Introduction to Navigation and Fieldwork Map Construction

Introduction

For our next project we shall be navigating our way around a mini orienteering course close to campus without the use of modern day navigation technology like GPS devices.  However, the weather here is Eau Claire is still bitterly cold (there was a wind chill of -3-F today), and there is still much snow on the ground, which would make the task quite challenging at the moment. So we are waiting until conditions improve slightly before carrying out our fieldwork. However, we can still learn about the skills we will need to use in the field in order to be able to find the markers in the field. We explored the more "old school" methods like pacing and compass work, and using the maps to relate yourself to the surrounding physical features what they were and how we could implement them.

We also had to create our own maps for use during our data point collection. This involved employing the computer skills in ArcMap, as well as being able to take in to consideration what elements to include in the map, and he appropriate projection to use for the data. Two maps needed to be produced for a Decimal Degree and Meters data set.

Methods

Pacing is the ability to work out your average number of steps over a certain difference in order to be able to remember this number and use it to calculate how far you have traveled in the field. By knowing the number of steps you usually take to cover a distance, by counting your steps whilst in the field, should be able to work our form the total amount of steps at x steps every x distance, how much ground you have covered.

As a class we went outside to work out our own pace count, so that we could use it in the future. We used the handheld laser distance measures like in the last project to measure out 100m. Then we each walked that 100 meters twice and took the average of how many steps we took each time. MY average was 66 steps, which is around about what most people got, as it's usually between 64 and 68. Except of course if you were particularly tall or particularly short, which would vary dramatically.

The class was then given a quick crash course in compass skills. How to read the values from them and what the different arrows mean were explained. Figure 1 below shows the different elements of a standard compass.

Figure 1: A standard field compass and it's elements ( © paddlinglight.com)

In order to gather where Magnettic North is we turn the compass dial (or bevel) so that the N (North) is in line with the direction of travel arrow. We then standing still move our bodies around until the red arrow is sitting on top of the red arrow drawn inside the compass housing. Calculating a map bearing involves placing the edge of the compass of following the direction of travel arrow point your compass on the map in the direction you are headed. Then adjust the housing until the orientating lines are in line with the latitude and longitude or coordinate systems on the map. The number that is now in line with the direction of travel was before, is the bearing. Bearings are technically given in 3 digit forms, which is fine if your bearing is e.g. 180 degrees, but if it is 20 for example, then we simply put a zero in front, so it becomes 020 degrees.

It is important to use all the information that a map is able to give you when navigating. people that are used to reading maps, especially topographic ones will almost be able to picture the landscape before you even see it. By looking at the contour lines (isobars of elevation) whose interval is usually marked on the map, the water features and having knowledge of how these and other parts of the landscape form can help you to predict what might be happening in the landscape. If pacing is not appropriate then the map scales can be used by utilising the string of your compass, or a nearby branch or something. If you measure a distance on the map, and then hold that up against the scale, you should be able to get the real life value. Sometimes, when a little lost it can help to take a look at significant features on a map and see if  you can identify them in a landscape, and then find your place on the map from there.

In order to make our maps we set up a new geodatabase in ArcMap to save everything to the same place. It was important to ensure that the default geodatabase was set to our own, and that the works pace was pre-set to it also.Then the geodatabase that contained the different shape files, point line and polygon features had to be explored and experimented with in order to decide what would be appropriate for our maps. The sizes and colour schemes of different elements were altered to something that would be easily readable and visually pleasing.

A grid co-ordinate system needed to be added to the maps, as we would be plotting our data points later on out in the field. A different grid system was used for each map from the properties window of the layer, one mad use of meters and the other decimal degrees. This involved also having to select a co-ordinate system for each map. Co-ordinate systems are used to project the earth accurately, as the Earth's shape is actually a geoid and not a sphere as is commonly thought. So, a series of different methods of projecting the Earth on to a flat surface were created, each one however will distort the shape of the earth in some way in; direction, distance, shape, area etc. as it is not possible to deconstruct a round shape on to a flat surface without some degree of distortion. Depending on the area and what you are looking at the system you use will change.

Then some of the essential elements of map design were added using the insert drop down menu. This included; a north arrow, a scale bar and data, projection and co-ordinate system labeling, data sources and our names. AS well as other elements we wanted to include. These were then exported as JPEG images,for use when we carry out our fieldwork. Figures 1 and 2 below show the finished products of the two different maps.

Figure 1: The final map for use in collection of field points using a projected coordinate system that had metres as the units.

Figure 2: The finished map containing a coordinate system that had decimal degrees as its units, for use in data point collection in fieldwork.

Discussion

Pacing is such a basic thing but can be very important and helpful when it is needed. However in areas like thick woodland where there is perhaps lots of vegetation, tree stumps and roots on the ground, you have to take in to consideration that your pace will be a bit slower, It is the same of areas of high relief and in icy or snowy conditions. Also, if this technique is being implemented over a long period of time, then it can be very easy to loose count. A method we were taught to overcome this was to take a twig and every time you reach done of your units of measurement, you would snap it off and put it away fir safe keeping then count all the pieces you have and times that by the distance represented by each.

