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Urban areas are dynamic systems, in which different infrastructural, social and economic subsystems continuously co-evolve. As such, disruptions in one system can propagate to another. However, open challenges remain in (i) assessing the long-term implications of change for resilience and (ii) understanding how resilience propagates throughout urban systems over time. Despite the increasing reliance on data in smart cities, few studies empirically investigate long-term urban co-evolution using data-driven methods, leading to a gap in urban resilience assessments. This paper presents an approach that combines Getis-ord Gi* statistical and correlation analyses to investigate how cities recover from crises and adapt by analysing how the spatial patterns of urban characteristics and their relationships changed over time. We illustrate our approach through a study on Helsinki’s road infrastructure, socioeconomic system and built-up area from 1991 to 2016, a period marked by a major socioeconomic crisis. By analysing this case study, we provide insights into the co-evolution over more than two decades, thereby addressing the lack of longitudinal studies on urban resilience., Transport and Logistics, System Engineering

Increasingly, our cities are confronted with crises. Fuelled by climate change and a loss of biodiversity, increasing inequalities and fragmentation, challenges range from social unrest and outbursts of violence to heatwaves, torrential rainfall, or epidemics. As crises require rapid interventions that overwhelm human decision-making capacity, AI has been portrayed as a potential avenue to support or even automate decision-making. In this paper, I analyse the specific challenges of AI in urban crisis management as an example and test case for many super wicked decision problems. These super wicked problems are characterised by a coincidence of great complexity and urgency. I will argue that from this combination, specific challenges arise that are only partially covered in the current guidelines and standards around trustworthy or human-centered AI. By following a decision-centric perspective, I argue that to solve urgent crisis problems, the context, capacities, and networks need to be addressed. AI for crisis response needs to follow dedicated design principles that ensure (i) human control in complex social networks, where many humans interact with AI; (ii) principled design that considers core principles of crisis response such as solidarity and humanity; (iii) designing for the most vulnerable. As such this paper is meant to inspire researchers, AI developers and practitioners in the space of AI for (urban) crisis response – and other urgent and complex problems that urban planners are confronted with., Transport and Logistics

Increasing frequency of climate-related disruptions requires transformational responses over the lifecycles of interconnected urban systems with short- and long-term change dynamics. However, the aftermath of disruptions is often characterised by short-sighted decision-making, neglecting long-term urban shifts. In this study, we present a first attempt to develop the theoretical foundation for temporal dynamics for increasingly disrupted yet ”connecting and moving” cities that can be used in planning for urban resilience. Using the lens of climate urbanism, we conceptualise the interplay of temporal dynamics to empirically examine how planning practice perceives and addresses temporality in two regions - Amsterdam, the Netherlands, and Mumbai, India. Our findings reinforce that disruptions do not inform long-term planning. Endogenous and exogenous dynamics of change are not viewed together nor used to embed short-term planning goals within long-term resilience visions. To address the lack of systematic planning approaches that can leverage temporal dynamics, we propose two options for temporally flexible urban planning processes., System Engineering, Transport and Logistics

BACKGROUND: Prompted by recent shocks and stresses to health systems globally, various studies have emerged on health system resilience. Our aim is to describe how health system resilience is operationalised within empirical studies and previous reviews. We compare these to the core conceptualisations and characteristics of resilience in a broader set of domains (specifically, engineering, socio-ecological, organisational and community resilience concepts), and trace the different schools, concepts and applications of resilience across the health literature. METHODS: We searched the Pubmed database for concepts related to 'resilience' and 'health systems'. Two separate analyses were conducted for included studies: a total of n = 87 empirical studies on health system resilience were characterised according to part of health systems covered, type of threat, resilience phase, resilience paradigm, and approaches to building resilience; and a total of n = 30 reviews received full-text review and characterised according to type of review, resilience concepts identified in the review, and theoretical framework or underlying resilience conceptualisation. RESULTS: The intersection of health and resilience clearly has gained importance in the academic discourse with most papers published since 2018 in a variety of journals and in response to external threats, or in reference to more frequent hospital crisis management. Most studies focus on either resilience of health systems generally (and thereby responding to an external shock or stress), or on resilience within hospitals (and thereby to regular shocks and operations). Less attention has been given to community-based and primary care, whether formal or informal. While most publications do not make the research paradigm explicit, 'resilience engineering' is the most prominent one, followed by 'community resilience' and 'organisational resilience'. The social-ecological systems roots of resilience find the least applicati, Ethics & Philosophy of Technology, Policy Analysis, Transport and Logistics

