Identifying Crisis Response Communities in Online Social Networks for Compound Disasters: The Case of Hurricane Laura and Covid-19

Online social networks allow different agencies and the public to interact and share the underlying risks and protective actions during major disasters. This study revealed such crisis communication patterns during hurricane Laura compounded by the COVID-19 pandemic. Laura was one of the strongest (Category 4) hurricanes on record to make landfall in Cameron, Louisiana. Using the Application Programming Interface (API), this study utilizes large-scale social media data obtained from Twitter through the recently released academic track that provides complete and unbiased observations. The data captured publicly available tweets shared by active Twitter users from the vulnerable areas threatened by Laura. Online social networks were based on user influence feature ( mentions or tags) that allows notifying other users while posting a tweet. Using network science theories and advanced community detection algorithms, the study split these networks into twenty-one components of various sizes, the largest of which contained eight well-defined communities. Several natural language processing techniques (i.e., word clouds, bigrams, topic modeling) were applied to the tweets shared by the users in these communities to observe their risk-taking or risk-averse behavior during a major compounding crisis. Social media accounts of local news media, radio, universities, and popular sports pages were among those who involved heavily and interacted closely with local residents. In contrast, emergency management and planning units in the area engaged less with the public. The findings of this study provide novel insights into the design of efficient social media communication guidelines to respond better in future disasters

Human dynamics in the age of big data: a theory-data-driven approach

The revolution of information and communication technology (ICT) in the past two decades have transformed the world and people’s lives with the ways that knowledge is produced. With the advancements in location-aware technologies, a large volume of data so-called “big data” is now available through various sources to explore the world. This dissertation examines the potential use of such data in understanding human dynamics by focusing on both theory- and data-driven approaches. Specifically, human dynamics represented by communication and activities is linked to geographic concepts of space and place through social media data to set a research platform for effective use of social media as an information system. Three case studies covering these conceptual linkages are presented to (1) identify communication patterns on social media; (2) identify spatial patterns of activities in urban areas and detect events; and (3) explore urban mobility patterns. The first case study examines the use of and communication dynamics on Twitter during Hurricane Sandy utilizing survey and data analytics techniques. Twitter was identified as a valuable source of disaster-related information. Additionally, the results shed lights on the most significant information that can be derived from Twitter during disasters and the need for establishing bi-directional communications during such events to achieve an effective communication. The second case study examines the potential of Twitter in identifying activities and events and exploring movements during Hurricane Sandy utilizing both time-geographic information and qualitative social media text data. The study provides insights for enhancing situational awareness during natural disasters. The third case study examines the potential of Twitter in modeling commuting trip distribution in New York City. By integrating both traditional and social media data and utilizing machine learning techniques, the study identified Twitter as a valuable source for transportation modeling. Despite the limitations of social media such as the accuracy issue, there is tremendous opportunity for geographers to enrich their understanding of human dynamics in the world. However, we will need new research frameworks, which integrate geographic concepts with information systems theories to theorize the process. Furthermore, integrating various data sources is the key to future research and will need new computational approaches. Addressing these computational challenges, therefore, will be a crucial step to extend the frontier of big data knowledge from a geographic perspective. KEYWORDS: Big data, social media, Twitter, human dynamics, VGI, natural disasters, Hurricane Sandy, transportation modeling, machine learning, situational awareness, NYC, GI

Post-Disaster Supply Chain Interdependent Critical Infrastructure System Restoration: A Review of Data Necessary and Available for Modeling

The majority of restoration strategies in the wake of large-scale disasters have focused on short-term emergency response solutions. Few consider medium- to long-term restoration strategies to reconnect urban areas to national supply chain interdependent critical infrastructure systems (SCICI). These SCICI promote the effective flow of goods, services, and information vital to the economic vitality of an urban environment. To re-establish the connectivity that has been broken during a disaster between the different SCICI, relationships between these systems must be identified, formulated, and added to a common framework to form a system-level restoration plan. To accomplish this goal, a considerable collection of SCICI data is necessary. The aim of this paper is to review what data are required for model construction, the accessibility of these data, and their integration with each other. While a review of publically available data reveals a dearth of real-time data to assist modeling long-term recovery following an extreme event, a significant amount of static data does exist and these data can be used to model the complex interdependencies needed. For the sake of illustration, a particular SCICI (transportation) is used to highlight the challenges of determining the interdependencies and creating models capable of describing the complexity of an urban environment with the data publically available. Integration of such data as is derived from public domain sources is readily achieved in a geospatial environment, after all geospatial infrastructure data are the most abundant data source and while significant quantities of data can be acquired through public sources, a significant effort is still required to gather, develop, and integrate these data from multiple sources to build a complete model. Therefore, while continued availability of high quality, public information is essential for modeling efforts in academic as well as government communities, a more streamlined approach to a real-time acquisition and integration of these data is essential

