Geospatial Data, Maps & Spatial Analysis

Elena Stacy

Consulting Drop-In Hours: Wed 10am-12pm

Consulting Areas: R, Stata, LaTeX, Data Manipulation and Cleaning, Data Sources, Data Visualization, Geospatial Data, Maps & Spatial Analysis, R Programming, Surveys, Sampling & Interviews, Text Analysis, Web Scraping, Regression Analysis, Means Tests, Excel, Git or Github, QGIS, RStudio, Stata

Quick-tip: the fastest way to speak to a consultant is to first ...

R Geospatial Fundamentals: Vector Data, Parts 1-2

November 7, 2023, 9:00am
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research. This workshop focuses on fundamental operations for reading, writing, manipulating and mapping vector data, which encodes location as points, lines and polygons.

From paper to vector: converting maps into GIS shapefiles

April 11, 2023
Madeleine Parker
by Madeleine Parker. GIS is incredibly powerful: you can transform, overlay, and analyze data with a few clicks. But sometimes the challenge is getting your data into a form to be able to use with GIS. Have you ever found a PDF or even paper map of what you needed? Or googled your topic with “shapefile” after it to no avail? The process of transforming a PDF, paper, or even hand-drawn map with boundaries into a shapefile for analysis is straightforward but involves a few steps. I walk through the stages of digitization, georeferencing, and drawing, from an image to a vector shapefile ready to be used for visualization and spatial analysis.

Mapping Time-Series Satellite Images with Google Earth Engine API

July 17, 2023
Meiqing Li
by Meiqing Li. Remote sensing imagery has the potential to reveal land use patterns and human activities at a planetary scale. For example, nighttime light intensity extracted from can shed light on spatial patterns of human activities and settlements, especially in places where traditional data are scarce. This blog post introduces Google Earth Engine (GEE) as a general purpose tool to extract time-series remote sensing data from GEE data catalog. I walk through using GEE to obtain data, filter by time and geographic region, and visualize it on static and interactive maps.

The Geography of Cannabis: Does California’s dual licensing program (de)criminalize cannabis and drive unnecessary anthropogenic activity in remote rural environments?

August 29, 2023
Chevon Holmes
by Chevon Holmes. When California voters (de)criminalized cannabis production, the state’s dual licensure requirement forced local jurisdictions to create permitting programs or uphold prohibition. Many Counties developed ersatz zoning ordinances to regulate cannabis activities and hired staff to administer local permits. As an inspector, administrator, and project planner for Mendocino County from 2017-2021, I visited hundreds of cultivation sites and production facilities where I learned first-hand how two legal pathways impacted the ways in which operators could transition their businesses. This post details a dataset created to track, aggregate, and analyze the relationship between cannabis infrastructure and licensing.

Python Geospatial Data and Mapping: Parts 1-2

October 3, 2023, 9:00am
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The Python programming language is a great platform for exploring these data and integrating them into your research.

Suraj Nair

Data Science Fellow
School of Information

I am a PhD Student at the School of Information. My research interests lie at the intersection of development economics and machine learning, with a focus on the use of large scale digital data and new computational tools to study pressing issues in global development.

Alex Ramiller

Data Science Fellow
City and Regional Planning

I am a PhD Candidate in City and Regional Planning. My research focuses on the use of large administrative datasets to study residential mobility, neighborhood change, and housing access. I received a Master in Geography from the University of Washington and a Bachelor's in Economics and Geography from Macalester College. I have also consulted on analytical projects for several organizations including the San Francisco Federal Reserve Bank, PolicyLink, and the City of Seattle.

Melike Sümertaş

Data Science Fellow
History

I hold a PhD in History from Boğaziçi University, Istanbul and B.A and M.A degrees from Middle East Technical University in Ankara, Department of Architecture, and Program in Architectural History. My research focuses on the urban/architectural/visual culture of the late Ottoman Empire and its capital city Istanbul, with a particular interest in the Greek-Orthodox community. My current project in the History Department of UC Berkeley under the umbrella of the Istanpolis collaboration led by Prof. Christine Philliou, focuses on utilizing digital humanities tools for urban/...

QGIS Geospatial Fundamentals: Parts 1-2

February 22, 2023, 1:00pm
This workshop will introduce methods for working with geospatial data in QGIS, a popular open-source desktop GIS program that runs on both PCs and Macs as well as linux computers. Participants will learn how to load, query and visualize point, line and polygon data. We will also introduce basic methods for processing spatial data, which are the building blocks of spatial analysis workflows. Coordinate reference systems and map projections will also be introduced.