Building Maps With UAS Data

Introduction

Why are proper cartographic skills essential in working with UAS data?
Maps require proper cartography to perform their intended function successfully. In working with UAS data, cartographic skills are essential so the reader can decipher an analyze the data properly. Without a compass, scale, or proper coordinate systems and projections the map would be meaningless.

What are the fundamentals of turning either a drawing or an aerial image into a map?
Ever map should include a north arrow, scale bar, locator map, watermark (map's creator), and data sources/metadata.

What can spatial patterns of data tell the reader about UAS data? Provide several examples.
Spatial patterns can tell readers where wet spots exist in a farm, for example. Using the correct sensors, soil saturation can be seen and analyzed. Another example would be crop health. Depending on the shading of the crop, analysis can be performed that show if a crop is receiving too much or too little water, fertilizer, or many other things.

What are the objectives of the lab?
This lab's objectives were to understand and apply map creation skills using UAS data. ArcMap and ArcScene are both utilized in this lab to create maps, perform analysis of the maps and metadata, and get different views of the data.

Methods

What key characteristics should go into folder and file naming conventions?
Both file and folder names should describe what is contained, either in the folder or the file. It should be obvious when looking at a file what the data inside it is. For example, if a DSM was created for a park called Community Park, a good file name may be community_park_dsm.

Why is file management so key in working with UAS data?
The sheer number of files can be incredibly overwhelming. Without proper file management files will easily get lost, or forgotten which would cause the layer to not load properly in the GIS software.

What key forms of metadata should be associated with every UAS mission?
The tools (UAS platform, sensors, ground control points, etc.) that were used to collect the data. Specifications of the tools, and other information regarding their usage (altitude of UAS). The specific coordinate system and projection being used with the data set, and the time and data of when the data was collected. Figure 1 below shows the key metadata associated with the data set being used throughout this lab.

Create a table that provides the key metadata for the data you are working with.

Figure 1: Metadata table

What basemap did you use? Why?

The streets basemap was utilized for this lab. Streets loads faster than some of the other basemaps that contain more information, but streets has everything that is needed for working with this data set.

What is the difference between a DSM and DEM?
DSM stands for digital surface model, while DEM stands for digital elevation model. A DEM contains the data for the elevation of the surface of the earth, typically above mean sea level (MSL). A DSM takes elevation data based on the surface the sensor interacts with, not just the earth. Therefore, a DSM will include elevation data for terrain like a DEM, but also for structures such as buildings. Descriptive statistics for the DSM are pictured in Figure 2 below.

DSM Statistics

Figure 2: Descriptive statistics for the DSM

What does hillshading do towards being able to visualize relief and topography?

Hillshading makes it much easier for the GIS user to visualize differences in elevation for the data set. It also makes terrain details pop out allowing for easier analysis.

How does the orthomosaic relate to what you see in the shaded relief of the DSM

The orthomosaic is the actual imagery of the site while the DSM is a digital model of the surface of the area. The orthomosaic makes it easy to tell what certain features are, such as trees or the silo in the middle of the picture. The DSM enables the reader to easily see elevation differences. Utilizing the swipe tool, as seen in Figure 3, allows easy navigation between the orthomosaic and the DSM to quickly look at differences in the data.

Figure 3: Swipe tool being used to compare the orthomosaic to the DSM

What is the purpose of vertical exaggeration? What settings do you have for your data?

Vertical exaggeration allows for easier discernible difference in surface elevation. Vertical exaggeration was enabled to the extent that ArcScene calculated it should be (2.37259), this is shown in Figure 4. In addition to changes in the symbology tab, floating on a custom surface in the base heights tab was enabled, as well as shading effects in the rendering tab. Figure 5 shows the settings changes made in the symbology tab, as well as the color ramp used.

Figure 4: Vertical exaggeration enabled

What color ramp did you use? Why?

Maroon to white shading (lowest to highest elevation) was used. To me, this is an easily visible color ramp that makes differentiating elevations very easy even without vertical exaggeration being used in ArcScene.

Figure 5: Layer properties for symbology settings and color ramp shown

What are the advantages of using ArcScene to view UAS DSM data vs. the overhead shaded relief in ArcMap. What are the disadvantages?

An advantage is the ability to view the DSM from various angles that allow three dimensional elevation data to actually be seen.

Is this export a map? Why or why not?

No, this is not a map because there is no scale, north arrow, or any of the other things listed in the introduction that a map must have.

Maps

Figure 6: Map of the DSM

Figure 7: Map of the Orthomosaic

Conclusion

UAS data is a very useful tool to cartographers and GIS users because of the incredible detail that can be seen with them. Satellite imagery is often of much lower quality than what UAS data can be. UAS platforms can have many different types of sensors as well, letting the users see multiple bands of the light spectrum for different types of image analysis.

A limitation with the UAS data, due to one of its major advantages, is rendering and processing time. Because the data is of such high quality, processing and rendering the images can be a very long process, especially when large plots of land are being used.

Other data that could be utilized in combination with this data would be additional DSMs taken at different points in time. Quarries move a large amount of land in a quick period of time. Over the course of weeks of taking UAS data, cut-fill analysis could be done to see the rate at which the land is being moved.