Wildland fuel characterization is foundational to fire behavior, consumption, and smoke modeling with cascading impacts to post-fire vegetation dynamics, carbon, smoke production, and air quality. All fire behavior and effects models require inputs on wildland fuel characteristics, but the detail and resolution at which fuels are represented have been typically generalized into coarse, two-dimensional representations. The 3D Fuels project provides invaluable datasets for the development of wildland fuel characterization and mapping for prescribed fire decision support. Using a hierarchically scaled approach, this Fire Ecology  collection of articles combines airborne and ground-based remote sensing with field sampling to inform realistic, three-dimensional (3D) characterization and mapping of wildland fuels. Articles within this collection detail the object-based classification methods and 3D fuel mapping approaches for next-generation models of fire behavior and smoke.

This topical collection focuses on advancing wildland fuel characterization and mapping by integrating airborne and ground-based remote sensing with field sampling to support next-generation fire behavior and smoke models using realistic 3D representations.