remote sensing

Fire activities introduce hazardous impacts on the environment and public health by emitting various chemical species into the atmosphere. Most operational air quality forecast (AQF) models estimate smoke emissions based on the latest available satellite fire products, which may not represent real-time fire behaviors without considering fire spread.

Background: Daily fire progression information is crucial for public health studies that examine the relationship between population-level smoke exposures and subsequent health events. Issues with remote sensing used in fire emissions inventories (FEI) lead to the possibility of missed exposures that impact the results of acute health effects studies.

Extreme fire spread events rapidly burn large areas with disproportionate impacts on people and ecosystems. Such events are associated with warmer and drier fire seasons and are expected to increase in the future.

Background: Daily fire progression information is crucial for public health studies that examine the relationship between population-level smoke exposures and subsequent health events. Issues with remote sensing used in fire emissions inventories (FEI) lead to the possibility of missed exposures that impact the results of acute health effects studies.

Background: Suppression effectiveness is often evaluated by measuring the extent to which it slows fire spread and reduces fireline intensity. Although studies have used infrared (IR) imaging methods to explore suppression effectiveness, most do not measure or assess the influence of water application on energy release.

In recent decades, bark beetle outbreaks have caused mass tree mortality in western US forests, which has led to altered wildfire characteristics, hydrological processes, and forest carbon dynamics.

In the age of big data and open science, what processes are needed to follow open science protocols while upholding Indigenous Peoples’ rights? The Earth Data Relations Working Group (EDRWG), convened to address this question and envision a research landscape that acknowledges the legacy of extractive practices and embraces new norms across Earth science institutions and open science research.

Drivers of forest wildfire severity include fuels, topography and weather. However, because only fuels can be actively managed, quantifying their effects on severity has become an urgent research priority. Here we employed GEDI spaceborne lidar to consistently assess how pre-fire forest fuel structure affected wildfire severity across 42 California wildfires between 2019–2021.

Increasing wildfire severity is of growing concern in the western United States, with consequences for the production, composition, and mobilization of dissolved organic matter (DOM) from terrestrial to aquatic systems.

Large-scale mapping of fuel load and fuel vertical distribution is essential for assessing fire danger, setting strategic goals and actions, and determining long-term resource needs. The Airborne LiDAR system can fulfil such goal by accurately capturing the three-dimensional arrangement of vegetation at regional and national scales.