Topological Survey Methods with a Total Station

Introduction

In the previous exercise we conducted a distance azimuth exercise, which is a very useful and effective fieldwork technique, but sometimes a higher level of accuracy is necessary or elevation points need to be collected also. In this case, it would be more appropriate to use a total station. A total station is an electronic device used in modern day surveying, it contains an electronic distance meter, and if combined with a GPS unit, location, distance and elevation methods can be taken and recorded. This assignment required us to learn how to set up the station and how to use it alongside the other equipment as, we were to use the open space int he middle of campus to collect data for fifty points using the unit and a sighting pole to make our points. This data could then be uploaded on to a computer and displayed using ArcMap.

The Study Area

The area we were suing to collect our points is know as the campus mall and is about the size of a two hectare plot, the land is a mixture of green space and paving, with a small creek running through it, as a result it lies on a slight slope. Unfortunately I can not show a aerial image of the site, as the last images were taken prior to the area being exposed the way it is today. We were to only study in one hectare plot within this area.

Methods

First of all we started in class by learning to set up the station and the associated tripod. This involved making sure it was set to a height that would be comfortable for our group members to have to be looking through constantly. We then had to attach the unit to the the tripod using the safety screw, and ensure the knobs were pointing away from us to make sure we were going to be bale to take measurements. We had to then look at the spirit level built within the unit, to make sure that the legs of the tripod were all at an equal height, and adjust them accordingly. Then we had t make sure that the unit was level, this was done by turning 3 separate dials on the corners of the unit, with the dial facing towards you, until the display bubble was withing the display circle. An example of a total station unit is shown in figure 1 below.

Figure 1: A total station unit like the one we used during our fieldwork to gather data on point'd distances and elevation. 

When we were out in the field gathering our data these same processes outlined above were carried out, and is shown in figure 2. We had to use the same azimuth instrument as in the previous exercise to calculate the one hectare plot we would be working in. Then then we had to ensure the Bluetooth was active on the unit in order to sync with the GPS unit to gather the location of points and their associated data. Then the GPS unit, was switched on, the Bluetooth option turned on and we made sure it was synced with the total station. Then on the GPS unit, a new project for our group was created and we selected the appropriate co-ordinate system was selected, we choose NAD 1983 UTM Zone 15N, for the state of Wisconsin. Then we had to enter the height of the sighting pole (in our case 2 meters), the  occupied point which could be read off the display on the total station screen, and the back sight point which we had to collect. This was done by one member of the group selecting and marking with a coloured flag a point and standing there with the total station. Another member of the group then looked through the lens of the total station and lined up the  target on the lens with the center of the upper circle of the sighting pole. Example of sighting poles for use with a total station are shown below in figure 3. The reading of this distance was shown on the station's screen and was entered in to the GPS data.

Figure 2: An image of the total station and tripod put together and being used to find the sighting pole where the photo is taken from.

Figure 3: Examples of sighting poles used in the collection of data with a total station, you can see the black lever which can be sued to adjust the height of the pole, and the central circle on the panel which is used to line up with the station's lens. 

This point is sort of a back up point if you were to have to move your unit. So, the actuall collection of points was done in rather the same matter. Except that now with the GPS linked with the station the measurements would go straight o to the GPS unit. So one member of the group moved around trying to capture the whole scope of the topography of the area as the other lined the station up and waited for the total station to register and transfer the measurements to the GPS units. No flags needed to be placed at these points as we would not need to return to them. For our group we tried to cover the areas in front of and either side of the unit, and go down a bit further in to the creek bank. 

Once we had the desired number of points we were ready to deconstruct our equipment and transfer our data on to the computer. This involved connecting the GPS device to the computer through the use of a GPS cable. The data then appeared as an x,y table on the computer so we had to make sure we added a z field for elevation and the table was imported in to Arc Map and a base ma could be added to give the points some relation. The points could also be taken to create a 3D surface using whichever interpolation technique worked best. 

