Sunday, February 23, 2014

Field Activity #4: Azimuth Survey

Introduction

Today new equipment is being developed at a high rate which is making old techniques near to obsolete, however when working in the field technology has a tendency to fail its user. Techniques get passed down from geographer to geographer and is invaluable when the fancy gadgets fail. While new technology makes the collection of spatial data much easier and time efficient it can also be plagued with flaws because it only understands what you give it and not the entire circumstance like the human mind does. The total cost for these new data collection equipment can be through the roof as well. Some equipment though can be considered as reliable and cost effective such as a compass or tape measure.

All things considered, it is necessary that geographers retain the knowledge and skills that can be derived by more basic tools and techniques. In the field activity that it described below the utilization of several tools was necessary to collect data to create a basic survey of objects in Eau Claire, WI. The tools used included a laser distance finder, tape measure, and TruPulse device. The tool that was used the most was the TruPulse because it could derive distance and azimuth which were paramount for this project. The device had several other functions and one that had been used by groups in the past included the height function which tells you the height of an object using trigonometry.

The goal of this lab was to survey several objects in the field by gathering their species/attributes, azimuth degrees and distance from base points. The next goal included getting GPS points for the data which would allow each group to put their data into ArcGIS where they could be mapped and analyzed for accuracy. The major goal of this lab was to  use several techniques of surveying in order to gain a broader understanding of the differing ways to do it.

Study Area

The study area of our group was located on upper campus and specifically located around Governors Hall. The points chosen from where the survey was taken place were all located at location where many objects of varying attributes could be located. The group utilized three different points to survey the region. Some different types of attributes that were surveyed included trees (oak and pine), snowmen, snow piles, cars, signs, etc. Image 1 below shows the Area of Interest of the group with the yellow dots representing the points that were surveyed.
Image 1: The image above shows a zoomed portion of the University of Wisconsin - Eau Claire's campus. The dots reflect our points that we survey which will be covered further in the sections below.
The study area as seen in the above image isn't currently cleared so the surface is much more obscured due to the snow cover. However the snow did help to create new features on the landscape including snow forts, snow mounds and snowmen. In image 2 below it is apparent just how deep the snow actually is. This deep snow made the survey much more difficult to traverse.
Image 2: This image shows myself, Cody Kroening, in the snow on the day of the survey. The snow was often up to my knee and sometimes above in the drifted zones. The temperatures were also below zero, which was the first time it had been that low during the day in about a week.
Magnetic Declination Web Service

Magnetic declination, or the angle between magnetic north and true north, is a tool that can be utilized when calculating variables such azimuth. Another important note to make is that declination values east of true north are positive while west values are negative. Magnetic declination isn't a solidified value and actually will change over time. Click here to learn more about declination and calculating it in your city.
Image 3: The image above shows the site where longitude and latitude values can be typed in to calculated the declination in your city. There are several other variables that can be typed in to calculate declination.
Image 4: The image shows a PDF copy of what is created from image 3 above. The declination is calculated and given given to the person desiring the data. The declination is used for calculating azimuth data which is important to this field activity.

TruPulse 360 Rangefinder

The TruPulse line of rangefinders come in several different levels, however our department owns the specific model 360. The 360 contains a compass within its core which allows for azimuth readings, which was perfect for the survey project. The 360 also gives distance values, height values, inclination and much more. This device was used in the survey through its distance value and state of the art azimuth data. These values, when combined with GPS values, can be mapped in software packages such as ArcGIS. The device is simply pointed at an object where it then uses its laser system to take measurements. These measurements are then presented to the user on the screen. To learn more about TruPulse devices here.
Image  5: The image above shows the Geography department's TruPulse 360 model. This device is described thoroughly above. Not only does this device work out in the dry western states but also works in below zero temperatures in desolate Wisconsin.

Methods

Several methods were utilized using several different techniques to retrieve the final results for the group. All of these methods were compiled and normalized in order to map them. After the points were mapped they were compared with a base map to check for accuracy.
Image 6: The above image shows some of the snowmen that were recorded during the surveying process along with one of the large piles of snow that found its way into our entries as well.

