{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T00:21:01Z","timestamp":1789172461280,"version":"build-2803163510"},"reference-count":115,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,4,20]],"date-time":"2023-04-20T00:00:00Z","timestamp":1681948800000},"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":["41971348"],"award-info":[{"award-number":["41971348"]}],"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":["220100010"],"award-info":[{"award-number":["220100010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Hubei Luojia Laboratory","award":["41971348"],"award-info":[{"award-number":["41971348"]}]},{"name":"Hubei Luojia Laboratory","award":["220100010"],"award-info":[{"award-number":["220100010"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Driving analysis of urban expansion (DAUE) is usually implemented to identify the driving factors and their corresponding driving effects\/mechanisms for the expansion processes of urban land, aiming to provide scientific guidance for urban planning and management. Based on a thorough analysis and summarization of the development process and quantitative models, four major limitations in existing DAUE studies have been uncovered: (1) the interactions in hierarchical urban systems have not been fully explored; (2) the employed data cannot fully depict urban dynamic through finer social perspectives; (3) the employed models cannot deal with high-level feature correlations; and (4) the simulation and analysis models are still not intrinsically integrated. Four future directions are thus proposed: (1) to pay attention to the hierarchical characteristics of urban systems and conduct multi-scale research on the complex interactions within them to capture dynamic features; (2) to leverage remote sensing data so as to obtain diverse urban expansion data and assimilate multi-source spatiotemporal big data to supplement novel socio-economic driving factors; (3) to integrate with interpretable data-driven machine learning techniques to bolster the performance and reliability of DAUE models; and (4) to construct mechanism-coupled urban simulation to achieve a complementary enhancement and facilitate theory development and testing for urban land systems.<\/jats:p>","DOI":"10.3390\/ijgi12040174","type":"journal-article","created":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T01:33:43Z","timestamp":1682040823000},"page":"174","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Development Process, Quantitative Models, and Future Directions in Driving Analysis of Urban Expansion"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0865-3850","authenticated-orcid":false,"given":"Xuefeng","family":"Guan","sequence":"first","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Hubei Luojia Laboratory, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingbo","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5152-2165","authenticated-orcid":false,"given":"Changlan","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiran","family":"Xing","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,20]]},"reference":[{"key":"ref_1","unstructured":"Ritchie, H., and Roser, M. (2022, May 16). Urbanization. Available online: https:\/\/ourworldindata.org\/urbanization."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.cities.2018.06.014","article-title":"Effects of urban planning in guiding urban growth: Evidence from Shenzhen, China","volume":"83","author":"Deng","year":"2018","journal-title":"Cities"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/j.scitotenv.2019.04.080","article-title":"Urban sprawl in China: Differences and socioeconomic drivers","volume":"673","author":"Li","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"102099","DOI":"10.1016\/j.habitatint.2019.102099","article-title":"The spatial restructuring and determinants of industrial landscape in a mega city under rapid urbanization","volume":"95","author":"Fan","year":"2020","journal-title":"Habitat Int."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"105189","DOI":"10.1016\/j.landusepol.2020.105189","article-title":"Urban expansion and forest reserves: Drivers of change and persistence on the coast of S\u00e3o Paulo State (Brazil)","volume":"101","author":"Hersperger","year":"2021","journal-title":"Land Use Policy"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.apgeog.2017.06.026","article-title":"Urbanization on the Mongolian Plateau after economic reform: Changes and causes","volume":"86","author":"Park","year":"2017","journal-title":"Appl. Geogr."