Involuntary displacement from conflict and other causes leads to clustering of refugees and internally displaced people, often in long-term settlements. Within refugee-hosting countries, refugee settlements are frequently located in isolated and remote areas, characterized by poor-quality land and harsh climatic conditions. Yet, the exposure of refugee settlements to climatic events is underresearched. In this article, we study the exposure of the 20 largest refugee settlements worldwide to extreme variations in climatic conditions. The analysis integrates exposure of camp locations compared to the national trends for both slow- and rapid-onset events and includes descriptive statistics, signal-to-noise analyses, and trend analyses. Our findings show that most refugee settlements included face relatively high exposure to slow-onset events, including high temperatures (for settlements in Kenya, Ethiopia, Rwanda, Sudan, and Uganda), low temperatures (in the case of Jordan and Pakistan), and low levels of rainfall (in Ethiopia, Rwanda, Kenya, and Uganda) compared to national averages. Our findings for rapid-onset events-heatwaves, coldwaves, and extreme rainfall-are less conclusive compared to country trends, although we find relatively high exposure to extreme rainfall in Cox's Bazar, Bangladesh. Our analyses confirm that refugee populations are exposed to extreme weather conditions postdisplacement, which, in combination with their sociopolitical exclusion, poses a threat to well-being and increased marginalization. Our findings call for an inclusive and integrated approach, including refugees and their host communities, in designing climate adaptation and sustainable development policies, in order to promote equitable sustainable development pathways in refugee-hosting countries., Transport and Logistics

Climate change is one of the main drivers of uncertainty in urban planning, but only a few studies systematically address these uncertainties, especially in the long term. Urban resilience theory presents principles to manage uncertainty but largely focuses on individual urban systems rather than complex interdependent dynamics. Further, most planning and resilience theory originates from the Global North and is unsuitable for capturing the dynamics of the Global South. This study uses an exploratory multi-case analysis towards developing an enhanced understanding of urban planning for climate uncertainty. We argue that long-term urban planning for climate uncertainty can benefit from systematically integrating resilience principles. We use a two-step qualitative research approach: (1) To propose a conceptual framework connecting urban resilience principles, approaches to urban planning under uncertainty and planning responses in urban systems. (2) To use the conceptual framework to analyse climate-related planning responses in two contrasting case studies in the Global North (GN) and Global South (GS) (Amsterdam and Mumbai). We conclude with four propositions towards an enhanced understanding of urban planning for climate uncertainty by drawing upon the empirical insights from the two case studies., System Engineering, Transport and Logistics

Evaluation and testing are significant steps in developing any information system. More attention must be devoted to these steps if the system is to be used in high-risk contexts, such as the response to conflict disasters. Several testing methodologies are designed to guarantee that software fulfills technology requirements; others will assure usability and usefulness. However, there is currently no integrated evaluation framework with agreed standards that bring together the three elements: technology requirements, usability, and usefulness. This gap constitutes a barrier to innovation and imposes risks to responders or affected populations if the technology is introduced without proper testing. This chapter aims to close this gap. Based on a review of evaluation methods and measurement metrics for information systems, we designed an integrated evaluation framework including standard metrics for code quality testing, usability methods, subjective usefulness questionnaires, and key performance indicators. We developed and implemented a reporting and evaluation system that demonstrates our evaluation framework within the context of the EU H2020 project iTRACK. iTRACK developed an integrated system for the safety and security of humanitarian missions. We demonstrate how our approach allows measuring the quality and usefulness of the iTRACK integrated system., Transport and Logistics

