Journal of Structural Geology 102 (2017) 98e112 Contents lists available at ScienceDirect Journal of Structural Geology journal homepage: www.elsevier.com/locate/jsg Structural data collection with mobile devices: Accuracy, redundancy, and best practices * Richard W. Allmendinger , Christopher R. Siron, Chelsea P. Scott 1 Dept. of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, 14850, USA article info abstract Article history: Smart phones are equipped with numerous sensors that enable orientation data collection for structural Received 12 May 2017 geology at a rate up to an order of magnitude faster than traditional analog compasses. The rapidity of Received in revised form measurement enables field structural geologists, for the first time, to enjoy the benefits of data redun- 19 July 2017 dancy and quantitative uncertainty estimates. Recent work, however, has called into question the reli- Accepted 27 July 2017 ability of sensors on Android devices. We present here our experience with programming a new smart Available online 2 August 2017 phone app from scratch, and using it and commercial apps on iOS devices along with analog compasses in a series of controlled tests and typical field use cases. Additionally, we document the relationships Keywords: Smartphone between iPhone measurements and visible structures in satellite, drawing on a database of 3700 iPhone Compass measurements of coseismic surface cracks we made in northern Chile following the Mw8.1 Pisagua Orientation earthquake in 2014. By comparing phone-collected attitudes to orientations determined independently Accuracy of the magnetic field, we avoid having to assume that the analog compass, which is subject to its own Redundancy uncertainties, is the canonical instrument. Our results suggest that iOS devices are suitable for all but the most demanding applications as long as particular care is taken with respect to metal and electronic objects that could affect the magnetic field. © 2017 Elsevier Ltd. All rights reserved. 1. Introduction without data redundancy, it is impossible to evaluate the signifi- cance and accuracy of a measurement. Thus, the ideal case would Structural geology has always suffered from a relatively small be to make lots of measurements of high accuracy and well number of recorded, quantitative measurements. A field geologist established uncertainty quickly enough that one can still visit many working with a traditional analog compass and paper field note- localities. book typically records a few tens of orientation measurements per Smart phone compass/stereonet programs (“apps”) will very day. Not only are the total measurements small in number, but likely replace traditional analog compasses (Brunton, Freiberg, repeat measurements of sufficient quantity to establish statistical Silva, etc.) because of convenience, cost, and ubiquity but mostly uncertainty are extremely rare in the published literature. Why because of their rapidity. The ability to record orientation along bother to make tens of measurement of a single bedding surface at with location (latitude and longitude or UTM) and date/time with a a single site when doing so would severely limit the number of single tap of an on-screen button reduces the amount of time that it outcrops we could document in a day? As Ramsay and Huber wrote takes to make a measurement. For timed tests on the same outcrop with respect to strain measurements 35 years ago (Ramsay and comparing analog compass and traditional paper note book to Huber, 1983, p. 78), “it is often more rewarding to spend time in smart phone measurement and recording, the latter was about nine the field collecting a lot of data of relatively low degree of accuracy times faster. If many more measurements can be made in the same at many localities, rather than to concentrate on obtaining a few period of time, then field geologists can begin to enjoy the benefits strain data with an extremely high degree of accuracy.” However, of data redundancy that simply are not feasible with analog in- struments. Additionally, in every cash-strapped geology depart- ment, the question will be, or is already being, asked: “why should * Corresponding author. we invest thousands of dollars in analog compasses when many E-mail address: [email protected] (R.W. Allmendinger). students already have a smart phone at their disposal?” 