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.landurbplan.2018.03.004","article-title":"The varying driving forces of urban expansion in China: Insights from a spatial-temporal analysis","volume":"174","author":"Li","year":"2018","journal-title":"Landsc. Urban Plan."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"101569","DOI":"10.1016\/j.compenvurbsys.2020.101569","article-title":"Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: A case study in Wuhan, China","volume":"85","author":"Liang","year":"2021","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1146\/annurev.energy.28.050302.105459","article-title":"Dynamics of land-use and land-cover change in tropical regions","volume":"28","author":"Lambin","year":"2003","journal-title":"Annu. Rev. Environ. Resour."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1007\/s13280-015-0699-8","article-title":"Meta-studies in land use science: Current coverage and prospects","volume":"45","author":"Magliocca","year":"2016","journal-title":"Ambio"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"103733","DOI":"10.1016\/j.landurbplan.2019.103733","article-title":"The peri-urbanization of Europe: A systematic review of a multifaceted process","volume":"196","author":"Shaw","year":"2020","journal-title":"Landsc. Urban Plan."},{"key":"ref_12","first-page":"60","article-title":"Cellular automata for urban growth modelling: A review on factors defining transition rules","volume":"4","author":"Wahyudi","year":"2016","journal-title":"Int. Rev. Spat. Plan. Sustain. Dev."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.gloenvcha.2018.05.001","article-title":"Urban land-use change: The role of strategic spatial planning","volume":"51","author":"Hersperger","year":"2018","journal-title":"Glob. Environ. Change"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"246","DOI":"10.3390\/land9080246","article-title":"A review of driving factors, scenarios, and topics in urban land change models","volume":"9","year":"2020","journal-title":"Land"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"105232","DOI":"10.1016\/j.landusepol.2020.105232","article-title":"Explaining Objective Forces, Driving Forces, and Causal Mechanisms Affecting the Formation and Expansion of the Peri-Urban Areas: A Critical Realism Approach","volume":"102","author":"Dadashpoor","year":"2021","journal-title":"Land Use Policy"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/j.landusepol.2018.08.017","article-title":"What drives land take and urban land expansion? A systematic review","volume":"79","author":"Colsaet","year":"2018","journal-title":"Land Use Policy"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"772","DOI":"10.1080\/01441647.2016.1168887","article-title":"Long-term impacts of transport infrastructure networks on land-use change: An international review of empirical studies","volume":"36","author":"Kasraian","year":"2016","journal-title":"Transp. Rev."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1146\/annurev-environ-100809-125336","article-title":"The new geography of contemporary urbanization and the environment","volume":"35","author":"Seto","year":"2010","journal-title":"Annu. Rev. Environ. Resour."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Seto, K.C., Fragkias, M., G\u00fcneralp, B., and Reilly, M.K. (2011). A meta-analysis of global urban land expansion. PLoS ONE, 6.","DOI":"10.1371\/journal.pone.0023777"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2307\/1907683","article-title":"Economic Change and Rural-Urban Land Conversions","volume":"29","author":"Muth","year":"1961","journal-title":"Econometrica"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.cities.2018.02.001","article-title":"Suburban industrial land development in transitional China: Spatial restructuring and determinants","volume":"78","author":"Zhang","year":"2018","journal-title":"Cities"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2307\/3144884","article-title":"The Nature and Economics of Urban Sprawl","volume":"41","author":"Harvey","year":"1965","journal-title":"Land Econ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1177\/016001700761012710","article-title":"Urban sprawl: Diagnosis and remedies","volume":"23","author":"Brueckner","year":"2000","journal-title":"Int. Reg. Sci. Rev."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Tang, W., Zhou, T., Sun, J., Li, Y., and Li, W. (2017). Accelerated urban expansion in Lhasa City and the implications for sustainable development in a Plateau City. Sustainability, 9.","DOI":"10.3390\/su9091499"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1007\/s12665-016-5926-5","article-title":"Analyses of traits and driving forces on urban land expansion in a typical coal-resource-based city in a loess area","volume":"75","author":"Cao","year":"2016","journal-title":"Environ. Earth Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.landurbplan.2016.03.011","article-title":"Capturing the varying effects of driving forces over time for the simulation of urban growth by using survival analysis and cellular automata","volume":"152","author":"Chen","year":"2016","journal-title":"Landsc. Urban Plan."