Files
Download Full Text (890 KB)
Digital Publisher
Digital Commons at St. Mary's University
Publication Date
Spring 2025
Keywords
Machine learning; Prickly Cacti; Invasive species; Software development; Python; CSS
Description
This project sets out to create a tool to help aid in the research and monitoring of the threatened prickly cacti [Fig. 1]. due to an invasive species of insect growing to be a threat. This website displays current and predictive locations of foliage within a region.
To get the data of the predictive location, an additional program was developed that uses a machine learning model to provide coordinates of potential areas where more plants may be. The computer program provides a visualization of potential patterns for the foliage in the database. The machine learning model combs through the data and provides patterns for researchers. The website provides visualizations by comparing the output of similar locations.
Format
Size
1 page
City
San Antonio, Texas
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Included in
Environmental Education Commons, Environmental Health and Protection Commons, Environmental Monitoring Commons
