Activity 12: Introduction Unmanned Aerial Systems

Introduction

This week for field methods we did something a little bit different than the normal activities. This week was more a show and tell and step by step demonstration of how to use an Unmanned Aerial System (UAV). Professor Hupy and myself gave the class a demo of pre-flight procedures, data collection, and post flight procedures. The class learned how a typical day flying and collecting data goes from the arrival on the cite and taking weather conditions to UAV inspection and post flight data processing. professor Hupy and myself stressed safety precautions and following our flight plan to ensure a safe and productive demonstration for the class. We were again out at the Priory just south of town. The two UAV platforms we flew were the Matrix (Figure 1) and Iris (Figure 2).

Figure 1 is an IRIS made by 3D Robotics. This is an out of the box ready to fly UAV that costs around $700.

Figure 2 is the Matrix by Turbo Ace. This is an image of the one we flew for this exercise. It is a more do it yourself kind of platform that requires a lot of assembly and much more mechanical knowledge to construct. This is about 4 to 5 thousand dollars with all the electronics on it.

Methods

I was involved in this activity to help demonstrate so my steps and methods may be different from others in the class who got to take notes and watch the demo.I will base my methods section off of the flight procedure checklist and what a normal data collection mission would be like when I do my research with professor Hupy. Again this whole procedure is used in order to eliminate human error during set up, increase flight safety and prevent damage to our vehicles and sensors that are on board collecting data.

Step 1 Study Area

The first step to collecting data with a UAV is have a study area or a location that you are going to fly. When selecting an area to fly there are some things that need to be considered. The first is am I going to be close to people or putting others in danger by flying this area. We usually fly in areas of low population away from houses and people. Large open parks are ideal for flying. Another thing to consider is where can I take off and land from. It is good to have a flat open area with little to no vegetation on it. This reduces the risk of the UAV crashing into something like a tree or bush during take off and landing. Avoiding areas with power lines and cell towers is also important. The current flowing through the power lines and the signal coming off the tower can create electromagnetic pulses which can cause the compass and/or the GPS on the UAV to malfunction which could lead to a crash. In figure 3 you can see our study area in the yellow rectangle for our demonstration flight at the Priory. If you look at the map you can see the areas where my navigation points are from a previous week is very heavy tree cover and steep elevation. That is not a good area to land and take off in. The yellow rectangle is over an area that is flat with very few trees, no power lines and from this area you could see the UAV in the air at all times which is another study area consideration that needs to be thought about. Figure is a view from the take off location for our demonstration and also a ground shot of the yellow rectangle in Figure 3. You can see how open the area what that we were flying in, which is ideal.

Figure 3 is a map of the Priory property from a previous exercise but I choose it for this one as well to contrast some things.  You can see the contrast in vegetation cover in the areas where the red navigation points are compared to the yellow rectangle where we flew the demonstration flight.  The less large vegetation the better, at least for this flight.

Figure 4 is a photo taken from the ground of the yellow rectangle area in Figure 3.

Step 2 Mission Planning

Once you have your study area chosen and travel to that location the next thing to do is create your flight path and data collection mission. In order to do this we use a program call Mission Planner made by 3D Robotics. This software communicates with the auto pilot on board the UAV and tells it where to fly. There are many other parameters that can be set in this program as well such as altitude, flight speed, how often to collect a picture, and what to do at each way point ascend, descend, land etc. To draw a flight path you draw a rectangle with a mouse on the screen and then based on the parameter you have set Mission Planner fills in the flight grid. You can also manually enter the way points like I have done in figure 5. Once it creates the grid it will tell you an estimated flight time which is good to know because these vehicles do have a limit on flight time. Once you have your mission drawn you can get ready to fly with the next step.

Figure 5 is a screenshot of Mission Planner. I have manually drawn out a flight path for a mission over the soccer park here in Eau Claire.  You can see at the bottom of the image where you can set all the parameters for each point in the flight. If I were connected to an aircraft it would also tell me an estimated air time for this flight. It is important that these flight lines are close enough together to ensure the correct amount of image overlap. We shoot for 30% overlap and this program will adjust the flight path to accommodate that depending on which sensor you are using.

Step 3 Pre-Flight Checklist and Notes

This next step is the most important. Professor Hupy and I after some crashes and other growing pains in our research with UAV's came up with a pretty extensive checklist to go through prior to putting any of the UAV's in the air. Once the mission is created and the UAV is assembled going through the checklist is essential. We use the checklist shown in figure 6. We check the weather, all connections both frame and electrical, prop and motor check, battery and antenna check, controller and command center, battery voltage, number of satellites, mission sent to UAV, check takeoff area for people and then clear for launch. I haven't read the whole list but this gives you an idea of how many things we check. We check everything we can think of every time we fly. This is the golden rule of using UAV's. It is over looked many times and that leads to accidents which cost money and can damage property or even kill someone. Notice how the majority of this checklist happens before the aircraft is powered up, there is a reason for that. Once the UAV is powered up reducing the time someone is around it adjusting things the better. An accidental arming of aircraft could result in loss of fingers or worse depending on the platform. After every flight we take notes about the flight in a log book we have created as well. This is more to do with battery charging, post flight maintenance of the vehicles if needed and data processing. Figure 7 is a screen shot of the other excel sheet we use to keep track of all of our flight data.

Figure 6 is the pre-flight checklist we go through before every flight.  We do not fly until there is a check by each  row.  Like I stated earlier this helps us to fly safely which is many times overlooked because people think UAV;s are just toys and that they aren't dangerous. We know the dangers and use our checklists!