The initial step in the surveying process began with picking a location and time to survey. Our group chose to survey on Friday, February 21st after the big snow storm, which turned out to be a bad idea since the snow was incredibly deep. The amount snow that Eau Claire received over the weekend actually allowed students to create large snowmen that can be observed in image 6 above. We then chose to do our survey around Governors Hall, which also happens to be the hall that I am a Resident Assistant in. Our first location was against the back fence behind the building. The second location was on the other side of the building near the "smokers picnic table." The final surveying point was at the front door of Governors Hall. Some of the surveyed points contained snow forts and trees much like in image 7 below. The technique that we used with the TruPulse included one of us using the device to tell the azimuth and distance to the recorder. The recorder would then put the distance, azimuth, and feature type into the field notebook which can be seen in image 8 below. The process of surveying over 100 points took just over an hour in total.
Image 7: The above images show both one of the pine trees and snow forts that we surveyed in our field activity. This fort was assembled the night of the snow storm from last night. 
Image 8: This image shows the method of data collection by the recorder. We included columns for distance, azimuth and the type of feature that we were recording.
The next phase of the project was to find the location of each point in decimal degrees through the use of bing maps. After the locations latitude and longitude were found then were then recorded into the excel file as x and y coordinates. The data can be see presented below in image 9. As can be seen in the image, the feature along with its number, azimuth, distance and attribute were all recorded in order to get an accurate survey of the desired location. Before the table could be put into arc for analysis a geodatabase had to be created. This was done by using ArcCatalog. In the catalog I followed the folder connection file to my folder where I then right clicked and selected new. From new I was able to create a new file geodatabase. This database was used for the entire exercise and contained all of the data that I would need to compute my results.
Image 9: This image shows the normalized table results with the latitude and longitude data. The table was then transferred into ArcGIS where it could be created into point data for easy transposition onto a base map.
The next step in the analysis of the data included bringing the table from excel into ArcMap where it could be made into point data by utilizing the "Bearing Distance to Line Command" located in ArcToolbox. This tool uses your data to create a brand new feature class that includes a bearing field, x and y coordinates, and a distance field. The output feature class has several lines which extend from a focal point. The focal point is the place where the data was recorded while the end of each line represents a feature that was used in the survey. The final step in the creation of the images was to use the "Feature Vertices to Points Command" which takes vertices of input features and makes output points in the dataset.
Image 10: The above image shows the output feature class that is produced via the "Bearing Distance to Line Command." The ends of the orange lines, which will have points attached to them in the images below, represent features in the survey.

Results

As can be seen in image 11 below if your GPS points are even slightly off then the whole image could be potentially compromised. Our data turned out fairly well and we seemed to only be a few meters off from the actual objects. When looking at image 11 it is apparent that some of the azimuths could have been slightly skewed since some objects are being placed on the buildings. We did utilize three of the doors to the building as features, but we also had a few stray signs converging upon the Governors Hall walls.
Image 11: This image shows the results of the "Feature Vertices to Point Command." Each yellow points represents a feature in the survey. Many of the points were near to perfect or only a meter off, but a few converged with the building, which was not actually where they were located.

Discussion

I think that your survey went very well despite the weather conditions that we had to face. I do think that the weather may have caused some of the azimuth values to vary because of how cold it was. I was in charge of taking most of the points using the TruPulse device and I would be lying if I said that I wasn't shaking slightly from the cold. Along with that, it was tough to stay in exactly the same spot when spinning around taking all of the points. On several occasions I found myself slipping further into the snow and even falling when trying to spin like a top to get more points. The snow was well above my knees at several locations which made it hard to stand still since my pants were freezing to my legs. It is essential to try to not move from your point so you can get accurate azimuth data so standing in the snow is something that I would avoid if I were to try this field activity again.

Another portion of the lab that made it difficult was trying to get the best possible position for each of the points without losing any integrity from the data. As can be seen in images 1, 10 and 11 above the points were slightly skewed and I would mainly blame this on inaccurate GPS locations.

Overall I would highly recommend this surveying method because if you don't have a surveying station near by, but you do have the right equipment then this strategy can be efficient and accurate down to a meter or so.

Conclusion

When all is said and done, I would have to say that I really enjoyed this lab even though I had to trudge through knee high snow to get it done. I was able to learn about azimuth and how to accurately survey using many different tools. All of the tools that were presented to us are powerful in their own right as surveying instruments and could potentially be my tools of the trade once I graduate. I hope to learn more about working in the field over the rest of the semester since each lab so far has given me valuable skills in the real world and job market.

Sunday, February 16, 2014

Field Activity #3: UAS

Introduction
This section of field and lab work surrounds the use of unmanned aerial systems (UAS). UAS surrounds the use of unmanned aerial vehicles (UAV) to perform tasks that would otherwise be unaccessable or dangerous for humans to do. These vehicles often carry a sensor or camera in order to gather data to assess a problem. Companies can purchase UAS devices for their own services or can purchase the abilities of an outside resource to gather the data for them.
UAS: Unmanned aerial systems (UAS) consist of any device that doesn't carry a human passenger to fly it while in air. These devices are fantastic at collecting remotely sensed data, images, and video. They can range from large plane-sized machines to RC devices. Balloons, kites and rockets can even be considered unmanned aerial vehicles (UAV).
The task presented to the groups was to create UAS mission plans. Different groups came up with different routes/proposals for plausible employers. The scenarios listed below describe the efforts that Cody Kroening, Blake Johnson and April Leistikow.

Scenarios
Scenario #1
Subject: A proposal to use Unmanned Aerial Systems to monitor the military testing range for the presence of desert tortoises.

