Research Database
Displaying 1 - 6 of 6
Projecting live fuel moisture content via deep learning
Year: 2023
Background: Live fuel moisture content (LFMC) is a key environmental indicator used to monitor for high wildfire risk conditions. Many statistical models have been proposed to predict LFMC from remotely sensed data; however, almost all these estimate current LFMC (nowcasting models). Accurate modelling of LFMC in advance (projection models) would provide wildfire managers with more timely information for assessing and preparing for wildfire risk. Aims: The aim of this study was to investigate the potential for deep learning models to predict LFMC across the continental United States 3 months…
Publication Type: Journal Article
Consistent, high-accuracy mapping of daily and sub-daily wildfire growth with satellite observations
Year: 2023
Background: Fire research and management applications, such as fire behaviour analysis and emissions modelling, require consistent, highly resolved spatiotemporal information on wildfire growth progression. Aims: We developed a new fire mapping method that uses quality-assured sub-daily active fire/thermal anomaly satellite retrievals (2003–2020 MODIS and 2012–2020 VIIRS data) to develop a high-resolution wildfire growth dataset, including growth areas, perimeters, and cross-referenced fire information from agency reports. Methods: Satellite fire detections were buffered using a historical…
Publication Type: Journal Article
Wildfire controls on land surface properties in mixed conifer and ponderosa pine forests of Sierra Nevada and Klamath mountains, Western US
Year: 2022
This study examines the post-fire biogeophysical and biochemical dynamics after several high-severity wildfires that occurred in mixed conifer and ponderosa pine forest types in the Sierra Nevada and Klamath Mountains regions between 1986 and 2017. We found a consistent pattern of reduced leaf area index (LAI) in the first year after fire, followed by gradual recovery over the subsequent 25 years. Recovery rate varied between forest types. For example, average summer LAI for 16-25 years post-fire was 88% of the pre-fire average for mixed conifers in the Sierra Nevada, 64% for ponderosa pine…
Publication Type: Journal Article
Mapping day-of-burning with coarse-resolution satellite fire-detection data
Year: 2014
Evaluating the influence of observed daily weather on observed fire-related effects (e.g. smoke production, carbon emissions and burn severity) often involves knowing exactly what day any given area has burned. As such, several studies have used fire progression maps – in which the perimeter of an actively burning fire is mapped at a fairly high temporal resolution – or MODIS satellite data to determine the day-of-burning, thereby allowing an evaluation of the influence of daily weather. However, fire progression maps have many caveats, the most substantial being that they are rarely mapped…
Publication Type: Journal Article
Mapping the daily progression of large wildland fires using MODIS active fire data
Year: 2014
High temporal resolution information on burnt area is needed to improve fire behaviour and emissions models. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) thermal anomaly and active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the timing of burnt area for 16 large wildland fires. For each fire, parameters for the kriging model were defined using variogram analysis. The optimal number of observations used to estimate a pixel’s time of burning varied between four and six among the fires studied. The median standard error from…
Publication Type: Journal Article
Ecosystem Greenspots: Identifying Potential Drought, Fire, and Climate-Change Micro-Refuges
Year: 2012
In response to climate change and other threatening processes there is renewed interest in the role of refugia and refuges. In bioregions that experience drought and fire, micro-refuges can play a vital role in ensuring the persistence of species. We develop and apply an approach to identifying potential micro-refuges based on a time series of remotely sensed vegetation greenness (fraction of photosynthetically active radiation intercepted by the sunlit canopy; fPAR). The primary data for this analysis were NASA MODIS 16-day L3 Global 250 m (MOD13Q1) satellite imagery. This method draws upon…
Publication Type: Journal Article