Download or read book Modeling Spatial Patterns of Wildfire Susceptibility in Southern California written by Philipp Schneider and published by . This book was released on 2008 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Comparative Spatiotemporal Statistical Analysis of Southern California Wildfire Regimes written by Gina M. Gerlich and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Guidance on spatial wildland fire analysis written by Richard D. Stratton and published by . This book was released on 2006 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Climate Change Growth and California Wildfire written by and published by . This book was released on 2009 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modeling and Prediction of Wildfire Hazard in Southern California Integration of Models with Imaging Spectrometry written by National Aeronautics and Space Administration (NASA) and published by Createspace Independent Publishing Platform. This book was released on 2018-06-19 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Scenarios to Evaluate Long term Wildfire Risk in California New Methods for Considering Links Between Changing Demography Land Use and Climate written by Benjamin P. Bryant and published by . This book was released on 2012 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Potential Effects of Climate Change on Residential Wildfire Risk in California written by and published by . This book was released on 2009 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A generic forest fire model written by and published by . This book was released on 1996 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Climate Change and Wildfire in and Around California written by and published by . This book was released on 2006 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using statistical models, wildfire risks are described as a function of climatic variables such as temperature and precipitation, and of hydrologic variables simulated using temperature and precipitation. Property damages due to wildfires are also modeled using the 2000 U.S. Census to describe the location and density of residential structures. This analysis indicates that the largest changes in property damages under the climate change scenarios occurs in wildland/urban interfaces proximate to major metropolitan areas in coastal southern California, the Bay Area, and in the Sierra foothills northeast of Sacramento.
Download or read book IDENTIFYING POTENTIAL PATTERNS OF WILDFIRES IN CALIFORNIA IN RELATION TO SOIL MOISTURE USING REMOTE SENSING written by Adam J. Link and published by . This book was released on 2020 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this study is determining a potential correlation between soil moisture and burn severity as well as examining potential correlations between slope, elevation, wind speed, wind direction and Normalized Difference Vegetation Index (NDVI) value and burn severity within the Mendocino Complex Fire, California, which occurred in 2018. A time-series of the difference Normalized Burn Ratio (dNBR), the difference between pre- and intra-fire NBR values, was calculated via Sentinel-2, soil moisture was mapped using SMAP, and the Digital Elevation Model (DEM) from ASTER was used to derive elevation and slope values. The imagery was obtained from USGS and USDA websites. Images were processed and reprojected to the same spatial resolution (60 m) and projection (UTM Zone 10N, WGS-87). dNBR imagery was subdivided in newly burned areas for each consecutive day for ten days from 29 July 2018 to 31 August 2018. The findings suggested that there was no strong correlation trend consistently found over the proposed period of time between dNBR values and soil moisture content (R ≈ -0.20 to 0.39), slope (R ≈ -0.35 to 0.46), elevation (R ≈ -0.24 to 0.56), wind speed (R ≈ -0.15 to 0.36), and wind direction (R ≈ -0.42 to 0.24). However, a positive correlation between NDVI values and dNBR values was found to be strong and consistent (R ≈ -0.48 to 0.57). This implies that burn severity increased more significantly and frequently with NDVI, a surrogate for vegetation biomass and leaf area index. It can be surmised that soil moisture must reach some higher values before having a possible impact upon burn severity. Considering that the summer of 2018 was one of the warmest and driest summers in the study area's recent history, soil moisture content was relatively low while, simultaneously, vegetation was dry and more prone to burning.
