Field Exercise 12 - Unmanned Aerial System Flights

INTRODUCTION

          For field exercise twelve our geospatial field methods class observed two Unmanned Aerial System (UAS) Flights. Both flights were done at the UW-Eau Claire Priory because there was a wide grassy expanse next to the parking lot that contained enough open space for both take off and landing. Both Unmanned Aerial vehicles (UAVs)(the iris and matrix) were multi-rotor UAVs so they didn't need a lot of room for take off and landing anyways. Below in figure one is an image showing the launch area for the UASs.

Figure 1: shows an image of part the UW-Eau Claire Priory property. The area surrounded by the red box was the grassy expanse south of the parking lot that the class used for the two UAS flights.

          It is important to remember that a UAS is composed of at least three different pieces of equipment. The first piece of equipment is the UAV or flight platform itself. The UAV is almost always rigged with different measuring tools, camcorders, and cameras so that imagery or climate data can be processed. The second piece of equipment is the transmitter. The transmitter contains the controls for the UAV and always has the final say in what the UAV does. This means that it can override autopilot in case of an emergency. The third piece of equipment is the base station and it contains the brains for the whole operation. All data acquired by the UAV is sent to the base station where it can be processed. The base station also relays the mission plan to the UAV. In our classes case we also had a tablet which acted as sort of a second base station.

METHODS

Mission Programming

 

          In field exercise four I discussed the versatility and applications of the different UAV types. This information can be viewed here. Because different UAV types have different applications the missions that they complete are going to be very singular to each flight scenario. This means that a different mission has to be programmed before each flight. This is not a problem because there is cheap easy to use software (mission planner or droid planner) out there that allows programmers to lay out a flight plan in a manner of minutes. I personally tested some flight planning software and it was as easy to use as Microsoft paint. I simply created way points where I wanted them by tapping on the screen and the UAV would fly to those points. Since the UAVs were multi-rotor UAVs I could also have them stall for a set amount of time. The image in figure two below shows the mission planner interface.

Figure 2: shows the mission planner interface. The touch screen of the tablet allows the programmer to draw out their desired mission with their fingers.

There were many other features I could've explored with the mission planning software but didn't have the time for. The software can be downloaded onto a phone or tablet with no license and it's free. Once a mission has been created for the UAV to fly It just has to be uploaded onto the platform through the base station pictured in figure three below.

Figure 3: shows the base station computer. The base station is the brains of the UAS and relays information to and from the flight platform.

Pre Flight

          Before the UASs could be launched a lot of pre flight and safety procedures had to be observed. The UAVs we were flying were not incredibly dangerous although their rotors probably could have taken a finger off, but they are expensive so great care was taken to ensure that they would take off, fly the mission, and land safely. The first thing taken into consideration was the weather. Wind speed, wind direction, and the probability of precipitation were three major weather factors that were taken into account. I f the wind had been too strong or it had started raining the flights would've been a no go. Rain was threatening but no actual precipitation had fallen, and the wind bordered on too strong to fly. The next thing checked was the UAV itself: props secure, cracks/chips, battery secure, antenna secure, sensor connected? Everything was a go so we powered up and performed another checklist: connected to satellites, connected to base station, batteries over 95 percent, transmitter on, batteries charged on transmitter, mission created, sensors on? The UAS was now ready to launch so we performed the take off sequence: throttle down, platform on, spectators clear, kill switch off, clear for launch, take off. Take off was performed manually by the course instructor and then switched over to autopilot so that the UAS could fly the mission that was programmed into it. It should be noted that during the "batteries charged on transmitter" phase, the batteries began smoking and had to be replaced with new ones. Images of the two UAVs in pre flight mode is provided in figures four and five below.


Figure 4: shows Iris UAV in pre flight mode

Figure 5: shows the Matrix UAV in pre flight mode

UAS Flights

          The first flight done with the Iris multi-rotor UAV went the whole length of the mission which looked like a Greek key design. The mission was really just created so that the class could see the UAVs in action. Even though the UAVs fly their missions on autopilot that doesn't mean that the pilots have nothing to do. It is important that there is a pilot manning the base station to give constant updates to the pilot on the transmitter controls what the status is of the flight. Updates on how many satellites are in contact with the UAS and the accuracy of the flight path are important. The second flight ended abruptly because of too much wind. The pilot manning the bay station informed the transmitter pilot that the UAV was trying to correct it's position on the flight path, but the UAV couldn't handle the wind gusts so it began to wobble dangerously. The transmitter pilot then flipped the HOME switch on the transmitter controls to bring the UAV straight back to the launch site. Figure six below shows the Matrix heading back to the launch site after it lost it's battle with the wind.

Figure 6: shows the end of the second flight performed by the multi-rotor Matrix flight platform

DISCUSSION/CONCLUSION

          Although I did not personally fly either of the UAVs observing the mission planning, pre flight, and launching proceedings was a good experience. It's not until you go through a process with someone who has done it a hundred times before that you learn all of the ins and outs of that process. Watching our course instructor harp on the importance of the pre flight and launch checklist really got it through to the whole class that these things are important to the success of the UAS mission. UAVs cost upwards of five hundred dollars and just one slip up can cost a flyer their UAV which is why it is so important to be completely prepared before launching.

