Volumetric Analysis

 Introduction

Building upon the map fundamentals learned from the lab demo before, the data from the Wolf Paving Piles are used once again for volumetric analysis, but data from the Litchfield Paving Piles area was also used for volumetric analysis and for other data processing. Volumetric analysis is a form of chemical analysis which measures the volume a substance occupies, which in the context of this lab it will be used to measure the volume of the paving piles. ArcGIS Pro has a series of tools and functions that were used to complete this lab demo, which will be discussed in detail later in this post.

Methods

To perform volumetric analysis, the Extract by Mask tool was used on three separate paving piles. The tool essential outlines a certain section of a raster and masks it as its own raster. A polygon must be created before running this function, to define the area that is being extracted. The surface volume function is then used to directly calculate the volume of the piles. The tool must have a preset z value so that any area above the set value is calculated. There were three maps generated for each of the piles, which are shown in Figure 1, Figure 2, and Figure 3.

Figure 1 displays the volume and elevation value for the pile labeled A.

Figure 2 shows the volume and elevation value for the pile labeled B.

Figure 3 shows the volume and elevation value for the pile labeled C.

After performing volumetric analysis, the Litchfield data was then analyzed, but it was processed differently. The data series used was temporal, meaning it was the same area, but it was collected over time, to view changes of the map as it was being used. Other than using Extract by Mask, the data was resampled each at 10 centimeters and 100 centimeters. The main difference between these resampled sizes is the pixel sizes and the processing time. A larger resample size results in larger pixels and quicker processing while making the overall quality of the final product more simplified and lesser quality. It is the exact opposite as the resample size is decreased. Both Figure 4 and Figure 5 will show the maps made for the resampled data at 100 centimeters, while Figure 6 and Figure 7 will show the resampled data at 10 centimeters.

Figure 4 shows the resampled data at 100 centimeters, which data is from June 22nd, 2017.

Figure 5 shows the resampled data at 100 centimeters, which was taken on September 30th, 2017.

Figure 6 shows the resampled data at 10 centimeters, which was taken on June 22nd, 2017.

Figure 7 shows the resampled data at 10 centimeters, which was taken on September 30th, 2017.

As it can be observed, the quality of the four maps above varies. The data resampled at 10 centimeters prove to be better quality than the 100 centimeters, but it is also obvious that the pile changed in height and the distribution of the materials changed. To get a better understanding of where the pile changed. the earliest data (7/22/17) and the latest (9/30/17) were used to run the tool called volumetric comparison. The main purpose of this tool is to compare elevation values with a predetermined z value and calculate net gain, net loss, and areas without a difference. Figure 8 displays the results from this tool.

Figure 8 displays the results of the volumetric comparison; the red represents the net gain, while the blue displays the net loss; the gray is meant to show if there were not any changes, which there is not a single spot without any changes.

Discussion

Volumetric analysis within geospatial data is important to understand the volume of an object of interest around you. The data that was used to create the masks were from the DSM's, which made displaying the piles easier. The volume is calculated by using the difference from the actual elevation compared to the determined elevation level. This lab was also useful in learning the importance of resampling data at different pixel sizes. Although it is easier to process data with larger pixel sizes, it sacrifices the quality of the data. It is the exact opposite for data resampled with smaller pixel sizes. It mostly depends on the quality of data you are wanting out of the analysis and the amount of time allocated for this processing. The use of volumetrics within GIS work is useful in learning more about different features and helps to give the data a lot more meaning.