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1007\/s10661-017-6224-8","article-title":"Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change","volume":"189","author":"Feng","year":"2017","journal-title":"Environ. Monit. Assess."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.compenvurbsys.2019.04.010","article-title":"How much can temporally stationary factors explain cellular automata-based simulations of past and future urban growth?","volume":"76","author":"Feng","year":"2019","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1080\/15481603.2018.1507074","article-title":"Multiple intra-urban land use simulations and driving factors analysis: A case study in Huicheng, China","volume":"56","author":"Zhang","year":"2019","journal-title":"GISci. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.landurbplan.2014.08.015","article-title":"A comparative analysis of megacity expansions in China and the U.S.: Patterns, rates and driving forces","volume":"132","author":"Kuang","year":"2014","journal-title":"Landsc. Urban Plan."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Subasinghe, S., Estoque, R.C., and Murayama, Y. (2016). Spatiotemporal analysis of urban growth using GIS and remote sensing: A case study of the Colombo metropolitan area, Sri Lanka. ISPRS Int. J. Geo-Inf., 5.","DOI":"10.3390\/ijgi5110197"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Lu, D., Li, L., Li, G., Fan, P., Ouyang, Z., and Moran, E. (2018). Examining spatial patterns of urban distribution and impacts of physical conditions on urbanization in coastal and inland metropoles. Remote Sens., 10.","DOI":"10.3390\/rs10071101"},{"key":"ref_33","first-page":"366","article-title":"Research on the influence of site factors on the expansion of construction land in the Pearl River Delta, China: By using GIS and remote sensing","volume":"21","author":"Ye","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"102696","DOI":"10.1016\/j.jtrangeo.2020.102696","article-title":"A multi-decade longitudinal analysis of transportation and land use co-evolution in the Greater Toronto-Hamilton Area","volume":"84","author":"Kasraian","year":"2020","journal-title":"J. Transp. Geogr."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Lei, H., Koch, J., and Shi, H. (2020). An analysis of spatio-temporal urbanization patterns in Northwest China. Land, 9.","DOI":"10.3390\/land9110411"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.habitatint.2015.09.007","article-title":"Urban land use change and regional access: A case study in Beijing, China","volume":"51","author":"Deng","year":"2016","journal-title":"Habitat Int."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.habitatint.2018.09.001","article-title":"Exploring the relationship between spatial driving forces of urban expansion and socioeconomic segregation: The case of Shiraz","volume":"81","author":"Azhdari","year":"2018","journal-title":"Habitat Int."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Arellano, M. (2003). Panel Data Econometrics, OUP Oxford.","DOI":"10.1093\/0199245282.001.0001"},{"key":"ref_39","unstructured":"Baltagi, B.H. (2008). Econometric Analysis of Panel Data, John Wiley & Sons. [6th ed.]."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1594","DOI":"10.1177\/0042098015577773","article-title":"Determinants of urban sprawl in European cities","volume":"52","author":"Oueslati","year":"2015","journal-title":"Urban Stud."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.habitatint.2015.11.040","article-title":"Urban land expansion and the transitional mechanisms in Nanjing, China","volume":"53","author":"Chen","year":"2016","journal-title":"Habitat Int."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.landurbplan.2012.08.008","article-title":"Multi-level modeling of urban expansion and cultivated land conversion for urban hotspot counties in China","volume":"108","author":"Jiang","year":"2012","journal-title":"Landsc. Urban Plan."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Liao, C., Dai, T., Cai, H., and Zhang, W. (2017). Examining the driving factors causing rapid urban expansion in China: An analysis based on GlobeLand30 data. ISPRS Int. J. Geo-Inf., 6.","DOI":"10.3390\/ijgi6090264"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1080\/1747423X.2015.1117530","article-title":"Approaches and terminology for causal analysis in land systems science","volume":"11","author":"Meyfroidt","year":"2016","journal-title":"J. Land Use Sci."