Purpose: The problem is that the military’s ability to engage in conducting its training exercises at the military testing range are being hindered by the presence of desert tortoises. It is necessary for the military to be able to use their testing range without any disturbances.

I suggest that we use Unmanned Aerial Systems with a mounted sensor to monitor the testing range for the presence of desert tortoises so that the military will be able to conduct their training exercises without any disturbances.
Image 1: The above image shows a desert tortoise and his burrowed out home. As described throughout this scenario these tortoises prevent military training exercises to be performed. They tend to burrow into the ground near moist places in the desert. 
Questions: There are several questions that we would need answered in order to accurately propose a form of aerial surveying.

The first question is, how big is the study area? This is a very important question because different UAS (Unmanned Aerial System) devices have different flight times. For example, a gas powered UAS has a much longer flight time than an electric one. But electric is much more cost and eco-friendly, so if the area were smaller the preferred route would be to use an electric powered UAS. The problem with the area that needs to be covered should be apparent now.

The second question is, is there a budget? The cost of UAS systems can vary significantly. Something such as a fixed wing copter can cost thousands of dollars. While it definitely has its advantages, if there is a low budget for the project this option would be out of the question. For lower budget projects there are options like a balloon or a kite that a sensor could be mounted to. These types of UAS devices can be as cheap as a hundred dollars. Another good thing about more primitive methods is that there is the option of building your own device. For every UAS there needs to a mount in order to attach the sensor to the UAS. Building your own is one way to cut down on the cost of your project. And if you mount your sensor to something like a kite or a balloon, the only significant cost would be the sensor itself.
In the description of this scenario it was stated that the military currently spends millions of dollars to rid their training facility of the tortoises, so I think it can be assumed that there is a fairly large budget for this project.

Possible Solutions: Because the questions above are something that cannot really be answered through this exercise, I will be presenting you with three different solutions to the tortoise problem. Before I can do this, there needs to be a base knowledge of the desert tortoise.

The desert tortoise is a large herbivore that inhabits the Mojave and Sonoran deserts in the southwestern portion of America. The desert tortoise’s habitat is classified as follows; semi-arid grasslands, gravely desert washes, canyon bottoms, and rocky hillsides. Tortoises can be found near water and prefer drier soils for their burrows.

The desert tortoise is able to live where ground temperatures may exceed 140 degrees F because of its ability to dig underground burrows to escape the heat. With this information about the desert tortoise we can conclude that within the area that needs to be surveyed, areas that contain water should be the first places to be surveyed. Also focusing on the soils that are being surveyed can be useful too. With remote sensing, drier soils have a higher reflectance. Once the survey is completed, the image can be studied, and where the soils are much brighter on the image shows the type of soil the desert tortoise prefers. Now if there is this soil with a high reflectance near water, that is where the tortoises are most likely going to be located.

** Attached to all of the UAS devices in each of our solutions would be a short-wave infrared sensor. This would enable us to see where the moisture content is in the soils. As it was explained before, the tortoises are going to be located in drier soils that are near water. With this sensor we would be able to see where the areas are that have that high reflectance (Drier soils) and find the drier soils that are closer to water sources.

Solution 1: With the assumption that the area of study is large, we propose the use of a fixed wing, gas powered, UAS copter. The fixed wing copter can cover a larger area than a multi-armed copter would be able to. Think of the fixed wing as a plane and the multi-armed as a helicopter. To cover a larger area you would want to use a plane rather than a helicopter. The choice of using gas power over electric came down to two factors. First, the gas powered can run for longer periods of time, thus covering more area without having to come back and be re-powered. The second factor is the gas power may be more expensive than electric, but this budget for this project seems to be so large that the cost for the gas would be irrelevant.

Solution 2: Using a fixed wing, electric powered, UAS copter is the second solution to the problem. If the military wishes to take a more “green “approach to solving this problem, electric would be the way to go. It would be cheaper and better for the environment by now using up so much gasoline. The only problem with this method is that electric powered copters have a substantially shorter flight time. While gas powered copters can fly for about 10 hours straight, the electric can go for about an hour on a calm day. Depending on how large the area is, the electric powered copter would need to continuously keep returning to the base to be re-charged. This would increase the time it would take to survey the area of study.

Solution 3: Using a weather balloon or a kite in the third and final solution. This would be used if the area of study is smaller than we presumed and the initiative for this project is to go as “green” as possible. This solution would use no power source, so the only real cost would be to purchase the UAS equipment (or to make it yourself). The idea behind these is the sensor would be mounted to either the balloon or the kite and raised up into the sky to take aerial imagery. This method would not produce as good of images and may hinder the surveying process.
  