Discussion

The assignment took a lot of set up and figuring out what to so at the beginning, and we ad run out of time during class to go through every group and show them what to do, so it was quite confusing. The first time we attempted to do it, there were very rainy conditions and the equipment ended up becoming too wet and so we had to abandon our fieldwork. So this could be seen as one disadvantage over the more traditional method which would have still worked during the rain as long as visibility was not impaired. 

When we did mange to complete our fieldwork we had some trouble with the Bluetooth on the total station working as some how it had a code programmed in to it which was not necessary, so we had to seek some assistance with figuring that out and why it wouldn't connect. There were also some points where the GPS would loose connection and quit out of the point recording, but after a while and keeping the GPS as close as possible, this stopped. This would have been easier if we had three people as we were meant to to have one person working the total station, one with the sighting pole and one with the GPS unit.  The person that was holding the sighting pole had to make sure they held it straight upright, so that the station could collect an accurate measurement. The day we did eventually complete our fieldwork the weather was unusually nice and there were many people in the area we were surveying, decreasing slightly the areas we were able to take measurements from. 

In figures 4 and 5 below, we can see to IDW interpolation 3D models that were created from points gathered during the fieldwork, we can see how they contain similarities and differences to each other. It is difficult to explain without having previously been able to show you an image of the study are, but both capture the small creek that was talked about. This is located to the East of the area, my group seemed to capture that valley side to the South, wheres as the other group captured more of the full extent of the creek;s course. Overall the other groups data seems to be more continuous, whereas ours seems slightly edgier, this may be due to the fact that we had so many people in the area that we could not follow a strict sampling method, and perhaps covered some areas better than others. Both capture the general trend of going down in relief as you move further North, with the total station being situated on the area of slightly higher relief. 

Figure 4: An Inverse Distance Weighted (IDW) Interpolation model of the area my group surveyed. 

Figure 5: An Inverse Distance Weighted (IDW) Interpolation model of another groups data that they collected in the same study area.

Conclusions

Using a total station can collect a wider range of data but takes a lot of set up and good weather conditions. Once you have all the elements set up and the equipment set up, you can gather the points fairly efficiently. But it does rely on the sighting pole being straight and balanced at every point so that all the measurements are comparable to each other.  The results gathered form such a form of data collection will gather different results for different people depending on your sampling method and the conditions you are carrying out the fieldwork in. However, all results should manage to map out the general relief of an area as well as the size and fairly accurately represent the real world phenomena. 

GPS Navigation

Introduction

This exercise was very similar to the traditional navigation exercise and was at the same study area, but this time we were using the more modern navigation strategy of a GPS and completing all 15 points of the full course at the priory. It also required some more work to be done on the maps we produced for navigation to add the points and decide upon a route for our group.There was also the added bonus of the whole class being armed with paintball guns as we were all completing the course!

Methods

First of all we had to go back and edit our maps in ArcMap during class time. Now we had access to the shapefile containing the points of the course as well as the three starting points, so we had to add them and ensure they were a suitable colour to stand out against the background map. Then on this map it was important that we included the polygons for the no-shooting zones, as there was a children's centre in the vicinity and one are was also near a main road, so we did not want to be shooting our paint ball guns in those areas.

Then, as a group we examined the topography and used our knowledge of the five points we had previously found to decided upon a route that would be the easiest to navigate and the fastest to complete. This mainly ensured that if we were going down in relief we stayed down and if we were going up we stayed up, as much as we could. The points shape file's attribute table has the points numbered in the course order, so we had to change this so they were numbered in the order we would be navigating them. Also, the starting points were included int he numbering system, so we made sure they were not included in our numbering system. We also made sure that these numbers were visible so we could see them on the GPS unit screen.

We then attached the GPS unit to the computer with a USB cable, and cut ad pasted a copy of the map file in to the device's folder on the computer. We then turned the unit on and made sure that we could open our map document and that everything that was meant to be displayed was. Also, that there was not to much information on the unit and made the screen to busy so we would not be able to read the map properly. We also had to ensure that we remembered the number of our unit, so we could get the same one when we out in the field so that it had our map file on it.