Field Exercise 11 - GPS Navigation

INTRODUCTION

          In the previous field exercise our geospatial field methods class was tasked with navigating the rugged and wooded terrain of the UW-Eau Claire Priory using only a map and compass. The experience was a real crash course in field navigation. For this field exercise the class was tasked with navigating the same rugged and wooded terrain of the Priory but with a handheld GPS unit. The class was broken down into five different groups of three so that each group could navigate one specific area of the priory. To complete the navigation exercise each group had to mark off five different points of interest (POIs) on the maps we created for the previous field exercise (field exercise ten - orienteering with a map and compass) and navigate to them using a handheld GPS device. The five POIs each group marked on their maps of course corresponded to the area their navigation exercise was supposed to focus on. Once a POI was navigated to the group had to first, record the point on their GPS unit, second, mark a large tree on the point, and third, take a picture of its location. This process was repeated for all five points.

Study Area

          My group decided that we would take on the responsibility of navigating the far Northwestern corner of the Priory property. This corner of the property contained the most densely wooded and steepest terrain of any other area on the property. I was personally on board for choosing this area of the property because I thought it would be the most fun to navigate. After all what's a navigation exercise without some sweat and dirt mixed in? Figure one below shows a map of the UW-Eau Claire Priory and my groups area of interest (AOI).

Figure 1: shows a map of the UW-Eau Claire Priory and my groups corresponding AOI. The property line of the Priory is delineated by the black box, the five meter contour lines are marked with red lines, and my groups AOI is marked with a green box. 

METHODS

          As stated above my group and I navigated to five predetermined points located in the far Northwest corner of the UW-Eau Claire Priory property. My group and I tried to space out the points so that they were all equally far apart from each other. We also tried to locate the points on prominent land marks such as ridge tops and ravine forks. The five POIs that we marked prior to the navigation exercise can be viewed in figure two below.

Figure 2: shows the priory map and the five predetermined points which are marked with green dots. The five POIs are also labeled in the order which we navigated to them in.

In order to navigate to these five POIs my group and I decided to use a Trimble Juno 3 handheld GPS device. We chose to navigate with this unit because we were all very comfortable using this piece of equipment and It can obviously get the job done. My group and I were also carrying around print outs of the Priory map for easy reference. In order to navigate to the five POIs one member of our group was in charge of the GPS unit. This persons job was to make sure that we were always on course. Another member of our group was responsible for referencing the Priory map. This persons job was to make sure that the GPS was taking us in a sensible direction and that the GPS and Map were congruent with one another. The final group member was responsible for finding the quickest and most sensible path through the terrain. There job required them to constantly reference the map and their immediate surroundings. For our purposes it was this final job that proved to be the most important because of how rough the terrain was in the Northwest quadrant of the Priory property.

DISCUSSION

          After navigating to each of the five predetermined POIs, my group and I flagged a nearby tree and took a picture of it. Below in figures three-seven are pictures of the five POIs my group and I navigated to.

Figure 3: shows POI one. POI one was located just on the other side of the first big gulch that navigators have to traverse. 

Figure 4: shows POI two. POI two was located at the bottom of four converging ravines.  

Figure 5: shows POI three. POI three was located on the farthest point of the most Northern knob on the Priory property.



Figure 6: shows POI four. POI four was located at the top of another ravine and was quite close to someone's backyard shed.

Figure 7: shows POI five. POI five was located at the fork of two converging ravines and stands out in the open.

          Even though we were all comfortable with GPS unit my group had problems with it because we did not make any of the features editable. We could still take points of our locations, but using it for navigating to the five predetermined POIs was impossible. My group and I troubleshot this problem by utilizing the orienteering skills we garnered in the previous field exercise. We had a map and compass so we just followed our compass bearing until we reached where we had marked on the Priory map.

CONCLUSION  

          The exercise for this week was very similar to the prior weeks exercise albeit not as intense because we chose the points we were navigating to. My group's GPS unit failed to help us in our navigating efforts so it was a good thing that the previous weeks orienteering exercise prepared us to navigate with a map and compass. Overall I'm glad we did another navigation exercise because I think it's a fun way to learn and be active at the same time.

Field Exercise 10 - Orienteering With a Map and Compass

INTRODUCTION

          For field exercise ten I was required to navigate a woodland through a method called orienteering. In brief, orienteering is the navigation of terrain using a map and compass. Orienteering is very much like a sport in that it is a race done at speed. For my purposes though, the orienteering exercise was not a race but rather a way to become familiar using a map and compass. Why the use of such rudimentary navigation tools? Sometimes technology fails and a GPS device cannot be relied on and in these situations it is necessary to navigate with what you have.
          For field exercise ten our geospatial field methods class was broken down into five groups of three. Breaking the class up into groups of three was a strategic move by the instructor and will be explained later. Each group of three, using only a map and compass, was required to navigate to five different control points that the instructor marked with tape prior to the exercise. Each group was given a different order in which they were required to navigate to each of the five points which prevented groups from following each other and colluding. Groups were required first: to mark the five control points on their respective maps, second: to actually navigate to the control points in the proper order, and third: to take a picture of the control point marker and move on to the next one.

Study Area

 

          The study area or area of interest (AOI) for field exercise ten was the UW-Eau Claire priory. Located approximately 3.1 miles south of the main Eau Claire campus the priory is a heavily wooded area with a day care/dorm on the south side of the property.  The map created for field exercise three (figure one below) is the priory map that will be used for this orienteering exercise. As seen in figure one below their are dark red contour lines which show five meter intervals in terrain relief. Due to the dispersal pattern of these contour lines it can be surmised that there is quite a bit of relief especially on the west side of the property. The base image of the map also shows that the property is mainly made up of trees which will make for rough going.