Towards LoRa mesh networks for the IoT

There are several LPWAN radio technologies providing wireless communication to the billions of connected devices that form the so-called IoT. Among them, LoRa has emerged in recent years as a popular solution for low power embedded devices to transmit data at long distances on a reduced energy budget. Most often, LoRa is used as the physical layer of LoRaWAN, an open standard that defines a MAC layer and specifies the star-of-stars topology, operation, roles and mechanisms for an integrated, full-stack IoT architecture. Nowadays, millions of devices use LoRaWAN networks in all sorts of agriculture, smart cities and buildings, industry, logistics and utilities scenarios. Despite its success in all sorts of IoT domains and environments, there are still use cases that would benefit from more flexible network topologies than LoRaWAN's star-of-stars. For instance, in scenarios where the deployment and operation of the backbone network infrastructure is technically or economically challenging, a more flexible model may improve certain performance metrics. As a first major contribution, this thesis investigates the effects of adding multi-hop capability to LoRaWAN, by means of the realistic use case of a communication system based on this architecture that provides a coordinated response in the aftermath of natural disasters like an earthquake. The capacity of end nodes to forward packets and perform multi-hop transmissions is explored, as a strategy to overcome gateway infrastructure failures, and analyzed for challenges, benefits and drawbacks in a massive system with thousands of devices. LoRa is also used as a stand-alone radio technology, independently from the LoRaWAN architecture. Its CSS modulation offers many advantages in LPWANs for IoT deployments. In particular, its different SFs available determine a trade-off between transmission time (i.e., data rate) and sensitivity (i.e., distance reach), and also generate quasi-orthogonal signals that can be demodulated concurrently by different receivers. The second major contribution of this thesis is the design of a minimalistic distance-vector routing protocol for embedded IoT devices featuring a LoRa transceiver, and the proposal of a path cost calculation metric that takes advantage of the multi-SF capability to reduce end-to-end transmission time. The protocol is evaluated through simulation and compared with other well-known routing strategies, analyzing and discussing its suitability for heterogeneous IoT LoRa mesh networks.Hi ha diverses tecnologies de ràdio LPWAN que proporcionen comunicació sense fils als milers de milions de dispositius connectats que conformen l'anomenada IoT. D'entre elles, LoRa ha emergit en els darrers anys com una solució popular per a què dispositius encastats amb pocs recursos transmetin dades a llargues distàncies amb un cost energètic reduït. Tot sovint, LoRa s'empra com la capa física de LoRaWAN, un estàndard obert que defineix una capa MAC i que especifica la topologia en estrella d'estrelles, l'operació, els rols i els mecanismes per implementar una arquitectura de la IoT integrada. A dia d'avui, milions de dispositius fan servir xarxes LoRaWAN en escenaris d'agricultura, edificis i ciutats intel·ligents, indústria, logística i subministraments. Malgrat el seu èxit en tot tipus d'entorns i àmbits de la IoT, encara romanen casos d'ús que es beneficiarien de topologies de xarxa més flexibles que l'estrella d'estrelles de LoRaWAN. Per exemple, en escenaris on el desplegament i l'operació de la infraestructura troncal de xarxa és tècnicament o econòmica inviable, una topologia més flexible podria millorar certs aspectes del rendiment. Com a primera contribució principal, en aquesta tesi s'investiguen els efectes d'afegir capacitat de transmissió multi-salt a LoRaWAN, mitjançant el cas d'ús realista d'un sistema de comunicació, basat en aquesta arquitectura, per proporcionar una resposta coordinada en els moments posteriors a desastres naturals, tals com un terratrèmol. En concret, s'explora