RCC-GIS offers a variety of instructor-led workshops focusing on different geospatial tools and technologies. Summer Workshops
Spatial Statistics for GIS Using RWith increasing amounts of spatial data generated each year, spatial analysis is becoming an increasingly useful tool across public health research, ecological modeling, and econometrics. The spatial statistical analysis looks beyond the map to the data mapped and to inquire about the patterns observed. In this tutorial, participants will explore point pattern analysis, spatial autocorrelation statistics, and geostatistical interpolation to estimate values across continuous and discrete distributions.Objective
- Representing geographical data in R
- Finding non-randomness in point maps using spatstat
- Detection and measurement of spatial autocorrelation in lattice data using spdep
- Creating contour-type maps and semivariance using inverse distance weighting and geostatistical methods
- Level: Intermediate
- Duration: 2 hours
- Prerequisites: Basic knowledge of statistics and some previous exposure to working with R is assumed.
Git repository: https://github.com/rcc-uchicago/SpatialStatistics_R
Tue. April 20, 2021, 2:00-4:00 p.m.
Tue. Feb 9, 2021, 2:00-4:00 p.m
Introduction to Spatial Analysis with RThe size of spatial data sets continues to grow, and advanced tools for their analysis are needed. R has become a widely used open-source tool for spatial data analysis and visualization. This training course introduces SF, an R package for handling geographic data. Participants will be provided with basic knowledge about spatial data manipulation and map visualization using R, as well as the fundamental principles and the specific methods for creating interactive maps using R. Participants will be provided with the necessary information for applying R's powerful suite of geographical tools to their own problems.Objective:
- The structure of spatial objects in R
- Loading and interrogating spatial data with sf
- Data manipulation with spatial data using dplyr
- Spatial operations such as intersections
- Interactive maps with leaflet
Introduction to ArcGIS and Arcpy
Abstract: This workshop is intended for those needing to learn ArcGIS Pro and explore its full potential. Attendees will learn automation of basic geoprocessing, and introductory level GIS programming with Python. This is a hands-on style workshop with exercises designed to teach basic geoprocessing operations used in spatial data science and visualization.
- Introduction to ArcGIS Pro
- GIS analysis using Geoprocessing tools
- Automation using ModelBuilder & Python
- Introduction to Arcpy and ArcGIS Notebook
- Dynamic visualization in 2D and 3D
Duration: 2 hours Tue. Nov 10, 2020, 2:00-4:00 p.m.
Prerequisites: Participants are encouraged to bring a laptop with a Windows operating system as ArcGIS only works on Windows. Mac users can use UChicago Virtual Lab (vLab) to access the software https://academictech.uchicago.edu/vlab/. An RCC account is not required.
Introduction to GDAL/OGR
Abstract: Geospatial Data Abstraction Library (GDAL/OGR) is the most widely used library for raster and vector geospatial data formats. GDAL supports over 50 raster formats and OGR over 20 vector formats. It provides the primary data access engine for many applications such as MapServer, GRASS, and QGIS and has been utilized by major packages such as FME, and ArcGIS. This workshop introduces GDAL through some examples to manipulate raster and vector files for Geographic Information Systems and Remote Sensing analysis.
Objectives: (i) understand what GDAL is, and how it is used (ii) write single line GDAL commands to process raster and vector data (iii) know how to interpret the help dialog for issuing GDAL commands (iv) write GDAL batch scripts to automate many common geoprocessing operations such as merging, cropping and re-projecting, mosaicing, and filtering images.
Duration: 1.5 hours Tue. Nov 24, 2020, 3:00-4:30 p.m.
Prerequisites: Basic knowledge of Geographic Information Systems and previous experience of working with the command line is assumed.
Github repository: https://github.com/rcc-uchicago/gdal_introduction
Introduction to HPC for GeoComputationAbstract: This workshop will introduce attendees to performing Geocomputation analysis using a High-Performance Computing (HPC) cluster. Methods for parallel computing will be presented in the context of geospatial analysis. Participants will be introduced to geospatial tools available on the midway cluster. Most of the hands-on training could be done on any operating system; however, some parts of the hands-on will be demonstrated using the Midway2 cluster.
Objectives: (i) introduction to single-threaded and multithreaded geospatial tools such as GDAL/OGR, arcpy, and simple features (SF), raster, and stars packages in R. (ii) implicit and explicit parallelization (iii) introduction to Slurm (iv) writing simple Bash scripts for raster and vector processing
Duration: 2 hours Tue. Aug 13, 2020, 3:00-5:00 p.m. Registration URL: https://www.eventbrite.com/e/introduction-to-hpc-for-geocomputation-tickets-110021976694Github repository: https://github.com/rcc-uchicago/GeoComputationPrerequisites: Basic knowledge of Geographic Information Systems and previous experience of working with the command line is assumed.
Introduction to ArcGIS
Abstract: This workshop introduces the underlying principles and methods of Geographical Information Systems (GIS) and provides opportunities for the development of practical skills in processing data using an industry-standard GIS software package. The workshop comprises presentations and computer-based practical sessions using ESRI’s ArcGIS software, with example data sets. Topics covered include data management, data visualization; data quality and analysis; georeferencing; data presentation and reporting.
Objectives: Participants will have a knowledge and understanding of (1) What a GIS is; what spatial data is; raster and vector data models (2) The core tasks involved in a GIS analysis e.g. data acquisition and input; data storage and management; data manipulation and analysis; and data presentation and output (3) Importing data from various sources, including scanned paper maps (4) Handling tables including selections and queries (5) Basic geoprocessing tasks e.g. buffering and clipping
Duration: 2.5 hours Tue. Feb 4, 2020, 2:00-4:30 p.m. Kathleen A. Zar Room, The John Crerar Library Shared Drive: introduction
Abstract: This course builds on participants existing knowledge of the underlying principles and methods of Geographical Information Systems (GIS). The workshop comprises presentations and computer-based practical sessions using ESRI’s ArcGIS software, with example data sets. Topics covered include geodatabases, using model builder, GIS customization with Python, extensions, online data, manipulating coordinate systems and spatial analysis/statistics tools. Objectives: Participants will learn (1) Working with geodatabases including importing existing data sets (2) Basic automation using ModelBuilder and Python (3) Introduction to arcpy and ArcGIS API (4) The basics of some ArcGIS extensions (Spatial Analyst and 3D Analyst) are demonstrated (5) Online mapping and sharing data (6) Spatial statistics concepts and tools
Level: IntermediateDuration: 2.5 hours Tue. Feb. 11, 2020, 2:00-4:30 p.m. Kathleen A. Zar Room, The John Crerar Library Shared Drive: intermediate
October 22, 2019
Introduction to ArcGIS Insights
November 13, 2019
Introduction to Satellite Imagery for Social Sciences
November 20, 2019
Introduction to ggplot
June 28, 2019
Introduction to GDAL
Aug 20, 2019
May 21, 2019
Introduction to GIS for historical data
April 30, 2019
Introduction to Raster processing with R
April 18, 2019