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Remote sensing has demonstrated to be an instrumental tool in monitoring land changes as a result of anthropogenic change or natural disasters. Most disaster studies have focused on large-scale events with few analyzing small-scale disasters such as tornadoes. These studies have only provided a damage assessment perspective with the continued need to assess reconstruction. This study attempts to fill that void by examining recovery from the 1999 Moore, Oklahoma Tornado utilizing Landsat TM and ETM+ imagery. Recovery was assessed for 2000, 2001 and 2002 using spectral enhancements (vegetative and urban indices and a combination of the two), a recovery index and different statistical thresholds. Classification accuracy assessments were performed to determine the precision of recovery and select the best results. This analysis proved that medium resolution imagery could be used in conjunction with geospatial techniques to capture recovery. The new indices, Shortwave Infrared Index (SWIRI) and Coupled Vegetation and Urban Index (CVUI), developed for disaster management, were the most effective at discerning reconstruction using the 1.5 standard deviation threshold. Recovery rates for F-scale damages revealed that the most incredibly damaged areas associated with an F5 rating were the slowest to recover, while the lesser damaged areas associated with F1-F3 ratings were the quickest to rebuild. These findings were consistent for 2000, 2001 and 2002 also exposing that complete recovery was never attained in any of the F-scale damage zones by 2002. This study illustrates the significance the biophysical impact has on recovery as well as the effectiveness of using medium resolution imagery such as Landsat in future research.
ContributorsWagner, Melissa A (Author) / Cerveny, Randall S. (Thesis advisor) / Myint, Soe W. (Thesis advisor) / Wentz, Elizabeth (Committee member) / Brazel, Anthony J. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Diseases have been part of human life for generations and evolve within the population, sometimes dying out while other times becoming endemic or the cause of recurrent outbreaks. The long term influence of a disease stems from different dynamics within or between pathogen-host, that have been analyzed and studied by many researchers using mathematical models. Co-infection with different pathogens is common, yet little is known about how infection with one pathogen affects the host's immunological response to another. Moreover, no work has been found in the literature that considers the variability of the host immune health or that examines a disease at the population level and its corresponding interconnectedness with the host immune system. Knowing that the spread of the disease in the population starts at the individual level, this thesis explores how variability in immune system response within an endemic environment affects an individual's vulnerability, and how prone it is to co-infections. Immunology-based models of Malaria and Tuberculosis (TB) are constructed by extending and modifying existing mathematical models in the literature. The two are then combined to give a single nine-variable model of co-infection with Malaria and TB. Because these models are difficult to gain any insight analytically due to the large number of parameters, a phenomenological model of co-infection is proposed with subsystems corresponding to the individual immunology-based model of a single infection. Within this phenomenological model, the variability of the host immune health is also incorporated through three different pathogen response curves using nonlinear bounded Michaelis-Menten functions that describe the level or state of immune system (healthy, moderate and severely compromised). The immunology-based models of Malaria and TB give numerical results that agree with the biological observations. The Malaria--TB co-infection model gives reasonable results and these suggest that the order in which the two diseases are introduced have an impact on the behavior of both. The subsystems of the phenomenological models that correspond to a single infection (either of Malaria or TB) mimic much of the observed behavior of the immunology-based counterpart and can demonstrate different behavior depending on the chosen pathogen response curve. In addition, varying some of the parameters and initial conditions in the phenomenological model yields a range of topologically different mathematical behaviors, which suggests that this behavior may be able to be observed in the immunology-based models as well. The phenomenological models clearly replicate the qualitative behavior of primary and secondary infection as well as co-infection. The mathematical solutions of the models correspond to the fundamental states described by immunologists: virgin state, immune state and tolerance state. The phenomenological model of co-infection also demonstrates a range of parameter values and initial conditions in which the introduction of a second disease causes both diseases to grow without bound even though those same parameters and initial conditions did not yield unbounded growth in the corresponding subsystems. This results applies to all three states of the host immune system. In terms of the immunology-based system, this would suggest the following: there may be parameter values and initial conditions in which a person can clear Malaria or TB (separately) from their system but in which the presence of both can result in the person dying of one of the diseases. Finally, this thesis studies links between epidemiology (population level) and immunology in an effort to assess the impact of pathogen's spread within the population on the immune response of individuals. Models of Malaria and TB are proposed that incorporate the immune system of the host into a mathematical model of an epidemic at the population level.
