Monday, May 12, 2014

Priory Navigation with GPS and Paintball Marker

Introduction
For this exercise, similar to the previous priory navigation, we would be in our teams and be required to reach a number of points.  This time, however, we would be required to hit all 15, not 5, and in addition to carrying a GPS unit instead of a map and compass, we were armed with paintball markers and masks.  

Methods
The GPS made navigation easier, in that instead of having to stop and take a compass reading, we could simply watch our position change on the GPS screen and see ourselves getting closer to the points, which were displayed.  On the other hand, when stopped, having a compass where you can just hold it up and get a reading in seconds is much better than having a GPS where getting to a compass requires a menu. 
The display we had on our GPS unit for this exercise.  The red border indicates the boundaries within which we maneuvered.  The red shaded areas were strict no firing zones.  The pink line traces our path.

The paintball markers made the exercise have an additional layer of tension.  Now, while we were scanning the trees for the orange and white flags, we were also keeping two eyes peeled for the movement of other classmates.  Because of this, we tended to move much slower and more cautiously than we would have if we were not in danger of being seen and fired upon.  Our team engaged in three firefights early on; for the first one, we lay in wait and ambushed an approaching team, and I got hit in the leg from a seated position.  The second engagement, I got the hit on the enemy.  For our third shootout, another of our team was hit.  When a team member was hit, his or her entire team was required to take a one minute time out.  This gave the other team time to move out of the area in search of their next point.
Professor Hupy and students prepping the paintball markers before the exercise commenced.

Each team was required to go to a certain point as their first, but after that, it was up to each team to determine their path.  Our path seemed a good one, taking up down into the ravine early on and then sticking to the edge of the map, working in a circle through the points until we doubled back towards the interior for our last four points.  As I said, our three engagements occurred in the beginning of the exercises; for the latter two hours, when we were on the east side of the course, we never saw another team. 


We had some difficulty on this exercise because of the nature of the gear we were carrying.  The masks would constantly get fogged up visors, making visibility extremely difficult.  To counter this, we had to keep pulling the masks up on our heads.  Doing so also made it easy to breathe, because inside those masks, it is hot and humid and horrible.  Also, the guns, while not heavy, were still a burden to carry around for three hours over rough terrain.   We arrived back at the parking lot at 5:30, not the first ones back and not last, but right in the middle.  Our course was good, but definitely could have been better.

Priory Navigation With Map and Compass

Introduction
For this exercise, we used the map and compass skills that we had learned previously for Assignment #5 in the field.  Thus, the study area is the same as for that entry.

Methods
We started at the parking lot.  We were given a sheet that lists fifteen separate points by the point’s lat/long and elevation.  Each group was assigned a course of five points. Our team marked our five points on the Transverse Mercator map that we had created previously and printed.  Five points does not seem like much.  We double check them.  Two of our points’ elevations do not match between what is listed on the sheet for the point and the elevation on the topo map in the point’s approximate location.  We are unable to figure out what is wrong.
The sheet listing the course points with lat/long and elevation.

The map that we had printed out for our use.

All the same, we start from a light post.  We lay out the map and place the compass on the line between our current position and Point 1.  We orient the north arrow on the compass dial to align with the north orientation on the map.  Lifting the compass off of the map and placing red in the shed, we have our direction.  We head off.  I am the one using the map and compass, while Travis and Jeremy move ahead of me.  I look for a landmark along our distance line and tell them to go to it.  When I reach them, I take another bearing, find another landmark, and send them to it again.  The majority of landmarks will be trees, hopefully distinctive enough ones that they can be pointed out in the middle of a forest.   For Point 1, we head out of the parking lot into the woods.  We walk down a short hill.  There is a nice tall tree with yellow leaves that works as a good landmark.  Just before it, we find the orange and white flag that signifies each point.  At this point and all of the others there is a puncher that is to be used to punch out a distinctive pattern of dots on a card that each team carries.  This ensures that we actually did make it to the point.

This day is, for me, a series of finding the bearing, spotting a landmark, getting to the landmark, and repeating the process.  To get to Point 2, we continue down the slope until we reach a ravine.  At the bottom, clearly visible, is the second flag.  We all head down to it and get the punch.  Up to this point, our group and another have been neck and neck, but after this point, we break up.  Looking at our map, the shortest path as the crow flies to Point 3 would involve heading straight up the other steep side of the ravine, heading across a flat area, and then down and up a second ravine.  The other group begins this path, but encounters sharp thorns.  We decide to take an alternate route.  We plot on our map a path that will lead us around the second ravine.  Walking out of this ravine on a gradual slope takes us to its edge.  From there, it should be a straight shot to the next point.
Example of one of the flags, this one in the bottom of the ravine.

