Measuring Structural Diversity using Lacunarity

Forests are important for a variety of ecological, social, and economic values. With climate change, forest ecosystems are globally impacted. More diverse, complex forests are thought to be resilient to climate change impacts. Forest complexity is a well established concept , yet poorly quantified. For forest managers and conservation biologists to make informed decisions, quantitative measures of complexity are required. This project utilizes a measure of complexity referred to as lacunarity. In simple terms, lacunarity measures the presence of gaps in vegetation structure. We propose using lacunarity to describe the vertical and horizontal complexity of forest structure using a variety of data sources including ground data, spherical imagery, and LiDAR.

Faculty Supervisor:

John Kershaw

Student:

Partner:

Indian Institute of Science and Education Research Tirupati

Discipline:

Mathematics

Sector:

Artificial Intelligence

University:

University of New Brunswick

Program: