A web-based analytical urban flood damage and loss estimation framework

Alabbad, Yazeed; Yildirim, Enes; Demir, İbrahim

doi:10.1016/j.envsoft.2023.105670

Cited by 24 publications

(9 citation statements)

References 36 publications

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“…The last two decades have witnessed a high number of flood disasters worldwide, resulting in overwhelming damage to people, infrastructure (Alabbad et al, 2023), and agriculture (Jongman et al, 2012;Davenport et al, 2021). Climate change, transforming natural landscapes for urban development purposes, and lack or detraction of flood hazard accounts when building a new environment have led to continuing and aggravating flood risk (Villarini & Zhang, 2020;Lehmann et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Geo-Spatial Analysis of Built-Environment Exposure to Flooding: Iowa Case Study

Alabbad¹,

Demir²

2024

Preprint

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Flooding is the most frequent type of natural disaster, inducing devastating damages at large and small spatial scales. Flood exposure analysis is a critical part of flood risk assessment. While most studies analyze the exposure elements separately, it is crucial to perform a multi-parameter exposure analysis and consider different types of flood zones to gain a comprehensive understanding of the impact and make informed mitigation decisions. This research analyzes the population, properties, and road networks exposed to the 100, 200, and 500-year flood events at the county level in the State of Iowa using geospatial analytics. We also proposed a flood exposure index at the county level using fuzzy overlay analysis to help find the most impacted county. During flooding, results indicate that the county-level percentage of displaced population, impacted properties, and road length can reach up to 46%, 41%, and 40%, respectively. We found that the most exposed buildings and roads are laid in residential areas. Also, 25% of the counties are designated as very high-exposure areas. This study can help many stakeholders identify vulnerable areas and ensure equitable distribution of investments and resources toward flood mitigation projects.

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Section: Introductionmentioning

confidence: 99%

Geo-Spatial Analysis of Built-Environment Exposure to Flooding: Iowa Case Study

Alabbad¹,

Demir²

2024

Preprint

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“…The contribution of this work includes a) introducing an openly accessible water extent mapper to facilitate fast mapping, analyzing, and comparing the Earth's surface water body using multimodal RS images; b) incorporating advanced functional modules to improve the accuracy of classifications in several complex conditions (i.e., areas under the influence of cloud & cloud shadow and dense vegetation and areas with constrained hydraulic conditions); and c) designing and building the system with open data that has global coverage as well as with a user-friendly interface. In short, the MultiRS Flood Mapper is aimed at providing accurate and reliable water extent predictions derived from multimodal RS images to support fast flood-related risk analysis Cikmaz et al, 2023), damage estimation (Alabbad et al, 2023) and decision-making Alabbad and Demir, 2022) tasks for users with different backgrounds.…”

Section: Introductionmentioning

confidence: 99%

MultiRS Flood Mapper: A Google Earth Engine Application for Water Extent Mapping with Multimodal Remote Sensing and Quantile-Based Postprocessing

Li,

Demir

2024

Preprint

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Remote Sensing (RS) imagery is an important data source in surface water mapping applications thanks to its high spatial and temporal consistency and scalability. The introduction of Google Earth Engine (GEE) has cleared some of the major barriers of fast and large-scale RS-based geospatial analyses by providing easy and open access to most of the commonly used RS image products as well as built-in functions designed for geospatial analysis. There is a growing interest in developing GEE applications that can work for different regions and time durations to improve the reusability of GEE scripts and reduce manual effort during the entire workflow of water-body extraction. Despite all those advancements and efforts, there is still a need for creating GEE applications that are user-friendly and can serve both remote sensing experts and students. These applications are also expected to be powerful and comprehensive enough to handle each step along the entire lifecycle of water body extraction workflow and are capable of handling geomorphic and geospatial discrepancies between regions under various configurations. Given these needs and challenges, this study presents the MultiRS Flood Mapper, a GEE application that incorporates three most used RS imagery (i.e., Sentinel-1 SAR, Landsat 8, and Sentinel-2) in water body mapping and integrates advanced dynamic thresholding algorithms and powerful postprocessing modules to improve classification results under the influence of dense vegetation and cloud, and in regions with constrained hydraulic conditions. In addition, the MultiRS Flood Mapper comes with a self-explanatory and user-friendly interface. Most functional modules for RS image processing that require professional knowledge are fully automated and the remaining function in an intuitive and interactive way, which therefore enables the MultiRS Flood Mapper to have great potential to serve a broad audience with various backgrounds and purposes.

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“…In the last two decades, the advancements in information technology and systems, including web applications, have facilitated the analysis of complex data (Xu et al, 2019) and the delivery of valuable information through visualization across various disciplines, including flood risk management (Alabbad et al, 2023). In the domain of transportation research, decision support systems (DSS) have allowed decision-makers, including the public, to assess the effects of floods on accessibility and manage emergency activities.…”

Section: Introductionmentioning

confidence: 99%

A Web-based Decision Support Framework for Optimizing Road Network Accessibility and Emergency Facility Allocation During Flooding

Alabbad¹,

Mount²,

Campbell³

et al. 2023

Preprint

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Transportation systems can be significantly affected by flooding, leading to physical damage and subsequent adverse impacts such as increased travel distance to essential services. Even though flooding is a frequently recurring phenomenon that can affect thousands of people per event, there are limited accessible online tools available for analyzing and visualizing flood risk for supporting decisions on routing and emergency planning, and response. Existing tools are generally based on complicated models and are not easily accessible to non-expert users. Therefore, it is critical to have efficient real-time communication and decision tools for analyzing flood impacts on transportation networks for various stakeholders, including the public, to minimize the adverse impacts on those groups. This paper presents a web application that uses graph network methods and the latest web technologies and standards to assist in describing flood events in terms of operational constraints and provide analytical methods to support mobility and mitigation decisions during these events. The framework is designed to be user-friendly, enabling non-expert users to access information about road status, shortest paths to critical amenities, location-allocation, and service coverage. The study area includes the following two communities in the State of Iowa, Cedar Rapids and Charles City, which were used to test the application's functionality and explore the outcomes. Our research demonstrates that flooding can significantly affect bridge operation, routing from locations to critical amenities, arbitrary point-to-point routing, planning for emergency facility placement, and service area accessibility. The introduced framework is capable of solving complex flood-related analytical decision tasks and providing an understandable representation of transportation vulnerability, enhancing mitigation strategies. Therefore, this web application provides a valuable tool for stakeholders to make informed decisions on transportation networks during flood events.

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A web-based analytical urban flood damage and loss estimation framework

Cited by 24 publications

References 36 publications

Geo-Spatial Analysis of Built-Environment Exposure to Flooding: Iowa Case Study

Geo-Spatial Analysis of Built-Environment Exposure to Flooding: Iowa Case Study

MultiRS Flood Mapper: A Google Earth Engine Application for Water Extent Mapping with Multimodal Remote Sensing and Quantile-Based Postprocessing

A Web-based Decision Support Framework for Optimizing Road Network Accessibility and Emergency Facility Allocation During Flooding

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