Policy Analysis, Transport and Logistics

Qualitative research is a powerful means to capture human interactions and behavior. Although there are different methodologies to develop models based on qualitative research, a methodology is missing that enables to strike a balance between the comparability across cases provided by methodologies that rely on a common and context-independent framework and the flexibility to study any policy problem provided by methodologies that focus on capturing a case study without relying on a common framework. Additionally, a rigorous methodology is missing that enables the development of both theoretical and empirical models for supporting policy formulation and evaluation with respect to a specific policy problem. In this article, the authors propose a methodology targeting these gaps for ABMs in two stages. First, a novel conceptual framework centered on a particular policy problem is developed based on existing theories and qualitative insights from one or more case studies. Second, empirical or theoretical ABMs are developed based on the conceptual framework and generic models. This methodology is illustrated by an example application for disaster information management in Jakarta, resulting in an empirical descriptive agent-based model., System Engineering, Transport and Logistics

Covid-19 has dramatically changed life in cities across the globe. What remains uncertain is how national policies and appeals to comply with suggested rules translate to changes in the behaviour of citizens in urban areas. This lack of local knowledge leaves urban policy makers and planners with few clues as to the determinants of social resilience in cities during protracted crises like a pandemic. Methods are required to measure the capacity of people to conduct routine activities without risking exposure to a prevalent disease, particularly for those most vulnerable during a health crisis. By spanning the fields of urban resilience, human geography, mobility studies and the behavioural sciences, this study explores how to measure social resilience in cities during a protracted crisis. Using a public participation GIS online platform, we observe changes in citizen behaviour within urban spaces during the Covid-19 pandemic. Inhabitants from three districts of a Dutch city mapped their activity routines during the lockdown period and during the year before the pandemic. Spatio-temporal analysis reveals changes in the clustering of activities into what we describe as ‘activity bubbles'. We reflect on the influence of the urban space on these changes and assess the contribution of this exploratory research methodology for gaining insights into behavioural change. Implications for urban planning and resilience theory are discussed., Design Conceptualization and Communication, Technology, Policy and Management, Transport and Logistics

Droughts and changing rainfall patterns due to natural climate variability and climate change, threaten the livelihoods of Malawi's smallholder farmers, who constitute 80% of the population. Provision of seasonal climate forecasts (SCFs) is one means to potentially increase the resilience of rainfed farming to drought by informing farmers in their agricultural decisions. Local knowledge can play an important role in improving the value of SCFs, by making the forecast better-suited to the local environment and decision-making. This study explores whether the contextual relevance of the information provided in SCFs can be improved through the integration of farmers’ local knowledge in three districts in central and southern Malawi. A forecast threshold model is established that uses meteorological indicators before the rainy season as predictors of dry conditions during that season. Local knowledge informs our selection of the meteorological indicators as potential predictors. Verification of forecasts made with this model shows that meteorological indicators based on local knowledge have a predictive value for forecasting dry conditions in the rainy season. The forecast skill differs per location, with increased skill in the Southern Highlands climate zone. In addition, the local knowledge indicators show increased predictive value in forecasting locally relevant dry conditions, in comparison to the currently-used El Niño-Southern Oscillation (ENSO) indicators. We argue that the inclusion of local knowledge in the current drought information system of Malawi may improve the SCFs for farmers. We show that it is possible to capture local knowledge using observed station and climate reanalysis data. Our approach could benefit National Meteorological and Hydrological Services in the development of relevant climate services and support drought-risk reduction by humanitarian actors., Water Resources, Transport and Logistics, System Engineering

