Over the last four years we have discussed some of the many challenges posed by the volume of data now available online – issues of quality, determining provenance, privacy, identifying the most appropriate source for particular requirements and so on. Being overwhelmed by the choice of data available or not always knowing what resources are available or where to start looking have been common responses from geospatial students and practitioners alike.
A recent report from the BBC on laser technology highlighted some current and future applications that have or will transform geospatial data capture, including the use of LiDAR and ultra precise atom interferometers that could be used to develop alternate navigation systems that do not rely on GPS. The article also discusses the inherent limitations of our current electronics-based computing infrastructure and the potential of silicon photonics, firing lasers down optical fibres, to help meet the demand for instant or near-instant access to data in the Internet-of-Everything world. If many feel overwhelmed now by the volumes of data available, what will technologies like silicon photonics mean for data practitioners in the future? Just because data may be available at unprecedented speeds and accessed more easily, that alone doesn’t guarantee the quality of the data will be any better or negate current concerns with respect to issues such as locational privacy. A critical understanding of these issues will be even more important if we are to make the most of these advances in digital data capture and transmission.
Recently, while at the Applied Geography Conference in Atlanta, I decided to test the spatial accuracy of my smartphone’s GPS in a challenging environment–a rooftop running track. Although located on a roof, the track was surrounded by buildings far taller, and in downtown Atlanta, a location with many other buildings impeding signals from GPS, wi-fi hotspots, and cell phone towers. A further challenge to the GPS positional accuracy was that each lap on the track was only 0.10 miles (0.16 km), and therefore, I would not travel very far across the Earth’s surface.
After an hour of walking, and collecting the track on my smartphone with a fitness app (Runkeeper), I uploaded my track as a GPX file and created a web map of it in ArcGIS Online. As I expected, the track’s position was compromised by the tall buildings–I only had a view of about half the sky during my time on the roof. As you can measure for yourself on the map linked above, the track lines formed a band about 15 meters wide, but interestingly, were more spatially precise along the eastern side of the track, where the signal was better, as you can see in my video that I recorded at the same time.
Also, as I have encountered numerous times in the past, a line about 100 meters long stretches to the north. Rest assured that I did not leap off the building, but rather, the first point that the GPS app laid down as I opened the doors to walk outside was about a block away. Then, as I remained outside, the points became more accurate. When you collect data, the more time you spend on the point you are collecting, typically the more accurate that point is spatially.
Another interesting aspect of this study is that if the basemap is changed to satellite imagery, it appears that the track overlaps the tall building to the west. Try it, using the map link above. However, a closer investigation reveals that this is a result of the orthocorrection that was performed on the imagery; the buildings do not appear from “straight overhead”, but rather, they “fall away” to the east. Turn this into another teachable moment: Images, like maps, are not perfect, but they are very useful. We can learn to manage error and imperfection through critical thinking and through the use of geotechnologies. This is a central topic of our book and of this blog.
To dig deeper into issues of GPS track accuracy, see my related post on errors and teachable moments in collecting data, and on comparing the accuracy of GPS receivers and smartphones and mapping field collected data in ArcGIS Online here and here.
Despite these challenges, overall, I was quite pleased with my track’s spatial accuracy, even more so considering that I had the phone in my pocket most of the time I was walking.
Almost a year ago we posted a review on the Internet of things, an emerging global network of internet-connected devices and sensors, so with the end of 2013 fast approaching it seems like a good time to see how things have developed over the last 12 months and what 2014 and beyond has in store for us. In his article How the internet of things will replace the web Christopher Mims predicts that the internet will change beyond all current recognition, with the role of the web reduced to displaying content. Although the dominant ‘species’ of the internet of things is currently the smartphone, with the latest versions kitted out with sensors and apps for tracking and monitoring many aspects of our lives, wearable technology – smart watches, wristbands, glasses, even temporary tattoos – will become increasingly prevalent as personal sensors and the medium for controlling the connected devices around us.
Accompanying these developments in the available devices are significant improvements in the levels of accuracy in location tracking with versions of GPS technology, such as Apple’s iBeacon technology, that work indoors. With this increasing accuracy comes the emergence of ‘invisible’ or ‘spatial’ buttons, which according to Amber Case (Esri) are simply locations in space in which some response is triggered when a person or a device enters that space. For example, walking into or out of a room automatically turns the lights on/off, or turning on the security system when you leave home. Needless to say, the potential for using this type of technology as a marketing tool hasn’t been missed. British Airways has already launched a new campaign called ‘Look Up‘ with an interactive billboard in London informing passers-by what aircraft is passing overhead and current deals on that particular route.
Along with the changing role of the web, Mims also discusses the emergence of what some refer to as anticipatory computing, as the internet develops from simply responding to requests to anticipating those requests based on past location, actions and preferences. As with most technical innovations, there will be both benefits and costs; the benefits should mean we have much more control over the resources we use, the cost will be having to make a lot of our personal information available to make this happen.
A theme running throughout our book The GIS Guide to Public Domain Data is to be critical of the data that you are using–even data that you are creating. Thanks to mobile technologies, anyone can create spatial data, even from a smartphone, and upload it into the GIS cloud for anyone to use. This has led to incredibly useful collaborations such as Open Street Map, but this ease of data creation means that caution must be employed more than ever before.
For example, analyze a map that I created ) using Motion X GPS on an iPhone and mapped using ArcGIS Online. It is shown below, or you can interact with the original map if you prefer. To do so, access www.arcgis.com/home (ArcGIS Online) and search for the map entitled “Kendrick Reservoir Motion X GPS Track” or go directly to http://bit.ly/Rx2qVp. Open the map. This map shows a track that I collected around Kendrick Reservoir in Colorado USA. This map was symbolized on the time of GPS collection, from yellow to gradually darker blue dots as time passed.
Note the components of the track to the northwest of the reservoir. These pieces were generated when the smartphone was just turned on and the track first began, indicated by their yellow color. They are erroneous segments and track points. Notice how the track cuts across the terrain and does not follow city streets or sidewalks. Change the base map to a satellite image. Cutting across lots would not have been possible on foot given the fences and houses obstructing the path. When I first turned on the smartphone, not many GPS satellites were in view of the phone. As I kept walking and remained outside, the phone recorded a greater number of GPS satellites, and as the number of satellites increased, the triangulation was enhanced, and the positional accuracy improved until the track points mapped closely represented my true position on the Earth’s surface.
Use the distance tool in ArcGIS Online to answer the following question: How far were the farthest erroneous pieces from the lake? Although it depends on where you measure from, some of the farthest erroneous pieces were 600 meters from the lake. Click on each dot to access the date and time each track point was collected. How long did the erroneous components last? Again, it depends on which points you select, but the erroneous components lasted about 10 minutes. At what time did the erroneous track begin correctly following my walk around the lake? This occurred at 11:12 a.m. on the day of the walk.
This simple example points to the serious concern about the consequences of using data without being critical of its source, spatial accuracy, precision, lineage, date, collection scale, methods of collection, and other considerations. Be critical of the data, even when it is your own!