The danger of Tornadoes in the United States

Die vorliegende Diplomarbeit soll der retrospektiven Analyse von Tornados in den Vereinigten Staaten von 1950 bis 2009 beitragen. Die räumliche und zeitliche Analyse wird unter der Verwendung von Geographischen Informationssystemen (GIS) und raumzeitlichen Statistiken durchgeführt. Zu Beginn wird ein umfangreicher Überblick über der Entstehung und die Struktur von Tornados geboten, dem vorangegangene Studien über die Tornadoaktivität in den Vereinigten Staaten folgen. In Kapitel 2 werden der für die Analyse verwendete Datensatz und Methoden zur Analyse des Datensatzes vorgestellt. Verschiedene Kartierungstechniken werden im Sinne einer Einsetzbarkeit in der räumlichen Clusteranalyse diskutiert. Im Anschluss daran werden die Grundlagen von räumlichen und raumzeitlichen Statistiken erörtert. Das Kapitel schließt mit der Vorstellung von vier gewählten Statistiken und deren Anwendung in der raumzeitlichen Analyse. Der Fokus wurde hierbei auf Statistiken gesetzt, die in frei verfügbaren Softwarepaketen enthalten sind. In der räumlichen und zeitlichen Analyse von Tornados werden die Kerndichteschätzung, die Nächste Nachbar Hierarchische Clusterungtechnik, der Lokale Moran’s I als Local Indicator of Spatial Association (LISA) und das raumzeitliche Permutationsmodell als raumzeitliche Scan Statistik verwendet. Es werden der gesamte Datensatz, Tornados gegliedert nach der F-Skala, monatliche Maxima in der Tornadointensität und die Anzahl von Personen, die während eines Tornados verunglückt sind, analysiert, wobei eine Kombination von den statistischen Methoden herangezogen wird. Die erhaltenen Ergebnisse von den verschiedenen angewendeten Techniken werden folglich zuerst untereinander als auch zu den Ergebnissen vorangegangener Studien verglichen. Generell gleichen die in dieser Diplomarbeit erhaltenen Ergebnisse der räumlichen Analyse der Tornados den Resultaten vorangegangener Studien. Höhere Konzentrationen von Tornados, welche in vorangegangenen Studien unentdeckt blieben, wurden im Süden der Vereinigten Staaten, speziell in Mississippi und Florida, gefunden. Da frühere Studien keine zeitlichen Veränderungen in räumlichen Mustern behandelt haben, sind diese Ergebnisse in dieser Diplomarbeit sehr aufschlussreich. Erhöhte Tornadointensitäten zwischen zwei definierten Zeiträumen wurden in der Nähe von Denver, CO, Houston, TX, und St. Petersburg, FL, identifiziert. Verminderte Intensitäten von signifikanten Tornados (die als F2 oder höher klassifiziert wurden) wurden in der Region der Great Plains, besonders im nördlichen Texas und Oklahoma, aufgezeichnet.This diploma thesis contributes to the retrospective analysis of tornado occurrences in the United States from 1950 to 2009. The spatial and temporal analysis is carried out with Geographic Information Systems (GIS) and spatiotemporal statistics. At the beginning an extensive overview about the genesis and composition of tornadoes is given, followed by a comprehensive discussion of previous studies about tornado occurrences in the United States. Data and the methodology that will be used for the analysis are the content of Chapter 2. Different mapping principles are presented and compared for the suitability in spatial cluster analysis. Then, the basics of spatial and temporal statistics are discussed. The chapter concludes with the presentation of four selected spatial and spatiotemporal statistics and how they can be applied for a space-time analysis of events. The focus of discussion in Chapter 3 is on spatial and spatiotemporal statistics that are available in open source software packages. For the spatial and temporal analysis of tornado touchdown points the kernel density estimation technique, the Nearest Neighbor Hierarchical Clustering (NNHC) routine, the Local Moran’s I as Local Indicators of Spatial Association (LISA) method, and the space-time permutation model as space-time scan statistic are applied. The entire tornado dataset, tornadoes by F-Scale, monthly maxima in tornado occurrences, and tornado fatalities are being analyzed by using a combination of these statistical techniques. Finally, the results from the different statistics are compared with each other and with related studies. In general, the results of the spatial analysis of tornado touchdown points in this thesis show similar outcomes compared to previous studies. Higher concentrations of tornado occurrences which have not been detected in previous studies can be found in the south of the United States, especially in Mississippi and Florida. Since the previous studies did not contain temporal variations of tornado patterns, these new results in this thesis are very insightful. High increases in tornado intensity between two defined time periods have been detected around Denver, CO, Houston, TX, and St. Petersburg, FL, whereas decreases in the intensity of significant tornadoes (rated F2 and higher) have been identified in the area of the Great Plains, especially in northern Texas and Oklahoma

