Dr. Clio Andris Visited UW-Madison Geography

Dr. Clio Andris (Assistant Professor of City & Regional Planning and Interactive Computing) from Georgia Tech was invited to the renowned Yi-Fu Lecture at UW-Madison Geography. Our GeoDS Lab was honored to host Dr. Andris’ visit and had a great conversation on collaborative projects and joint research.

Dr. Andris is giving her talk on spatial social network analysis.
Grads Brown-Bag Talk
UW-Madison’s own made ice cream

Prof. Song Gao received a new NSF Research Grant

Recently, Dr. Song Gao (Co-PI) received a NSF grant together with Dr. Qunying Huang (PI), Dr. Daniel Wright (Co-PI), Dr. Nick Fang (Co-PI), and Dr. Yi Qiang (Co-PI).

Title: A GeoAI Data-Fusion Framework for Real-Time Assessment of Flood Damage and Transportation Resilience by Integrating Complex Sensor Datasets

Abstract: Traditional modeling approaches for flood damage assessment are often labor-intensive and time-consuming due to requirements for domain expertise, training data, and field surveys. Additionally, the lack of data and standard methodologies makes it more challenging to assess transportation network resilience in real-time during flood disasters. To address these challenges, this project aims to integrate novel data streams from both physical sensor networks (e.g., remotely-sensed data using unmanned aerial vehicles [UAVs]), and citizen sensor networks (e.g., crowdsourced traffic data, social media and community responsive teams connected through a developed mobile app). The goal is to develop a framework for real-time assessment of damage and the resilience of urban transportation infrastructures after coastal floods via the state-of-the-art computer vision, deep learning and data fusion technologies. The project will also advance Data Science through multi-disciplinary and multi-institutional collaborations. The project is expected to improve the sustainability, resilience, livability, and general well-being of coastal communities by having a direct impact on the effectiveness, capability, and potential of using both physical and social sensor data. This will in turn enable and transform damage assessments, and identify critical and vulnerable components in transportation networks in a more effective and efficient manner. The interdisciplinary research team, along with students and collaborators from different coastal regions, will facilitate the sharing of knowledge and technologies from different socio-environmental contexts and testing the transferability of the research outcomes.

The project will harmonize physical and citizen sensors within a geospatial artificial intelligence (GeoAI) data-fusion framework with a focus on three research thrusts: (1) unsupervised flood extent detection by integrating UAV images collected throughout this project with existing geospatial data (e.g., road networks and building footprints); (2) flood depth estimation using deep learning and computer vision techniques combined with crowdsourced photos and UAV imagery; and (3) assessment of the impact on and resilience of transportation networks based on near real-time flood and damage information. The innovative methodology will be demonstrated and deployed through collaborative efforts in response to future flood events as well as several historical storms. The project will produce open-source algorithms for future educational use, raw and processed datasets and associated processing software, a mobile app to engage community responsive science teams, and three research publications.

Source: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1940091

Prof. Song Gao received an AI for Earth Grant from Microsoft

[Madison, WI/USA] – [August 8, 2019] – Professor Song Gao as the Principal Investigator (PI) has been awarded an AI for Earth research grant from Microsoft to help further the efforts in the area of Geospatial Artificial Intelligence (GeoAI).

This new grant will provide Dr. Song Gao and his research assistants Yuhao Kang and Jake Kruse at the GeoDS@UW-Madison lab, and Dr. Fan Zhang (Postdoc Researcher at the MIT Senseable city Lab and Peking University) with the Azure cloud computing resources and AI data labelling services to accelerate their work on understanding the playability of cities and metropolitan areas from the human-environment interaction perspective using multi-source geospatial big data (e.g., images, texts, and videos).

The Microsoft AI for Earth is a $50 million, 5-year program that brings the full advantage of Microsoft technology to those working to solve global environmental challenges in the key focus areas of climate, agriculture, water and biodiversity. Through grants that provide access to cloud and AI tools, opportunities for education and training on AI, and investments in innovative, scalable solutions, AI for Earth works to advance sustainability across the globe. 

Learn more about the Microsoft AI for Earth program: https://www.microsoft.com/en-us/aiforearth 

Timothy Prestby Received the HILLDALE FELLOW Award

Please join us congratulating our junior student Timothy Prestby, who is currently an undergraduate research assistant in the GeoDS Lab under Prof. Song Gao’s mentorship, just got the university “Hilldale Undergraduate/Faculty Research Fellowships” and was awarded  in the 2019 Chancellor’s Undergraduate Awards Ceremony! 

The awarded research project title is: Understanding Neighborhood Isolation through Big-Data Human Mobility Analytics”. 

Previous Hilldale Fellows at the University of Wisconsin-Madison:


Professor Gao was appointed as the Associated Editor of Annals of GIS

Professor Song Gao was invited and appointed as the Associated Editor for the CPGIS flagship journal: Annals of GIS  published by Taylor & Francis.

Annals of GIS is an international peer-reviewed journal that encourages the interdisciplinary exchange of original ideas on theory, methods, development and applications in the fields of geo-information science. Research papers are invited to cover the latest development in the following areas:

  • remote sensing and data acquisition
  • geographic information systems
  • geo-visualization and virtual geographic environments (VGE)
  • spatial analysis and modeling
  • uncertainty modeling

and their applications in natural resource, ecosystem, urban management, and other humanities and social science areas.