Imaging Disaster is a rich social history of Japan’s Great Kanto Earthquake of 1923. Drawing on a kaleidoscopic range of images from the fine arts, magazines, cartoons, and other popular sources, Gennifer Weisenfeld has produced an original study of this catastrophic event from an art historical perspective. —Jonathan Reynolds, Barnard College Imaging Disaster is an exhaustive and illuminating study of the visual culture generated by Japan’s most devastating natural disaster. Comprehensive in scope—covering photography, cinema, painting, postcards, sketches, urban planning, and even scientific models—Weisenfeld makes a compelling point that the massive profusion of visual representations that followed the quake must itself be considered an integral part of this tragic historical event.—Seiji Lippit, UCLA

Minutes before midnight on the evening of March 12, 1928, the St. Francis Dam collapsed. The dam's 200-foot concrete wall crumpled, sending billions of gallons of raging flood waters down San Francisquito Canyon, sweeping 54 miles down the Santa Clara River to the sea, and claiming over 450 lives in the disaster. Captured here in over 200 images is a photographic record of the devastation caused by the flood, and the heroic efforts of residents and rescue workers. Built by the City of Los Angeles' Bureau of Water Works and Supply, the failure of the St. Francis Dam on its first filling was the greatest American civil engineering failure of the 20th century. Beginning at dawn on the morning after the disaster, stunned local residents picked up their cameras to record the path of destruction, and professional photographers moved in to take images of the washed-out bridges, destroyed homes and buildings, Red Cross workers giving aid, and the massive clean-up that followed. The event was one of the worst disasters in California's history, second only to the San Francisco Earthquake and Fire.

Two years after Hurricane Maria hit, Puerto Ricans are still reeling from its effects and aftereffects. Aftershocks collects poems, essays and photos from survivors of Hurricane Maria detailing their determination to persevere. The concept of "aftershocks" is used in the context of earthquakes to describe the jolts felt after the initial quake, but no disaster is a singular event. Aftershocks of Disaster examines the lasting effects of hurricane Maria, not just the effects of the wind or the rain, but delving into what followed: state failure, social abandonment, capitalization on human misery, and the collective trauma produced by the botched response.

Naturkatastrophen und ihre Bilder sind allgegenwartig; innerhalb der Kultur- und Bildwissenschaften sind jedoch bislang keine umfassenden Versuche unternommen worden, sie in einem transkulturellen Zusammenhang zu analysieren.Der Band folgt der gleichnamigen Konferenz, die der Cluster Asia and Europe 2012 an der Universitat Heidelberg veranstaltet hat, und versammelt Beitrage aus der interdisziplinaren Forschung zur Darstellung, Vermittlung und Interpretation von Katastrophen. Zugleich bildet er die wissenschaftliche Grundlage fur die Ausstellung Atlantis bis Fukushima , die 2014 in den Reiss-Engelhorn-Museen in Mannheim gezeigt wird. Die behandelten Themen reichen von Fallstudien zur historischen Bildfindung in der europaischen Renaissance bis zur Untersuchung aktueller Medienphanomene, wie der internationalen Berichterstattung der Katastrophen des 21ten Jahrhunderts.

This volume constitutes the refereed and revised post-conference proceedings of the 5th IFIP WG 5.15 International Conference on Information Technology in Disaster Risk Reduction, ITDRR 2020, in Sofia, Bulgaria, in December 2020.* The 18 full papers and 6 short papers presented were carefully reviewed and selected from 52 submissions. The papers focus on various aspects and challenges of coping with disaster risk reduction. The main topics include areas such as natural disasters, remote sensing, big data, cloud computing, Internet of Things, mobile computing, emergency management, disaster information processing, disaster risk assessment and management. *The conference was held virtually.

This new guide describes the application of spatial technology to improve disaster risk management (DRM) within the aquaculture sector. DRM requires interrelated actions and activities to ensure early warning, prevention, preparedness, response and recovery for a wide range of natural, technological and complex disasters that can impact aquaculture operations and livelihoods. Spatial technology refers to systems and tools that acquire, manage and analyse data that have geographic context. Some of the technologies include satellite remote sensing, aerial surveys, global positioning systems, geographic information systems, information and communication technology and other data gathering sensors used, for instance, in meteorology. Spatial technology supports activities across all phases of the DRM cycle and its rapid development provides enhanced opportunities to support DRM within the aquaculture sector. This guide is organized in two parts. Part one is the “guidance”; it is the main body of the document and describes the processes and steps for the use of spatial technology within DRM for aquaculture. Part two includes selected country case studies from Bangladesh, the Gulf of Mexico and the Caribbean, and Indonesia to illustrate the application of spatial technology in DRM for aquaculture at the national level within local contexts. Best practices at the farm and area management levels, supported by spatial technology, reduce volatility and risks and thus facilitate investment. Countries that would like aquaculture to grow sustainably and reliably are encouraged to use this guide in order to support spatial planning approaches and protect responsible investors. A separate summary version accompanies this publication.

G -- H -- I -- J -- K -- L -- M -- N -- O -- P -- R -- S -- T -- U -- V -- W -- Z

Geo-information technology can be of considerable use in disaster management, but with considerable challenge in integrating systems, interoperability and reliability. This book provides a broad overview of geo-information technology, software, systems needed, currently used and to be developed for disaster management. The text invites discussion on systems and requirements for use of geo-information under time and stress constraints and unfamiliar situations, environments and circumstances.

Acute events of natural origin, spanning atmospheric, biological, geophysical, hydrologic, and oceanographic realms, persistently menace societies globally. Approximately 160 million people annually bear the brunt of these disasters, with certain regions facing disproportionate impacts. The lack of predictability intensifies the challenge, creating intercommunal capacity gaps and amplifying the dire consequences. Utilizing AI and Machine Learning for Natural Disaster Management provides instances of ML in predicting earthquakes. By leveraging seismic data, AI systems can analyze magnitude and patterns, providing invaluable insights to forecast earthquake occurrences and aftershocks. Similarly, the book unveils the potential of ML in simulating floods by recording and analyzing rainfall patterns from previous years. The predictive power extends to hurricanes, where data on wind speed, rainfall, temperature, and moisture converge to anticipate future occurrences, potentially saving millions in property damage.