This comprehensive handbook covers human mobility within urban contexts, integrating academic theories with pragmatic insights and offering a detailed analysis of the diverse facets of human mobility and its substantial impact on the urban landscape, economy, and societal structures. It explains key fundamental concepts, methods, and models, presenting an in-depth exploration of predictive analytics, clustering patterns, advanced trajectory embedding techniques, artificial intelligence, machine learning, geographic information systems (GIS), Internet of Things (IoT), and smart city innovations. The authors include many case studies and examples of urban mobility in practice, making the content relatable and practical for educators, students, researchers, and practitioners.
Features
Urban Human Mobility: Practices, Analytics, and Strategies for Smart Cities is for professionals, academics, and upper-level undergraduate and graduate students in the fields of urban planning/design, GIScience, data mining, and social sciences.
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Dr. Xiao Huang is an assistant professor in the Department of Environmental Sciences at Emory University. His research expertise encompasses human-environment interaction, computational social sciences, urban informatics, disaster mapping and mitigation, geospatial artificial intelligence (GeoAI), and disaster remote sensing. Dr. Huang has contributed extensively to his field, authoring over 200 peer-reviewed journal articles and over 20 book chapters and playing a pivotal role in editing five books. He is among the World's Top 2% Scientists by Stanford/Elsevier's rankings. In his professional capacity, he serves as an associate editor for Computational Urban Science and is a member of the editorial board for several prestigious journals. Dr. Huang's research has garnered significant attention and received coverage in renowned media outlets such as Nature News, NASA, NBC, and Fox. His work has attracted substantial funding from NSF, NASA, the Bill and Melinda Gates Foundation, the National Academies, and the Centers for Medicare and Medicaid Services.
Dr. Xinyue Ye is the Harold Adams Endowed Professor in Urban Informatics and Stellar Faculty Provost Target Hire at Texas A&M University (TAMU). His research integrates computational social science, urban data science, and GeoAI to address issues ranging from infrastructure resilience and climate change to social justice and community perceptions, underscoring the dynamic interplay between technology, policy, and human behavior in shaping sustainable and livable cities. Dr. Ye was named one of the top 10 young scientists by the World Geospatial Developers Conference in 2021. His work has been funded by the National Academies, National Science Foundation, National Institutes of Health, National Institute of Justice, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, Department of Commerce, Department of Defense, Department of Energy, Department of Health and Human Services, Department of Housing and Urban Development, Department of Transportation, Department of the Treasury, Microsoft, Baptist Health Foundation, Robert Wood Johnson Foundation, and the Canada Social Sciences and Humanities Research Council.
Dr. Kathleen Stewart is a professor in the Department of Geographical Sciences and director of the Center for Geospatial Information Science. She works in the area of geographic information science with a particular focus on geospatial dynamics. She investigates movement and mobility for a number of different application domains, for example, health and transportation where movement patterns or behaviors and spatial access are key topics. Her research is supported in part by grants from the National Institutes of Health, the National Science Foundation, the Federal Highway Administration, and Maryland Department of Natural Resources, among other organizations. Dr. Stewart serves as a member of the National Geospatial Advisory Committee (NGAC), a federal advisory committee sponsored by the Department of the Interior. She served on the Mapping Science Committee of the National Academies of Sciences, Engineering and Medicine (2016-2023). She is a fellow of the University Consortium of Geographic Information Science (UCGIS) and a member of the editorial boards of The International Journal of Geographical Information Science (IJGIS), Geographical Analysis, Journal of Spatial Information Science (JOSIS), and International Journal of Geo-Information and Geomatics, among others.
