Spatial Data Models

This module is all about spatial data! What makes spatial data special and how do we represent it in a GIS? Spatial Data has some unique properties which mean we need to implement specific strategies to work with it. There are two key formats we work with in GIS for spatial data: Raster and Vector. Both models can be used to represent most spatial phenomena; but they are not equally suited for all applications.

Learning Outcomes

  • Learn how to apply different analysis methods to both Raster and Vector data
  • Use spatial overlay methods to answer a research question
  • Introduction to Model Builder
  • GIS Applications in Hazards planning

Spatial Analysis Workflows

Now that we’ve covered the different types of geospatial data, lets start thinking about how it all fits together.

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Raster Analysis Methods

Raster data is less complex, but there are many different types of analysis we can conduct with it!

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Vector Analysis Methods

Vector data structures are quite complex, so there are a number of different ways to see how features relate to each other.

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Working Examples

Raster Methods

This Raster Methods Examples Project contains models with examples of methods that can be applied to raster data, using some data from the NRCAN DEM covering Port Alberni and a LANDSAT 8 image of the Mackenzie River Delta. You can follow along in lecture or download the project and play around with the data on your own.

The methods covered include:

  • Euclidean Distance
  • Reclassification
  • Slope
  • Aspect
  • Raster Calculator
  • Weighted Overlay
  • Specifying Visible Bands & Creating False Color Images
  • Clipping Rasters
  • Creating Mosaics
  • Calculating NDVI & Other Raster Tools

Vector Methods

This Vector Methods Example Project contains models with examples of methods that can be applied to vector data, using some data from Burns Bog. You can follow along in lecture or download the project and play around with the data on your own.

The methods covered include:

  • Merging vector layers
  • Buffering
  • Clipping
  • Erasing
  • Intersecting
  • Unioning
  • Dissolving
  • Converting a vector to raster