Conclusion: In conclusion, I think purchasing one of the UAS devices mentioned about to take aerial imagery of the desires area of study would give you your most efficient way to locate the tortoise burrows. It would be much more cost effective than manually surveying the land for burrows. Depending on the route you wish to take for this project, one of the three methods mentioned above will be your best bet for effectively completing the project and giving you quality data as to conduct your research.

Scenario #2
Subject: To the power line company that is seeking to lessen their expenses by moving away from the use of helicopters.

Purpose: The issue in this scenario revolves around creating a more efficient way to spend money on verifying problems power line towers. The key to solving this issue is to find a cheaper means of collecting data while also keeping maneuverability.
Image 2: This image shows a power line tower as described in the scenario above. These towers will often require maintenance and in this case the company needs a more cost efficient system to get good images of possibly damaged material on these towers.
Questions: Several questions need to be addressed in order to get the best view of how to help this company. Knowing the answers to these questions can aid someone quite a bit since they are relevant to costs on a wide margin.

What’s the budget? This question is essential when deliberating on purchasing an unmanned vehicle because the costs can reach very high amounts. A budget can either make or break what a consulting company would suggest.
 Is this cost a preventative issue/occurring often? Knowing whether these costs are continuous or not would help in knowing how much of a return that the power line company is actually receiving by purchasing a UAV.
 How big of an area are they covering/effecting? I would consider this questions paramount in knowing how many devices that need to be bought and also how many new employees need to be trained to fly these devices.
City wide or country or even state wide? This goes back to the above question and knowing how large of a region that we are dealing with. The area helps to understand exactly what needs to be purchased.
How often does monitoring occur? This questions is a bit less prominent, but still important because it will show whether or not spending the extra money on higher quality items is worth the price.
How do you know if there is a problem? Finding out how to see a problem is important because it determines the precision in which the camera needs to be and the maneuverability of the UAV.
Solutions: At the moment it would appear that the power company is being charged far too much for the services of a helicopter crew. These costs could be diminished significantly by utilizing unmanned aerial systems ranging from fixed wing devices to multi-armed copters. The costs per year could be redirected and lessened by owning a device. The initial cost would be higher, but the only costs afterwards are for maintenance and gas.

In the case of this power line issue it would be most advisable to purchase a multi-armed craft because of its maneuverability. The multi-armed copters are used to move and turn on a dime. They don’t have a long fly life time though, but they will be able to get the best image if the company is trying to get an accurate image of an area that needs to be fixed.

Helicopter rental costs are incredibly high and being able to find a helicopter near these towers could also be difficult. The power line company would save thousands of dollars by owning their own multi-armed copter because of the non-recurring costs other than gas and maintenance.

Another aspect to consider though with piloting a multi-armed copter is the danger that comes with it. These devices, piloted by inexperienced or reckless people, can cause death because of how the blades of the copters work. This could be a potential danger when coming close to power lines, however it also the best device to have for versatility. When looking at the dangers any company using the services of a helicopter must also consider the dangers of having employees lean out of the copter to take pictures.

Other plausible options that would be cheaper include, a kite with a camera attached to it, a weather balloon with a camera attached to it, and a fixed wing copter. There are a few issues with each of these other options, but they all have the potential of being less expensive. A kite could potentially not work if it got caught up in the lines and potentially ruin the cameras too. The weather balloon probably couldn’t get the image that we needed to see a problem with the tower. The fixed wing copter is also a great option, however it won’t have the same maneuverability as the multi-armed copter.

Scenario #3 
Subject: To the oil pipeline company who has sprung a leak in the Niger River delta in regards to finding the leak and containing its damage in the area.

Purpose: The inability of this oil company to obtain an accurate depiction of where this leak is has brought them in the needs of an outside resource. They are most likely losing money from this leak and are also doing an incredible amount of harm to the ecosystem that is already being ravaged by pollution.

The oil company needs quick and efficient results. Their company and local farmers are both losing a profit/livelihood.
Image 3: This image shows the Niger River delta. The scenario above describes an oil companies misfortune in springing a leak in their pipe that travels through the delta. As described below, the delta is over 50,000 square kilometers and contains hundreds of species of fish. This issue needs a quick fix in order to save the ecosystem.
Questions: The questions below are very essential in attempting to answer the overall problem of how to find this leak and contain it.

What is the budget? Budget is always really important because it determines the equipment that can be purchased.

Where is it leaking? Knowing where the leaking is occurring can help to contain it and fix the issue. Knowing where the pipe is leaking will solve the entire problem.

What are the signs of the leaking? Knowing what the signs of a leaking pipe are important to fixing this problem because it will give the analyst a better idea of what to look for when perusing the data.

How polluted is the river already? Knowing the amount of pollution in the river delta currently can give the company an idea of how badly this leak has impacted the ecosystem.

How large is the study area/delta? This question is answered through leg work near the end of the report.

Where does the pipeline run through the delta? The pipeline’s location can help in finding the leak as well during analysis because the analysts can focus on certain regions for specific occurrences that are associated with leaking.

