As climate change intensifies extreme weather, two new NYU studies show 3D flood visualizations developed by a cross-institutional research team dramatically outperform traditional maps for communicating risk.
When Sunset Park, Brooklyn residents compared both formats that visualized flooding, 92% preferred the dynamic 3D approach.
"The challenge we face is that substantial sectors of the population ignore flood warnings and fail to evacuate," said Professor Debra F. Laefer , the NYU Tandon School of Engineering senior researcher involved in both studies who holds appointments in the Civil and Urban Engineering Department and in the Center for Urban Science + Progress (CUSP). "Our findings suggest dynamic 3D visualizations could significantly improve how we communicate these life-threatening risks."
A Laefer-led team from NYU Tandon and NYU Steinhardt School of Culture, Education, and Human Development — with colleagues from University College Dublin and Queen's University Belfast — developed a low-cost visualization method that transforms LiDAR scans of urban streets into immersive flood simulations, detailed in a paper called " Low-Cost, LiDAR-Based, Dynamic, Flood Risk Communication Viewer " published in Remote Sensing.
Under leadership of Tandon and Steinhardt researchers, the team evaluated these visualizations in a second paper, " From 2D to 3D: Flood risk communication in a flood-prone neighborhood via dynamic, isometric street views ," published in Progress in Disaster Science. This study compared visualization methods for a Category 3 hurricane scenario: a conventional NOAA flood map versus a 3D simulation showing water rising to three feet at the intersection of 4th Avenue and 36th in Sunset Park.
The results were stark. Not only did participants overwhelmingly prefer the 3D visualization, but 100% found it more authoritative than the traditional map, with a significantly better understanding of evacuation challenges.
What makes this approach innovative is its computational efficiency. Unlike existing systems that require powerful hardware, it decouples flood prediction from visualization, allowing operation on standard computers.
"We achieved this using a Potree viewer coupled with Inkscape to create dynamic flood water flow," Laefer notes. "Our study didn't require a graphics card — just a single, quad-core processor."
The visualization includes realistic water movement created through compounding sine wave functions, with algorithms controlling transparency, color, and flow speed.
"One of the most rewarding aspects was seeing how participants instantly grasped the flood severity without technical explanations," said Kshitij Chandna, a master's student advised by Laefer at the time of the research, who is the co-author on both studies. "When someone looks at a 3D simulation and says 'I would need to evacuate,' you know you've successfully communicated risk in a way traditional maps cannot."
For Sunset Park's immigrant community, many facing language barriers, the intuitive 3D visualization proved particularly valuable. Participants described it as "more realistic," "clearer," and "more visual" than traditional maps.
The implications extend beyond flood visualization. The researchers have already demonstrated visualizing water flowing through pipes and are exploring applications for other types of flooding.
As climate change increases flooding frequency, this research suggests dynamic 3D visualization could bridge the gap between abstract warnings and concrete actions needed to save lives.
The Remote Sensing paper's authors are Laefer, Chandna, Evan O'Keeffe, Kim Hertz (NYU Tandon); Jing Zhu and Raul Lejano (NYU Steinhardt); Anh Vo and Michela Bertolotto (University College Dublin); and Ulrich Ofterdinger (Queen's University Belfast). The Progress in Disaster Science paper was authored by Zhu, Laefer, Lejano, Peter Gmelch (NYU Tandon), O'Keeffe, and Chandna.
The United States National Science Foundation provided funding for this research, which builds upon Laefer's pioneering work in LiDAR and remote sensing technologies for urban applications.