Figure 7 is the spreadsheet where we keep all the information about each flight. We record battery voltages, weather info, maintenance needs and suggestions for what to do better on the next flight. 

Step 4 Mission Execution

Once the the pre-flight checklist is complete the next step is to fly the mission. Part of the checklist is sending the mission to the UAV's auto pilot. Once this is done the aircraft is armed. After we are sure the area is safe we prefer to take off manually to about 10 meters height and do a stability and normal function test. We place it into loiter to see if it is functioning properly and can hold its position, if everything looks good it is flipped to auto pilot and it begins to fly the previously created flight path. During the flight there are a couple different jobs the crew flying the UAV need to perform. One is the pilot at the controls who has the controller in there hands and is piloting the aircraft. Another is the spotter who keeps an eye on the UAV at all times while it is in the air to make sure it is flying normally. The third person is the pilot in command. This person sits at the command station and watches the diagnostics on the Mission Planner screen (Figure 9). The person watching the laptop watches diagnostics like battery voltage, number of satellites, altitude, air speed, pitch, yaw, roll and that the aircraft is following the planned flight path. If anything looks suspicious this is the person who can abort a mission. When we flew the Matrix at the Priory for this activity we aborted a mission and safety landed the aircraft. I was at the laptop and saw that the UAV was deviating from the flight path and the spotter observed it acting rather strange in the air. I made the decision to say abort mission and the pilot at the controls, professor Hupy, said aborting mission and put the aircraft in RTL mode. RTL mode stands for return to launch. If at any time during the mission this switch is flipped the UAV stops whats it is doing and returns to where it took off from and lands itself. The mission may not have needed to be aborted however the class was relatively close to where the UAV was flying and as a safety precaution I decided to abort. 

Figure 9  is the display that the Pilot in Command watches as the UAV is in the air. You can see altitude, speed, battery voltage and other vital information is displayed here. If there is a catastrophic failure on board the UAV it will tell you on this display. If the GPS failed for example where it says DISARMED on the screen it would say NO GPS or GPS FAILURE in big red letters at which the mission would be aborted. 

Discussion

Stressing safety and common sense while flying a UAV is very important. UAV's are very useful and economic solution to perform a wide variety of tasks, however they get a bad reputation from people who use them improperly.I think this activity showed the class how important safety is and how much we are trying to stress it and emphasize it when we fly for research here at UWEC. I hope the class found this activity interesting, It can be a lot of fun flying UAV's and it is a good hobby to have I think but it is going beyond just the hobby and attaching cameras and sensors to the UAV to make it a system which can collect valuable data. When we flew this activity at the Priory we were using a special sensor made for us in the Twin Cities by a small private company. It contains two cameras, one RGB and one near infrared. With this camera we can take normal aerial imagery and look at vegetaion health at the same time. To give you an idea what the imagery looks like that we collected at the Priory I've included a few samples in figures 10 and 11. Figure 12 is a short video of the IRIS UAV.

Figure 10 is an image of  the data we collected during the aborted mission with the Matrix. The sensor we are using saves the images to a USB drive which is plugged into the command laptop where the images are quick mosaic together so that we can see if we have images of everything we wanted before heading back to the lab.

Figure 11 is a RGB image taken by the Matrix during its short flight at the Priory last week. You can see the parking lot and the students looking up at the UAV. Hundreds of images like this one get combined or mosaic to make up one big image of a study area.

 Conclusion

I really enjoyed this activity. Helping with the demonstration was fun too. I look forward to doing similar activities next semester with professor Hupy in his UAV class. It is rare to have a class like that offered at the undergraduate level especially when you can combine it with an already impressive GIS program. These classes will allow a student to learn how to go out and collect data with the UAV and then be able to their own data analysis with the GIS skills they are learning. This combination of skills will be very desirable to employers when the students graduate and they can continue to use their skills in this field for one of the hundreds of uses for UAV's and spatial data analysis. 

Activity 11:Navigation with a GPS device using a UTM Coordinate System

Introduction

This weeks activity was an addition to the activity last week of orienteering using a compass. In Activity 10 we used a compass to conduct an orienteering exercise out at the Priory which is just south of Eau Claire. This week Dr.Hupy wanted us to use a GPS unit to do a similar activity. He wanted us to see how helpful a GPS could be or how difficult it could be to use the unit because of lack of satellite signal and other issues caused by the elevation changes and heavy vegetation on the property. Dr.Hupy  also thought it would be interesting to have each group create their own orienteering course. He will be using these courses we created in the coming years for compass orienteering exercises. We used our same groups of three people from the previous weeks activity. Each person had a different task just like last week. This time one person was operating the GPS unit, a second was relating the GPS and navigation map and the third person was in charge of using the compass for orienteering and finding easier paths through the woods. Each group created and navigation their new course marking 5 trees with pink tape along the way.,

Study Area

The weather was again perfect for an outdoor activity. It was sunny with an air temperature in the mid to upper 70's and a slight breeze. The pollen content was high because trees and flowers we budding which made my allergies pretty miserable but otherwise it was a perfect day. (see Activity 10 for further study area details). We were in the same general area of the priory property for this activity however the groups spread out quite a bit to create a navigation course on each part of the property and not have them overlap too much if at all. Our course we created ended up being through a lot of very thick brush and brambles.Walking was very difficult even more so than the previous week on the property. Our course was more in the northern part of the property which has a very steep slope down into a much flatter area where our points are located. This was a much more mature forest than other parts of the property. The trees were much larger in diameter than other parts of the property and the tree canopy is pretty thick though this portion of the property which caused some problems for us with our GPS.

