Incorporating stakeholder concerns in Land Information Systems for urban flood management

Pradeep, R.M.M.; Wijesekera, Nts

doi:10.1016/j.array.2020.100037

Cited by 4 publications

(3 citation statements)

References 43 publications

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“…From a total of about 177 projects with around 40 of high priority, local evacuation road upgrades were identified to be essential for the maintenance of access to major regional evacuation routes. These upgrades were led by the Roads and Maritime Services in collaboration with other bodies including local councils, NSW State Emergency Service and other stakeholders [73]. The Hawkesbury FRM strategy lacks attention to aged care facilities and the utilization of emerging cutting-edge technologies such as AI, the Internet of Things (IoT) and Unmanned Aerial Vehicles (UAV) for flood disaster management.…”

mentioning

confidence: 99%

An AI/ML-Based Strategy for Disaster Response and Evacuation of Victims in Aged Care Facilities in the Hawkesbury-Nepean Valley: A Perspective

et al. 2022

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The Hawkesbury-Nepean Valley, Australia’s longest coastal catchment, is spanned by a river system of more than 470 km, that runs from Goulburn to Broken Bay, covering a total area of over 2.2 million hectares. This region has remained prone to flood events, with considerable mortalities, economic impacts and infrastructural losses occurring quite regularly. The topography, naturally variable climatic conditions and the ‘bathtub’ effect in the region are responsible for the frequent flood events. In response, the Government at the national/federal, state and local level has focused on the design of efficient flood risk management strategies with appropriate evacuation plans for vulnerable communities from hospitals, schools, childcare and aged care facilities during a flood event. Despite these overarching plans, specialized response and evacuation plans for aged care facilities are critical to reducing the loss incurred by flood events in the region. This is the focus of this present paper, which reviews the history of flood events and responses to them, before examining the utilization of artificial intelligence (AI) techniques during flood events to overcome the flood risks. An early flood warning system, based on AI/Machine Learning (ML) strategy is being suggested for a timely decision, enhanced disaster prediction, assessment and response necessary to overcome the flood risks associated with aged care facilities within the Hawkesbury-Nepean region. A framework entailing AI/ML methods for identifying the safest route to the destination using UAV and path planning has been proposed for timely disaster response and evacuation of the residents of aged care facilities.

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confidence: 99%

An AI/ML-Based Strategy for Disaster Response and Evacuation of Victims in Aged Care Facilities in the Hawkesbury-Nepean Valley: A Perspective

et al. 2022

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“…Different criteria allow assessing importance of a BP (Bruwier, 2020;Pradeep & Wijesekera, 2020;Qi et al, 2020), and the most influential of them were selected in this study. Table 1 presents the scale adopted to assess and score the used criteria with direct or indirect relations with SDS's floods.…”

Section: Multicriteria Analysis-evaluation Scale and Criteriamentioning

confidence: 99%

Urban floods management using AHP and FMEA methods-case study of Bejaia, Algeria

Azoune

Cherrared

2022

J GEOGR INST CVIJIC

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This study aims to help the management of the Stormwater Drainage System (SDS) of Bejaia City to manage urban flood problems, i.e., to provide them with tools for a better organization of information on SDS combined with a better optimization of its interventions on the network. Our study is based on a multicriteria analysis of the ?SDS-inundation-Impact? system. We used a multicriteria approach and classified the overflow points called Black Points (BPs) using two methods: Analytic Hierarchy Process (AHP) and Failure Mode, Effect and criticality Analysis (FMEA). The criteria and the evaluation scale were defined on the basis of past observations, expert opinions, and feedback experience. The map of the past flooded areas was made and used to calibrate the two models. We mapped the BPs according to intervention priorities (one to four). The outcomes from both models are greatly comparable to the results of the impact assessment of past floods. The proposed approach can also reduce flood risks by integrating some of influencing factors (causing floodings) and the application can be adapted and implemented in other cities too. Both methods are reliable, particularly the AHP for the most overflowing BPs. They could be advantageously combined to improve decision-making.

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“…Researchers are also investigating various algorithms for analysing large scale data sets that would solve the real-time issues with minimum computational time. Robust risk-related data analysis, enhancing computational potential and applying different sensors within drones and satellites for capturing real-time data analysis are a few of the many domains that researchers are investigating [38][39][40][41]. These include observing disaster areas by employing drones and analysing real-time data for mapping the area and finding the safest route to reach the victims during floods.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Approach for Post-Disaster Flood Management Via the Use of Cutting-Edge Technologies and UAVs: A Review

et al. 2021

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Rapid advances that improve flood management have facilitated the disaster response by providing first aid services, finding safe routes, maintaining communication and developing flood maps. Different technologies such as image processing, satellite imagery, synthetic imagery and integrated approaches have been extensively analysed in the literature for disaster operations. There is a need to review cutting-edge technologies for flood management. This paper presents a review of the latest advancements in the flood management domain based on image processing, artificial intelligence and integrated approaches with a focus on post-disaster. It answers the following research questions: (1) What are the latest developments in image processing for flood management in a post-disaster scenario? (2) What are the latest techniques for flood management based on artificial intelligence in a post-disaster scenario? (3) What are the existing gaps in the selected technologies for post-disaster? (4) How can the authorities improve the existing post-disaster management operation with cutting-edge technologies? A novel framework has been proposed to optimise flood management with the application of a holistic approach.

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Incorporating stakeholder concerns in Land Information Systems for urban flood management

Cited by 4 publications

References 43 publications

An AI/ML-Based Strategy for Disaster Response and Evacuation of Victims in Aged Care Facilities in the Hawkesbury-Nepean Valley: A Perspective

An AI/ML-Based Strategy for Disaster Response and Evacuation of Victims in Aged Care Facilities in the Hawkesbury-Nepean Valley: A Perspective

Urban floods management using AHP and FMEA methods-case study of Bejaia, Algeria

An Integrated Approach for Post-Disaster Flood Management Via the Use of Cutting-Edge Technologies and UAVs: A Review

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