This Data Skills Webinar Series workshop will demonstrate working with NEON Airborne Observation Platform (AOP) discrete-return lidar point cloud data to explore change detection in vegetation structure following a wildfire disturbance.
The Creek Fire was a large wildfire which started in September, 2020, in the Sierra National Forest, California, and became one of the largest fires of the 2020 California wildfire season. This fire had burned into NEON's Soaproot Saddle site (SOAP) by mid-September, resulting a high intensity burn scar over a large portion of the site.
The NEON Airborne Observation Platform (AOP) conducted aerial surveys for the SOAP site in 2019 and 2021, a year before and after the Creek Fire. The goal of this lesson is to demonstrate the effects of fire on vegetation structure by comparing the lidar-derived relative height percentiles before (2019) and after (2021) the fire. In addition to the discrete return data, this webinar demonstrates using a Digital Terrain Model (DTM) to determine the relative height of the discrete return with respect to ground.
Instructor: Shashi Konduri, Environmental Scientist
Programming language: Python
Prerequisites: Previous experience working in Python is recommended, but not required.
Requirements for participation: Install Python (3.10 or 3.11) and Jupyter Notebooks, or can use Google Colab (requires a gmail account). If working locally, install the following packages (all can be installed with pip install).
This workshop is part of the ongoing data skills and science seminar webinar series. Learn more about our Data Skills Webinars and Science Seminars HERE.
TBD