Figure 1: shows a fifty meter grid map of the UW-Eau Claire priory. The 5 meter contour line feature class is depicted using dark red lines, the navigation boundary feature class is depicted using a faded grey outline, and the aerial image of the priory can be seen as the base for the whole map. I also added the latitude and longitude onto this map as can be seen by the small black numbering and tick marks on the periphery of the map. All of the other elements that go into creating a proper map including scale bar, legend, north arrow, meta data, title, and my name are also included.

METHODS

 

Map Preparation

 

           The first task preformed for field exercise ten was preparing the maps for orienteering. In order to do this each group of three had to first mark the five control points on their respective maps. The instructor provided us with the lat/long positions of the five control points, and since I implemented lat/long onto my map in figure one above it was simply a matter of marking the point on the map with a blue marker. Each group then had to draw lines in between the points with a straight edge in order to delineate the direction they must head from point to point. Remember that the direction and route each group takes will be different from every other group because they must navigate to each point in the correct order. Once the lines were drawn my group and I estimated the pace count between each point using my pace count, which I measured back in field exercise 3, and the map's scale bar/reference scale. To estimate the pace count between each point I first used a ruler to measure in between each point knowing that two centimeters was roughly 100 meters. Knowing from my pace count that 100 meters is roughly 65 paces I could then do simple math to figure out the distance or pace count between each control point. In figure two below is our orienteering map with the five control points, lines of direction, and pace count drawn in.

Figure 2: depicts the UW-Eau Claire priory map as well as drawn in features including five control points, lines of direction, and pace count. All of these drawn in features fall within the lime green box on the map which made for some small and detailed orienteering work. It should be noted that the west side of the property (the area we are navigating in) is the side with the most steep and rugged terrain. 

 

Compass Navigation

 

          The second task preformed for field exercise ten was learning how to actually navigate with a compass and map. The image of a compass in figure three below can be referenced as I go through the procedure of using a compass.

 

Figure 3: shows a labeled compass. The important labels to pay attention to are the direction of travel arrow, the dial or bezel, the orienteering arrow, and the needle.

          The task of teaching the class how to navigate shall be accredited to our colleague Zachary Hilgendorf, who briefed the class on how to properly use a compass for navigation. His instructions were as follows: first, place the compass over the map with the straight edge scale running parallel to the line of direction drawn on the map; second, swivel the bezel of the compass so that the built in red arrow (orienteering arrow) is facing north on the map; third, place the compass in your hand and get the floating needle to match up with the orienteering arrow (this is called putting red in the shed); and fourth, once red is in the shed follow the black line of direction arrow to the control point drawn on the map.

 

Group Dynamic

 

           Now that compass navigation has been explained it is time to explain how to physically navigating utilizing the group dynamic. In other words each group member is responsible for his/her part of the orienteering to ensure smooth navigation. There are three basic jobs the first of which is to use the compass to find the line of direction or azimuth in which to travel (this person must also stay put once they find the direction of travel), the second is walking to a point of interest that lies in the direction of travel, and the third is to pace off the distance between each point of interest. I will now give an example of how a group might navigate to a control point. I will refer to each group member by their job (job1, job2, job3). Job1 uses the compass and the map to find that the group's direction of travel is 180 degrees or due south. Job1 then directs job2 to a point of interest that is due south. This point of interest could be anything but a tree will work nicely. Once job2 has successfully made his/her way to the point of interest job3 will walk directly to this point while counting his/her pace. After job3 has reached the point of interest, job1 will walk to job2 and job3's position and repeat the process until they have reached the final control point.

 

DISCUSSION

 

          My group's specific route taken for the orienteering exercise is pictured below in figure four. This image is a cleaned up version of the route within the green box in figure two. This image shows the order in which we navigated to the control points, direction of travel, and the paces between the control points.

Figure 4: shows a clear image of the route taken for the orienteering exercise. The five control points are shown using red dots, the direction of travel is shown with blue lines, and the pace count is shown in black type. 

 

My group navigated to each of the five control points and took a picture at each one to prove we did indeed navigate to each point. Figures five, six, seven, eight, and nine show control points one, two, three, four, and five respectively.

Figure 5: shows control point one. Traveling to point one from the starting point was by far the farthest travel distance between points. Because the distance was so great it was also the trickiest marker to find. Control point one was the farthest north of all the points and it was located in a deep ravine. The ravine was deep enough to where a person would have to stand on the lip of the ravine in order to look down and see the marker.

Figure 6: shows control point two. The proximity of point two to point one made it the easiest marker to find. Control point two was also located on the top of a small hill making it easy to see from a distance.

Figure 7: shows control point three. Control point three was easy to spot as well because it was located on the edge of a clearing. Traveling to control point three was done through unconventional means due to its proximity to the starting point.

Figure 8: shows control point four. Control point four was of medium toughness to find. It was located in some thick brush and the group was forced to traverse a few ravines to get to its location, but good orienteering mechanics saw us there quickly.

Figure 9: shows control point five. Control point five was located on the edge of a very steep ravine. This point would have been tough to spot due to its location but the group was lucky enough to navigate directly to the marker.

