An open retail boundary dataset for South Korea using open data and computer vision technique

Abstract Although delineating retail boundaries is important to explore and comprehend the dynamics of the retail sector, it is hard to find studies specifically addressing it in the South Korean context. This study fills this gap by proposing new retail boundaries across South Korea. To achieve thi...

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Main Authors: Byeonghwa Jeong, Juhwan Song, Younghoon Kim
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-025-04958-1
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author Byeonghwa Jeong
Juhwan Song
Younghoon Kim
author_facet Byeonghwa Jeong
Juhwan Song
Younghoon Kim
author_sort Byeonghwa Jeong
collection DOAJ
description Abstract Although delineating retail boundaries is important to explore and comprehend the dynamics of the retail sector, it is hard to find studies specifically addressing it in the South Korean context. This study fills this gap by proposing new retail boundaries across South Korea. To achieve this goal, we employed a variety of retailers and building datasets and proposed a unique computer vision-based framework with a deep ensemble voting technique. As a result, we delineated 6,636 distinct retail boundaries that were validated against existing reference retail boundaries. These newly delineated retail boundaries provide valuable insights for researchers, governments, and other relevant stakeholders by enhancing their understanding of retail geography. This dataset can be used as a foundational resource for analyses on topics such as pandemic recovery, retail gentrification, and the resilience of retail spaces in response to e-commerce growth, ultimately contributing to more robust retail sector research in South Korea.
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spelling doaj-art-ea3bd8973df242d59e6ed425eed10a0e2025-08-20T02:17:53ZengNature PortfolioScientific Data2052-44632025-04-0112111210.1038/s41597-025-04958-1An open retail boundary dataset for South Korea using open data and computer vision techniqueByeonghwa Jeong0Juhwan Song1Younghoon Kim2R&D Associate, Human Geography Group, Oak Ridge National LaboratoryPh.D. candidate, Department of Geography Education, Korea National University of EducationProfessor, Department of Geography Education, Korea National University of EducationAbstract Although delineating retail boundaries is important to explore and comprehend the dynamics of the retail sector, it is hard to find studies specifically addressing it in the South Korean context. This study fills this gap by proposing new retail boundaries across South Korea. To achieve this goal, we employed a variety of retailers and building datasets and proposed a unique computer vision-based framework with a deep ensemble voting technique. As a result, we delineated 6,636 distinct retail boundaries that were validated against existing reference retail boundaries. These newly delineated retail boundaries provide valuable insights for researchers, governments, and other relevant stakeholders by enhancing their understanding of retail geography. This dataset can be used as a foundational resource for analyses on topics such as pandemic recovery, retail gentrification, and the resilience of retail spaces in response to e-commerce growth, ultimately contributing to more robust retail sector research in South Korea.https://doi.org/10.1038/s41597-025-04958-1
spellingShingle Byeonghwa Jeong
Juhwan Song
Younghoon Kim
An open retail boundary dataset for South Korea using open data and computer vision technique
Scientific Data
title An open retail boundary dataset for South Korea using open data and computer vision technique
title_full An open retail boundary dataset for South Korea using open data and computer vision technique
title_fullStr An open retail boundary dataset for South Korea using open data and computer vision technique
title_full_unstemmed An open retail boundary dataset for South Korea using open data and computer vision technique
title_short An open retail boundary dataset for South Korea using open data and computer vision technique
title_sort open retail boundary dataset for south korea using open data and computer vision technique
url https://doi.org/10.1038/s41597-025-04958-1
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