The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world's most vulnerable populations at risk. Epidemiological modelling is vital to guiding evidence-informed or data-driven decision making. In forced displacement contexts, and in particular refugee and internally displaced people (IDP) settlements, it meets several challenges including data availability and quality, the applicability of existing models to those contexts, the accurate modelling of cultural differences or specificities of those operational settings, the communication of results and uncertainties, as well as the alignment of strategic goals between diverse partners in complex situations. In this paper, we systematically review the limited epidemiological modelling work applied to refugee and IDP settlements so far, and discuss challenges and identify lessons learnt from the process. With the likelihood of disease outbreaks expected to increase in the future as more people are displaced due to conflict and climate change, we call for the development of more approaches and models specifically designed to include the unique features and populations of refugee and IDP settlements. To strengthen collaboration between the modelling and the humanitarian public health communities, we propose a roadmap to encourage the development of systems and frameworks to share needs, build tools and coordinate responses in an efficient and scalable manner, both for this pandemic and for future outbreaks., Transport and Logistics, System Engineering

Humanitarian crises, such as the 2014 West Africa Ebola epidemic, challenge information management and thereby threaten the digital resilience of the responding organizations. Crisis information management (CIM) is characterised by the urgency to respond despite the uncertainty of the situation. Coupled with high stakes, limited resources and a high cognitive load, crises are prone to induce biases in the data and the cognitive processes of analysts and decision-makers. When biases remain undetected and untreated in CIM, they may lead to decisions based on biased information, increasing the risk of an inefficient response. Literature suggests that crisis response needs to address the initial uncertainty and possible biases by adapting to new and better information as it becomes available. However, we know little about whether adaptive approaches mitigate the interplay of data and cognitive biases. We investigated this question in an exploratory, three-stage experiment on epidemic response. Our participants were experienced practitioners in the fields of crisis decision-making and information analysis. We found that analysts fail to successfully debias data, even when biases are detected, and that this failure can be attributed to undervaluing debiasing efforts in favor of rapid results. This failure leads to the development of biased information products that are conveyed to decision-makers, who consequently make decisions based on biased information. Confirmation bias reinforces the reliance on conclusions reached with biased data, leading to a vicious cycle, in which biased assumptions remain uncorrected. We suggest mindful debiasing as a possible counter-strategy against these bias effects in CIM., Multi Actor Systems, Organisation and Governance, Policy Analysis, Transport and Logistics, System Engineering

The challenges for sustainable cities to protect the environment, ensure economic growth, and maintain social justice have been widely recognized. Along with the digitization, availability of large datasets, Machine Learning (ML) and Artificial Intelligence (AI) are promising to revolutionize the way we analyze and plan urban areas, opening new opportunities for the sustainable city agenda. Especially urban spatial planning problems can benefit from ML approaches, leading to an increasing number of ML publications across different domains. What is missing is an overview of the most prominent domains in spatial urban ML along with a mapping of specific applied approaches. This paper aims to address this gap and guide researchers in the field of urban science and spatial data analysis to the most used methods and unexplored research gaps. We present a scoping review of ML studies that used geospatial data to analyze urban areas. Our review focuses on revealing the most prominent topics, data sources, ML methods and approaches to parameter selection. Furthermore, we determine the most prominent patterns and challenges in the use of ML. Through our analysis, we identify knowledge gaps in ML methods for spatial data science and data specifications to guide future research., Funding Information: This work was supported by the Delft University of Technology (TU Delft). Publisher Copyright: © 2022 The Author(s), Transport and Logistics, System Engineering

The growing need for humanitarian assistance has inspired an increasing amount of academic publications in the field of humanitarian logistics. Over the past two decades, the humanitarian logistics literature has developed a powerful toolbox of standardized problem formulations to address problems ranging from distribution to scheduling or locations planning. At the same time, the humanitarian field is quickly evolving, and problem formulations heavily rely on the context, leading to calls for more evidence-based research. While mixed methods research designs provide a promising avenue to embed research in the reality of the field, there is a lack of rigorous mixed methods research designs tailored to translating field findings into relevant HL optimization models. In this paper, we set out to address this gap by providing a systematic mixed methods research design for HL problem in disasters response. The methodology includes eight steps taking into account specifics of humanitarian disasters. We illustrate our methodology by applying it to the 2015 Nepal earthquake response, resulting in two evidence-based HL optimization models., System Engineering, Transport and Logistics

