This study examines social disparities in U.S. K–12 school flood exposure and the distribution of federal disaster recovery aid for affected schools. Using national datasets on school locations, flood hazards, and socioeconomic characteristics, we analyze (1) the spatial patterns of schools within 100-year flood zones, and (2) factors associated with the local receipt of FEMA recovery aid for schools. Our findings reveal substantial regional variation, with flood-prone schools concentrated in the Southern and Gulf Coast states. Local geographic conditions are consistently associated with schools’ flood exposure across most states. Schools in communities with higher poverty rates and larger Hispanic populations are more likely to be located in flood zones. Regarding recovery, greater FEMA aid is allocated to schools in localities with greater damage, larger populations, and more schools in floodplains. The relationship between social factors and aid is mixed: communities with lower incomes and larger Hispanic populations receive less school aid, yet aid levels are also positively correlated with poverty rates. This study contributes to understanding school flood exposure and social equity in disaster recovery, offering insights for policymakers, urban planners, and school administrators to develop targeted mitigation strategies and promote more equitable recovery for flood-prone schools.

Landfilling wasted food (WF) is a significant source of greenhouse gas emissions. Anaerobic digestion (AD) is emerging as a promising alternative to jointly manage WF and generate bio-based energy, yet its widespread adoption is limited by transportation and operating costs. To reduce costs, AD facilities must be sited reasonably close to WF sources, energy transmission infrastructure, and available cropland for managing digestate, the liquid by-product from AD. Nutrient-rich digestate can displace synthetic fertilizer use on farms but can also runoff and create ecological risks, depending on location and application rate. Here, we introduce a multi-criteria geospatial model to assess the placement of future AD systems relative to (1) the distance over which AD feedstocks and products must be transported and (2) ecological risks created by land-application of digestate. Using Western New York State as a case study, we show that only 12% of land within the study area is suitable for siting AD systems. Further, the distance that digestate can be transported for land application is constrained to between 6 and 15 km to avoid exceeding crop nutrient demand. However, runoff modeling using the long-term hydrological impact analysis (L-THIA) tool showed that even sites with sufficient capacity to accept digestate could be sources of downstream water quality risk. This type of integrated analysis of ecological and economic constraints to AD siting is critical for sustainable food waste management strategies.

Local emergency management agencies (EMAs) are on the front line of providing essential services to protect their communities from disasters, yet their efforts often fall short in addressing the needs of populations with disabilities (PWD). Based on a nationwide survey of county government emergency managers, this paper examines organizational practices adopted by local EMAs to advance disability inclusion, identifies barriers to their implementation, and explores whether broader disability-inclusive actions correlate with enhanced deaf/hard of hearing (DHH)-specific services. We find that local EMAs report more commonly engaging in inclusion practices for PWD that align with existing planning and collaboration practices such as incorporating disability considerations into emergency planning and assessments, while other practices are largely not implemented, in part because of financial and staffing limitations. We also find that these disability-inclusive actions taken by local EMAs are strongly positively correlated with increased variety and accessibility of DHH services. Many of these DHH services focus on communication, of which there was reliance on a few common practices such as using written language. Given the range of communication needs and preferences in the DHH community, these practices may not meet the needs of some DHH persons. These findings highlight the need for targeted strategies to advance disability inclusion and enhance emergency management outcomes for PWD, particularly DHH populations.

The ongoing displacement of Ukrainian refugees into Poland highlights critical gaps in timely, data-driven hu-manitarian response. This paper presents Aegis, a visual analytics platform that integrates large language models (LLMs) to extract, structure, and analyze social media narratives in real time. A case study-based user evaluation and testing of Aegis with humanitarian professionals assessed Aegis's ability to identify service access barriers and community concerns. Results showed that Aegis reduced analytic burden, enabled rapid thematic discovery, and supported actionable insights. While users found the system intuitive and effective, they emphasized the need for improved geolocation accuracy, interface flexibility, and AI transparency. Recommendations include refining models, scaling data capacity, and deploying Aegis in live crisis settings. This work contributes to humanitarian technology by demonstrating how LLM-driven tools can enhance situational awareness and support evidence-based decision-making in forced displacement contexts.