When deciding upon which map elements to use I added all the different elements at first and decided what was unnecessary as it it did not hold a purpose in helping me in t he field, what image worked better than others in terms of clarity. Also, some elements were obscuring the view of those more important and so were not included.

It is also important not to just stick to a bearing and follow it dead on from the compass, check it against the map and look around often. As we were dealing with the state of Wisconsin and needed something from the UTM zone, I chose the NAD 1983 (2011) UTM Zone 15N, as the projected co-ordinate system, this is one of two UTM zones for Wisconsin, and this is on this covers the area we are studying. NAD 1983 was used for the other map so that the units would be in decimal degrees, and it is a widely excepted coordinate system for U.S. datum.

Conclusions

There are many more skills involved in reading an interpreting a map, than people might have at first thought, It is this bringing together a mix of skills and elements that will make for an effective team in finding points in orienteering. How to use the compass correctly, calculation pace rates, looking at the landscape and identifying on the map, can all help greatly. The projection you use and it's influence needs to be thought about when adding a grid to a map, so as to still remain effective, and not obscure the area too much, which would then make it more difficult to navigate.

Conducting a Distance Azimuth Survey

Introduction

This next field activity was looking in to how data points about an area can be collected more easily than using a co-ordinate system, as was used in the terrain model assignments. We learnt how to make use of some of the older and more recent technology that is available for surveying sights. Our aims were to firstly be introduced to and to try the equipment, then conduct our own group fieldwork. Then, the data needed to be used in ArcMap to produce a map of the data points collected. Throughout the process we were discovering the advantages and disadvantages of different technologies and techniques and some of the problems that people may encounter using these sorts of techniques.

The Study Area

The area we used to practice with the new equipment was located just outside of the academic Science building where our class is held, on the University campus. The area is fairly flat and contains a number of different features with green areas, woodland, car parking space, pavements, lampposts and various signs for the University. Figure 1 below, shows an areal image of the area.


    Figure 1: Aerial image of the first site used to carry out fieldwork. (C. Google Earth)

The study area that my group chose to use for our fieldwork project was located outside of the Nursing building on campus. One of the corners of the building was used as our point of origin, in order to plot our data points on top of an aerial image. The location is similar to the first one and contained trees, poles, signs, mailboxes, bike racks, and some car parking spaces. The land outside of it is a green space and there is a steep slope containing woodland. This are was chosen as due to the high levels of snowfall there had been we needed somewhere local that would be easy to get to and somewhere where all members of the group would be able to meet. We also thought that there would be a good mix of different point types.

Methods
 In class we were introduced to three different types of equipment that can be used to gather information on the distance and azimuth of a point from a source. We then moved outside as a class in order to all have a go at trying each of the methods and to discuss what sort of things we should measure and what should be taken in to account when picking a study site.

One: A filed compass with a built in azimuth viewfinder. Figure 2 below, shows an example of such a device. This is a more basic method that involves less high-tech technology, but is a multistage device. By looking through the viewfinder towards the point you are measuring you can read the scale to collect data on the azimuth of the object from the point of origin.

Figure 2: An example of a field compass with a viewfinder for reading an azimuth recording.

Two: Handheld laser distance measures, this includes two devices, one is held at the starting point and another at the point you are collecting data about and when pointed at one another the distance is recorder digitally on the first device. An example of these devices is displayed in figure 3.

Figure 3: An example of handheld laser distance measures for use in fieldwork.

Three: Trupulse Laser Rangefinder, we found to be the best all round option for ease in the field. This device can be pointed at a recording point and a you can select using buttons on the side what you want to calculate, so both the distance and the azimuth, are displayed and can be read easily and quickly off the screen. An image of what can be seen through the viewfinder and an the device itself is in figure 4 below.

Figure 4: The Trupulse laser rangefinder and what can be seen when looking through it when it's in use.

My group decided that we were going to survey trees, and then decided on our location as discussed previously. A table was constructed before going out in to the field to make the data collection more organised and speedy. Said table with it's filled in value is shown in figure 5. We decided to bring a tripod out with us in order to guarantee, that the origin for the points would be exactly the same, figure 6 is an example of my group collecting and recording data. The attribute we decided to collect was the point type as we felt this would be the quickest and easiest to gather seeing, as we had to wait till late on in the week until everyone in our group could meet to do the fieldwork.  Once we were actually at the site we also saw and decided that we would have to record more features than just trees in order to make up one hundred points. So, once having a look through the viewfinder to see where our maximum range ( 1-4 to 1 hectare plot), and then selected points to measure and the point number, attribute type, distance from origin (m) and azimuth from origin (Degrees) were collected.