l'estratègia d'afegir la capacitat de reenviar paquets als nodes finals per tal d'eludir les fallades en la infraestructura, i se n'analitzen els reptes, beneficis i inconvenients per a un sistema massiu amb milers de dispositius LoRa s'empra també com a tecnologia de ràdio de forma autònoma, independentment de l'arquitectura LoRaWAN. La seva modulació CSS li confereix molts avantatges en xarxes LPWAN per a desplegaments de la IoT. En particular, els diferents SFs disponibles hi determinen un compromís entre la durada de les transmissions (i.e., la taxa de dades) i la sensibilitat en la recepció (i.e., l'abast en distància), alhora que generen senyals quasi-ortogonals que poden ser desmodulades de forma concurrent per receptors diferents. La segona contribució principal d'aquesta tesi és el disseny d'un protocol d'encaminament dinàmic vector-distància per a dispositius de la IoT encastats amb un transceptor LoRa, i la proposta d'una mètrica per calcular el cost d'un camí que aprofita la capacitat multi-SF per minimitzar el temps de transmissió d'extrem a extrem. El protocol és avaluat mitjançant simulacions i comparat amb altres estratègies d'encaminament conegudes, analitzant la seva conveniència per a xarxes LoRa mallades per a la IoT.Existen varias tecnologías de radio LPWAN que proporcionan comunicación inalámbrica a los miles de millones de dispositivos conectados que forman el llamado IoT. De entre ellas, LoRa ha emergido en los últimos años como una solución popular para que dispositivos embebidos con pocos recursos transmitan datos a largas distancias con un coste energético reducido. Habitualmente, LoRa se usa como la capa física de LoRaWAN, un estándar abierto que define una capa MAC y que especi_ca la topología en estrella de estrellas, la operación, los roles y los mecanismos para implantar una arquitectura del IoT integrada. A día de hoy, millones de dispositivos utilizan redes LoRaWAN en escenarios de agricultura, edificios y ciudades inteligentes, industria, logística y suministros. A pesar de su éxito en todo tipo de entornos y ámbitos del IoT, existen casos de uso que se beneficiaran de topologías de red más flexibles que la estrella de estrellas de LoRaWAN. Por ejemplo, en escenarios en los que el despliegue y la operación de la infraestructura troncal de red es técnica o económicamente inviable, una topología más flexible podrá mejorar ciertos aspectos del rendimiento. Como primera contribución principal, en esta tesis se investigan los efectos de añadir capacidad de transmisión multi-salto a LoRaWAN, mediante el caso de uso realista de un sistema de comunicación basado en dicha arquitectura, para proporcionar una respuesta coordinada en los momentos posteriores a desastres naturales, tales como un terremoto. En concreto, se explora la estrategia de añadir la capacidad de reenviar paquetes a los nodos finales para sortear las fallas en la infraestructura, y se analizan los retos, beneficios e inconvenientes para un sistema masivo con miles de dispositivos. LoRa se usa también como tecnología de radio de forma autónoma, independientemente de la arquitectura LoRaWAN. Su modulación CSS le confiere muchas ventajas en redes LPWAN para despliegues de IoT. En particular, los distintos SFs disponibles determinan un compromiso entre la duración de las transmisiones (i.e., la tasa de datos) y la sensibilidad en la recepción (i.e., el alcance en distancia), a la vez que generan señales cuasi-ortogonales que pueden ser desmoduladas de forma concurrente por receptores distintos. En segundo lugar, esta tesis contiene el diseño de un protocolo de enrutamiento dinámico vector-distancia para dispositivos Internet of Things (IoT) embebidos con un transceptor LoRa, y propone una métrica para calcular el coste de un camino que aprovecha la capacidad multi-SF para minimizar el tiempo de transmisión de extremo a extremo. El protocolo es evaluado y comparado con otras estrategias de enrutamiento conocidas, analizando su conveniencia para redes LoRa malladas para el IoT.Postprint (published version