Purpose: The coronavirus disease (COVID-19) pandemic has emerged as an unprecedented health crisis worldwide and heavily disrupted the healthcare supply chain. This study focuses on analysing the different types of disruptions occurring in personal protective equipment (PPE) supply chains during the COVID-19 pandemic and on proposing mitigation strategies that are fit to the global scale and many interdependencies that are characteristic for this pandemic. The authors construct a conceptual system dynamics model (SD) based on the literature and adjusted with the use of empirical data (interviews) to capture the complexity of a global supply chain and identify leverage points (mitigation strategies). Design/methodology/approach: This research follows a mix-methods approach. First, the authors developed a conceptual framework based on four types of disruptions that usually occur during health emergencies (direct effect, policy, supply chain strategy, and behaviourally induced disruptions). Second, the authors collected and analysed data from interviews with experts in the PPE supply chain. Based on the interviews data, the authors developed a conceptual system dynamics (SD) model that allows to capture the complex and dynamic interplay between the elements of the global supply chain system, by highlighting key feedback loops, delays, and the way the mitigation strategies can impact on them. From this analysis, the authors developed four propositions for supply chain risk management (SCRM) in global health emergencies and four recommendations for the policy and decision makers. Findings: The SD model highlights that without a combination of mitigation measures, it is impossible to overcome all disruptions. As such, a co-ordinated effort across the different countries and sectors that experience the disruptions is needed. The SD model also shows that there are important feedback loops, by which initial disruptions create delays and shortages that propagate through the s, Transport and Logistics, System Engineering

Agent-based models (ABM) for policy design need to be grounded in empirical data. While many ABMs rely on quantitative data such as surveys, much empirical research in the social sciences is based on qualitative research methods such as interviews or observations that are hard to translate into a set of quantitative rules, leading to a gap in the phenomena that ABM can explain. As such, there is a lack of a clear methodology to systematically develop ABMs for policy design on the basis of qualitative empirical research. In this paper, a two-stage methodology is proposed that takes an exploratory approach to the development of ABMs in socio-technical systems based on qualitative data. First, a conceptual framework centered on a particular policy design problem is developed based on empirical insights from one or more case studies. Second, the framework is used to guide the development of an ABM. This step is sensitive to the purpose of the model, which can be theoretical or empirical. The proposed methodology is illustrated by an application for disaster information management in Jakarta, resulting in an empirical descriptive ABM., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., System Engineering, Transport and Logistics

The evidence review report from SAPEA presents the latest scientific evidence on the subject of crisis management, and evidence-based policy options for action. The European Union is confronted with an increasing number of crises with growing complexity. Their effects can cascade and ripple to all parts of society, the economy, and the environment. The effects of such crises are not limited to specific geographical regions or sectors of society, and many crises continue indefinitely. Because they last, they overlap and amplify each other. Decisions made during crises are not only urgent, but have long-lasting consequences. Therefore, strategic crisis management needs to be aligned with broader policy objectives. Using digital tools, guidance and standards can be set for strategic foresight and risk monitoring, to ensure that a longer-term perspective is integrated. Better data preparedness can ensure that information can be shared effectively while respecting privacy and security when a crisis hits. To address the growing complexity of crises, we need a vision that integrates both risk management and crisis management. Different activities and organisations also need to coordinate: responses on multiple geographical and temporal scales need to be aligned, rather than aiming at the one ‘right’ level. Here, the EU could play an important coordinating role. The EU can also play a role in training decision- and policy-makers to coordinate and manage crises. Crises amplify existing inequalities, hitting the most vulnerable the hardest — and this can erode trust across society at exactly the time when trust is most needed. New technologies and forms of communication offer ways for citizens to be engaged and empowered. Involving civil society can bring many advantages, producing a better informed, tailored, and localised response., Transport and Logistics