Whilst out in the field each group had one person with the GPS device navigating the group, as the others were on the lookout for the markers and other groups potentially firing paint balls. The tracklog was switched on, to follow our route and log each time we we had reached a point. We then followed the course displayed , but went of course at times when we had to hide from other groups, so then had to find our way back to the route we were meant to be following.

Discussion

It was quite difficult to decide what to include on the map so as not to overwhelm the GPS unit. We did have to slightly decrease the size of the numbers marking the points,k as they were preventing us from seeing the rest of the map. When using the unit in the field, it was very sort of trial and error, we had to just walk in a direction and see if our track log was following the route or not, and the adjust accordingly until we were following the line on the screen.

There really wasn't much room for us to zoom in or out of the map as it would take a very long time to slowly load, and we were meant to be going as quickly as possible, So, we had already decided that we would print out a copy of our map anyway which came in very handy when the screen would be loading or froze. Our group also did not realise that we had to add a point to the map every time we reached a marker we assumed that it would be shown in the fact that our route had gone past/through the point.

At one point the unit quit out of the map and then took along time to open up again, so we had to seek shelter in a small valley and try and use the paper map without a compass. Then once it had opened again it had lost our tracklog, so according to what our map would show you we did not do the course.

I think that we would have been able to navigate the course a lot quicker if we were using the traditional methods as once we had a rhythm and pattern it worked efficiently. We can also see the whole map and are we need to on a paper map without having to wait to zoom in and out. But I can see how much easier it is to just carry one device, especially when you have paint guns!

Study Area

The study area, as should be apparent, is the same as was used in the previous traditional navigation exercise, except we were physically covering more of the course rather than just one section.

Conclusion

When planning an efficient route it is important to make sure you are not climbing up and down hills constantly, and you do not go back on yourself if possible. When putting a map on to a GPS device you must consider what is necessary to see, so you use as little memory space as possible. As people should do with their Sat-Navs in their cars, you should follow along with map also, so you are not led blindly astray, and you can not always rely on technology to work efficiently and properly. As for the paint balling, I don't really think it was my cup of tea!

Traditional Navigation

Introduction

This exercise was the outcome of the navigation skills and fieldwork map construction we had previously completed, and now that the weather had improved we were bale to put it all in to use. In groups of three we were to navigate a short course of five points using the maps we constructed, a compass and our pace counts we calculated. We had not previously been given the course points and so had to add them to the map in the field and calculate the bearing and distance of each point in order to get to them.

The Study Area

We were completing a course at the Priory in Eau Claire, this is shown in the aerial image in  figure 1.It is an area primarily of forest with varying reliefs with many steep declines to some small creeks. It is off the I94, and about a 15 minute drive from the UW-Eau Claire main campus.

Figure 1: Aerial Image f the priory where the navigation exercise took place. 

Methods

Before setting off on our route we used the co-ordinate grid on the map to mark on the points we needed to go to, then we used a ruler to draw line between these points. A compass was then used to calculate the bearing between points for us to follow during the course. We also used the string of the compass to measure the distance of the lines on the map and then placed that length against the map's scale to calculate the distance between the two points. Within our group we delegate one person to get the bearing on the compass from the map and ensure that we were following it, one person to go to a directed point along the bearing to see g they could see the marker, and the third person was using their pace count to see measure the distance we had traveled to give us an idea if we should be near the marker or not. Once the person looking for the marker had gone to the assigned place, the other two group members followed to then assign a further point that they could see and to check in the t we were headed on the right path. 

Once we had found our marker we then had to use the puncher attached to the marker so stamp the card we had, matching up to the marker number to prove we had found the points. There was no assigned route, but because we were finding points on a section of a course they pretty much followed an order. As there was so much forest around us we could not really use the technique of relating yourself to physical features to find where you are going, but we could use this in the one cleared are we had to go to, you can see i the North East corner of figure 1. 