},{"key":"ref_45","unstructured":"Thomas, H. (2008). Chemical Engineer, Guilford Publications."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"2880","DOI":"10.1177\/0042098013513649","article-title":"Land use change and economic growth in urban China: A structural equation analysis","volume":"51","author":"He","year":"2014","journal-title":"Urban Stud."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"104424","DOI":"10.1016\/j.landusepol.2019.104424","article-title":"Exploring the mechanism of border effect on urban land expansion: A case study of Beijing-Tianjin-Hebei region in China","volume":"92","author":"Wang","year":"2020","journal-title":"Land Use Policy"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"05018018","DOI":"10.1061\/(ASCE)UP.1943-5444.0000480","article-title":"Administrative-Hierarchical Urban Land Expansion in China: Urban Agglomeration in the Yangtze River Delta","volume":"144","author":"Zhou","year":"2018","journal-title":"J. Urban Plan. Dev."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"100840","DOI":"10.1016\/j.retrec.2020.100840","article-title":"Did high-speed railway cause urban space expansion?\u2014Empirical evidence from China\u2019s prefecture-level cities","volume":"80","author":"Deng","year":"2020","journal-title":"Res. Transp. Econ."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"979","DOI":"10.1001\/jama.2019.10347","article-title":"Will the Development of a High-Speed Railway Have Impacts on Land Use Patterns in China?","volume":"109","author":"Zhang","year":"2019","journal-title":"Ann. Am. Assoc. Geogr."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Angrist, J.D., and Pischke, J.-S. (2008). Mostly Harmless Econometrics: An Empiricist\u2019s Companion, Princeton University Press.","DOI":"10.2307\/j.ctvcm4j72"},{"key":"ref_52","first-page":"116","article-title":"Geodetector: Principle and prospective","volume":"72","author":"Wang","year":"2017","journal-title":"Acta Geogr. Sin."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.cities.2018.01.001","article-title":"Addressing the rural in situ urbanization (RISU) in the Beijing\u2013Tianjin\u2013Hebei region: Spatio-temporal pattern and driving mechanism","volume":"75","author":"Zhou","year":"2018","journal-title":"Cities"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Liu, Y., Cao, X., and Li, T. (2020). Identifying driving forces of built-up land expansion based on the geographical detector: A case study of pearl river delta urban agglomeration. Int. J. Environ. Res. Public Health, 17.","DOI":"10.3390\/ijerph17051759"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Yan, Y., Ju, H., Zhang, S., and Jiang, W. (2020). Spatiotemporal patterns and driving forces of urban expansion in coastal areas: A study on urban agglomeration in the pearl river delta, China. Sustainability, 12.","DOI":"10.3390\/su12010191"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Zhang, J., Yu, L., Li, X., Zhang, C., Shi, T., Wu, X., Yang, C., Gao, W., Li, Q., and Wu, G. (2020). Exploring annual urban expansions in the Guangdong-Hong Kong-Macau Greater Bay Area: Spatiotemporal features and driving factors in 1986\u20132017. Remote Sens., 12.","DOI":"10.3390\/rs12162615"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"813","DOI":"10.1177\/0042098009349770","article-title":"Economic growth and the expansion of urban land in China","volume":"47","author":"Deng","year":"2010","journal-title":"Urban Stud."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"118061","DOI":"10.1016\/j.jclepro.2019.118061","article-title":"Spatiotemporal characteristics and driving forces of urban sprawl in China during 2003\u20132017","volume":"241","author":"Feng","year":"2019","journal-title":"J. Clean. Prod."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1080\/17421772.2016.1126674","article-title":"The Causes of Urban Sprawl in Spanish Urban Areas: A Spatial Approach","volume":"11","author":"Li","year":"2016","journal-title":"Spat. Econ. Anal."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"8856","DOI":"10.3390\/su6128856","article-title":"Urban land expansion and spatial dynamics in Globalizing Shanghai","volume":"6","author":"Li","year":"2014","journal-title":"Sustainability"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.apgeog.2014.11.029","article-title":"Administrative hierarchy and urban land expansion in transitional China","volume":"56","author":"Li","year":"2015","journal-title":"Appl. Geogr."