YouTube as a crowd-generated water level archive

Michelsen, Nils; Dirks, Heiko; Schulz, Stephan; Kempe, S.; Al-Saud, Mohammed; Schüth, Christoph

doi:10.1016/j.scitotenv.2016.05.211

Cited by 40 publications

(28 citation statements)

References 17 publications

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“…In other cases, mostly during flooding situations, citizens provide pictures (Fohringer et al, 2015;Kutija et al, 2014;Li et al, 2017;McDougall, 2011;McDougall and Temple-Watts, 2012;Smith et al, 2015;Starkey et al, 2017) or videos (Le 15 Boursicaud et al, 2016;Le Coz et al, 2016;Michelsen et al, 2016). In the case of pictures/images, the water level is compared with objects in the images that have known or approximately known dimensions.…”

Section: Water Levelmentioning

confidence: 99%

“…non-scientists) in the generation of new knowledge". In the same manner that the involvement of citizens can be diverse, such is the way their participation is found in the scientific literature: 5  Citizen Science (Buytaert et al, 2014)  Citizen Observatory (Degrossi et al, 2014)  Citizen Sensing (Foody et al, 2013)  Trained volunteers (Gallart et al, 2016)  Participatory data collection methods (Michelsen et al, 2016) 10  Crowdsourcing (Leibovici et al, 2015)  Participatory sensing (Kotovirta et al, 2014)  Community-based monitoring (Conrad and Hilchey, 2011)  Volunteer Geographic Information (Klonner et al, 2016)  Eye witnesses (Poser and Dransch, 2010) 15  Non-authoritative sources  Human Sensor Network (Aulov et al, 2014)  Crowdsourced Geographic Information Some of the terms used by the above-mentioned articles have specific definitions that are used to delineate debates on the 20 social mechanisms of citizen participation. Others are just the best form the researcher found to characterise the contribution or the citizen (e.g.…”

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confidence: 99%

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Citizen observations contributing to flood modelling: opportunities and challenges

Assumpção¹,

Popescu²,

Jonoski³

et al. 2017

Preprint

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Abstract. Citizen contributions to science have been successfully implemented in many fields -and water resources is one of them. Through citizens, it is possible to collect data and obtain a more integrated decision-making process. Specifically, data scarcity has always been an issue in flood modelling, which has been addressed in the last decades by remote sensing and is already being discussed in a citizen science scenario. In this context, this article aims to review the literature on the 10 topic and analyse the opportunities and challenges that lie ahead. The literature on monitoring, mapping and modelling, was evaluated according to the flood-related variable citizens contributed to. Pros and cons of the collection/analysis methods were summarised. Then, pertinent publications were mapped into the flood modelling cycle, considering how citizen data properties (spatial and temporal coverage, uncertainty and volume) are related to its integration into modelling. It was clear that the number of studies in the area is rising. There are positive experiences reported in collection and analysis methods, 15 for instance with velocity and land cover, and also when modelling is concerned, for example by using social media mining.However, matching the data properties necessary for each part of the modelling cycle with citizen generated data is still challenging. Nevertheless, the concept that citizen contributions can be used for simulation and forecasting is proved and further work lies in continuing developing and improving not only methods for collection and analysis but certainly for integration into models as well. Finally, in view of recent automated sensors and satellite technologies, it is through studies 20 as the ones analysed in this article that the value of citizen contributions is demonstrated.

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Section: Water Levelmentioning

confidence: 99%

mentioning

confidence: 99%

Citizen observations contributing to flood modelling: opportunities and challenges

Assumpção¹,

Popescu²,

Jonoski³

et al. 2017

Preprint

View full text Add to dashboard Cite

show abstract

“…Recent use of active transmitters (Ravazzolo et al, 2015) or ground cameras (Benacchio et al, 2017) provided useful insights into the dynamics of logs during floods, but are still experimental. The present paper shows that conventional methods may be successfully complemented by participatory sensing (Michelsen et al, 2016) and that despite some relatively minor issues (i.e. access to internet technology, geographic and demographic biases) it offers an interesting alternative for collecting relevant information of infrequent events in remote areas.…”

Section: Final Remarksmentioning

confidence: 99%

Brief communication: The curious case of the large wood-laden flow event in the Pocuro stream (Chile)

Ravazzolo

Mao

Mazzorana

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. Large wood transported during extreme flood events can represent a relevant additional source of hazards that should be taken into account in mountain environments. However, direct observations and monitoring of large-wood transport during floods are difficult and scarce. Here we present a video of a flood characterised by multiple phases of large-wood transport, including an initial phase of wood-laden flow rarely described in the literature. Estimations of flow velocity and transported wood volume provide a good opportunity to develop models of large-woodcongested transport.

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“…This idea is part of a growing application of so-called "citizen science" approaches to water resources systems operation (Buytaert et al, 2014) and, more generally, to diverse environmental problems (Fraternali et al, 2012). Crowdsourced observations may act as low-cost virtual sensors in a variety of environmental contexts (Lowry and Fienen, 2013), for example, contributing to monitoring the dynamics of forests (e.g., Daume et al, 2014), storms (e.g., Good et al, 2014), or streamflow (e.g., Michelsen et al, 2016), with potential benefit in terms of the prediction of flood events and of the timely delivery of alarms (e.g., Smith et al, 2015;Mazzoleni et al, 2015a, b;Fohringer et al, 2015;Le Boursicaud et al, 2016). However, despite this interest in environmental public weband user-generated data (Vitolo et al, 2015), most works focus on data collection and analysis, with limited assessment of the practical value of such crowdsourced information.…”

Section: Introductionmentioning

confidence: 99%

Using crowdsourced web content for informing water systems operations in snow-dominated catchments

Giuliani

Castelletti

Fedorov

et al. 2016

Hydrol. Earth Syst. Sci.

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Abstract. Snow is a key component of the hydrologic cycle in many regions of the world. Despite recent advances in environmental monitoring that are making a wide range of data available, continuous snow monitoring systems that can collect data at high spatial and temporal resolution are not well established yet, especially in inaccessible high-latitude or mountainous regions. The unprecedented availability of user-generated data on the web is opening new opportunities for enhancing real-time monitoring and modeling of environmental systems based on data that are public, low-cost, and spatiotemporally dense. In this paper, we contribute a novel crowdsourcing procedure for extracting snow-related information from public web images, either produced by users or generated by touristic webcams. A fully automated process fetches mountain images from multiple sources, identifies the peaks present therein, and estimates virtual snow indexes representing a proxy of the snow-covered area. Our procedure has the potential for complementing traditional snow-related information, minimizing costs and efforts for obtaining the virtual snow indexes and, at the same time, maximizing the portability of the procedure to several locations where such public images are available. The operational value of the obtained virtual snow indexes is assessed for a real-world water-management problem, the regulation of Lake Como, where we use these indexes for informing the daily operations of the lake. Numerical results show that such information is effective in extending the anticipation capacity of the lake operations, ultimately improving the system performance.

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YouTube as a crowd-generated water level archive

Cited by 40 publications

References 17 publications

Citizen observations contributing to flood modelling: opportunities and challenges

Citizen observations contributing to flood modelling: opportunities and challenges

Brief communication: The curious case of the large wood-laden flow event in the Pocuro stream (Chile)

Using crowdsourced web content for informing water systems operations in snow-dominated catchments

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