A comparative analysis to forecast apartment burglaries in Vienna, Austria, based on repeat and near repeat victimization

In this paper, we introduce two methods to forecast apartment burglaries that are based on repeat and near repeat victimization. While the first approach, the “heuristic method” generates buffer areas around each new apartment burglary, the second approach concentrates on forecasting near repeat chain links. These near repeat chain links are events that follow a near repeat pair of an originating and (near) repeat event that is close in space and in time. We name this approach the “near repeat chain method”. This research analyzes apartment burglaries from November 2013 to November 2016 in Vienna, Austria. The overall research goal is to investigate whether the near repeat chain method shows better prediction efficiencies (using a capture rate and the prediction accuracy index) while producing fewer prediction areas. Results show that the near repeat chain method proves to be the more efficient compared to the heuristic method for all bandwidth combinations analyzed in this research.DK W 1237-N23(VLID)286105

Binary systems and their nuclear explosions

Peer ReviewedPreprin

Spatial and temporal analysis of crime and the impact of rhythmic cycles to predict future crime locations : studies from the city of Vienna, Austria

submitted by Mag. rer. nat. Philip GlasnerLiteraturangabenParis Lodron University Salzburg, Dissertation, 2018OeBB(VLID)500314

Evaluating the Impact the Weekday Has on Near-Repeat Victimization: A Spatio-Temporal Analysis of Street Robberies in the City of Vienna, Austria

The near-repeat phenomenon refers to the increased risk of repeat victimization not only at the same location but at nearby locations up to a certain distance and for a certain time period. In recent research, near-repeat victimization has been repeatedly confirmed for different crime types such as burglaries or shootings. In this article the near-repeat phenomenon is analyzed for each day of the week separately. That is, the near-repeat pattern is evaluated for all consecutive Mondays, Tuesdays, Wednesdays, etc. included in the dataset. These consecutive weekdays represent the fictive set of consecutive dates to allow for spatial and temporal analysis of crime patterns. Using these principles, it is hypothesized that street robberies cluster in space and time and by the same day of the week. This research analyzes street robberies from 2009 to 2013 in Vienna, Austria. The overall research goal investigates whether near-repeat patterns of robberies exist by weekdays and in an additional step by time of day, and whether these near-repeat patterns differ from each other and from purely spatial patterns. The results of this research confirm the existence of near-repeat patterns by weekday and especially by time of day. Distinctive locations have been identified that differ greatly per weekday and time of day. Based on this information, law enforcement agencies in Austria can optimize strategic planning of police resources in combating robberies

Laws of Geography

This article explores and unpacks the entanglements between law and geography that enable and advance the exclusion of non-citizens from entry into sovereign territory. We suggest that states manipulate jurisdiction within and beyond sovereign territory to extend enforcement. This jurisdiction applies primarily to the bodies of migrants themselves as opposed to fixed spaces. Like Elden’s (2009, 2013) imperio, or imperial power, this extension is spatially boundless, limitless in internal checks and administrative. Imperio places migrant bodies into new legal regimes with subjectivities that overlap and override existing protections, such as international refugee law. We develop our argument by considering enforcement practices in three areas: the waiting zone at Paris Charles de Gaulle airport, search and rescue areas on the Central Mediterranean Sea and Australian excision zones

Automatic construction of explanation networks for a cooperative user interface

Computer Science Departmen