Dr. Subasish Das is an assistant professor of the Civil Engineering Program in the Ingram School of Engineering at Texas State University. He is also involved with Texas A&M Transportation Institute (TTI) as a part-time associate research scientist. He has more than 13 years of experience related to roadway safety, traffic operation, and connected and automated vehicle (CAV) technologies. He is a systems engineer by training, with hands-on experience in Six Sigma and Lean Engineering. His major areas of expertise include database management, statistical analysis, and machine learning with emphasis on safety and transportation operations, spatial analysis with modern web GIS tools, interactive data visualization, and deep learning tools for CAV technologies. Dr. Das is a prolific author. He has published more than 160 technical reports and journal articles. He is the author of the book Artificial Intelligence in Highway Safety, which was published by CRC Press in 2022. The AASHTO Research Advisory Committee (RAC) awarded one of his research reports as 2014 AASHTO Sweet Sixteen High Value Research Project. Dr. Das is an active member of ITE and ASCE. He is an Eno Fellow. He served as vice president of membership of the Young Professionals in Transportation Houston chapter. He is currently a member of three TRB Committees: Information and Knowledge Management (AJE45), Artificial Intelligence and Advanced Computing Applications (AED50), and Impairment in Transportation (ACS50).
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Hardcover. Etat : new. Hardcover. This comprehensive handbook covers human mobility within urban contexts, integrating academic theories with pragmatic insights and offering a detailed analysis of the diverse facets of human mobility and its substantial impact on the urban landscape, economy, and societal structures. It explains key fundamental concepts, methods, and models, presenting an in-depth exploration of predictive analytics, clustering patterns, advanced trajectory embedding techniques, artificial intelligence, machine learning, geographic information systems (GIS), Internet of Things (IoT), and smart city innovations. The authors include many case studies and examples of urban mobility in practice, making the content relatable and practical for educators, students, researchers, and practitioners.FeaturesProvides a multidisciplinary and holistic understanding of urban mobility with systematic introductions and discussions of theory, methods, technologies, tools, and applicationsCovers a wide range of real-world case studies of urban mobility in practice globally that include data, programming code, and toolsDiscusses cutting-edge technologies involved in mobility data analyticsAddresses practical challenges in data collection and the ethical implications of mobility research, which are crucial for professionals in the fieldOffers future directions of human mobility research under the big data and artificial intelligence (AI) revolutionUrban Human Mobility: Practices, Analytics, and Strategies for Smart Cities is for professionals, academics, and upper-level undergraduate and graduate students in the fields of urban planning/design, GIScience, data mining, and social sciences. This comprehensive handbook covers human mobility within urban contexts, integrating academic theories with pragmatic insights offering a detailed analysis of the diverse facets of human mobility and its substantial impact on the urban landscape, economy, and societal structures. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781032821627
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Hardcover. Etat : new. Hardcover. This comprehensive handbook covers human mobility within urban contexts, integrating academic theories with pragmatic insights and offering a detailed analysis of the diverse facets of human mobility and its substantial impact on the urban landscape, economy, and societal structures. It explains key fundamental concepts, methods, and models, presenting an in-depth exploration of predictive analytics, clustering patterns, advanced trajectory embedding techniques, artificial intelligence, machine learning, geographic information systems (GIS), Internet of Things (IoT), and smart city innovations. The authors include many case studies and examples of urban mobility in practice, making the content relatable and practical for educators, students, researchers, and practitioners.FeaturesProvides a multidisciplinary and holistic understanding of urban mobility with systematic introductions and discussions of theory, methods, technologies, tools, and applicationsCovers a wide range of real-world case studies of urban mobility in practice globally that include data, programming code, and toolsDiscusses cutting-edge technologies involved in mobility data analyticsAddresses practical challenges in data collection and the ethical implications of mobility research, which are crucial for professionals in the fieldOffers future directions of human mobility research under the big data and artificial intelligence (AI) revolutionUrban Human Mobility: Practices, Analytics, and Strategies for Smart Cities is for professionals, academics, and upper-level undergraduate and graduate students in the fields of urban planning/design, GIScience, data mining, and social sciences. This comprehensive handbook covers human mobility within urban contexts, integrating academic theories with pragmatic insights offering a detailed analysis of the diverse facets of human mobility and its substantial impact on the urban landscape, economy, and societal structures. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781032821627
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