Arc Collector

Introduction

            The current state of technology has allowed for some ingenenious advancements. Computing devices have become small and compact, and are combined with more versatile abilities, opening up many new aveneus of data collection. Most people walk around with mini computers in their pockets that are capable to processing enormious amounts of data. These pocket compters, cell phones, have given geographers an unprecedented ally to be mobile and collect data. The cell phones also carry onboard an (fairly) accurate GPS, for use with navigation. Untilizing both of these advancments, the geographers and computer programers at Esri have found a way to use the cell phones interface computing abilities, screen, and GPS to produce a mobile app that allows a user to implement a project online, and access it through the devices data connection.

            The task for this project, is to gain a familiarity with Esri ArcCollector application, and produce several different micro-climate maps of the University of Eau Claire campus. For the means of this introductory project, the featureclass domains where constructed by the instructor. The different types of information for the collection process includes; wind-speed, wind direction, temperature, and dew point.

Study Area

            The area of interest for this project, is the University of Wisconsin Eau Claire campus. The campus is located in the city of Eau Claire, directly adjacent to/containing portions of the Chippewa River. The campus features environmental factors like a forested area, several fields, and a steep inclining slope acting as a boundry between upper and lower campus. On the day of collection, the date was November 9^th, and collection was carried out from 3:30pm – 5:30 pm. The temperature was an average of 58 degrees F. The assigned zone for collection for group 7 was zone 5. 

Methods

 

Figure 1: Image of devices used to collect data.
From left to right, Samsung Smartphone,
Weather Device, Compass. 

            The data is collected in points using cellular devices, employing the ArcCollector application. Using the phones GPS units, points can be collected within a spatial accuracy of between 10-15ft. A weather device was used to collect wind speed, dew point, and temperature at the time of each reading. For the same data point, a compass was used to note the direction of the wind (where it was coming from). The end product of this project resulted in 3 maps being produced. A microclimate temperature map, dew point map, wind speed and wind direction maps. The data points were interpolated into a continueous surface using the IDW technique, which assumes cells that are closer should be more heavily weighted to be a similar quantity. For this interpolation, the power was increased to 4 because the AOI is realativly small, and the cell search radiious neightbor hood was decreased from the standard to further define the mirco climates that may exist on the campus. All the maps produced are displayed on top of a arial image (latest year taken) of the study area.

Results

A. Temperature is represented in the surface as a spectrum of red/brown to teal blue. Red/brown represents the high end of the temperature specture, and teal blue to low.

Figure 2: Campus map of Temperature.

B.

Dew Point

Dew point was a maesurment that was collected, in aim to make a visual distinguishing mark between cement and concerte areas, and grassy or forested areas.  For this map, IDW interpolation was used with the same characteristics as specified before.

Figure 2: Campus map of Relative Dew Point

C.

Wind speed and direction was taken with each point collection. The direction was taken using an azimuth direction on a compass.

Figure 3: Campus map of wind speed and wind direction

Discussion

            This project is a great example of how the versatile field of geography finds new solutions to the age old task of how to collect data. The ability to use a previously existing computational platform (cell phone), and apply a online collection platform, allows users to compile vast amounts of data remotely, utilizing the cells phones screen, GPS, and hardware. This platform fit this project perfectly, allowing a class full of young geographers collect data simultaneously to compile a dynamic map displaying the findings. The collection process was facilitated by a previously compiled map project, with domains controlling the acceptable answers for each of the categories. The output maps are a product of a data collection process that is very much the future of technical geography, and a valuable skill to learn.