To prevent floods from becoming disasters, social vulnerability must be integrated into flood risk management. We advocate that the welfare of different societal groups should be included by adding recovery capacity, impacts of beyond-design events, and distributional impacts., Ethics & Philosophy of Technology, Hydraulic Structures and Flood Risk, Transport and Logistics

To adapt to a changing climate, decision-makers design, evaluate, and implement measures that have an implication of justice on citizens in the present and well into the future. Decision-makers are often required to make decisions without certainty of the consequences and understanding their effects on intergenerational justice. Thus, managing the impacts of climate change requires novel decision-aiding approaches that consider climate impacts’ temporal and spatial heterogeneity and the uncertainty in climate predictions, preferences, and values. We reviewed the literature on the extent to which principles of intergenerational justice—conservation of options and resources for future generations—have been integrated to traditional approaches in climate resilience decision-making. We explore the extent to which flexibility, i.e., the conservation and expansion of options in subsequent decision periods, can contribute to upholding the principles of intergenerational justice under uncertainty. We illustrate the approach in the case of the Delta Programme in the Netherlands, a complex system designed to protect against sea-level rise (SLR). Designing adaptation strategies to SLR with flexibility as a core concept brings significant advantages in circumstances of uncertainty. The conservation of options in flexible pathways, in this case, contributes to the principles of intergenerational justice. Our civilization’s long-term sustainability and survival may depend on the extent to which individuals can see beyond their gains and toward the gains of the collective society at an intergenerational scale., Transport and Logistics, Values Technology and Innovation, Ethics & Philosophy of Technology, Policy Analysis, Multi Actor Systems, System Engineering

Cities are complex socio-technical systems (STSs) under tremendous stress due to climate change. To incorporate resilience into urban plans and move towards evidence-based long-term decision-making, we must unravel complex land-use dynamics and the effect of climate uncertainties on cities. Currently, land-use dynamics are explored through Cellular Automata models to investigate the impacts of urban planning scenarios. What is, however, missing to support resilience decisions, is a systematic analysis of long-term climate uncertainties on land-use change. This study addresses this gap by analysing the effects of flood uncertainties on land-use patterns. While conventionally, urban planning decisions for climate uncertainty are based on a few scenarios, we use exploratory modeling to sample and combine uncertain climate variables to scenarios and understand the implications of the climate scenarios on land use via computational experiments. Specifically, we integrate flood probability maps into land-use maps to assess land suitability. Agglomerative clustering allows us to analyze the resulting land-use maps based on their similarity. Finally, we select representative maps from each cluster and compare them with the baseline map. We apply our integrated modeling approach in the Metropolitan Region of Amsterdam (MRA). Our results show spatially explicit alternatives for high-density residential development that is climate-resilient. The proposed framework can be applied to other cities to investigate the long-term impacts of climate uncertainties and adopt resilience-informed decision-making., System Engineering, Transport and Logistics

During infectious disease outbreaks, early warning is crucial to prevent and control the further spread of the disease. While the different waves of the Covid-19 pandemic have demonstrated the need for continued compliance, little is known about the impact of warning messages and risk perception on individual behavior in public health emergencies. To address this gap, this paper uses data from the second wave of Covid-19 in China to analyse how warning information influences preventive behavior through four categories risk perception and information interaction. Drawing on the protective action decision model (PADM) and the social amplification of risk framework (SARF), risk warning information (content, channel, and type), risk perception (threat perception, hazard- and resource-related preparedness behavior perception and stakeholder perception), information interaction, and preparedness behavior intention are integrated into a comprehensive model. To test our model, we run a survey with 724 residents in Northern China. The results show that hazard-related preparedness behavior perception and stakeholder perception act as mediators between warning and preventive action. Stakeholder perception had much stronger mediating effects than the hazard-related attributes. In addition, information interaction is effective in increasing all categories risk perception, stimulating public response, while functioning as a mediator for warning. The risk warning information content, channel, and type are identified as key drivers of risk perception. The research found that information channel was more related to different risk perception than other characteristics. Overall, these associations in our model explain core mechanisms behind compliance and allow policy-makers to gain new insights into preventive risk communication in public health emergencies., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport and Logistics, System Engineering

