GPS Topographic Survey

INTRODUCTION
In this assignment the class used a survey grade GPS to mark points in one small area on the University of Wisconsin-Eau Claire.  The GPS unit that was used, is accurate to a sub-meter.  The certain GPS that was used for this assignment was even accurate to within one millimeter.  This means that the points gathered were extremely accurate.  The points gathered were on a small hill giving the points very different elevation values.  This data for each point was placed into a text file which the students then imported into ArcGIS.  When the table was moved into ArcMap the students then made points from the XY data in the text file.  With these points the interpolation methods were then used to show the overall elevation of the location.  The interpolation methods that were used were Spline, Nearest Neighbor, Kriging, IDW, and a TIN was created (Figure 1).  (For definitions of these methods, please refer to the sandbox survey Blog post).

Figure 1:  This map shows the final product of all maps in one.  This shows the differences in the maps.  

METHODS

The data collection used an extremely accurate survey grade GPS unit, although the class ran into some minor difficulties about 20 points were still collected.  The way this area was surveyed was a random sample.  Students took the GPS unit and took points from where ever they saw fit.  This would be the best way to take a survey with nearly 20 people.  Everyone can go where ever they like and take a random point.  This also gives the students control of where they think more points should be collected.  The survey would become more accurate if more points were taken on the sides of the hill slopes.  The survey data was put into a text file.  From the text file the data was copied into excel to make a file that could be imported into ArcMap.  After the excel file was imported into arcMap the points were created using XYZ data where longitude is the X value, Y is the latitude value, and Z is the height or elevation value.  Then the interpolation methods were run to come up with the final maps.

RESULTS

According to the results more points should have been gathered around the steep sides of the slope.  In the results of this map the Natural Neighbor map came out the best and most accurate (Figure 2).  This is because of the smoothing that occurs between the different points.  This makes the map smoother and flow better.  There is much more flow in the Natural Neighbor than there is in the Spline (Figure 3) and also with the IDW (Figure 4).  The Tin image (Figure 5) shows very rough cut edges and no smoothness almost resembling a mountain.  This is obviously not accurate in this situation in the middle of the UWEC campus.  The Kriging is probably the second most accurate in this situation.  The only thing is that the hill comes to a crest and seems on the south western side to never slope back down to the sidewalk (Figure 6).

Figure 2:  This map shows the Natural Neighbor interpolation method.  This is the most accurate of the maps created.  It shows very smooth moving from point to point.

Figure 3:  This map shows the Spline method of interpolation.  This method showed the very large white portion meaning the elevation was highest here.  This map has the most white in any of the images.

Figure 4:  The IDW method shows precisely the opposite of the spline.  This map shows the smallest area of white.  This means that when the ground is only this high for a very small area.

Figure 5:  The TIN image shows the very rough areas.  This image abruptly goes from one elevation to another.  This image almost resembles a mountain.

Figure 6:  The Kriging Method shows the second most accurate of the maps created.  This is easy to see that the map very slowly and fluidly increases in elevation from the northeast to the southwest corners of the map.

CONCLUSION

These methods were the same ones that were used in the sandbox survey with different results.  This is most likely due to the fact that different survey methods were used.  The spline method produced the best looking map in the sandbox survey.  With the sandbox survey a very uniform method of sampling was used.  A point was taken at every cross in the grid pattern.  Where as in the GPS topographic survey a random sample was taken.  This could also be partly due to the fact that the class was working as one in the GPS survey rather than small groups as they were with the sandbox survey.  These maps could be much better if a stratified or a systematic sample.