ACM SIGSPATIAL 2025 – Accepted Applications Papers

  • Generative AI in Map-Making: A Technical Exploration and Its Implications for Cartographers
    Claudio Affolter (ETH Zurich), Sidi Wu (ETH Zurich), Yizi Chen (ETH Zurich), and Lorenz Hurni (ETH Zurich)
  • REALISM: A Regulatory Framework for Coordinated Scheduling in Multi-Operator Shared Micromobility Services
    Heng Tan (Lehigh University), Hua Yan (Lehigh University), Yukun Yuan (University of Tennessee at Chattanooga), Guang Wang (Florida State University), and Yu Yang (Lehigh University)
  • FieldSAT: A Scalable Query Workflow for Precision Agriculture with Large Raster Datasets
    Zhuocheng Shang (University of California, Riverside), Ahmed Eldawy (University of California, Riverside), Elia Scudiero (University of California, Riverside), Ramesh Dhungel (USDA Salinity Lab), and Ray Anderson (USDA Salinity Lab)
  • An Orchestration Engine for Scalable, On-Demand AI Phenotyping from UAS Imagery in Agriculture
    Lucas Waltz (The Ohio State University), Sarikaa Sridhar (The Ohio State University), Ryan Waltz (The Ohio State University), Paul Rodriguez (University of California, San Diego), Chaeun Hong (The Ohio State University), Armeen Ghoorkhanian (The Ohio State University), Nicole DiMarco (The Ohio State University) Raghu Machiraju (The Ohio State University), and Sami Khanal (The Ohio State University)
  • DeepTopoNet: A Framework for Subglacial Topography Estimation on the Greenland Ice Sheets
    Bayu Adhi Tama (University of Maryland, Baltimore County), Mansa Krishna (Dartmouth College), Homayra Alam (University of Maryland, Baltimore County), Mostafa Cham (University of Maryland, Baltimore County), Omar Faruque (University of Maryland, Baltimore County), Gong Cheng (Dartmouth College), Jianwu Wang (University of Maryland Baltimore County), Mathieu Morlighem (Dartmouth College), and Vandana Janeja (University of Maryland Baltimore County)
  • RADAR: Resource Allocation for Disaster Resilience in Senior Health Care
    Modeste Kenne Mefenya (University of California, Irvine), Fernanda Ventorim (University of California, Irvine), Chad Cossey (Orange County Health Care Agency), Zhenghui Hu (ImageCat, Inc), Julie Rousseau (University of California, Irvine), and Nalini Venkatasubramanian (University of California, Irvine)
  • Scalable Inter-County Food Flow Prediction Using Graph Neural Networks
    Qianheng Zhang (University of Wisconsin - Madison), Dev Paul (University of Wisconsin-Madison), Michelle Miller (University of Wisconsin-Madison), Alfonso Morales (University of Wisconsin-Madison), and Song Gao (University of Wisconsin-Madison)
  • Fine-Scale Soil Mapping in Alaska with Multimodal Machine Learning
    Yijun Lin (University of Minnesota), Theresa Chen (University of Minnesota), Colby Brungard (New Mexico State University), Sabine Grunwald (University of Florida), Sue Ives (ABR, Inc.), Matt Macander (ABR, Inc.), Timm Nawrocki (University of Alaska-Anchorage), Yao-Yi Chiang (University of Minnesota), and Nic Jelinski (University of Minnesota)
  • A Behavior-Informed and Geo-Context-Aware Home Detection Framework for Mobile Phone Positioning Data
    Ying Song (University of Minnesota), Meicheng Xiong (University of Minnesota), Xiaohuan Zeng (University of Minnesota), and Di Zhu (University of Minnesota)
  • HydroGAT: Distributed Heterogeneous Graph Attention Transformer for Spatiotemporal Flood Prediction
    Aishwarya Sarkar (Iowa State University), Autrin Hakimi (Iowa State University), Xiaoqiong Chen (Iowa State University), Hai Huang (Iowa State University), Chaoqun Lu (Iowa State University), Ibrahim Demir (Tulane University) and Ali Jannesari (Iowa State University)
  • MuST2-Learn: Multi-view Spatial-Temporal-Type Learning for Heterogeneous Municipal Service Time Estimation
    Nadia Asif (University of Tennessee at Chattanooga), Zhiqing Hong (Rutgers University), Shaogang Ren (University of Tennessee at Chattanooga), Xiaonan Zhang (Florida State University), Xiaojun Shang (University of Texas at Arlington), and Yukun Yuan (University of Tennessee at Chattanooga)
  • Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals’ Mobility Beyond Visited Places
    Xinglei Wang (University College London), Tao Cheng (University College London), Stephen Law (University College London), Zichao Zeng (University College London), Ilya Ilyankou (University College London), Junyuan Liu (University College London), Lu Yin (University of Surrey), Weiming Huang (University of Leeds), and Natchapon Jongwiriyanurak (University College London)
  • Transit for All: Mapping Equitable Bike2Subway Connection using Region Representation Learning
    Min Namgung (University of Minnesota), Janghyeon Lee (University of Minnesota), Fangyi Ding (The University of Hong Kong), and Yao-Yi Chiang (University of Minnesota)
  • A Novel Evaluation Framework for 15-Minute City Using Satellite Imagery
    Chan Jae Song (KAIST), Seong Yeub Chu (KAIST), Jong Woo Kim (KAIST), and Mun Yong Yi (KAIST)
  • MVeLMA: Multimodal Vegetation Loss Modeling Architecture for Predicting Post-fire Vegetation Loss
    Meenu Ravi (Virginia Tech), Shailik Sarkar (Virginia Tech), Yanshen Sun (Virginia Tech), Vaishnavi Singh (Georgetown University), and Chang-Tien Lu (Virginia Tech)