ContributorsSoho, Edmé L (Author) / Wirkus, Stephen (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Chowell-Puente, Gerardo (Committee member) / Arizona State University (Publisher)
Created2011
Description
Surveys have shown that several hundred billion weather forecasts are obtained by the United States public each year, and that weather news is one of the most consumed topics in the media. This indicates that the forecast provides information that is significant to the public, and that the public utilizes details associated with it to inform aspects of their life. Phoenix, Arizona is a dry, desert region that experiences a monsoon season and extreme heat. How then, does the weather forecast influence the way Phoenix residents make decisions? This paper aims to draw connections between the weather forecast, decision making, and people who live in a desert environment. To do this, a ten-minute survey was deployed through Amazon Mechanical Turk (MTurk) in which 379 respondents were targeted. The survey asks 45 multiple choice and ranking questions categorized into four sections: obtainment of the forecast, forecast variables of interest, informed decision making based on unique weather variables, and demographics. This research illuminates how residents in the Phoenix metropolitan area use the local weather forecast for decision-making on daily activities, and the main meteorological factors that drive those decisions.
ContributorsMarturano, Julia (Author) / Middel, Ariane (Thesis director) / Schneider, Florian (Committee member) / School of Geographical Sciences and Urban Planning (Contributor, Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This dissertation research investigates both spatial and temporal aspects of Bronze Age land use and land cover in the Eastern Mediterranean using botanical macrofossils of charcoal and charred seeds as sources of proxy data. Comparisons through time and over space using seed and charcoal densities, seed to charcoal ratios, and seed and charcoal identifications provide a comprehensive view of island vs. mainland vegetative trajectories through the critical 1000 year time period from 2500 BC to 1500 BC of both climatic fluctuation and significant anthropogenic forces. This research focuses particularly on the Mediterranean island of Cyprus during this crucial interface of climatic and human impacts on the landscape. Macrobotanical data often are interpreted locally in reference to a specific site, whereas this research draws spatial comparisons between contemporaneous archaeological sites as well as temporal comparisons between non-contemporaneous sites. This larger perspective is particularly crucial on Cyprus, where field scientists commonly assume that botanical macrofossils are poorly preserved, thus unnecessarily limiting their use as an interpretive proxy. These data reveal very minor anthropogenic landscape changes on the island of Cyprus compared to those associated with contemporaneous mainland sites. These data also reveal that climatic forces influenced land use decisions on the mainland sites, and provides crucial evidence pertaining to the rise of early anthropogenic landscapes and urbanized civilization.
ContributorsKlinge, JoAnna M (Author) / Fall, Patricia L. (Thesis advisor) / Falconer, Steven E. (Committee member) / Brazel, Anthony J. (Committee member) / Pigg, Kathleen B (Committee member) / Arizona State University (Publisher)
Created2013
Description
Solution methods for certain linear and nonlinear evolution equations are presented in this dissertation. Emphasis is placed mainly on the analytical treatment of nonautonomous differential equations, which are challenging to solve despite the existent numerical and symbolic computational software programs available. Ideas from the transformation theory are adopted allowing one to solve the problems under consideration from a non-traditional perspective. First, the Cauchy initial value problem is considered for a class of nonautonomous and inhomogeneous linear diffusion-type equation on the entire real line. Explicit transformations are used to reduce the equations under study to their corresponding standard forms emphasizing on natural relations with certain Riccati(and/or Ermakov)-type systems. These relations give solvability results for the Cauchy problem of the parabolic equation considered. The superposition principle allows to solve formally this problem from an unconventional point of view. An eigenfunction expansion approach is also considered for this general evolution equation. Examples considered to corroborate the efficacy of the proposed solution methods include the Fokker-Planck equation, the Black-Scholes model and the one-factor Gaussian Hull-White model. The results obtained in the first part are used to solve the Cauchy initial value problem for certain inhomogeneous Burgers-type equation. The connection between linear (the Diffusion-type) and nonlinear (Burgers-type) parabolic equations is stress in order to establish a strong commutative relation. Traveling wave solutions of a nonautonomous Burgers equation are also investigated. Finally, it is constructed explicitly the minimum-uncertainty squeezed states for quantum harmonic oscillators. They are derived by the action of corresponding maximal kinematical invariance group on the standard ground state solution. It is shown that the product of the variances attains the required minimum value only at the instances that one variance is a minimum and the other is a maximum, when the squeezing of one of the variances occurs. Such explicit construction is possible due to the relation between the diffusion-type equation studied in the first part and the time-dependent Schrodinger equation. A modication of the radiation field operators for squeezed photons in a perfect cavity is also suggested with the help of a nonstandard solution of Heisenberg's equation of motion.
