Dr. Kyle R Kovach is a postdoctoral researcher at the University of Wisconsin-Madison, working with Dr. Phil A. Townsend in the department of Forest and Wildlife Ecology. He works primarily on two funded projects which include NASA ABoVE (Arctic-Boreal Vulnerability Experiment) and NSF NEON (National Ecological Observation Network). Both utilize ground sampled foliar traits to create airborne hyperspectral imagery models to predict traits at larger scales. In his doctoral work, he used drone-based hyperspectral and lidar remote sensing in experimental biodiversity-ecosystem function tree plantations to assess biochemical and morphological properties of trees to reveal functional variation. In his masters, he worked to build drones and sensor systems for ecological applications, as well as predictive models for harvest analysis in cooperation with the Cary Institute on a USDA grant.
Research Keywords & Expertise
Community Ecology
Landscape Ecology
Microsystems
Plant Ecology
Statistics
System Design
UAV
Structure from Motion ...
Boreal Ecosystems
Sensor Engineering
Terrestrial LiDAR
Machine Learning (geo...
Computer Engineering
Remote Sesnsing
Arctic Ecology
Hyperspectral Imagery
Lidar
Drone
Functional Ecology
UAV Engineering
Hyperspectral Spectros...
Short Biography
Dr. Kyle R Kovach is a postdoctoral researcher at the University of Wisconsin-Madison, working with Dr. Phil A. Townsend in the department of Forest and Wildlife Ecology. He works primarily on two funded projects which include NASA ABoVE (Arctic-Boreal Vulnerability Experiment) and NSF NEON (National Ecological Observation Network). Both utilize ground sampled foliar traits to create airborne hyperspectral imagery models to predict traits at larger scales. In his doctoral work, he used drone-based hyperspectral and lidar remote sensing in experimental biodiversity-ecosystem function tree plantations to assess biochemical and morphological properties of trees to reveal functional variation. In his masters, he worked to build drones and sensor systems for ecological applications, as well as predictive models for harvest analysis in cooperation with the Cary Institute on a USDA grant.