EAGER: Evaluating the Accuracy of Digital Compass Measurements on Mobile Devices

移动设备正在彻底改变地球科学家处理实地研究的方式，正在开发的新技术与前几代人使用的方法有很大不同。例如，许多智能手机和平板电脑内置的硬件允许这些设备充当数字地质罗盘。数字测量的易用性和速度似乎代表了在野外使用模拟地质罗盘的明显优势。然而，初步调查表明，数字罗盘应用程序可能无法提供专业野外地质学家所需的准确性。为了解决这些问题，该项目将对在移动设备上使用数字罗盘与模拟罗盘进行定位测量的相对精确度进行统计评估。该项目将产生对所有使用地质罗盘进行定向测量的地球科学家产生影响的结果，因此，跨地球科学学科的潜在影响是巨大的。该项目将利用学生的设施和移动设备，使他们成为现场数据的主要收集者。高级地质学课程的学生将同时使用模拟罗盘和数字罗盘进行方位测量，然后将其用于统计评估数字罗盘与模拟罗盘测量的相对精度。研究人员将评估他们数据集中的统计差异，包括平台之间的差异，现场不同位置观察员测量的内部差异，以及同一表面上重复测量的差异。统计分析，如Fisher分布和Watson-Williams分析，以及Bland-Altman检验，将应用于现场数据集。研究人员将评估测量类型和软件之间的差异和一致性的大小；跨测量、平台和软件的差异是否存在任何系统性趋势；以及评估跨收集的现场数据范围的测量的一致性。除了研究的实际方面，该项目还将通过吸引本科生参与该项目，为STEM(科学、技术、工程和数学)教育做出贡献。

Mobile devices are revolutionizing how geoscientists approach field-based research, and new technologies are being developed that are significantly different from methods used by previous generations. For example, hardware built into many smart phones and tablets allow these devices to function as digital geologic compasses. The ease of use and speed of taking digital measurements seem to represent distinct advantages over using an analog geologic compass in the field. However, preliminary investigations suggest that digital compass apps may not provide the accuracy that a professional field geologist needs. To address these concerns, this project will statistically evaluate the relative accuracy of orientation measurements using digital compasses on mobile devices as compared with analog compasses. This project will produce results that impact all geoscientists that use geologic compasses to take orientation measurements, and as such, the potential impacts across geoscience disciplines are substantial. The project will tap into students' facility with mobile devices to make them the primary collectors of field data. Students in upper-level geology courses will take orientation measurements with both analog and digital compasses, which will then be used for statistical evaluations of the relative accuracy of digital vs. analog compass measurements. The researchers will assess statistical variation in their datasets to include variation between platforms, variation within measurements by observers on different locations in the field, and variation in repeated measurements on the same surface. Statistical analyses, such as Fisher distribution and Watson-Williams analyses, and Bland-Altman tests, will be applied to the field datasets. The researchers will assess the magnitude of the discrepancy and limits of agreement between types of measure and software; the existence of any systematic trends in variation across measurements, platforms, and software; as well as evaluate the consistency of measurement across the range of collected field data. In addition to the practical aspects of the research, the project will contribute to STEM (science, technology, engineering, and mathematics) education by the engagement of undergraduate students in the project.