publications

publications by categories in reversed chronological order. generated by jekyll-scholar.

2026

  1. PopGNN: Graph Neural Network-Based Flexible Future Population Forecasting Model
    Byeonghwa Jeong, Viswadeep Lebakula, and Marie Urban
    2026
  2. Satellite Embedding-Based Population Imputation for Areas with Missing Building Footprint Data: A Computer Vision-Based Approach
    Byeonghwa Jeong, Daniel Adams, and Andrew Zimmer
    2026
  3. Popnet: computer vision based deep learning model for forecasting gridded population
    Byeonghwa Jeong and Bo Kyeong Lee
    International Journal of Geographical Information Science, 2026
  4. Development of Grid-Based Population Projection Method: A Modified Cohort Component Approach Applied to South Korea
    Bokyeong Lee and Byeonghwa Jeong
    Population, Space and Place, 2026

2025

  1. Coastal Commercial Area Extraction and Characteristics Study: Using Image Segmentation Mode
    Younghoon KiM, Byeonghwa Jeong, and Juhwan Song
    Journal of the Korean Geographical Society, 2025
  2. A large language model-based chatbot system framework for urban planners
    Xiaoxin Zhou, Byeonghwa Jeong, and Karen Chapple
    Expert Systems with Applications, 2025
  3. Landscan global 2024
    Viswadeep Lebakula, Jack Gonzales, Clinton Stipek, and 8 more authors
    2025
  4. Assessing downtown recovery rates and determinants in North American cities after the COVID-19 pandemic
    Amir Forouhar, Karen Chapple, Jeff Allen, and 2 more authors
    Urban Studies, 2025
  5. An open retail boundary dataset for South Korea using open data and computer vision technique
    Byeonghwa Jeong, Juhwan Song, and Younghoon Kim
    Scientific Data, 2025
  6. Does class matter? Understanding differential pandemic recovery via a building typology
    Byeonghwa Jeong and Karen Chapple
    Environment and Planning B: Urban Analytics and City Science, 2025

2024

  1. A new commercial boundary dataset for metropolitan areas in the USA and Canada, built from open data
    Byeonghwa Jeong, Jeff Allen, and Karen Chapple
    Scientific Data, 2024

2023

  1. An Integrated Deep Learning Model based on Retail, Residential and Footfall Changes data to Predict Retail Gentrification
    Byeonghwa Jeong
    UCL (University College London), 2023

2020

  1. Topic Modeling of the Transition of the Sense of Place in Urban Regeneration Area: A Case Study of Daegu Bangcheon Market
    Byeong Hwa Jeong and JW Kim
    Journal of Daegu Gyeongbuk Studies, 2020

2019

  1. Application and evaluation of self-organising map-based spatial clustering for regional policy recommendations
    B Jeong and J Kim
    Journal of the Korean Geographical Society, 2019

2018

  1. Anticipation of Commercial Gentrification through Time and Space Seoul, South Korea
    Byeonghwa Jeong
    2018

2016

  1. Comparative evaluation of South versus North Goseong County in terms of forest carbon offset potential
    ByeongHwa Jeong and Jung-Sup Um
    Spatial Information Research, 2016

  1. Anticipation of Retail Gentrification Through Data Science Approach in Seoul, South Korea
    Byeonghwa Jeong and Junwoo Kim
    South Korea