Discussion

We managed to find all of our points in good time, some of them were a little closer or rather than we originally thought, due to the fact that when you are walking in dense forest you can't really walk in a straight line, moving us in and off course constantly. I think it is worth noting that when we were first getting our bearings they seemed slightly off, but then we realised that it was due to the fact we had been leaning against the bonnet of a car and so the metal was interfering with the magnet of the compass, this also lead to the person using the compass taking off their jewelry so as not to inter fear with it also. 

One of our point we thought was meant to be right in the middle of the clearing and we couldn't see it and we figured that it should be fairly obvious i such an pen are, so we double checked the co-ordinates with where we had placed it on the map and then realised that one of the co-ordinates had been read wrong, so we changed the point on the map and then took bearings from where we knew we were, as we were right on the edge of the forest and could see the road which made it much easier. 

Conclusion

If you have several people working as part of a team you can navigate your way through an area fairly easily, as long as you are all constantly paying attention and ensuring you are sticking to the right path you set. Double checking that points have been plotted correctly before setting off reduces the likelihood of being off course and making sure that you have reduced the compass's exposure to metal is important. Your pace count can vary depending on the type of terrain you are walking on. Being able to see surrounding physical features can help you figure out your position withing an area and on a map. 

The UW-Eau Claire Campus Microclimate

Introduction

This exercise was the second half of the microclimate geodatabase creation for deployment to arc pad exercise. The goals were to go out in to the field and collect micro climate data using a Kestral unit, a compass and a GPS unit, with the hope of creating micro climate maps in ArcMap. From our own groups data as well as the datum collected by the other groups in the class we would be able to get an overall impression of the climatic patterns across our campus.

Study Area

The whole study area was as the title stated the University of Wisconsin- Eau Claire Campus, as shown in figure 1 below. Which comprises of an upper an d lower campus separated by a hill and lies along the Chippewa river. But, the data that my group collected specified in the area just before the hill behind a residence hall and along the river, as can be sen in figure 2.

Figure 1: Aerial Image of the University of Wisconsin-Eau Claire campus, used for a micro climate study. 

Figure 2: The area of the University of Wisconsin- Eau Claire's campus that my group surveyed to collect micro climate data. 

Methods

Our first task was to move the database we had created in the previous exercise to the GPS unit we would be using outside, so that the data points we collected would be recorded correctly and transferred back to the computer easily. In ArcMap we had to make sure that the feature points we collected collected could be seen easily, so we chose a bright pink hue, in order to contrast with the aerial imagery base map we then added to the document. We also had to put the feature classes we previously created in to the map document.

The ArcPad toolbar was found, by selecting the get data button we were walked through the process of deploying our information on t the GPS unit. Once ensuring that our folder was added and the GPS unit was connected to the computer and then our folder was copied and pasted on to the SD card of the unit.

The different climatic factors we were collecting were; temperature, dew point, wind speed, wind direction, relative humidity, the height of the snow and of course the unit was recording our location. The Kestral unit (figure 3) was used for the temperature, dew point, wind speed and relative humidity. A basic field compass was used for the wind direction data collection. A meter stick was also used to record the snow height. The aim was to collect 50 points in our area of campus.

Figure 3: Image of a Kestrel Weather unit, used to take and read measurements of climatic conditions to do with temperature, winds, pressure etc. 

Once we had as many points as the time limit of our class would allow, the data then had to be moved from the GPS unit back in to ArcMap. This was done the same way as the folder was moved on to the unit in the first place, by copying and pasting. All of the groups data then had to be combined in one feature class to examine the whole of campus.

We then had to individually create a series of maps, that would portray different aspects of climate. This was done using ArcMap and techniques used in previous exercises to create maps, and had to be presented including the basic elements of map design. However, we were to put all of the different groups' study areas together so we could have a map for the whole of campus. This involved using the merge tool in ArcMap to put all the feature classes together in one geodatabase, within this coma every groups data was standardised under the parameter's of what the first group used. Some groups were missing descriptions and times in their data, so their part of the columns were left blank but the main data for temperature, wind speed etc, were all filled in.

