Project Image

Analysis of Suitability for Eucalyptus Growth in the San Francisco Bay Area, California

Using MaxEnt in ArcGIS Pro and Random Forest in Python

Team Members:

Jason Andrews, Rory Dickinson, Tanner Honnef, and Caleb Kluchman

Affiliation:

GEOG 397: Advanced Raster GIS

Project Description:

This project compared the output of Random Forest and MaxEnt for Eucalyptus suitability in the San Francisco Bay Area. This analysis was done with a vareity of input variables which can be found on the poster above. The MaxEnt model found that Eucalyptus is most likely to grow near structures and at low elevations. Eucalyptus is frequently planted in built areas which is likely why the distance to built is such an important variable.



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