Methods

Before we went out we went out into the field for this activity there was some pre-planning and preparation that has to be done. One thing that had to be done was to set up a GPS unit to use in the field. For this activity like many others this semester we used a Trimble Juno GPS unit (Figure 1). This unit allows the user to load a whole map document onto the GPS. This is nice because that gives you a base map for reference as well as the ability to created layers or feature classes to the map while out in the field. We used our GPS unit mostly for keeping track and tracking what direction we were moving in and then collecting points where we taped the trees for our course. Another thing we had to do before going out in the field was to plot points where we would mark trees to create our course (Figure 2). In order to do this we went into an ArcMap document and created a new layer. It was a point file where we could place points wherever we wanted on the map. We tried to space our points about 150 meters apart to make the course a bit challenging. Once we had the layer created all we had to do is deploy the document to the Juno, When we got out in the field we looked at these points on the Juno and the little locator circle on the screen which tells you where you are and when the points we laid out were covered by this locator circle we found a large tree to place our tape and point numbers on for our course. 

Figure 1 is an image a Trimble Juno GPS unit. This is what we used to conduct this activity. This unit gives you the option of loading a whole map document onto it and editing that document right on the GPS.

 Figure 2 is the an image of the map we created with our new course location points on it. We loaded this document onto the Juno unit to aid in navigation to these points.

Before leaving the parking lot at the priory to mark our trees each group picked a part of the property to place there course in so that the courses did not overlap and most of the property had courses created on it. Once the areas were decided we plotted our points on our paper navigation maps just like we did in activity 10 the previous week. From this point on the activity this week was very similar to the one the week before. We used the compass to find our bearing keeping 'red in the shed' and 'following Fred' to find our new locations for a course. Like I said before we used also used our Juno unit to track the direction we were traveling and hep us get close to the points we previously plotted in ArcMap. This activity was also of test of how well the GPS units would do in the deep valleys and heavy canopy cover on the property. For the most part the GPS unit worked pretty (or so I thought) well which surprised me a bit. While in the field creating our course it looked liked the GPS had plenty of satellites and good signal but as I will explain later this wasn't the case. 

The process of places our points in the woods was easy. We got our bearing walked to the point we had on our Juno map and put a piece of pink marking tape around the tree. We then wrote the group number and point number on the tape so Dr.Hupy knew which group made each course and which points were part of each course. We places five points for our course and figures 3-12 are pictures of those locations.

Figure 3  This is the first point marked
 1:1 for group 1 point number 1.

Figure 4 This is the location of the first point.
It is on a rather large tree in a fairly open area.

Figure 5 This is the second point
marked 1:2 for group 1 point 2.

   

Figure 6 This is the location of the second 

point. It is on a medium size tree in another 

pretty open area.

Figure 8 This is the location of third point.
It is on a bigger tree with a large knot on
the side. This tree is in a thicker vegetation
area of the forest.

Figure 7 This is the third points
marked 1:3 for group 1 point 3.

Figure 9 is the fourth point in
 our course.It is labeled 1:4 for
group 1 point 4.

Figure 10 This is the location of the fourth point.
On another medium size tree in an open area where
it is easily visible.

Figure 12 This is the location of the fifth and final
point. It is fairly close to the parking lot and close to a
large clearing, It is on the only large tree in the area.

Figure 11 is the fifth and final point
 in the course. It is marked like the
other  1:5 for group 1 and point 5.

Discussion

As I mentioned before, when we were out in the field placing the markers and recording the GPS location of the 5 points I though the GPS was working well and collecting accurate data. When we got back and I put the collected locations of the new course points into ArcMap they are not accurate at all. There are 3 of the points that are in the general area but the other two points are way way out of place. Figure 13 is the map I created with the collected GPS points which are supposed to be where we marked trees for the navigation map but I would not trust these GPS locations at all. One reason for this awful GPS accuracy is the change in elevations throughout the Priory property as well as the thick vegetation canopy. The e combination of these two factors makes it very difficult for the GPS to record accurate information. The signal from the satellites gets bounced around off of trees and elevation above you causing large error in the collected data. For all of the locations where we collected this makes sense because we were down in a large gully that was at least 20 meters lower in elevation than the upper part of the property. I also mentioned that the area we were walking through had very thick vegetation. There was low ground vegetation just above our heads and another layer of tree top canopy. Both of these vegetation layers cause interference with the GPS readings. Another reason for possible error was that we could not get the GPS to collect points while we had our navigation map open on the unit. To fix this we manually collected the GPS locations for each point by looking at the GPS which gives latitude and longitude all the time for your current location. The lat long was collected in a cell phone memo sheet and later put into an Excel spreadsheet (Figure 14). Once it was in that Excel sheet it was then imported into ArcMap and assigned a coordinate system. This was much more time consuming and frustrating than it would have been if we had been able to just record the locations with the GPS itself and load the locations into ArcMap with a coordinate system and everything all set up.

Figure 13 This is a map of the location that we collected with the GPS of where our navigation course points were supposed to be. Points 2,3 and 4 are fairly close, within 10 meter or so of where they should be however points 1 and especially 5 are way out of place. This could be caused by high interference with the GPS signal or possible human error when we were collecting the points. The green box on the map is around the Priory property so you can see that the points were not even close to that property.

Figure 14 is the Excel table that I created with the Latitude and Longitude of the points we collected. What you see is not lat long but decimal degrees which are used with UTM system. Using an online converter I was able to take the lat long and get the decimal degrees for each point.