Discussion

Below in figure 4 you can see all the data points that were collected when you put each group's fieldwork together, it covers on top of and below the hill as well as on and across the footbridge that lies over the Chippewa river.

Figure 4: A map of the points where microclimate data was collected. 

In figure 5 below we can see a map that I created of the wind speed data that was collected. It can be seen that on the day that the fieldwork was carried out wind speeds were fairly calm at round about 3-5mph on average. However there are three noticeable points in the centre of campus that are 9-11mph. This could be due to the fact that these points are between buildings and so the wind would be channeling and concentrated through the space. However the points around it are lower, which would tend to suggest that is not the case and maybe they just picked up a gust of wind in that moment in time. 

Figure 5: Map containing the wind speed in areas of the university campus. 

Some of the measurements may not be as accurate as possible as the readings on the Kestrel were fluctuating so much that we would not have been able to collect all our points if we had waited to get a definitive answer, or it may have not settled on a figure at all. As it was a very cold day, and we perhaps were not quite as appropriately dressed as we should have been, we went inside a building for a few minutes to warm up before continuing. This meant that the sensors were put in to the warmth before going back out in to the cold again and it took some time for them to readjust.

The snow depth and wind direction measurements were perhaps quite controversial also as, the snow depth can var greatly even withing the point you are standing at so it depends very much on where you choose to place the measuring stick.  Some of these areas of snow may also have been there because they were piles of cleared snow, and so would not be accurately representing the real world snow fall measurements. The wind direction was taken from a compass and so was not showing a precise location, but more of a general, direction.

Conclusion

The collection of information of data about an areas microclimate can be fairly simple to collect once you get the use of the equipment and in to a flow. There can be more general readings for points in cases where the Kestrel unit is fluctuating greatly. Physical conditions like snowfall, may have been influenced by man and would not represent the real world phenomenon one hundred percent.

Aerial Mapping through the use of Unmanned Aerial Systems

Introduction

The methods we have been looking in to for taking air images have apart from the kite, so far been highly technological advanced, expensive and still a progressive field. There are some occasions where money will not allow, or the scope of such equipment is simply not necessary, and there for methods like the kite are more suited. So we used a helium balloon to capture images from above ground, in order to be able to mosaic them to ascertain and accurate, detailed, and well presented image of the surveyed land. For the first part we were concentrated on how the fieldwork was carried out, with the idea to spend an extended period of time looking in to and putting in to practice methods of putting together and displaying the images.

 We were also able to go out to the field for a second time with the unmanned aerial vehicle (UAV), as the first time was pretty much a test for the new machine. So now, were were able to witness the drone in it's full flight and the technology and preparation it takes to achieve data collection over a period of time, in order to collect images over a specified area.

Study Area

We used the same study area as was used in the previous exercise where we were introduced to some Unmanned aerial systems,  in Eau Claire's soccer park, because of the open green space.

Methods

The initial equipment set-up was to do with the balloon itself. A large strengthened rubber balloon (obviously significant;y larger and more durable than your every day balloon) was inflated using a helium tank. This was then tied at the bottom and attached to the same spool that we attached to the kite in a previous exercise. The balloon after inflation and before being launched is shown in figure 1.

Figure 1: The  balloon we would be using to gather aerial imagery, post-inflation and before any imaging equipment was attached. 

We then need to attach cameras to the balloon in order to take photos of the terrain. The same "harnessing" device was used as we did for the kite. This involved two digital cameras being attached to stabalisers, and then string to be attached to the cord of the spool on the balloon. Unlike the kite, this did not require a significant amount or height to the balloon first, as it was not going to be diving down to the ground as can happen with a kite. The balloon with the camera harness attached is portrayed in figure 2. 

Figure 2: The balloon in the air with the two digital cameras attached for taking images using a stabalising device. 

