Geog336: Field Activity 11: Point Features Survey Using a Dual Frequency GPS

Introduction

This lab is designed to provide experience using a survey grade GPS, which is accurate within centimeters. The mapping grade GPS can result in error of up to a meter and some projects demand precision. For example, the mapping of a cemetery could not have error of that extent as overlap of burial plots could occur. For this lab the class surveyed a small section of the campus mall (figure 1) and mapped the results.

Figure 1. Reference map for survey area

Methods

To begin this lab the components of the survey GPS were explained. The GPS itself is mounted at the top of a tripod apparatus and there is a handheld component that is blue toothed to communicate with the GPS unit. The class paired up and each pair took two sets of points. One of the members positioned the tripod where the point was to be recorded by staking the front leg into the ground and then letting out the length of the other two legs as needed to place them into the ground as well. The tripod was then leveled using a leveler that is attached to the tripod at about waist height. When the tripod is in position the partner, who is holding the handheld device records the point (figure 2). This resulted in a total of 20 points collected in a random, stratified manner that was supposed to emphasize the area of relief in the study area. The information collected was then transferred into a text file used to create a point feature class in ArcMap. The point feature class was then used to create a series of continuous surfaces using the various interpolation methods used in Field Activity 5.

Figure 2. Data collection

Results/Discussion

In the sandbox survey performed in Field Activity 4, 434 points were collected in a square meter area. Each of the interpolation methods resulted in an accurate portrayal of the surface and the merits of each interpolation method could be evaluated based on these results. In this lab, only 20 points were collected in a much larger area. The interpolation methods; IDW, kriging, and spline employ algorithms not recommended for random sampling schemes as they will result in over representation of areas more densely populated with survey points. The TIN interpolation method is not recommended for areas away from survey points. While none of the interpolations employed were not advisable for the sampling scheme used, they should have resulted in a surface representative of the actual surface. Figure 3 depicts much of the survey area, which is a mound shaped area. When compared to figures 4, 5, 6, and 7; one can see that a lack of sufficient sample points resulted in inaccurate representations in all interpolation methods. Perhaps if the number of points had only been doubled to 40, an accurate continuous surface may have resulted. Furthermore, had it been included the natural neighbor interpolation method would most likely have been the best fit for a stratified sampling scheme.