daltonkw / ea-05-lidar-uncertainty-workflow-daltonkw

ea-05-lidar-uncertainty-worflow

This repository is to recreate the LiDAR data analysis exploring tree heigh from the canopy heigh model. This analysis will compare these measurements to the same types of measurements made by humans in the field.

The necessary data can be retreived from the EarthPy pacakge.

https://earthpy.readthedocs.io/en/latest/

This package, and other necessary packages can be installed into your local environment by installing the environment.yml file. For example:

• conda env create -f environment.yml

It may be helpful to review the notes from EarthLab on creating and installing Conda Environments.

https://www.earthdatascience.org/courses/intro-to-earth-data-science/python-code-fundamentals/use-python-packages/use-conda-environments-and-install-packages/

Once you have the necessary packages installed you can download the data necessary to run this notebook as:

et.data.get_data('spatial-vector-lidar')

This notebook will:

• For both the SJER and SOAP field sites, create scatterplots (with regression and 1:1 lines) that compare:
  • MAXIMUM canopy height model height in meters, extracted within a 20 meter radius, compared to MAXIMUM tree
• height derived from the insitu field site data.
  • MEAN canopy height model height in meters, extracted within a 20 meter radius, compared to MEAN tree height derived from the insitu field site data.