We then as a class walked with the balloon around or field site, taking it in turns to hold the balloon and direct, so that we covered the majority of the field site and would acquire multiple images. The balloon was then reeled in and the cameras and stabalisers attached, the SD card from the camera was then used to import the images taken on to a computer system, ready to be used for the mosaic.

The Unmanned Aerial vehicle (shown in figure 3 below) is out of the skill range of the majority of those in the class and so the flight and data collection was very much lead by the class professor, and we were observing and taking notes. We were able to see the laptop (Shown in in figure 4 below) that was used at the control section and it was explained to us how a designated checklist should be made prior to the flight so as to minimise the room for error and make sure everything is working as it should, especially when you are working with such expensive equipment.

Figure 3: The Unmanned Aerial Vehicle at it's starting (and finishing) point before taking flight over the field you can see.

Figure 4: The Laptop set up during the flight of the unmanned aerial vehicle used to observe the flight path to make sure it matches with the pre-set path. 

We learned the importance of looking in to the topography of the area whilst setting up the flight, as the vertical GIS on the device is not great, and you want to  make sure you are going to clear trees etc. On the laptop there is a survey grid so you can follow the path of the device and make sure it is going the same way as the pre-set course. The importance of having two people was emphasised and displayed, so that one person to watch the flight and keep control from the laptop and another to be watching the device int he air and ready with the remote control if necessary. 

As part of the follow up to the fieldwork the class was to look in to and play around with ways of collaborating all the images gathered, so that we could see the whole study area, which is ultimately what you are aiming to do with this sort of fieldwork. We found that Photoscan, a program used by 3D artists and graphic designers, worked well. When adding the images we had to eliminate those that were of poorer quality of were of the cameras initially reaching it's desired elevation, if you were to have taken many more photos over a much larger area then we had, the process of putting them all together could run for a very long time.  The images were then aligned, which created a point cloud, which I have previously talked about in the UAV mission planning assignment.  Building a "Mesh" of these images created a TIN, which we have created from our own data modes before. IN order form images to be georefferenced, we would have to export the TIFF in to ArcMap, then alongside the base map of the are you studied the georeference tool would be used, where you would add control points. Figure 7 below, shown the result that a class member   ( http://fieldmethodreports.blogspot.com/ ) managed to put together form our images. You can see now how we can cover a much wider are. However there are some slight distortions, particularly if we look at the outer parts where it appears more curved. 

Discussion

In figures 5 and 6 below you can see two of the images that were taken using the cameras attached to the balloon. Figure 5 in many ways can be used to compare and contrast with the image that was taken using the kite over the same area, except that this time it is not covered in snow. We ca also see how much higher up in the sky the camera was able to go. Figure 6 shows that with elevated height you can see more of a wider frame, but the slight angle of the photograph does also highlight the problem with using a more basic piece of equipment like the balloon, as the cameras may not stay as stable when attached using the harness and with the effect of the wind. 

Figure 5: The study site from above using the camera attached to the balloon.

Figure 6: The study site and surrounding area from the camera attached to the balloon. 

Figure 7: The images taken from the cameras on the Balloon, put together as a mosaic in the form of a TIFF.

Before we were even able to start the exercise I feel it is worth noting that with such big heavy equipment it required a few people to be able to get the equipment to the field site.  The SD card for one of the cameras was also left out and so once we were all in the field, someone had to go back and retrieve it before we could begin, which in the work force could cost time and money.

When the balloon and camera were being deployed, the camera attachment rope was winding and twisting around the balloon string, so the cameras were less stable, and consequently affecting the quality of those initial images. When we were walking the balloon around the site, the method was not really set before hand, and so the route did not really follow and order. Which will probably result in an unequal covering of areas. 

We were also only able to carry out the survey for about 30 minutes, due to the battery life of the cameras with the system overrides. We were covering a fairly small area, and still felt we needed a little more time t cover it efficiently, so in larger problems this could be problematic. 

The UAV had a similar flight time to the time of the balloon, for battery purposes. It flew very well and matched it's pre-set course and was surprisingly fast when it needed o be and went quite high, it also landed nicely back to where is started from. 

