Salmonshield

Inspiration

On our 5th grade outdoor trip, we went to streams full of salmon that was dwindling salmon. In Earth Scince 8, we learned how vital they are to the PNW ecoystem and we wanted to help safe them.

What it does

It's takes user address and runs it through key datasets to get data and ways to help for the user. We offer suggestions for the community members to better support the local environment of salmon using gpt 4o. It shows nearby salmon streams colorcoded by risk, stormwater discharge points, watershed boundaries, and animates the actual path runoff travels from your street to the nearest stream. It lends them detailed insights into how their community affects salmon population through URMS which returns a 0-100 Danger Score.

How we built it

Took data from usgs and wagov and downloaded as geojson
Used Flash backend with geopandas
Watched a lot of yt tutorials and documation to implement the reading of these files.
Used leaflet for the map and openstreetmap tiles
Used a weight scoring model for the most accurate end resu;lt

Challenges we ran into

Reading the data that was absolutely massive -Understanding how geojson works. We had never seen them before

Accomplishments that we're proud of

Gathering a bunch of databases and piecing together into one big helpful map. ## What we learned
Geojson files -Managing data and large files -Working as a team with github desktop -Merge conflicts -Annotating maps -And finding features for implemantion