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"234","DOI":"10.2307\/143141","article-title":"A Computer Movie Simulating Urban Growth in the Detroit Region","volume":"46","author":"Tobler","year":"1970","journal-title":"Econ. Geogr."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.landurbplan.2008.11.010","article-title":"Modeling spatial variations of urban growth patterns in Chinese cities: The case of Nanjing","volume":"91","author":"Luo","year":"2009","journal-title":"Landsc. Urban Plan."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Jing, S., Yan, Y., Niu, F., and Song, W. (2022). Urban Expansion in China: Spatiotemporal Dynamics and Determinants. Land, 11.","DOI":"10.3390\/land11030356"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"801","DOI":"10.1007\/s00477-012-0620-y","article-title":"Modeling determinants of urban growth in Dongguan, China: A spatial logistic approach","volume":"28","author":"Liao","year":"2014","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1007\/s11442-020-1729-4","article-title":"Urban expansion patterns and their driving forces based on the center of gravity-GTWR model: A case study of the Beijing-Tianjin-Hebei urban agglomeration","volume":"30","author":"Wang","year":"2020","journal-title":"J. Geogr. Sci."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.regsciurbeco.2013.10.005","article-title":"Geographically and temporally weighted likelihood regression: Exploring the spatiotemporal determinants of land use change","volume":"44","author":"Wrenn","year":"2014","journal-title":"Reg. Sci. Urban Econ."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"101459","DOI":"10.1016\/j.compenvurbsys.2020.101459","article-title":"Modeling urban growth using spatially heterogeneous cellular automata models: Comparison of spatial lag, spatial error and GWR","volume":"81","author":"Gao","year":"2020","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"142591","DOI":"10.1016\/j.scitotenv.2020.142591","article-title":"The varying driving forces of urban land expansion in China: Insights from a spatial-temporal analysis","volume":"766","author":"Wu","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1080\/13658810802672469","article-title":"Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices","volume":"24","author":"Huang","year":"2010","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1111\/gean.12071","article-title":"Geographical and Temporal Weighted Regression (GTWR)","volume":"47","author":"Fotheringham","year":"2015","journal-title":"Geogr. Anal."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.isprsjprs.2016.01.011","article-title":"Random forest in remote sensing: A review of applications and future directions","volume":"114","author":"Belgiu","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"119959","DOI":"10.1016\/j.jclepro.2020.119959","article-title":"Characterizing spatial patterns and driving forces of expansion and regeneration of industrial regions in the Hangzhou megacity, China","volume":"253","author":"Huang","year":"2020","journal-title":"J. Clean. Prod."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1016\/j.landusepol.2017.06.020","article-title":"Urban expansion in 30 megacities of China: Categorizing the driving force profiles to inform the urbanization policy","volume":"68","author":"You","year":"2017","journal-title":"Land Use Policy"},{"key":"ref_75","unstructured":"Molnar, C. (2023, April 08). Interpretable Machine Learning. Available online: https:\/\/christophm.github.io\/interpretable-ml-book\/."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.gloenvcha.2018.08.006","article-title":"Middle-range theories of land system change","volume":"53","author":"Meyfroidt","year":"2018","journal-title":"Glob. Environ. Change"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.apgeog.2018.07.002","article-title":"What drives urban growth in China? A multi-scale comparative analysis","volume":"98","author":"Li","year":"2018","journal-title":"Appl. Geogr."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"7687","DOI":"10.1073\/pnas.1117622109","article-title":"Urban land teleconnections and sustainability","volume":"109","author":"Seto","year":"2012","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"119","DOI":"10.7551\/mitpress\/9780262026901.003.0007","article-title":"Applications of the telecoupling framework to land-change science","volume":"14","author":"Liu","year":"2014","journal-title":"Rethink. Glob. Land Use Urban Era"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1111\/pirs.12340","article-title":"A spatial panel data analysis of China\u2019s urban land expansion, 2004\u20132014","volume":"98","author":"Li","year":"2019","journal-title":"Pap. Reg. Sci."