Lab4-Using ArcGIS Pro to Generate an Orthomosaic with UAS Imagery

Introduction

• What is the Ortho Mapping Suite in ArcPro? How does it relate to UAS imagery?

This program and its tools focus on aerial photography and allow for a series of orthorectified images and maps.

• What is Bundle Block Adjustment?

Bundle block is important because it performs a series of adjustments to each image so that the exterior orientation of the image is changed in a way that matches up with the surrounding images in a more appealing way. After this, the entire image is also adjusted to better fit the basemap.

• What is the advantage of using this method? Is it perfect?

This method provides a cleaner final product but is not perfect. It requires a long processing time and can lead to residual and overall errors. These errors stem from images that were very off focus and the program can not adjust fully but are identified for the user so that they can manually be adjusted.

Methods

For this lab, we created an orthomosaic using ArcPro. We took a series of photographs that were provided to us for the lab from the 319 folder and imported them to the program. We then began the processing for the creation of the orthomosaic, which created the initial flight path and boarder of the image and placed it over a basemap. Then we processed the bundle block adjustment which took a very long time but provides for a more accurate and visually appealing final product. Then a new layout was made, and the photo was placed over a basemap and a reference map was added to the top corner, along with a scale bar, north arrow, metadata, title, and watermark in order to create the final map.

• What key characteristics should go into folder and file naming conventions

The folders and file names should follow a logical date, time, location, and sensors used in order to easily find and access the data that you are looking for. By adding all of these characteristics it will be easy to separate and sort various flights.

• Why is file management so key in working with UAS data?

The number of flights and amount of data collected can grow very rapidly, meaning data size gets very large very fast. In one day a series of flights can be flown and various locations or sensors could be used and it is important to keep track of all the data so when it comes time for processing there is no confusion.

• What key forms of metadata should be associated with every UAS mission?

The key forms of metadata can be seen below in figure 1.

Figure 1: Table of MetaData

Results

• Describe you maps in detail. Discuss their quality, and where you see issues in the maps. Are there areas on the map where the data quality is poor or missing?

The map is a high-quality final project that shows clear detail of the surrounding area and provides the user with a good picture of the scene. Overall the high quality of the ortho can be seen, such as individual leaves on the ground and a clear sense of the area that was flown. Some areas are of much lower quality such as the trees. The area was densely packed with trees in areas and this becomes very difficult to have a high-quality final product of as the leaves are always moving and trees have dark areas and create shadows that become hard to process when creating the final product. Houses, cars, ground references, and other major components of the ortho came out very well so overall it has a high quality.

• Processing time is time and money in the UAS world. Here you want to create a table that shows the time it took.
• How much time did it take to process the data.

Figure 2: Processing Time Table

Figure 3: Orthomosaic

Figure 4: Map of Lab 4 Flight

Conclusion

• Summarize the Orthomosaic Tool.

This tool creates a detailed image composed of a series of images that are spliced together to create one fluid large image. This tool allows the user to create digital surface models that can be used to show a detailed selection of land while only having to perform one flight.

• Summarize the process in terms of time invested and quality of output.

This particular orthomosaic was a high time creation because of the large number of images being used and the amount of processing time it takes to make the adjustments. A factor of this was the fact our entire class was trying to upload to the server all at once, and the more powerful computers are able to process this data faster. However, without a very powerful computer this process has a very high processing time to produce a quality result.

• Think of what was discussed with this orthomosaic in terms of accuracy. How might a higher resolution DTM (from LiDAR) make this more accurate? Why might this approach not work in a dynamic environment such as a mine?

As of now the orthomosaic is just a surface model, meaning there is no real depth to the image. The trees and buildings have depth but not 3d qualities to them therefore they can not count as terrain. By adding another level to the image, like from LiDAR data once could create a terrain model because actual depth could be given to the image. This would be more accurate as the the features of the image that have terrain could be given more dynamic values such as an accurate height and depth of field. This can be complex in a dynamic environment because as objects on the ground move while the flight is conducted the end result could produce errors or be corrupted because as the data is collected repeatedly due to the high overlap, the same piece of the image could return different values. Things such as leaves rustling in the wind and then recorded using images or LiDAR would produce problems.