The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.


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Abstract: Prediction of Building Energy Consumption in Urban Areas: Integrating Environmental and Morphological Context through Machine Learning (AGU25)

Prediction of Building Energy Consumption in Urban Areas: Integrating Environmental and Morphological Context through Machine Learning

Eunju Ji1,2, Sang Hyunk Kim3, Sunjin Kim1,2 and Dong-Kun Lee4, (1)Seoul National University, Department of Landscape Architecture and Rural Systems Engineering, College of Agriculture and Life Sciences, Seoul, Korea, Republic of (South), (2)Seoul National University, Integrated Major in Smart City Global Convergence, Seoul, Korea, Republic of (South), (3)Seoul National University, Interdisciplinary Program in Landscape Architecture, Seoul, South Korea, (4)Seoul National Universiy, Department of Landscape Architecture and Rural System Engineering, Seoul, South Korea