"Does the cafe entrance look accessible? Where is the door?" Towards
  Geospatial AI Agents for Visual Inquiries
Interactive digital maps have revolutionized how people travel and learn
about the world; however, they rely on pre-existing structured data in GIS
databases (e.g., road networks, POI indices), limiting their ability to address
geo-visual questions related to what the world looks like. We introduce our
vision for Geo-Visual Agents--multimodal AI agents capable of understanding and
responding to nuanced visual-spatial inquiries about the world by analyzing
large-scale repositories of geospatial images, including streetscapes (e.g.,
Google Street View), place-based photos (e.g., TripAdvisor, Yelp), and aerial
imagery (e.g., satellite photos) combined with traditional GIS data sources. We
define our vision, describe sensing and interaction approaches, provide three
exemplars, and enumerate key challenges and opportunities for future work.
68a7f31139413c456c05b195
Jon E. Froehlich
68a7f31139413c456c05b196
Jared Hwang
68a7f31139413c456c05b197
Zeyu Wang
68a7f31139413c456c05b198
John S. O'Meara
68a7f31139413c456c05b199
Xia Su
68a7f31139413c456c05b19a
William Huang
68a7f31139413c456c05b19b
Yang Zhang
68a7f31139413c456c05b19c
Alex Fiannaca
68a7f31139413c456c05b19d
Philip Nelson
68a7f31139413c456c05b19e
Shaun Kane
admin_assigned
2025-08-22T13:05:09.790Z
65ceebf9522b760d74fa7a39
https://cdn-avatars.huggingface.co/v1/production/uploads/65ceebf9522b760d74fa7a39/jv-oJlarsG86ndQo1mwDZ.png
Shaun Kane
user
shaunkane
"Does the cafe entrance look accessible? Where is the door?" Towards
  Geospatial AI Agents for Visual Inquiries
Interactive digital maps have revolutionized how people travel and learn
about the world; however, they rely on pre-existing structured data in GIS
databases (e.g., road networks, POI indices), limiting their ability to address
geo-visual questions related to what the world looks like. We introduce our
vision for Geo-Visual Agents--multimodal AI agents capable of understanding and
responding to nuanced visual-spatial inquiries about the world by analyzing
large-scale repositories of geospatial images, including streetscapes (e.g.,
Google Street View), place-based photos (e.g., TripAdvisor, Yelp), and aerial
imagery (e.g., satellite photos) combined with traditional GIS data sources. We
define our vision, describe sensing and interaction approaches, provide three
exemplars, and enumerate key challenges and opportunities for future work.
Geo-Visual Agents integrate geospatial images and GIS data to answer nuanced visual-spatial inquiries about the world.
Geo-Visual Agents multimodal AI agents geospatial images streetscapes place-based photos aerial imagery GIS data sources