Projects

High house values cluster in areas with high tree cover. 

Results

The choropleth map shows definite spatial clustering around high levels of greeness in Santa Clara County tracts.  Moran's I confirms spatial clustering (I = 0.22, p = 0.001). Greener neighborhoods cluster together and have higher Greenness values. People put a high value on houses in green spaces with tree canopy. 

I used US Census variables and NOAA 2.5 foot sea level flood predictions to determine whether neighborhoods are more or less vulnerable to 3.5 ft. sea level rise based on income and poverty factors. 

StoryMap

Industrial and commercial employments lands in the City of San José have been converted to residential, or from industrial to commercial lands over the last 40 years. The city planning department asked my team to document the changes over time and examine the 2040 General Plan to  project land use changes. 

Group Work with Ingrid Salazar and Sanjana Kurupatir Ramakrishna for Mr. Rick Kos' Advanced Urban Planning Course at San José State University. This project was completed in cooperation with the City of San José  Planning Department. 

GIS Skills: Calculate Fields, ModelBuilder, Python coding, Spatial Join, Georeferenceing, Select by Attribute, Dashboards, Instant Web Apps and Maps, ArcGIS Online. 

This lab project explored the accessibility of Portland Bus Stations. I then compared the network polygons with access to bus travel by different population groups: renters vs. owners. 

GIS skills:  Network Analysis, Calculate Geometry, bivariate maps, census data research. Layout Sample.