Spring Regional Spotlight: "Shiny" things!
Every so often it's fun to hear about something other than parcels and addresses, don't you agree? We have just such a diversion for you at the Spring Regional Meeting.
Matthew Haffner, Assistant Professor or Geography and Anthropology at UW-Eau Claire, will demonstrate and detail the development of a web-based landscape search engine for the state of Wisconsin. The search engine combines the qualities of terrain and vegetation to return similar locations, and it allows users to specify the weight placed on each quality. Similarity metrics for terrain are derived using three existing deep learning models -- VGG16, ResNet50, and NasNet -- while the vegetation similarity metrics are computed using normalized difference vegetation index (NDVI). The modeling was completed using Python, and the web application was created with R's web framework Shiny.
The tool, titled "LSE Wisconsin" can be found at the following link: https://uwec-geog.shinyapps.io/lse-wi. Make sure to check it out before the meeting. Pick your location and play around with the variables to find other similar locations around the state. You might be surprised where it takes you!
Come to the 2023 WLIA Spring Regional Meeting to learn more.