Distance Azimuth Survey

Nathan Sylte

Azimuth Tree Survey

Introduction:

A common method used in surveying involves the collection of distance and azimuth measurements from a certain point. The distance azimuth surveying method provides an extremely versatile way to collect data when other methods and technologies fail. Preferably, the distance azimuth method involves two people with one person stationed at the starting point. The starting point is where the azimuth is measured (degrees). The distance to the desired object is also measured. Essentially, a standard point is created (starting point), and all the other survey points are measured based off of the standard point. This insures that the survey area is portrayed accurately. The methods versatility arises due to the fact that this method can be performed anywhere under any conditions.

Study Area:

The distance azimuth survey took place along Putnam Drive in Putnam Park on the campus of the University of Wisconsin Eau Claire. Specifically, the general location of the survey was the stretch of Putnam Park directly south of Davies Center (Figure 1). This area is not uniform in forest type and elevation, with the area possessing two general habitat descriptions. Part of the study area is lowland and is generally wet year round. Therefore, the types of trees that grow in this area are different from the higher ground and ridge area which makes up the other part of the study area. The frozen ground allowed for easy surveying so the lower area was selected as the primary survey area. The ridge area was not selected because the frozen ground made for difficult sampling. For the sake of time the lower area was selected. The outline of the ridge can be seen in (Figure 1).

Figure 1. Shown above is the study area where the distance azimuth survey took place. UW Eau Claire lower campus is on the north side of the image (top side). 

Methods:

To begin the survey using the distance azimuth method a starting location at each site was chosen. This would be the designated spot where the distance and azimuth measurements where taken from.Trees where then selected and the distance was recorded from the starting point to the tree. Multiple devices where used to measure distance between the starting point and the tree. One method involved measuring tape while the other method involved remote devices such as the Sonic Combat Pro device. This device involved a receiver at the tree that was to be sampled while a person held the device at the starting location (Figure 2). The Sonic Combat Pro emits a sound wave to measure distance. To measure the azimuth one method involved a hand held compass that involved looking into the device to get a visual of the azimuth (Figure 3). The other methods involved remote devices such as the True-pulse 360B device (Figure 4). This device is similar to a range finder however it contains other options such as the azimuth option. To use this device one must simple aim the device at the desired point. Next,  the circumference of the tree was measured in centimeters.

After the data were recorded and normalized in excel, the data were brought into ArcMap (Figure 5). Once the data table was added into the map, instead of adding using the add x,y data option, the Bearing distance to line tool was used to import the data. Next, the data were converted to points using the Feature Vertices to Points tool. This tool can be found by simply entering its name into the search option. Finally, maps were able to be generated using the survey points.

An important note! The compass would not work properly to begin with. Make sure when using the compass or any other devices that there are not magnets near by. For example, little magnets in gloves can interact with the compass. Also, when entering data the x coordinates must be a negative value otherwise the survey points will end up on the opposite end of the globe. Another important note involves the Feature Vertices to Points tool. The end option must be selected in order to create points at the end of the distance line.

Figure 2. Using the Sonic Combat Pro device. 

Figure 3. Using the compass to find the azimuth.

Figure 4. Using the True-Pulse 360 B unit to find the distance and azimuth. 

Figure 5. Survey data as show in excel. 

Results/Discussion: 

The survey yielded a very mixed variation in the sizes of trees in the study area (Figure 6) (Figure 7). Several trees had a circumference greater than 150 centimeters while multiple trees had a circumference between 16 and 25 centimeters. The largest trees were located in site three which is the cluster of points in the south east portion of the map. A close up view of the survey locations are shown in (Figure 7). 

Figure 6. Graduated symbols map of the distance azimuth survey trees. 

Figure 7. Graduated symbols map of the distance azimuth survey trees in the three different locations. 

Part of the lab involved investigating another survey method. The survey method was the point quarter method described in a lab report Point Survey Method. The point survey method could be used to survey the trees surrounding the different site locations. In the case of the point survey method the survey points are randomly determined to insure an accurate representation. There are four quadrants with a center point.The distance azimuth method can be used to enhance the point survey method. It can do this by speeding up the process by adding a degree component to the quadrants. Samples can be taken at a specific interval of degrees.The azimuth can be taken at the survey points which in turn enhance the spatial accuracy of the survey. 

Conclusion: 

Overall, the azimuth survey possesses many beneficial qualities. The method is very quick, efficient, and applicable. A great advantage of the azimuth method is that it is low tech. Many times technology fails and the azimuth method can be used as a great back up option. Also, the azimuth method is very compatible with GIS which adds to the list of beneficial qualities. 