Figure 5: The table that our group used post data collection in the field.

Figure 6: Two members of my group collecting data using the Trupulse and recording it into a spreadsheet.


This table was then converted into digital form by typing the values into a excel spreadsheet, A base map satellite image of the field area was added to a blank map in Arc GIS (figure 7), and then using the same corner that we measured from on the nursing building we were able to read of the bottom of the screen the origin x and y co-ordinates, by holding the cursor over it. The x and y co-ordinates were then added to each data poin in the table, in order to be able to export the table to Arc Map.

Figure 7: The base map used in ArcMap to display recorded points on.

A geodatabase was set up in Arc Map and then the excel table was imported in to it. ArcToolbox was opened, then we went in to Data Management, Features and double clicked Bearing Distance to Line. A window then opened up where we had to select or data table as the input and select the various fields, then the lines were added to the map to show the distance and azimuth from our starting point, as conveyed in figure 8.

Figure 8: The AcrMap basemap once the Bearing Distance to Line tool had been applied.

We wanted to have our data displayed as points also, to in the same features toolbox the Feature Vertices to Points command was used, and the same process as before was applied. Figure 9 now shows the final map created from our fieldwork.

Figure 9: Final Map of the distance azimuth survey on campus. 

Discussion

As mentioned slightly in the methods section, as a class we decided that the Trupulse laser rangefinder was the best for carrying out our fieldwork. As, it is able to carry out a greater number of measurements the other pieces of equipment, the data is displayed for you so you do not have to read it off a scale, and if you were by yourself you could carry out fieldwork alone fairly easily.

When we arrived at our site we were able to see just how much of our view was obstructed by the buildings and how many data points would be within our distance range, and it did not look like enough, so it meant we had ti branch out to different types of points. But I think it gives a better impression of what is actually at the location. Also, with the trees it was quite difficult to tell them apart at this time of year, as they were closely situated next to each other, had shed their leaves and were covered in snow.

Towards the end of our data collection there was some precipitation starting to fall which was obstructing the lens, so we had to make sure that was clear. Entering the data in to excel was fairly time consuming and can be quite frustrating when you already have it in a table from and it's just not digitised. So we have decided that during future field work, (weather permitting) we shall use my iPad to record the data on, so that it goes straight in to a digital form and can save some time.

The first few times that the Bearing Distance to Line feature was used it failed, as some of the table categories and names contained numbers and punctuation which did not allow the tool to run, so this had to be altered. Bright colours had to be used for the line and point displays in order to be visible against the satellite image.

This technique for collecting field data is very useful as it is much easier to be able to stay in the same location with all your equipment and record data than having to go out to each point, especially if you were doing this on a larger scale. It is time effective, and as previously mentioned is suitable if you were carrying out a project alone. It can be used for nay form of data collection where you need to measure how far away points are from each other, their distribution, the prevalence of something occurring. It can in many cases be used in conjunction with GIS or in fact replaced with GIS if no fieldwork were to be involved.

The gathering, recording and displaying of data seemed to all go well, and so I feel that our results are probably fairly accurate. Especially seeing as we made use of a tripod, it meant that we could ensure that all the measurements originated in exactly the same location. Of course there is always the chance that technology will fail you and perhaps won't be completely accurate, or that they may be read or recorded wrong.

Also, with Azimuth calculations there is always the problem of magnetic declination, this is the angle between North and true North. This varies according to location and changes over time. Using the National Oceanic and Atmosphere Administration website, you can calculate the magnetic variation for your site, the calculation for our groups fieldwork site is shown in figure 10.

Figure 10: The NOAA calculation of the magnetic declination for our azimuth survey fieldwork location.

Conclusions

There are many different methods and instruments that can be used nowadays to measure the distance and azimuth of selected features whilst carrying out fieldwork, one that can calculate a wide variety of measurements quickly and easily is preferable. it is important when collecting points from a source, that the source remains the same each time, and magnetic declination must be taken in to account when calculating the azimuth. Tables being used in ArcMap must have simple headings and titles in order for tools to run successfully. The type of data that you can collect whilst doing fieldwork can alter when you see the site for real than when you look at it on a map or are planning, and some things may be more difficult o see or measure depending on the weather conditions.

Unmanned Aerial System Mission Planning

This assignment was aimed at getting us thinking about the re-planning and preparation that goes in to any type of field work, and especially where very high tech expensive equipment is used. As, any time lost in the field due to lack or preparedness, or failure to assess if the conditions are suitable, can waste significant amounts of money.  

In thinking about the Geographical world today and many of the data collection that is carried out, some astonishing technological advances have been made. Data can be collected, quicker, more often, to a higher standard, with less people, and different data types can be collected. Much of it involves out sourcing to other professions that have a better understanding of the data collection. But these professionals can sometimes have a lack of understanding for the sort o f geospatial thinking that is required by geographers to carry out fieldwork.

