Perspectives on flood forecast-based early action and opportunities for Earth observations

Nauman, Claire; Anderson, Eric; Pérez, Erin Coughlan de; Kruczkiewicz, Andrew; McClain, Shanna N.; Markert, Amanda; Griffin, Robert; Suarez, Pablo

doi:10.1117/1.jrs.15.032002

Cited by 17 publications

(8 citation statements)

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“…Finally, this data could be used within anticipatory action program development, which currently has seen little use in the context of flash floods and in urban areas. There have been few attempts to develop methods to identify which neighborhoods, far from the level of granularity of roads, are candidates for prioritization or deprioritization for anticipatory action when certain thresholds of flood risk are indicated within a forecast 78 .…”

Section: Discussionmentioning

confidence: 99%

Evaluating the usefulness of VGI from Waze for the reporting of flash floods

Lowrie

Kruczkiewicz

McClain

et al. 2022

Sci Rep

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Using volunteered geographic information (VGI) to supplement disaster risk management systems, including forecasting, risk assessment, and disaster recovery, is increasingly popular. This attention is driven by difficulties in detection and characterization of hazards, as well as the rise of VGI appropriate for characterizing specific forms of risk. Flash-flood historical records, especially those that are impact-based, are not comprehensive, leading to additional barriers for flash-flood research and applications. In this paper we develop a method for associating VGI flood reporting clusters against authoritative data. Using Hurricane Harvey as a case study, VGI reports are assimilated into a spatial analytic framework that derives spatial and temporal clustering parameters supported by associations between Waze’s community-driven emergency operations center and authoritative reports. These parameters are then applied to find previously unreported likely flash flood-events. This study improves the understanding of the distribution of flash flooding during Hurricane Harvey and shows potential application to events in other areas where Waze data and reporting from official sources, such as the National Weather Service, are available.

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Section: Discussionmentioning

confidence: 99%

Evaluating the usefulness of VGI from Waze for the reporting of flash floods

Lowrie

Kruczkiewicz

McClain

et al. 2022

Sci Rep

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“…Natural hazard driven disasters [75] disproportionately impact vulnerable populations who are often not represented on a map [76]. A lack of data, or a lack of data of a sufficient quality, leads to challenges in various decision-making contexts, including it being particularly challenging to design risk-based anticipatory action programs, especially in complex settings such as those involving migration, displacement and informal settlements [77].…”

Section: Discussionmentioning

confidence: 99%

Advancing Data for Street-Level Flood Vulnerability: Evaluation of Variables Extracted from Google Street View in Quito, Ecuador

Velez

Calderón

Carey

et al. 2022

IEEE Open J. Comput. Soc.

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Data relevant to flood vulnerability is minimal and infrequently collected, if at all, for much of the world. This makes it difficult to highlight areas for humanitarian aid, monitor changes, and support communities in need. It is time consuming and resource intensive to do an exhaustive study for multiple flood relevant vulnerability variables using a field survey. We use a mixed methods approach to develop a survey on variables of interest and utilize an open-source crowdsourcing technique to remotely collect data with a human-machine interface using high-resolution satellite images and Google Street View. Finally, we perform an inter-rater agreement to assess if this technique provides consistent results. This paper focuses on Quito, Ecuador as a case study, but the methodology can be replicated to produce labeled training data in other areas. The overall goal is to advance methods to help build training datasets that allow for assessing and automating the mapping of flood vulnerability for urban areas.

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“…Humanitarian agencies use EO as inputs to anticipatory actions that reduce flood risk via early warning systems and forecast‐based financing (Kruczkiewicz, Klopp, et al., 2021; Nauman et al., 2021). While anticipatory action programs for floods typically use forecast models rather than EO (Coughlan de Perez et al., 2016), EO data is employed to activate interventions when flood conditions breach pre‐defined thresholds (e.g., Chen et al., 2019).…”

Section: Earth Observation Applications For Post‐flood Recoverymentioning

confidence: 99%

Earth Observation to Address Inequities in Post‐Flood Recovery

Friedrich,

Tellman,

Sullivan

et al. 2024

Earth's Future

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Floods impact communities worldwide, resulting in loss of life, damaged infrastructure and natural assets, and threatened livelihoods. Climate change and urban development in flood‐prone areas will continue to worsen flood‐related losses, increasing the urgency for effective tools to monitor recovery. Many Earth Observation (EO) applications exist for flood‐hazard monitoring and provide insights on location, timing, and extent in near real‐time and historically to estimate flood risk. Less attention has been paid to flood recovery, even though differing recovery rates and outcomes can have immediate and enduring distributional effects within communities. EO data are uniquely positioned to monitor post‐flood recovery and inform policy on hazard mitigation and adaptation but remain underutilized. We encourage the EO and flood research community to refocus on developing flood recovery applications to address growing risk. Translation of EO insights on flood recovery among flood‐affected communities and decision‐makers is necessary to address underlying social vulnerabilities that exacerbate inequitable recovery outcomes and advocate for redressing injustices where disparate recovery is observed. We identify an unequivocal need for EO to move beyond mapping flood hazard and exposure toward post‐flood recovery monitoring to inform recovery across geographic contexts. This commentary proposes a framework for remote sensing scientists to engage community‐based partners to integrate EO with non‐EO data to advance flood recovery monitoring, characterize inequitable recovery, redistribute resources to mitigate inequities, and support risk reduction of future floods.

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Perspectives on flood forecast-based early action and opportunities for Earth observations

Cited by 17 publications

References 0 publications

Evaluating the usefulness of VGI from Waze for the reporting of flash floods

Evaluating the usefulness of VGI from Waze for the reporting of flash floods

Advancing Data for Street-Level Flood Vulnerability: Evaluation of Variables Extracted from Google Street View in Quito, Ecuador

Earth Observation to Address Inequities in Post‐Flood Recovery

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