},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Chen, B., Wu, C., Huang, X., and Yang, X. (2020). Examining the relationship between urban land expansion and economic linkage using coupling analysis: A case study of the Yangtze River Economic Belt, China. Sustainability, 12.","DOI":"10.3390\/su12031227"},{"key":"ref_82","doi-asserted-by":"crossref","unstructured":"Tan, R., Zhou, K., He, Q., and Xu, H. (2016). Analyzing the effects of spatial interaction among city clusters on urban growth-case of Wuhan Urban agglomeration. Sustainability, 8.","DOI":"10.3390\/su8080759"},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"104687","DOI":"10.1016\/j.landusepol.2020.104687","article-title":"Telecoupling mechanism of urban land expansion based on transportation accessibility: A case study of transitional Yangtze River economic Belt, China","volume":"96","author":"Wu","year":"2020","journal-title":"Land Use Policy"},{"key":"ref_84","first-page":"109","article-title":"A Quantitative Evaluation of Major Factors Influencing Urban Land Development in a Regional Cluster","volume":"22","author":"Weiss","year":"1968","journal-title":"Traffic Q."},{"key":"ref_85","first-page":"100","article-title":"Satellite scatterometer estimation of urban built-up volume: Validation with airborne lidar data","volume":"77","author":"Mathews","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"111859","DOI":"10.1016\/j.rse.2020.111859","article-title":"Continental-scale mapping and analysis of 3D building structure","volume":"245","author":"Li","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"1705","DOI":"10.3390\/rs6021705","article-title":"Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data","volume":"6","author":"Shi","year":"2014","journal-title":"Remote Sens."},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Stevens, F.R., Gaughan, A.E., Linard, C., and Tatem, A.J. (2015). Disaggregating census data for population mapping using Random forests with remotely-sensed and ancillary data. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0107042"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1080\/00045608.2015.1018773","article-title":"Social Sensing: A New Approach to Understanding Our Socioeconomic Environments","volume":"105","author":"Liu","year":"2015","journal-title":"Ann. Assoc. Am. Geogr."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/s10708-007-9111-y","article-title":"Citizens as sensors: The world of volunteered geography","volume":"69","author":"Goodchild","year":"2007","journal-title":"GeoJournal"},{"key":"ref_91","first-page":"1875","article-title":"Sensing Urban Dynamics by Fusing Multi-sourced Spatiotemporal Big Data","volume":"45","author":"Tu","year":"2020","journal-title":"Wuhan Daxue Xuebao (Xinxi Kexue Ban)\/Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1080\/00343404.2021.1955098","article-title":"Network capital and urban development: An inter-urban capital flow network analysis","volume":"56","author":"Shi","year":"2022","journal-title":"Reg. Stud."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"7735","DOI":"10.1073\/pnas.1802537115","article-title":"Urban mobility and neighborhood isolation in America\u2019s 50 largest cities","volume":"115","author":"Wang","year":"2018","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"101827","DOI":"10.1016\/j.compenvurbsys.2022.101827","article-title":"Investigating the spatiotemporal pattern between the built environment and urban vibrancy using big data in Shenzhen, China","volume":"95","author":"Chen","year":"2022","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"103869","DOI":"10.1016\/j.scs.2022.103869","article-title":"Aggravated social segregation during the COVID-19 pandemic: Evidence from crowdsourced mobility data in twelve most populated U.S. metropolitan areas","volume":"81","author":"Li","year":"2022","journal-title":"Sustain. Cities Soc."},{"key":"ref_96","first-page":"5363","article-title":"A Hybrid Deep Learning-Based Unsupervised Anomaly Detection in High Dimensional Data","volume":"70","author":"Muneer","year":"2022","journal-title":"Comput. Mater. Contin."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1007\/s13735-019-00183-w","article-title":"A survey of traditional and deep learning-based feature descriptors for high dimensional data in computer vision","volume":"9","author":"Georgiou","year":"2020","journal-title":"Int. J. Multimed. Inf. Retr."