Developing a Framework for Stigmergic Human Collaboration with Technology Tools: Cases in Emergency Response

Information and Communications Technologies (ICTs), particularly social media and geographic information systems (GIS), have become a transformational force in emergency response. Social media enables ad hoc collaboration, providing timely, useful information dissemination and sharing, and helping to overcome limitations of time and place. Geographic information systems increase the level of situation awareness, serving geospatial data using interactive maps, animations, and computer generated imagery derived from sophisticated global remote sensing systems. Digital workspaces bring these technologies together and contribute to meeting ad hoc and formal emergency response challenges through their affordances of situation awareness and mass collaboration. Distributed ICTs that enable ad hoc emergency response via digital workspaces have arguably made traditional top-down system deployments less relevant in certain situations, including emergency response (Merrill, 2009; Heylighen, 2007a, b). Heylighen (2014, 2007a, b) theorizes that human cognitive stigmergy explains some self-organizing characteristics of ad hoc systems. Elliott (2007) identifies cognitive stigmergy as a factor in mass collaborations supported by digital workspaces. Stigmergy, a term from biology, refers to the phenomenon of self-organizing systems with agents that coordinate via perceived changes in the environment rather than direct communication. In the present research, ad hoc emergency response is examined through the lens of human cognitive stigmergy. The basic assertion is that ICTs and stigmergy together make possible highly effective ad hoc collaborations in circumstances where more typical collaborative methods break down. The research is organized into three essays: an in-depth analysis of the development and deployment of the Ushahidi emergency response software platform, a comparison of the emergency response ICTs used for emergency response during Hurricanes Katrina and Sandy, and a process model developed from the case studies and relevant academic literature is described

Cross-Border Collaboration in Disaster Management

Wenn sich eine Katastrophe ereignet, ist eine schnelle und koordinierte Reaktion der verschiedenen Krisenmanagementakteure unerlässlich, um die vorhandenen Ressourcen bestmöglich einzusetzen und somit ihre Auswirkungen zu begrenzen. Dieses Zusammenspiel wird erschwert, wenn die Katastrophe mehrere Länder betrifft. Neben den unterschiedlichen Regelungen und Systemen spielen dann auch kulturelle Einflüsse wie Sprachbarrieren oder mangelndes Vertrauen eine entscheidende Rolle. Obwohl die Resilienz von Grenzgebieten von fundamentaler Bedeutung ist, wird diese in der wissenschaftlichen Literatur immer noch unterschätzt. Im ersten Teil dieser Arbeit wird ein agentenbasiertes Modell zur Untersuchung der organisationsübergreifenden Zusammenarbeit bei Katastropheneinsätzen in einer Grenzregion vorgestellt. Indem Kommunikationsprotokolle aus der Literatur auf den Kontext der grenzüberschreitenden Kooperation erweitert werden, analysiert das Modell die globale Dynamik, die aus lokalen Entscheidungen resultiert. Ein szenariobasierter Ansatz zeigt, dass höheres Vertrauen zwar zu signifikant besseren Versorgungsraten führt, der Abbau von Sprachbarrieren aber noch effizienter ist. Insbesondere gilt dies, wenn die Akteure die Sprache des Nachbarlandes direkt sprechen, anstatt sich auf eine allgemeine Lingua franca zu verlassen. Die Untersuchung der Koordination zeigt, dass Informationsflüsse entlang der hierarchischen Organisationsstruktur am erfolgreichsten sind, während spontane Zusammenarbeit durch ein etabliertes informelles Netzwerk privater Kontakte den Informationsaustausch ergänzen und in dynamischen Umgebungen einen Vorteil darstellen kann. Darüber hinaus verdoppelt die Einbindung von Spontanfreiwilligen den Koordinationsaufwand. Die Koordination über beide Dimensionen, zum einen die Einbindung in den Katastrophenschutz und zum anderen über Grenzen hinweg, führt jedoch zu einer optimalen Versorgung der betroffenen Bevölkerung. In einem zweiten Teil stellt diese Arbeit ein innovatives empirisches Studiendesign vor, das auf transnationalem Sozialkapital und Weiners Motivationstheorie basiert, um prosoziale Beziehungen der Menschen über nationale Grenzen hinweg zu quantifizieren. Regionale Beziehungen innerhalb der Länder werden dabei als Vergleichsbasis genommen. Die mittels repräsentativer Telefoninterviews in Deutschland, Frankreich und der deutsch-französischen Grenzregion erhobenen Daten belegen die Hypothese, dass das Sozialkapital und die Hilfsbereitschaft über die deutsch-französische Grenze hinweg mindestens so hoch ist wie das regionale Sozialkapital und die Hilfsbereitschaft innerhalb der jeweiligen Länder. Folglich liefert die Arbeit wertvolle Erkenntnisse für Entscheidungsträger, um wesentliche Barrieren in der grenzüberschreitenden Kooperation abzubauen und damit die grenzüberschreitende Resilienz bei zukünftigen Katastrophen zu verbessern. Implikationen für die heutige Zeit in Bezug auf Globalisierung versus aufkommendem Nationalismus sowie Auswirkungen von (Natur-) Katastrophen werden diskutiert