It seems to be going well.  We are able to avoid the second ravine and are marching in the proper direction when we spot the distinctive orange of a flag.  At this point we make a critical mistake and abandon our path to head straight for it.  At the time, maybe we figured that our bearing was a bit off due to our sidetrack.  More likely, we saw the flag and just assumed it was ours.  We got our punch and were taking our new bearing when our Professor and his course taveling companion walked up to observe.  Our bearing pointed up a tall hill.  We had gotten nearly to the top when I heard shouting coming from the base.  We were going the wrong way, the voice shouted.  We walked back down to our Professor who told us that what we thought was Point 3 was actually Point 7, and if we had continued up that hill we would have gotten way off course.  We thanked him, and, after getting pointed in the proper direction, walked on to our next point.  This error taught us the importance of keeping track of your bearing and pace at all times, and not simply abandoning it when a possible point was in sight. 

The rest of the exercise is largely uneventful.  I regret wearing shorts and a t-shirt, as the undergrowth tore my arms and legs up pretty decently.  Ours was the first group to complete the course.  One thing that I think helped us to do this was in keeping our landmarks close.  That way, it was easy to reach them and take the next bearing; we were able to keep pretty well on the move without a lot of long pauses.

Aerial Mapping

Introduction
For this activity, we used a large inflatable balloon to do some aerial photography and also got a preview of how aerial photography can be done with UAV systems.  

Methods
For the balloon, we inflated it with helium to around five feet in diameter.  When this happened it was let out on a string and a camera was attached to it.  The string was then lot out a great deal more.  When the balloon was about 500 feet up in the air and the camera set to take pictures at a certain interval, we were ready to begin mapping.  We wanted to get a large area for this activity and the best way to do that was to just start walking with the balloon string in hand.  We walked all over the course, starting with a perimeter path and then crossing through the middle.  When we thought that we had covered the right amount of area we returned to our starting location, brought the balloon back down, and deflated it. 
The balloon being inflated.

The camera rig which will be attached with the yellow strings to the balloon string.

The balloon is airborne, with the camera rig attached.

For the UAV, there are many important details to have in mind.  The flight path of the UAV is programmed on computer with Mission Planner software. When setting up the waypoints that the craft is to follow, first create the take-off point.  Next, plot your waypoints on the map.  Finally, make sure to put a "return to home" point so that when the aircraft is done with its route it returns to the point where it took off from.  When it does land, be sure to hit the kill-switch button on the remote.  Failure to do so can be bad if you try to pick up the aircraft and it tries to return to the ground while you are holding it. 
It is important that you do not attempt to run a mission alone.  Two people can run a mission together but three are ideal: a pilot at controls, a pilot in command, and an engineer.  The pilot at controls stands by the laptop computer and monitors the status of everything.  The pilot in command holds the remote, and has manual control over the aircraft.  This task is very important and difficult.  Lastly, the engineer is on hand to fix any problems that arise with the controls or the aircraft.
We were able to see a mission get programmed with the take off point, 11 waypoints, and a return to home point, and then watch it unfold.  There was a camera mounted on the bottom of the aircraft set to take pictures at a set interval, similar to the balloon exercise.

The three-armed UAV, the remote control, and the laptop that were used.

A better view of the laptop running the Mission Planner software.

One of the shots taken by the UAV on its flight.  The resolution is excellent.

Total Station Survey

Introduction
For this exercise we would be learning how to use a TOPCON Total Station.  These are commonly seen being used by highway workers.  They are used to gather elevation data of an area from a fixed point to create a topographic map.  The total station works by sending a laser from the station out to a prism on top of a pole.  This bounces the laser back to the station, where it records the distance between the two as well as the change in elevation between them. 
The TOPCON Total Station, ready for use.

Study Area
The study area we chose is the UWEC campus mall, at the site of the original Davies Center student building.  That building was torn down in recent years and replaced with a large open green lawn crisscrossed with cement walking paths.  It is bordered on its wide sides by a brook and a series of planters in front of the library.  It is bounded on its long sides by the edge of the library and the social sciences building. 

 The main view of our study area, facing the library.
Methods
The procedure is, the total station stays put.  It has a tripod that is mounted into the ground to hold it steady.  Once this is done, the device is calibrated.  Similar to a microscope, it has a rough adjustment knob and fine adjustment knobs.  The purpose of the calibration is to get the device level with the ground.  The rough adjustment gets it roughly in place, and then there are three fine adjustment knobs, one for each leg of the tripod, that need to be dialed into place.  A bevel is above each leg and the bubble in the bevel needs to be centered.  When this is done, the device is ready to use.

There are two additional pieces of equipment that are used to do the survey: the remote, that is used to capture the data, and the pole, which has a prism mounted on top of it.  To do the survey, the pole is walked out to a point in the mappable area and held steady, level with the ground.  The pole has a bevel as well, which makes this simple.  At the same time, a person at the Total Station looks through the viewfinder window and points its crosshairs at the mirror atop the pole.  When this is positioned correctly, he indicates for the person holding the remote to capture a point.  The remote is linked to the Total Station via Bluetooth.  Capturing a point in as simple as pushing a button on the touchscreen of the remote.  After it says that the point has been captured, hyou are ready to move the pole, re-aim the total station, and capture another point. 
Using the Total Station.  Jeremy, pictured in the right, is handling the remote.  Circled in red is the member of our group holding upright the pole.