},{"key":"ref_98","first-page":"5668","article-title":"Revisiting spatial-temporal similarity: A deep learning framework for traffic prediction","volume":"33","author":"Yao","year":"2019","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.isprsjprs.2019.04.015","article-title":"Deep learning in remote sensing applications: A meta-analysis and review","volume":"152","author":"Ma","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"153559","DOI":"10.1016\/j.scitotenv.2022.153559","article-title":"Machine learning in modelling land-use and land cover-change (LULCC): Current status, challenges and prospects","volume":"822","author":"Wang","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_101","first-page":"417","article-title":"Interpretable Machine Learning\u2014A Brief History, State-of-the-Art and Challenges","volume":"1323","author":"Molnar","year":"2020","journal-title":"Commun. Comput. Inf. Sci."},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1145\/3359786","article-title":"Techniques for interpretable machine learning","volume":"63","author":"Du","year":"2020","journal-title":"Commun. ACM"},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1109\/JPROC.2021.3060483","article-title":"Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications","volume":"109","author":"Samek","year":"2021","journal-title":"Proc. IEEE"},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"612","DOI":"10.1109\/JPROC.2021.3058954","article-title":"Toward Causal Representation Learning","volume":"109","author":"Scholkopf","year":"2021","journal-title":"Proc. IEEE"},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1038\/s41586-019-0912-1","article-title":"Deep learning and process understanding for data-driven Earth system science","volume":"566","author":"Reichstein","year":"2019","journal-title":"Nature"},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"869","DOI":"10.5194\/gmd-16-869-2023","article-title":"AttentionFire_v1.0: Interpretable machine learning fire model for burned-Area predictions over tropics","volume":"16","author":"Li","year":"2023","journal-title":"Geosci. Model Dev."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"101457","DOI":"10.1016\/j.compenvurbsys.2019.101457","article-title":"Modelling multi-regional urban growth with multilevel logistic cellular automata","volume":"80","author":"Shu","year":"2020","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/0304-3800(94)00151-0","article-title":"CLUE: A conceptual model to study the conversion of land use and its effects","volume":"85","author":"Veldkamp","year":"1996","journal-title":"Ecol. Model."},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.landurbplan.2017.09.019","article-title":"A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects","volume":"168","author":"Liu","year":"2017","journal-title":"Landsc. Urban Plan."},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1080\/136588198241617","article-title":"; Gaydos, L.J. Loose-coupling a cellular automaton model and GIS: Long-term urban growth prediction for San Francisco and Washington\/Baltimore","volume":"12","author":"Clarke","year":"1998","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_111","first-page":"329","article-title":"Simulation model of land use dynamics and application: Progress and prospects","volume":"21","author":"Li","year":"2017","journal-title":"Yaogan Xuebao\/J. Remote Sens."},{"key":"ref_112","first-page":"1884","article-title":"Applications and New Trends of Machine Learning in Urban Simulation Research","volume":"45","author":"Chen","year":"2020","journal-title":"Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"104430","DOI":"10.1016\/j.cageo.2020.104430","article-title":"A novel cellular automata model integrated with deep learning for dynamic spatio-temporal land use change simulation","volume":"137","author":"Xing","year":"2020","journal-title":"Comput. Geosci."},{"key":"ref_114","first-page":"1","article-title":"Science Mapping: A Systematic Review of the Literature","volume":"2","author":"Chen","year":"2017","journal-title":"J. Data Inf. Sci."},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1023\/A:1024940629314","article-title":"Bursty and hierarchical structure in streams","volume":"7","author":"Kleinberg","year":"2003","journal-title":"Data Min. Knowl. Discov."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/12\/4\/174\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:20:13Z","timestamp":1760124013000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/12\/4\/174"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,20]]},"references-count":115,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["ijgi12040174"],"URL":"https:\/\/doi.org\/10.3390\/ijgi12040174","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,20]]}}}