LB 36-302 - Open Source Tools for Working with NEON's Airborne Remote Sensing Data

Each year, the National Ecological Observatory Network (NEON) collects high-resolution hyperspectral imagery, discrete and waveform lidar, and RGB camera data through its Airborne Observation Platform (AOP). The coincident collection of AOP remote sensing data with field and instrumented data products provides a rich resource for carrying out ecological research at multiple scales. We present open-source, reproducible code resources for working with NEON's remote sensing data, including tutorials in R and Python, which can be run in the CyVerse Discovery environment with minimal overhead and software dependencies. We also provide an update on NEON's progress on adding AOP datasets to Google Earth Engine (GEE), a cloud-based platform for conducting geospatial analysis on large scale datasets. The open-source resources presented can be used as a starting point for scientists at any level to start working with AOP data, and to build upon in conducting ecological research.