The Process of creating a Digital Elevation Surface

Introduction

The task of creating a digital elevation surface involves the application of numerous concepts of geospatial thinking. Although there are many ways to conduct a digital terrain analysis, the students in groups of three were required to use their imaginations on what procedure to take to come out with the final product. The objective of this project is to construct an elevation surface of terrain in one of the garden planter boxes in the courtyard outside of the Phillips science building by using an improvised survey technique. This exercise also requires that the group revisits the study area after the initial survey to assess where data in the terrain is lacking based off the results of the interpolation techniques conducted in the program ArcMap. Each surface needed to contain a ridge, hill, depression, valley, and a plain in the newly created terrain. This report will include a step by step description of the methods on the initial surveying technique that was applied to the study area, data entry, interpolation techniques used in ArcMap, the changes implemented in the second survey, and an evaluation on the success of the project's experience.  

Methodology

There are numerous steps in creating a Digital Terrain Model (DTM) of an area. This study gave the class an opportunity to split up into groups of three and create an original landscape in the 4 feet by 8 feet garden planter boxes outside of the Phillips science building using any improvised material. The project is laid out in the following methods: conducting a survey of the study area, creating the terrain model with GIS software using several interpolation techniques, assessing the model for errors, revisiting the site to correct those errors with another survey, and recreating the surface using the best interpolation method for the data.
Before implementing the initial survey technique on the study area, our group had to create the terrain inside the planter’s box based on the study’s criteria which include a ridge, hill, depression, valley, and plain. To fulfill this objective, the group gathered up piles of powder snow and even broke apart snow/ice from pre-existing snow piles to solidify the mountains and ridges in the area of interest. Figure 1 shows all of the five landforms that were included in the terrain.

Figure 1: Constructed Terrain with the Five Landforms

The materials in group 2’s planter’s box include the following: thumb tacks, string, one-meter measuring sticks, pen, and paper for recording the measurements. Once the group started to construct the terrain and implement a survey method, more materials were found in the surrounding environment such as the snow, ice, and 2 by 4 inch pieces of wood. Ideas for utilizing these objects came to the group in the process of pondering how to employ a survey technique, which reflects the ability to think critically and improvise in the field.
In conducting the initial survey of the terrain, our group decided to implement a regularly spaced stratified grid-sampling scheme as the coordinate system. Since the box has a width of approximately 110 centimeters (under 4 feet) and a length of 240 centimeters (~8 feet), we decided to measure each point at 10 centimeter increments on the x and y axis. The short side served as the x-axis and the longer side served as the y-axis of the garden planter’s box. One of the corners on the south side was chosen to be the origin for the coordinate system.
The thumb tacks were used in the survey technique by placing them on the x-axis 10 centimeters apart from one another. The placing of the thumb tacks in these locations helped serve as points to wrap the string around on each side of the planter’s box, which also extends the entire length of the study area and creates a grid over the newly formed terrain. Figure 2 shows the spots of the thumb tacks on the x-axis, which are measured 10 centimeters apart.

Figure 2: Placing of the Thumb Tacks 10 centimeters apart

After a string is tied around each thumb tack forming lines across the length of the box, the next step is to use two 2 by 4 inch pieces of wood that are placed on the long sides (y-axis) of the study area. Each piece of wood was placed on top of the walls on the y-axis of the planter’s box parallel from each other so that a thumb tack could be placed on the ends of each one and then be connected by a string stretching across the study area. This allowed the group to have a mobile x-axis to measure an elevation at every 10 centimeter increment that the line crossed the y-axis. The height of this string shown in Figure 3, would serve as the Z value (height elevation) of the terrain, which was recorded at each intersection to the nearest centimeter with the 11 rows of string that stretch the length of the study area. The boards would then be shifted down 10 centimeters to take another set of measurements. This process was repeated until the Z values for the entire terrain was measured at each location.

Figure 3: Measuring the Elevation of the Terrain

The last step in our initial survey is to enter in the X, Y, and Z values in to Microsoft Excel. Since the measured Z values are negative from the height of the string across the planter’s box, we subtracted 25 centimeters from each value. We decided that 25 centimeters from the string would serve as sea level because before our group created the surface, the land was about 10 centimeters down from the top of the box wall and the pieces of wood were 15 centimeters on their sides. This process will give the data a positive above sea level value and fix the problem of inverted values. Figure 4 shows a sample of the recorded Z values that were manually entered into Excel.