Conclusion

Balloons can be used to take aerial images in a field if money is a factor in a project. The equipment is more basic and easier to use, but may be tricky to transport and handle. Some images may not be very clear due to the effect of the weather on the balloon, this method can not be used in particularly windy unstable conditions. A clear path for taking the balloon over the area you are examining may be needed in order to ensure accuracy and clarity across all areas. The UAV gathers a clearer picture through the use of the stablisers on the vehicle, and can be observed and carried out from a distance and does not require you to physically follow the course yourself, unlike the balloon. But for a much higher price you do get the same amount of time to gather footage. The images you collect can be meshed together using software applications, in order to make use of all the data you created. This can then create an image platform for yuo to perform a number of tasks from. 

Aerial Imaging Equipment Introduction

Introduction

The class took the opportunity from the much improved weather conditions to go outside and test some of the ways of gathering field data we had discussed in the unmanned aerial system mission planning assignment and throughout class . It was simply to see some of the ideas put in to basic practice.

We tested 3 methods of collecting aerial data unmanned with 4 different equipment types. With no specific project set or in mind, other than to capture some images from above where we were, there were no specified attributes to be analysed.

Study Area

We needed an area, that would be fairly clear of people and buildings in order not to invade people's privacy and to have the are beneath clear of people in case the instruments should fall. We used the green area outside Eau Claire's indoor sport's centre and soccer park, as shown in figure 1. It is a flat area covered in grass, with the areas of tarmac for the car park.

Figure 1: Green space in Eau Claire's soccer park used for our aerial imaging. 

Methods

The first method we looked at was unmanned aerial vehicles, where we tested two different types of  remote control rotor copters. Each had on board cameras and GPS devices as well as the operational circuit boards. One had three large  "legs" (figure 2) and another with  smaller "legs"(figure 3). The first one was its first launch, and so when it was flown it was slightly less stable as it calibrated to where it was (figure 4).  The second had been flown many times and so was more stable and was able to get more where it was directed.

Figure 2: The first rotor copter that was used to capture aerial images in the field. 

Figure 3: The second rotor copter that was used to gather aerial images whilst in the field. 

Figure 4: The slightly less stable first rotor copter calibrating on it's first flight. 

We also tried a more basic method of a kite, we assembled the kite (figure 5) then attached the belay device and cast it until it was at about 100 feet (figure 6). A camera was then attached to a form of hamper device and attached to the kite string, and then the kite was cast higher in order for the camera to become high enough to take images. (figure7)

Figure 5: Assembling our kite before flying it to gather data from the air.

Figure 6: The camera once attached to the kite string being sent up in to the air. 

Figure 7: The kite and attached camera high up during data collection. 

The third method we tried was using a rocket with two micro cameras attached to the side. These were very small lightweight cameras as was the rocket, and so were attached to the sides of the craft with industrial tape (figure 8). The rocket was electrically powered and so had a fuse device to set it off with. (figure 9)

Figure 8: Attaching the small cameras to the sides of the rocket. 

Figure 9: The rocket we were using in the field before setting it off, the wire can be seen which lead to the control button. 

Discussion

The rotor copters were by far the most technical advanced, and as such could cover a much wider are much faster, both made use of the emergency device in which the on board G.P.S. unit will direct it back to it's starting position on the ground should control be lost, which I felt was a really good design feature. It also had a device on it that made sure the camera was always in the same steady and stable position which is useful in being able to get high quality comparable images.


If money was an issue in a project or technology, as it so often does fails, then the kite it is a good alternative method. However, it does require the right conditions to be able to fly, and it was relatively quick to set up and deploy.

The rocket launch did not work particularly well for us, and we have yet to see if the cameras were able to catch any stable images which is questionable given the speed of the device.

The results of the photos fro the kite worked well. As it was not positioned extremely high up and we did not walk around with it, only the area directly above us and a little bit around us was covered, but the quality of the picture is good. One of the best images from the days can be seen below in figure10, where the snow covered playing fields, the outbuilding and our group can be seen.