How fast is it leaking? If the amount of leaking can be tracked then the company can have a better idea of how the oil is affecting the aquatic and land vegetation’s.

Solutions: It would appear that the greatest need for this oil company is stop the leak so as to not lose any more of their potential profit. The surrounding community is in great need for this leak to get fixed as well since the oil is spilling into their water resource. I would place this issue at high demand since it is affecting the lives and wellbeing of those that live near the Niger river delta. Fortunately for these people it is in the best interest of our client to also find and fix this leak in the pipeline. There are several ways to quickly and efficiently solve this problem and future issues along the pipeline as well.

Some background information about the Niger River delta is important in understanding just how to best go about giving a valid solution to this problem. For instance, the delta is 53,000 square kilometers and the river itself is a natural source of irrigation, drinking water and bathing source for both people and animals. There are over 200 different species of fish living within the delta and it is considered a crossroads for two differing habitats of fish. While the river is already very polluted by human contact, the entrance of oil directly into the delta is bad for both aquatic life and the livelihood of farmers.

Several options were discussed by a team of professionals and two main options were devised with the addition of several others depending on the oil company’s needs. The top two ideas that were created were a weather balloon with a camera attached to it for cost efficiency or a multi-armed rotary copter for maneuverability efficiency. A weather balloon would be a low cost item to attach a camera to in order to find the source of the leak. The only real issue with a balloon is the ability to control it if you do find a region of leak.

The other option of either a fixed wing or multi-armed copter could also work. The device itself would cost a lot more money but the ability to maneuver would be paramount in the search for the leaking pipe. There are two types of models to consider: a gas powered copter used for long time lapses or an electric for cost, but less air time. Both of these machines provide a higher source of maneuverability than a balloon but will be much more expensive. When all is said and done, a budget would grant the team a better clue at how much would be viable to spend on the mission.

Depending on whether or not the company wants to do additional research on the affects that this leak made on their surroundings a sensor would be suggested in order to do research on the health of the vegetation in the region. This could also be important for future research as well since they could track the health of the vegetation around the pipelines. A sensor would be needed to add to one of the devices, most likely a copter.

Some additional options to consider include the use of a rocket with a camera attached and maybe even the use of a kite. A rocket could be a fun venture for the company but it could be a boom or bust situation, which seems like a bad idea since the spill could be affecting both animals and people. The other option of a kite could be a failure as well if there is no wind present or if the area to search is too large, which in this case, it most likely is.

Scenario #4
Initial Problem: 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.
Image 4: The image above shows a pineapple farm. The scenario calls for a way to tell if vegetation is healthy or not and when the best time to harvest is. As outlined below by April Leistikow, they needed infrared sensors in order to see the plans health.
Questions to Consider: The initial question is always the budget.  More accurate information can be acquired based on how much you want to spend.  If the budget allows, the plantation could purchase its own unmanned aerial system to fly over the land that the pineapples are planted on to obtain how healthy the crops are doing.  A better sensor could be purchased to get more precise information about the pineapple plants.

The way that the company farms the pineapples is important too.  The type of harvesting and when they are harvesting could have an impact on how well the plants do.  It is important to consider if irrigation is being used to water the plants, and what kind.  The type of soil that the pineapples are planted in could also affect their growth, because pineapples prefer light soils, but the use of pesticides and mulch may also have an impact on the fruits’ growth.  All of these factors could contribute to the output of quantity and quality of pineapple.

A few different options should be considered when trying to see at a glance how healthy the pineapple crop is doing.  The following solutions are ordered from the least costly solution to the solution with the highest cost.

Solutions:
Option One
A hyperspectral sensor using the infrared band can be put on a weather balloon.  The infrared band is best for researching vegetation health.  The healthier the plants are, the brighter the red color will appear in the imagery.  The use of the balloon could save a lot of money.  They can travel fairly high in order to scope out the entirety of the plantation area and it can give a good idea of what is going on in the area in a short amount of time without having to search through a lot work.  This method is also extremely low on energy use.
           
Option Two
The infrared band in a hyperspectral sensor is still the best option for sensors to see how healthy vegetation is.  An electric powered fixed wing copter may be a good option to get more accurate data compared to the balloon.  Running on electric power copter is a cheaper option than a gas powered copter.  The flight time would not be as long, but it may be more cost effective for the company to bring it down and charge it if the copter cannot survey the area in one flight.

Option Three
The same kind of hyperspectral sensor with the infrared band should still be used, but for this option, a gas powered fixed wing copter could be used to scan the pineapple crops.  This way, the copter could be in the air longer and get more detailed information about the plants. Since the craft is able to stay in the air longer, it could fly closer to the ground and get more accurate information about the pineapples’ health conditions.

