CANCELED: R Geospatial Fundamentals: Vector Data, Parts 1-2

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Location: Remote via Zoom. Link will be sent on the morning of the event.

Recordings: This D-Lab workshop will be recorded and made available to UC Berkeley participants for a limited time. Your registration for the event indicates your consent to having any images, comments and chat messages included as part of the video recording materials that are made available.

Date & Time: This workshop is a 2-part series running from 10am-1pm each day:

• Part 1: Monday, November 14
• Part 2: Wednesday, November 16

Start Time: D-Lab workshops start 10 minutes after the scheduled start time (“Berkeley Time”). We will admit all participants from the waiting room at that time.

Description

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.

• Part I: Core concepts, vector data, and plotting
  • Basic geospatial concepts
  • Basic vector data
  • Geospatial data structures (the sf package)
  • Basic plotting (base::plot and the ggplot3 package)
  • Managing coordinate reference systems (CRS)
  • Advanced plotting (the tmap package)
  • Map overlays
• Part II: Spatial analysis
  • Spatial measurement queries
  • Spatial relationship queries
  • Buffer analysis
  • Spatial and non-spatial joins
  • Aggregation
  • Continued mapping practice

Prerequisites: D-Lab’s R Fundamentals or equivalent knowledge; previous experience with base R is assumed and basic familiarity with the tidyverse.

Workshop Materials: https://github.com/dlab-berkeley/R-Geospatial-Fundamentals

Software Requirements: Requirements for R and RStudio

Feedback: After completing the workshop, please provide us feedback using this form

Questions? Email: dlab-frontdesk@berkeley.edu