I love to explore and build new things. I've recently been focused on projects to support reproducible web-based mapping. The source for nearly all my projects is available at Github.
An open-source project for exploring and navigating U.S. National Scenic Trails, starting with the Pacific Crest Trail.
The website is designed to bring together most information hikers want: data overlays exist for land management boundaries, current and historical wildfires, public transit options near the trail or trail towns, current air quality, photography, and Wikipedia articles. All units, including peak elevations and contour lines, can be switched between Imperial and Metric.
The mobile app (in progress) will give hikers a free option for navigation while
hiking the trail. It's built with React Native and
cover both platforms as efficiently as possible while giving me more experience
Essentially all data generation is automated, to allow for the possibility of expanding to other National Scenic Trails in the future.Source
A free topographic Mapbox GL basemap style with complete liberty to use and self host. This is a fork of OSM Liberty and combines vector tiles in the schema of OpenMapTiles with contour lines and hillshading to create a beautiful topographic vector map.
OSM Liberty is one of the best free Mapbox GL basemap styles for general use. I contributed styling for river names and glacier land cover.
nst-guide/terrainPython Bash Source
Scripts to generate contours, hillshade, Terrain RGB, and slope-angle shading tiles from Digital Elevation Model (DEM) data.Python Source
Scripts to generate high-resolution aerial imagery tiles from USDA National Agriculture Imagery Program (NAIP) data.Python Source
Scripts to generate map tiles from US Forest Service Topo quadrangle maps.Python Bash Source
Scripts to generate vector tile contours from USGS contour data.
Python library and command line interface to quickly and easily query elevation values on Digital Elevation Models. The command line interface can add elevations to a provided GeoJSON FeatureCollection.
Python library and command line interface to quickly and interactively visualize geospatial data with Kepler.gl. Since I work with GIS data in Python, I use this whenever I need to see my data on a map.
Stata Jupyter KernelPython Source
Jupyter Notebooks permit sharing of code and results together, with simple reproducible modifications in a web-based computational environment. Alternative front-ends like Hydrogen allow for rich HTML output even from computations on a remote server.
As of February 2020, it has been downloaded nearly 90,000 times.
The Hydrogen project is a front-end for the Jupyter project, enabling interactive coding and rich output formats inside the Atom text editor. I contributed code that allowed Jupyter Notebook files to be imported and exported as regular Python files.
While working as an economics research assistant, I built a number of open-source tools that interface with the Stata statistical package to improve research reproducibility and increase productivity.
Send code to the Stata window from the Atom text editor. This is a more primitive version of running Stata code from Atom than the Jupyter kernel above.
Syntax highlighting for Stata for the Atom text editor.
A prototype Java implementation of reading Parquet files into Stata. My first Java project, I was able to successfully read Parquet files into Stata's memory, but it ended up being less performant than my friend Mauricio Caceres' C++ implementation.
While working with Medicare data, I was frustrated with the fragmented state of public documentation regarding the data I was working with.
I scraped the ResDAC documentation website and joined it with public NBER documentation to create my own beautiful, responsive documentation website to help me search documentation faster. I used MkDocs as the static site generator and Material for MkDocs as the theming.