Monday, April 22: Balloon Mapping II, Results.

Results:

                This week’s activity rolled out much more easily than last week’s.  The first balloon launch had a number of issues, not the least of which was the weather.  When taking aerial imagery from a lighter-than-air craft, it is obviously quite beneficial to have stable air conditions.  The wind during the first launch provided the class with some interesting images, however not many that were particularly useful.  Mosaicking works far better with less oblique imagery: the edges work out much better that way.  The more oblique an image is, the more distortion is introduced.  Fortunately, throughout the entire first batch of photographs we were able to pull enough to build a workable mosaic of the area that was walked.  This might be taken to indicate that even with conditions of moderate wind; a slow enough walk-through the area of interest can yield workable results.  Walking speed does not however remedy the problem of getting the tether tangled in local features like buildings or trees introduced by wind… in fact if the project had been completed quicker Bessie may never have taken off over the river.  On that note, while waterproofing may have seemed a luxury at the time I would definitely spend the extra few dollars and minutes next time to ensure that my data is that much safer should trouble arise (or fall).

                When it comes to mosaicking images together, MapKnitter does an okay job, I have to say my expectations were quite low for this free software and I was thoroughly impressed.  It was relatively easy to use, and it’s completely free.  It does have some disadvantages though.  It lacks some functionality present in the more advanced programs offered to the class (Arc and Imagine), and even the best images that I saw mapknitted by classmates don’t quite equal the seamlessness of the images provided by ESRI and ERDAS.

                Speaking of, my group’s final section was produced in ESRI ArcMap.  Georeferencing took a very, very long time in order to get all of those sidewalks to stack well together.

Discussion:

                I can’t believe the amount of work done by half the class… thank you especially amy and bea. Next time, more responsibility needs to be taken by someone to ensure that the project is completed start to finish. …

Monday, April 15: Balloon Mapping II, Methods

Introduction:

In early February, I posted about the early stages in perparing for a method of collecting aerial imagery using helium balloons known as Balloon Mapping. Now, for the past two weeks the class has been making good on the first half of that project: the low-altitude ballon launch has come to fruition. On the 1st and 8th of April, the launched our noble apparatus and towed it around the campus here at the University of Wisconsin -- Eau Claire as it collected thousands of aerial images from which to develop a single image of campus tied to defined geographic reference points. The following is an account of the methodology of our launch and image processing, as well as what was learned in the class's two launches.

 The goal for this section of the project is to develop a high-quality, georeferenced aerial image of campus.  We will require the helium balloon, an effective compartment to house and protect a digital camera inside, and the software to combine disparate images into a single unit.  This week’s blog post will describe the methods used to develop the rig, collect images, and process what was collected.

  

Methodology:
    Launch 1:
          The first launch was conducted on Monday, April 1^st.  April 1^st in Eau Claire, WI was windy, to say the least. Naturally, the wind was highest during the period from 3 to 6 p.m. which was exactly when it was decided to launch the aerial rig.  Noticing wind speeds around 15 mph and gusts in excess of 25mph, it was decided to use the more substantial platforms to house the digital camera today; so the HABL rig was attached to the helium balloon instead of the Low-Altitude rigs developed for the project.

 

figure 1: wunderground historical weather data for Eau Claire, WI on Apr 1. Note the wind gusts around 4 PM.

The HABL provided certain advantages over the other aerial mapping platforms: it was more insulated, painted with hydrophobic material for waterproofing and heavier which it was reasoned would provide more stability in the wind.  Its design was based around a Styrofoam bait container, the type used in fishing which would prove fatefully ironic. Perhaps most importantly, it was heavier and therefore (in theory) less susceptible to the prevailing winds, however the end results of this project indicate that the added weight was inadequate in this case. 

         
           Bessie, as the big red weather balloon came to be called, was attached to 400 meters of rope in addition to the camera platform and released into the air while attached to a ground crew whose duty was to guide the balloon around campus (and around obstacles on campus, such as light poles, buildings etc.).  In the wind, however, Bessie's actual distance from the ground was significantly reduced from 400m because she was pushed some distance away from the ground control crew in the breeze.  It was attempted to find her precise height using the radar distance finder (see distance azimuth exercise) but this attempt met poor results.  The camera rig was tossed around rather harshly in the turbulence, which had the side effect of providing some nice oblique images of campus caused some concern for those on the ground.  Regardless, the exercise continued as scheduled and the ground crew guided Bessie through the area until she broke free and made for the horizon somewhere over the bridge connecting campus across the Chippewa River.  Fortunately, she was kind enough to drop her payload in the river before lifting off, and being waterproof the images retrieved from the day were quite usable after the rig was fished from the River by Professor Hupy.