Critical infrastructure (CI) organizations increasingly face disruptions that cascade across interdependent systems. Preparing for this fact requires thorough training, yet many existing training methods, especially tabletop exercises, are too resource-intensive, classified, or narrowly scoped to prepare diverse civilian and military stakeholders effectively. To address this gap, we introduce resilience games, a form of serious gaming with wargaming elements. First, we present the JV4.0 technical framework, the latest iteration of the U.S. Army Cyber Institute’s Jack Voltaic series, an open-source, modular architecture for creating, running, and adapting such games. Second, we demonstrate Access Denied and Sector Down as two implementations of the framework. Access Denied is an entry-level, non-technical card game focused on incident recognition and communication. Sector Down is a cross-sector game that trains CI decision-makers to sustain essential functions under cascading attrition. We describe gameplay mechanics, alignment with practitioner taxonomies (e.g., CISA lifelines, MITRE ATT&CK/ICS, D3FEND), and insights from formative playtesting across military, academic and public venues. We conclude by outlining next steps for empirical evaluation and policy integration. The aim is to provide a scalable, accessible tool to help Department of War installations and civilian communities prepare for disruptions ranging from cyberattacks to extreme weather events.

We evaluated the utility of the large language model (LLM) ChatGPT to develop situation awareness related to the forced displacement of Ukrainian refugees into Poland. Utilizing text messages derived from the Help for Ukrainians in Poland Telegram message group, we used ChatGPT to translate messages in multiple languages into English and identify message topics and themes. Topics and themes from beginning of the war in Ukraine in 2022 were analyzed and visualized using K-means clustering and word clouds. The language identification and translation capabilities of the LLM were evaluated by two human evaluators and measured using Kappa (0.86) and BLUE scores (0.46) with the LLM performing effectively. We conclude that the ability of LLM using carefully developed language prompts for large data volume analysis with no need for manual human analysis shows promise for humanitarian analytics focused on rapidly identifying potential key trends, needs, and locations of displaced people.

Household resilience to natural hazards is a critical issue facing society with the advent of climate change. In this work, we developed one of the first household natural hazard resilience geospatial models for Rwanda designed to understand household resilience at detailed spatial resolutions. We evaluated indicators within the model through empirical field work using an easy to deploy survey on Android tablets. To the best of our knowledge, the work presented here is innovative as it some of the first work to use geospatial technology-based surveys to conduct household-level natural disaster resilience surveys in Rwanda. Select results presented in this paper indicated that household vulnerabilities and subsequent resilience generally matched with existing district-level risk mapping of Rwanda. However, our work went beyond existing risk mapping to understand individual household perceptions of resilience. Respondents generally reported a mix of positive and negative drivers of household resilience. General security and economic situation was perceived as very insecure, healthcare and education were very secure, and utilities, food and water, and housing were generally perceived as insecure but not as insecure as economic situation and security. There is much more that can be understood in terms of household resilience as it relates to many factors of household resiliency in our model including physical vulnerabilities, financial capacity, information access, technological capacity, and most importantly, resilience perceptions.

Displaced populations are at the highest level since WWII with an estimated 4.5 million people living in managed refugee camps. Concurrently, natural hazards continue to escalate worldwide with new science for characterizing disaster resilience. Despite the scientific need and societal importance of research focused on linking displacement and disaster resilience, the two areas have received little attention as one interdisciplinary research topic. In this work, we address this gap by investigating the disaster resilience of displaced people. Specifically, we developed a set of natural disaster resilience indicators to evaluate their efficiency for understanding natural disaster resilience as it applies to displaced people living inside of a refugee camp. We tested these indicators with a pilot survey in the Kigeme refugee camp of Rwanda. Our results indicated that negative drivers of disaster resilience in Kigeme are primarily focused on factors related to physical risk such as erosion and landslides and economic challenges that stem from lack of access to livelihoods and business materials. Positive drivers of disaster resilience included access to healthcare, education and the camp governance structure many of the refugees themselves rely upon for both information and general support during disasters. This work presents some of the first work to directly access refugees themselves at the community-level scale to understand refugee disaster resilience.

