Sandboxed

Introduction

            For this assignment, the main focus was the methodology of sampling, and various techniques involved in best practice. A standardized practice for data collection is needed in order to promote a successful experiment or project involving any time of field collection of data.

            As a loose definition, sampling can be defined as the selection of individuals or individual points within a population to estimate the characteristics of the whole population. If this is thought of in a spatial perspective, sampling can be used to produce an estimate of the whole only using a select number of data points, which can save both time and energy. This is an important concept because the way in which you sample your data affects the workflow of the entire project, and potentially the accuracy of the data in the end product. There are a few common ways to sample spatial data, including random, systematic, and stratified systematic.

            Random sampling involved the completely random selection of a certain amount of points from a specified area. This form of sampling is often used for forest population estimates, or for water quality sample test sites. The next form of sampling, systematic, involved placing the area of interest in a grid pattern, and sampling the entire area only collecting data from the intersections of the grid lines. This technique produces an even distribution of samples throughout the area of interest. This technique is commonly used to collect information about large areas with as few points while still remaining spatially accurate. Expanding on systematic sampling, stratified (systematic) utilizes the same grid technique of the systematic, but features certain areas, which are broken up into smaller grid patterns. This allows researchers to collect more information on areas with large amounts of relief or change, while focusing less on spaces with that are less important or contrasting. Allowing researchers to focus on the areas, which need the more intensive sampling to gather accurate data.

            The project, which we are working on for this assignment, utilizes sampling methods and builds on practical problem solving and team decision making. Our task is to conceive a sampling method to use, to accurately collect the topographic variation of a sandbox, which has the following features: a ridge, a hill, a depression, a valley, and a plateau.

Methods

            The sampling technique, which our group chose, is the simple systematic method.  The rational behind choosing this method over the others is based on the following reasons; the variation of our sandbox featured well defined and separate features, so the need for dynamic sampling (stratified) was low, also the features are presented in a space (sandbox) which is quite small so a grid with a even interval would properly capture most of the relief.

            The sandbox, which we sampled, had 5 features, which were described in the earlier text. Spatially, we designed our features to be located in the four corners, with the plateau to be found in the center of the sandbox. By the way in which we organized the features, the valley is found in along the western side of the sandbox, stretching from the south side of the box to the north side. In the southeast corner of the box are two small hills adjacent to each other paralleling the southern side of the box? Leading from the small hills, a ridge follows along parallel to the eastern side of the box, eventually tapering off. The ridge flows directly into the depression, which is featured in the northeast corner of the sandbox.

            The material which were used in this project are as listed: String, pushpins, a measuring stick (cm), and a sandbox.

Our sampling scheme was directly influenced by the structure and shape of the sandbox. Beause the box was a (near) perfect square, we measured all four sides to find the dimentionality of the actual sandbox space. It measured 144cm for each side. In order to get a properly small enough grid space, with consistant spacing, the group played with the numbers until an even ratio could be found. The grid was then formed, using 19 distinct classifications for X, Y, which spaced them about 6cm apart. This gave us a 6cmx6cm grid box for which to sample. We used the south, western corner of the box as our source point, which means that the X vales increased from left to right, and our y values increased from bottom to top. For the purposes of collecting the Z value, or elevation, we used the sandbox lip as a zero elevation. This means that anything below the lip is below sea level, and anything above is above.

            Once the grid was formed, and set up, data collection took place via manual data entry into a physical notebook. One member of the group took the reading of the elevation at each point, while the others wrote in information down. We choose to do a physical copy initially, to make sure that each member of our group was active in the data collection, and so that we had a physical copy to reference back to if any of our data was corrupted later in the project process.

Results and Discussion

As a result of our data collection, we collected 361 data points across the entirety of the sandbox. While looking at the data, the variation of our elevation was not very pronounced, and this is purposeful. We did not make our sandbox features very drastic, because we are measuring the sandbox with centimeters. The scale is much larger at the centimeter level then the inches or foot level, which most people operate on a daily basis. By not making the features very drastically pronounces, we ensured that the features, which we did produce, would have a consistent scale and be easier to identify once the data is imported into computer systems. The system, which we devised in the beginning of the project, worked in practice, and help up to the collection process, leading to the successful survey of the sandbox landscape.  During the project, we encountered very minimal problems, mostly stemming from time constraints placed by other obligations. Our group was purposeful in the task by making sure that our sampling method was completely thought through, and planned out so would encounter as few problems as possible during the data collection process, because data integrity is of utmost importance.

 Conclusion

Our methodology for the sampling techniques for this procedure flow directly from the definition provided because the spatial sampling is a landscape can provide a greatly cost effective (time and money) way to produce an estimate of the topographic variation captured in the sandbox landscape. Using the numbers, which we gathered, our survey did an appropriate job or representing the landscape. The technique always has a potential to be refined and redesigned for the future, one potential would be to add a stratified section if a more detailed sample is needed for a particularly complex area in the landscape, but for our purposes the simple systematic technique produces a satisfactory result.