This data that we collected in figure 13 will most likely have to be recollected using a different GPS unit. In order to do this we will have to use our orienteering skills previously learned in this class to essentially run our own course we created and find our points. An accurate GPS location will be collected so that Dr.Hupy can actually use this course and know where the points are in the woods on the property. Figure 15 is a map showing the comparison of the plotted points and the GPS locations we collected. These points should be exactly the same or at least very close but they are not even close and that is why the locations need to be recollected.

Figure 15 This is just a map of both sets of points to show how far off our GPS collected points were.

 Conclusion

This activity was good because it made us use multiple skill sets we have learned during the semester. We used our knowledge of a Trimble Juno unit along with ArcMap, our orienteering knowledge from last week as well the process of creating a navigation map again with our plotted course points. Again the pre planning came into play more than other activities this semester and we see again how technology does not always make things easier. Human error and attention to detail were also important to the success of this activity. It appears as though our group may have made some mistakes in data recording but it is also possible that our GPS unit failed us. The only way to know is to take another GPS unit to the location and repeat the collection of the new course points. 

Activity 10: Field Navigation Using Orienteering Methods

Introduction

The activity this week made use of navigation maps the class made earlier in the year in Activity 3 The maps were used to navigate a course set out by Dr. Hupy at the University Wisconsin Eau Claire Priory. 5 points through out the wooded area of the property were found by using orienteering techniques which were learned when we constructed our navigation maps about a month and a half ago. Each group was assigned a different order of the 5 points so group wouldn't just follow each other around.

We were split up into groups of three which is the ideal number when doing orienteering exercises. Each person in the group has a different task which included the bearing finder holding the compass, a pace counter and a runner. Before heading into the woods we were given the UTM and lat/long positions of each point which we then placed on our navigation maps. All the groups started from the same location and took pictures of each stop to prove they had been there. The points were marked with pink tape around birch trees. 

Study Area 

The Priory (Figures 1,2) is a large piece of property owned by UW-Eau Claire about ten minutes away from the main campus and 3 miles south of Eau Claire. At the current time it is serving as a children s daycare center and dormitories for UWEC students. The majority of the property is heavily wooded and rather hilly which made navigation rather difficult. There is lots of buck thorn and brambles as well as downed trees and other obstacles to navigate around. While navigating between points we tripped and stumbled on logs and stumps and slid down steep embankments which made collecting an accurate pace count difficult. Although the terrain is somewhat challenging the other field conditions were perfect. It was a sunny spring day with hardly any clouds and a air temperature in the mid 70s. There was a slight breeze which kept us cool while trudging through the woods and the navigation area was dry with no mud to slip on. We heard horror stories of past years when this activity was done with snow on the ground so I am thankful that was not the case for our activity. The nice weather made this activity easier and more enjoyable.

Figure 2 This sign at the Priory entrance.

Figure 1 is a view of the front of the main
building on the Priory property where the child's
daycare and college  dormitories are located.

Methods

Upon arrival at the Priory Dr. Hupy gave each group of three people as set of 5 coordinates,each set being in a different order. Each group was then told to plot these points on the previously created navigation maps. The groups used UTM grids and meter increments given them to plot the points (Figures 3, 4). Our group right away recognized that the scale on the UTM grid was incorrect. The scale was too large and did not include enough decimal points to differentiate between each grid line. This significantly decreased the plotting locations accuracy which made the navigation to each point more difficult as well. We knew general ballpark of the points but we were off by roughly 10 to 15 meters on each point. Thankfully the trees did not have leaves on them and the pink tape stood out and was easy to see.

     

Figure 3 This is the 5 points we were given to plot. Text boxes and the bad scale on our map made it difficult to accurately plot the points, which did create problems for us later on in the exercise.  

Figure 4 is a map showing the Priory property. The red box is  where the navigation exercise was supposed to take place but as you can see the course ended up being slightly outside that area.

After each group had the points plotted Zach Hilgendorf, a classmate with knowledge on orienteering went over the a review of materials and basic procedure we had read about previous to coming in the field. He did a demonstration of how to properly use distance-bearing navigation to navigate from one point to the next.The first thing to do is assign each group member a job. Again the three roles are the bearing locator, pace counter and runner. In order to find a bearing you use a compass(Figure 5). You align the edge with the point where you are currently located and the next location. The direction of travel arrow on the compass always needs to be pointed at the point you want to go to next. Then spinning the dial on the compass and pointing it to true north on the map the bearing line will show you the direction of travel (Figure 6,7). Then remove the compass from the map and line the red north arrow up with the red arrow outline in the bezel of the compass. This is referred to as putting red in the shed. As long as you keep the red in the shed the direction of travel arrow will always point you to your next location failure to do so will lead to incorrect navigation headings and a lot of wasted time.

Figure 5 is an orienteering compass similar to the ones we used for this exercise. You can see all the different parts labeled above. Knowing how to use this device properly is the key to this exercise. 

Figure 6 shows a student setting
up the bearing on the compass. Setting north
 on the compass to true north on the map 
to get the bearing direction.

Figure 7 is Dr. Hupy giving instructions
on how to plot points to the groups of 3 and
giving final instructions before we headed into 
the woods.

Next the runner the is sent out to a set landmark or recognizable point in the exact bearing of the next location. Once the runner reaches this point the pace counter walks in a straight line to the runner recording how many paces he/she takes to get a rough estimate of distance traveled. Comparing this pace count to measured lengths on the map tells you approximately how far it is between the points. This process is repeated for each location.

