Lab members Kai Sun and Jiyeon Kim receive ICA Scholarship and Student Presentation Award

At the 2024 CaGIS+UCGIS Symposium, lab member Kai Sun received the ICA Scholarship from the International Cartographic Association (ICA). The ICA Scholarship is awarded to “support early career scholars and professionals in advancing their career in cartography and GIScience.” Kai also made a poster presentation, “GALLOC: A GeoAnnotator for Labeling LOCation descriptions from disaster-related text messages”, at UCGIS.

Kai Sun receiving the ICA Scholarship.

Lab member Jiyeon Kim made an oral presentation, “Assessing the ability of deep learning models integrated with environmental and weather variables for predicting fire spread: A case study of the 2023 Maui wildfires.” Jiyeon’s presentation received the 3rd Place Award in the Student Presentation Competition.

3rd Place Student Paper Award received by Jiyeon Kim
GeoAI Lab members at the 2024 CaGIS + UCGIS Symposium.

Dr. Hu receives the UCGIS Early/Mid-Career Research Award

Dr. Yingjie Hu was selected as the recipient of the 2024 Early/Mid-Career Research Award from the University Consortium for Geographic Information Science (UCGIS). This award is “given to an individual who has made a particularly outstanding research contribution to geographic information science.” The contribution can be “a single contribution or a series of research works that are seminal and have significant impacts on Geographic Information Science community.” This is an international award that is given to “researchers in the Early/Mid-Career level that is 15 years or less after the terminal degree or within 15 years of accumulated professional service, worldwide are eligible for the award.”

Yingjie is extremely honored to receive this award. He really appreciates the great encouragement from the UCGIS community and is grateful for the support of his mentors, colleagues, and students. He looks forward to continuing contributing to GIScience research, education, and community service.

Lab member Ryan Zhenqi Zhou receives the 2024 CESASC Scholarship

Chinese-American Engineers and Scientists Association of Southern California (CESASC) is one of the largest and the most established Chinese-American professional organizations in Southern California. CESASC offers annual scholarships to encourage young students to develop their interests and pursue their careers in the fields of science, engineering, and technology.

Lab member Ryan Zhenqi Zhou received the 2024 CESASC Scholarship and both attended and volunteered at the 2024 CESASC Annual Convention. Ryan is deeply grateful for the great and consistent support from his mentor, Dr. Yingjie Hu, who himself also was a recipient of the CESASC Scholarship while a PhD student at UCSB.

Lab member Ryan Zhenqi Zhou receives the 2024 Hugh Calkins Applied GIS Award and the 2024 Michael Trapasso Climate Impacts Award

Lab member Ryan Zhenqi Zhou receives both the 2024 Hugh Calkins Applied GIS Award and the 2024 Michael Trapasso Climate Impacts Award!

The Hugh Calkins Applied GIS Award is given annually to a graduate student from UB Geography, who best applies the principles that Dr. Calkins developed and taught for many years.

The Dr. L. Michael Trapasso award is given annually to a current graduate student from UB Geography in order to advance his/her research involving the use of meteorological or climatological data in the following year. For Ryan, he uses meteorological or climatological data to advance his research on winter storms and blizzards, and to help communities become more resilient during these disasters.

Congratulations, Ryan!!

Dr. Hu receives the 2024 AAG SAM Emerging Scholar Award

Yingjie is extremely honored to receive the 2024 Emerging Scholar Award from the American Association of Geographer (AAG) Spatial Analysis and Modeling (SAM) Specialty Group. This award “honors early- to mid-career scholars who have made significant contributions to education and research initiatives.”

Due to family care responsibilities (his second child was born a few weeks ago), Yingjie couldn’t travel to Hawaii to receive this award. Many thanks to UB PhD student Qingqing Chen who brought back the award plaque for him. Yingjie is extremely grateful for the great support from his mentors, colleagues, and students, and he looks forward to continuing contributing to GIScience, SAM, and beyond!

