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The physicality of digital public space
Published in Naomi Jacobs, Rachel Cooper, Living in Digital Worlds, 2018
However digital maps can also be used for new purposes which were not possible with the paper versions. Collaborative mapping uses digital map technology to collect real-time information from vast numbers of people. This creates powerful mapping tools that can be used for all sorts of things: for example the Ushahidi platform, created in the wake of the 2007 Kenyan crisis, collected eyewitness reports of violence during the political crisis (Thompson, 2013). Patrick Meier, Ushahidi’s former head of crisis mapping, describes the power that such maps have. ‘Having a real-time map is almost as good as having your own helicopter. A live map provides immediate situational awareness, a bird’s-eye view – and thus an additional perspective on events unfolding in time and space’ (Meier, 2015).
Satellite image analysis using crowdsourcing data for collaborative mapping: current and opportunities
Published in International Journal of Digital Earth, 2020
Wei Su, Daniel Sui, Xiaodong Zhang
With the emergence of Web 2.0, crowdsourcing has been increasingly used in satellite image analysis for collaborative mapping, as in the example of involving the public to support the efforts of experts to analyze satellite images for various applications (Maisonneuve and Chopard 2012). Collaborative mapping is the aggregation of Web mapping and user-generated content, from a group of individuals or entities, and can take several distinct forms (See, Fritz, and Leeuw 2013; Wikipedia 2016). With the growth of technology for storing and sharing maps, collaborative maps have become competitors to commercial services, in the case of OpenStreetMap (OSM), Ushahidi, GeoWiki, Wikimapia, Field Papers etc. initiatived by Google Map Maker and Yandex. Map editor, Youth Mappers, Missing Maps, Tomnod, Talking Points Collaborative Mapping. Among all the articles published during the last decade, satellite image analysis and crowdsourcing have accounted for a large share of the total applications. An analysis using the Institute of Science Information Web of Science found that, in an example of parallel evolution, 5655 articles about crowdsourcing and 24,962 articles about satellite image analysis have been published since 2006 (Figure 1). The number of crowdsourcing articles increased rapidly, from 8 articles in 2006 (when the crowdsourcing first appeared in the database) to 1690 in 2016. The number of publications about satellite image analysis increased more slowly, from 1494 in 2006–2646 in 2016. However, articles that combine these two research areas are much less common, since satellite image analysis using crowdsourcing is a new research field; thus, there have been only 31 articles since 2012.