Figure 10: Aerial image taken with the sue of a kite of the area directly above the class.

Conclusion

It was really good to be able to go out in to the field and put in to practice some of the methods that we had spent to long talking about and researching and learning,a little about the technologies and the processes that go in to actually using them. It is good to have a variety of different methods to use in case one does not work, or the project does not dictate that such advanced technology is necessary.

Microclimate Geodatabase Creation for Deployment to ArcPad

Introduction

Data collection in the field should be as efficient as possible in order to make the most of time and money, and still achieve an accurate and satisfactory result. So creating a geodatabase in ArcMap with the fields you will be studying, allows you to out the information you collect straight in to an organised and workable format.

This task was preparing us for some fieldwork data collection we would be doing in order to make a micro climate map of the University of Wisconsin-Eau Claire campus. For us to collect the various datum about the climate we had to create a geodatabase in ArcMap, with feature classes withing that geodatabase that would relate to the various climatic factors we would be measuring. Appropriate domains fo each feature set needed to be stated also.

Methods

When creating a geodatabase for use in the field it is important to consider that there will more than likely be various different attributes  included in the data, each with their own characteristics and unit of measurement. So, one must set pre-defined domains to each different attribute in order to make sure that the data is recorded in a way specified by an employer or project leader and will be within a format that is applicable to that type of data and so can be related to other features.

It also means that results and datum are more easily adjusted, and can be compared with each other and trends noticed and queried whilst in the field. You want the geodatabase to be as easy to use as possible for as many different users as possible s fieldwork can be carried out in groups and data added to the same standards as each other. It allows fieldwork to be undertaken more quickly also. Other users of the ESRI products may also be able to use the data in a way they can understand and edit and add to.

For a climate map such as the one we were to be creating for this geodatabase's use, the attributes that can be recorded include; temperature, wind speed, wind direction, dew point, the relative humidity, snow depth, the time of the data collection as well as any notes on the data that are felt appropriate. Attributed can contain domains with short or whole integers, or float integers. Short and long domains are used for datum whose values contain whole numbers, and float integers are used when those values contain decimal figures.

In order to create our geodatabases  we used the ArcCatalog program, where we directed through the University server to make a folder connection to our own personal class folders. Right clicking on this folder and hovering the cursor over "New..." in the drop down menu, and then selecting "New File Geodatabase", allowed us to create a blank geodatabase.

Clicking twice on this un-named geodatabse slowly, meant we could change the name to something more appropriate e.g. Campus Microclimate. Right clicking on this newly named geodatabase and selecting "Properties..." from the bottom of the drop down menu, opened up the properties window. We then clicked on the "Domain" tab at the top. Here we could add the features we wanted to the table in the window and set the appropriate domains for each.

Clicking on an empty cell in the first column allows you to add a title for a feature, this was repeated for all the desired features. In the second column a description can be given once necessary. When a row is highlighted a second table appears below, and can be used to set the domains. The integer type can be chosen from the drop down menu in the first row, and where a range is necessary for the value this can be typed in to the cell next to the "Range" cell.

For use with the Juno the devices we will be using during our fieldwork a new feature class had to be created. This is done by going back to the "New" option this time in the named database menu and feature class clicked on. Opening the properties of this feature class enabled us to set up the fields in the table in the "Fields" tab, the field was typed in to the rows again and the domains added.

A raster hat had been previously created for the class was imported in tot the geodatabase by right clicking to get the drop down menu, hovering over 'Import...", then selecting the raster file from a folder. Both the feature class and the raster we added to a new map in ArcMap, by dragging them over from ArcCatalgoue, atnd this map was saved ready to input the data post fieldwork.

Conclusions

Creating geodatabses and map documents prior to carrying out fieldwork, can then enable data to be inputted straight to the geodatabse with the use if a handheld digital fieldwork device. Making both the data collection and analysis afterwords more efficient. Data sets can have many different features that require domains to be preset to assure accuracy.