Scenario #5
Initial Problem: 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.
Image 5: This image shows a pit mine, much like the one that could be described in the scenario above. The company wants to know how much earth that they are removing from their mine on a weekly basis and LIDAR would be the best way to do this, however they don't have the funds.
Questions to Consider: The most important question is to ask what the budget is for the mining company.  The company could get better information about the volume extracted from their mine depending on methods used to collect data.  The economy has a large impact on whether or not the mine can even be active, so surveying methods costs need to be low.

One factor that could hinder a volume calculation is if the mine is continuously productive or if they have periods of time when productivity is stagnant.  An accurate reading cannot be given for a distinct period of time if the mine is not constantly producing resources.  It is also important to consider what kind of mine it is and how large the mining area is.

Some options should be weighted when considering how much the mine is extracting from the land.The following solutions to this question are listed from least to highest cost.

Solutions:
Option One
A kite could be flown over the mine with cheap imaging sensors.  This would be the most cost efficient option because the area of interest is not very large and the materials for a kite are very cheap.  Point cloud software based sensors could be used on the kite.  The software collects survey points and creates 3D surfaces by connecting the points.  Ground control points would assist in accuracy and keeping low costs at the same time.

Option Two
The mining company can use other cheaper software and sensors that create 3D point clouds.  These kinds of sensors can be put on any kind of aircraft.  To save money, it may be wise to use an electric powered fixed wing aircraft to fly over the mine rather than a rotary craft.  That way, you can fly the craft over strips of land one section at a time.  Flying the craft parallel to the strip of land that was previously scanned will allow the sensors to collect sets of data from the same point on the terrain.  True x, y, and z data can be interpolated from this parallax of a single point from different aerial angles.  Using an electric powered craft is a cheaper option than a gas powered one.  It does not have as long of a flight time, but probably would not need to be very long because the mine pits do not extend over a very large amount of area.

Option Three
If it is possible to get more funding, it would be worth getting access to LIDAR data for the area of the mine.  This could also be accessible through county data if they could have access to it.  They would need to sort through the tiles of the county LIDAR data to find where their mine land would be.  This process may be monetarily costly as well as costly with time, but it would be worth having this kind of data.  LIDAR data can be processed in ArcGIS to estimate where the land surface once was and run a model to see how much land mass has been removed from the mine pit. 

Image 6: This image shows the popular camera brand GoPro.
These devices are becoming much more prominent in the UAS
 world since the price of these devices and their connectivity
with iPhones are reasonable.

Image 7: The image above shows a multi-armed rotary
copter device. There is also a sensor attached to its
base which is used to detect phenomena when
in the air. These devices are used for their
precision and maneuverability.

Costs
One of the many options that were listed above contained multi-armed rotary copters that run on gas or electricity. These devices range from $700 to over $1,400. http://store.3drobotics.com/products/3dr-rtf-x8-2014.  The first UAS method mentioned was a fixed wing, gas powered copter. This type of UAS will cost you about $7,000. http://www.robotshop.com/en/cropcam-unmanned-aerial-vehicle-uav.html. The second UAS method mentioned was a fixed wing, electric powered copter. This type of UAS will run you about $1000. http://store.3drobotics.com/products/3DR-ARF-APM:Plane. The third UAS method mentioned was using either a balloon or a kite. A kite would cost you a little over one hundred dollars, while a balloon would cost you about $300. http://www.kapshop.com/Lifters-Balloons-&-Blimps/c75_32/p99/Balloon-150/product_info.html. These are without the sensors, and depending on how sophisticated of a sensor you attach to your device, it could cost you anywhere from $50 to $5000.

Conclusion
This field activity was much different than the first two. Our actual work was to do massive amounts of research into the field of unmanned aerial systems and mission planning. Each scenario described above had its own mission plan that it needed to get done. They each also had their own requirements and budgets. This activity really spurred the imagination and critical thinking abilities of the group. Not only did we have to get background information on each of the issues, but it was also necessary to look at specific devices to suggest to each client. The importance of meeting their needs along with giving other options was paramount in creating a good outline for a possible employer.

Sunday, February 9, 2014

Field Activity #2: Visualizing Terrain Survey

Introduction

In this second portion of the terrain model activity the goal was to use ArcGIS in order to create a model of the data that we collected in the landscape field activity. The purpose of this activity was to go over our sampling scheme, see if additional points needed to be collected and resurvey those areas where needed. This labs goal was to create a 3D model of our landscape in order to showcase ArcGIS skills along with field methods.

Methods

In order to create a model of the landscapes the data that was initially collected needed to be imported into ArcGIS. This is done by converting the Excel spreadsheet into a dbf file format which works well with Arc. Once in Arc the user simply imports the dbf file into Arc as an xy file with z coordinates as well. These were then exported as a shapefile so they could be interpoled for spatial analysis.