 

          My group and I did encounter a few problems while orienteering through the priory's woods. The first problem we encountered was missing control point one. We ended up about twenty paces west of the control point due to the confusion that was caused by heavy undergrowth. Orienteering through thick brush can cause a navigator to lose his/her sense of direction because its difficult to keep one's bearing and sense of direction. My group and I ended up navigating to control point four because it was a known location and from there we re-assessed our situation and navigated to control point one. Part of the reason why we had difficulty finding control point one was the fact that it was located down in a ravine beneath the lip if the ravines edge. Twenty paces west of the control point may not seem like a huge distance, but where steep and rugged terrain is involved it can make all the difference. Our group also had difficulty keeping our pace count because of how difficult it was to walk in a straight line through the thick brush. To take an accurate pace count it's necessary to walk in a straight line so that the count is not skewed. This was an all but impossible task, therefore, our groups pace count was less accurate than expected.

          Navigating to control point two went off without a hitch and so did navigating to control point three, but as mentioned above in the caption of figure seven, my group and I navigated to control point three through unconventional methods. Because control point three was located due west of the priory building clearing, my group and I navigated to the clearing in order to avoid walking through the thick underbrush of the woods. We then chose a large tree that was located due east of control point three and traveled west using traditional orienteering methods. By utilizing the priory clearing my group and I did not travel directly to control point three from control point two  (as the crow flies), but we saved time because we didn't have to pass through the thick underbrush of the woods. Figure ten below shows the path my group took to get to control point three from control point two.

Figure 10: The green line shows the route my group and I took to get to control point three from control point two.

 

          Navigating to control points four and five went smoothly for the group due to excellent navigation methods. As mentioned above control point five was located on the edge of a very steep ravine so depending on where the navigator was standing it could have potentially been very hard for them to spot the marker.

 

CONCLUSION

 

          Navigating through the woods using only a compass and map is not only a sport (orienteering) but a necessary skill that every navigator should have. In todays technological world there are many different GPS units that will navigate you to where you are going, however, sometimes technology fails and rudimentary navigation skills will have to be relied on.  Overall the orienteering activity performed for field exercise ten was very successful due to its interactive quality. Every student had to be on top of their game and aware of what each group member was doing at all times because the success of the group hinged on each individuals navigation efforts. Although my group and I ran into a few problems such as missing the first marker and having to refigure our position and not being able to keep an accurate pace count, we learned a lot from the hands on experience.

Field Exercise 9 - Topcon and Total Station Topographic Survey

INTRODUCTION

          For field exercise nine a partner and myself were tasked with carrying out two topographic surveys of UW-Eau Claire's campus mall. The first topographic survey was measured and recorded using a Topcon HiperSR GPS unit and a Topcon Tesla unit, and the second topographic survey was measured and recorded using a prism pole, Topcon Total Station, and Topcon Tesla unit. The purpose of this field exercise was to create elevation maps of the UW-Eau Claire campus mall, and get students familiar and comfortable using modern surveying equipment.
          There were three reasons why my partner and I were required to conduct two different topographic surveys of UW-Eau Claire's campus mall. The first reason as discussed in previous blog posts is to always come prepared with a back up plan in case of equipment failure in the field. One piece of equipment or method may not work for every surveying scenario so it is a good idea to come prepared with back ups. The second reason for conducting two surveys of the same area of interest (AOI) is that after both surveys are conducted my partner and I could compare the two sets of data to see which method ended up working better than the other. The third reason for conducting two different surveys is that a lot of firms have budget constraints and aren't able to afford the newest surveying technologies. If this is the case it is important to be able to use older equipment and methods to get the job done.

STUDY AREA

          The study area for field exercise nine was the UW-Eau Claire campus mall. Surrounded by Phillips hall in the southeast, the Davies Center to the south, McIntyre Library to the west, and Schofield Hall to the north, the campus mall is located in the center of UW-Eau Claire's lower campus. The UW-Eau Claire campus mall's position can be viewed relative to the surrounding academic buildings below in figure one.

Figure 1: shows the campus mall which is outlined in red. Both topographic surveys are to be conducted on the campus mall for field exercise nine

Due to its flatness, openness, and relatively small size the UW-Eau Claire campus mall is an easy area for students to survey. The only bad thing about surveying the campus mall is that it sees a lot of foot traffic during school hours due to its central location. This did not pose much of a problem when using the Topcon HiperSR GPS unit because lasers were not used to shoot positions, but when using the Topcon Total Station the laser that shot out to the prism pole was constantly interfered with by pedestrians. This interference may or may not have effected the integrity of the Topcon Total Station's data.

METHODS

          The first thing I'll run through in the methods section is the four different pieces of surveying equipment used: the Topcon HiperSR GPS unit, the Topcon Total Station, the Topcon Tesla unit, and the prism pole. I will also discuss how my partner and I utilized each piece of equipment.

The Topcon HiperSR

          The Topcon HiperSR unit works in conjunction with the Topcon Tesla unit to measure and record elevation data. both pieces of equipment connect to each other via a mifi unit which allows them to communicate. The HiperSR unit is mounted on top of a tripod of known height so that the unit can accurately record elevation data, and the Tesla unit is mounted on the side of the tripod so that the surveyor can record data points at the touch of a button. The way this unit works is that it is physically moved around by the surveyor to each point he/she wants recorded. The unit is then leveled using a bubble level built in to the tripod to make sure that the Topcon HiperSR unit is directly above the desired point. Once the tripod is made level the surveyor elects for the unit to record a point using the Topcon Tesla interface. A Topcon HiperSR unit attached to a tripod is pictured in figure two below.

