Charles Parr ¶

email: charlie dot parr at alaska dot edu

Education ¶

University of Alaska Fairbanks ¶

• B.S. Geography - concentration in Landscape Analysis & Climate Change - 2012
• M.S. Geoscience - Snowdrift Landscape Patterns: An Arctic Investigation - in progress

Professional Experience ¶

• 2015 – Current: Research Technician, Geophysical Institute Snow Ice & Permafrost Group, UAF
  • Creating and publishing knowledge at the intersection of snow and geospatial science
  • Economic analysis of the present and future value of water from snow in the western U.S.
  • Snow stakeholder engagement: report and workshop with industry and management agencies on the snow of the Arctic National Wildlife Refuge
  • Veteran of 1000s of miles of scientific snowmobile traverses across the Arctic
• 2014 – 2015: VP of Business Development, ArcticFire Development Corporation
  • Tech startup building open source software and hardware for drones
  • Investor relations - won the 2014 Arctic Innovation Competition
• 2012: Research Technician, Alaska Center for Energy & Power, UAF
  • Investigation of geothermal energy resource at Pilgrim Hot Springs, Alaska

Technical Skills ¶

• Python Programming: SciPy ecosystem, geospatial tools (e.g. Rasterio, GeoPandas, xarray), image processing (e.g. OpenCV), data visualization (e.g. seaborn, Bokeh) and web scraping (e.g. Selenium).
  • Created novel toolbox of geospatial image/pattern similarity metrics
  • Developed a Monte Carlo-style method of raster subsampling
  • Built a web scraper for Alaska FAA webcam images
• Data Wrangling and QA/QC
  • Automated snow depth raster correction and validation process using over 100,000 ground control points
  • Established process for cleaning tabular geospatial snow depth data
  • Produced open source processing pipelines to go from lidar/photogrammetry point clouds to DEMs/DSMs.
  • Metadata creation and curation for dataset publication (Arctic Data Center)
• GIS, GDAL, & PDAL
  • Designing publication quality maps and figures (QGIS, ArcGIS)
  • Automated raster management and creation of terrain derivative products
  • Reproducible point cloud outlier filtering for gridded surface generation
• Linux
  • Fedora is my daily driver
  • Bash scripting to manage all the above