Grassy Knoll Assignment

Introduction:

This lab was designed to teach the user how to use a dual frequency survey GPS to collect data and create continuous rasters in ArcMap with the data collected. The lab was centered right in the middle of campus and used a familiar land feature to make the students comfortable with the equipment.

Study Area:

Figure A: the study area denoted by the red rectangle in the middle of UWEC campus.

Methods:

Using the dual frequency survey grade GPS on a small grassy knoll on campus mall, the group was able to get 19 data points (Figure B below) The students broke up in to groups of 2 so each person could learn how to use the equipment effectively. Each group gathered at least 2 GPS points that had X,Y,Z data. This is done by first leveling the tall GPS post with its 3 legs. Then gather the point on the handheld touch screen GPS monitor. The class gathered data points at random, meaning the class used a stratified sampling method. The data was compiled into a text file and given to the class by our professor. Individually each student had to normalize the data. After having an X, Y, and Z column it was time to import the table to ArcMap. From there a feature class was created from the XY data ready to be interpolated. 5 rasters were created for the 5 types of interpolation, IDW, Kriging, Natural Neighbor, Spline, and TIN. From there the rasters were then put into ArcScene to be viewed as 3 dimensional.

Figure B: Dr. Hupy teaching us the ins and outs of the survey grade GPS

Results/ Discussion:

The Interpolations ran smoothly without a hiccup, and were translated successfully in ArcScene.

Figure C: IDW interpolation

The IDW interpolation put too much emphasis on the low points and high points giving the almost level parts divots and the top of the hill a point. Neither of which exist in real life.

Figure D: Kriging Interpolation

The kriging gave a very accurate representation of the hill, nice and steady slope and even shows where the slope is most drastic.

Figure E: Natural Neighbor Interpolation

Nearest neighbor was great because, not the best, however it did use the outer most points to make the shape of the actual area we were dealing with and not a rectangle.

Figure F: Spline Interpolation

Spline worked quite well in accurately showing how the hill wasn't perfectly even. It showed the wave of the base of the hill nicely.

Figure G: TIN Interpolation

The TIN was great as it used triangles to show depth and variation. It really shows the slope better than the others, however it makes it seem more drastic and puts a point at the top of the hill.

Conclusion:

This field assignment was great in teaching the class how to really use a survey grade GPS, as we had tried to do in the first week but failed due to time problems. These skills can be transferred to the real world easily because a GPS unit like this is quite common for gathering data. The technology worked very well and the rain didn't stop our class from learning well.