Current Lab Members

Morgan Crowley

PhD Student (Department of Natural Resource Sciences)

Research Interests: Remote sensing, GIS, land cover mapping, land-cover change detection, monitoring, Google Earth Engine, applications of GIS and remote sensing

Land-cover change is very important to map because it informs government decisions regarding land-use planning, carbon sequestration, disaster susceptibility assessments, and other land management. My current research explores the use of the Bayesian Updating of Land Cover (BULC) algorithm in rapid and accurate identification of land-cover change. I hypothesize that using Google Earth Engine and BULC, I can improve the temporal frequency and categorical depth of land-cover change classification compared with other common methods. I am interested in applying these techniques to analyze both natural and human land-cover change events such as wildfires, urbanization, logging, etc. Scientific communication and outreach is an additional goal of this project. To address this goal, I am working with a fifth grade teacher to make this science accessible for young scientists of all backgrounds. A curriculum exploring these concepts and theories will be freely available for teachers in Summer 2018.

Jacky Lee

MSc Candidate (Department of Natural Resource Sciences)

Research Interests: Landscape ecology, Remote sensing, spatial ecology, community ecology, invasion ecology.

Humans are causing extraordinary changes in our environment from changes in land use to introduction of invasive species. It is important then to track these changes and identify areas where we are able to target conservation efforts to conserve biodiversity. As technology has improved to the point where it is now possible to see time lapse changes in landscape using remote sensing techniques in real time. In my project. I have developed the tools needed in Google Earth Engine platform to quickly update classifications. I use Bayesian statistics, machine learning, fine scale satellite images, and global level land cover classifications to create time series of land cover classifications which are downscaled and accurate. The algorithm called Bayesian updating of land cover classifications: Unsupervised (BULC - U) allows the creation of land cover classification in minutes using fine scale satellite images. My MSc thesis focused on creating and using BULC-U to track changes in the Brazilian Land cover over 14 years.

Xavier Giroux-Bougard

PhD Student (Department of Natural Resource Sciences)

Research Interests: Landscape genetics, landscape ecology, functional connectivity, spatial ecology

As the configuration and spatial structure of landscapes change, conservation biology and wildlife management are ever more concerned with the degree of flow and movement of individuals within and between wildlife populations, defined as functional connectivity. Understanding how species use habitat to disperse and migrate is critical in assessing the long-term viability of their populations as well as developing improved tools to identify areas which significantly contribute to the connectivity of the landscape. My research focuses on optimizing models of landscape connectivity using population genetic data as a proxy for long term wildlife movements at large scales. Specifically, I am interested in: (1) understanding how individual species respond to large disturbances in a landscape (forestry, forest fires, etc...), (2) understanding how much time it takes to restore the functional connectivity of a disturbed landscape, and (3) developing new tools to build landscape connectivity models which optimize the functional connectivity of multiple species.

Eric Davies

Bachelors of Computer Science Student (2015-Present)

Focus on: Project support, development, and maintenance along with documentation and support of past projects.

Computer Science is a field to itself, complex to its own right. Expecting researchers to understand how to take advantage of computers while being knowledgable of their own field is asking them lose time in their field of choice to learn about computers. As a programmer, my task is to bridge this gap by making advantageous computer technologies available to our team. This has led to support of the BULC algorithm for the Google Earth Engine, support and development of the student learning tool Metaland and it's child Metrics Finder, and general project support for a multitude of different projects being developed in this lab. My focuses are on code optimization and knowledge accessibility, two aspects that are key in bringing programming to a general audience.