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Author: Philipp Schneider
Publisher:
ISBN: 9780549842675
Category :
Languages : en
Pages : 494
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Book Description
This dissertation investigates the potential of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and mesoscale numerical weather models for mapping wildfire susceptibility in general and for improving the Fire Potential Index (FPI) in southern California in particular.
Author: Philipp Schneider
Publisher:
ISBN: 9780549842675
Category :
Languages : en
Pages : 494
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Book Description
This dissertation investigates the potential of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and mesoscale numerical weather models for mapping wildfire susceptibility in general and for improving the Fire Potential Index (FPI) in southern California in particular.
Author: Gina M. Gerlich
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Drought and wildfire occurrences are predicted to compound due to global climate change, especially in Mediterranean climates. Therefore, researching potential wildfire determinants is imperative in preparing for and managing future wildfires. The primary goal of this research was to determine if specific environmental, spatial, and human-based variables can explain large wildfire occurrences in Southern California during four designated wildfire regimes, which are drought and post-drought years within the two fire seasons (i.e., dry and Santa Ana (SA) wind fire seasons), between 2012 and 2019 utilizing binary logistic regression models. The secondary goal was to map the predictive patterns of large wildfire occurrences in Southern California. This research used remotely sensed land surface temperature (LST), normalized difference vegetation index (NDVI), and evapotranspiration (ET) datasets. This research also used other raster datasets, such as precipitation, wind, aspect, slope, and digital elevation model (DEM). Various vector derived raster datasets were also used, such as distance to roads, powerlines, cities, and campgrounds, ecoregions, and the wildland-urban interface (WUI). Wildfire occurrences are influenced by anthropogenic, environmental, and spatial factors; however, once ignition occurs and wildfires begin to spread, the environmental factors become more significant in fueling large wildfires. The results indicated that lower NDVI values were the strongest predictor when wildfires were smaller in terms of area burned and when less wildfires occurred. Higher wind speeds were the strongest predictor when wildfires were larger. However, higher LST values were the strongest predictor when wind was not a significant contributor to the model. These conclusions determine that large wildfires are mostly explained by wind, and when wind is not a significant contributor, then LST takes on that role, as these two variables have the ability to dry vegetation and to spread wildfires. This research further establishes the potential for early detections of large wildfires based on wildfire prediction patterns, provides useful information for resource issuance and wildfire management, and enhances general knowledge of the predicted extreme wildfire events in Southern California.
Author:
Publisher:
ISBN:
Category : Biotic communities
Languages : en
Pages : 46
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Author:
Publisher:
ISBN:
Category : California
Languages : en
Pages : 32
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Author: National Aeronautics and Space Administration (NASA)
Publisher: Createspace Independent Publishing Platform
ISBN: 9781721278039
Category :
Languages : en
Pages : 32
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Book Description
Large urban wildfires throughout southern California have caused billions of dollars of damage and significant loss of life over the last few decades. Rapid urban growth along the wildland interface, high fuel loads and a potential increase in the frequency of large fires due to climatic change suggest that the problem will worsen in the future. Improved fire spread prediction and reduced uncertainty in assessing fire hazard would be significant, both economically and socially. Current problems in the modeling of fire spread include the role of plant community differences, spatial heterogeneity in fuels and spatio-temporal changes in fuels. In this research, we evaluated the potential of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data for providing improved maps of wildfire fuel properties. Analysis concentrated in two areas of Southern California, the Santa Monica Mountains and Santa Barbara Front Range. Wildfire fuel information can be divided into four basic categories: fuel type, fuel load (live green and woody biomass), fuel moisture and fuel condition (live vs senesced fuels). To map fuel type, AVIRIS data were used to map vegetation species using Multiple Endmember Spectral Mixture Analysis (MESMA) and Binary Decision Trees. Green live biomass and canopy moisture were mapped using AVIRIS through analysis of the 980 nm liquid water absorption feature and compared to alternate measures of moisture and field measurements. Woody biomass was mapped using L and P band cross polarimetric data acquired in 1998 and 1999. Fuel condition was mapped using spectral mixture analysis to map green vegetation (green leaves), nonphotosynthetic vegetation (NPV; stems, wood and litter), shade and soil. Summaries describing the potential of hyperspectral and SAR data for fuel mapping are provided by Roberts et al. and Dennison et al. To utilize remotely sensed data to assess fire hazard, fuel-type maps were translated in
Author: Richard D. Stratton
Publisher:
ISBN:
Category : Wildfires
Languages : en
Pages : 18
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Author:
Publisher:
ISBN:
Category :
Languages : de
Pages : 0
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Author: Benjamin P. Bryant
Publisher:
ISBN:
Category : Climatic changes
Languages : en
Pages : 64
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Author: Emilio Chuvieco
Publisher: World Scientific
ISBN: 981448525X
Category : Technology & Engineering
Languages : en
Pages : 280
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Book Description
The book presents a wide range of techniques for extracting information from satellite remote sensing images in forest fire danger assessment. It covers the main concepts involved in fire danger rating, and analyses the inputs derived from remotely sensed data for mapping fire danger at both the local and global scale. The questions addressed concern the estimation of fuel moisture content, the description of fuel structural properties, the estimation of meteorological danger indices, the analysis of human factors associated with fire ignition, and the integration of different risk factors in a geographic information system for fire danger management.
Author: Armin Ratz
Publisher:
ISBN:
Category :
Languages : en
Pages : 135
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Book Description