Figure 4: Z values of the study area in Excel

The second method is to import the data into ArcMap and create a terrain model using the following five interpolation methods: IDW, Natural Neighbors, Kriging, TIN, and Spline. IDW or Inverse distance weighted assumes that the variable being mapped decreases in influence with distance from its location that it was sampled from. Natural Neighbors interpolation method uses the closest input sample points to a query point and gives them weights based on proportionate areas to interpolate a value. One downfall of this method is that it does not produce peaks, pits, ridges, or valleys that are not already represented by the input samples. This is a disadvantage for our terrain as it includes most of these features and is not measured in detail with the coarse coordinate system we implemented in the first survey. Kriging generates an estimated surface from a scattered set of points with Z-values. This method is similar to IDW, however it also gives a measure of accuracy of the predictions whereas IDW does not. TIN (Triangulated irregular network) is an old interpolation method to represent a given surface. Our group found that this was the worst method out of the five to represent the data for the terrain. Not only did it take the computer a long time to process the tool, but it did not show up well on the screen when it was complete. The last interpolation method called spline estimates values using an algorithm that results in a smooth surface that passes exactly through the input points. After running the tool in ArcMap, our group decided that this method shown in Figure 5 best represents the data.

Figure 5: 1st Survey: Digital Terrain Model using the Spline Interpolation Method

After our group chose Spline as the favorable interpolation method to represent the terrain model, we decided to go back and resurvey the study area to make sure we were not lacking anything in our data. We still used the same survey technique as before, however we changed the coordinate system to measure each point at 5 centimeter increments (on the x and y axis). Another change was that we used a longer measuring stick that extended across the area of interest on top of the parallel wooden boards to represent the mobile x-axis instead of using a string at the top of the two parallel boards. This was a more time intensive process than before, but it would ensure that the survey is more accurate than the initial one.
The last method is to recreate the digital terrain surface by using the spline interpolation tool with the new surveyed data in ArcMap. This prediction surface is also made into a 3 dimensional surface in the program ArcScene. When comparing the new digital terrain model (shown in Figure 6) with the old one in the spline method, it is evident that there is more detail in the landscape of the model from the second survey. Changing the coordinate system from 10 centimeter increments to 5 centimeter increments shows more variation in the terrain that might have been missed when conducting the first, more coarse survey. The changes in elevation appear to be more natural in the new image and significantly improve the distinction between all of the five features that were included in the study.

Figure 6: 2nd Survey: Digital Terrain Model- Spline Interpolation Method

Discussion

The concepts of geospatial thinking and working together in groups helped make the completion of the digital terrain model a success. There are multiple approaches one can take to survey a parcel of land and after it was all said and done, we realized that we could have done some things differently in that particular objective of the study. We could have utilized electronic instruments in surveying land such as an automatic level or an actual surveying rod to record the measurements. However, since the study area is so small in comparison to a large parcel of land, sophisticated surveying instruments are not necessary and would have yielded less accurate results than our technique, which was done by hand. Nevertheless, the project was open to improvising and using the imagination to apply a surveying technique, which makes it more creative. All three group members contributed their ideas and were able to compromise a good time where everyone could meet to pitch in their share of the survey model. Although the weather outside called for a wind chill of below zero, the group was able to stay strong and seek the project through its completion. Dressing for the weather elements is one of the most important parts of conducting work in the field. Weather can be unpredictable in this part of the world so it is always wise to come prepared otherwise it could make for a bad experience in land surveying.

Conclusion

The goal of the project is to create a terrain model in one of the garden boxes in the courtyard of the Phillips science building by utilizing critical thinking in a group setting and employing a creative survey technique. Communication between the group members is essential to the project’s success because a coordinate system has to be agreed on before the other methods can be conducted. I have taken a lot out of this experience by learning how to figure out a way to survey the land among other people and learn how to build and organize a terrain model in the end.