Creating a Digital Elevation Model from GPS Data Using Interpolation Methods

A colorful pattern representing elevation.

Table of Contents

  1. Creating a Digital Elevation Model from GPS Data Using Interpolation Methods
  2. Setting up Your Workspace
  3. Preparing the Data
  4. Skill Drill: Downloading data using the Minnesota Department of Natural Resources GPS Application (DNRGPS)
  5. Creating a Surface Model Using the IDW Interpolation Method and the Geostatistical Wizard
  6. Creating a Surface Model Using the Spline Interpolation Method
  7. Creating a Surface Model Using the Kriging Interpolation Method
  8. Creating a Digital Elevation Model from a Geostatistical Layer
  9. Skill Drill: Creating a Map of the Results

A surface model is an approximation of a surface based on a set of sample points. It represents a phenomenon that can be measured continuously across a surface. Elevation, slope, temperature, precipitation, population, crime, and disease are all examples of surface models that you may be familiar with or have seen before. There are two primary surface modeling techniques used to create surfaces, density, and interpolation.

Density is a function that distributes the quantity or magnitude of a phenomenon over a unit of area. It is derived from the quantity measured at each location and the spatial relationship of the locations of the measured quantities. Density does not try to predict specific values at a location but instead communicates geographic trends. For example, a map of cancer density in a region does not predict that someone developed cancer at a specific location. Instead, it communicates the patterns and perhaps the likelihood of cancer over a region.

Like density, interpolation allows you to create a surface from point locations. However, it does try to predict values at specific locations, in between known values. For example, a temperature surface may be interpolated from a series of weather stations across the state of California. A surface model using interpolation attempts to predict the specific temperature values at all locations across the entire surface.

Estimated time to complete this tutorial: 4 hours

Learning Outcomes

  • Review data collection methods using a GPS receiver
  • Review downloading waypoints
  • Review converting GPX files to Shapefiles
  • Create a surface model using the Inverse Distance Weighted (IDW) method
  • Create a surface model using the Spline method
  • Create a surface model using the Kriging method
  • Optimize inputs for interpolation methods
  • Compare interpolation results


In this scenario, you have been charged with the task of collecting elevation data to create a digital elevation model. You will generate points for the surface model by collecting elevation data using a GPS receiver. You will then compare the accuracy of the surface model using various interpolation methods.

Conduct this analysis using the Universal Transverse Mercator (UTM) system along with the North American Datum of 1983 (NAD83). Humboldt County lies in Zone 10 of the UTM system. All of your data must be in this spatial reference system at the start of your analysis. Create working copies of your data in this spatial reference system using the Project tool in ArcMap as needed.

If you are a non-local student, you may use your local UTM zone instead of zone 10.