Points should be taken a reasonable distance from one another.  Obviously, the closer that they are taken, the more precise the resulting survey will be.  For our exercise we took points that were roughly five to ten feet apart.  This generated a reasonable surface for our study area.  With this data in hand, it is easy to import into Arc to generate a elevation surface model.  
The finished Total Station survey, created by group member Travis Haas.

Sunday, March 30, 2014

Microclimate Survey

Introduction
For this exercise we surveyed an area on the UWEC campus and created a map of microclimates.  First, we took the feature class that we had created previously and uploaded it to a GPS.  We took the GPS out into the field and, along with other tools, surveyed our study area.  We downloaded the data from the GPS into the geodatabase and combined our results with the results of the other teams’ surveys.  We then were able to make a map of microclimates on campus.

Study Area
Our study area was a portion of the UWEC campus.  The campus is divided between a lower and upper portion by a hill.  Upper campus is composed primarily of residence halls for students, while lower campus features predominantly academic buildings.  Groups were distributed so as to cover as much ground as possible. Our group's area was west of the Haas Fine Arts building, and consisted of a field and parking lot.
 The UWEC campus.  In the top portion of this image, separated from the rest of campus by the Chippewa River, is the Haas Fine Arts building and our study area.

Our portion of the study area.  This image is out of date; the brown areas are now paved parking lots and obviously the field is, at this time of year, covered with snow.


The field west of the Haas Fine Arts building.  This area had snow cover.

The parking lot west of the field west of the Haas Fine Arts building.  This portion of the area did not have any snow cover.

Methods
The class was divided up into two person teams.  Each team chose an area to canvas and then set about prepping for the survey.  First, the GPS needed to be loaded with the feature class.  Since both group members had previously set up their own feature class, each team decided which person’s would be used.  Once this was decided on, the GPS was hooked up to the computer through a USB cord and the feature class was uploaded using the Add to ArcPad feature in Arc. 

Then it was time to head out to the field.  Travis and I tested our GPS unit just after getting outside to make sure that we had satellites.  We were having some trouble with it, and had to go back inside twice to make sure that we had it working properly.  The last thing we wanted was to walk all the way over to our site only then to find out that we couldn’t collect anything.  Once we were assured of our GPS’s readiness, we headed to our site: across a walking bridge to the Haas Fine Arts building.  West of the building is a large open field covered with snow and further west is a parking lot.  We decided to start taking points along the building first, and then more or less take points along the outline of our area.  At each point, which we chose visually as well as by looking on the GPS unit to make sure it was a good distance from other points, we stopped and took measurements.  These measurements were entered onto the GPS with a stylus on the touch screen.  First, you tap on an icon that is a pencil and then on a purple circle.  This captures a point.  Then, a screen will come up with the feature class attributes and a blank space next to each one to record data.  At this point, the second person takes the measurements and calls them out for the GPS user to record. 
Utilizing the GPS in the field.

Utilizing the Kestrel in the field.

Using a Kestrel, we looked up the temperature, wind speed, relative humidity, and dew point.  Unfortunately, the Kestrel never seemed to settle on any reading.  For example, at any point we took, the temperature would swing anywhere between nine degrees in either direction, and was constantly going up or down.  This made it hard to know what the actual temperature was at each point.  Also, wind speed was somewhat difficult to gauge, as it was not constant; the wind was gusting, so one minute it would read 0 mph and the next minute it go up to 5 mph before coming back down.  This meant that for any reading we took, we had to basically watch the Kestrel until the reading seemed to stabilize for a few seconds and then record that.  We also measured wind direction and snow depth.  For wind direction we used a compass and handkerchief.  We held the handkerchief up in the air and let the wind push it.  We then brought the compass nearby and estimated the direction in degrees from north that the wind was blowing from.  Snow depth was measured by sticking a measuring stick straight down into the snow and reading the measurement.
Our full tool set: the handkerchief with compass, the GPS, the collapsible measuring stick and the Kestrel.

Once we had collected as many data points as we could within our time limit, we headed back and downloaded our data from the GPS.  We copied and pasted our data into the class geodatabase.  This allowed for all teams’ data to be used in one map. 

Results
The collected data can now be used to make a map.  This is done by taking all teams’ data and importing it into a single ArcMap document.  Maps can then be made which display any selected attribute. 

Discussion
Having two people teams made this go much smoother than if it had to be done as one person.  It could have been done with one person, but that would have required a lot of hand switching to handle all of the equipment, and would also have taken a lot longer to collect data.  Having one person to take the measurements and a second to record them is definitely more efficient.

The Kestrel seemed to be very inaccurate.  It is hard to be confident in the readings you have collected when it seems that you had to more or less guess on what reading was accurate.


All teams were required to make a Notes attribute for their feature class, but hardly anyone entered anything into this category, our team included.  There were several instances where data points were extreme outliers and have no notes clarifying why this could be; for instance, while the majority of temperatures recorded were around 32 degrees, one point recorded 81 degrees, but there are no notes explaining the reason for this high reading.  

Overall, the surveying was a good experience.  It was cold and windy but not unbearable.  The data we collected can be used to make several interesting maps of campus climate zones.

