Youjung Kim

Dr. Youjung Kim

orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 July 2020 in Land
Verified
Journal Article
Open access
PDF file
YKYoujung Kim
Youjung Kim
GNGalen Newman
Galen Newman
BGBurak Güneralp
Burak Güneralp
Due to the increase in future uncertainty caused by rapid environmental, societal, and technological change, exploring multiple scenarios has become increasingly important in urban planning. Land Change Modeling (LCM) enables planners to have the ability to mold uncertain future land changes into more determined conditions via scenarios. This paper reviews the literature on urban LCM and identifies driving factors, scenario themes/types, and topics. The results show that: (1) in total, 113 driving factors have been used in previous LCM studies including natural, built environment, and socio-economic factors, and this number ranges from three to twenty-one variables per model; (2) typical scenario themes include “environmental protection” and “compact development”; and (3) LCM topics are primarily growth prediction and prediction tools, and the rest are growth-related impact studies. The nature and number of driving factors vary across models and sites, and drivers are heavily determined by both urban context and theoretical framework.

24 April 2020 in Computers, Environment and Urban Systems
Verified
Journal Article
Closed access
YKYoujung Kim
Youjung Kim
GNGalen Newman
Galen Newman

18 February 2019 in Sustainability
Verified
Journal Article
Open access
PDF file
YKYoujung Kim
Youjung Kim
GNGalen Newman
Galen Newman
Rising sea levels and coastal population growth will increase flood risk of more people and assets if land use changes are not planned adequately. This research examines the efficacy of flood protection systems and land use planning by comparing Amsterdam in the Netherlands (renown for resilience planning methods), with the city of Houston, Texas in the US (seeking ways of increasing resilience due to extreme recent flooding). It assesses flood risk of future urban growth in lieu of sea level rise using the Land Transformation Model, a Geographic Information Systems (GIS)-based Artificial Neural Network (ANN) land use prediction tool. Findings show that Houston has currently developed much more urban area within high-risk flood-prone zones compared to Amsterdam. When comparing predicted urban areas under risk, flood-prone future urban areas in Amsterdam are also relatively smaller than Houston. Finally, the increased floodplain when accounting for sea level rise will impact existing and future urban areas in Houston, but do not increase risk significantly in Amsterdam. The results suggest that the protective infrastructure used in the Netherlands has protected its future urban growth from sea level rise more adequately than has Houston.

7 February 2019 in Landscape Research
Verified
Journal Article
Closed access
GNGalen Newman
Galen Newman
MMMatthew Malecha
Matthew Malecha
SYSiyu Yu
Siyu Yu
ZQZixu Qiao
Zixu Qiao
JHJennifer A. Horney
Jennifer A. Horney
PBPhil Berke
Phil Berke
Uncertainty about the impacts of sea-level rise make the ability to forecast future spatial conditions a necessary planning/design tool. Geodesign integrates multiple fields of science with change/impact models and planning/design strategies. Proactive planning analyses such as newly developed scorecards allow for plan evaluation; design strategies can now be quantitatively assessed using landscape performance calculators. Neither have been explored as Geodesign tools. A Geodesign process was developed using the resilience scorecard to assess flood vulnerability using projections for the 100-year floodplain with sea-level rise by 2100. Projections were used as a guide to develop a resilient master plan for League City, TX, USA. Future impacts of the plan are projected using landscape performance measures.

1 May 2024 in Environment and Behavior
Verified
Journal Article
Closed access
SLSungmin Lee
Sungmin Lee
YKYoujung Kim
Youjung Kim
BKBon Woo Koo
Bon Woo Koo
The perception of safety significantly influences choices in outdoor activities, profoundly impacting overall well-being. While previous studies have highlighted urban trees’ potential to reduce crime rates, the link between urban trees and perceived safety remains uncertain. This study investigates the relationship between urban trees and safety perception in Austin, Texas, USA, with a specific focus on the moderating role of neighborhood cleanliness and environmental justice considerations. Using multinomial logistic regression models, our analysis reveals a positive association between urban tree canopy coverage and safety perception, with a significant interaction between tree canopies and neighborhood cleanliness, further enhancing the sense of safety. Furthermore, we identified an optimal threshold of tree canopy that maximizes this effect. This highlights the crucial role of well-maintained urban green spaces, particularly tree canopies, in bolstering perceived safety. Such insights hold significance for evidence-based urban planning and community development, fostering well-being and safety for all residents.

30 January 2020 in Journal of Spatial Science
Verified
Journal Article
Closed access
GNGalen Newman
Galen Newman
YKYoujung Kim
Youjung Kim
GKGunwoo Kim
Gunwoo Kim
RLRyun Jung Lee
Ryun Jung Lee
DGDonghwan Gu
Donghwan Gu
DGDaniel Goldberg
Daniel Goldberg
Populating and depopulating cities have some degree of underutilised land. The duration of vacancy, or length of time a property remains unused, more strongly influences urban decline than the amount of vacant land. Assessment of the duration of vacancy is seldom conducted, due to a lack of linking longitudinal data. This research creates and applies a Python script to track the duration of vacancy in Minneapolis, MN, U.S.A, to create a tool that can be utilised by cities with vacant land inventories. The tool can be used globally to prioritise treatment areas for urban regeneration plans.