1 Now at: School of Earth and Space Exploration, Arizona State University, Tempe, The enthusiasm for smart phone orientation measurement apps AZ, USA. http://dx.doi.org/10.1016/j.jsg.2017.07.011 0191-8141/© 2017 Elsevier Ltd. All rights reserved. R.W. Allmendinger et al. / Journal of Structural Geology 102 (2017) 98e112 99 was recently dampened somewhat by Novakova and Pavlis (2017) magnetic fields, especially from other components within the de- as well as earlier studies (e.g., Hama et al., 2014; Mookerjee et al., vice such as the power supply, etc., so that the orientation with 2015) that demonstrate considerable variation in quality of device respect to magnetic north can be determined. Dip measurements sensors and accuracy of recorded observation. Most conclude that collected with smart phones are generally much more accurate the least reliable sensor is the device magnetometer which likewise than strikes because the magnetometer is much more sensitive to, accords with our experience. However, comparisons in previous and local perturbations more common in, the local magnetic field studies tend to be incomplete or misleading in assessment of ac- than in the local gravity field. The dip of the device can be deter- curacy because: only one operating system (i.e., Android or iOS) is mined from the three components of the acceleration due to tested, multiple devices are not used in testing, the details of the gravity alone and does not have to depend on the magnetometer at algorithms used in the apps are seldom well described, the error in all. the dip is assessed separately from the error in the strike (rather Sensors in the iPhone, sampled by the Sensor Kinetics Pro app at than using poles to planes; see section S1 in the Supplementary about 30 Hz, appear to be very stable (Fig. 1) especially in com- Material), single measurements from analog compasses are regar- parison to the Android devices tested by Novakova and Pavlis (2017, ded as canonical rather than comparing multiple analog compass their Fig. 2). Nonetheless, the iPhone magnetometer is easily per- measurements to multiple smart phone apps, and there is no turbed by passing even small metal objects within several centi- assessment of accuracy that does not rely on the magnetic field. meters of the device (Fig. 1b). This behavior has considerable Here, our purpose is three fold: (1) introduce a new, free iOS implications for best practices in the field when using phones as app, Stereonet Mobile, written by the senior author2 and document data collection devices. the basics of its functioning; (2) compare Stereonet Mobile and a popular smart phone app, Fieldmove Clino, to each other and to analog compass measurements on a datum by datum and group by 2.2. Device coordinate system and determining orientation group basis; and (3) document the accuracy of app measurements independent of analog compass measurements by using a database The iOS device coordinate system and the rotations about the of >3700 measurements of surface crack measurements and three axes are shown in Fig. 2. One “reads” the face of the device 0 comparing those measurements with the same cracks visible on like a right-handed map coordinate system: the first axis, X 1,is Google Earth imagery. parallel to and in the short, or side-to-side, direction of the face ® 0 Our study, using only Apple iPhones (iOS operating system), with positive to the right. The second axis, X 2, is parallel to the face stands in contrast to Novakova and Pavlis (2017) who used only and the long axis of the device with positive toward the top of the 0 Android devices. Together, these two studies tend to suggest that phone, and X 3, the third axis, is perpendicular to the face and the four different iPhones devices used here are significantly su- positive towards the user. The change in orientations of the device perior in accuracy and reliability compared to the two tested is determined by the rotation of this coordinate system with Android devices. This conclusion has also been reached by Midland respect to a reference coordinate system. The iOS operating system Valley, the publisher of Fieldmove Clino who state, “We have provides the programmer with four different potential reference observed much larger variations in the measured data recorded frames. Stereonet Mobile uses the “CMAttitudeReferenceFrameX- using Android devices which we suspect is largely down to the TrueNorthZVertical” reference frame. That is, the rotation matrix is quality of the hardware components inside the device” (Midland equal to the identity matrix when the phone face is horizontal with 0 Valley, 2017). Our data are also consistent with the recent work of the short axis (X 1) aligned NS. To determine true north, the oper- (Cawood et al., 2017) who compared remotely sensed surface data ating system must know the device position on the globe in order (LiDAR, Structure from Motion) to both digital and analog compass to calculate magnetic declination. Thus, reading an orientation readings. However, anyone collecting irreplaceable field data with must also turn on the device GPS receiver. any electronic device will want to conduct their own tests and The change in orientation is supplied to the programmer by iOS continue to carry an analog compass in the field with them. Even in several different ways. Perhaps most common is using the Euler where a device is not reliable for data collection, many apps allow angles (Fig. 2), the pitch, roll, and yaw (sometimes known as the manual data entry, giving the user some of the benefits of the smart Tait-Bryan angles), which are familiar to anyone in aviation or phone (e.g., automatic recording of location, time, and date) boating.