Sources:

http://www.saddleback.edu/faculty/steh/bio3afolder/Point-Quarter%20Lab.pdf

Processing UAS Imagery with Pix4D

Nathan Sylte
03/14/17

Digital Surface Modeling Using Pix4D

This lab/post was different than some of the previous technical labs and posts. Compared to the technical format that we usually use this post will be broken into three parts. First, background on Pix4D will be provided with an emphasis on its capabilities. Second, the Pix4D software will be discussed. Finally, several maps will shown that were the products of Pix4D software.


Part 1: Becoming familiar with Pix4D. How is the program used, and how is the data processed?

Pix4D essentially generates a three dimensional images. First, a drone will fly over the area of interest and take aerial photographs in a specific manner. Then Pix4D will overlap the photos pixels with specific ground points. The camera position is then calculated using an algorithm so a 3D image can be developed.


Using the Pix4D manual, some key questions can be answered regarding the dynamics of Pix4D.

1. What is the overlap required for Pix4D to process imagery?
A high amount of overlap is required to obtain accurate results. This means that a very specific plan to acquire the images must be put in place to insure the proper amount of overlap. When making the "image acquisition plan" the ground sampling distance must be known along with the terrain type and other project specifications. Failure to have a proper plan will result in low quality data.

2. What if the user is flying over sand, snow, or a uniform field?
The manual states the recommended overlap should have at least 75% overlap. There must also be 60% side overlap between flying paths. A uniform surface such as those listed above will require at least 85% overlap and 70% side overlap.

3. What is rapid check?
Rapid check quickly determines if the images taken are good enough to sufficiently cover the area of interest. It determines whether the image can be processed.

4. Can Pix4D process multiple flights? What does the pilot need to maintain if so?
Yes, Pix4D can process multiple flights. However, a specific number of overlap points are required (figure 1). Figure one displays what this might look like.

Figure 1.

5. Can Pix4D process oblique images, and what type of data would you need to do so?

Pix4D can process oblique images, but the camera must take pictures at a 90 degree angle to the ground or a 45 degree angle to the ground.

6. Are GCPs (ground control points) required for Pix4D or are they just recommended?

GCPs are not required, however, using GCPs will greatly increase the accuracy of the data. The project can then be placed on the exact position of the Earth.

7. What is a quality report?

After the points taken by the drone are processed a quality report is then generated. The quality report will include information pertaining to the processing of the image. If there are questions about the integrity of the image generated the quality report should be viewed.

Part 2: Using Pix4D.

After starting Pix4D one will simply go to "start new project". Next, the images must be added from the drone flight. This is done by copying all of the images from the drone flight into Pix4D.

Below are the image points as shown in Pix4D (figure 2).

Figure 2.

Then, you must select the type of project you with to create. We selected create a new 3D map (figure 3).











Figure 3.

After the data is uploaded it must be processed (figure 4). We first selected initial processing making sure the other options were unchecked. It is important to make sure that "Point Cloud and Mesh", and "DSM, orthomosaic, and Index" are unchecked initially. After the initially processing the two previous options were then checked and ran.

Figure 4.

Once processing is complete a quality report is then generated (figure 5). Figure five was taken directly from the quality report.

Figure 5. Fist displayed in the quality report is the initial quality check. Our initial quality check was very promising. A total of 68 images were used. 68 out of 68 images calibrated correctly.

This image taken from the quality report shows that our image had a great amount of overlap as indicated in green. There were a couple small areas with poor overlap on the outsides of the image. This is because there were no other images taken outside the AOI.

Here are some of the geolocation details.

Next, an animated fly over was created to provide a great view of the mine. 

After the animation was created I wanted to take a volume measurement from one of the sand piles (figure 6). This was done for future reference. The volume measurement was fairly straight forward. It simply required digitizing the desired area. As shown below.  

Figure 6. The total volume of this sand pile was 7195.05 meters cubed. The error was + or - 76.10 meters cubed.

Part 3. Maps

The first map created was a map showing the 2D aspect of the Litchfield Mine (figure 7). This was done in ArcScene and ArcMap. The DSM (digital surface model) portion displayed on the top of figure two clearly shows the physical features of the mine. The individual piles are clearly shown whereas the mosaic on the bottom is less clear.

Figure 7. Here is the Litchfield Mine shown in 2D. The sand pile that had the volume measurement taken is labeled in the bottom portion of the map. Metadata is provided in the center of the map.

The second map created displays the Litchfield Mine in 3D (figure 8). In ArcScene the base heights were set to 1 to best display the 3D aspect of the mine. In 3D the mosaic image on the bottom of figure 8 better portrays the mine compared to the 2D mosaic image. An advantage of the mosaic image is that equipment can be portrayed whereas in the DSM equipment cannot be made out.

It should also be pointed out that the pile that the volume measurement was taken from is shown as the dark pile in the mosaic in the west central portion of the map.  

