Building Maps with UAS Data

Introduction

    Possessing cartographic skills is essential for working with UAS data. Nearly every piece of data that the UAS collects can be plotted and portrayed on a map. Knowing how to do this in a clear and concise way is a marketable skill. Turning a drawing or aerial image into a functional map requires at least a directional reference, scale bar, locator map, and the source and metadata from the compiled data. Depending on the location and spatial patterns present, a number of techniques can be applied to create a functional map out of UAS data. In this exercise, the terrain elevation varied and there were multiple man-made developments present across the property. Hillshading, the process of adding light and dark areas to the map, was used to bring out a three dimensional view of the hills and structures. The objectives of this exercise were to apply cartographic fundamentals to create a map, and to set an example for a map I will create in the future.

Methodology

    The data was provided to me for this exercise by Dr. Hupy via the class server. It consisted of multiple raster files, including a digital surface model (DSM) and an orthomosaic (Figure 3.1), and metadata in a text file. A DSM is not to be confused with a DEM (digital elevation model). The difference is the DSM contains everything on the surface including trees, people, cars, etc. The DEM is edited more heavily to calculate the elevation of the surface without the noise on top. The relevant metadata for this data set can be viewed in the lower left corner of all provided maps (Figure 3.1-3.4). In order to manage the many files that are created when gathering and manipulating GIS data, it is important to develop sound naming conventions and keep an updated metadata file. In this case, the main folder I am accessing is named based on both the location and client’s business: “Wolf Paving”. Furthermore, all files within this folder include “wolfpaving” in the name as well, so they can easily be traced back to this folder. Metadata is essential to the dataset as well because it keeps track of the who, what, where, and when of the UAS mission.

    Moving on to the map setup; The basemap in this application is an elevation map. It displays ranges of elevation with simple lines. This gives the detailed map context without distracting from it. Before bringing the data into the map, I calculated the statistics on each data set. This gives important information such as the cell size, units, projection, highest and lowest elevations. Knowing this can reaffirm the data collected is accurate, the resolution of the data, and how to use it for further calculations. When loading the data into the map, I told ArcGIS to build Pyramids. This allows the frame to be recalculated faster when zooming in and out of the data.

    The raw DSM alone is dull. To make the features and elevation pop, a hillshade was generated from the data (Figure 3.2). The hillshade can be set to a color ramp of the user’s choice. The one in this map is a natural earth-tone scale as this is standard for representing elevation. In this case, it is set to be transparent over the shaded DSM for maximal feature distinction. While editing the map, the swipe tool can be used to strip back the hillshade and shaded DSM to reveal the orthomosaic for reference. This is helpful to quickly reference the surface structures. At this point the hillshade provides feature relief. This can be draped over the actual elevation to create a three dimensional figure. Depending on what the client requires, this may be helpful especially if there are features observed with varying heights. Another useful analytical tool in this scenario is the slope and aspect calculations. Slope colors the raster data to the steepness of each cell (Figure 3.3). Aspect can then be used to show the compass direction these slopes face (Figure 3.4). This can be useful for analyzing which areas will be exposed to the most sun and tend to be dry. In Figure 3.4 the final map illustrates the aspect as the top layer with the hillshade directly below for extra feature relief.  

Figure 3.1: Initial orthomosaic rendering of the

provided data.

Figure 3.2: A transparent hillshade analysis overlaid

on the DSM.

Figure 3.3: A transparent slope analysis overlaid

on the hillshade.

Figure 3.4: Final map portraying a transparent aspect
analysis overlaid on the hillshade.

Conclusion

    UAS data is a useful tool to both cartographers and GIS users because they can quickly, and accurately gather various types of data at a location for GIS analysis. With that being said, the data collected is not bulletproof. The cartographer still must have an understanding of the data type, how it was collected, and the limitations of it. If any of these points are ignored, the analysis and presentation of the data risks being inaccurate. UAS collected data can be a powerful tool for geographic analysis. It can stand alone or be supplemented with preexisting projections of the area collected from satellites, aircraft or other means.