GIS & Geospatial Technology
Why GIS?
While completing my associate in geology at Santiago Canyon College, I was enrolled in purely physics and calculus courses. Longing to have a connection to geology and technology while waiting to transfer to a university, I enrolled in the UCLA Geographic Information Systems (GIS) and Technology certificate program.
As a child, I had always loved maps and geography, spending countless hours pouring over an oversized Atlas and worn-out globe. My most coveted toy was the GeoSafari Electronic Learning System, which has geography cards to learn about geologic landmasses and geography. Studying GIS and geology as an adult was a natural fit.
GIS Education
UCLA's GIS and Spatial Technology certificate, a comprehensive 5-course online program geared towards complementing STEM degrees, taught me how to use datasets of all sizes to visualize complicated relationships between places and data through hands-on experience. As a scientist and STEM educator, this skillset has been invaluable in how I communicate advanced scientific concepts.
Coursework
Introduction to GIS
Advanced GIS
GIS Programming
GIS Databases and Enterprise GIS
Cartography
GIS Software
ESRI ArcGIS Suite
ArcGIS Pro
ArcGIS Enterprise
ArcGIS StoryMaps
ArcGIS Field Maps
ArcGIS Online
ArcGIS Desktop
ArcMap
ArcScene with 3D Analyst
ArcCatalog
QGIS
Tableau
GIS Case Studies
GIS Climate Report
ArcGIS maps I created for to analyze different methodology of interpolation to compare and understand best practices in a climate consumer report.
This report was created to inform potential homebuyers of California’s climate for January and August. The warmest and coolest cities in California during winter and summer are estimated using interpolated values of normal monthly high temperatures. All temperatures given are in Fahrenheit. Data collected by NOAA in 2010.
Technical Addendum
The estimates in the report use Inverse distance weighting (IDW) interpolation with 8 sectors and optimized power with the mean prediction error of 0.3605 for January and -0.1307 for August.
Using the other method of Empirical Bayesian Kriging (EBK) interpolation on the data with log empirical transformation and K-Bassel semivariogram type, the mean prediction error is 0.1141 for January and 0.1317 for August.
When the same data is derived by using zonal statistics on EBK prediction maps there is only slight variances in temperature when compared to the results for IDW. In most cases the top ten listed cities are shifted by a few places within the list.
GIS Market Analysis
ArcGIS maps I created in a market analysis, prepared to offer recommendations for store closures based on service areas of stores in Riverside, California, through GIS-based market analysis using population, demographic characteristics, and estimated geographic areas served by each existing Starbucks location. Data collected by OpenStreetMap in 2020.
Technical Addendum
Store #6616 was recommended for closure because of a 2.6% of the population coverage area and 27,796 residents within a three-mile drive. Four nearby stores were between four to eight minutes from store #6616, allowing plenty of other store options within a short drive away to service customers who would have frequented store #6616.
QGIS Maps for PAPERS
When I am short on time, do not have a current ESRI license activated, or need to make a simple map from small provided data, I often turn to the open-source software QGIS.
I collected data and created this ArcGIS StoryMap of my favorite local hiking spot as part of a project in my UCLA GIS and Geospatial Technology certificate program.