Leveraging the next generation of spaceborne Earth observations for fuel monitoring and wildland fire management Journal Article uri icon

Overview

abstract

  • AbstractManaging fuels is a key strategy for mitigating the negative impacts of wildfires on people and the environment. The use of satellite‐based Earth observation data has become an important tool for managers to optimize fuel treatment planning at regional scales. Fortunately, several new sensors have been launched in the last few years, providing novel opportunities to enhance fuel characterization. Herein, we summarize the potential improvements in fuel characterization at large scale (i.e., hundreds to thousands of km2) with high spatial and spectral resolution arising from the use of new spaceborne instruments with near‐global, freely‐available data. We identified sensors at spatial resolutions suitable for fuel treatment planning, featuring: lidar data for characterizing vegetation structure; hyperspectral sensors for retrieving chemical compounds and species composition; and dense time series derived from multispectral and synthetic aperture radar sensors for mapping phenology and moisture dynamics. We also highlight future hyperspectral and radar missions that will deliver valuable and complementary information for a new era of fuel load characterization from space. The data volume that is being generated may still challenge the usability by a diverse group of stakeholders. Seamless cyberinfrastructure and community engagement are paramount to guarantee the use of these cutting‐edge datasets for fuel monitoring and wildland fire management across the world.

publication date

  • August 16, 2024

has restriction

  • gold

Date in CU Experts

  • September 4, 2024 8:23 AM

Full Author List

  • Leite RV; Amaral C; Neigh CSR; Cosenza DN; Klauberg C; Hudak AT; Aragão L; Morton DC; Coffield S; McCabe T

author count

  • 11

Other Profiles

International Standard Serial Number (ISSN)

  • 2056-3485

Electronic International Standard Serial Number (EISSN)

  • 2056-3485