In this assignment we were given 5 scenarios in which companies may require unmanned air vehicles in order to collect data in aspects of geographical phenomenon. We had to think about the different things we would have to survey, how we would do that, the inputs that would be needed from technology to a sampling method. In order to come up with some ideas that a company could use in these situations.

Scenario1: 

 

-       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.

Firstly, the area is fairly large so if the methods we come up with prove to be too time consuming or expensive, a sampling method could always be employed in order to get a general idea of the vegetation on the land.

Also, we thought that maybe the type of data that we would be collecting could maybe be used over several seasons, so may prove to be worth the money and time. We thought that once it had been highlighted which areas had the pooper quality vegetation, and which area was best to harvest then, these trends might apply across a few growing seasons.

I order to highlight the areas where the vegetation is less health than others, we felt that a near infrared sensor could be used. Near infrared sensors detect electromagnetic waves of wavelength 3.5 to 20 micrometers, as this is the wavelength of moisture particles. As water is one of the input elements of the process of photosynthesis, we thought that areas where we could detect higher moisture levels would be areas where the vegetation would be healthier. Figure 1 below shows an example of this type of sensor being put in to practice in relation to vegetation health. You can see how it clearly shows the different areas of soil health, and how you could determine which areas were less healthy. 

Figure 1: An example of a near infrared sensor image being used to measure the health of vegetation in Colorado. (© Federation of American Scientists)

However it must be taken in to consideration that these sensors can be expensive, and they must be kept very cold when used, as the radiation that is being sensed is so weak. In order to acquire knowledge on areas where the plants are ready to harvest, we thought perhaps a digital camera could be used in order to see the colours of the landscape and wee where the crop is ripe enough to pick. This would be a fairly cheaper part of data collection as cameras are cheaper than remote sensors, but it would have to be a high resolution camera, in order to detect the image from a significant height above the fields.

These sensors would then have to be attached to an unmanned aerial system, in order to acquire the data from above and keep costs to a minimum. We would recommend using an Aerosonde, as theses are commonly used for collecting weather data. It is gasoline powered which we felt was necessary as we are covering such a large area, and many of the battery operated ones do not last very long. It has the ability to hold sensor equipment as many of them come with different sensors, and it can last about 38 hours in the field in one flight.

We propose that a flight course would be pre-made to fly the vehicle back and forth across lengths of the fields taking images along the way until the whole area had been covered. You may want to carry this fieldwork out just before the 18-20 month growing period is over. Also, seeing as many of the regions where pineapples are cultivated have cold very hot days but cold nights, it might be best to fly the unmanned aerial vehicles at night, so as to keep the sensors clod, but there would still be moisture content in the air. The data on harvesting times would have to be done during the day, so that the hues of the vegetation could be seen, and the camera does not require a special temperature. 

Scenario 2: 

 

-       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)

We are presuming that since the company the company wanted to use LiDar but couldn’t afford it, then the type of mining they are engaged in is open pit and not underground. We came up with two possible ways for monitoring the amount removed from the mine each week. One approach would be to use digital imagery to detect the slag heaps, where measurements could be carried out from the data collected to detect the volume of matter removed. The other would be to use a cloud point method where laser detectors are used to detect and later recreate an area, these detectors would be flown over the actual mining pit in order to construct the space, and then once this is done over time we could see how the size changes and therefore the volume removed could be calculated.

For the first method the data collection should be fairly quick so that type of unmanned air vehicle we would recommend would be perhaps a slightly cheaper unmanned aerial vehicle can be used, so as to save money. The flight time does not need to be that long so maybe even a battery operated one would be sufficient, a quad copter may be a good choice as it could fly straight up and over the slag heap and remain fairly steady and balanced for the image taking.

This data collection would have to be carried out during the day so that the heap could be seen, and the time of year would only be an issue if the mine was located in a region that experiences winters with high precipitation rates, that might obstruct the camera’s view. As the company wants to know how much it removes each week, the image could be taken once a week. Then using computer software like ArcMap, the image could be downloaded a scale applied, and then volume calculations could be made from measurements made on the computer.

3D scanning can be performed using a regular camera attached to a UAV and entered into the appropriate modelling software. A steady camera would be required, such as rotary wing copter with the ability to hover. A rotary copter is most suitable for hard to reach locations, which may include some mines. Using this technology an open pit mine can be visualized; from this visualization it may be possible to determine the volume of the mine. Another option may be to attach a specific 3D scanning camera to the UAV creating a point cloud mesh, this option is very similar to LiDar; but would increase the cost of the survey. Use of 3D sensor camera would yield a more detailed report of the mine and would be very similar to overhead aerial LiDar and ground LiDar surveys.

The data collection for the cloud point method will be quite extensive, as the unmanned aerial vehicle that the sensor will be attached to will have to cover all of the exposed mine, and may at some points need to go down in to the pit. So definitely a gasoline powered on would be appropriate and with a long flight time, so we would recommend a General Atomics GNAT. Also, as the data needs to be recorded each week, the cost of the vehicle should probably be kept fairly low.

