UCSB Research and Course Work

All Work Done Through R Studio and ArcMap Pro

Project 1

COVID-19 Data Analysis

  • Found “safe” counties in California

  • Found highest cumulative, daily new, and 7 day rolling average of cases by county

  • Look at state level data in total cases and per capita

Project 2

U.S Border Statistics

  • Looks at areas and populations within 100 miles from any US Border

  • Majority of Americans live within 100 miles of the national border <<<<<<< HEAD

  • Identify every city in which US Border Patrol has jurisdiction

Project 3

US National Dam Tessalations

  • Look at different tessalations of US County lines to identify modifiable arial unit problems

  • Analysis on dams to find where the highest dam counts are based on uses of dams

  • Point in polygon function to idenditfy number of dams in counties

Project 4

Raster Flood Analysis

  • Read in web based landsat imagery of Palo, Iowa during a flood with the goal of locating flooded regions

  • Using remote sensing data, function created to manipulated bands in satelite images to produce water oriented raster images

  • Tested 5 different flooding index function and compared accuracy

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Project 5

Flood Risk in Mission Creek

  • Analyzed the Santa Barbara basin to understand how floods will effect infastructure

  • Using raster and vector data all points within basin can be indentified relative to nearest stream elevation

  • GIF created that shows flooding effects at 20 different flood levels

Project 6

Wind Turbine Power Density Analysis

  • Determined the effect of land factors on power density (w/m2) of wind turbines with regression analysis

  • From analysis, located ideal place to construct future wind turbine facility to meet needs of Kern County

Project 7

Arizona Solar Panels

  • Based on data layers from electrical grids, wildlife, DEM, solar radiation, and cities a solar suitabilty map was generated.

  • Ideal location for photovoltaic panels was determined based upon the generated suitability data layer.

Project 8

Do Baseball Players Earn Their Salary?

  • Used 2016 offensive hitting statistics and salary data to compare high and low paid players

  • Analysis used T-test, Wilcox Rank Sum, Linear Models, ANOVA, Tukey-Kramer, Generalized Linear Models

  • conclusion: As MLB hall of famer Jeff Kent once said, “the money lies in the RBI’s”