Modeling and Predicting Urban Expansion in South Korea Using Explainable Artificial Intelligence (XAI) Model
Source abstract
Abstract
Over the past few decades, most cities worldwide have experienced a rapid expansion with unprecedented population growth and industrialization. Currently, half of the world’s population is living in urban areas, which only account for less than 1% of the Earth. A rapid and unplanned urban expansion, however, has also resulted in serious challenges to sustainable development of the cities, such as traffic congestion and loss of natural environment and open spaces. This study aims at modeling and predicting the expansion of urban areas in South Korea by utilizing an explainable artificial intelligence (XAI) model. To this end, the study utilized the land-cover maps in 2007 and 2019, as well as several socioeconomic, physical, and environmental attributes. The findings of this study suggest that the urban expansion tends to be promoted when a certain area is close to economically developed area with gentle topography. In addition, the existence of mountainous area and legislative regulations on land use were found to significantly reduce the possibility of urban expansion. Compared to previous studies, this study is novel in that it captures the relative importance of various influencing factors in predicting the urban expansion by integrating the XGBoost model and SHAP values.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Land Use and Ecosystem Services · Remote Sensing and LiDAR Applications · Spatial and Panel Data Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Environmental Planning, Korea Environment Institute, Sejong 30147, Korea
Funding
National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)
References (60)
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