GIS4113 GIS6104 Spatial Networks Dr. Yujie Hu, yujiehu@ufl.edu Course Description Many real-world systems can be represented as networks of many interacting components. This course teaches the fundamental concepts, models, and techniques for describing, visualizing, measuring, and analyzing networks. It also introduces their applications in geography, transportation, social science, etc. A series of labs using popular […]
GEO4700 GEO6706 Transportation Geography Course Description Introduces the history and evolution of transportation systems, and essential concepts, theories, and topics in transportation geography, such as spatial organization, economic foundations, urban form, major modes, globalization, and environmental impacts. Also covers network representation of transportation systems, network measures, and core methods and tools for visualizing and analyzing […]
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“The further you commute, the longer you commute – the more likely you’re able to find affordable housing,” Dr. Yujie Hu told WUSF’s Gabriella Paul in her recent piece Lack of affordable homes means longer commute times for more people in the Tampa metro area. You can listen to the story and read the transcript […]
HU – A cyclically adjusted spatio-temporal kernel density estimation method for predictive crime hotspot analysis Ya Han, Yujie Hu, Haojie Zhu, Fahui Wang Article first published online: 11 January 2023 DOI: https://doi.org/10.1080/19475683.2023.2166584 ABSTRACT: This paper presents a new method for predictive crime hotspot analysis that further improves the kernel density estimation (KDE) method and the […]
JING, HU – Identifying critical transfer zones to coordinate transit with on-demand services using crowdsourced trajectory data Jiahua Qiua, Yue Jing, Wang Peng, Lili Du, Yujie Hu Article first published online: 21 November 2022 DOI: https://doi.org/10.1080/15472450.2022.2132389 ABSTRACT: This study develops a data-driven approach for identifying critical transfer zones in the city to facilitate the coordination […]
JING, HU – Neighborhood divides: Where you live matters for commuting and its efficiency Yu Jing, Yujie Hu, Michal A Niedzielski Article first published online: 11 November 2022 DOI: https://doi.org/10.1016/j.cities.2022.104091 ABSTRACT: Excess commuting reflects a cits overall commuting efficiency by quantifying the proportion of non-optimal commute that would be avoided if resident workers could freely […]
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HU – Delineating and comparing local labor market geographies of Millennials, Generation Xers, and Baby Boomers Yujie Hu, Jing Huang Article first published online: 5 November 2022 DOI: https://doi.org/10.1016/j.tbs.2022.10.012 ABSTRACT: There has been an increasing share of older workers in America’s workforce as Baby Boomers continue to age into this group. This raises questions about […]
GLOVER, MAO, HU, ZHANG – Enhancing the Retail Food Environment Index (RFEI) with Neighborhood Commuting Patterns: A Hybrid Human−Environment Measure Bailey Glover, Liang Mao, Yujie Hu, Jiawen Zhang Article first published online: 30 August 2022 DOI: https://doi.org/10.3390/ijerph191710798 ABSTRACT: The Retail Food Environment Index (RFEI) and its variants have been widely used in public health to […]
Modeling, Measurement, Visualization and Computation: techniques for the collection, analysis, interpretation and display of geospatial data, using tools such as GeoAI, GIS, Remote Sensing, GPS, and Spatial Statistics. Sub Areas GEOAI: Geographic Artificial Intelligence Geographic Information Systems (GIS) Remote Sensing Spatio-temporal analysis Geospatial Modeling Courses GIS2002: The Digital Earth GIS2114: Geographic Artificial Intelligence & Big […]
Shakhawat Tanim, Brenton Wiernik, Steven Reader, Yujie Hu Article first published online: 10 Dec 2021, Journal of Environmental Psychology DOI: https://doi.org/10.1016/j.jenvp.2021.101742 Dr. Yujie Hu – Predictors of hurricane evacuation decisions: A meta-analysis ABSTRACT: We systematically review and meta-analyze quantitative prediction models for hurricane evacuation decisions. Drawing on data from 33 prediction models and 29,873 households, we estimate distributions […]
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