New paper led by student Ryan Zhenqi Zhou published in the International Journal of Disaster Risk Reduction

In a new research led by PhD student Ryan Zhou, we examined the impacts of the 2021 Texas Winter storm on local communities in three stages and impact disparities. Winter Storm Uri slammed Texas between February 13–17, 2021 and caused widespread power outages. Understanding the impacts of this catastrophic event on local communities has important meaning. In this study, we examine the impacts of this winter storm and its impact disparities on different population groups over three stages of this disaster: the initial-hit stage, power-outage stage, and recovery stage. The study focuses on Harris County, Texas which was severely affected by the winter storm. We leverage home-dwelling time information from anonymized mobile phone location data to study the constrained mobility of people due to the winter storm as a way to quantify its impacts on local communities. Considering that mobile phone location data may be affected by the power outages, we further integrate nighttime light (NTL) images into our analyses to assess disaster impacts during the power-outage stage, and use home-dwelling time to assess the impacts during the other two stages (i.e., the initial-hit stage and recovery stage). The results reveal disparate impacts of this winter storm on local communities in the three stages of this disaster. We also find impact disparities on population groups with different socioeconomic and demographic backgrounds, especially during the initial-hit stage. These results help us better understand the impacts of this catastrophic event, and could inform future response and mitigation efforts in identifying vulnerable communities, allocating resources, and curtailing negative impacts of similar disasters.

More information about this article is at: Ryan Zhenqi Zhou, Yingjie Hu, Lei Zou, Heng Cai, and Bing Zhou. (2024): Understanding the disparate impacts of the 2021 Texas winter storm and power outages through mobile phone location data and nighttime light imagesInternational Journal of Disaster Risk Reduction, 104339. [PDF]

New paper on the five-year milestone of GeoAI published in the journal Annals of GIS

The Annual Meeting of the American Association of Geographers (AAG) in 2023 marked a five-year milestone since the first Geospatial Artificial Intelligence (GeoAI) Symposium was held at AAG in 2018. In the past five years, progress has been made while open questions remain. In this context, we organized an AAG panel and invited five panelists to discuss the advances and limitations in GeoAI research. The panelists commended the successes, such as the development of spatially explicit models, the production of large-scale geographic datasets, and the use of GeoAI to address real-world problems. The panellists also shared their thoughts on limitations in current GeoAI research, which were considered as opportunities to engage theories in geography, enhance model explainability, quantify uncertainty, and improve model generalizability. This article summarizes the presentations from the panellists and also provides after-panel thoughts from the organizers. We hope that this article can make these thoughts more accessible to interested readers and help stimulate new ideas for future breakthroughs.

Full paper is available at: Hu, Y., Goodchild, M., Zhu, A.X., Yuan, M., Aydin, O., Bhaduri, B., Gao, S., Li, W., Lunga, D., & Newsam, S. (2024): A five-year milestone: reflections on advances and limitations in GeoAI researchAnnals of GIS, in press.

Figure 1. The GeoAI panel at AAG 2023

Dr. Hu joins the Editorial Board of the journal Cartography and Geographic Information Science

Dr. Hu has been invited to join the Editorial Board of Cartography and Geographic Information Science (CaGIS).

CaGIS is the official publication of the Cartography and Geographic Information Society. The Society supports research, education, and practices that improve the understanding, creation, analysis, and use of maps and geographic information. The CaGIS journal implements the objectives of the Society by publishing authoritative peer-reviewed articles that report on innovative research in cartography and geographic information science.

Research on geo-knowledge-guided AI model for disaster response was reported by news media

Our recent research on geo-knowledge-guided AI model for disaster response was reported by a number of news outlets:

It is great to see the wide public interest in our work. Look forward to doing more research that positively impacts on our society.

New Handbook of Geospatial Artificial Intelligence (GeoAI) is published by Taylor & Francis

The new “Handbook of Geospatial Artificial Intelligence” edited by Drs. Song Gao (University of Wisconsin-Madison), Yingjie Hu (University at Buffalo), and Wenwen Li (Arizona State University) is now published and is available at the website of Taylor & Francis and a preview of the book is available here.

This handbook covers key fundamental concepts, methods, models, and technologies of GeoAI and discusses the recent advances, research tools, and applications that range from environmental observation and social sensing to public health and disaster responses. We hope this book can provide an organized resource for educators, students, researchers, and practitioners learning and using GeoAI.

