The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Crowdsourcing for climate and atmospheric sciences: current status and future potential
Open accessAbstract
Crowdsourcing is traditionally defined as obtaining data or information by enlisting the services of a (potentially large) number of people. However, due to recent innovations, this definition can now be expanded to include ‘and/or from a range of public sensors, typically connected via the Internet.’ A large and increasing amount of data is now being obtained from a huge variety of non‐traditional sources – from smart phone sensors to amateur weather stations to canvassing members of the public. Some disciplines (e.g. astrophysics, ecology) are already utilizing crowdsourcing techniques (e.g. citizen science initiatives, web 2.0 technology, low‐cost sensors), and while its value within the climate and atmospheric science disciplines is still relatively unexplored, it is beginning to show promise. However, important questions remain; this paper introduces and explores the wide‐range of current and prospective methods to crowdsource atmospheric data, investigates the quality of such data and examines its potential applications in the context of weather, climate and society. It is clear that crowdsourcing is already a valuable tool for engaging the public, and if appropriate validation and quality control procedures are adopted and implemented, it has much potential to provide a valuable source of high temporal and spatial resolution, real‐time data, especially in regions where few observations currently exist, thereby adding value to science, technology and society.
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Cites
Will the real smart city please stand up?: Intelligent, progressive or entrepreneurial?
Hollands, R. G. (2008) · City · doi:10.1080/13604810802479126 · Cited by 3,025
Current trends in Smart City initiatives: Some stylised facts
Neirotti, P., De Marco, A., Cagliano, A. C., Mangano, G., & Scorrano, F. (2014) · Cities · doi:10.1016/j.cities.2013.12.010 · Cited by 2,322
Unique in the Crowd: The privacy bounds of human mobility
de Montjoye, Y.-A., Hidalgo, C. A., Verleysen, M., & Blondel, V. D. (2013) · Scientific Reports · doi:10.1038/srep01376 · Cited by 1,645
Cited by
Geospatial big data handling theory and methods: A review and research challenges
Li, S., Dragicevic, S., Castro, F. A., Sester, M., Winter, S., Coltekin, A., Pettit, C., Jiang, B., Haworth, J., Stein, A., et al. (2016) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2015.10.012 · Cited by 749
Eight grand challenges in socio-environmental systems modeling
Elsawah, S., Filatova, T., Jakeman, A. J., Kettner, A. J., Zellner, M. L., Athanasiadis, I. N., Hamilton, S. H., Axtell, R. L., Brown, D. G., Gilligan, J. M., et al. (2020) · Socio-Environmental Systems Modelling · doi:10.18174/sesmo.2020a16226 · Cited by 205
Beele, E., Reyniers, M., Aerts, R., & Somers, B. (2022) · Earth System Science Data Discussions · doi:10.5194/essd-2022-113 · Cited by 44
Quality control and bias adjustment of crowdsourced wind speed observations
Chen, J., Saunders, K., & Whan, K. (2021) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.4146 · Cited by 31
Sgoff, C., Acevedo, W., Paschalidi, Z., Ulbrich, S., Bauernschubert, E., Kratzsch, T., & Potthast, R. (2022) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.4276 · Cited by 18
Metadata
- Authors
- Muller, C. L., Chapman, L., Johnston, S., Kidd, C., Illingworth, S., Foody, G., Overeem, A., & Leigh, R. R.
- Venue
- International Journal of Climatology
- Publisher
- Wiley
- Published
- 2015-01-05
- Volume
- 35
- Issue
- 11
- Pages
- 3185-3203
- ISSN
- 0899-8418 (ISSN-L)
- 1097-0088
- OpenAlex
- W2161448838
- Cited by
- 372
- References
- 4
- FWCI
- 52.27
- Type
- journal article
- Language
- en
- Open access
- bronze
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