By Lingshan Li, PhD candidate at Concordia University

In the last year of my PhD program at Concordia University (2024), I went to Washington, D.C., to attend the American Geophysical Union (AGU) annual conference to present my work with the help of the excellence award provided by the QCBS. 

When I departed from Montreal, it snowed a lot (the first big snowstorm of the year in Montreal) and I struggled to get to the bus station. After I landed in Washington, the sun and the nice weather gave me a warm welcome. I went to the conference centre first and got my badge printed, then I took a city walk and visited some landmarks.

AGU is a huge conference that involves almost all the fields you can imagine in earth science studies. Though it was not my first time attending this conference, the enormous number of presentations still shocked me. There were more than 27,000 presentations in the conference and hundreds of subsessions. In other words, as a student working on an interdisciplinary program, I was able to find a bunch of studies that match my research a lot or fit one of my disciplines. 

This year, the theme of AGU was “What’s Next for Science”. Machine learning is very popular in recent “AI” years, and I saw hundreds of thousands of studies that have applied machine learning models in earth science studies, helping people with observing, mapping, simulating and decision making. The varied applications of machine learning gave me a deep impression, which kind of encouraged me to think about using it in my own research.

I gave an eLightning presentation on how spatial patterns of urban green infrastructure impact the cooling service they provide and how equitable is the people’s access to the cooling service in terms of their socioeconomic status, race and education level in Montreal. I really enjoyed the eLightning presentation type, it’s just like a combination of oral and poster presentations. I gave a 3-minute talk followed by an hour of discussion. Actually, I feel like a 3-minute talk is more challenging than a long talk, as you have to introduce the key points of your research and attract people’s interest as well within such a short time. But I believe I did it well and received much positive feedback. There was almost no blank time during the discussion part, and I was very happy to introduce my research to people coming from similar or different fields. Some of the questions or comments also brought inspiration to me.

During the conference, I found an interesting study which is similar to mine but conducted in Maryland, U.S. We had a deep discussion on combining the natural science and social science together to help the stakeholders make more efficient, local-based and balanced policies. We exchanged our contact information and we expect further cooperation in the future. 

I also explored the GeoAI tools at the ESRI’s platform. The staff introduced the AI tool in ArcGIS Pro and the applications for ecosystem studies, such as tree segmentation, 3D tree canopy modelling, biodiversity mapping, etc. A bunch of companies that work on environmental assessment showed their products at the conference, and I was impressed by the variety of sensors that can implement air temperature, air quality, or surface temperature monitoring with a high spatial/temporal resolution. As part of my PhD study also involves field measurement, I had some valuable discussions with them and just wondered if there is any possibility to use them in my future work.

Most of the research at the AGU conference was conducted at quite a large scale (global or country scale), which gave me a better view of the recent global environmental change. Though my study focused on a relatively small spatial scale (limited to Montreal), the global scale studies still provided great references and inspiration to me. Better communication across various cities could also bring valuable insights for the stakeholders in each individual city. 

I was really immersed in the conference, spending the whole time at the convention centre every single day until the end. I feel like I did a “literature review” of the latest earth science progress during these intense 5 days. Thanks to QCBS’s help, I got a great experience in Washington and had a better view of urban heat, air quality, machine learning, community science and decision making studies, hopefully to support the ongoing or future studies in Quebec.

About the author: Lingshan is a PhD student in the program Geography, Urban and Environmental Studies at Concordia University. She is supervised by Dr. Ursula Kross, Dr. Carly Ziter, and Dr. Angela Kross. She is studying the effects of vegetation and the built environment on urban microclimate in Montreal, using a combination of remote sensing and field-based approaches. Her research falls within the Next Generation Cities Institute as well as the DesignLIFES NSERC CREATE.