Once this demonstration was over we were given the OK to start navigating to the first point. We started at a light pole just off of the parking lot (Figure 8) and set our bearing based on our map towards the first point. The runner was sent to the edge of the woods to a large tree in the bearing direction followed by the pace counter recording the distance. This was repeated again and in a short time the first point (Figure 9) was found on the edge of an open area. The location of this point was very visible so navigation right to the point was not necessary because it could be seen from a ways away. This navigation only took 5 minutes or so.

Figure 8 is the light pole from which each group
 began  their navigation to the other 5 points.

Figure 9 is a picture of point 1 proving that
we were there.

The next point was more difficult and the error of locations on our navigation map came into play. We followed the bearing and estimated the distance but overshot the point. We actually ended up finding point number three instead (Figure 10) about 20 minutes later. We then back tracked from point 3 to 2 which were fairly close together. We had missed point two the first time by a good 20 meters again because of the bad scale on our map. Point 3 to 2 (Figure 11) took about 10 minutes to navigate.

Figure 10 is a picture of point 3 proving that 
we were there.

Figure 11 is a picture of point 2 proving that 
we were there.

We then navigated from 2 to 4. Point 4 (Figure 12) was pretty easy to find. We had a good bearing and had a pretty accurate idea of distance but simply went too far. It was hidden over the side of a bank which we walked right past and failed to look down the embankment.  We only had to backtrack about 4 meters to find the point so we were very close with our calculations. Had we not overshot the point it wouldn't have taken as long to find but it took about 15 minutes because of that mistake.

Figure 12 is a picture of point 4 proving that we were there.

The final point (Figure 13) was rather difficult. Our bearing for this point was not spot on again caused by the map scale and this sent us into some very thick brush where our pace count got very skewed. For most of the navigation we figured that 85 paces would be close to 100 meters in distance but in this area it was more like 100 paces equaled 100 meter because of the small steps through thick brush. For this point we got our bearing and then split up and moved in a line in that bearing direction. This helped us to covered a wider area and increase our chances of finding the final point. This strategy worked. I crested a hill and down on the other side was the final point. The bad bearing and thick brush made this the longest navigation of about 25 minutes.

Figure 13 is a picture of point 5 proving that we were there.

Discussion

This excise had components that worked well and others that did not. It was quite difficult to use this technique in the heavily wooded and brush areas of the Priory. I did not expect it to be that difficult but all those obstacles really add up. It was hard for the runner to find a good distinguished position in line with the bearing because of all the brush and branches in the way. The pace count is what was effected the most by the terrain and study area features. Some places you could walk easily using the 65 paces per 100 meter measure but other places struggling through brush is almost 100 paces for 100 meters. Changes in elevation also greatly effected the accuracy of the pace count. Our map scale also made this exercise more difficult than it had to be. If we had had a better map scale we would have been more spot on with our bearings, cutting down on the time it took to find the points.

Even with these difficulties we were still able to find all 5 of our points in a relatively short time finishing before the other teams and finding points from previous years exercises that were still in the woods which Dr. Hupy was searching for using a GPS unit. 

Conclusion

This activity went quite well overall. The weather and lack of leaves on the trees were huge contributors to this result. The preparation in class for this exercise in previous weeks was also very helpful in the execution. All the groups found all of their points in order for the most part. This coming week we will be creating our own orienteering course at the priory using GPS units and Arcmap to plot the points on a map and then go into the woods find the locations and mark the trees for future classes to navigate. It will interesting to see how well the GPS units do in the woods with leaf cover and large elevation changes throughout the property.

Activity 9: Surveying with a Topcon Total Station and GMS-2 GPS Unit

Introduction

The last couple of weeks we have been working on two different but very similar projects. Dr. Hupy assigned us to use a couple of different pieces of technology to collect elevation data of the campus mall here on the UW-Eau Claire campus between the Davies student center and Schofield Hall. The two different equipment pieces we used were the Topcon Total Station (Figure 1) and the Topcon Tesla GPS unit (Figures 2,3,4). With both of these pieces of equipment we were to collect elevation points and create interpolated surface maps with the results of each and compare the two methods of data collection. A previous activity where we collected distance/azimuth data is a simple way to do what we are doing with these high tech units however we did not collect elevation data which is vital for creating interpolated surface maps. These high tech units increase accuracy in most cases and give you that important elevation measure at a very high accuracy. These high tech units are costly however. They are expensive costing thousands of dollars and it is very time consuming and inconvenient because of the amount of equipment you have to bring with you to conduct the survey and collect the data. The complexity of these units is much greater as well so knowing when to use them compared to just doing a simple distance/azimuth survey is important.

Figure 1 This is the total station. It is used to conduct a surface survey as it can provide distance/azimuth and elevation data with high accuracy. This is a very pricey unit with a cost of 5 to 6 thousand dollars.

Figure 2 This is the Telsa GPS survey grade unit. This is the main console with all the different programs and tools installed on it. It is both WiFi and Bluetooth enabled which is why we need a MiFi console Figure 4. This is where you create files to store the data collected.

Figure 3 This is the GPS part of the unit. This communicates with the console above through Bluetooth. This will give you 2 to 3 millimeter accuracy of the location of data points being corrected. Elevation or Z values are also very accurate when collected with this unit.

Figure 4 This is a MiFi unit. This uses a 4G cellular connection to provide WiFi signal for up to 15 devices. This is used with the Tesla unit to increase location accuracy and enable wireless data transfer.

