Digital Earth from vision to practice: making sense of citizen-generated content

Craglia, Max; Ostermann, Frank O.; Spinsanti, Laura

doi:10.1080/17538947.2012.712273

Cited by 94 publications

(58 citation statements)

References 8 publications

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“…and implicit (e.g., Flickr, Twitter, etc.) sources of GI [15,16], which, considering the advances in GI retrieval methodologies, can be used to extract meaningful data from all kinds of content available on the Web and thus create innovative spatial products (e.g., from bicycle maps to emotion maps). These spatial products are out of the scope of traditional geo-data producers such as National Mapping Agencies (NMAs) or large corporations.…”

Section: Introductionmentioning

confidence: 99%

Assessing Crowdsourced POI Quality: Combining Methods Based on Reference Data, History, and Spatial Relations

Touya¹,

Antoniou²,

Olteanu‐Raimond³

et al. 2017

IJGI

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Abstract:With the development of location-aware devices and the success and high use of Web 2.0 techniques, citizens are able to act as sensors by contributing geographic information. In this context, data quality is an important aspect that should be taken into account when using this source of data for different purposes. The goal of the paper is to analyze the quality of crowdsourced data and to study its evolution over time. We propose two types of approaches: (1) use the intrinsic characteristics of the crowdsourced datasets; or (2) evaluate crowdsourced Points of Interest (POIs) using external datasets (i.e., authoritative reference or other crowdsourced datasets), and two different methods for each approach. The potential of the combination of these approaches is then demonstrated, to overcome the limitations associated with each individual method. In this paper, we focus on POIs and places coming from the very successful crowdsourcing project: OpenStreetMap. The results show that the proposed approaches are complementary in assessing data quality. The positive results obtained for data matching show that the analysis of data quality through automatic data matching is possible but considerable effort and attention are needed for schema matching given the heterogeneity of OSM and the representation of authoritative datasets. For the features studied, it can be noted that change over time is sometimes due to disagreements between contributors, but in most cases the change improves the quality of the data.

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Section: Introductionmentioning

confidence: 99%

Assessing Crowdsourced POI Quality: Combining Methods Based on Reference Data, History, and Spatial Relations

Touya¹,

Antoniou²,

Olteanu‐Raimond³

et al. 2017

IJGI

View full text Add to dashboard Cite

show abstract

“…Given the diversity feature of VGI, a variety of choices of ways for creating and analyzing VGI should be supported. The forms of VGI creation can be active (e.g., OpenStreetMap) or passive (e.g., Twitter) [46], or facilitated (e.g., see Seeger [18] and Cinnamon and Schuurman [47]). VGI collection and sense-making methods can be quantitative or qualitative solely, or can be quantitative-qualitative combined either sequentially at different stages or interactively throughout the process.…”

Section: A Conceptual Frameworkmentioning

confidence: 99%

Towards Enhancing Integrated Pest Management Based on Volunteered Geographic Information

Yan

Feng

Chang

2017

IJGI

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Integrated pest management (IPM) involves integrating multiple pest control methods based on site information obtained through inspection, monitoring, and reports. IPM has been deployed to achieve the judicious use of pesticides and has become one of the most important methods of securing agricultural productivity. Despite the efforts made to strengthen IPM during the past decades, overuse as well as indiscriminate use of pesticides is still common. This problem is particularly serious in underserved farming communities which suffer from ineffectiveness with respect to pest management information collection and dissemination. The recent development of volunteered geographic information (VGI) offers an opportunity to the general public to create and receive ubiquitous, cost-effective, and timely geospatial information. Therefore, this study proposes to enhance IPM through establishing a VGI-based IPM. As a starting point of this line of research, this study explored how such geospatial information can contribute to IPM enhancement. Based on this, a conceptual framework of VGI interaction was built to guide the establishment of VGI-based IPM. To implement VGI-based IPM, a mobile phone platform was developed. In addition, a case study was conducted in the town of Shuibian in Jiangxi province of China to demonstrate the effectiveness of the proposed approach. In the case study, by analyzing infestation incidents of an overwintering outbreak of striped rice stem borers voluntarily reported by farmers through mobile phones, spatiotemporal infestation patterns of the borers throughout the study area were revealed and disseminated to the farmers. These patterns include the dates and degree-days the pest infestations intensified, and the orientation or spatial structural variations of the clustering of the infestations. This case study showcased the unique merit of VGI in enhancing IPM, namely the acquisition of previously unrecorded spatial data in a cost-effective and real-time manner for discovering and disseminating previously unknown pest management knowledge.

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“…Accordingly, volunteers can add, edit, share and apply geographic information through these platforms. Craglia et al [21] present a VGI typology in order to have a common base for discussions and analyses (Table 1). They divide VGI into explicit and implicit geographic content.…”

Section: Implicitly-volunteered Passive Sensingmentioning

confidence: 99%

Volunteered Geographic Information in Natural Hazard Analysis: A Systematic Literature Review of Current Approaches with a Focus on Preparedness and Mitigation

Klonner

Marx

Usón

et al. 2016

IJGI

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Abstract:With the rise of new technologies, citizens can contribute to scientific research via Web 2.0 applications for collecting and distributing geospatial data. Integrating local knowledge, personal experience and up-to-date geoinformation indicates a promising approach for the theoretical framework and the methods of natural hazard analysis. Our systematic literature review aims at identifying current research and directions for future research in terms of Volunteered Geographic Information (VGI) within natural hazard analysis. Focusing on both the preparedness and mitigation phase results in eleven articles from two literature databases. A qualitative analysis for in-depth information extraction reveals auspicious approaches regarding community engagement and data fusion, but also important research gaps. Mainly based in Europe and North America, the analysed studies deal primarily with floods and forest fires, applying geodata collected by trained citizens who are improving their knowledge and making their own interpretations. Yet, there is still a lack of common scientific terms and concepts. Future research can use these findings for the adaptation of scientific models of natural hazard analysis in order to enable the fusion of data from technical sensors and VGI. The development of such general methods shall contribute to establishing the user integration into various contexts, such as natural hazard analysis.

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Digital Earth from vision to practice: making sense of citizen-generated content

Cited by 94 publications

References 8 publications

Assessing Crowdsourced POI Quality: Combining Methods Based on Reference Data, History, and Spatial Relations

Assessing Crowdsourced POI Quality: Combining Methods Based on Reference Data, History, and Spatial Relations

Towards Enhancing Integrated Pest Management Based on Volunteered Geographic Information

Volunteered Geographic Information in Natural Hazard Analysis: A Systematic Literature Review of Current Approaches with a Focus on Preparedness and Mitigation

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