Spatial Data 101: Onboarding with The Stanford Geospatial Center

Get the basics of spatial data and geospatial tools with Stanford Geospatial Center, live and in person!

Spatial Data 101: Onboarding to Stanford’s Spatial Data Resources

Interested in working with spatial data at Stanford but not sure where to start? This introductory workshop provides a quick foundation in spatial data science while introducing the spatial data, software, imagery, and analysis resources available to the Stanford community through the Stanford Geospatial Center (SGC).

We’ll begin with the fundamentals: What makes data spatial? Participants will learn about the two primary models for representing geographic information—vector and raster data—and how points, lines, polygons, grids, imagery, and their associated attributes are used to represent and analyze the world around us.

From there, we’ll explore some of the possibilities of spatial analysis. How can we determine what is near what, what falls within a particular area, or where different conditions overlap? How can we identify geographic patterns, measure change through time, turn place names and addresses into geographic coordinates, combine multiple sources of spatial information, or use satellite and historical imagery to observe how places change?

With that foundation, we’ll introduce major spatial data resources available to Stanford researchers, along with open tools and services that can support spatial research. We’ll show you how to access them, what each provides, and when you might use one rather than another:

• ArcGIS Online — Stanford’s web-based GIS environment for mapping, spatial analysis, data visualization, sharing, and publishing.
• SimplyAnalytics — A web-based mapping and analysis platform providing demographic, socioeconomic, consumer, business, and market data.
• EarthWorks — Stanford Libraries’ discovery platform for finding and accessing geospatial datasets, maps, and other spatial resources from Stanford’s collections and beyond.
• Stanford Locator (locator.stanford.edu) — A free, high-performance geocoding service for Stanford research, built on Esri ArcGIS Server. Locator enables researchers to convert addresses and place information into geographic coordinates for mapping and spatial analysis, including workflows involving large numbers of records.
• Allmaps (allmaps.org) — A free and open-source set of tools for georeferencing digitized maps and using them in modern web mapping environments. Allmaps works with IIIF resources, making it possible to bring digitized historical maps from libraries, archives, and other collections into contemporary spatial research and visualization workflows.
• Planet.com — Access to high-resolution satellite imagery and Earth observation data for research and teaching.
• Google Earth Engine — A cloud-based platform for analyzing large collections of satellite imagery and other geospatial datasets at scales ranging from individual study areas to the entire planet.

Along the way, we’ll look at how these resources complement one another and how to choose appropriate data, tools, and analytical approaches for different kinds of spatial questions.

By the end of the workshop, participants should have a basic understanding of how spatial data represents the world, what kinds of questions spatial analysis can answer, where to find spatial data at Stanford, and which Stanford-supported and open tools and services can help them begin working with it.

No previous GIS, remote sensing, or spatial data experience is required. This workshop is designed as an entry point for anyone interested in incorporating geographic information, mapping, satellite imagery, historical maps, or spatial analysis into their research, teaching, or projects.

Participants are encouraged to bring a laptop so they can access resources and follow along.

Who should attend: Stanford students, faculty, researchers, and staff interested in learning how spatial data and analysis can support their research, teaching, or projects.

Presented by: Stanford Geospatial Center, Stanford Libraries