article-title":"Non-Linear Associations between Zonal Built Environment Attributes and Transit Commuting Mode Choice Accounting for Spatial Heterogeneity","volume":"148","author":"Ding","year":"2021","journal-title":"Transp. Res. Part-Policy Pract."},{"key":"ref_46","first-page":"47","article-title":"Innovation in Europe: A Tale of Networks, Knowledge and Trade in Five Cities","volume":"36","author":"Simmie","year":"2002","journal-title":"Taylor Fr."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"976","DOI":"10.1049\/iet-its.2017.0274","article-title":"Vehicle Scheduling Approach and Its Practice to Optimise Public Bicycle Redistribution in Hangzhou","volume":"12","author":"Liu","year":"2018","journal-title":"IET Intell. Transp. Syst."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"5725009","DOI":"10.1155\/2023\/5725009","article-title":"Hierarchical Vehicle Scheduling Research on Tide Bicycle-Sharing Traffic of Autonomous Transportation Systems","volume":"2023","author":"Hao","year":"2023","journal-title":"J. Adv. Transp."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1016\/j.tourman.2003.07.004","article-title":"Tourist Market Segmentation with Linear and Non-Linear Techniques","volume":"25","author":"Bloom","year":"2004","journal-title":"Tour. Manag."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.tranpol.2020.08.014","article-title":"On the Importance of Shenzhen Metro Transit to Land Development and Threshold Effect","volume":"99","author":"Yang","year":"2020","journal-title":"Transp. Policy"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Batty, M. (2009). Cities as Complex Systems: Scaling, Interaction, Networks, Dynamics and Urban Morphologies. Encyclopedia of Complexity and Systems Science, Springer.","DOI":"10.1007\/978-0-387-30440-3_69"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"104315","DOI":"10.1016\/j.trd.2024.104315","article-title":"Nonlinear Associations of Built Environments around Residences and Workplaces with Commuting Satisfaction","volume":"133","author":"Chen","year":"2024","journal-title":"Transp. Res. Part-Transp. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"103930","DOI":"10.1016\/j.trd.2023.103930","article-title":"Using Machine-Learning Models to Understand Nonlinear Relationships between Land Use and Travel","volume":"123","author":"Cao","year":"2023","journal-title":"Transp. Res. Part-Transp. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"241","DOI":"10.5198\/jtlu.2024.2434","article-title":"The Nonlinear Impact of Cycling Environment on Bicycle Distance: A Perspective Combining Objective and Perceptual Dimensions","volume":"17","author":"Zhang","year":"2024","journal-title":"J. Transp. Land Use"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1007\/s12469-024-00371-w","article-title":"Predicting Travel Demand of a Bike Sharing System Using Graph Convolutional Neural Networks","volume":"17","author":"Behroozi","year":"2025","journal-title":"Public Transp."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Gu, W., Zhang, Z., and Liu, O. (2025). Social Factors Influencing Healthcare Expenditures: A Machine Learning Perspective on Australia\u2019s Fiscal Challenges. Smart Cities, 8.","DOI":"10.3390\/smartcities8030097"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1177\/03611981221074371","article-title":"Short-Term Travel-Time Prediction Using Support Vector Machine and Nearest Neighbor Method","volume":"2676","author":"Meng","year":"2022","journal-title":"Transp. Res. Rec."},{"key":"ref_58","first-page":"1","article-title":"Prediction of Traffic Time Using XGBoost Model with Hyperparameter Optimization","volume":"1","author":"Deepika","year":"2025","journal-title":"Multimed. Tools Appl."},{"key":"ref_59","unstructured":"Lundberg, S., and Lee, S.-I. (2017, January 4). A Unified Approach to Interpreting Model Predictions. Proceedings of the 31st International Conference on Neural Information Processing Systems (NIPS\u201917), Red Hook, NY, USA."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"106617","DOI":"10.1016\/j.aap.2022.106617","article-title":"On the Interpretability of Machine Learning Methods in Crash Frequency Modeling and Crash Modification Factor Development","volume":"168","author":"Wen","year":"2022","journal-title":"Accid. Anal. Prev."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"103789","DOI":"10.1016\/j.tra.2023.103789","article-title":"Spatial-Temporal Heterogeneity and Built Environment Nonlinearity in Inconsiderate Parking of Dockless Bike-Sharing","volume":"175","author":"Wang","year":"2023","journal-title":"Transp. Res. Part Policy Pract."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1177\/03611981231225654","article-title":"Trip Purpose Inference and Spatio-Temporal Characterization Based on Anonymized Trip Data: Empirical Study from Dockless Shared Bicycle Dataset in Xi\u2019an, China","volume":"2678","author":"Wang","year":"2024","journal-title":"Transp. Res. Rec. J. Transp. Res. Board"},{"key":"ref_63","first-page":"652","article-title":"A Scientometric Review of Research on Built Environment Influence on Public Transportation Demand","volume":"12","author":"Shi","year":"2025","journal-title":"J. Traffic Transp. Eng. Engl. Ed."},{"key":"ref_64","first-page":"100260","article-title":"Relationships between Density, Transit, and Household Expenditures in Small Urban Areas","volume":"8","author":"Mattson","year":"2020","journal-title":"Transp. Res. Interdiscip. Perspect."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Gao, C., Li, S., Sun, M., Zhao, X., and Liu, D. (2024). Exploring the Relationship between Urban Vibrancy and Built Environment Using Multi-Source Data: Case Study in Munich. Remote Sens., 16.","DOI":"10.3390\/rs16061107"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Guo, L., Cheng, W., Liu, C., Zhang, Q., and Yang, S. (2023). Exploring the Spatial Heterogeneity and Influence Factors of Daily Travel Carbon Emissions in Metropolitan Areas: From the Perspective of the 15-Min City. Land, 12.","DOI":"10.3390\/land12020299"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"652","DOI":"10.1016\/j.foar.2021.03.005","article-title":"Measuring the Built Environment of Green Transit-Oriented Development: A Factor-Cluster Analysis of Rail Station Areas in Singapore","volume":"10","author":"Niu","year":"2021","journal-title":"Front. Archit. Res."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"105191","DOI":"10.1016\/j.landurbplan.2024.105191","article-title":"Optimized Green Infrastructure Planning at the City Scale Based on an Interpretable Machine Learning Model and Multi-Objective Optimization Algorithm: A Case Study of Central Beijing, China","volume":"252","author":"Chen","year":"2024","journal-title":"Landsc. Urban Plan."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1007\/s11709-024-1015-0","article-title":"Prediction of Vertical Displacement for a Buried Pipeline Subjected to Normal Fault Using a Hybrid FEM-ANN Approach","volume":"18","author":"Jalali","year":"2024","journal-title":"Front. Struct. Civ. Eng."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/14\/9\/333\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:34:07Z","timestamp":1760034847000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/14\/9\/333"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,27]]},"references-count":69,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2025,9]]}},"alternative-id":["ijgi14090333"],"URL":"https:\/\/doi.org\/10.3390\/ijgi14090333","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,27]]}}}