Processing UAS data in Pix4D

Charlie Krueger

GEOG 336
Processing UAS data in Pix4D

Part 1:

What is the overlap needed for Pix4D to process imagery?

The recommended frontal overlap is 75% and at least 60% side overlap.

What if the user is flying over sand/snow, or uniform fields?

The recommendation is to increase the overlap between images to 85% frontal and 70% side, fly higher, and have accurate image geolocation

What is Rapid Check?

The Pix4Dmapper allows the user to process using a template that templates are labeled Rapid/low res produces fast results at low resolution to indicate whether the data set is good or not.

Can Pix4D process multiple flights? What does the pilot need to maintain if so?

Yes, it can process multiple flights and the pilot must maintain the same height for both of the flights so the spatial resolution is similar.

Can Pix4D process oblique images? What type of data do you need if so?

Yes, Pix4D can process oblique images with others like interior/exterior and/or aerial/terrestrial and /or nadir.

Are GCPs necessary for Pix4D? When are they highly recommended?

GCPs are not necessary but greatly add to the improvement of the georeferenced and accuracy of the reconstruction of the image. In corridor mapping, building reconstruction, city reconstruction, mixed reconstruction, and large vertical object reconstruction

What is the quality report?

It gives information on the reconstructed surface about how successful it was and how many errors there were during the process. It is a big summary of everything that happened with the reconstruction of the image and puts it into a write up separated by sections of importance.  

Introduction:
This lab was slightly different then previous in the sense that the whole lab would be conducted using a computer. The data that was used in the lab was gathered already by Professor Hupy so it was already stored in a file that was accessible to the class. This lab would give the class a chance to use the program Pix4D, which is an amazing program for creating point cloud images. This program is one of the premier programs and is very easy to use so this is why it would be prefect to get a quick course it in. In a previous lab the class created some georeferenced mosaic of imagery, but the ones that would be created in this program would be much better in quality and would quickly give the measurements of imagery through this program. This program could do the work that top groups of the class like 3 hours to measure the height of the object 30 minutes to do a section at least 1000 times larger.

Methods:

To start the process of creating this image the data was taken from the TEMP folder of the geography program. This was data that was collected in Eau Claire not that far from the University of Wisconsin Eau Claire. The data was taken of a sand mine that worked near the Chippewa river and had large piles and other equipment on it. Data was then saved into a personal folder to be worked with in Pix4D. To start in Pix4D the images were loaded into the program then all the class had to do was sit back and watch the program run two different sets of images. In total it took about 25 minutes to get the data into the program and then to run the different image makers.

Results:
Below are all the results of the quality report produced by the image making process. It explains all the different actions that went into making this image and how well the image came out after the process. As it can be seen by the quality report it goes very in depth about how well the images captured by the drone were then turned into an image that could be used to survey the land and the mass on it.

Here is the start of the quality report which is a big summary of the process that occurred in the image

This image shows the flight pattern that the drone took while collecting data of the area

Here is the volume measurement not working in Pix4D. The lab had instructed the class to measure one of the piles of material in the sand mine to create a volume for that pile. This was not possible because the computer would close pix4D mapper every time that a volume was trying to be valued from the map. If this issue did not occur then a proper volume could have be gathered.

Below are two different measurements being taken from the point cloud data and these are a measurement of a late object in the image and the surface area of the whole image. These tools were easy to learn and really showed how useful this software could be.

Measuring a distance using the image. Here a point in the road is measured to a break in the road

Here is surveying the whole land cover and seeing how much surface area the image had.

Conclusion:
Through this lab the exposure to Pix4D really proved that this program is the best point cloud program out there for creating and analyzing data. Yes it was a bit confusing at first using the program but this is common with all new program users. The only downfall that was found was that the volume measurement tool caused the program to crash, but this could have also been from user error. Overall this program is well beyond any other program that was used during this course and if this program would have been used earlier a lot of the late nights in the lab could have been avoided because this program does it all.

GPS Topographic Survey

Charlie Krueger

GEOG 336
GPS Topographic Survey

Introduction:
This lab gave the class the task of gathering GPS points with a high precision GPS unit. The data points that were collected would then be used to create maps showing the change in something like elevation. The data was gathered with a GPS unit that gave the GPS position, the height above sea level and much more data. This lab was to created to show how the GPS locations could be gathered with different equipment and plus how the data collected can be used to show change by interpolating the data.

Study Area/Methods:
The study area of this lab was a section of land on the campus of the University of Wisconsin Eau Claire. This study area was chosen because Professor Hupy believed that it would show a decent amount of change from the data points gathered. The area was a small section of land on the campus between the buildings of Centennial Hall and Schofield Hall where the new construction had left a large hump of sorts.

The study area is near the circle growth on the map

When it came to collecting the data Professor Hupy demonstrated to the class about how to use the GPS unit that would take the point. This unit was one were a person would hold it and stick it into the ground so it holds the position and does not move around when collecting the data point. Once the point was it was stored inside of the GPS to then later be moved into an Excel spread sheet where the class could use the data. The data was then taken from the Excel document and downloaded into the program ArcMap. ArcMap would be the program that is used to create the maps with the interpolations. Once the data was downloaded and saved in a folder in ArcMap a shapefile would have to be created from the data so that it could be used when using the interpolation tools. The shapefile would be saved in a separate folder that only contained data for this lab. Once the shapefile was create the interpolations could be created using the program tools in ArcMap. These different types of interpolations would create maps from the data points using the Z value or height above sea level in meters in this lab as the main source. The different types of interpolations are defined in a previous blog named Visualizing and refining terrain survey Sandbox Part 2. This blog gives great definitions of the interpolations and when using certain ones comes in handy.

Results/Discussion:
Below are all the interpolations that were run in this lab and like in pervious lab there is obviously large differences between some of the interpolations. The interpolation that really captures the slope of the hillside would be Natural Neighbor because it shows the small step like lines increasing just like the hillside did when it was being measured and recorded. There was a small problem in this lab and it came from the time zones mix up when the GPS was still in time zone 16 when it should have been in 15. This was because it was used by Professor Hupy in Indiana prior to this lab and shows a great example of how technology can always get mixed up even though it was still giving results to the class.

Conclusion:
Overall this lab gave the class an opportunity to work with a very high grade GPS which some may use in their careers later in life. This lab was on the small scale but just shows how the data taken from the field can be used and analyzed by some many different programs such as ArcMap. The lab showed another good way to gather data and showed the class that even with such high grade equipment a small mistake like not changing time zones can throw off an entire dataset.