Figure 2: shows a Topcon HiperSR unit attached to the top of a tripod. The Topcon Tesla recording unit is also located in the middle of the tripod. It should be noted that it is through the HiperSR unit (top of tripod) that the data points are measured and it is through the Tesla unit (middle of tripod) that the data points are recorded.

          In order to begin recording data points with the HiperSR and Tesla units my partner and I first had to create a new job (geog336_toposurvey_group3). The unit then asks for a coordinate system to project the data in. My partner decided to project using the UTM 15 North projection. We then created a point feature to use for when we actually start recording data points. After setting up our job, projection, and feature class it was simply a matter of setting up the tripod and recording the points using the Tesla interface. My partner and I set our point collection interval at five points. This meant that for every data point we collected the HiperSR unit took five points and averaged them for increased accuracy. My partner and I were supposed to take a total of 100 points to effectively cover the entirety of the AOI, but due to rain we were only able to collect 90 points. This did not greatly effect the integrity of our data, however, because we still were able to collect data points throughout the entire campus mall.

The Topcon Total Station

          Like the Topcon HiperSR the Topcon Total Station worked in conjunction with the Tesla unit to measure and record elevation data. The Total Station and Tesla unit also connected via mifi in order to communicate with each other as well. The difference between the HiperSR and the Total Station is that the Total Station is not physically moved to each data point. Instead a piece of surveying equipment called a prism pole is moved to the desired collection point and a laser is shot from the Total Station to the prism pole and back to the Total Station to measure elevation data. The first thing that must be done before collecting elevation data with the total station is that it must be properly set up. Like the HiperSR the Total Station sits on top of a tripod, but the set up procedure is much more difficult. First an occupied point (OCC) must be flagged so that the total station can be placed directly over it. Second, the tripod must be placed over the OCC and the Total Station must be placed on top of the tripod. Both the tripod and Total Station have many leveling knobs that must be tweaked until they are both perfectly level and over the OCC. A laser plummet is used to make sure that the Total Station is directly over the OCC. Thirdly, two back sight points must be taken to zero out the Total Station GPS unit for true north. This is done by clicking on the back sight icon in the Total Station interface, entering in pertinent information such as prism rod height (2 meters), and physically taking the back sight points. Both the OCC and two back sight points were taken using the HiperSR GPS unit. It is important to set the height at two meters for the prism rod or every measurement taken by the Total Station will be skewed by the difference inputted for rod height. Once the Total Station has been zeroed out for north the Magnet program located on the Tesla interface can be utilized to collect elevation data. A full list of set up instructions can be viewed here in Appendix A. Below in figure three a tripod complete with total station and prism rod is pictured.

Figure 3: shows a total station mounted on top of a tripod and facing a prism rod. To take an elevation point with a total station it must be directly facing the prism rod. When the point is taken a laser is shot from the total station to the prism rod which then reflects the laser back to the Total station which records the elevation at which the laser shot back at.

              Before my partner and I began collecting points with the Total Station we initiated the setup procedure described above including the collection of the OCC and two back sight points. My partner and I then split the surveying job into two tasks with one person manning the Total Station and the other manning the prism rod. The person manning the Total Station used the Tesla unit and the Magnet program to record data points measured by the Topcon Total Station and prism rod. The person manning the prism rod physically moved the prism rod around the campus mall in order to collect elevation data around the entirety of it. For this topographic survey my partner and I were not required to take 100 data points; instead, we were simply tasked with taking a representative example of the campus mall's elevation. This ended up being 45 data points.

Transferring the Data

          Once the campus mall elevation data was measured and recorded by both the Topcon HiperSR and the Topcon Total Station, My partner and I had to upload the data as text files. A tutorial for how to do this was provided by the University of Wisconsin Eau Claire's geospatial facilitator Martin Goettl. In a nut shell, I used the exchange function to transfer the job I created for both the HiperSR and Total Station topographic surveys into text files. The two text files created can be viewed in figure four below.

Figure 4: shows the two text files for the HiperSR and Total Station elevation data. This data is organized into longitude (easting), latitude (northing), and height (elevation).

After I transferred the data into text files I uploaded it into ArcMap as x, y, and z data. The x-data corresponded to the longitude (easting) data, the y-data corresponded to the latitude (northing) data, and the z-data corresponded to the height (elevation) data. To import the x, y, and z-data I simply clicked on the add data and add XY data tabs located under the ArcMap file tab. Once the x, y, and z-data was uploaded I could create elevation maps.

DISCUSSION

           The final elevation maps were made up of the x, y, and z-data, a topographic base map, and a continuous raster surface created using the natural neighbors interpolation method. In figures five and six below elevation maps of the Topcon HiperSR and Topcon Total Station data can be viewed respectively.

Figure 5: shows an elevation map of UW-Eau Claire's campus mall. This map was created using the data collected with the Topcon HiperSR GPS unit.

Figure 6: shows an elevation map of UW-Eau Claire's campus mall. This map was created using the data collected with the Topcon Total Station GPS unit.