Scenario 3: 

- 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.

The Desert Tortoise is an endangered species that lives in the Mojave and Sonoran desert of southern California, Nevada, and Utah. They prefer semi-arid grasslands, desert washes, and sandy canyon bottoms that are below 3,500ft elevation. They live in burrows that are 3-6ft deep. They are most active in the Spring and least active from November through February, when they hibernate in burrows. Desert Tortoises depend upon vegetation such as new cacti growth for food and water; they also consume calcium-rich soil for digestion, and prefer to burrow in sandy loam soils (ardisols) with varying amounts of gravel or clay. When rain is anticipated, the tortoise will dig basins to collect the rainwater. Tortoises also prefer south facing slopes. A recent study performed by the Department of Defense, states that tortoises prefer to build burrows under a vegetation canopy near to a desert wash. (Grandmaison 2010). All of these factors can be used to aid in locating the tortoise habitats.

 

 Figure 2: An Example of the Unmanned Air Vehicle that we feel would be appropriate to use in the data collection.

The use of unmanned aerial systems (UAS) can aid surveyors in determining where Desert Tortoise burrows are located. There are several options available for UAS, including a fixed wing UAS, or rotary wing UAS. A fixed wing UAS is more suitable for covering large areas, and can travel in a preplanned grid flight path, as shown in figure 2 above. A rotary UAS is more versatile and can be used for small, but hard to reach areas. A gas powered fixed wing UAS can have up to 10 hours of flight time, allowing your organization to cover large areas in one survey. A multi-spectral camera can be attached to this UAS to survey the area and determine the soil type, vegetation and moisture of the ground below. Since Desert Tortoises dig their burrows or basins the freshly dug soil may have a different spectral signature than the ground; a simple remote sensing analysis of the collected image would be required. The same multi-spectral sensor can be used to create a false color image that will aid in visualizing areas of high vegetation and moisture content, which tortoises prefer. The data collected from the fieldwork can be shown in figure 3 below.

 Figure 3: An example of the data collection model that would be created during the U.A.V.  surveillance. 

Other sensors could be used to create a point cloud which would be used to create a digital elevation model through photogrammetry. This model would be used to determine elevation and slope. Combining the vegetation, elevation, slope and soil type information, a habitat map could be created which highlights key areas that Desert Tortoises prefer indicating areas also that would be better suited for training exercises. This survey could be completed in early spring or during the months of November through February.

Using a simple camera at low altitude and analyzing the photography would be a low cost option to detecting the burrows, other options such as using a multispectral camera and perhaps creating a habitat map would be more expensive.

Scenario 4: 

 - 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.

 

 The first question for this company would be "How much is 'lots of money?'" While it was difficult to determine the cost to utilize a helicopter from websites of companies that provided such services, those used for the purpose of medical evacuation cost about $6500 per transport in 2010 (Wykes and Sanford, 2013).

 Assuming that a medical transport would last approximately one- to three-hours, one could estimate a cost of about $2170-$6500/per hour of specialized helicopter services. Even so, using the lower end of this estimate, i.e. $2100, a power company would have to spend about $19500 to use the helicopter services, assuming a 9 hour workday.

The other major issue with using a helicopter is that finding a nearby airport may be difficult in cases where the power lines are located in remote areas. Flying or otherwise transporting helicopters (e.g. via truck) to such remote areas would only add to the cost of fuel and per-hour cost of the use of the helicopter.

 Another problem with using full-size helicopters to monitor power lines is that flights would be weather-dependent. For instance, if the power lines are located in a region plagued with inclement weather, how likely is it that a cancelled flight would be able to resume ASAP once the weather improved? Probably not too likely considering that the helicopter company would probably have other appointments scheduled with other clients.

 The most effective solution to the problems presented by full-size helicopter inspection of power lines mentioned above would be to employ an unmanned aerial vehicle to inspect the power lines for damages. However, a fixed-wing UAS platform (FWP) would not be recommended in the case of power line inspections due to: 1) the vehicle's inability to hover and take the pictures/video necessary to asses damage, if any and 2) the danger that power lines pose to the FWP should it become entangled in them. The risk of entanglement in power lines also rules out other, even cheaper, UAS platforms such as kites and balloons for the inspection of power lines and towers.

 The most practical solution to the problems inherited by inspecting power lines and towers would be to use rotary wing platforms (RWPs).  Following are two examples of RWP systems on opposite ends of the price spectrum.  

The cheapest resolution that would allow the utility company to effectively monitor its lines and towers would be to deploy a relatively cheap RC RWP unit to the areas where the towers are located. For instance, the Align RC 600 Nitro (fig. 4), which comes as a kit and costs approximately $700, could be retrofitted with a durable camera on its underside that would allow for the video inspection of power lines and towers.