Friday, March 21, 2014

Aerial Photography Field Day

For this exercise, we went out into the field to test out some options for aerial photography.  It was a warm day and the sun was out.  This was an excellent change from the bitter cold of this recent winter; however, the sun reflecting off of the snow did make visibility a bit tricky for anyone not wearing sunglasses.  We saw a demonstration of two rotor-copters, a kite, and a rocket.  The first copter was Joe Hupy’s own, a three armed version equipped with a digital camera on a gyroscope and a forward facing video camera.  The video camera was linked up to a pair of wearable goggles that, when put on, allowed the wearer to see in real time what the video camera was seeing.  This was really cool.  The second copter was a six armed model that was brought along by Max, a student at UWEC who has spent a lot of time with operating copters.  His did not have camera equipment on it. 
 Joe's three armed copter, with its remote control next to it.

Max's six armed copter, with Max next to it.

It started with a calibration.  Max brought the copters, one at a time, up into the air, and manually held them steady via remote control until the onboard GPS was calibrated.  Once this was completed, which took several minutes, the copters could hover in a position without input from the remote control.  Joe’s copter was operated very carefully by Max as he was new to controlling it and also needed to be held steady to take photos.  On the other hand, when Max had his own copter up in the air, he drove it fast, whipping it through the air deftly to show what kind of maneuverability can be possible.
Max operating Joe's copter, concentrating on keeping it steady.

Max's copter, hovering just above the snow covered ground.

In addition to the two copters, we also tested out two additional methods of aerial photography collection: a kite and a rocket.  The kite was roughly human-sized.  It was raised up into the air to a certain height.  Then, a small camera was attached to the string via two cords to hold it stable.  Once these cords were clipped onto the string, the kite was let rise even higher until it was almost out of sight.  The camera was programmed to take a photo every five seconds, and was pointed towards the ground.  Once the camera had reached our desired height, our kite holder walked up the sidewalk with the kite string, so that the camera moved with him and got additional ground photos.  When this was over we reeled the kite back in.
The kite, freshly constructed.

The kite is airborne.

The camera attached to the kite string.

The last method we previewed was the use of a rocket.  The rocket was set on the launcher base by Joe and two small keychain video cameras were taped to it.  These cameras were very efficient; they lacked the features and view screen of a traditional camera, but were able to collect video just fine, we were told.  Joe launched the rocket, which didn't go quite as high as we had been thinking it might, before coming back down and thankfully landing in the snow and not on the sidewalk, where it would have been dashed to pieces.  Upon inspecting the rocket, Joe found that one of the two engines had not fired because it had been put into the rocket body backwards.  Despite this mix-up, we were able to see how a rocket could be used to collect aerial footage, so it was not a failure by any means.  We are all looking forward to seeing the footage from the rocket as well as the imagery captured by the kite and copters.
Joe attaching the keychain cameras to the rocket.  

Sunday, March 9, 2014

Assignment #6: Microclimate Geodatabase Construction

Introduction
When starting a large GIS project, it is smart to create a file geodatabase.  File geodatabases are a useful way of storing multiple files and pieces of information in one place.  They are defined by ESRI as being, “a collection of various types of GIS datasets held in a file system folder.”  They are advantageous in that they can hold a very large amount of data, from 1 to 256 TB.  File geodatabases allow you to work with very large file sizes without having to compromise on speed, a very important factor, as having large files open at once can slow a system down dramatically. 

What to consider when creating a geodatabase for deployment in the field
When setting up a geodatabase, it is important to stop and consider the purpose of the geodatabase.  Obviously, you are setting this up so that all of your information can be held and later accessed in one convenient place, but the considerations must go further than that.  You must consider the data collection component and the needs of the field agent who will be doing the collection.  There are several questions to consider. 

What types of data will be collected? Will they be points, lines, areas, or a combination? For example, if the field agent is collecting GPS coordinates of trees, he or she will be collecting point data. 

How much information will need to be entered about each piece of data? For the above example regarding trees, what does the field agent need to record about the tree? Tree type and relative size or age might be example of information he or she needs to enter in addition to simply capturing the GPS coordinates.

Next, to ensure the accuracy of the data collected in the field by the agent, domains can be set up in the geodatabase.  Domains are rules that govern the data being entered.  For example, if your field agent is collecting air temperature data at various locations, you can set a domain for the temperature field such that a temperature value cannot be recorded outside of a set range.  That way, if the agent is trying to record a temperature of 100 degrees and types 1,000 by mistake, he will get an error message and be able to enter the correct value instead.  Domains can be very valuable at preventing faulty numbers from being entered and ensuring accurate data collection. 

The number and type of feature classes to create is also an important consideration.  While a GIS user may be used to incorporating multiple feature classes into a single project, and would have no issue with simply creating a number them, the field agent collecting the data must again be remembered.  It is easy to display and edit multiple feature classes on a computer with a large screen and the pinpoint control of a mouse, but the field agent does not have this luxury.  His or her data collecting device likely has a small screen and buttons.  This makes switching feature classes a tedious endeavor, especially if it must be done on a regular basis.  To maximize the time a field agent has for collecting data it is important to keep the number of feature classes to a minimum.  This will also make the data collecting process easier on the field agent. 

