R Packages





UCSB | GEOG 176C w/ Dr. Krzysztof Janowicz


BURNDEX: Spatial-temporal Burning Index Forecasting
  • Supplementing Chandler Burning Index forecasts with a machine learning approach.
  • Built together with Angus Watters.

UCSB | GEOG 176A w/ Dr. Mike Johnson

Tracking COV…

Tracking COVID-19 Data
  • Parsed real-world data using tidyverse functions and plotted using ggplot2.
  • Used statistical methods for analyzing confirmed COVID-19 cases.
  • Analyzed COVID-19’s weighted mean center travel across the United States.

Analyzing Sp…

Analyzing Spatial Data in the US
  • Gathered spatial data about US cities and their relation to national borders using tidyverse and sf libraries.
  • Used gghighlight and ggplot2 to visualize spatial data, and sf to calculate distances.
  • Analyzed controversial Federal Agencies’ claims based on an ACLU article to verify statistics given.


Point-in-Polygon Analysis with Tessellations
  • Generated and analyzed tessellated spatial datasets, such as: square and hexagonal coverages, Voronoi tessellations, and Delaunay triangulation.
  • Performed point-in-polygon analysis using US Dams dataset from US Army Corps of Engineers.
  • Created a leaflet interactive map to analyze dams at risk for floods along the Mississippi river system.

Flood Analys…

Flood Analysis using Remote Sensing
  • Using Landsat Data generated rasters and computed band combinations for surface water features.
  • Utilized statistical methods, namely k-means clustering to highlight potential flood areas.
  • Applied flood data to visually identify at-risk areas using leaflet/mapview.

Flood Risk i…

Flood Risk in Mission Creek: Past, Present, Future
  • Pulled data from the USGS and OpenStreetMap to assess the flood risk of buildings near a river system.
  • Used whitebox to create a Height Above Nearest Drainage raster for a specific AOI.
  • Created a Flood Inudation Map Library to observe flood impact on surrounding buildings.