This paper focuses on the particular power of storytelling to foster reflection and connections between people in urban life. In fact, the core principles and mechanisms for public storytelling to achieve this have yet to be made explicit. This gap is addressed by introducing a novel reflective storytelling framework that unveils the underlying principles of fostering reflection and connection through public storytelling. The framework is proposed on the basis of the literature and its appropriateness is explored in a case study in the Hague (the Netherlands) with particular focus on the influence of content and form on successfully orchestrating reflective storytelling. The impact of citizen stories on the creation of new and stronger social ties, as well as challenges, tensions, and opportunities are discussed. These results inform researchers, urban planners, and other city practitioners on how to design effective storytelling initiatives to strengthen ties in urban communities., System Engineering, Transport and Logistics

Along with climate change, more frequent extreme events, such as flooding and tropical cyclones, threaten the livelihoods and wellbeing of poor and vulnerable populations. One of the most immediate needs of people affected by a disaster is finding shelter. While the proliferation of data on disasters is already helping to save lives, identifying damages in buildings, assessing shelter needs, and finding appropriate places to establish emergency shelters or settlements require a wide range of data to be combined rapidly. To address this gap and make a headway in comprehensive assessments, this paper proposes a machine learning workflow that aims to fuse and rapidly analyse multimodal data. This workflow is built around open and online data to ensure scalability and broad accessibility. Based on a database of 19 characteristics for more than 200 disasters worldwide, a fusion approach at the decision level was used. This technique allows the collected multimodal data to share a common semantic space that facilitates the prediction of individual variables. Each fused numerical vector was fed into an unsupervised clustering algorithm called Self-Organizing-Maps (SOM). The trained SOM serves as a predictor for future cases, allowing predicting consequences such as total deaths, total people affected, and total damage, and provides specific recommendations for assessments in the shelter and housing sector. To achieve such prediction, a satellite image from before the disaster and the geographic and demographic conditions are shown to the trained model, which achieved a prediction accuracy of 62%, Transport and Logistics

Information and communication technologies (ICT), including artificial intelligence, internet of things, and mobile applications, can be utilized to tackle important societal challenges, such as the ongoing COVID-19 pandemic. While they may increase societal resilience, their design, functionality, and underlying infrastructures must be resilient against disruptions caused by anthropogenic, natural and hybrid crises, emergencies, and threats. In order to research challenges, designs, and potentials of interactive technologies, the second iteration of the workshop investigates the space of mobile technologies and resilient systems for crisis response, including the application domains of cyber threat and pandemic response., Transport and Logistics

The Covid19 crisis has highlighted once more that socio-economic inequalities are a main driver of vulnerability. Especially in densely populated urban areas, however, these inequalities can drastically change even within neighbourhoods. To better prepare for urban crises, more granular techniques are needed to assess these vulnerabilities, and identify the main drivers that exacerbate inequality. Machine learning techniques enable us to extract this information from spatially geo-located datasets. In this paper, we present a prototypical study on how Principal Component Analysis (PCA) to analyse the distribution of labour and residential characteristics in the urban area of Helsinki, Finland. The main goals are twofold: 1) identify patterns of socio-economic activities, and 2) study spatial inequalities. Our analyses use a grid of 250x250 meters that covers the whole city of Helsinki, thereby providing a higher granularity than the neighbourhood-scale. The study yields four main findings. First, the descriptive statistical analysis detects inequalities in the labour and residential distributions. Second, relationships between the socio-economic variables exist in the geographic space. Third, the first two Principal Components (PCs) can extract most of the information about the socio-economic dataset. Fourth, the spatial analyses of the PCs identify differences between the Eastern and Western areas of Helsinki, which persist since the 1990s. Future studies will include further datasets related to the distribution of urban services and socio-technical indicators., Transport and Logistics, System Engineering