 The waterproof Ion-Air Pro 2 helmet camera (fig. 5), for instance, weighs only 4.6 ounces, is small in dimension (1.4 x 1.4 x 4.5 in.), and has 2.5 hours of battery life. Costing roughly $250 apiece, several of these cameras could be bought and attached to the Align throughout the workday as the battery fails in each.

Although the Align comes as a kit, it would likely be no problem for one of the power company's maintenance workers to assemble it on site. Replacement parts for the Align, such as rotary shafts, blades, and fuselages are also available on the NitroPlanes web page (http://www.nitroplanes.com/15h-kx0160npc.html).

Furthermore, the relatively cheap cost of the Align RWP would enable more than one copter to be purchased, thus cutting down substantially on the time it takes to inspect the towers and lines. For instance, ArcGIS could be used to establish inspection zones and use a feature class layer to represent the towers. Each Align operator could carry a GPS unit that was programed with the coordinates of each tower and geographically "check off" each tower that was inspected in their respective zone. Towers could also get identifying placards installed on them so that their unique identifier could be synchronized to specific coordinates in ArcGIS and the GPS device.

 Mobility is another pleasing aspect to the RWP solution. For example, operators could take the small (approx. 7.1 pound) Align model with them in their company/all terrain vehicles (ATVs) to the locations where the inspections would take place. Once there, the Align could be deployed and the applicable data collected.

 Weather would not affect Align missions as much as those conducted by companies with full-sized copters because missions could simply be postponed until weather permitted their re-initiation. Also, since all the Align operators would be in-house (i.e. linemen trained to operate the RWP) rescheduling missions would not be as daunting as compared to doing so for independent helicopter companies. Furthermore, the low cost of the Align would ensure that if one of the RWPs did happen to become lost or damaged, a replacement, although not ideal, would be doable in terms of cost.

 One downside to this particular RWP model (i.e. the Align 600 Nitro)  is that its 440 cc fuel tank only allows for 10 minutes of flight time, assuming no payload and ideal conditions. However, the problem of limited flight time could be solved by simply replenishing the fuel supply periodically throughout the workday. Also, the Nitromethane fuel that this RWP uses is relatively cheap costing about $25 per gallon, according to some internet sources (http://www.ultimaterc.com/forums/showthread.php?t=176431) and would allow for 84 minutes of continuous flight time, assuming about 3700cc per gallon.

Figure 4: The Align RC 600 Nitro is a nitromethane powered, remotely controlled helicopter. With a camera attachment, such as the Ion Air 2 in figure 2 below, this device would be an ideal platform from which to monitor power lines and towers more cost effectively than current full-sized helicopter services allow (http://www.nitroplanes.com/15h-kx0160npc.html). 

 

  Figure 5:  The cheap, sturdy, waterproof Ion Air 2 helmet camera could be retrofitted to the underside of the Align RC helicopter (or similar RWP system) in order to visually inspect power lines and towers for damage. Multiple Ion Airs could be purchased in order to compensate for the devices 2.5 battery life.   (http://www.bestbuy.com/site/ion-air-pro-2-wi-fi-hd-camcorder-blue-black/2174008.p?id=1219070712053&skuId=2174008&ref=06&loc=01&ci_src=14110944&ci_sku=2174008&extensionType={adtype}:{network}&s_kwcid=PTC!pla!{keyword}!{matchtype}!{adwords_producttargetid}!{network}!{ifmobile:M}!{creative}&kpid=2174008&k_clickid=02b4ced1-feed-2e49-2a09-00003036eaf6#tab=overview).

 When fitted with a fuel engine, the Avenger by Leptron (fig. 6) gets about 2 hours of flight time. The biggest draw-back for the Avenger is its price tag which equates to about $100,000 apiece (Joyce). The reason for the high cost of the Avenger compared to the Align 600 is because, in addition to increased flight time; durability; and performance (i.e. its ability to operate in 40 mph winds), the avenger is much more versatile in terms of operability. For instance, the Avenger can be manually controlled by an operator through either a laptop Windows interface, or via a controller.

Also, a more sophisticated RWP such as the Avenger can also be flown by using GPS way-points to guide its flight path (autopilot). This option would be useful as the RWP could be flown to previously geocoded towers before the operator switches over to RC mode in order to perform a more precise inspection of the tower. Once each geocoded tower was inspected, it could be "checked off" the list if the inspection was a part of routine, preventative maintenance (PM).

Also, the ability of the Avenger to switch between RC and auto pilot mode is good since remotely located power lines might be miles from the road. In this case, the 11-pound Avenger could be transported via ATV or company vehicle to the area of interest and operated by remote control in order to inspect power lines and towers.

 Another attractive aspect of the Avenger is that Leptron sells specialty cameras that can be fitted onto the Avenger. These turret-mounted cameras (fig. 7) have geo-locator capabilities, are stabilized, and can be operated from the Avenger's remote control as opposed to commercially available cameras that could be mounted to the avenger in order to cut costs.