There is alot of new technology and processes to learn for this activity and that is why we spent basically a whole class period learning from Dr. Hupy how to operate these units. Set up and use of these units is a little tricky and needs to be repeated a couple of times before the work flow becomes easier. First we started with a general overview of the units and their purpose and Dr. Hupy emphasized the importance of being careful with them and handling them with care because they are very expensive. Another key point he emphasized is the importance of making sure both the Tesla and total station are level when data is being collected. This takes time. Through adjusting the tripod legs and black knobs on the total station it is leveled and when using the Tesla just tilting the pole until the circle level is inside the ring will do the same. The total station was definitely more difficult to level off. After the units are leveled Dr. Hupy explained how to collect the data which I will explain later in the Methods section of this post. 

Each group was to collect 50 points per person with the Tesla GPS unit and as many as we saw fit with the total station. My group collected 150 with the Tesla and 50 with total station. This data was then imported into ArcMap and surface maps were created from it.

Study Area

The area Dr. Hupy wanted use to collect data in is what we refer to as the campus mall Figures 5. It is a large open area in the middle of lower campus. It is fairly flat for the most part with little elevation variation however the whole area is pitched towards the south and the Little Niagara Creek Figure 6 that runs through lower campus next to the Davies student center. This activity was delayed because of  rain and poor weather in which these units should not be used in. The days data was collected were sunny spring days in the mid to upper 60s with little wind.

Figure 5 View of the campus mall from the occupy point during our total station data collection. Schofield Hall is on the right and Davies Center is on the left with the library at the end.

Figure 6 Little Niagara Creek runs through the middle of the campus mall past Davies Center.

Methods

Total Station Collection

First step to collecting our data was check out the equipment from the Geography department here on campus. We then walked from Phillips Hall to the campus mall to set up the total station. Before the total station was put in place and leveled two points had to collected with the Tesla. These two points are called the occupy and bascksight points. The occupy point is where the total station would be set directly above and stay during the duration of the data collection. The backsight point is recorded to give the total station a zero point from which to calculate the azimuth values. This backsight point is what the total station will record as North. Once the location of these two points is recorded the total station can be setup and leveled off to start data collection. The first step in setting up the total station is opening up and tripod that the station sits on. Then the station is mounted to the top and screwed into place. Then using the built in laser on the station we made sure that the station was directly over the occupy point location collected earlier. Once this is done then the tripod legs can be pushed into the ground and the leveling processing can begin. There is a circle level on the tripod stand and the key to making sure the stand is level is to get the bubble into the center ring of the level. This is done by slowly sliding the tripod legs one at a time up or down. Once the stand is level the next step is to level the total station itself. There are two tubular levels one on each side of the unit. There are 3 black knobs on the bottom of the unit at each corner. When turned these move the unit up and down slightly allowing you to level the unit. 

Once the unit is leveled the collection can begin. The total station is connected via Bluetooth to the Tesla console (Figure 2) which caused a lot of headaches for most groups. Once connected a new job is created where the data points will be stored. In order for the collection locations to be accurate the occupy and backsight point are entered in the file setup. It also asks for a height of the station off the ground as well as the height of the reflector (Figure 7) off the ground. In our collection the total station was 1.55 meters off the ground and the reflector was 2 meters up. Making sure these heights stay consistent during data collection is vital for accurate elevation measurements. Once this is all set up point collection begins. 3 person groups are ideal for this exercise so that one person can focus the total station, one can walk with the reflector pole and one can record the points in the Tesla console. Point collection was fairly easy after setup was complete. To collect a point the person holding the reflector picks a location and then holds as still as possible facing the reflector as straight back at the total station as possible. The person at the total station then uses the top sight to find the general location of the reflector. Then looking through the scope and using the adjustment knobs to move the scope up, down, left and right the cross hairs are placed on the center point of the reflector. Once the crosshairs are locked on the person on the Tesla console taps the collect point button. The total station will then collect the azimuth, distance and elevation for that point. This process is repeated for as many points as the user desires. We collected 50 points in approximately 30. Getting the crosshairs locked in is the most difficult and time consuming part of collection but the more you do it the better you become at locating the reflector and locking on.

Figure 7 This is the reflector that the total station shoots the laser beam at to calculate distance when taking the survey. It is hard to see but there are 3 lines that intersect in the middle of the scope and that point is where you want to line up the crosshairs of the total station scope on to get an accurate reading.

Tesla GPS Collection

The data collection with the Tesla GPS unit was much simpler and quicker. The GPS unit Figure 3 is mounted on the tripod with the MiFi velcrod to the pole and console either attached to the pole or carried. The MiFi, GPS and console are all powered up. Once the console is connected to the MiFi connection the GPS can be connected to the console via Bluetooth just like with the total station. Once everything is connected the next step is to create a new file to store the collected data in. Then inside that file collection begins. In order to collect the points the tripod is leveled using the circle level attached to the tripod. Once it is level all you have to do to collect a point is tap the collect point button on the console. We did this for a 150 points throughout the mall. It took about 2 hours to collect the points just because there were so many. The setup is simple and collection is easy.

Results

Once the data was collected using each method the files were dumped onto a computer in the form of a text or .txt file. This files include the latitude, longitude, height and name of each point that was collected in the field. Once the text files are of the console they are imported into ArcMap. They show up as a bunch of points on the map but when the interpolation tool is used a surface elevation map is created in both 2D and 3D. Figures 8,9,10 and 11 below are the resulting maps from the two surveys.

Figure 8 This is the interpolation of the points collected with the Tesla GPS unit. I used the Kriging interpolation method to create this map. You can see the elevation change of the campus mall from this 2D map.

Figure 9 This is the interpolation of the points collected with the total station. I used the Kriging interpolation method to create this map. You can see the elevation change of the campus mall from this 2D map.