Blockchain technology promises to improve the efficiency, transparency, and accountability of humanitarian operations. Yet at the same time, especially the humanitarian context with its characteristic volatility poses unique challenges to any technology. Most prominent are the humanitarian principles that are fundamental to humanitarian operations. These ethical principles are set to protect the most vulnerable populations. Designing blockchain projects in the humanitarian context therefore requires a systematic framework that helps humanitarians make critical choices. While some design instructions can be found for commercial applications, the humanitarian context requires different design principles and guidelines. To address the lack of a design framework for humanitarian blockchain projects, in this paper, we design and validate guidelines for humanitarian blockchain-projects. We use data from two humanitarian blockchain pilots in Jordan and Kenya to design our framework. Thereafter, we benchmark its applicability and relevance against another pilot in Vanuatu. Our framework highlights the need to consider infrastructure, end-users, ethics, stakeholders, and privacy in contexts, scalability and in/out mechanisms in technology, and knowledge/skills and intellectual property in organisation-related design requirements., Transport and Logistics

More than any other facet of resilience, social resilience raises the inherent tension within the concept between identity or persistence, and transformation. Is a community the people who make it up, or the geography or physical infrastructure they share? What about the resilience of communities that transform, as a result of a sudden disaster or over time? In this paper, we explore the impact of this tension on how social resilience indicators can be developed and used. Beginning with a close look at the ways in which our concepts of resilience and our use of indicators interact, several points are raised. First, that how we identify a community and frame its resilience conveys particular conceptualisations of resilience, which in turn have normative implications for the communities themselves. In part, this is because of the difficulty in capturing important adaptations and transformative actions within and by those communities. Further, measuring and comparing the resilience of communities, and aspects of quantification that go along with selecting, aggregating and comparing indicator values, ensure that the decisions made about how indicators ought to be used carry normative weight. Through this exploration, we identify several normative implications of choices in indicator design and application. We conclude with recommendations for moving forward with greater transparency and responsibility toward those communities whose social resilience we hope to measure in order to improve., Ethics & Philosophy of Technology, System Engineering, Transport and Logistics

Traditionally, disaster management information systems have been designed to facilitate communication and coordination along stable hierarchical lines and roles. However, to support coordination in disaster response, disaster management information systems need to cater for the emerging roles, responsibilities and information needs of the actors, often referred to as self-organization. To address this challenge, this paper proposes a framework for disaster management information systems that embraces an actor-centered perspective to explicitly support coordination and self-organization. The framework is designed and validated to (i) analyze the current practice of disaster information management, including the way changes occur through self-organization, and (ii) study how to design disaster management information systems that support coordination and self-organization within the current practice. A case study in Jakarta is used to modify and validate the framework, and to illustrate its potential to capture self-organization in practice. The analysis showed that analyzing the actors’ activities through the framework can provide insights on the way self-organization occurs. Moreover, networking, preparedness and centralization were found to be key elements in the design of disaster management information systems with an actor-centered perspective., System Engineering, Transport and Logistics, Policy Analysis

Humanitarian disasters are highly dynamic and uncertain. The shifting situation, volatility of information, and the emergence of decision processes and coordination structures require humanitarian organizations to continuously adapt their operations. In this study, we aim to make headway in understanding adaptive decision-making in a dynamic interplay between changing situation, volatile information, and emerging coordination structures. Starting from theories of sensemaking, coordination, and decision-making, we present two case studies that represent the response to two different humanitarian disasters: Typhoon Haiyan in the Philippines, and the Syria Crisis, one of the most prominent ongoing conflicts. For both, we highlight how volatile information and the urge to respond via sensemaking lead to fragmentation and misalignment of emergent coordination structures and decisions, which, in turn, slow down adaptation. Based on the case studies, we derive propositions and the need to continuously align laterally between different regions and hierarchically between operational and strategic levels to avoid persistence of coordination-information bubbles. We discuss the implications of our findings for the development of methods and theory to ensure that humanitarian operations management captures the critical role of information as a driver of emergent coordination and adaptive decisions., System Engineering, Transport and Logistics, Policy Analysis