Motivating and Sustaining Participation in VGI

Fritz, Steffen; See, Linda; Brovelli, Maria Antonia

doi:10.5334/bbf.e

Cited by 22 publications

(9 citation statements)

References 21 publications

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“…This kind of analysis helps us to more understand cause and the event flow. As many studies pointed out, there is importance for VGI volunteer's education as well as the need for increased motivation (Fritz et al, 2017, Mooney et al, 2016, Fonte et al, 2015, Sui et al, 2012. Educated volunteers provide and collect more relevant data, even participate in the data quality process.…”

Section: Discussionmentioning

confidence: 99%

Combining Social Media and Authoritative Data for Crisis Mapping: A Case Study of a Wildfire Reaching Croatian City of Split

Tavra

Racetin

Peroš

2019

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

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<p><strong>Abstract.</strong> Due to climate changes, wildfire breakouts get more frequent and difficult to control. In the mid-July 2017, the wildfire spread from wildland to the city of Split, the second-largest city in Croatia. This unpredictable spread almost caused the collapse of emergency response systems. Fortunately, a greater tragedy was avoided with the composure of the responsible services and the help of the citizens. The citizens helped in extinguishing the fire and timely provided the significant amount of disaster-related information on different platforms and through social media. In this paper, we address the problem of identifying useful Volunteered Geographic Information (VGI) and georeferenced social media, for improving situation awareness while the wildfire was reaching the Croatian city of Split. Additionally, we combine social media with other external data sources (e. g. Sentinel-2 satellite images) and authoritative data (e.g. Croatian National Protection and Rescue Directorate official data and Public Fire Department of Split data) to establish the geographical relations between the wildfire phenomena and social media messages. In this manner, we seek to leverage the existing knowledge and data about the spatiotemporal characteristics of the Split wildfire in order to improve the identification of useful information from georeferenced social media with other integrated data sources that can be valuable for improving situation awareness in wildfire events.</p>

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Section: Discussionmentioning

confidence: 99%

Combining Social Media and Authoritative Data for Crisis Mapping: A Case Study of a Wildfire Reaching Croatian City of Split

Tavra

Racetin

Peroš

2019

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

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“…Research shows that the incentive to participate in VGI projects depends on the volunteers' knowledge and interest in the topic being mapped and their available time and resources (Brady et al, 1995;Coleman et al, 2009). A literature review on motivation to participate in VGI projects is presented by Fritz et al (2017). VGI is produced by heterogeneous contributors with different levels of detail and precision, which introduces errors and variable quality of VGI data sets (Senaratne et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Community Mapping Supports Comprehensive Urban Flood Modeling for Flood Risk Management in a Data-Scarce Environment

et al. 2020

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In this paper we demonstrate a framework for urban flood modeling with community mapped data, particularly suited for flood risk management in data-scarce environments. The framework comprises three principal stages: data acquisition with survey design and quality assurance, model development and model implementation for flood prediction. We demonstrate that data acquisition based on community mapping can be affordable, comprehensible, quality assured and open source, making it applicable in resource-strained contexts. The framework was demonstrated and validated on a case study in Dar es Salaam, Tanzania. The results obtained show that the community mapped data supports flood modeling on a level of detail that is currently inaccessible in many data-scarce environments. The results obtained also show that the community mapping approach is appropriate for datasets that do not require extensive training, such as flood extent surveys where it is possible to cross-validate the quality of reports given a suitable number and density of data points. More technically advanced features such as dimensions of urban drainage system elements still require trained mappers to create data of sufficient quality. This type of mapping can, however, now be performed in new contexts thanks to the development of smartphones. Future research is suggested to explore how community mapping can become an institutionalized practice to fill in important gaps in data-scarce environments.

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“…However, more research is still needed that looks into what constitutes effective incentives for participation and how citizens can be mobilised to participate in ways that are mutually beneficial to them while contributing VGI. These aspects of recruitment, motivation and sustainability are covered in detail in Chapter 5 by Fritz et al (2017), where the authors review a series of crowdsourcing initiatives in a comparative analysis on recruitment strategies, techniques for motivation and, more generally, issues of sustainability.…”

Section: Issues Related To Vgi For Mappingmentioning

confidence: 99%

Sources of VGI for Mapping

See

Estima

Pődör

et al. 2017

Mapping and the Citizen Sensor

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The concept of Volunteered Geographic Information (VGI) is often exemplified by the mapping of features in OpenStreetMap (OSM), yet there are many other sources of VGI available. Some VGI is very focused on the creation of map-based products, while in other applications location is simply one attribute that is routinely collected, due to the proliferation of Global Positioning System (GPS) enabled devices, e.g. mobile phones and tablets. This chapter aims to provide an overview of the variety of sources of VGI currently available, categorised according to whether they can contribute to framework data (i.e. the type of data that are commonly part of the spatial data infrastructure of national mapping agencies and governments) or not and whether the data have been actively or passively collected. A range of examples are presented to illustrate the different types of VGI in each of these main categories. Finally, the chapter discusses some of the main issues surrounding the use of VGI and points to chapters in the book where these issues are described in more detail.

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Motivating and Sustaining Participation in VGI

Cited by 22 publications

References 21 publications

Combining Social Media and Authoritative Data for Crisis Mapping: A Case Study of a Wildfire Reaching Croatian City of Split

Combining Social Media and Authoritative Data for Crisis Mapping: A Case Study of a Wildfire Reaching Croatian City of Split

Community Mapping Supports Comprehensive Urban Flood Modeling for Flood Risk Management in a Data-Scarce Environment

Sources of VGI for Mapping

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