Working Groups

Parametric Geodesign in Park County

This proposal, by Ryley Enich and Aleck Gantick, focuses on the collection and sharing of prioritized data layers for Park County. These data layers include the quantification and characterization of various ecological, socioeconomic, and land use conditions of Park County. The beginning of this project will focus on sourcing existing data and identifying data needs based on various stakeholder’s inputs. The data will then be used to generate a model which creates maps and 3D visualizations of existing conditions, both human and natural. In addition, this model will have the capacity to project and simulate “what if” scenarios based on scientific data. Ultimately, these data layers and models can be used to inform decision making. This proposal strives to make data and decision making more transparent, inclusive, and accessible.

If a picture is worth 1,000 words, what is a 3D visualization worth?

Aleck Gantick

I grew up in Clark, Colorado and have always had a great passion for the outdoors and the environment. I have a Bachelors in Environmental Design and a Masters in Architecture from Montana State University. Currently, I am helping YERC quantify, characterize, and visualize various ecological, socioeconomic, and land use conditions in Park County. In my free time you can find me fishing small creeks, backpacking, mountain biking, or backcountry skiing.

Ryley Enich

Hi, I'm Ryley. Growing up in Missoula I have always had a passion for the outdoors. I came to Bozeman to pursue a masters degree in Architecture from Montana State University. I am excited to use my background in architecture to help YERC visualize ecological data by creating three dimensional models to aid in decision making for land use in Montana. In my free time I enjoy watercolor painting, backpacking, and fly fishing.

MSU Computer Science Students

**Hannah Madsen**
**Kieran Ringel**
**Natalia Eigner**
**Grayson O’Leary**

YERC Mobile Application and Data Integration Processes

Mobile Application for field data collection (by YERC): Design and build a mobile application to improve the timeliness and accuracy of ecology data collected in the field. Types of data collected will include photos of wildlife, aquatic insects, and vegetative ground cover, and data for water quality samples or soil moisture. The application will integrate with YERC's EPIIC platform which is an open source, cloud-based platform for sharing of ecological/environmental data. These data streams will be also used for further analysis and modeling such as identification of species and ecological forecasting of climate change impacts.

Enhance EPIIC data ingress processes for Integration of remote sensing data (by YERC): Using cloud-based services, EPIIC currently supports the downloading and integration of a limited number of satellite imagery datasets from Microsoft Planetary Computer (MPC). This needs to be expanded to include additional MPC data products as well other airborne sensors -- in particular, lower-cost drone imagery that YERC is now regularly collecting. This project includes the integration of imagery into AI mapping products as well as ingestion into simulation models of water budgets, habitat succession, flooding and wildfire risk.

MSU Mechanical Engineering Students

Large Mammal Tagging

Ungulates, or hooved animals like elk, deer, and bison, perform vital roles within the ecosystem and there is a growing need to monitor their populations. Monitoring wild animal populations may include aerial surveys, live trapping, or camera trapping. These methods can be expensive, inaccurate, invasive, and laborious. Automating camera trapping methods can be an inexpensive, accurate, and non-invasive means to estimate population size as well as gather other important ecological information. Camera trapping methods gather the required information to utilize the statistical formula, Capture-Mark-Recapture (CMR), for estimating a population.

This project aims to combine traditional camera trapping with computer recognition software and paintball gun technology to create a more automated method for obtaining the data required for CMR. In the terms of this project, a “capture,” will be a short video clip of an ungulate taken by a motion censored camera. The camera will trigger a paintball to be released and “mark” the large mammal. Any subsequent video clips containing ungulates with paint on their fur will be considered a “re-capture.” A computer recognition software will be developed to identify the ungulate and to distinguish between human or animal and large adult mammal versus small. This software may be developed by modifying other software resources.

Front Row (left to right): **Toni Seppi, David Taylor, Matt Chase, Charlie Kinneberg, Raychel Limnios**
Back Row (left to right): **Nathan Blomback, Aaron Schoening**

Aerial Predator Deterrent - Team A

Our challenge is to design and build a rotating camera system that attaches to the drone of the other Aerial Predator Deterrent team. The camera will not only send back live video feed, but also the feed will be encrypted in order to incorporate some sort of cybersecurity in the transmission.

Aerial Predator Deterrent - Team B

Design an auditory, visual, and olfaction deterrent device(s) capable of mounting (pod system). Design criteria include a mechanical remote point-and-shoot trigger system for spraying the carnivore with bear spray. The auditory/visual deterrent would only require a remote switch to 'turn-on' once it is near the carnivore

**Jake Claeys**
**AJ Johnson**
**Patrick Richardson**

John Winfield
Isaak Bell
Macager Mcallister
Noah Cleary

Smart Fishnet

Design, develop, and test a RFID reader for trout to see if they are marked or not.