Field Activity #1: Creation of a Digital Elevation Surface

Introduction:
For our first lab assignment we were instructed to create a Digital Elevation Model of features within a sandbox model. We were given minimal guidance on how to complete the task, which required us to think critically to develop our own methods and solve problems as they arose. Our methods involved sculpting features in our sandbox, followed by creating a coordinate system. This allowed us to collect elevation data and associate it with a precise X and Y location within our study area. With this data we will be able to replicate the landscape features as a 3D model.

Methods:
On September 18, 2015, my two partners and I gathered our supplies and headed to our study area located in the flood plain of the Chippewa River, within the campus of the University of Wisconsin-Eau Claire. At 1:30pm, we chose a location under the walking bridge that had a sufficient amount of moldable sand. As we set up our 122cm x 114cm box, we attempted to level out the sand beneath it to the best of our ability by using a leveler at each side length and corner of the box. Following this step, we constructed a ridge, valley, hill, plain, and a depression in the sand within the box.

Molding our landscape

 

Our landscape that includes a ridge, valley, hill, plain, and a depression.

 

 

Knowing that the inside space of our previously constructed box had the dimensions of 122cm x 114cm, we decided to make a string grid of boxes with the dimensions of 8cm x 8cm. Using a measure stick to measure our columns and row, and pushpins to hold our string grid in place, we designed a coordinate system that contained 15 squares x 14 squares.



Our coordinate system grid, made by using string and pushpins.

Next, we labeled one side X and the other Y. Each column and row was then labeled with continuous number scale to create our coordinate system. The X variable had values ranging from 1-14, and the Y variable had a values ranging from 1-15. In this case, the x, y values recorded in the table represent a location in the grid. Once we had the coordinate system labelled on the box, we collected the distance value from the surface of the sand to the string above in the top right corner of each grid square. We considered the sting’s level to be at level 0, similar to sea level, where an elevation recorded beneath the string receives a negative value, and any elevation above the string would receive a positive value. In our model, all of our elevations were below the string, and therefore had negative values.

Casey measuring the Z value on an individual grid square.

Collecting X, Y, and Z values while entering them in the computer.

A portion of our data table, including X, Y, and Z values.

Discussion:
In general, the project went well. We successfully constructed our own coordinate system for our sandbox model, and gathered over 210 data points. Although we did complete the assigned lab, the methods took longer than expected due to a few unexpected issues. These issues required us to think critically and work together to develop solutions in a timely matter.

As previously stated, leveling the box was more difficult than we assumed it would be. We used the resources we had to make our best attempt, however it is difficult to say how accurately the box was initially leveled.

Another problem we ran into was deciding the dimensions of our grid boxes. We realized our box’s side lengths were not perfectly divisible by practical grid square dimensions, which required us to have one column and one row of grid squares with the remaining smaller side lengths. To overcome the issue, we made the decision to not collect data points within these smaller squares in order to keep our coordinate system grid as accurate and consistent as possible.

While collecting our Z values for elevation, we became aware of an issue dealing with data accuracy. To keep the measurement collection consistent and unbiased, every Z value was collected at the top right corner of each grid square. Due to this, the surface elevation measured within that corner was recorded as the elevation of that entire square. Although 8cm x 8cm squares did not seem oversized, they were large enough to contain a surface with varying elevations. Here I saw firsthand how using this method to collect Z values generalizes the squares surface information, which I imagine can lead to potential data accuracy errors. Using smaller grid squares in the coordinate system could possibility alleviate the issue, however would require more time and resources.  

Lastly, we experienced the unpredictability of fieldwork due to weather conditions. We had to postpone our meeting time to later in the week due to heavy rain, which required all group members to be flexible.

Conclusions:
By creating our own digital elevation model, we were required to create our own methods of surveying our study area. This required us to think critically and geospatially to determine the best fit methods. Our group successfully designed a way to collect elevation data within our sandbox model using our unique coordinate system. This lab required team work, creativity, geospatial thinking, flexibility, and patience. Overall, our group is happy with the outcome of our project and expects to generate a 3D model of our data in a future lab using ArcMaps.