          Looking at the two maps in figures five and six above it should be noticed that one of these maps turned out much better than the other. The map in figure five showing the HiperSR elevation data is much more accurate and comprehensive than the map in figure six which shows the data collected with the Topcon Total Station. The map in figure five shows a good representative example of elevation data throughout the campus mall, the points are nicely spaced out, and none of the data points appear out of place. The map in figure six however is a different story. The survey does not showcase a good representative example of elevation data throughout the campus mall, the data points are clumped and unevenly spread out, and some points even appear inside buildings. the data discrepancy in figure six could have come from a number of different reasons with human error being at the top. My partner and I may have set up the two back sights incorrectly and it's entirely possible that the skewing of the data was caused by improperly setting up the Total Station. As stated above it is extremely difficult to set up the Total Station so that is perfectly level. If my partner and I set up the Station so that it was just slightly off balance it would account for the inconsistency of our data. I also mentioned that there were many pedestrians crossing our line of sight as my partner and I were collecting data points. It's also possible that our elevation data was skewed by the interference of these pedestrians with the Total Station's laser.

CONCLUSION

          Overall this was a tough field exercise due to having to work with unfamiliar and complicated equipment. Working with the HiperSR unit in tandem with the Tesla unit was actually a fun experience because they were easy to understand and produced accurate results. Working with the Topcon Total Station was a horse of a different color. The level of effort that goes into setting up a total station is astronomically higher than a HiperSR. Even though my partner and I inputted a lot of effort into the setup, the results of the Total Station elevation data were still highly inaccurate. I stated above that it is good to have a back up system and a broad base of knowledge when it comes to using surveying equipment, but if at all possible I would opt to use the HiperSR GPS unit for any and all surveying applications.

Field Exercise 8 - TruPulse Range Finder Distance Azimuth Survey

INTRODUCTION

          For field exercise eight a partner and I were tasked with measuring and recording a distance azimuth survey. A distance azimuth survey is an older process of surveying where a reference point is used for the basis of the entire survey. Surveyors chose a reference point based on how easy it is to recognize from aerial imagery and measure a desired number of data points out from that reference point. Surveyors measure these data points by picking out objects or landmarks surrounding the reference point and measuring there distance an azimuth in relation to the reference point using a measuring tape and compass. My partner and I measured and recorded 100 data points. My partner and I did not, however, go as old school as using a tape measure and compass. Instead we used a true pulse 200 Range Finder which shoots out a laser to instantly measure both the distance an object is from the reference point and the azimuth of the object. The reason why my partner were instructed to utilize this method of surveying versus something more complex and high tech is that sometimes things may go wrong out in the field and older methods that use fewer technologies may be necessary to get the job done.

Study Area

          My partner and I chose to conduct our survey in a grassy field just West of the UW-Eau Claire McIntyre Library. This area had a good central location in which to place the reference point as well as many surrounding landmarks/objects with which we could measure and record as data points. The image in figure one below shows the location on which we conducted our distance azimuth survey.



Figure 1: shows the lower UW-Eau Claire campus. Inside the red box is the field in which my partner and I conducted our distance azimuth survey.



METHODOLOGY

 

          To get started my partner and I set up the TruPulse Range Finder on a tripod so that it was unable to move its position from start to finish. Then, using a downloaded phone app we took the coordinates of our reference point (middle of the TruPulse Range Finder tripod). collecting the reference points coordinates is not necessary if it's easily identifiable from aerial imagery. We then divided the surveying into two different jobs. Person number one was tasked with actually measuring the data points with the TruPulse. To use the TruPulse Range Finder all a surveyor has to do is turn it on (make sure it has enough battery), toggle between its different functions (two of them are distance in meters and azimuth in degrees), and press a button to shoot the laser at the object of interest. Below in figure two is an image of a TruPulse 200 Range Finder mounted on a tripod.

Figure 2: shows a TruPulse 200 Range Finder mounted on a tripod.

Person number two was tasked with recording the data in a notebook. Person number recorded the distance the data point was away from the reference point in meters, the azimuth the data point was in relation to the reference point in degrees, and what type of object the data point was. Many of the data points were trees but some others included light poles, cars, rocks, and benches. It was important that we recorded data point type because later on when the data points are overlaid onto aerial imagery they will be compared with actual features, and labeling them by type will allow us to know which point is supposed to match up with certain features. After this data was measured and recorded my partner and I inputted it into an excel spread sheet which can be viewed in table one below.

Table 1: shows the distance azimuth data as an excel spread sheet. The object ID, Distance, Azimuth, Type, Latitude, and Longitude of each data point is given.

The data is now ready to be imported into ArcMap. This is done by creating a geodatabase, right clicking it, and importing the data as a table (single). This process can be viewed in figure three below.

Figure 3: shows the pathway to importing the excel file into a geodatabase table.

Once the table is in the geodatabase the Bearing Distance To Line command is used. This process can be viewed in figure four below.

Figure 4: shows how to navigate to the Bearing Distance To Line tool - Data Management tools > Features > Bearing Distance To Line.

Once the Bearing Distance To Line tool has been run an image like the one in figure five below will pop up.

Figure 5: shows the distance and bearing image. The reference point appears at the center of all the lines which are shooting out to the 100 data points collected for the exercise.

After the Bearing Distance To Line tool is used the Feature Vertices to Points tool needs to be utilized in order to add points onto the ends of the lines. Figure six: below shows the pathway to the Feature Vertices to Points tool.