Download or read book Modeling Naturally Occurring Wildfires Across the US Using Niche Modeling written by Brandon Polk and published by . This book was released on 2017 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wildfires can cause significant damage to an area by destroying forested and agricultural areas, homes, businesses, and leading to the potential loss of life. Climate change may further increase the frequency of wildfires. Thus, developing a quick, simple, and accurate method for identifying key drivers that cause wildfires and modeling and predicting their occurrence becomes very important and urgent. Various modeling methods have been developed and applied for this purpose. The objective of this study was to identify key drivers and search for an appropriate method for modeling and predicting natural wildfire occurrence for the United States. In this thesis, various vegetation, topographic and climate variables were examined and key drivers were identified based on their spatial distributions and using their correlations with natural wildfire occurrence. Five models including General Linearized Models (GLM) with Binomial and Poisson distribution, MaxEnt, Random Forests, Artificial Neural Networks, and Multiple Adaptive Regression Splines, were compared to predict natural wildfire occurring for seven different climate regions across the United States. The comparisons were conducted using three datasets including LANDFIRE consisting of thirteen variables including characteristics of vegetation, topography and disturbance, BIOCLIM containing climate variables such as temperature and precipitation, and composite data that combine the most important variables from LANDFIRE and BIOCLIM after the multicollinearity test of the variables done using variance inflation factor (VIF). This results of this study showed that niche modeling techniques such as MaxEnt, GLM with logistic regression (LR), and binomial distribution were an appropriate choice for modeling natural wildfire occurrence. MaxEnt provided highly accurate predictions of natural wildfire occurrence for most of seven different climate regions across the United States. This implied that MaxEnt offered a powerful solution for modeling natural wildfire occurrence for complex and highly specialized systems. This study also showed that although MaxEnt and GLM were quite similar, both models produced very different spatial distributions of probability for natural wildfire occurrence in some regions. Moreover, it was found that natural wildfire occurrence in the western regions was more influenced by precipitation and drought conditions while in the eastern regions the natural wildfire occurrence was more affected by extreme temperature.
Download or read book Spatial and Temporal Variation in Biomass Accumulation in Southern California Chaparral written by Kellie Ann Uyeda and published by . This book was released on 2015 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wildfires are a common occurrence in chaparral shrublands, and post-fire patterns of biomass accumulation are important for understanding ecosystem productivity and fuel available for future fires. In this research, I examine patterns of biomass accumulation in southern California chaparral shrublands at early and late stages of post-fire recovery using a combination of detailed field work and remote sensing. Using field measurements of a site with adjacent stands of varying ages and high spatial resolution imagery, I examine patterns of species composition and associated levels of biomass to characterize long-term patterns in biomass accumulation. I also evaluate the potential for utilizing shrub growth ring widths to track annual biomass accumulation in the first decade of post-fire recovery, and test for the relationship between biomass and spatial variation in factors related to the energy and water balance. In addition, I examine the potential for extending the use of shrub growth rings to track biomass across larger spatial extents using satellite-based growth metrics. The study of stands of varying ages reveals that biomass shows substantial variation even within stands of the same age, and that species composition is different in younger stands of chaparral compared to the more mature stands. In the study of growth rings, I find that while measuring growth rings widths is a valuable method for tracking biomass accumulation in the first decade following a fire, there is no apparent relationship between biomass and factors related to the energy and water balance. Annual biomass growth, as estimated from shrub growth ring widths, shows a promising relationship with satellite-based metrics of annual growth, indicating the potential for further study of the relationship over larger spatial extents.
Download or read book Spatial Patterns of Post wildfire Neighborhood Recovery written by Jacqueline W. Curtis (corresponding author) and published by . This book was released on 2012 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Characterizing the Spatial Patterns and Spatially Explicit Probabilities of Post Fire Vegetation Residual Patches in Boreal Wildfire Scars written by Yikalo Hayelom Araya and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Spatio temporal Mapping and Modeling of a New Forest Disease Spread Using Remote Sensing and Spatial Statistics written by Desheng Liu and published by . This book was released on 2006 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Spatial and Temporal Variation in Biomass Accumulation in Southern California Chaparral written by and published by . This book was released on 2014 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wildfires are a common occurrence in chaparral shrublands, and post-fire patterns of biomass accumulation are important for understanding ecosystem productivity and fuel available for future fires. In this research, I examine patterns of biomass accumulation in southern California chaparral shrublands at early and late stages of post-fire recovery using a combination of detailed field work and remote sensing. Using field measurements of a site with adjacent stands of varying ages and high spatial resolution imagery, I examine patterns of species composition and associated levels of biomass to characterize long-term patterns in biomass accumulation. I also evaluate the potential for utilizing shrub growth ring widths to track annual biomass accumulation in the first decade of post-fire recovery, and test for the relationship between biomass and spatial variation in factors related to the energy and water balance. In addition, I examine the potential for extending the use of shrub growth rings to track biomass across larger spatial extents using satellite-based growth metrics. The study of stands of varying ages reveals that biomass shows substantial variation even within stands of the same age, and that species composition is different in younger stands of chaparral compared to the more mature stands. In the study of growth rings, I find that while measuring growth rings widths is a valuable method for tracking biomass accumulation in the first decade following a fire, there is no apparent relationship between biomass and factors related to the energy and water balance. Annual biomass growth, as estimated from shrub growth ring widths, shows a promising relationship with satellite-based metrics of annual growth, indicating the potential for further study of the relationship over larger spatial extents.