How to set up a file geodatabase
To demonstrate, here is an explanation of the creation of a file geodatabase used in this class.  The geodatabase will store information collected in the field by a group of students including myself.  Our project goal is to create a microclimate map of a section of the UWEC campus.  First, we need to set up our file geodatabase for the project.  We open up Arc Catalog and pick the location where the geodatabase will be created.  This location should have enough free space as is predicted to be needed for the entire project.  In Arc Catalog, find the folder where you will be working and right-click on it.  Mouse over “New” and click on “File Geodatabase.”  Your file geodatabase is created. 

There are two steps now to get the data collection ready to go.  We need to create our feature class and we need to define our domains.  It will be easiest if we start with the domains.  We know that we want to record information on the following items: Temperature, Wind Speed, Wind Direction, Relative Humidity, Dew Point, Snow Depth, Time, Group Name, and Notes.  By setting up our domains, we can define each of these further and set the limits on their ranges.  We will be defining, for each domain, its name, description, and field type, along with the range of acceptable values.  For instance, for the Temperature domain, “Temperature” will be typed in for Name and “Air Temperature” will be typed in for the Description.  The description can be anything that helps explain the name further.  For Field Type, there are several options: Short, Long, Float, Double, Text, and Date.  The first four of these describe numeric values.  Short and Long refer to whole numbers while Float and Double refer to numbers with decimals.  Short can contain a number value from -32,768 to 32,767.  Long can contain a number value from -2,147,483,648 to 2,147,483,647.  Float can contain a number value with a decimal after it, and has a range far larger even than Long.  Double can also have a number value with a decimal, with a range way larger than Float has.  The range of Double is so large that it will probably not ever be necessary to use.  Essentially, if you are going to be entering whole numbers, you will probably use Short, unless its range is not large enough for the data you need to enter.  If you need the exactness of a decimal point, you should use Float.  If the data you are entering is not a number, but is a calendar date, such as the date that you are entering the data, choose Date as the Field Type.  If what you are recording is text, choose Text.

For example, for my domain “Temperature,” I know that the temperature variations I will be recording will be very small due to the small size of my study area, and therefore I need the precision of a decimal.  Therefore, for my Field Type, I choose “Float.”  On the other hand, for my domain “Notes,” I know that I will need to be able to enter text.  Therefore, I choose “Text” as my Field Type.  After you have chosen the field type, you can set the range of values.  For “Temperature,” I know that with it being a Wisconsin winter day that we will be doing the data collection, I may have temperatures in the negative.  Therefore, I set my minimum value to -20.  Realistically, the temperature should not exceed 50 degrees, so I can set my maximum to 50.  That’s it.  I now do this for all of my domains.  Wind Speed has a description of “Wind Speed in mph” and will be a Short field with values from 0 to 60.  Wind Direction will be a Text field, and have no set range.  Relative Humidity and Dew Point will each by Short with a range of 0 to 100.  Snow Depth, which is described as “Snow Depth in inches,” will be a Float field with range from 0 to 36.  Notes is a Text field.  Time will be a Short field, and will contain the time of day in military notation, with 0 as the minimum and 2400 as the maximum value.  Group Number will be a Short field, and at present will have no set range.  Later, when I know what my group number is, I can change the range to be that exact number; if my group number is 2, I can make the range be from 2 to 2.  When all of these domains have been entered, you can click OK to close the window.  These domains can be reopened and edited later if you need to.


Lastly, I have to create my feature class that will be loaded into the data collecting device my field agents and I will use to record our data.  The feature class does not have to contain all of the domains you created, but it certainly can.  In our case, it will.  However, if our project had been larger, and we had created more domains than we would be using for this particular data collecting excursion, we could pick which domains we would need and leave the rest alone for now.  This is part of the glory of creating domains: they are created for the geodatabase as a whole, not for the individual feature class, and can therefore be utilized in any feature class created in the geodatabase.  To create our feature class, we right-click on our geodatabase and choose “New” then “Feature Class.”  We give it a name, “Microclimate.”  Since the features we will be creating will be points on campus with our various domain-linked attributes associated with them, we choose “Point” as the type of feature.  Click Next.  Choose the coordinate system.  Click Next.  Click Next a second time.  Now we will add our fields.  This process will be much like what we did for defining our domains.  There are two fields already present; these are required for the feature class.  Below them, click in a box and enter your field’s name.  We will make our first field “Temperature.”  We made Temperature Float field, so choose Float as the type.  This allows you to select “Temperature” from the drop-down menu where you can choose the field’s domain, as Temperature was one of the domains you created that has the Float type.  Now the correct domain is linked to this attribute in the feature class.  Repeat this step until you have all of the attributes you need and the correct domains associated with each attribute.  When you are finished, click Finish and your feature class will be created.  It is now ready to be imported into your team’s GPS and used in the field.  

