Vegetation classification map and covariates associated with NEON AOP survey, East River, CO 2018

The package includes data layers developed for the "EcoImaging: Advanced Sensing to Investigate Plant and Abiotic Hierarchical Spatial Patterns in Mountainous Watersheds" manuscript by Falco et al. (2024). The manuscript focuses on investigating how environmental gradients—specifically topography and near-surface soil properties—drive the spatial arrangement of dominant plant communities. The geospatial products developed in this package, which helped to understand the above mentioned relationships, are derived from airborne hyperspectral and LiDAR datasets acquired by the The National Ecological Observatory Network (NEON) airborne observation platform (AOP) in conjunction to an extensive ground field campaign occurred in summer 2018.
This work is part of the DOE Watershed Function Science Focus Area (SFA) and features geospatial datasets developed based on observations and ground data collected at East River, Colorado, in collaboration with the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) survey in June 2018.
Classification Map:
- Classification Map (PNG, GeoTIFF): Derived from hyperspectral and LiDAR airborne data using a machine learning approach.
- Class Code Mapper (CSV): Associates pixel values with corresponding vegetation/non-vegetation classes.
- Classification Reference Data (CSV): Reference data used in the machine learning procedure.
LiDAR-Derived Products:
- Topographical Metrics (GeoTIFFs): Elevation, slope, curvature, TWI, TPI, solar insolation, and canopy height model (CHM), smoothed with a 5x5 pixel window.
Vegetation Indices:
- GeoTIFFs of NDVI, NDNI, NDWI: Vegetation indices derived from hyperspectral data.
Urban Masks:
- Urban Mask (GeoTIFF): Applied to the mapping to convert bare soil classes to urban classes.
Software Compatibility:
GeoTIFFs: Can be visualized with GIS software or libraries that support GeoTIFF images.
CSV Files: Can be opened with any software that handles comma-separated values.
The FLMD file provides details and links to the source datasets used to derive the products. The manuscript (in the Method session) provides details on how each product was derived.
This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.
Update on 2026-03-25: Since the original dataset publication date of 02/28/2020, this package has a new classification map derived by an improved methodology. This update also includes additional ground data that improved the representation of some of the communities. See the methods for further details on what has changed between versions.