Activity Two: Visualizing and Refining Terrain Survey

Introduction

Often in trying to analyze a digital elevation surface multiple methods need to be considered and utilized to come up with an accurate visualization of what exists. As a continuation of last week's grid based survey of our sandbox we revised our methods to include more selective points to better represent the valley area. After analyzing the digital elevation models from our first set of data, we realized there were not enough points to properly show the narrow valley included in our sandbox.

After the revision of the data surveying collection, different interpolation models were used to analyze the accuracy of the features within the sanbox. ArcMap and ArcScene were used to achieve this task.  

Study Area

• Date: 22 September 2015 from 3-5pm 
• Sandy bank of the Chippewea River Valley 
• Conditions: Sunny, Average temp. 65°F (retrieved from Weather Underground)

Methods

Figure 1. Original 8 x 8cm coordinate
       system, 18th Sept. 2015.

Revising the Coordinate System

Figure 1 shows the original coordinate system created 18 Sept. 2015 with the cell size of 8 x 8cm. 

The valley was too narrow to be represented by an 8 by 8cm coordinate system. 

Only x-values from Y12 to Y15 were re-recorded, because we thought the digital elevation models produced an accurate representation of our other features. 

Figure 2. Revised coordinate system 4 x 4cm from Y12 to Y15.

From Y12 to Y15 the coordinate grid was adjusted to include points every 4 by 4cm. 

Push pins were placed every four centimeters around the edge of the rectangle, and then string was wrapped around it to produce the 4 x 4cm squares. 

This area was selected because the narrow nature of the valley. The other features within the sandbox were large enough to be recognized in the original depictions of the digital elevation models. 

Figure 3. Casey Aumann recording the z-values using
the 4 x 4cm coordinate system. 

Data Collection

Again, a meter stick was used to measure the depth of the features below sea level (from the top edge of the rectangle). 

The meter stick was lowered until it was touching the sand and hovered there until a measurement could be read. The meter stick should not have gone below the surface of the sand. 







Digital Elevation Models 

We used the Natural Neighbor, Spline, IDW, and Kriging interpolation methods to analyze how well our coordinate system represented the features in the sandbox. Side by side comparisons are shown below to view the improvement of using the 4 x 4cm grid system through out the valley area. 

Natural Neighbor ( "area stealing" interpolation) 

The Natural Neighbor method places value on the cell depending on what values lie inside of it. 

Figure 4. Natural Neighbor model with
4 x 4cm coordinate system. Made in ArcScene.

Figure 5. Natural Neighbor model withoriginal 8 x 8cm 
coordinate system. Made in ArcScene.

Spline

The appearance of the spline method is smooth because it takes into account the overall surface curvature and tries to minimize it. The points go directly through the input values. 

Figure 6. Spline model from revised data
with 4 x 4cm coordinate system. Made in ArcScene.

Figure 7. Spline model from original data with
8 x 8cm coordinate system. Made in ArcScene.

IDW (Inverse Distance Weighted)

This method values the center point of the cell, making the peripheral values of the cell less important overall. 

Figure 8. IDW model from revised
data with 4 x 4cm coordinate system. Made in ArcScene.

Figure 9. IDW model original 8 x 8cm
coordinate system. Made in ArcScene.

Kriging 

Kriging places high value on the z-values of the cells. It can take many z-values and predict the surface. 

Figure 10. Kriging model 4 x 4cm coordinate
system. Made in ArcScene.

Figure 11. Kriging model 8 x 8xm coordinate
system. Made in ArcScene.

Metadata
Who: Casey Aumann, Ally Hillstrom, Morgan Freeburg
What: Grid based surveying of a sandbox with different features
When: 22 September 2015
Where: The bank of the Chippewa River underneath the UWEC footbridge
Why: To revise the technique of a grid based surveying technique


Discussion

The spline and natural neighbor interpolation methods best represented our elevation surface. The difference from the 8 x 8cm grid system to the improved 4 x 4cm grid within the valley area is clearly visible. The valley has distinct boundaries, especially with the spline. With the  Kriging method , the valley still is much improved and visible however the banks of the river are somewhat blurry and it seems the features run together. IDW does not appear as accurate for our sandbox surface either because of the pixelated nature of how it is display. The IDW is giving the surface the appearance that the features are choppy and disconnected. This is where the spline method comes in between a happy medium of the IDW and kriging. The features run smoothly together, but not so much that they are not distinct. 

The second time around as far as collecting data was simpler in the sense we knew what we needed to improve on and how to go about getting the materials and setting up. On the other hand, it did not take us any less time to collect the data.


Conclusion

We were more confident in our abilities to create and execute grid based surveying system. We did not realize we could have selectively chosen the valley area to include more points in the first trail, we thought this would inflict some bias. Looking at the surface and features that were created it only made sense to subjectively select this area for more surveying points.For this extension we challenged our critical thinking skills and were able to overcome the obstacles we had in the first activity. 

References
ESRI. (2015). Comparing interpolation methods. ArcGIS Software (Version 10.3) [Software]