Figure 10 This is the 3D surface map of the campus mall collected with the Tesla GPS unit. I exaggerated it by 2 to make the elevation change more apparent because it is really hard to see using the actual elevation values. This unit captures the surface a little better probably because there are 3 times the number of points in this model than there are in the total station model.  As you can see the campus mall is a pretty flat area.




Figure 11 This is the 3D surface map of the campus mall collected with the total station. I exaggerated it by 2 to make the elevation change more apparent because it is really hard to see using the actual elevation values. This representation isn't as accurate because there are much fewer points used in this model. The weird point that is in this image is most likely where the total station was sitting while collecting this data. That point is obviously an error created by ArcScene.

Discussion

Both of these units and data collection methods are important to know how to do and very applicable in real world situations. One is obviously easier to do than the other. The total station has a much higher cost associated with it. Not only does it cost a large amount of money but the time and knowledge that is required to use is also very high. The frustration and time wasted while trying to get it all set up properly and get everything on the total station and the Tesla console to work together was a big annoyance and set back. It took us about twice as long to get everything set up and working than it did to collect our survey data. This goes back to what Dr. Hupy told us a couple of weeks ago that the more technology you are relying on the better chance that it won't work. That is why knowing how to do a distance/azimuth survey with very little technology is a good skill to have. Even when Dr.Hupy was doing demonstrations in class of how to use the units they weren't always working right. He wasn't doing anything wrong that is just what happens many times when working with high tech equipment. The biggest problem we ran into is getting the Tesla console to connect to the total station via Bluetooth. I turned them both on and off a couple of times before they finally connected to each other. Once it was connected everything went smoothly. Setting up the tripod for the total station was also a little tougher than I thought it would be. Getting it level was difficult. Overall the total station is a longer more involved and frustrating process.
Using the Tesla GPS was much easier in my opinion. Everything connected the first time we tried and with this unit one person could have collected all the data. You don't need three people. The data collection went much faster because you didn't have to find the reflector every time you collected a point. Getting the tripod level was the biggest part of the work for this method. This process can be sped up by not using two of the legs on the tripod and just using the center pole with the level on. Simply holding that middle pole and leveling it allows you to move much more quickly than trying to level out all three legs at every point. Being careful to keep the pole steady while collecting the points is the biggest concern when collecting data in this way. The Tesla GPS overall was much quicker and user friendly in my opinion there was much less equipment to bring with you, fewer moving parts, less back and forth between devices and less human input required.

Conclusion 

This semester we have now learned the low tech way (azimuth/distance) and high tech way (total station and Tesla GPS) to conduct a survey. Both ways have advantages and disadvantages and the usefulness of each is dependent on the situation. However if it is accuracy that you want which is the case most of the time I would chose the high tech method. Even though it can be more time consuming and frustrating the results tend to be much more accurate and reliable. It also provides you with elevation data without which creating surface models like we did in this activity would be much harder or even impossible. This activity taught us how to use these new technologies, work together in teams and again do some more work in a GIS sharpening those skills. Overall a good exercise it was frustrating at times but the end result that can be created from this highly accurate data what makes the activity useful.

Activity 8:Conducting a Distance Azimuth Survey

Introduction

This week Joe Hupy gave the class the assignment conducting a survey through the use of the distance and azimuth method. The most important part of this method is finding a base point. Once you have that point it is used to map out all the features in relation of distance and azimuth to it. This is a low tech method that can be used when technology and more advanced methods fail or are not possible. This could be caused be bad weather like extreme cold or hot temps that cause the instruments to malfunction or something as simple as running out of battery. Technology does and will fail and this method gives you an easy and effective alternative. There a couple of different ways the data could be collected for this exercise. You could two separate instruments to find the distance and azimuth such as a range finder (Figure 1) and a compass (Figure 2). In our case we got to use a instrument that can do both at the same time. This was very handy and a big time saver. We used a TruPulse laser (Figure 3).


This is a Vector Optics laser range finder. By looking through the lenses and placing the crosshairs on your target it will read the distance you are from that object. (Figure 1)



This is a Suunto compass. You can find azimuth by looking through the hole on the compass and when you point it at the object you want to find the azimuth for it will display in that hole. (Figure 2)

This TruPulse laser unit will find both azimuth and distance at the same time. These are the units we used for this exercise. (Figure 3)

Joe Hupy took us outside into the Phillips Hall court yard here on campus and gave a quick demo on how to use this equipment. He then split us into our groups for the week and gave us the assignment. We were to find a study are that was 1/4 to 1 hectare in size to collect our data in. In this area we were supposed to collect at least 100 data points recording their distance, azimuth and a couple other attributes of our choice for each one. After the data is collected it will be imported back into ArcMap where it will be used to make maps of the collected points.

One thing Joe told us to consider is Magnetic Declination. It is the angle between magnetic north and the true north which changes as the earth's magnetic field varies based on location and time. I looked on line and found a website dedicated to Magnetic Declimation values based on your search location and it said that on the day our data was collected the declination for Eau Claire was one degree west. This means our recorded data will be one degree less than true north. This isn't a huge factor here in Eau Claire but in other areas of the world this declination value can be much higher.

Methods

Study Area

The first step of the assignment and data collection was to choose a study area. Our group decided that the parking lot area behind Davis Center and Phillips Hall here on campus would be a good location (Figure 4). We were interested in collecting car data so this was a very well suited location. There are lots of cars in a relatively small area making the collection of 100 points pretty easy. In order to find a base location we opened up Google Earth and looked for easily identifiable objects in the this area that would also give us a good view of the parking lot. We also found the latitude and longitude for our base locations which will be used at a later time in ArcMap when creating our maps. We determined that one of the statues behind Phillips Hall and a sewer cap down by Davis Center would be the best location for our base points. They were both raised platforms which made the cars easy to see and not only see one row but multiple rows of cars. Figures 5 and 6 are panoramic views from our two base locations.