Book chapters and their authors:

Section 1: Historical Roots of GeoAI

Chapter 1: Introduction to Geospatial Artificial Intelligence (GeoAI)

By Song Gao, Yingjie Hu, Wenwen Li

Chapter 2: GeoAI’s Thousand-Year History

By Helen Couclelis

Chapter 3: Philosophical Foundations of GeoAI: Exploring Sustainability, Diversity, and Bias in GeoAI and Spatial Data Science

By Krzysztof Janowicz

Section 2: GeoAI Methods

Chapter 4: GeoAI Methodological Foundations: Deep Neural Networks and Knowledge Graphs

By Song Gao, Jinmeng Rao, Yunlei Liang, Yuhao Kang, Jiawei Zhu, Rui Zhu 

Chapter 5: GeoAI for Spatial Image Processing

By Samantha T. Arundel, Kevin G. McKeehan, Wenwen Li, Zhining Gu

Chapter 6: Spatial Representation Learning in GeoAI

By Gengchen Mai, Ziyuan Li, Ni Lao

Chapter 7: Intelligent Spatial Prediction and Interpolation Methods

By Di Zhu, Guofeng Cao

Chapter 8: Heterogeneity-Aware Deep Learning in Space: Performance and Fairness

By Yiqun Xie, Xiaowei Jia, Weiye Chen, Erhu He

Chapter 9: Explainability in GeoAI

By Ximeng Cheng, Marc Vischer, Zachary Schellin, Leila Arras, Monique M. Kuglitsch, Wojciech Samek, Jackie Ma

Chapter 10: Spatial Cross-Validation for GeoAI

By Kai Sun, Yingjie Hu, Gaurish Lakhanpal, Ryan Zhenqi Zhou

Section 3: GeoAI Applications

Chapter 11: GeoAI for the Digitization of Historical Maps

By Yao-Yi Chiang, Muhao Chen, Weiwei Duan, Jina Kim, Craig A. Knoblock, Stefan Leyk, Zekun Li, Yijun Lin, Min Namgung, Basel Shbita, Johannes H. Uhl 

Chapter 12: Spatiotemporal AI for Transportation

By Tao Cheng, James Haworth, Mustafa Can Ozkan 

Chapter 13: GeoAI for Humanitarian Assistance

By Philipe A. Dias, Thomaz Kobayashi-Carvalhaes, Sarah Walters, Tyler Frazier, Carson Woody, Sreelekha Guggilam, Daniel Adams, Abhishek Potnis, Dalton Lunga 

Chapter 14: GeoAI for Disaster Response

By Lei Zou, Ali Mostafavi, Bing Zhou, Binbin Lin, Debayan Mandal, Mingzheng Yang, Joynal Abedin, Heng Cai 

Chapter 15: GeoAI for Public Health

By Andreas Züfle, Taylor Anderson, Hamdi Kavak, Dieter Pfoser, Joon-Seok Kim, Amira Roess 

Chapter 16: GeoAI for Agriculture

By Chishan Zhang, Chunyuan Diao, Tianci Guo 

Chapter 17: GeoAI for Urban Sensing

By Filip Biljecki 

Section 4: Perspectives for the Future of GeoAI

Chapter 18: Reproducibility and Replicability in GeoAI

By Peter Kedron, Tyler D. Hoffman, Sarah Bardin

Chapter 19: Privacy and Ethics in GeoAI

By Grant McKenzie, Hongyu Zhang, Sébastien Gambs

Chapter 20: A Humanistic Future of GeoAI

By Bo Zhao, Jiaxin Feng

Chapter 21: Fast Forward from Data to Insight: (Geographic) Knowledge Graphs and Their Applications

By Krzysztof Janowicz, Kitty Currier, Cogan Shimizu, Rui Zhu, Meilin Shi, Colby K. Fisher, Dean Rehberger, Pascal Hitzler, Zilong Liu, Shirly Stephen 

Chapter 22: Forward Thinking on GeoAI

By Shawn Newsam