Tuesday, March 4, 2014

Assignment #5: Introduction to compass and map orienteering

Introduction
For this exercise, we were to prepare ourselves for an orienteering field course at the UWEC Priory that we will navigate at a later date.  For the orienteering course we will have on hand a compass and two maps of the area.  Both the compass skills and the maps were generated in this exercise.  Additionally, we learned how to use our own walking strides to measure distance, or pace.
The class was given an excellent compass and map orientation demonstration by Al Wiberg of the University of Wisconsin Eau Claire’s Environmental Action Center.  We were also taught how to calculate our pace by our instructor, Dr. Joe Hupy.  The maps were created using data provided in advance by Dr. Joe Hupy.

Methods
One skill that we will be using to navigate is pace.  To calculate our pace, we found a distance of 100 meters on campus.  Start at the beginning of the 100 meters and take normal steps towards the goal.  Every other step you count off in your head.  For instance, every time you take a step with your left foot.  Once you have reached the 100 meter mark, remember how many paces it took to get there.  Now turn and repeat the course back to where you started, again counting every other step.  When you have finished, take the average of the two numbers of steps it took you to walk the 100 meters and that average (rounded to a whole number) is your pace.  Apparently the average is between 60 and 65, with men generally taking longer strides than women.  My pace is 57.  Knowing your pace can make the orienteering easier in the field because it allows you to keep track of your distance by counting your steps. 
In addition to pace we will be using a compass.  To use a compass for navigating, first take your map and place it down on a flat surface.  Mark a starting point on the map and a point that you would like to travel to.  Place the compass on the map with the navigating arrow pointing towards the second point.  Spin the bevel on the compass up to the top of the map, where north is.  Then read how many degrees clockwise from north your direction of travel is.  This is your bearing.  Once you know your bearing you are able to hold the compass out in front of you, turn the bevel until north on the compass matches up with true north, turn your physical body around until you are facing your bearing, and then start walking in the correct direction. 
For the maps of the Priory, we were provided with several datasets that we could pick from to create our maps.  I decided to use a DEM, or digital elevation model, aerial imagery, and a five meter topographical contour map in addition to an outline of the Priory property and an outline of the orienteering course.  I created a geodatabase to store all of the data I would be using.  I then added the data to my map.  I made the aerial imagery transparent so as to show the DEM underneath.  I felt it was important to include the aerial imagery to have as a reference when out in the field.  We were also instructed to overlay two grid styles on our maps, one with UTM zones and one with WGS lat-long coordinates.  We will be using both when we are out in the field doing the orienteering exercise, and it will be interesting to see them in action. 
 My Priory map with UTM grid.

My Priory map with WGS grid.

Discussion and Results

I had a lot of difficulty getting my maps positioned properly in the layout view in Arc Map.  That was my main stumbling block.  When I finally did get that straightened out, I was able to make two maps that I believe will help me to navigate the Priory course.  In time this will be put to the test, and I'm excited to see the results.

Monday, February 24, 2014

Assignment #4: Distance Azimuth Survey


Introduction
For this exercise, we were to learn how to do surveying without a GPS.  We were to use a rangefinder to measure slope distance and azimuth and then record points to create our survey.  The Azimuth compass starts at 0 degrees as true north, and then going in a clockwise rotation, 90 degrees is found to be east, 180 degrees as south, and 270 degrees as west.  Slope Distance is more accurate than straight distance when measuring distances along the Earth’s surface as it takes into account the curvature of the Earth in its measurement.  If you know the coordinates of one starting point and are able to take several slope distance and azimuth readings of other stationary objects visible from the starting point, you can accurately map where they are.

Methods
We used a TruPulse 360 Laser Rangefinder.  This device allows you to take a reading of a stationary object and immediately get its slope distance and azimuth from the starting location.
The TruPulse 360 Laser Rangefinder

We proceeded outside to the location of our first starting point, in front of the railing in the center of the stairs in front of the Schofield Administration building.  We took twenty-five readings from this point.  To take a reading, the instrument was held up to the eye and directed at a stationary target.  The crosshairs of the instrument we held in place on the object while the button on top of the device was held down for a couple of seconds.  This captured the distance to the object and displayed it as a digital display on the viewing window of the device.  Next, by pushing a button on the side of the device (the down arrow), twice, the device was switched from taking the distance reading to taking the azimuth reading.  We did this work as a group, so we rotated between one person using the instrument and taking a measurement, another person recording the information in a notebook, and the third person helping the instrument-user keep track of the objects being recorded. 

Zach using the TruPulse at our starting location

We took twenty-five readings at the first location and then moved on.  Owing to the thick layer of snow on the ground, we were forced to take readings of items with enough height to be visible.  The majority of the readings we took were off of trees.  We were able to capture readings from park benches, heating vents, road signs, and light poles as well.  We walked across the way and stood at our second point, at the edge of a railing near the UWEC campus footbridge.  From this position, we took an additional twenty-five readings.  When this was done with, we moved along a path in front of the walking bridge and took our remaining twenty five readings. 
The view from our third location

Once these were collected we returned and copied the readings from our notebook into Excel.  If we had used a laptop or tablet device in the field to record our readings and had been able to directly record them into Excel we could have been able to skip this step.  Anyway, we got our Excel spreadsheet set up.  The next step was to import the Excel spreadsheet into Arc Map.  First we set up a geodatabase.  This was done by going into Arc Map, opening up the Catalog tab (typically found along the right side of the interface) and navigating to the folder where we want to save our work.  Then, by right-clicking on the folder, we choose “Create new file geodatabase.”  This opens the Table to Table dialog box (figure).  For Input Rows, use the folder to find the spreadsheet and select the sheet where the data is kept.  Output Location is already filled in, and the only other thing to do is to provide a name for the imported table in the Output Table box.  Click OK and the table is imported.

