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Session Proposal: Urban Forest Dynamics: Integrating Geospatial Data and Process-Based Models (AGU25)

H148
Urban Forest Dynamics: Integrating Geospatial Data and Process-Based Models

Session ID#: 252085

Session Description:
Urban forests are essential for regulating temperature, improving air quality, and enhancing climate resilience. This session invites contributions that use remote sensing (e.g., UAVs, LiDAR, multispectral imagery) and numerical modeling (e.g., WRF, BEP-Tree, i-Tree, CMAQ) to assess urban forest structure, function, and ecosystem services. Topics may include but are not limited to, urban canopy mapping, microclimate modeling, stormwater mitigation, tree growth dynamics, and data integration frameworks. We especially encourage submissions exploring urban vegetation's role in advancing outdoor thermal comforts and sustainable city planning. This session aims to bring together interdisciplinary researchers and practitioners using innovative tools to understand and manage urban forests in a rapidly changing world.
Index Terms:

1813 Eco-hydrology [HYDROLOGY]
1851 Plant ecology [HYDROLOGY]
1855 Remote sensing [HYDROLOGY]
3322 Land/atmosphere interactions [ATMOSPHERIC PROCESSES]
Primary Convener:  Rubab Saher, Purdue University, West Lafayette, IN, United States
Conveners:  Brady S Hardiman, Purdue University, Forestry and Natural Resources, West Lafayette, United States and Daniel Aliaga, Purdue University, West Lafayette, United States
 
Novel LiDAR Indices Reveal Scale-Dependent Vertical Structure and Typologies in a Temperate Forest (1863108)
Seunghyeon Lee1, Uirin Ha2, Heejae Lee3, Hansoo Kim4 and Youngkeun Song1, (1)Seoul National University, Seoul, South Korea, (2)Department of Agriculture, Forestry and Bioresources, Seoul National University, Seoul, Republic of Korea, 08826, Seoul, South Korea, (3)National Forest Satellite Information & Technology Center, National Institute of Forest Science, Seoul, Republic of Korea, Seoul, South Korea, (4)Gyeonggi Research Institute, Suwon, South Korea
 
Quantifying the Air Pollution Mitigation Function of Urban Forests: Evaluating NO₂ Impacts via Machine Learning-Based Integration of Satellite and Ground Observations (1877737)
Hong-Duck Sou1, Dong Yeong Chang2, Yoori Cho2, Jaeeun Woo2, Yoonji Hahn2, Chaewan Kim1, Jinsuk Jeong1, Sumin Choi1 and Chan-Ryul Park1, (1)National Institute of Forest Science, Livable Urban Forests Research Center, Seoul, South Korea, (2)Seoul National University, Department of Environmental Planning, Seoul, South Korea
 
Correcting Urban Canopy Area Estimates for Management and Planning (1884954)
Camille Pawlak1, Matthew Ritter2, Greg S Okin1, Geoffrey A Fricker3, Jenn Yost2 and Thomas W Gillespie4, (1)University of California Los Angeles, Department of Geography, Los Angeles, United States, (2)California Polytechnic State University San Luis Obispo, Biological Sciences, San Luis Obispo, United States, (3)California Polytechnic State University San Luis Obispo, San Luis Obispo, CA, United States, (4)University of California, Los Angeles (UCLA), Department of Geography, Los Angeles, United States
 
The Influence of Tree Canopy Cover Data Choices on Urban Ecosystem Accounting (1899975)
Levi Sweet-Breu1, Gregory Cermak2, Lucila Corro2, Peter C Ibsen2, Mehdi P. Heris3, Raimundo Atal4, Ryan McManamay1, Jay Diffendorfer2 and Kenneth Bagstad2, (1)Baylor University, Department of Environmental Science, Waco, TX, United States, (2)U.S. Geological Survey, Geosciences and Environmental Change Science Center, Denver, United States, (3)Hunter College, Urban Policy & Planning, New York, United States, (4)New York University, Department of Environmental Studies, New York City, United States
 
HIGH-RESOLUTION URBAN ABOVE‑GROUND BIOMASS MAPPING USING GEDI AND SENTINEL DATA: A CASE STUDY OF GYEONGGI‑DO, KOREA (1939715)
JooYeong Lee1, Sukyoung Kim2 and Chan Park2, (1)University of Seoul, Seoul, Korea, Republic of (South), (2)University of Seoul, Department of Landscape Architecture, Seoul, South Korea
 
Evaluating the Long-Term Ecosystem Service Benefits of Trees using i-Tree Eco and Determining Student Willingness to Pay (WTP) at The University of Texas Rio Grande Valley (2002927)
Juliete Gonzalez, The University of Texas Rio Grande Valley, The School of Earth, Environmental, and Marine Sciences, Edinburg, United States, Alex Racelis, University of Texas Rio Grande Valley, School of Earth, Environmental, and Marine Sciences, Edinburg, TX, United States and Amie Bostic, The University of Texas Rio Grande Valley, Department of Sociology, Edinburg, United States
See more of: Hydrology