     Launch 2:
           Monday the 8^th provided far clearer weather than the week prior, and as such it was decided that a less weight-intensive payload could be attached to the second balloon (named Bertha).  The old Low-Altitude, bottle-based design for the rig was improved by Stacey’s addition of an old arrow whose fletching was augmented with cardstock to stabilize the rig in the air and keep it from spinning much in the wind this time.
       

          The rig was launched to a height of 550 meters and guided through campus much like it had been one week prior, but today the balloon was recovered as well as the imagery.  Because of the good weather conditions, the balloon was taken over significantly more territory on this occasion than earlier.



     Processing:
            The class was allowed to use any combination of three programs to mosaic the images from each rig into a pair of georeferenced orthophotographs of campus: ArcMap, Imagine, and MapKnitter.  Some students used the online services of MapKnitter, but I decided to use ArcMap, having mosaicked orthophotos in Imagine before and feeling some trepidation about the quality of Mapknitter’s abilities to provide a seamless image.  Before Images can be mosaicked however, they must be georeferenced to locations on the earth.
         
            The first task is to select the images to be used for processing from the camera.  When looking for a good image, one looks for an image that is taken as close to directly overhead as possible: oblique images are not very useful for mosaicking.  In the first set of images, this restriction made selecting appropriate images difficult as many of them were very oblique indeed.  The second set of images was difficult to sift through simply because there were so many usable images, which is a good problem to have I suppose.

           After the enough images to cover the area of interest have been selected, they need to be georeferenced.  One does not simply piece each individual image together and call it done: the pixels in the image need to be tied to coordinates in reality using georefrencing.  To do this, several “control points” in the image are selected which are readily identifiable and relatively stationary such as lamp posts, building corners, or road edges.  These points in the image are then “tied” to the geographic coordinates of that point in reality; this can be done in several ways.

One way is to use another image, which is already georeferenced, on which to overlay the new image being referenced.  The points in the new image are selected, and then related to the points in the original image in order to warp the new image into an appropriate approximation of reality.  Another possibility is to use GPS or Surveying in order to physically collect each point in the field, and use these points to connect to the image being georeferenced.  For both sets of images, I used a georeferenced basemap to tie my GCP’s to, but for the second set of images a group of students also set out to collect GCP’s using GPS equipment.

In Arc, this requires the Georeferencing toolbar.  First, a dataset with spatial reference is opened, and the new image is imported on top of it.  Not having any spatial information, the new image will not be displayed with the currently open map and so must be added to the display by using the “fit to display” tool on the georeferencing toolbar.  Then, the rotate, shift and scale tools are used to roughly position the image where it belongs in relation to the control points of the map.  Then, the control points on the map are selected individually and connected to the control points of the reference image.  Finally, a transformation is applied to the raster which warps the image to best fit the changes in each point.  Most of the images I mosaicked used 2^nd-order polynomial transformation.

            Finally, once all of the images are selected and georeferenced, they need to be mosaicked together into a single orthophoto.  In my case, this is accomplished by using the mosaic to new raster tool in ArcMap, which creates a fresh new image from my multiple component images.  For the first set of images, I used eight photographs to create a rough mosaic of campus.  For the second set of images, there were so many photographs covering so much of campus that the class divided the area into six sections and worked on each section in groups of three.  Then the class uploaded each section into a class geodatabase to be finally pulled together in and a single, high-quality image of campus from the class will have been made.

Monday, March 25: The Navigatorial Competition and a Comparison of

Introduction:
 

This week's activity is best described as the culmination of the previous month's work. Each team of three will be provided with both the land nav maps and the GPS units, and will be tasked with finding all fifteen points in the course. To add a level of urgency to the exercise, all six of our groups will be in competition for the fastest navigation in the class. The fastest (or most complete) group in three hours will be declared winner; what exactly they win is as yet uncertain but it must surely be something pleasant. Most likely, the answer is simply 'not getting shot,' because as a final measure to complicate our traversal of the Priory is the inclusion of paintball guns. The ultimate goal of this task is to see how well our navigation skills will hold under duress, hopefully we shall pass.

 

Study Area:

For March, the terrain around the Priory has not altered much since our first excursion on the 11th. This is at once both a good and a bad thing: in particular the persistent snow cover continues to impede our ability to make use of the aerial imagery and digital elevation models in our land navs. In addition, when multiplied over the size of the entire course, the snow which at places remained waist high was a tremendous burden to movement. With this in mind, Professor Hupy decided to offer snowshoes (fig 1) to the class for this exercise.

