Leveraging the next generation of spaceborne Earth observations for fuel monitoring and wildland fire management

Author:

Leite Rodrigo V.123ORCID,Amaral Cibele345,Neigh Christopher S. R.2,Cosenza Diogo N.3ORCID,Klauberg Carine6,Hudak Andrew T.7,Aragão Luiz89,Morton Douglas C.2,Coffield Shane210,McCabe Tempest210,Silva Carlos A.6

Affiliation:

1. Goddard Space Flight Center Greenbelt Maryland 20771 USA

2. Biospheric Sciences Laboratory Code 618, NASA Goddard Space Flight Center Greenbelt Maryland 20771 USA

3. Department of Forest Engineering Federal University of Viçosa Viçosa Minas Gerais 36570900 Brazil

4. Earth Lab Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder Boulder Colorado 80303 USA

5. Environmental Data Science Innovation & Inclusion Lab (ESIIL) University of Colorado Boulder Boulder Colorado 80303 USA

6. Forest Biometrics, Artificial Intelligence and Remote Sensing Laboratory (Silva lab) School of Forest, Fisheries, and Geomatics Sciences, University of Florida Gainesville Florida 32611 USA

7. Forestry Sciences Laboratory, Rocky Mountain Research Station USDA Forest Service 1221 South Main Street Moscow Idaho 83843 USA

8. Earth Observation and Geoinformatics Division National Institute for Space Research (INPE) São José dos Campos Brazil

9. Faculty of Environment, Science and Economy University of Exeter Exeter UK

10. Earth System Science Interdisciplinary Center University of Maryland College Park Maryland 20740 USA

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.

Funder

U.S. Forest Service

English Institute of Sport

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Wiley

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