Developing a Fire-Risk Web Map and Monitoring Methodology for Southern California Chaparral using Multispectral Drone Imagery
Dates
Publication Date
2022-09-08
Citation
Kyle Lunneberg, Walter Oechel, and Nicole DeCrappeo, 2022-09-08, Developing a Fire-Risk Web Map and Monitoring Methodology for Southern California Chaparral using Multispectral Drone Imagery: .
Summary
Fire in Southern California chaparral communities is a historically common occurrence [1]. Hot, dry summers interact with strong “Santa Ana” winds and large human interfaces to create extreme risks of devastating wildfires [6], [11]. These plant communities also feedback into wildfire probabilities, producing drought-resistance mechanisms – such as volatile oils and woody stems - that can increase the spread and intensity of wildfire [1], [13]. Understanding the main drivers of wildfire is a priority in the wake of recent drought conditions, which are likely to worsen. California experienced its most extreme drought of the last millennia during the 2012-2016 period [5]. These extreme conditions interact with an increasing human-habitat [...]
Summary
Fire in Southern California chaparral communities is a historically common occurrence [1].
Hot, dry summers interact with strong “Santa Ana” winds and large human interfaces to create
extreme risks of devastating wildfires [6], [11]. These plant communities also feedback into wildfire
probabilities, producing drought-resistance mechanisms – such as volatile oils and woody stems -
that can increase the spread and intensity of wildfire [1], [13].
Understanding the main drivers of wildfire is a priority in the wake of recent drought
conditions, which are likely to worsen. California experienced its most extreme drought of the last
millennia during the 2012-2016 period [5]. These extreme conditions interact with an increasing
human-habitat interface, exacerbating environmental conditions favorable for fire and the threat of
accidental ignition [11]. While environmental conditions are significant predictors of fire, community
composition, and the spatial distribution of species have substantial effects [7].
Because of limitations in manually sampling large areas, recent studies have just begun to
address the role of individual vegetation communities. Current remotely-sensed measurements of
community composition have shown that various chaparral communities promote different intensities
and frequencies of fires [10]. This may be due to the differing fuel-load water content between species
in chaparral systems [8], [9]. With remotely sensed parameters, studies begin to address the spatial
probabilities that puzzled earlier environmental modeling.
Multispectral measurements are a connector between the effects of inter-annual variability
and community composition. Aerial and satellite multispectral measurements of chaparral can detect
canopy water content, community composition, fuel load accumulation, and a suite of environmental
conditions [3],[12]. While multispectral measurements can characterize large areas spatially and
temporally, they often lack the resolutions needed for species- and subcommunity-level study. Our
preliminary data using high-resolution drone imagery (Figure 2), has shown its ability to produce
high-quality multispectral datasets that are comparable to satellite and aerial methods.
