Lab 2: Survey of Terrain Surface - Revisted

•   Introduction

• After completing the previous lab where a terrain was created and surveyed, This lab goes through the process of taking those survey points, putting them into GIS software and creating 3D maps using the 5 main interpolation methods. Then after comparing each method one is chosen by its closeness to the actual created terrain and additional sample points are taken and added through a stratified sampling method to create better likeness to the real terrain. 

Figure 1. data points in orange with new points in purple

•   Methods 
• Using ArcScene, the excel files of the X Y and Z coordinates that were surveyed in the previous lab were imported in and converted to points on a grid by making a point feature class and then brought to life by these 5 different interpolation methods  by creating a continuous surface along the points. This is done by simply inputting the point feature class into the interpolation methods found in the ArcToolbox. Below are the 5 interpolation methods used:
• IDW - (inverse distance weighted) This method follows the 1st rule of geography which states that things closer together are more alike than things farther away. It makes its prediction by measuring the values of the points closest to it. Seen in figure 2.
• Kriging -  Creates it's estimated surface by looking at a larger picture of the sample points and finds a more generalized value by taking in the other high and low values. Seen in figure 3.
• Natural Neighbor - Puts weighted values on the nearby sample points based on their proportionate areas and uses those subsets to create its surface. Seen in figure 4.
• Spline - generates a continuous surface by passing through all the data points  while remaining above a calculated minimum curvature. Seen in figure 5.
• TIN - (Triangular Irregular Networks) which are vector based and create a surface by triangulating the vertices of the sample points. Seen in figure 6.
• Maps were then created of each method using ArcMap.  Areas that needed extra attention and additional sampling had more data recorded by recreating the previous landscape and new points 4cm from the points to the side of it.

•   Discussion 

Figure 2. IDW Interpolation of the surface

Figure 3. Kriging Interpolation of the surface

Figure 4. Natural Neighbors Interpolation of terrain surface

Figure 5. Spline Interpolation of terrain surface

Figure 6. TIN Interpolation of terrain surface

After adding the additional points a final map was created using Spline Interpolation.

•   Conclusion 
• Over the past 2 labs a terrain including a ridge, hill, depression and valley were created out of snow in a planter box in the courtyard of Phillips science building at the University of Wisconsin, Eau Claire campus. After the creation of the landscape the systematic sampling method was was chosen to record points over a grid created with strings and pins over the landscape. The sample points were transported into Excel, ArcScene and ArcMap to create a 3D visual representation of the landscape created in order to gain a better understanding of different methods used in geospatial fieldwork and techniques, how to use and work with them in addition to knowing how and when to use the proper method or technique. Spline Interpolation seemed to fit the real terrain the best and the additional points added to the overall likeness.