GIS and mapping projects vary in size, difficulty and complexity and the increase in freely available spatial data and consumer grade GPS units has heightened the profile of geographic data and changed the expectations of relative accuracy at different scales. Geospatial companies, government agencies and universities have largely been responsible for the creation of spatial data and the implementation of GIS projects, however, the participatory and community-based mapping movement has reduced the reliance on these traditional sources (Fox, Suryanata, and Hershock 2005).
Participatory spatial mapping has been recognized as a practical tool for many natural resource management applications and the advancements in desktop GIS and personal GPS technologies have further allowed for a range of stakeholders to participate in data collection (Chambers 2006). Community-based mapping projects that allow multiple stakeholders to participate in data collection and mapping have focused on the assessment of community vulnerability in disaster management (Morrow 1999; Jing, Liu, and Gang 2013), environmental conservation mapping (Wood 2005; Roth 2007) and indigenous knowledge and community values mapping (Wilson 2007). More recently, the high participation needs of watershed management and river/stream monitoring programmes has demonstrated that data quality and data accuracy do not have to be rigorous to satisfy the more descriptive and inventory-based needs of management and decision-making at these scales (Glockner, Mkanga, and Ndezi 2004).
Inventories for stormwater management purposes have traditionally been developed through GIS-based facility management that required commercial quality GPS readings for public works to map the exact spatial location of manholes and gullies (Cabuk, Eren, and Ozcan 2002). The role of quality assurance procedures in the project development stages of a GIS for stormsewer inventories now provides a high level of redundant data and repeatability resulting in greater accuracy over time. The introduction of more participatory approaches to mapping and stormwater management (Liebl 2010), such as those that incorporate water sensitive urban design (Roy et al. 2008) requires spatial and temporal information about the conditions of tributaries and stormwater infrastructure. Hartman (2002) used GPS technology in a stormwater inventory to determine the conditions of stormwater inlets in Kansas City Missouri. Planners themselves were able to walk the streets with hand-held devices and digital cameras and enter data related to the type of maintenance and management actions required. The use of more detailed attribute data further allows for a greater range of acceptable positional error from buildings and trees that could be reduced over time (Cobb 2003).
Consumer grade GPS units have been successfully utilized in numerous research studies for field data collection (Duncan, Mummery, and Dascombe 2007; Tougaw 2002; Miluzzo et al. 2008). Consumer grade GPS units are available in a range of devices, including automobile navigation units, personal audio devices and cellular devices. Cellular phones with GPS accessibility have been used to help understand adolescent social and health-related patterns (Wiehe et al. 2008) and user activities with the combination of GPS and accelerometer within the cellular phone (Kwapisz, Weiss, and Moore 2010). The insurgence of smart phones into everyday life for a large portion of the population has provided a tool for researchers to gain location-based information related to human behaviour and daily patterns (Ashbrook and Stamer 2002; Zhao 2000; Miluzzo et al. 2008; Lester et al. 2008). The introduction of Apple's touch technology (i.e., iPhone, iPod Touch and the iPad) further provides users with a relatively inexpensive mobile field collection device with GPS capabilities, built-in camera and georeferencing software, and the ability to develop customized inventory applications and drop-down lists that make field collection for a range of local stakeholders more adaptable.
Smart phones that have GPS technology provide an excellent tool for collecting spatial information of a population or place, without the need for intrusive and cumbersome data collection devices. However, there is a gap in our understanding of the suitability of these devices for a wider range of uses that may require a smaller margin of GPS error. A comparison of consumer grade hand-held GPS units with Apple's Touch technology devices with a GPS option was conducted. Garmin and Apple products were chosen as these devices are targeted towards individuals based on their relative ease of use and functionality. The goal of the research was to provide insight into the relative accuracy of consumer grade GPS technology and newly developed Apple touch products for the use of field data collection. Understanding the relative accuracy of the devices will provide information for researchers who conduct research in an urban landscape with the need for spatial data collection.
There has been significant GPS testing conducted, primarily with differential GPS units (Serr, Windholz, and Weber 2006). GPS-related research has been conducted on assessing consumer grade GPS receivers, iPhone 3G devices and GPS accuracy within urban environments.
Modsching, Kramer, and Hagen (2006), Mezentsev et al. (2002), Melgard and Gehue (1994) collected research related to GPS accuracy in urban environments. Modsching, Kramer, and Hagen (2006) used four different GPS receivers to collect GPS information along four defined urban routes. GPS data were collected at 706 different locations along the four routes, resulting in an average of 4149 GPS points per collection route. A mean error of 24.5 meters was calculated for each urban route. Melgard and Gehue (1994) research collected GPS information in two urban situations; around buildings up to 50 storeys, and in residential areas around two-storey buildings in Calgary, Alberta. The accuracy assessment resulted in positional accuracy ranging from less than 5 meters to 50 meters. Mezentsev et al. (2002) collected GPS data in the urban core of Calgary, Alberta, where buildings ranged from 50 to 210 meters in height. Data were collected along five driving loops in Calgary, with a two-minute break between each loop. Data were collected while driving the urban loop at speeds not exceeding 70 km/hr. The average error was less than 20 meters, with the maximum error around 75 meters.
Wing, Elkund, and Kellogg (2005) focused on evaluating the accuracy of consumer grade GPS units in a forest environment. Wing, Elkund, and Kellogg's (2005) data collection methodology consisted of three measurement courses and six measurement stations, consisting of open sky, young forest and closed canopy environment conditions. Wing, Elkund, and Kellogg (2005) collected 25 data points at each location, at a four-second interval. The collection method was repeated five minutes after the first collection process, resulting in 450 collection points for each consumer grade GPS device, for a total of 2700 collection points. Collection points from...