Image 1: X, Y and Z values from Field Activity #1. The grid data was placed into a field notebook then transferred over to Microsoft Excel later, however as the project went on the group decided to place some of the points directly into a laptop for convenience sake.
This data then needed to be interpolated in order to get a continuous surface. The five interpolation methods that we utilized to create those surfaces included: IDW, Natural Neighbors, Kiging, Spline and TIN. Each of these methodologies use different ways to project your data to a surface model. They each have their own advantages and disadvantages. All of these methods can be found using the help portion of the Arc Toolbox and are easily accessible.

The IDW method uses weighted combination sets of sample points in torder to generate cell values. Points must be very dense in this method so as to consume the variation of the surface. The weight that is assigned to each point is a function of the output cell location. Because of this the greater the distance that a point is the less influence a cell has on it.
Image 2: This image shows the IDW output. The data is somewhat choppy and rigid. The edges of each elevation is frayed out and rather inaccurate compared to the real landscape. 
Natural Neighbor also uses the weighted method to interpolate the points. It can be used for both interpolation or extrapolation. It is best used with scattered points that are also clustered in groups. IDW and Natural Neighbor are very similar in their equation. Local coordinates will define how much influence scattered points have on a cell.
Image 3: The above image is the output of performing the natural neighbors interpolation method. This method is smoother than the IDW method, but is still rigid at perceived edges in the data. This image shows a fairly accurate description of the landscape.
Kriging on the other hand assumes that points distance and direction reflect correlation. It is best used when there is bias in direction or distance in the data. It uses very sophisticated interpolation abilities to calculate weighted averages.
Image 4: This image is the product of the Kriging interpolation method. This method appears to do a good job of portraying highs and rounded portions of data, but is still lacking a smooth transition that the group wanted to obtain to best describe our snow landscape.
Spline is used to estimate values using mathematical fuctions. It attempts to create a very smooth surface that passes through each point. It has been said that the spline method is like bending rubber through each point to get a smooth surface.

Finally, a TIN is known for its ability to accomodate unevenly spaced elevation points. A TIN uses irregular triangles to connect points to create models of elevation.

After all of these methods were brought into Arc and altered to best fit the data they were then imported in Arc Scene where data is modified into a 3D version. Some of the methods did a better job than others at creating a surface model of our original landscape. The image below is a reminder of what the actual surface looked like.

Image 5: The final product of our landscape building. Areas of interest on the image above include a small hill at the top right of the image, a mountain/volcano at the center, a plain at the top left, a valley just in front of the mountain, a depression atop the mountain and a ridge near the bottom.

Image 6: The results of the Spline. The best method in my opinion. The original landscape can be seen in image 1 above. The spline method creates a very smooth graphic, which does a great job of portraying the original landscape. The only thing that I noticed was that the digital image appears to be inverted.
In my opinion the spline interpolation method was the best at creating an accurate model of our original landscape. Image 6 above shows the results of the spline method when imported into Arc Scene. Another method that did a good job at giving accurate elevation details was the TIN. The TIN image can be seen below in Image 7.
Image 7: TIN model of the original data from Field activity #1. This TIN image compared to the spline (image 2) above is much more chopping, however does justice to the differing heights of the model. The color scheme seems to stretch better and portray elevation.
When our group revisited our data and box, it had already snowed on our box and ruined any chance of us getting more data where it may have been lacking. While a resurvey could have been justifiably used, I believe that our 5 cm x 5 cm grid data did a superb job of recreating our final results. In essence our group decided that resampling and attempting to gather more data would have been near to impossible. I would suggest that future students try to accomplish the whole assignment in a days time to avoid the snow issue.

When all is said and done, our model came out very clean and accurate of our original terrain model. The spline is probably the most appealing because of its smoothness.

Discussion

I thoroughly enjoyed using Arc GIS and Scene in order to create the terrain models because of the ability to compare the digital image to the original creation. Being able to see a physical landscape in a 3D environment is incredible and could definitely be a valuable tool to model actual regions.

It would have been nice to revisit our landscape to see if we wanted to add additional points, but the weather really put a halt to that. None the less, I believe that our data came out much better than I would have expected. I would say that the group's ambition worked out quite well. As a group it was hard to find a time that worked for everyone and more often than not not all of us were able to attend each group meeting. When everyone was together we were able to work as an efficient team that also was able to joke around.

As I put it in the last blog, I wish we could have come up with a better method to take our elevation, but it seemed to all work out in the end. Higher accuracy in our measurements would have been nice for the perfectionist in me, but our models worked better than expected.

Conclusion

This activity taught me many things about field work. For one, ambition can kill you when it comes to data collection and accuracy. If we were to have a flaw though I would want it to be excessive ambition because it shows that we are truly trying to make the best quality work that we can.

I also learned that having more tools in the field are better than less. Its best to be overprepared. Also that delegation is incredibly important to efficiency in a group environment.

