DAVID "DK" KIM

Urban and Regional Planning | Spatial Data Scientist

ABOUT ME

- My scholarly interests focus on human residence, mobility, and accessibility within urban areas, and how these aspects are influenced by individuals’ socioeconomic status. Additionally, I am interested in the functional relationships among cities. My current research encompasses three main areas: 1) Residential polarization and preferences determined by socioeconomic factors such as income, race, nationality, and jobs (e.g., artists), and their response to external shocks like natural disasters, 2) Accessibility to services and facilities, including transportation, cultural venues, food services, and parks, exploring how the access varies among different socioeconomic groups, 3) Network flow analysis between cities and the optimization of functional regions.

My primary approach utilizes GIS, network analysis, visualization, and AI techniques to extract meaningful patterns from large spatial data sets. This data typically includes points and zones (such as residential parcels and administrative boundaries) as well as network and flow patterns (e.g., navigation and mobile phone GPS trajectories, card transaction data, and vehicle origin-destination flows). By applying these analytical techniques, my objective is to transform raw data into actionable knowledge, which can then be used to support urban planning and policy-making related to land use, residential market, social inequities, and safety. For instance, please see Research Highlights below.

Experience

  • Associate Research Fellow

    Korea Research Institute for Human Settlements

    June 2019 - present

  • Researcher

    Korea Research Institute for Human Settlements

    Mar. 2012 - June 2019

  • Research Assistant

    Colleage of Design, Construction, and Planning

    University of Florida

    Jan. 2021 - Dec. 2024

  • Project Consultant & Manager

    Millennium Promise & Merry-Year International

    Jul. 2011 - June 2012

Education

  • Ph.D in Urban and Regional Planning

    University of Florida

    Jan. 2021 - Dec. 2024

  • MS in Urban and Regional Planning

    Seoul National University

    Mar. 2009- Feb. 2011

  • Bachelor of Science in Urban and Environmental Engineering

    Graduated first class honor, Handong Global University

    Mar. 2002 - Feb. 2009

Technical Skills

  • Languages: Python | R | SQL | Java | HTML
  • Libraries & frameworks:
    • Visualization: Mapbox.js | Processing
    • Machine learning: PyTorch | TensorFlow
    • Network anlaysis: Gephi | UCINET | NetMiner
  • Spatial Analysis Tools: ArcGIS | ArcGISPro | QGIS | S-Cube
  • Other software: SPSS | JMP

Interests

  • AI&Big data-based planning support
  • Climate gentrification | Residential location & Housing market
  • Geospatial analytics | Visualization | GIS
  • Data science | Machine Learning | Computer vision
  • Spatial Network analysis | Urban modeling and simulation

Detecting Housing Market Actors' Dynamics in Responses to Sea level Rise

Examining the data at the census tract level covering years between 2009 and 2020, which enables us to include the effects of socio- demographic factors during periods of heightened public attention to SLR around 2013, this study assesses the impact of climate change on the local residential market in Miami-Dade County, one of the riskiest regions due to environmental changes. Unlike previous research, this study accesses both prices as an indicator of sellers’ reactions and transaction volume as a measure of buyers’ reactions to SLR-associated risks. (Kim, D., & Tepe, E. (2025)).

Gumulira Village Digital Map
Map Project with Villiage Youth

My year of experience in Malawi showed me how well appropriate spatial data analysis can support a public decision. As a GIS analysist, I participated in the Gumulira Millennium Villages Project (Millennium Villages), an aid demonstration project run by the United Nations Development Program (UNDP). I witnessed how aid proliferation without adequate spatial monitoring data led to policy ineffectiveness. In the case of a healthcare scheme, even though a number of projects were conducted, no decision could be made regarding the placement of new donations due to the lack of knowledge on the current spatial distribution of both disease and aid supplies. By educating village youth on the use of GPS and by visiting every single household, I created a village health map using ArcGIS. When I showed the geospatial map presenting the distribution of mosquito nets, AIDS and malaria patients, and health facilities, the leaders of villages could reach an agreement on the allocation of new mosquito nets and health centers. This experience made me consider the role of geospatial information in the planning field.

publications

Kim, D., & Tepe, E. (2025). Estimating the impacts of climate change risk perception on local housing market: A case study in Miami-Dade, Florida Cities, 169 , 106517.
Kim, D., & Tepe, E. (2025). A Closer Look at Housing Market Actors' Dynamics in Responses to Sea Level Rise in Miami-Dade, Florida Journal of Environmental Management, 373 , 123640.
Kim, D., & Kim, D. (2018). Development and Application of Dynamic Visualization Model for Spatial Big Data. Journal of the Korean Association of Geographic Information Studies, 21(1), 57-70.