Lab 8: LiDAR


In this lab students use LiDAR and GPS data to investigate the the amount of woody debris available for habitat in a local river. Students collect GPS data, explorer local LiDAR data and write a Python script to conduct the analysis of the LiDAR data.

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This exercise is used in an introductory GIS course for geology and environmental studies students.

Skills and concepts that students must have mastered

Familiarity with ArcMap and ArcCatalog; Basic familiarity with ArcScene; geoprocessing; familiarity with Python scripting; familiarity with rasters.

How the activity is situated in the course

This is the sixth in a series of stand-alone GIS exercises that introduce students to using Python Scripting for ArcGIS.


Content/concepts goals for this activity

Experience working with LiDAR data, introduction to GPS concepts; experience collecting GIS data;

Higher order thinking skills goals for this activity

Connecting GIS data to the real world; replicating methodology from the literature; writing computer scripts from scratch.

Other skills goals for this activity

Description and Teaching Materials

In 2011, Kasprak et al. published a paper describing a methodology for using LiDAR data to estimate the amount of channel spanning large woody debris available to a certain stream. Channel spanning large woody debris is an important resource for habitat development. The method is a perfect opportunity for connecting the literate, students' GIS abilities, and their local environment.

Lab 8a: In this homework assignment, students download and explore LiDAR data.

Lab 8b: In this lab/homework assignment, students put together their LiDAR, GPS, and aerial data, and trace the banks of a local stream.

Lab 8c: In this lab assignment, students write a script to conduct the large woody debris analysis component of the exercise.
Lab 8a: Data Download (Acrobat (PDF) 84kB Jun6 17)
Lab 8b: Working with LiDAR and GPS Data (Acrobat (PDF) 83kB Jun6 17)
Lab 8c: Large Woody Debris Available for Habitiat (Acrobat (PDF) 155kB Jun6 17)

Teaching Notes and Tips

This lab specifically talks about Plum Creek, a stream local to Oberlin College. To do this exercise elsewhere, the GPS component can be omitted, and/or the stream could be changed to one local to you where similar data is available. Both of these can be done with no detriment to the student experience.

Although we belief the Python exercise to be clear, students should be given an opportunity to do the Python component, Lab 8c in an environment where a teacher or T.A. will be available to over one on one help to assist students with any conceptual issues they are having, particularly regarding variable assignment.


Students are assessed based on a map showing the available large woody debris in the area, as well as a workflow and letter summarizing what they did and learned in the lab.

References and Resources

The exercise replicates part of the methodology of Kasparak et al. (2011), referenced in full below, which should be read by students prior to the exercise.
Kasprak, A., Magilligan, F. J., Nislow, K. H., & Snyder, N. P. (2011). A Lidar‐derived evaluation of watershed‐scale large woody debris sources and recruitment mechanisms: Coastal Maine, USA. River Research and Applications, 28(9), 1462-1476.