Thanks to funding from an EPSCoR grant, we have partnered with the University of Alaska, Anchorage, to study effective natural resource management through the application of machine learning to drone acquired data.

Project Summary

We will use machine learning (ML) to process imagery and other data acquired by autonomous aerial systems (UAS). Processed data will support scientific research in natural resource management by providing a clear means of testing hypotheses. The three areas of natural resource management we will investigate and the intellectual merit of studying them are:

1) Snow water resources, because energy production, agricultural output, and economic growth require improved assessment of the natural capital banked in the mountain snowpack.

2) Fire management and science, because an advanced understanding of the physical and ecological processes driving wildfire is required for management practices that better protect forests and the critical infrastructure within them.

3) Abandoned oil well monitoring, because detecting and mapping uncapped or improperly sealed oil and gas wells will provide critical data for improved mitigation, site reclamation, and hazard removal.

This material is based upon work supported in part by the National Science Foundation EPSCoR Cooperative Agreement OIA-2119689. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.