ContributorsVega-Guzmán, José Manuel, 1982- (Author) / Sulov, Sergei K (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Platte, Rodrigo (Committee member) / Chowell-Puente, Gerardo (Committee member) / Arizona State University (Publisher)
Created2013
Description
The characteristics of the wintertime 500hPa height surface, the level of non-divergence and used for identifying/observing synoptic-scale features (ridges and troughs), and their impact on precipitation are of significance to forecasters, natural resource managers and planners across the southwestern United States. For this study, I evaluated the location of the 500hPa mean Pacific ridge axis over the winter for the period of 1948/49 to 2011/12 and derived the mean ridge axis in terms of location (longitude) and intensity (geopotential meters) from the NCEP/NCAR Reanalysis dataset. After deriving a mean ridge axis climatology and analyzing its behavior over time, I correlated mean location and intensity values to observed wintertime precipitation in select U.S. Climate Divisions in Arizona, Colorado, Nevada, Utah and New Mexico. This resulted in two findings. First specific to the 500hPa ridge behavior, the ridge has been moving eastward and also has been intensifying through time. Second, results involving correlation tests between mean ridge location and intensity indicate precipitation across the selected Southwest Climate Divisions are strongly related to mean ridge intensity slightly more than ridge location. The relationships between mean ridge axis and observed precipitation also are negative, indicating an increase of one of the ridge parameters (i.e. continued eastward movement or intensification) lead to drier winter seasons across the Southwest. Increased understanding of relationships between upper-level ridging and observed wintertime precipitation aids in natural resource planning for an already arid region that relies heavily on winter precipitation.
ContributorsNolte, Jessica Marie (Author) / Cerveny, Randall S. (Thesis advisor) / Selover, Nancy J. (Committee member) / Brazel, Anthony J. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Droughts are a common phenomenon of the arid South-west USA climate. Despite water limitations, the region has been substantially transformed by agriculture and urbanization. The water requirements to support these human activities along with the projected increase in droughts intensity and frequency challenge long term sustainability and water security, thus the need to spatially and temporally characterize land use/land cover response to drought and quantify water consumption is crucial. This dissertation evaluates changes in `undisturbed' desert vegetation in response to water availability to characterize climate-driven variability. A new model coupling phenology and spectral unmixing was applied to Landsat time series (1987-2010) in order to derive fractional cover (FC) maps of annuals, perennials, and evergreen vegetation. Results show that annuals FC is controlled by short term water availability and antecedent soil moisture. Perennials FC follow wet-dry multi-year regime shifts, while evergreen is completely decoupled from short term changes in water availability. Trend analysis suggests that different processes operate at the local scale. Regionally, evergreen cover increased while perennials and annuals cover decreased. Subsequently, urban land cover was compared with its surrounding desert. A distinct signal of rain use efficiency and aridity index was documented from remote sensing and a soil-water-balance model. It was estimated that a total of 295 mm of water input is needed to sustain current greenness. Finally, an energy balance model was developed to spatio-temporally estimate evapotranspiration (ET) as a proxy for water consumption, and evaluate land use/land cover types in response to drought. Agricultural fields show an average ET of 9.3 mm/day with no significant difference between drought and wet conditions, implying similar level of water usage regardless of climatic conditions. Xeric neighborhoods show significant variability between dry and wet conditions, while mesic neighborhoods retain high ET of 400-500 mm during drought due to irrigation. Considering the potentially limited water availability, land use/land cover changes due to population increases, and the threat of a warming and drying climate, maintaining large water-consuming, irrigated landscapes challenges sustainable practices of water conservation and the need to provide amenities of this desert area for enhancing quality of life.
ContributorsKaplan, Shai (Author) / Myint, Soe Win (Thesis advisor) / Brazel, Anthony J. (Committee member) / Georgescu, Matei (Committee member) / Arizona State University (Publisher)
Created2014
Description
I present the results of studies from two historically separate fields of research: heat related illness and human thermal comfort adaptation. My research objectives were: (a) to analyze the relationships between climate and heat related morbidity in Phoenix, Arizona and Chicago, Illinois; (b) explore possible linkages of human thermal comfort adaptation to heat-related illness; and (c) show possible benefits of collaboration between the two fields of research. Previous climate and mortality studies discovered regional patterns in summertime mortality in North America: lower in hot, southern cities compared to more temperate cities. I examined heat related emergency (911) dispatches from these two geographically and climatically different cities. I analyzed with local weather conditions with 911 dispatches identified by responders as "heat" related from 2001 to 2006 in Phoenix and 2003 through 2006 in Chicago. Both cities experienced a rapid rise in heat-related dispatches with increasing temperature and heat index, but at higher thresholds in Phoenix. Overall, Phoenix had almost two and half times more heat-related dispatches than Chicago. However, Phoenix did not experience the large spikes of heat-related dispatches that occurred in Chicago. These findings suggest a resilience to heat-related illness that may be linked to acclimatization in Phoenix. I also present results from a survey based outdoor human thermal comfort field study in Phoenix to assess levels of local acclimatization. Previous research in outdoor human thermal comfort in hot humid and temperate climates used similar survey-based methodologies and found higher levels of thermal comfort (adaptation to heat) that in warmer climates than in cooler climates. The study presented in this dissertation found outdoor thermal comfort thresholds and heat tolerance levels in Phoenix were higher than previous studies from temperate climates more similar to Chicago. These differences were then compared to the differences in weather conditions associated with heat-related dispatches. The higher comfort thresholds in Phoenix were similar in scale to the climate differences associated with the upsurge in heat-related dispatches in Phoenix and Chicago. This suggests a link between heat related illness and acclimatization, and illustrates potential for collaboration in research between the two fields.