Next we need to create a feature to display the numbers visually in Arc Map.  We will use two Tools from the Arc Toolbox: Bearing Distance To Line and Feature Vertices To Points.  Bearing Distance To Line is found in Arc Toolbox under Data Management Tools, Features, Bearing Distance To Line. 

The Bearing Distance To Line Tool and its location in the Arc Toolbox

To use this tool, specify the imported spreadsheet for Input Table by using the dropdown arrow and matching the fields up from the spreadsheet for each of the four boxes likewise.  The Azimuth column goes in the Bearing Field box.  Click OK and the feature is created.

The created feature after running the Bearing Distance To Line Tool

Since what we want to show are the ends of these lines on the map, as they are the objects that we took our readings off of in the field, we need to use the Feature Vertices To Points Tool.  This Tool is found in the same folder in Arc Toolbox as Bearing Distance To Line. 

The Feature Vertices To Points Tool and its location in Arc Toolbox

For Feature Vertices To Points, simply choose the feature created in the previous step for the Input Features box with the dropdown arrow and click OK.  Points are now created at the ends of all the lines.

The Point features created after running the Tool

Finally, our basemap of satellite imagery is added to Arc Map.  The colors of the lines and points can now be changed to stand out better against the basemap.

The finished survey


Discussion and Results

The survey turned out all right, although there were a few problems with it.  First of all, there are some points that are way off, appearing to be in the center of buildings or in the water.  These points could have resulted from not having the rangefinder totally steady when taking measurments.  If we had used a tripod to steady the rangefinder we could have greatly improved the accuracy.  Second, the starting locations on our map appear just slightly off from where they should be, by a matter of a couple of feet.  This is not horrible, but could also have been more accurate.  All in all, this was a good exercise.  We learned how to create a survey of an area without the use of GPS.  If GPS is not available, this method would be very valuable.

Sunday, February 16, 2014

Assignment #3: Unmanned Aerial System Mission Planning

Introduction



Unmanned Aerial Systems are used in a variety of scenarios.  In this lab, we have been given five real life scenarios that unmanned aerial systems could be used in.  We are to look at these scenarios and critically think how we would plan our attack by using an unmanned aerial system.  Since these are vague scenarios there are some questions that arise as we are mission planning.  This lab is designed to help familiarize us with one of the most up and coming job markets in technology and to gain knowledge of what kinds of unmanned aerial systems are on the market.

Types of Unmanned Aerial Systems



Multicopters- Multicopter Unmanned Aerial Systems are perfect for tight fit areas like power lines or for a quiet approach.  Multicopters can have two or more wings.  Multicopters are used to fly short times from 10 to 30 minutes in length.  These multicopters can be landed or can take off in a relatively small area.  These are best used in tight spaces, for they can hover, go faster or slower.  Here is an example of a flight being performed by a multicopter: DIY IRIS


Fixed wing- Fixed wing craft are perfect for mapping large areas. They can reach a higher altitude and stay in the air for a longer period of time compared to multicopters. This makes them perfect for terrain modelling or aerial mapping. A downside is that the do require some space for takeoff and landing, whereas multicopters do not.

Lighter than air- Lighter than air craft are similar to balloons and blimps. The main area is a section filled with a gas that is lighter than the surrounding air (like helium). Like multicopters, these are capable of taking off and landing vertically, making them very versatile. They are also usually cheaper than the other two. The biggest problem is the lack of control. Any wind would throw a balloon or blimp type craft off course, limiting the situations they could be used it.
Scenarios



Scenario 1
A military testing range is having problems engaging in conducting its training exercises due to the presence of desert tortoises. They currently spend millions of dollars doing ground based surveys to find their burrows. They want to know if you, as the geographer can find a better solution with UAS.


Questions before Starting:
  • How big is the survey area?
  • What time of year will the survey be done?
  • Where do desert tortoises burrow?
  • When are desert tortoises most active?
 
For example, desert tortoises are most active during the morning and evening hours of the spring, when the desert air is coolest (they hibernate during the winter). Locating tortoises on the military testing range would be easiest during these times, as they would be out of their burrows looking for food.


One way of locating the creatures would be to use a gas-powered, fixed wing UAV equipped with a thermal imaging sensor and a video camera. A fixed wing craft would be able to cover more area faster than most rotary craft, and using a gas engine as opposed to an electric would enable the craft to stay in the air longer. Thermal sensors would pick up heat given off by the tortoise while it is outside of its burrow.