    • Short Papers

  • Weather-Driven Agricultural Decision-Making Under Imperfect Conditions
    Tamim Ahmed (Washington State University), and Monowar Hasan (Washington State University)
  • The Maximum Coverage Model and Recommendation System for UAV Vertiports Location Planning
    Chunliang Hua (Southeast University), Xiao Hu (International Digital Economy Academy), Jiayang Sun (International Digital Economy Academy), and Zeyuan Yang (International Digital Economy Academy)
  • MODyPer: Multi-Objective Dynamic Personalized Route Planning for Vulnerable Road Users
    Federica Rollo (University of Modena and Reggio Emilia), and Laura Po (University of Modena and Reggio Emilia)
  • GeoRAG: Delivery Address Augmented Retrieval and Validation
    El Moundir Faraoun (Université Paris 8), Nédra Mellouli (Université Paris 8), and Stéphane Millot (TALK solutions)
  • Physics-Guided Multi-Contextual Learning: Understanding the Surface and Subsurface Processes in Southeast Greenland
    Chhaya Kulkarni (University of Maryland, Baltimore County), Nicole-Jeanne Schlegel (NOAA), and Vandana Janeja (University of Maryland Baltimore County)
  • Denoising Diffusion Probabilistic Models for Coastal Inundation Forecasting
    Kazi Ashik Islam (University of Virginia), Zakaria Mehrab (University of Virginia), Mahantesh Halappanavar (Pacific Northwest National Laboratory), Henning Mortveit (University of Virginia), Sridhar Katragadda (City of Virginia Beach), Derek Loftis (Virginia Institute of Marine Science), and Madhav Marathe (University of Virginia)
  • Graph symbolic regression to interpret the spread of Vesicular Stomatitis Virus across the U.S. and Mexico
    Tamanna Rashme (Mississippi State University), Zonghan Zhang (Mississippi State University), Jason Weeks (Mississippi State University), Marouane Benbrahim (Mississippi State University), Zijian Zhang (Mississippi State University), Zhiqian Chen (Mississippi State Univerrsity), Nisha Pillai (Mississippi State University), Ram Ramkumar (Mississippi State University), and Bindu Nanduri (Mississippi State University)
  • A topology-based approach to extract pressure ridges from sea ice surfaces
    Yunting Song (University of Maryland at College Park), Leila De Floriani (University of Maryland at College Park), Kyle Duncan (University of Maryland at College Park), and Sinead Farrell (University of Maryland at College Park)
  • MapQA: : Open-domain Geospatial Question Answering on Map Data
    Zekun Li (University of Minnesota), Malcolm Grossman (University of Minnesota), Eric Qasemi (Oracle), Mihir Kulkarni (Pennsylvania State University), Muhao Chen (University of California, Davis) and Yao-Yi Chiang (University of Minnesota)
  • FoundationSoil: Enhancing Soil Organic Carbon Mapping Using a Multi-Temporal Geospatial Foundation Model
    Jiayi Song (University of Florida), Chang Zhao (University of Florida), Hao-Yu Liao (University of Florida), and Wei Shao (University of Florida)
  • Mapping Cultural Ecosystem Services Using One-Shot In-Context Learning with Multimodal Large Language Models
    Hao-Yu Liao (University of Florida), Chang Zhao (University of Florida), Jiayi Song (University of Florida), and Wei Shao (University of Florida)
  • Urban-STA4CLC: Urban Theory-Informed Spatio-Temporal Attention Model for Predicting Post-Disaster Commercial Land Use Change
    Ziyi Guo (University of Florida), and Yan Wang (University of Florida)
  • Learning Individual Movement Shifts After Urban Disruptions with Social Infrastructure Reliance
    Shangde Gao (University of Florida), Zelin Xu (University of Florida), and Zhe Jiang (University of Florida)
  • Leveraging Reinforcement Learning for Maternity Care Resource Reallocation: A Case Study in Florida
    Andy Qin (The University of Texas at Austin), Yuhao Kang (The University of Texas at Austin), Hanqi Li (Louisiana State University), Shiqi Wang (University of Edinburgh), Bing Zhou (The Pennsylvania State University), Fahui Wang (Louisiana State University), and Peiyin Hung (University of South Carolina)