Title: Professor
Institution: Montclair State University
Address: 1 Normal Ave., Department of Earth and Environmental Studies, Montclair, New Jersey 07043
Email: yud@montclair.edu
Phone: (973) 655-4313
Visit Danlin’s Research Website
Research Interests: Geographic Information Systems, Spatial and Spatiotemporal data analysis, Complex System Simulative Modeling, Urban Remote Sensing, Urban Public and Environmental Health, Spatial Statistical Analysis, Big Data Analytics, Urban Planning and Development Studies
Biographical Sketch:
Dr. Danlin Yu is a distinguished Geographic Information Scientist, urban public and environmental health scholar, and complex system simulative modeler with extensive expertise in urban remote sensing, spatial data science, and complex system modeling. His research primarily focuses on geographic information analysis, urban remote sensing, system dynamic modeling for complex systems and their applications on urban public health studies. He is listed as one of the top 2% scientists by Standford and Elsevier since 2020.
Dr. Yu has over a decade of experience in geographic information analysis and complex system modeling, including application and methodological development. He pioneers the development of an AI/Machine Learning integrated covariation-mining modeling strategy in his recent US Department of Housing and Urban Development grant. He has published widely in these fields, with over 100 peer-reviewed articles in high-caliber journals with wide international circulation and three collaborative books on urban development and urbanization in China. His strong statistical analysis skills are applied to urban and regional planning, public health, environmental management, and population prediction.
A notable aspect of Dr. Yu’s career is his work as a system dynamics modeler studying urban sustainability and environmental health. He is currently the Principal Investigator (PI) for a US Department of Housing and Urban Development (HUD) funded project titled “A system dynamics simulative model to assess bioaccessibility of lead in the environment, Jersey City, New Jersey,” with a total funding of $699,981. This project aims to develop interactive and operational modeling frameworks for policymakers, the general public, and the academic community to simulate various policy scenarios affecting lead bioaccessibility.
Dr. Yu is also preparing to submit new project proposals to the National Science Foundation (NSF), including those focused on covariation-mining and system dynamics modeling, seeking funding of over $2 million. These proposals will further explore innovative approaches to urban public health and environmental management.
Currently, Dr. Yu serves as the associate editor of the ASCE’s Journal of Urban Planning and Development and as an academic editor for PeerJ and Remote Sensing. He is well recognized in the field of spatial data analysis. Collaborating with leading spatial economist Dr. Roger Bivand, Dr. Yu co-authored the R package “spgwr” for geographically weighted regression analysis. He is also leading the development of an R package for “geographically weighted panel regression,” a method he proposed and has been developing since 2010.
Education:
April 2005, Ph.D. Department of Geography, University of Wisconsin-Milwaukee.
Dissertation title: “GIS and Spatial Modeling in Regional Development Studies: A Case of Greater Beijing”
June 1997, M.S., Department of Geography, Lanzhou University, Lanzhou, P.R. China
Thesis title: “Studies on the Urban Traffic Efficiency: Case Study on Lanzhou”
Jun 1994, B.S. Department of Geography. Changsha Electric Power University. Changsha, P.R. China
Professional Certifications:
No.
Other Research:
- A system dynamics simulative model to access bioaccessibility of lead in the environment, Jersey City, New Jersey
- Lowering Lead Bioavailability in Residential Soils of Variable Physico-Chemical Properties using Sustainable In-Situ Treatment Methods. Phase-II: Validating under Scaled-up Field Conditions.
- Quantifying the role of vegetation cover on berm-dune geometry and sedimentation patterns in Long Branch, New Jersey
- Developing a Wetland Baseline at the Watershed Scale – A system dynamic simulation of wetland biophysical conditions and secondary fish products
- Studies of urban vulnerability based on micro-geographic units via spatial data analysis and GeoComputation
- Urban public safety analysis: quantification and dynamic simulation from a GIS and spatial data analysis perspective
- A System Dynamic Study of Interaction Among Urbanization, Industrialization and Watershed Sustainable Development
- System dynamic model development for Passaic River watershed sustainability and environmental management study