One problem that might arise is if the tortoise shell warms from the heat of the desert sun, therefore blending in with the surrounding rocks on a thermal imaging sensor. This is why the time of day would be very important, and the thermal camera would be supplemented with a normal video camera.


The survey area could be cut down by focusing on areas near some kind of vegetation. The animals burrows would have to be somewhat near an area where they could get food, since they do not move very quickly. Beginning the search in this area would be a good start.


When tortoises are spotted, the technician could plot a point using a GIS program, or the UAS flight software. When the craft has finished its flight, we could send out a truck equipped with gear for collecting tortoises to those locations marked, and relocate the animals. Tortoises would not have moved far from the position they were in when the UAS spotted them. Additional reading on tortoises can be found here: Tortoise Information.
A desert tortoise eating local vegetation.

A desert tortoise in its burrow.


Scenario 2
A power line company spends lots of money on a helicopter company monitoring and fixing problems on their line. One of the biggest costs is the helicopter having to fly up to these things just to see if there is a problem with the tower. Another issue is the cost of just figuring how to get to the things from the closest airport.


Questions before Starting:
  • How tall are the power lines?
  • How far is it between the towers?
  • How many miles of power line are we looking at? 2 miles or 30 miles?
  • What is the weather like?
 
If the weather is bad, for example if there is any wind or precipitation, the unmanned aerial system will have a harder time operating and not running into a power line.  


Since we don’t know how far we have to plan for, it would be best to imagine that we need to look at a long stretch of power line.  With a long stretch of power line we will need an unmanned aerial system that can fly for a long time.  Gas powered or dual battery UAS systems will be our best bet because it will allow us to view greater amounts of power line and help save the electric company money.  With power lines being close together, we will need a small, versatile UAS system that has a video camera with the option to take pictures.  I think being able to fly the UAS down the power line with a video/still camera would be our best option.  When flying down the power line if you notice a problem you could take a still picture and see what equipment you would need to fix the problem. There are many UAS available, but the best one for this job would look like the 3DR RTF X8 with a GoPro camera attached. You can check out this UAS here and check out the camera here.  

Here is an example of a power line tower that was surveyed by a UAS.

Scenario 3
A pineapple plantation has about 8000 acres, and they want you to give them an idea of where they have vegetation that is not healthy, as well as help them out with when might be a good time to harvest.


Questions before Starting:
  • What time of year is it?
  • Harvest or growing season?
  • Is there a history of problems (like parasites, bacteria, fungus, etc.) on this plantation?


For a situation like this, the best thing to do would be to start with the most recent NDVI (normalized difference vegetation index) satellite data of the area. The plantation is too large to start combing the entire area with a small, unmanned craft. Using recent NDVI satellite data, we could see what areas are not as healthy. Then, once we have narrowed down our survey area, we could send out a UAS to gather data on those specific parts of the plantation. With video and infrared devices on board, we could find out why those areas are having trouble (if it is a soil issue, pest issue, etc), and plan accordingly.
An example of the NDVI.

Another, cheaper option would be to use a balloon after analysing the NDVI data. The same type of multispectral cameras could be fitted to a balloon to get images from above the plantation. The problem with this option is that you wouldn’t have as much control over a balloon as you would a fixed wing or rotary device.


A gas powered fixed wing craft may be the best option, as it would be able to cover more area and remain in the air for longer periods of time, as compared to a rotary craft. After analysing the satellite images and narrowing down the area, we could send out a fixed wing craft that would circle the areas in question and gather multispectral data. Here is a company that is doing this exact thing right now.

Scenario 4
An oil pipeline running through the Niger River delta is showing some signs of leaking. This is impacting both agriculture and loss of revenue to the company.


Questions before Starting:
  • How many miles of pipeline do we have to monitor?
  • How much oil they are losing from the leaking?


There are more ways to start like remotely sensed or LIDAR images.  The first, but most expensive option would be to use LIDAR data.  LIDAR data are images have a closer resolution, have more depth and detail than remote sensing images from LandSat or other satellites.
A good, cheap way would be to use the latest NDVI (normalized difference vegetation index) or LandSat image of the area to see where vegetation is dying or where a leak might be. If the pipeline is in two or more images you can mosaic the images together to be able to look at the full pipeline.
In order to use an UAS for this situation we would have to use a very quiet and undetectable system.  Niger has been through a lot of changes in the past few decades which has led to violent outbreaks.  You can read about Niger and it’s history here.  


Scenario 5
A mining company wants to get a better idea of the volume they remove each week. They don’t have the money for LiDAR, but want to engage in 3D analysis (Hint: look up point cloud)


Questions before Starting:
  • How large is the mine?
  • How in depth does the photo have to be?


Since they don’t have the money for LiDar they could use DroneMapper to create 3D landscape images.  DroneMapper software can create 3D images from 2D aerial photos.  We could send up a UAV  to take still images of the mining site at the end of each week for the mining company.  Those still images could then be sent in to DroneMapper for the conversion.  Another way would be to have a balloon with a camera mounted on it take the pictures.  An advantage of using a balloon instead of a UAV would be that it would cut down further on cost.  Further information about the DroneMapper service can be found here and information about their image requirements can be found here.