 

I did not wear the snowshoes, but from a distance they looked a good deal like these.

In my estimation, choosing snowshoes would improve my ability to trek over a distance but could be an extra burden in a fight, restricting my maneuverability in the sometimes thick niches of the Wisconsin Woods which can make for wonderful mock-ambushes. I chose to forgo the snowshoes on today’s journey.

A few changes have been made to the course for this week’s activity from our last encounter with the Priory.  As mentioned earlier, this week we are expected to (or striving to) visit each checkpoint on the map.  Furthermore, because of the similarity that paintball markers bear to real weapons and the proximity of the Priory and Interstate 94 to our activity, Joe has designated several areas as off-limits to the navigation.  There will be no shortcuts or firefights across the Nature Academy’s Lawn. These areas have been designated on both our aerial and topographic maps (fig. 2 and 3 below).

fig. 2: the final aerial

 

fig. 3: the final topo

 

Methodology:

            The final maps created for this activity are above, including both the off-limits zones and each of the points that should be navigated to during the afternoon.  The groups are allowed to make use of all, or none, of the previously learned tools in our belts: the compass, GPS, and of course maps are all available and acceptable.

fig. 4: the Garmin Etrex H

The data collection this week will be done with Garmin Etrex Handheld GPS’s again (fig 4), taking a continuous tracklog at 30s intervals.  We will also have to input each waypoint from the course into the GPS as a waypoint.  The Etrex are set to record position in UTM coordinates (zone 15N), and will be used for navigation as well as data collection as participants are given the coordinates for each point at the outset of the exercise.  As a final quality assurance / quality control measure (safeguard against tomfoolery), each team will again receive a punch card which has unique punches to be received at each individual navigation point.  

            After the event is finished, each group will again export their tracklog and waypoint data from their individual GPS into the GIS using the DNR_GPS program.  After downloading the GPS information using this program (fig 5), the data will then be compiled by the professor to make available to the class through the GIS on UW-Eau Claire’s network.  The final stage of this project will be to look at the data in ArcMap and analyze what each team did, and see how well it worked.

    

fig 5: DNR GPS, pre-loading. The path to download is GPS>>Connect to GPS then Track (or Waypoint) >> Download.
Connect GPS to computer before attempting.

Discussion:

          The final data is not altogether surprising.  The final map is figure six below, and by looking closely at it one can see that groups branched off most in the beginning (start was just north of the Priory) and in the middle of the map especially closest the interstate where compressed againt a hill  the groups clustered along a single path almost exclusively.  Some points of conflict can be seen clearly, in a few areas it appears as though a conflict may hav forced a group or so to shift course.  An example of this can be found halfway between points 1A and 2; or directly north of point 5B just south of the restricted zone.

fig 6: the final Aerial Map with Each Group's Tracklog.

          Each point was visited, but no group visited each point.  Suprising to me was that point 4 got hit by each group, while it was extremely remote and difficult to find. On the other hand, point 5A was easy to reach because of the flat terrain and nice forest cover that kept the snow lower, but it hardly recieved any visitors by comparison to many other points. 


Conclusion:

With regards to the terrain itself, it would be a lie to say that I did not wish that I had taken the snowshoes by the end of the trek. While I stand by my previous assertion that snowshoes can be an impediment during a fight, I do not think that the slight loss of ability on a small number of occurrences warrants the massive amount of energy exerted unnecessarily fighting the elements.  Watching my colleagues glide across the snow after a fight, I determined that the snowshoe/no snowshoe issue is best summed up in fig. below.  I would conclude that snowshoes were beneficial to those that wore them.

Snowshoes

Noshoes

            Personally I found that I prefer to trust the land maps to the GPS units.  There are advantages and disadvantages to each, but in this situation I found that using the maps to navigate with provided data that was simply not available through the Etrex.  That aside, my group spent much of its time working forward with our noses half buried in the diminutive screen of the handheld GPS in an effort to stay on course.

There is something to be said for knowing one’s exact location in relation to a goal, and if lost (as we would have been on several occasions after a particular battle or two) the GPS gives the immediate position of the beholder.  On the other hand, valuable time could have been wasted trying to conclude our position on a map.  Of course, maps never run out of batteries which is a situation that my GPS appeared to be nearing a mere three hours into the activity.  Ultimately, the ideal navigation scenario for me would include both a GPS and a map.