AbstractForced displacement is inherently spatial, with aspects operating at multiple scales. At the individual scale, space shapes a survivor’s experience. At the regional scale, space mediates our understanding of global processes of forced displacement and shapes our local responses to these worldwide trends. As long as there has been forced displacement, some form of geographic mapping has been used to understand, represent, and reason about forced displacement. In modern times, mapping technology comes in the form of geospatial technologies that can range from a displaced person using Google Maps on their phone to navigate in an unfamiliar environment as they migrate from their home country, to powerful geographic information systems (GISs) that drive core operations of organizations such as United Nations High Commissioner for Refugees (UNHCR), supporting countries hosting refugees and international humanitarian operations.

Provides ideas about where to get information to complete each step in the vulnerability assessment.LOOKING AHEAD-This box denotes information or procedures that are explained further in subsequent steps.

As electric vehicle adoption increases, there is a need for strategic innovation to manage end-of-life lithium-ion batteries (LIBs). When no longer viable for vehicle use, LIBs still retain significant energy storage capacity. Enabling second-use of LIBs for stationary energy storage presents an opportunity for circular economy innovation, value retention, and sustainable management of raw materials. Second-use LIBs used for stationary back-up power can also contribute to energy resilience, disaster relief, and resource efficiency. This study analyzes a circular economy management model for LIBs by integrating three methods: Multi-criteria decision analysis is used to determine strategic locations for second-use LIB stationary deployment; geospatial analysis is used to determine efficient transportation routes from LIB consolidation points to strategic destinations; and material flow analysis estimates anticipated local availability of second-use LIBs. A case study of Berlin, Germany, is used to demonstrate the model. Results show that under business-as-usual growth, >23,000 second-use LIBs could be diverted for second-use applications by 2040, and could provide back-up power to critical infrastructure, such as emergency traffic signals, for up to 380 h during a disaster event. Under an aggressive electric vehicle adoption scenario to 2040, more than 100,600 LIBs could be diverted from waste, providing significant opportunities for post-disaster recovery using distributed energy infrastructure. This model demonstrates the potential contribution of integrated circular economy strategies to achieving both resilience and sustainability objectives.

NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Geospatial Technology in a Multidisciplinary Academic Center Because the technical evolution of the geospatial technologies has led to new and exciting approaches to problem solving in technology fields, the Center of Multidisciplinary Studies at the Rochester Institute of Technology has developed six geospatial technology courses and is currently proposing a BS degree that focuses on developing, advancing, and studying the application of geospatial technology. The Center has been the home for numerous certificate programs and BS and MS degrees in Arts and Sciences that encourage students to build personalized degree programs based on concentrations drawn from across the Institute. These geospatial technology courses are available to all university students and have been attracting students from a variety of majors. Because of the depth and breadth of geospatial applications, the design of the new BS program proposal integrates topics in Geographic Information Science as delineated in the UCGIS Book of Knowledge1 with general education, professional minors and free elective choices. In a world where computing, network access, and data sensors are ubiquitous, today’s students and researchers are already capitalizing on the abundance of raw data. The capability to effectively summarize and draw inferences to transform this raw data into useful knowledge is critical in many undergraduate curricula. The pressing global issues in today’s world that these students will face upon graduation require extensive measurements as well as the location and changes of those measurements over time. The underlying mathematics, sciences and technologies used in collecting, transforming, and communicating this data are vital components. Introduction This paper describes a proposed Bachelor of Science degree in Geospatial Technology to be offered by the Center for Multidisciplinary Studies in the College of Applied Science and Technology. This degree will educate a new generation of students who can combine spatial thinking, problem solving, and creative thinking skills with technical skills on effective use of the varied approaches to Geospatial Technologies (GTs). Achieving this combination will allow students to achieve maximum successes in their careers or research disciplines. Background technologies and the anticipated future of the field Geospatial Technologies (GTs) have evolved from initial beginnings as simple computer-based map making tools to complex visual and computational environments. GTs are used world- wide in diverse application domains ranging from community planning to the exploration of outer space. The increased use of GTs has led the development of new tools, techniques and theory that have imbued GTs with new forms of geographic visualization, support for spatial thinking, and opportunities for research and education. It is an exciting time for GT research and education. Industry standard, commercial desktop Geographic Information System (GIS) platforms such as ArcGIS2 by ESRI Inc that were once the hallmark of GTs are now being complemented by freely available virtual globe software such as Google Earth3 and NASA Worldwind4. The easy-to-use functionality of virtual globe environments provide users with rich interactivity and visualization capabilities that are allowing millions of people to develop

