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  This image is out of date; the brown areas are now paved parking lots and obviously the field is, at this time of year, covered with snow.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

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.  

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.  

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.