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Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions
Reviews of Geophysics ( IF 25.2 ) Pub Date : 2018-12-01 , DOI: 10.1029/2018rg000616
Feifei Zheng 1 , Ruoling Tao 1 , Holger R. Maier 1, 2, 3 , Linda See 4 , Dragan Savic 5, 6 , Tuqiao Zhang 1 , Qiuwen Chen 7 , Thaine H. Assumpção 8 , Pan Yang 9, 10 , Bardia Heidari 10 , Jörg Rieckermann 11 , Barbara Minsker 12 , Weiwei Bi 13 , Ximing Cai 10 , Dimitri Solomatine 8, 14, 15 , Ioana Popescu 8
Affiliation  

Data are essential in all areas of geophysics. They are used to better understand and manage systems, either directly or via models. Given the complexity and spatiotemporal variability of geophysical systems (e.g., precipitation), a lack of sufficient data is a perennial problem, which is exacerbated by various drivers, such as climate change and urbanization. In recent years, crowdsourcing has become increasingly prominent as a means of supplementing data obtained from more traditional sources, particularly due to its relatively low implementation cost and ability to increase the spatial and/or temporal resolution of data significantly. Given the proliferation of different crowdsourcing methods in geophysics and the promise they have shown, it is timely to assess the state of the art in this field, to identify potential issues and map out a way forward. In this paper, crowdsourcing-based data acquisition methods that have been used in seven domains of geophysics, including weather, precipitation, air pollution, geography, ecology, surface water, and natural hazard management, are discussed based on a review of 162 papers. In addition, a novel framework for categorizing these methods is introduced and applied to the methods used in the seven domains of geophysics considered in this review. This paper also features a review of 93 papers dealing with issues that are common to data acquisition methods in different domains of geophysics, including the management of crowdsourcing projects, data quality, data processing, and data privacy. In each of these areas, the current status is discussed and challenges and future directions are outlined.

中文翻译:

地球物理学数据收集的众包方法:现状、问题和未来方向

数据在地球物理学的所有领域都是必不可少的。它们用于直接或通过模型更好地理解和管理系统。鉴于地球物理系统(如降水)的复杂性和时空变异性,缺乏足够的数据是一个长期存在的问题,气候变化和城市化等各种驱动因素加剧了这一问题。近年来,众包作为补充从更传统来源获得的数据的一种手段变得越来越突出,特别是由于其相对较低的实施成本和显着提高数据的空间和/或时间分辨率的能力。鉴于地球物理学中不同众包方法的激增及其所显示的前景,现在评估该领域的最新技术是及时的,找出潜在的问题并制定前进的道路。在本文中,基于对 162 篇论文的回顾,讨论了基于众包的数据采集方法,这些方法已被用于地球物理学的七个领域,包括天气、降水、空气污染、地理、生态、地表水和自然灾害管理。此外,还介绍了一种对这些方法进行分类的新框架,并将其应用于本综述中考虑的七个地球物理学领域中使用的方法。本文还回顾了 93 篇涉及地球物理学不同领域数据采集方法常见问题的论文,包括众包项目的管理、数据质量、数据处理和数据隐私。在这些领域中的每一个领域,都讨论了当前状况,并概述了挑战和未来方向。
更新日期:2018-12-01
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