ContributorsHartz, Donna (Author) / Brazel, Anthony J. (Thesis advisor) / Heisler, Gordon (Committee member) / Cerveny, Randal (Committee member) / Arizona State University (Publisher)
Created2012
Description
Isentropic analysis is a type of analysis that is based on using the concept of potential temperatures, the adiabatically established temperature at 1000 hPa. In the 1930s and 1940s this type of analysis proved to be valuable in indicating areas of increased moisture content and locations experiencing flow up or down adiabatic surfaces. However, in the early 1950s, this type of analysis faded out of use and not until the twenty-first century have some researchers started once again to examine the usefulness of isentropic analysis. One aspect in which isentropic analysis could be practical, based on prior research, is in severe weather situations, due to its ability to easily show adiabatic motion and moisture. As a result, I analyzed monthly climatological isentropic surfaces to identify distinct patterns associated with tornado occurrences for specific regions and months across the contiguous United States. I collected tornado reports from 1974 through 2009 to create tornado regions for each month across the contiguous United States and corresponding upper air data for the same time period. I then separated these upper air data into tornado and non-tornado days for specific regions and conducted synoptic and statistical analyses to establish differences between the two. Finally, I compared those results with analyses of individual case studies for each defined region using independent data from 2009 through 2010. On tornado days distinct patterns can be identified on the isentropic surface: (1) the average isentropic surface lowered on tornado days indicating a trough across the region, (2) a corresponding increase in moisture content occurred across the tornado region, and (3) wind shifted in such a manner to produce flow up the isentropic trough indicating uplift. When comparing the climatological results with the case studies, the isentropic pattern for the case studies in general was more pronounced compared to the climatological pattern; however, this would be expected as when creating the average the pattern/conditions will be smoothed. These findings begin to bridge the large gap in literature, show the usefulness of isentropic analysis in monthly and daily use and serve as catalysts to create a finer resolution database in isentropic coordinates.
ContributorsPace, Matthew Brandon (Author) / Cerveny, Randall S. (Thesis advisor) / Selover, Nancy J (Committee member) / Brazel, Anthony J. (Committee member) / Arizona State University (Publisher)
Created2012
Description
Accurate characterization of forest canopy cover from satellite imagery hinges on the development of a model that considers the level of detail achieved by field methods. With the improved precision of both optical sensors and various spatial techniques, models built to extract forest structure attributes have become increasingly robust, yet many still fail to address some of the most important characteristics of a forest stand's intricate make-up. The objective of this study, therefore, was to address canopy cover from the ground, up. To assess canopy cover in the field, a vertical densitometer was used to acquire a total of 2,160 percent-cover readings from 30 randomly located triangular plots within a 6.94 km2 study area in the central highlands of the Bradshaw Ranger District, Prescott National Forest, Arizona. Categorized by species with the largest overall percentage of cover observations (Pinus ponderosa, Populus tremuloides, and Quercus gambelii), three datasets were created to assess the predictability of coniferous, deciduous, and mixed (coniferous and deciduous) canopies. Landsat-TM 5 imagery was processed using six spectral enhancement algorithms (PCA, TCT, NDVI, EVI, RVI, SAVI) and three local windows (3x3, 5x5, 7x7) to extract and assess the various ways in which these data were expressed in the imagery, and from those expressions, develop a model that predicted percent-cover for the entire study area. Generally, modeled cover estimates exceeded actual cover, over predicting percent-cover by a margin of 9-13%. Models predicted percent-cover more accurately when treated with a 3x3 local window than those treated with 5x5 and 7x7 local windows. In addition, the performance of models defined by the principal components of three vegetation indices (NDVI, EVI, RVI) were superior to those defined by the principal components of all four (NDVI, EVI, RVI, SAVI), as well as the principal and tasseled cap components of all multispectral bands (bands 123457). Models designed to predict mixed and coniferous percent-cover were more accurate than deciduous models.
ContributorsSchirmang, Tracy Lynn (Author) / Myint, Soe W (Thesis advisor) / Fall, Patricia L. (Thesis advisor) / Brazel, Anthony J. (Committee member) / Arizona State University (Publisher)
Created2012