Finally, the Arc GIS and Scene portions of the lab were very helpful in creating surface models and showcasing those results. Some group members were able to learn more than others about the scene portion of the activity. Arc is an incredibly helpful and powerful tool in the Geography world so it is great that the course is already implementing it. I'm excited to see what other new tools and processes that we will be introduced to.

Field Activity #1: Creating a Digital Elevation Surface Model

Introduction

The first adaption of a multipart course, this activity was designed to endow students with some basic skills of thinking in a geospatial reference. The task was relatively open in its instructions other than being tasked to create a landscape in a sand box. Some requirements for this landscape included having a ridge, hill, depression, valley and plain to create a more advanced model. Having only suggestions from previous students from the course via their blogs each group had to come up with their own method of measuring their landscape.

Methods

Several methods really could have been used to measure the landscapes that were created. Some groups chose to use intricate grids of yarn, however Group 3 (my group) chose a loftier goal. Each group was given a sand box with an area of 1.10 x 2.35 meters. Our group used the top of the sand box as our base layer of 0 cm. The landscape parameters were then met by piling more snow onto or removing from the initial base layer. Contrast was a goal that all of the groups attempted to meet in order to get a better digital elevation model. The requirements for the landscape again were:

-Ridge
-Hill
-Depression
-Valley
-Plain

Image 1: Bottom left: Hill. At the top of the volcano there is a Depression. A valley can be seen dipping down on the back of the volcano. A ridge is found at the back of the box rising up out of the valley. The plain spans the area at the bottom right of the screen.
As can be seen in Image 1 above the group met all of the expections for the assignment with the addition of a volcano where our depression sits at the top of as a caldera. Because of the massive spectrum that was dealt with it was difficult to record the data. In hind site the group should have decided to dig down to the dirt and use the grid method of measurement. In the next lab though the data may prove otherwise.

As a group we were very ambitious in our measuring methods as well. We used a 5 cm x 5  cm grid to get our x, y and z data. As the day went on and the cold really set in we all started to regret many decisions, but the data was fairly precise and many points were obtained. The biggest hope was that the model would be very exagerated so as to give us the best results possible for elevation.

Image 2: Measuring the Volcano. This process included the use of yard sticks to get flat edge measurements in each cell of our grid at each elevation. The yard stick in my hand (red coat) was placed at the base level while Jeremy's (green jacket) was measured up along the base stick then moved out to each grid for elevation measurements.

The next big step was to create some sort of grid to measure the elevation. We used a piece of yarn to make slight impressions every 5 cm in the snow to create a grid across the snow. As can be seen in image 2 above we used yard sticks to get the elevation (z) values from the base level (0 cm). The major issue with measuring the data was when trying to measure elevation because we would sometimes have to stick the yard stick into the snow to an estimated 0 cm point. This was rather inaccurate at times which once again pointed to the fact that we were most likely too ambitious as a group.


Image 3: Above is an image of the landscape from above once again showing how ambitious the group was.  The large mountain in the middle was created initially, then the depression (caldera) was dug out at the top. The mountain then became a volcano. Our group chose to do this so as to set ourselves apart.
We used two different methods that led to the same result in order to record the data. At first a field notebook was used to write down the x, y and z values (Image 4). These values then were transposed into Microsoft's Excel. The second method that was used included putting the data straight into an Excel spreadsheet with the use of a laptop. The laptop made recording our data much easier and efficient.

Image 4: Field Notebook containing grid data. The x and y points were initially written down as we created our grid system. Our z points (elevation) were then added as we measured each cell. We later utilized a computer to input our data, but were forced to manually add those that were already in the notebook.
Once the data collection portion of the project was finished the group compiled all of the data into one Excel spreadsheet that could be used in ArcGIS.

Looking back on how we collected our data, I think that the group would agree that the landscape should have been dug down below the 0 cm base level to get easier and better measurements for the elevation data.

Discussion

I had a great time doing this project, specifically creating the landscape, however we, as a group, had our flaws as well. I am very excited to see the models that we will create with of our data because of the great elevation differences that were created.

One of our biggest issues was being able to measure the elevation, or z values, because of the incredible height and depth of our model. I do feel though that we got some of our best measurements on the most difficult parts of the project. The grid system using yarn seemed to work best among the other groups, which would have decreased the amount of time that we spent outside as well. In the end ambition was our biggest enemy, but when all is said and done I think that that's the best kind of enemy to have.

In brighter news, I think that our use of a 5 cm grid format will give us the best data possible. While it was tedious, it should give us the best results when it comes to creating an elevation model. We all really worked well as a team too and were able to have fun during the project.

Conclusion

At the end of the day, we had a few take aways from this assignment. If this project were to replicated I would suggest using the yarn grid system, but also stay as ambitious to get the most exageration possible. Another note to be taken would be to start off taking the data with a laptop so that the group wouldn't have to sit and take over an hour to transpose the notes onto a computer. The data should create a great model since we were rather tedious with our use of measurements in small spaces.