 One problem that the power company may have with the Avenger is that its price may limit the utility company to only one unit, and thus less area covered over a given time as compared to multiple cheaper units being operated simultaneously, as given in the Align example. 

 

  Figure 6: Image of the Avenger by Leptron in flight.  Although far more expensive than the Align RWP, the durable Avenger integrates all its geospatial technology, such as geocoding, geo-locating, and GPS way-points, into one unit so that data relating to power line and tower inspection can be easily classified (http://www.leptron.com/corporate/products/avenger/specs.php).

Figure 7: Some of examples of the more sophisticated, turret-mounted, remotely operated cameras that can be used fitted onto the Avenger RWP system (https://www.leptron.com/corporate/products/avenger/camera.php).

 While the Align and Avenger RWP options above both solve the fiscal problems associated with of utility line inspection via full-sized helicopters, each does so in a different way. For instance, while the Align option is much cheaper than the Avenger option, the Align would be much more cumbersome in terms of operation, mobility, flight time, convenience and data accuracy. That being said, all the problems associated with the Align option could be solved, but it would require unconventional synchronization of many different systems such as cameras, GIS, GPS, and flight operation; whereas with the Avenger option, all these systems would come already integrated with one another.

 However, with the convenience of the integrated flight, GPS, and GIS systems, as well as other luxuries such as improved quality and performance in addition to high-tech camera systems, the Avenger by Leptron comes at a price. While the price of the Avenger may limit the utility company's ability to purchase more than one unit, the overall price of the system would still save the company money in the long run with the unit paying for itself after five or so uses (assuming $19500/nine-hour day for a conventional helicopter service).

Scenario 5:  

 

- 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.

According to the scenario above, the main problem is that the oil company does not know where the source of the leak is located on the Niger River Delta (fig. 8). Following is one method in which the leak could be determined in a cost effective and efficient manner from an unmanned aerial platform in order to prevent further damage to the delta environment as well as to the oil company's revenue.

 The proposed system will not only make locating the leak easy, but will also allow for the data obtained from the proposed monitoring system to be easily synchronized with geospatial systems. For instance, taking advantage of such geospatial programs such as GPS and ArcGIS in order to locate the leaky pipeline.

However, it should be noted that the following idea involving the use of tethered balloons to locate the source of the leaking oil on the Niger River are based solely upon the small amount of information provided by the oil company thus far. It may be determined that other, more effective unmanned aerial systems may be better suited to locate the oil leak after the following important questions are answered by the oil company:

1) How was the leak discovered?

2) What, if any, is the estimated cost of the leak in terms of its impact on the delta region and in terms of revenue lost to the oil company

3) What is the estimated area of interest (AOI) of the leak in both terms of size and geographic location?

4) What measures, if any, have already been undertaken to locate and stop the leak by the oil company

5) What, if any, has been the involvement of Nigerian government regarding the matter of the contamination of the Niger River delta

6) Has the oil company consulted with other authorities, such as environmental consulting firms, on the matter of contamination due to oil leaking into the Niger River delta?

Figure 8: The general area of interest in the Niger River delta on the west coast of the African continent. More information from the company whose oil pipeline is leaking will be needed in order to pinpoint the exact AOI in this region

  The first problem is that the location of the leaking pipe is unknown. In this case, an aerial surveillance system consisting of near infrared (NIR) cameras suspended from tethered balloons will be placed at various, predetermined locations on banks of the Niger River in order to take aerial photographs of the river's surface water. NIR cameras attached to each balloon platform would be periodically retrieved so that the spectral data collected by them could be computationally analyzed. From this spectral data it could then be determined whether or not a specific section of the Niger River corresponding to a particular balloon was contaminated with oil. Once a non-contaminated portion of the river was found, ground crews could then search between the balloon that exhibited no signs of an oil leak and the nearest balloon that did downstream of it; this is the area where the leak should be.

  In order to illustrate this procedure more clearly, figure 2 shows a series of balloons along the banks of a model river; numbers on the right-hand side of the image correspond to arbitrarily determined river-miles. Blue and grey shading corresponds to water that is uncontaminated and contaminated by oil, respectively, while arrows indicate the direction of water flow. So, for example, if the sensor on the balloon at river-mile 9 detects no contamination, but the balloon at river mile 7 does, then it could be reasoned that the leak in the pipeline is between river-miles 7 and 9 and ground crews could be dispatched to this area in an attempt to locate the leak.

 Figure 9:  illustrates how the source of oil contamination could be determined using a system of tethered balloons to monitor contamination in the AOI. Balloons in this diagram correspond to odd-numbered river miles. Each balloon will take a series of aerial photographs in NIR to locate surficial oil contamination on the river (grey areas). Once an area the river is found to be free of contamination (blue) using aerial surveillance, ground crews need only to search between that balloon and the nearest one exhibiting contamination downstream of it to find the source of the leak; in this example, between river miles 7 and 9.

