An analytics dashboard visualization for flood decision support system

Saha, Sudipto; Shekhar, Shashank; Sadhukhan, Sounak; Das, Prasun

doi:10.1007/s12650-017-0453-3

Cited by 13 publications

(9 citation statements)

References 12 publications

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“…Visual variables, mainly in such context, colors, transparency, textures could be used to make something salient, and to support visual attention. Some works alternatively propose the visualization of analytics dashboards synthesizing flood risks data and socio-economic data for flood managers, thus geovisualizing processed data (Saha et al, 2018).…”

Section: Related Work In Flood Risks Geovisualizationmentioning

confidence: 99%

Visual Analysis of Inconsistencies in Hydraulic Simulation Data

Perrin

Christophe

Jacquinod

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. We present our contribution to the geovisualization and visual analysis of hydraulic simulation data, based on an interdisciplinary research work undertaken by researchers in geographic information sciences and in hydraulics. The positive feedback loop between researchers favored the proposal of visualization tools enabling visual reasoning on hydraulic simulated data so as to infer knowledge on the simulation model. We interactively explore and design 2D multi-scale styles to render hydraulic simulated data, in order to support the identification over large simulation domains of possible local inconsistencies related to input simulation data, simulation parameters or simulation workflow. Models have been implemented into QGIS and are reusable for other input data and territories.

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Section: Related Work In Flood Risks Geovisualizationmentioning

confidence: 99%

Visual Analysis of Inconsistencies in Hydraulic Simulation Data

Perrin

Christophe

Jacquinod

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…An analytics dashboard visualization for flood decision support system [92]; a dashboard built on open-source frameworks, made use of geoservices based OGC, and established a wireless sensor network [93].…”

Section: Urban Flood Analyticalmentioning

confidence: 99%

“…For the analytical dashboard, the analysis model is its core that is used to explore the reasons behind patterns and results [2,97], which includes visual analysis [92,94], spatiotemporal analysis [27], and decision support [90,93]. To integrate models into dashboards, data exchange and application program interface (API) callback are the most popular methods.…”

mentioning

confidence: 99%

Geospatial Dashboards for Monitoring Smart City Performance

Jing

et al. 2019

Sustainability

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Geospatial dashboards have attracted increasing attention from both user communities and academic researchers since the late 1990s. Dashboards can gather, visualize, analyze and advise on urban performance to support sustainable development of smart cities. We conducted a critical review of the research and development of geospatial dashboards, including the integration of maps, spatial data analytics, and geographic visualization for decision support and real-time monitoring of smart city performance. The research about this kind of system has mainly focused on indicators, information models including statistical models and geospatial models, and other related issues. This paper presents an overview of dashboard history and key technologies and applications in smart cities, and summarizes major research progress and representative developments by analyzing their key technical issues. Based on the review, we discuss the visualization model and validity of models for decision support and real-time monitoring that need to be further researched, and recommend some future research directions.

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“…Through their review, Newman et al (2017) observe that such systems mostly focus on identifying areas of risk (Inform phase, prior to design), whereas systems that support the evaluation of risk reduction options are not researched as much. For example, such a system that focuses on providing information about flood hazard is presented by Saha et al (2018) who develop a model based on rainfall history, which can predict the areas with increased flood risk, using vulnerability and hazard calculations. The risk zones and vulnerable areas are presented in a geo-visualization, which allows decision-makers to utilize the presented information and take necessary measures of prevention.…”

Section: Introductionmentioning

confidence: 99%

“…Unlike the works presented above, the proposed system does not focus on a specific policy phase but rather provides a holistic solution that allows policy makers to use a single platform throughout the entire policy making cycle, from policy design to policy implementation monitoring and evaluation. In addition, unlike other works that focus on the analysis of limited data sources (Horita et al, 2014;Sharma et al, 2016;Saha et al, 2018), we propose a system that effectively combines heterogeneous environmental, social and economic data, including also new sources of information such as social media, providing a more complete overview of the current status but also of the potential impact and real-life consequences of the examined flood protection measure. Moreover, for the first time we propose the use of a Business Process Engine to help steer the decision-making process with regard to flood-related policies, exploiting and combining recent advances in business process modeling and DSS systems.…”

Section: Introductionmentioning

confidence: 99%

Decision support system for flood risk reduction policies: The case of a flood protection measure in the area of Vicenza

et al. 2021

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Climate change is one of the most significant and pressing issues faced by humanity; it frequently results in major natural disasters, such as catastrophic floods, which require the establishment of effective management policies by local and national authorities. These policies involve complex multistep decision-making processes that require combined assessment of various sources of data by different stakeholders. Even though an abundance of data is being collected to monitor climate change and estimate its consequences on the society, the environment, and the economy, policy-making is still largely based on intuition rather than evidence due to lack of a structured approach for modeling the decision-making process and considering the appropriate use of data in every step of the process. The goal of this work is to introduce a novel decision support system that can guide policy makers through a structured data-driven decision-making process aiming to create policies for flood risk management. The proposed system is a multifacet platform that guides policy makers through five phases—inform, advise, monitor, evaluate, and revise—of the policy cycle. For each phase, different dashboards provide relevant information regarding the environmental, social, and economic conditions. To demonstrate the potential of the proposed system, we use it to assess a flood protection policy in the city of Vicenza, Italy. The results reveal the benefits and challenges of the proposed decision support tool for public administrations involved in flood risk management.

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An analytics dashboard visualization for flood decision support system

Cited by 13 publications

References 12 publications

Visual Analysis of Inconsistencies in Hydraulic Simulation Data

Visual Analysis of Inconsistencies in Hydraulic Simulation Data

Geospatial Dashboards for Monitoring Smart City Performance

Decision support system for flood risk reduction policies: The case of a flood protection measure in the area of Vicenza

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