The capacity to utilize geographic information is a critical element of disaster risk management. Although access to and use of geographic information system (GIS) technology continues to grow, there remain significant gaps in approaches used by disaster risk management stakeholders to understand geographic information needs, sources, and information flow-ultimately limiting the efficacy of management efforts. To address this problem, we introduce the concept of geographic information capacity (GIC) to measure and analyze the ability of stakeholders to understand, access, and work with geographic information for disaster risk management. We propose a framework for assessing GIC, the GIC Profile, which we situate within a review of disaster risk management-relevant frameworks. We evaluate the GIC Profile using two case study countries at the first (sub-national) geo-administrative boundary level. Chi-square analyses suggest GIC across equivalent regional units within each country is relatively uniform, and that this uniformity is comparable between nations despite significant difference in overall capacity. Contributions of the GIC Profile to disaster risk management research are twofold. First, this is a first attempt to develop a profile based on key indicators for quantifying GIC highlights critical areas for capacity improvement, allowing decision makers to identify and prioritize pathways to strengthen disaster risk management programs. Through this initial effort, a decision tool has been developed which may enhance decisions on how to utilize GIS in support of disaster risk management. This tool is iterative and can be updated as new events occur to maximize GIS benefits, ultimately reducing disaster risks and their potential consequences.

Novel engineered nanomaterials (ENMs) are increasingly being manufactured and integrated into renewable energy generation and storage technologies. Past research estimated the potential impact of this increased demand on environmental systems, due to both the life cycle impact of ENM production and the potential for their direct release into ecosystems. However, many models treat ENM production and use as spatially implicit, without considering the specific geographic location of potential emissions. By not considering geographical context, ENM accumulation or impact may be underestimated. Here, we introduce an integrated predictive model that forecasts likely ENM manufacturing locations and potential emissions to the environment, with a focus on critical environmental areas and freshwater ecosystems. Spatially explicit ENM concentrations are estimated for four case study ENMs that have promising application in lithium‐ion battery production. Results demonstrate that potential ENM exposure from manufacturing locations within buffer zones of sensitive ecosystems would accumulate to levels associated with measured ecotoxicity risk under high release scenarios, underscoring the importance of adding a spatial and temporal perspective to life cycle toxicity impact assessment. This predictive integrated modeling approach is novel to the nanomaterial literature and can be adapted to other regions and material case studies to proactively inform life cycle tradeoffs and decision‐making.

The chapter presents the geographic information systems. A geographic information system (GIS) is a computer system that allows various sources to gather and organize, manage, analyze and combine, develop, and present geographically located information contributing in particular to the management from space. A geographic information system is also a database management system for entering, storing, retrieving, querying, analyzing, and displaying localized data. It is a set of data located in space, structured so that it can conveniently extract syntheses useful to the decision.

The chapter presents the geographic information systems. A geographic information system (GIS) is a computer system that allows various sources to gather and organize, manage, analyze and combine, develop, and present geographically located information contributing in particular to the management from space. A geographic information system is also a database management system for entering, storing, retrieving, querying, analyzing, and displaying localized data. It is a set of data located in space, structured so that it can conveniently extract syntheses useful to the decision.