Figure 8. The Litchfield Mine shown in 3D. The same metadata used in figure 7 applies to figure 8.

Conclusion:

Pix4D turned out to be a great tool for processing 3D images. There are also some features that are very practical such as the volume measurement feature and the animation feature. The manual proved to be very informative and easy to use. The main critique would include the time required to initially process the images. This can take a significant amount of time.

Sources:

Pix 4D Website and Manual Website, Manual

Creating a Custom Survey with Survey 123

Nathan Sylte

HOA Survey

Survey 123: Collecting Data with a Smart Phone 

Introduction:

A majority of smart phones now have similar capabilities to a computer. Smart phones can be linked to different data collection mechanisms or use their GPS to collect data in the field. This lab involved the use of Survey 123 for ArcGIS (Survey 123) to create a survey to be used on a mobile device for field data collection. Instructions on how to create the survey were found in an ESRI course (Survey Instructions). In this case, the survey was to be conducted by the HOA to determine a communities readiness in the event of a natural disaster. After the simulated survey was conducted the survey data was then put into a geodatabase to be used for analysis purposes. 

Methods:

The HOA survey was generated on the Survey 123 website. The first step involved going to the create a new survey tab (Figure 1.) 

Figure 1. Create a new survey tab. 

Then by going to the design tab, different survey parameters could be set including what questions were to be included in the survey. In this instance, the survey questions related to safety information pertaining to the survey participants residence. After the survey was created, the survey was then submitted so that people could take the survey. This was done by sharing the URL with members of the University of Wisconsin Eau-Claire organization (Figure 2.) 

Figure 2. Sharing the Survey URL

The Survey 123 application was then downloaded via smartphone. Once the app was downloaded the survey could then be taken. Multiple hypothetical surveys were then completed via smartphone and the data was complied on the Survey 123 website. The survey format as seen on a smartphone is shown below (Figure 3) (Figure 4). 

Figure 3. Survey as seen on the Survey 123 application. 

 Figure 4. Completed surveys as seen on the Survey 123 application. 

The survey data was then analyzed by accessing the analyzed tab. Many different analyses are performed on the data which can be used. In our situation, the data analyses could be used in disaster planning. After viewing the different analyses the data was then downloaded as a geodatabase to be used in ArcMap. Finally, a unique values map was generated. 

Results/Discussion:

After viewing some of the important statistical analyses of the HOA survey data, several important observations can be made. The first being the presence of fire extinguishers in a large majority of the residencies (Figure 5). A total of 87.5 percent of the residencies that participated in the survey contained fire extinguishers. This is important information to consider in disaster planning. Another important statistic relates to the type of residence that survey participants reside in (Figure 6). Twenty five percent of survey participants resided in a type of residence other than a single family house or a multi-family apartment complex. When planning for a disaster it would be critical to know the other type of residence people were living in. The "other" type of residence may influence evacuation plans. 

The HOA Survey results were important for uncovering how many people were living in the particular residence (Figure 7). This information would be critical to know in a disaster situation. Out of the five local survey participant locations the participant that lived on Niagara Street location lived with the fewest amount of people at 3. In contrast, the participant living at The Pickle on Water Street was living with 50 other people. This could pose a severe evacuation risk in a disaster situation. It should be noted that the nearest hospital (Sacred Heart Hospital) is located only around 1 mile from The Pickle. In a disaster situation knowing where hospital locations are will be critical for saving lives. 

Figure 5. The bar graph above that was retrieve from the survey data online shows that 12.5 % of survey participants do not have fire extinguishers in their residence. 

Figure 6. The bar graph above that was retrieved from the survey data online shows that 50% of survey participants live in single family residencies. 

Figure 7. Above is a unique values map of the five local survey participant locations. The number of people living in each residence are depicted by different colored dots. The participants living with the smallest number of people are shown in light green while the participants residing with the most people are shown in red (danger). 

Conclusion:

To conclude the Survey 123 lab various applications of Survey 123 were visited. One application that Survey 123 could be used in is public surveying by the DNR (Department of Natural Resources). For example, the DNR could use Survey 123 to survey hunters after they register deer to determine whether that particular hunter has noticed any chronic wasting disease in the region. The survey data could then be used to help track the spread of chronic wasting disease in Wisconsin. Overall, Survey 123 is a very practical application that could be used in countless situations. 

It should be noted that the above survey was just hypothetical and does not contain precise data about residences in the Eau Claire area. This survey was simply conducted for educational purposes. 

Sources:

"Lesson Gallery Learn ArcGIS." Accessed March 7, 2017. https://learn.arcgis.com/en/gallery/.

Notitle. Accessed March 7, 2017. https://survey123.arcgis.com/.