Figure 4
The red rectangle in the image shows our study area behind Phillips Hall and the Davis Center.

 

Figure 5
Panorama view of base point 1

Figure 6
Panorama view of base point 2

Survey Process

In order to collect our data and get values for distance and azimuth that were as accurate as possible we mounted the TruPulse laser to a tripod for stability and base point location accuracy. Keeping the laser unit in the same base location while collecting data is essential to getting accurate readings. We took turns locating cars and firing the laser to gather our distance and azimuth values. The other team member was recording these reading as well as our other attributes such as car color and brand. The distance was recorded in units of meters and the azimuth was collected in decimal degrees. We gathered the data in increments of 10 to 20 cars row by row to make it easy to keep track of what cars we had done. In some cases it was difficult to get the TruPulse to get an accurate reading on the distances of the cars. Shadows and reflection from the sun were likely contributors to this problem. Keeping the TruPulse steady was difficult at times as well which also contributed to less accurate or more time consuming readings.

 

Data Entry and Mapping

All of our data points were collected in a Excel spread sheet using one of the Geography departments Microsoft Surface tablets. Having that tablet in the field was super convenient because instead of having to write down the data and later transfer it into an Excel sheet we could do all that in the field as we went. Figure 7 a and b is the resulting Excel sheet which we then imported into ArcMap.

 

Figure 7b

Figure 7a

 

 

The first step of the mapping process in ArcMap was to add a basemap. This gives us a visual reference as to where our data points were collected. For my base map I used an aerial photo in the geography departments Eau Claire County data folder (Figure 8).

Figure 8
Aerial photo from Geography GIS data folder

 

 

Next a geodatabase was created to hold all the collected field data. This is where the Excel spread sheet will be imported to. We then needed to determine the location of our too base points. In order to do so we located them on Google Earth imagery and found location one to be 44.796908 N and 91.50104 W. Location 2 was 44.796408 N and 91.49952 W  (Figure 9).

 

Figure 9
Base points for data collection

 

Once we had our base locations we then imported the Excel spread sheet. In order to do this you right click on the geodatabase and hit import and then choose the Excel file. We now need to find the location of the surveyed features so that they can be mapped. We used the Bearing Distance to Line tool in ArcMap to do so (Figure 10). The tool takes the information in the Excel and turns it into a line feature class based on the an X and Y coordinate field (Longitude and Latitudinal location in decimal degrees), a bearing field or azimuth and a distance field. Figure 11 is the resulting map from running this tool.

 

Figure 10
Bearing Distance to Line tool

Figure 11
Line feature class generated by Bearing Distance to Line tool

 

This tool does not give you the actual location of the data points collected however for that a different tool must be run. Using the Feature Vertices to Points tool (Figure 12) in ArcMap points are placed at the end of the vertices giving a point for each collected data point (Figure 13).

 

Figure 12

Figure 13
Data points generated by Vertices to Points tool

 

These are only location points however we are interested in displaying the attributes we collected for each point as well. In order to this a simple join between these surveyed points and the original Excel sheet with the attribute information in it. The join is based on the ID fields. Once these are joined we were able to display not only the locations but the attributes we collected as well. Figures 14 and 15 show the collected data points sorted by color and car brand respectively.

 

Figure 14
Map showing data points by vehicle color

Figure 15
Map showing data points by vehicle brand

 

Results and Discussion

For the most part our data points seem to be quite accurate and line up with the real life aerial imagery very well. There is a row of cars that seems to be slightly off the actual arrangement of the cars in the parking lot but this could be due to old aerial imagery that has different parking spaces than the current layout of the parking lot. This also could have been user error causing inaccurate distance readings with the TruPulse unit. It also could have been incorrect entry of the distance values but this seems less likely because there seems to be a pattern to the location error. If it was incorrect data entry you would expect a point that is drastically our of place and random. Making sure the base location does not change during data collection is vital. Movement from the base point between point collection will give you inaccurate readings. Like I talked about before other errors could be caused by shadows or sun reflecting off car windows which make it harder for the TruPulse to get an accurate reading.

Data collection went very smoothly for our group. We were familiar with the technology and technique we were to use and weren't really doing trial and error to find the best way to collect the data. This cut down on the time it took to collect our data and I think it also improved our data accuracy over someone who has never used this technology or method before. From reading past years blogs we could see what worked well and what didn't. From that information we made the biggest decision of where to put our base points for collection. The key to this exercise for us was the fact that our base points were elevated location that had few if any obstacles between us and the data point locations. We were able to collect our data in just over an hour which was pretty fast for the amount of points needed. If you were going to be out in the field for extended periods of time extra batteries or potable chargers for the tablet and TruPulse would be good to have. Anything you can do to cut down on the risk of technology failure is ideal.

Once we had our data collected the analysis and map creation for this exercise were fairly easy. It took about 20 minutes to run our tools in ArcMap and get the data in a displayable format. We only did 2 attributes for our points but the detail you could collect and display for each point is endless. It all depends what the purpose of the project is.

 

Conclusion

This is a low tech method of data collection. It is handy to know how to use because we all know technology fails from time to time. (Usually when we need it most.) This activity could have been done with a measuring stick and a compass, you don't need anything fancy. We were lucky using the TruPulse instead but it can be done in many other even simpler ways. The class leaned a valuable field skill that is applicable in many situations but more than that we learned the best way to do this technique and what to watch for that could reduce accuracy of your data.