Transformative disaster resilience in times of climate change underscores the importance of reflexive governance, facilitation of socio-technical advancement, co-creation of knowledge, and innovative and bottom-up approaches. However, implementing these capacity-building processes by relying on census-based datasets and nomothetic (or top-down) approaches remains challenging for many jurisdictions. Web 2.0 knowledge sharing via online social networks, whereas, provides a unique opportunity and valuable data sources to complement existing approaches, understand dynamics within large communities of individuals, and incorporate collective intelligence into disaster resilience studies. Using Twitter data (passive crowdsourcing) and an online survey, this study draws on the wisdom of crowds and public judgment in near-real-time disaster phases when the flood disaster hit Germany in July 2021. Latent Dirichlet Allocation, an unsupervised machine learning technique for Topic Modeling, was applied to the corpora of two data sources to identify topics associated with different disaster phases. In addition to semantic (textual) analysis, spatiotemporal patterns of online disaster communication were analyzed to determine the contribution patterns associated with the affected areas. Finally, the extracted topics discussed online were compiled into five themes related to disaster resilience capacities (preventive, anticipative, absorptive, adaptive, and transformative). The near-real-time collective sensing approach reflected optimized diversity and a spectrum of people’s experiences and knowledge regarding flooding disasters and highlighted communities’ sociocultural characteristics. This bottom-up approach could be an innovative alternative to traditional participatory techniques of organizing meetings and workshops for situational analysis and timely unfolding of such events at a fraction of the cost to inform disaster resilience initiatives.

Resilience in the urban context can be described as a continuum of absorptive, adaptive, and transformative capacities. The need to move toward a sustainable future and bounce forward after any disruption has led recent urban resilience initiatives to engage with the concept of transformative resilience when and where conventional and top-down resilience initiatives are less likely to deliver effective strategies, plans, and implementable actions. Transformative resilience pathways emphasize the importance of reflexive governance, inclusive co-creation of knowledge, innovative and collaborative learning, and self-organizing processes. To support these transformative pathways, considering techno-social co-evolution and digital transformation, using new data sources such as Volunteered Geographic Information (VGI) and crowdsourcing are being promoted. However, a literature review on VGI and transformative resilience reveals that a comprehensive understanding of the complexities and capacities of utilizing VGI for transformative resilience is lacking. Therefore, based on a qualitative content analysis of available resources, this paper explores the key aspects of using VGI for transformative resilience and proposes a comprehensive framework structured around the identified legal, institutional, social, economic, and technical aspects to formalize the process of adopting VGI in transformative resilience initiatives.

The concept of community disaster resilience is an increasingly important discourse on environmental changes and has been under debate on international academic and policy circles over the past decade. While conceptualizing disaster resilience is increasingly seen as a significant and requisite undertaking in hazard mitigation, reduction, and planning, there exist only a few number of frameworks in the literature presenting systematic methodology and guideline for empirical measurement of the concept. In addition, the question of whether such a measurement can adequately address the ongoing or emerging needs of local stakeholders and governments remains in agenda. To tackle this challenge, this study first intends to synthesis the needs of local stakeholders in community resilience measurement to serve both as a shared vison of resilience measurement missions and as a basis for developing a technical procedure for operationalizing community disaster resilience. Next, based on the defined needs, we propose a synthesized procedure that highlights how the needs of local stakeholders can be translated in measurement process. Finally, the developed framework is applied in order to perform a quality assessment of the 10 most well-known and related measurement frameworks. This synthesized approach, therefore, can bridge the gap between the visions and actions in resilience measurement and provide a measurement that is need-based, proactive rather than reactive, and action-oriented. Furthermore, it can predispose local stakeholders, leaders, and planners to prioritize those actions that are needed more to build and sustain resilience. The quality assessment demonstrates in-depth information regarding the characteristics of each measurement framework, which can be used to identify weaknesses and limitations of current disaster resilience measures and to improve them where needed, in order to meet the risk preparation and planning needs of stakeholders, decision makers, and urban planners.

Urban areas face multifaceted challenges such as climate change, rapid urbanization, aging infrastructure, and social inequality. Urban digital twins (UDTs) as virtual replicas of physical urban systems have emerged as pivotal tools in addressing these challenges through enabling real-time monitoring, data-driven modeling, and anticipatory planning. However, the effective deployment and institutionalization of UDTs remain an issue in practice. Therefore, this chapter conceptualizes UDT governance and identifies five central principles: data stewardship, algorithmic oversight, participatory access, institutional intelligence, and regulatory compliance. It presents examples from cities worldwide and introduces a three-tiered governance structure (strategic, tactical, and operational) and outlines implementation strategies for integrating digital twin into urban decision-making. In particular, a case study of apply digital twins for flood management in Victoria, Australia is presented. Emphasis is placed on participatory governance, scenario-based planning, and institutional adaptability to align digital twin applications with long-term urban transformation goals. Finally, the chapter advocates aligning UDT governance with post-2030 agendas to support sustainable and resilient urban futures.