Education

PhD 2014	Geomatics / Landscape Ecology	University of Connecticut
MS 2006	Natural Resources - Earth Resources Information Systems	University of Connecticut
BS 2002	Environmental Science and Biology	University of Connecticut

Professional Experience

2019 - Present	Adjunct professor, Department of Natural Resources and the Environment, University of Connecticut
2016 - 2019	Assistant research professor, Department of Natural Resources and the Environment, University of Connecticut
2014 - 2015	Postdoctoral research associate, Department of Natural Resources and the Environment, University of Connecticut

Courses Taught

NRE 5585	Geospatial Data Processing Techniques (online) Developing Custom Geoprocessing Tools with Python
NRE 4575/5575	Natural Resource Applications of GIS
NRE 5461	Landscape Ecology

Research Interests

My research interests are in using remote sensing and geospatial analysis to address issues related to natural resources. My current research focuses on using remote sensing to help utility companies more effectively manage roadside trees to reduce power outages.

Publications

• Parent, J. and J. Volin. 2016. Validating Landsat-based landscape metric with fine-grained land cover data. Ecological Indicators 60, 668-677.
• Parent, J. and J. Volin. 2015. Assessing species-level biases in tree heights estimated from terrain-optimized leaf-off airborne laser scanner (ALS) data. International Journal of Remote Sensing 36:10, 2697-2712, DOI: 10.1080/01431161.2015.1047047.
• Parent, J., J. Volin, D. Civco. June 2015. A fully-automated approach to land cover mapping with airborne LiDAR and high resolution multispectral imagery in a forested suburban landscape. ISPRS Journal of Photogrammetry and Remote Sensing 104: 18-29.
• Parent J., M. Graziano, X. Yang. 2014. The potential of using forest residue to offset coal use in co-fired coal power plants in the eastern United States. International Journal of Agricultural and Biological Engineering 7: 99-105
• Parent, J., and J.C. Volin. 2014. Assessing the Potential for Leaf-off LiDAR Data to Model Canopy Closure in Temperate Deciduous Forests. ISPRS Journal of Photogrammetry and Remote Sensing 95: 134-145. DOI: 10.1016/j.isprsjprs.2014.06.009