Fort Collins, Colorado, United States
• Geospatial data scientist with nearly a decade of experience in remote sensing, spatial data analysis, spatial statistics, cartography, data visualization, time-series analysis, tool development, and ecological modeling. • Strong technical proficiencies in Google Earth Engine, Python, R, GIS (ArcGIS and QGIS). Also works in MATLAB, Linux, and web development. • Subject matter expertise in spatial ecology, landscape ecology, remote sensing of vegetation, decision-support systems, ML for remote sensing.. • Developer of multiple natural resources management decision-support tools using remotely sensed datasets and multiple regional modeling analyses.
- Maintains and enhances the Climate Engine web application by adding new datasets and resolving bugs and issues in Python and Javascript. - Develops and maintains Earth Engine database to manage time-series climate end remote sensing data for large vector datasets. - Develops Earth Engine web applications to provide advanced analysis of spatiotemporal datasets, including the ARkStorm project. - Provides workshops, Colab notebooks, documentation, technical tutorial videos, and public presentations to support federal agency applications of the Climate Engine tool and API. - Contributes to project proposals to BLM and NASA ROSES and research projects for the Upper Colorado River Basin, ARkStorm, and others. - Led initiative to update the ClimateEngine.org website and develop a new Support website, including creating code, content, and data visualization.
Affiliate Faculty Member in the Department of Ecosystem Science and Sustainability (ESS) through the Radical Open Science Syndicate (ROSSyndicate).
- Provide technical contributions in a multi-disciplinary team environment to improve and build upon our analytics-driven platform - Identify valuable data sources and automate collection processes - Undertake preprocessing of structured and unstructured data - Work under the direction of the Head of Technology to analyze industry trends, identify gaps and build predictive models and machine-learning algorithms - Present information using data visualization techniques - Propose solutions and strategies to business challenges - Collaborate with engineering and product development teams
- Developed and administered RAP Production Explorer web application using R (leaflet, plotly, tidyverse, shiny), CSS, HTML, Bootstrap, and Javascript - Developed and administered Bureau of Land Management Allotment Reporter web application using R (leaflet, plotly, tidyverse, shiny), Mapbox, CSS, HTML, Bootstrap, and Javascript - Produced web-based interactive reports using ecological model outputs for every state and county in the western US using RMarkdown (leaflet, tidyverse, ggplot, etc.), Bootstrap, CSS, and HTML. - Developed and maintained Rangeland Analysis Platform user support website including support documentation, videos, and CSS code. - Produced technical training and data support videos using Shotcut and OBS Studio. - Provided workshops, short courses, and presentations applications of remote sensing and ecological modeling data in resource management. - Created cartographic and data visualization products featured in publications and online media using ArcGIS Pro, R, and Google Earth Engine. - Provided direct consultation to local- to regional-scale rangeland initiatives using satellite-derived data in conservation decision-making.
- Developed scripts in R to generate image centroids for 3D modeling in Agisoft Metashape, manage ground control points, and perform quality checks on rectified images. - Developed script in MATLAB to crop and standardize all historical images downloaded from USGS Earth Explorer (30,000+ images). - Generated point clouds, 3D models, DEMs, and orthorectified images using Agisoft Metashape using 18,000+ images for Montana, Wyoming, and Idaho. - Performed georeferencing of historical imagery orthomosaics in QGIS and ArcGIS Pro. - Validated model spatial accuracy using a system that I developed in QGIS and R.
Thesis research involved remote sensing and machine learning modeling of post-fire vegetation recovery and plant species diversity in Great Basin shrublands using ArcGIS Pro, R, and javascript and Python APIs in Google Earth Engine. - Developed dozens of scripts in Google Earth Engine (javascript and python APIs to calculate over 200 predictor variables for machine learning models including climate, vegetation, remote sensing, fire, and soils variables. - Developed dozens of scripts in R for machine learning modeling (random forest and XGboost), time-series analysis, automating the downloading and mosaicking thousands of raster images from online repositories, and other purposes - Developed two Google Earth Engine applications for the Normalized Differenced Perennial Dominance index and plant species richness models. - Cleaned and processed data from tens of thousands of field training points from the Bureau of Land Management and Natural Resources Conservation Service for training models. - Designed field vegetation sampling schema in ArcGIS using remotely sensed data to ensure sampling across a gradient of fire severity for training models. - Developed project proposals for Joint Fire Science Program (awarded, $25,000) and NASA FINESST (not awarded). - Teaching Assistant for GIS, remote sensing, and ecological management courses. - Produced training data for multiple other remote sensing and ecological modeling projects.
- Served as student representative on NREL Executive Committee. - Established the Graduate Student Finance Committee. - Contributed to Graduate Student Finance Committee identifying policies to improve student equity and fiscal well-being. - Fundraised through t-shirt design and sales, coordination with Graduate Student Council, and soft drink sales. - Organized department social events.
- NR323 - Remote sensing - Prof. Michael Lefsky — Spring 2020 2 lab sessions (64 students), introduction to remote sensing; transition to online curriculum. - NR322 - Geospatial Applications in Natural Resources - Rocky Coleman — Spring 2019 2 lab sessions (60 students), introduction to geospatial concepts, analysis, and GIS. - NR420 - Integrated Ecosystem Management - Dr. Jeremy Sueltenfuss — Fall 2018 2 lab sessions (24 students), capstone for data-driven natural resources management.