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GEOG 2232

Introduction to Geomatics and GIS

0.5 credits · Undergraduate

Fall 2024

Topics

  • Date Lab Reading
  • (week
  • Day) & web mapping applications
  • Introduction to GIS and geospatial data
  • sources
  • Create a data management
  • plan for the course
  • Intro to GIS Theory, Introduction to GIS Lab 2: GIS file &
  • terms and concepts data models management, introduction
  • Introduction to Raster data model, Lab 3: Working with raster
  • Remote Sensing – raster data data
  • aerial photographs, catalogues
  • satellite images
  • Introduction to Spatial reference Lab 4: Datums, map
  • Cartography, basic systems projections and coordinate
  • map elements, systems
  • create a simple map
  • project
  • typography/ Vector quantitative data display
  • and raster data methods and map-making
  • display – qualitative
  • and quantitative
  • Georeferencing GIS Data capture and Lab 6: Georeference an &
  • data, join and relates create a map
  • select by attributes, GIS/GPS data – onscreen

Readings

Fall 2024

Topics

  • Introduction to Read
  • mapping
  • fundamentals
  • Essential map Lab 1 Part 1: Sketch
  • elements, map mapping

Readings

  • Mastering ArcGIS Pro ISE, 2nd Ed. 2022. Maribeth Price. McGraw-Hill Canada.
  • Make sure to purchase the textbook by the second week of class.
  • Purchase the 2nd ISE edition from MCGraw Hill Canada (Print or digital edition) with access to Canadian Companion Connect, which has essential exercises leveraging Canadian datasets. 9781265127718-can-group
  • Map critique in lab () due by Thursday Nov 21 at 5PM.
  • Source-linked resource
Winter 2024

Topics

  • Lecture Topic Lab
  • mapping
  • fundamentals
  • Map projections Lab 1 Part 1: Sketch mapping
  • Measuring Earth: Lab 1 Part 2: Sketch mapping
  • map scale, geodesy
  • coordinate systems
  • Spatial data models Lab 2: Intro to ArcGIS Pro and Georeferencing
  • vectors and rasters
  • Georeferencing
  • Symbolization lab
  • material)
  • Map design and Lab 3: Data classification
  • planning
  • The power of maps Lab 3: Data classification
  • Spatial analysis
  • Remote sensing Lab 4: Spatial analysis
  • All lab sections
  • (including weekend days)

Readings

Sources