Mapping Floods and Assessing Flood Vulnerability for Disaster Decision-Making: A Case Study Remote Sensing Application in Senegal

Schwarz, Bessie; Pestre, Gabriel; Tellman, Beth; Sullivan, Jonathan A.; Kuhn, Charles; Mahtta, Richa; Pandey, Bhartendu; Hammett, Laura

doi:10.1007/978-3-319-65633-5_16

Cited by 18 publications

(11 citation statements)

References 4 publications

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“…Other similar research ties the use of EO data to flood management, tsunami monitoring and forecasting, landslide and volcanic activity monitoring, and general disaster management. Concepts covered span such aspects as applications of EO data, accuracy of EO-derived data processing, integrated management platforms, and case studies (Alfieri et al, 2018;Novellino et al, 2018;Schwarz et al, 2018;Wang and Xie, 2018;Korup et al, 2019).…”

Section: State Of Researchmentioning

confidence: 99%

Using Earth Observations to Help Developing Countries Improve Access to Reliable, Sustainable, and Modern Energy

Leibrand

Sadoff

Maslak

et al. 2019

Front. Environ. Sci.

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In this review paper, the authors identify priority areas, and opportunities for electric utilities in developing and emerging economies to incorporate Earth observation (EO) data into rural electrification planning, renewable energy resource assessment, distributed generation, grid operation and reliability, and disaster risk reduction and recovery efforts. Using a methodological framework, the authors conducted a comprehensive literature review of primary and gray literature. This paper reviews the many existing applications for EO data, such as the use of nighttime lights imagery for estimations of rural electrification, EO-derived normalized difference vegetation index (NDVI) products for vegetation monitoring for overhead transmission line management, solar radiance data for renewable energy project planning, and nowcasting for extreme weather events and other disaster monitoring. These and other applications can enhance energy security through improved governance of and access to modern and reliable electricity, renewable energy management, and disaster risk assessment in developing nations, paving the way for more sustainable social and economic development. Real-world examples of EO data use by utilities in developing and emerging economies, as well as barriers and opportunities for EO technology transfer, are discussed. Recommendations for stakeholder engagement, future EO training opportunities, and human capacity building are also presented.

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Section: State Of Researchmentioning

confidence: 99%

Using Earth Observations to Help Developing Countries Improve Access to Reliable, Sustainable, and Modern Energy

Leibrand

Sadoff

Maslak

et al. 2019

Front. Environ. Sci.

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“…Further contributions to VA and its dynamics are coming from machine learning techniques, helping to extract information from different sources of data. For instance, Schwarz et al (2018) used machine learning, remote sensing (RS) and census data to predict the socio-physical vulnerability to floods and dynamically deliver that information to decision makers through a web platform in the case of Senegal.…”

Section: Introductionmentioning

confidence: 99%

Integration of earth observation and census data for mapping a multi-temporal flood vulnerability index: a case study on Northeast Italy

2021

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Climate sciences foresee a future where extreme weather events could happen with increased frequency and strength, which would in turn increase risks of floods (i.e. the main source of losses in the world). The Mediterranean basin is considered a hot spot in terms of climate vulnerability and risk. The expected impacts of those events are exacerbated by land-use change and, in particular, by urban growth which increases soil sealing and, hence, water runoff. The ultimate consequence would be an increase of fatalities and injuries, but also of economic losses in urban areas, commercial and productive sites, infrastructures and agriculture. Flood damages have different magnitudes depending on the economic value of the exposed assets and on level of physical contact with the hazard. This work aims at proposing a methodology, easily customizable by experts’ elicitation, able to quantify and map the social component of vulnerability through the integration of earth observation (EO) and census data with the aim of allowing for a multi-temporal spatial assessment. Firstly, data on employment, properties and education are used for assessing the adaptive capacity of the society to increase resilience to adverse events, whereas, secondly, coping capacity, i.e. the capacities to deal with events during their manifestation, is mapped by aggregating demographic and socio-economic data, urban growth analysis and memory on past events. Thirdly, the physical dimension of exposed assets (susceptibility) is assessed by combining building properties acquired by census data and land-surface characteristics derived from EO data. Finally, the three components (i.e. adaptive and coping capacity and susceptibility) are aggregated for calculating the dynamic flood vulnerability index (FVI). The approach has been applied to Northeast Italy, a region frequently hit by floods, which has experienced a significant urban and economic development in the past decades, thus making the dynamic study of FVI particularly relevant. The analysis has been carried out from 1991 to 2016 at a 5-year steps, showing how the integration of different data sources allows to produce a dynamic assessment of vulnerability, which can be very relevant for planning in support of climate change adaptation and disaster risk reduction.

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“…This type of analysis can help better decision making. Some examples of this type of analysis can be seen in the papers presented in [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Experience in MAPATÓN 2021: "ApuMayu" a Tool for the Analysis of Flood Risk Zones in Piura

Vargas-Cuentas¹,

Cosi²,

López³

et al. 2021

IJETAE

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Abstract—MAPATÓN 2021 was organized by CONIDA (Peruvian Space Agency) as part of the celebrations for the bicentennial of Peru's independence. MAPATÓN was oriented to disaster management. This work aims to transmit the experience of participation in MAPATON and communicate the results achieved. The authors participated in developing flood simulation models and analyzing SENTINEL-1 satellite images to identify areas affected by floods that occurred in 2017, 2019 and 2020. The results obtained, shown in a story map, show the great utility of this type of analysis for risk management and disaster management. Keywords—MAPATON 2021; natural disasters; Peru; disaster management; Sentinel; satellite images

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Mapping Floods and Assessing Flood Vulnerability for Disaster Decision-Making: A Case Study Remote Sensing Application in Senegal

Cited by 18 publications

References 4 publications

Using Earth Observations to Help Developing Countries Improve Access to Reliable, Sustainable, and Modern Energy

Using Earth Observations to Help Developing Countries Improve Access to Reliable, Sustainable, and Modern Energy

Integration of earth observation and census data for mapping a multi-temporal flood vulnerability index: a case study on Northeast Italy

Experience in MAPATÓN 2021: "ApuMayu" a Tool for the Analysis of Flood Risk Zones in Piura

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