 In order to determine whether or not the water in the Niger River is contaminated, the correct sensors must be attached to the tethered balloons. Figure 10 shows some of the spectra associated with oil slicks on water, as determined by the USGS during the 2010 Deepwater Horizon (DWH) oil spill in the Gulf of Mexico.

While the DWH spill was likely more massive than the one being examined in this article, the USGS found that  when viewed in infrared wavelengths, different thicknesses of oil slicks displayed different spectral signatures. Computational analysis could then be performed on the images collected by the sensors to determine whether or not the portion of the river corresponding to that particular sensor was contaminated or not.

Using the spectral information provided by the USGS, NIR cameras would likely be the best photographic method for determining whether or not the surface waters on the Niger River are contaminated with oil or not.

 Figure 11 shows an example of a near-infrared camera, from Edmund Optics, that could be suspended from a balloon platform in order to locate surficial oil contamination on the Niger River. While far from cheap at nearly $2000 apiece, this price likely pales in comparison to what the oil company is losing in revenue and mounting cleanup cost. 

Figure 10: An example of the spectra measured by the USGS during the Deepwater Horizon oil spill in 2010. It was found that when using NIR sensors, thin layers of oil could be spotted on the surface of the water; i.e. those less than 0.5 mm thick (blue line).

  Figure 11: One of the cheaper NIR cameras offered by Edmund Optics. This device, which weighs about 90 g and costs about $2000, could be suspended from the tethered balloon platforms in order to detect thin layers of surficial oil contamination on the Niger River delta

According to precipitation graphs for Lagos, Nigeria, which is approximately 200-300 miles away from the AOI on the Atlantic coast, weather should not inhibit the deployment of balloons except, maybe, in the months of May, June, and July, when rainfall exceeds 200 mm per month (fig. 5). However, if inclement weather were to occur on a day when the balloons were scheduled to collect data, their deployment could be easily rescheduled until a more meteorologically favorable day.

The cost of the balloons themselves is very minimal when compared to overall cost of the spill in terms of ecological damage and revenue lost. Offered by Balloons Direct, figure 6 shows an example of a weather balloon that could be used in this project. Each balloon costs about $35 and has a payload capacity of 3 pounds, which is more than enough to lift the 90 gram infrared sensor mentioned above in figure 4.

  In order to deter theft of the expensive NIR cameras, it would be beneficial to outfit each camera with a harness system that was easy to detach from its balloon monitoring platform. This detachable harness system would also be beneficial as the NIR cameras would need to be removed periodically anyway in order to download their images onto a computer for spectral analysis.

Balloons could be tethered to the ground using a rope or cable attached to either a hand operated or motorized winch. However, the balloons would likely not be very high off the ground (<20ft.) and a more expensive, motorized winch system would be more of a luxury than a necessity.

Figure 12: The average precipitation for each month in Lagos, Nigeria, located approximately 200-300 miles up the Atlantic coast from the Niger River delta. Based on rainfall averages projected here, the only problematic months for a balloon launch somewhere in the Niger River delta would be May, June, and July of any given year; that is, when the precipitation is greater than 200 mm per each  month (http://www.eldoradocountyweather.com/climate/africa/nigeria/Lagos.html).

 FIGURE 13: The cost-effective ($35) "Cloud Buster" weather balloon offered by balloons direct. Its 3-pound payload capacity would be more than adequate to lift the 90 g NIR camera shown in figure 4 (http://www.balloonsdirect.com/products/55-foot-cloudbuster-weather-balloon-orange).

While locating the oil leak on the Niger River Delta is no easy task, regardless of what method is used to determine its source, the use of tethered balloons outfitted with NIR-sensors would provide an efficient and cost effective manner of doing so given the information that was made available by the oil company thus far. 

Once the questions presented in the beginning of the article are answered, other, more effective measures may be recommended based on that information. For instance, if the size of the leak is large enough, the Nigerian government or an environmental consulting firm may be able to offer further assistance to the oil company in addition to our services.

 

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Clark, R.N., Swayze, G.A., et. al, 2010 , A method for qualitative mapping of thick oil spills using imaging spectroscopy: http://pubs.usgs.gov/of/2010/1101/ (accessed February 2014).

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http://www.eldoradocountyweather.com/climate/africa/nigeria/Lagos.html (accessed February

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Sanford, J., and Wykes, S, 2013, Study examines cost-effectiveness of helicopter transport of trauma victims: http://med.stanford.edu/ism/2013/april/helicopter.html (accessed February 2014).

Unknown. Unknown. UAV: fixed wing or rotary?. (n.d.). sUAS News. Retrieved February 16, 2014, from http://www.suasnews.com/2013/09/25214/uav-fixed-wing-or-rotary/

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