Figure 6: shows the pathway to the Feature Vertices to Points tool - Data Management tools > Features > Feature Vertices to Points. 

After the Feature Vertices to Points tool is used the final step is to lay down a base map so that some imagery can be viewed. This is an important step because the imagery will show how accurate the surveying data was. Figure seven below shows my partner and mine's data compared to actual imagery.

Figure 7: shows the distance azimuth survey map along with aerial imagery. Each red line leaves the reference point according to it's azimuth and each line ends at a teal point according to it's distance.

DISCUSSION

          Figure seven above shows that the data collected by my partner and I was not completely accurate. Three points appear in the building to the northeast of the reference point, and six points appear in the building to the east of the reference point. There are two different theories I have hypothesized that could explain this error the first of which is a bad reference point. My partner and I chose to put our reference point in the middle of the field so that we could have 360 degrees with which to measure data points. In hind sight we should have picked the corner of a building so that we could pin point exactly where our reference point was by looking at aerial imagery. The other theory is that knocking over the tripod halfway through our data collection screwed things up. The wind was gusting up to twenty miles per hour on the day we conducted our survey and it knocked over the tripod at one point. My partner and I had difficulty finding the exact same spot we had set up the tripod so it may have been a few inches off.
          Something I should mention when talking about conducting a survey is magnetic declination which is the angle between magnetic north and true north. Basically the direction a compass points to is magnetic north and the direction along the earth's surface towards the geographic North Pole is true north. The difference between the two is magnetic declination and in Eau Claire's case it is 1.36 degrees west. This means that every azimuth measured needs 1.36 degrees subtracted from it to be accurate. Magnetic Declination is an important concept to understand because it can cause a survey to be inaccurate if it is not accounted for. For my surveys purposes correcting for magnetic declination was not imperative, but if it was a survey being conducted for a high end firm I would have to account for this error.
          Although my partner and I used a relatively new piece of technology (TruPulse 200 Range Finder) to measure both the distance and azimuth of the data points in relation to the reference point, the method is an old one and has been replaced with newer methods such as dynamic surveys, controlled networks surveys, and trilateration surveys. As stated above, there are times when an older method must be fallen back on because of technology failure or budget constraints. Having a backup method that is quick and cost effective is a great plan B.

CONCLUSION

          Being aware of the different types of errors that can occur was the most important part of this field exercise. There was nothing My partner and I could have done about the wind blowing our tripod over, but we definitely should have had the foresight to pick a better reference point. At the very least we were able to overcome the magnetic declination difference between magnetic north and true north. This exercise marked the first time that groups conducted their surveys without collusion with other groups or the instructor. For me it was a defining moment in my geospatial technologies world.

Field Exercise 7 - ArcPad Data Collection Part 2

INTRODUCTION

          In the previous blogpost (Field Exercise 6 - ArcPad Data Collection Part 1) I explained how to transfer a geodatabase from a desktop platform onto a portable GPS device. Unlike the previous exercise, where each group created their own specific geodatabase to be deployed, every group in this exercise will use an identical master geodatabase agreed upon by the class. In the previous blogpost I also explained how to collect and record climate data for the purpose of creating a microclimate map of our area of interest (AOI). In this field exercise seven groups of two will be measuring and recording climate within their individual AOI or zone. This climate data will then be stitched together to create one giant microclimate map which will encompass the entirety of The University of Wisconsin's Eau Claire campus. Finally seven different maps will be constructed to show off the individual climate data fields including wind speed, dew point, surface temperature, temperature at two meters, wind chill, wind direction, and humidity.

STUDY AREA

          The study area or area of interest for this field exercise is the entirety of UW-Eau Claire's campus as well as seven zones within the campus. The campus has been broken up into seven different zones so that each group of two can focus their measuring and recording efforts on a designated zone. In my partners and my case we were tasked with collecting forty climate points within zone seven. Below in figure one the seven different zones of the UW-Eau Claire campus can be viewed.

Figure 1: shows the seven different zones that the UW-Eau Claire campus was broken down into. The highlighted zone on the right hand side of the map (zone 7) was the zone my partner and I were tasked with measuring and recording climate data.

           Even though seven different groups are recording climate data in seven separate zones on seven different GPS units, this data will eventually be combined so that one comprehensive climate map can be created for the UW-Eau Claire campus. Breaking the campus down into individual zones and designating one zone to each group was a smart move because more data points could be measured and recorded within each zone; Otherwise, each group would have to cover too much ground and fewer data points would be recorded. This method of data collection also emphasizes collaboration between the individual groups. Only after communicating with each other and putting forth a group effort can the data recorded within each individual zone be added to the comprehensive campus climate map.

METHODS 

          The first task to be performed for this exercise was deploying the uniform geodatabase agreed upon by the class onto a portable GPS device. Again the device used was the Trimble Juno 3 handheld GPS unit and I explained the deployment process in the previous blogpost. The next step was measuring the 40 different microclimate points within our designated zone. Each microclimate point had to include the fields agreed upon for the master geodatabase which were as follows: wind speed, dew point, surface temperature, temperature at two meters, wind chill, wind direction, and humidity. These  seven different climate fields were measured using the Kestrel 3000 weather meter and recorded using the handheld Juno GPS unit. Figure two below shows the dispersal of the points my partner and I recorded within zone seven.

Figure 2: shows zone seven and the forty microclimate points. It can be seen that not all of the recorded points fall completely within the outlined area. The dispersal pattern of the points in general follows the walk ways of the UW-Eau Claire campus, however their are two distinctive points which appear on the roof of the building in the bottom of zone seven. 

          After my partner and I collected our forty points we had to transfer the recorded data from the Juno GPS unit into ArcMap. This process is also explained in the previous blogpost. Once our data was transferred my partner and I had to collaborate with our peers and create the comprehensive UW-Eau Claire campus microclimate map. In figure three below a comprehensive map of the UW-Eau Claire campus showing all the data points from the seven groups can be viewed. In table 1 below an attribute table of the merged data with the microclimate fields can be viewed.

Figure 3: shows the seven zones of the UW-Eau Claire campus as well as all of the data points recorded within. Each Individual group had to collaborate with each other in order to create this one comprehensive map.

Table 1: shows a snapshot of the data point merger of the seven individual groups. Points 142 - 169 are shown with their corresponding microclimate field attributes. From left to right the columns in the attribute data show wind speed, dew point, surface temperature, temperature at two meters, wind chill, wind direction, and humidity

          Now that all of the data points along with their corresponding microclimate attributes have been merged into one comprehensive map, the construction of seven different microclimate maps can take place. The seven subsequent maps were created using ArcMap, designed using Adobe Illustrator, and include a wind speed, dew point, surface temperature, temperature at two meters, wind chill, wind direction, and humidity map (figures 4, 5, 6, 7, 8, 9, 10 respectively).



Figure 4: shows a map of the wind speed on UW-Eau Claire's campus. I have used both a point feature class to show wind speed at the recorded data points and a continuous surface feature to show an interpolated average wind speed in between the recorded points. I also used the red boxes to delineate the seven zones. I used the Kriging method of interpolation to create this continuous surface.

Figure 5: shows a dew point map measured in Fahrenheit of the UW-Eau Claire campus. I have used a continuous surface feature to show the interpolated average dew point in between the recorded points. I also used the red boxes to delineate the seven zones. I used the Kriging method of interpolation to create the continuous surface.

Figure 6: shows a map of the surface temperature on UW-Eau Claire's campus. I have used both a point feature class to show the surface temperature at the recorded data points and a continuous surface feature to show an interpolated average surface temperature in between the recorded points. I used the Kriging method of interpolation to create this continuous surface.

Figure 7: shows a map of the surface temperature at two meters on UW-Eau Claire's campus. I have used both a point feature class to show the temperature at the recorded data points and a continuous surface feature to show an interpolated average temperature in between the recorded points. I used the Kriging method of interpolation to create this continuous surface.

Figure 8: shows a wind chill map measured in Fahrenheit of the UW-Eau Claire campus. I have used a continuous surface feature to show the interpolated average wind chill in between the recorded points. I used the Kriging method of interpolation to create this continuous surface.

Figure 9: shows a map of both wind speed and direction on UW-Eau Claire's campus. I have used both a point feature class to show wind direction in azimuth at the recorded data points and a continuous surface feature to show an interpolated average wind speed in between the recorded points. My partner and I were the only group to actually record wind direction, therefor, zone seven is the only zone shown on the map. I used the Kriging method of interpolation to create the continuous surface.

Figure 10: shows a percent humidity map of the UW-Eau Claire campus. I have used a continuous surface feature to show the interpolated average percent humidity in between the recorded points. I also added the red boxes to delineate the seven campus zones. I used the Kriging method of interpolation to create the continuous surface.



DISCUSSION

          The maps created above may look similar to one another, but there are subtle changes in each one to enhance the climate feature being displayed. Different color schemes, different symbology the addition or omission of the zone boxes, and different classification methods are but a few of the various ways in which the maps were tweaked. Creating the perfect map is always a tricky process and normally takes twice as long as I originally intended. This exercise was no exception. Finding the perfect transparency for the interpolated continuous surface was very tricky as well as simply fitting the map image into a aesthetic shape. I had a lot of difficulty cropping the first two maps until I realized that there was a ghost background keeping them from fitting onto a cropped background.
          As far as what the maps actually show regarding UW-Eau Claire's microclimate foot print, it's about as normal as it can possibly be. Two distinctive patterns that I did notice were that it is much windier on top of the hill than down in the river valley, and It is coldest right at the base of the hill where the cold air sinks and chills out. No pun intended.
          My partner and I encountered no problems with any part of our data set and I attribute some of this luck to the geodatabase domains established in the previous lab. Planning ahead of time by creating safety nets in the form of domains really helped our group once we were out measuring and recording microclimate data in the field.
          As discussed above, every individual group was held accountable for measuring climate data in their campus zone and merging it into the master geodatabase. Every group but one did not record the wind direction, ergo the wind direction map shows only zone seven. There was also a group that didn't measure the temperature at two meters. Although these oversights effected the group as a whole, they did not ruin the master data set.

CONCLUSION

          Overall this field exercise allowed me to go back over the process of transferring data to and from a handheld portable GPS unit, which was important because it can be a tricky process. This exercise also allowed me to brush up on my ArcMap and Adobe Illustrator map making skills. I spent roughly three and a half to four hours creating these microclimate maps and I could have spent double that If I really wanted to make them standout. This goes to show that aesthetics and creativity take a lot of effort and time especially with map making. After finishing this lab I feel extremely comfortable not only using a portable GPS unit but transferring data to and from it as well.