UAS Data Processing with Pix4D

Introduction:

Pix4D is an incredible program that allows the user to to convert aerial images taken by unmanned aerial surveillance vehicles into georeferenced 2D, and 3D surface models, point clouds, DEM, orthomosaics, and many more options.  It has many uses which include being used in agriculture, the mining industry, construction, and almost any other place as well. This program can create amazing models if done with the correct accuracy.

Pix4D Questions:

• What is the overlap needed for Pix4D to process imagery?

The recommended overlap for the user is at least 75% front lap and 60% sidelap.

• What if the user is flying over sand/snow, or uniform fields?

In an area with sand/snow 85% frontlap and 70% sidelap is needed.

• What is Rapid Check?

It is a quick processing that creates a visual surface of the area, but it will have a low resolution.  

• Can Pix4D process multiple flights? What does the pilot need to maintain if so?

Pix4D can process multiple flights and the pilot only needs to maintain the same vertical and horizontal coordinate system throughout the multiple flights. 

• Can Pix4D process oblique images? What type of data do you need if so?

Pix4D can process oblique images, but it is recommend to take images every 5-10 degrees.  It is also recommend to capture two sets of data at different heights. 

• Are GCPs necessary for Pix4D? When are they highly recommended?

They are not necessary for Pix4D, but they are highly recommend when there is no geolocation.  

• What is the quality report?

The Quality report produces a description with information informing the user how the initial processing looks. It gives a summary of all the checks of the data during the initial report and a low quality picture of the area.

Methods

To start creating surface models in Pix4D start with a new project named something that follows a naming scheme and save it in the correct folder.  Next, the select images screen will open which allows the images taken with the drone to be selected.  Find the correct folder containing the images and select them all to be processed.  Click next and and review the image properties.  With the drone used for our images the shutter mode needs to be changed to linear rolling.  Click next, to review the output coordinate system, click next to select the processing type.  For this case it will be "AG RGB."  To make the processing faster it may be useful to create an area of interest.  This is done by selecting map view and then selecting processing area.  Now click and draw a figure around the area intended and finish with a left click. Now to run only use the initial processing first to make sure the data is all good to go.  Finally, run the next two processes next to the initial processing to create the 3D surface model.

Calculate Surface Area

• Select View
• Select Ray Cloud
• Select New Surface
• Left click to make area and Right click to finish. 

Figure 1: Surface area. 

Measure the Length of a linear feature

• Select View
• Select Ray Cloud
• Select new PolyLine
• Click to select distance to be measure

Figure 2: Linear Distance

Calculate the Volume of a 3D object

• Select View
• Select Volume
• Click New Volume
• Draw out the points around the part of the image and right click to finish the shape. 

Figure 3: Volumetric calculation.

Create an Animation that 'flys' through the project

• Select View
• Select Ray Cloud
• click on the camera icon from the create box
• Choose generated waypoints or computer generated waypoints
• choose the duration and speed of the flight
• save the file

Results

Figure 1: DSM of the area of interest of the mine in Litchfield. 

Review

Pix4D seems to be a relatively easy program to use with everything layed out well on the main screen.  Even a beginner could pick up this program and upload the images and start making material with the help of other internet sources.  Its great that this program creates high quality data without having to have relatively high quality data to start with.  Although, this can be dangerous to some this is a wonderful program to work with.  It may not be as accurate and speedy as LiDAR, moreover it is still a wonderful tool if only aerial photo are available.  This program has many uses, it can be used in consulting for environmental firms, real estate, or even just taking aerial photographs as a hobby. overall this is a great program to use.

GPS Topographic Survey

Introduction:

This weeks lab was to use a dualff frequency GPS to get an accurate point that will be accurate to less than a meter.  This can compare to a smartphone GPS which will be around 10m accurate or a consumer GPS which is within 5m.  It also gives an elevation which can be used to create a continuous surface of the area. The GPS is connected through Bluetooth to a handheld device with the interface on it.  This makes it simple and easy to use in the field.  The important aspect for creating an effective surface area map is to get enough points to cover the areas with high relief and to create a study area that will accurately represent the area being studied.  The sampling method that was used is random sampling.  This means that random points were taken through the area rather than in one of the first labs using a sandbox when systematic sampling was used.

Study Area:

• 29 November 2016
• 40 degrees, Rainy
• Location: In front of Centennial Hall on the University of Wisconsin - Eau Claire campus.  The more detailed location would be tot he south of the circle area with the dancers statue.  

Methods:

Materials

Topcon Tesla Field Controller 

Topcon Hiper SR Positioning Unit

Tripod Stand (With level)

Figure 1: Dual band GPS in the background, and Dr. J Hupy holding the Topcon Tesla Field Controller to collect the first elevation point. 

The Data was collected using a dual frequency GPS which included using the materials above.  The information was Bluetoothed to a handheld which was downloaded to a computer.  Dr. Hupy processed the data and shared a text file.  The text file was then processed in Excel to be able to upload it into ArcMap using the import XY tool.  Then, the data can be used to create continuous surface raster layers using the IDW, Kriging, Natural Neighbor, Spline, and TIN tools.


Results/Discussion

Figure 2: Spline Interpolation of Elevation in a 2D view

Figure 3: IDW Interpolation 

Figure 4: Kriging Interpolation Method

Figure 5: Natural Neighbor interpolation 

Figure 6: TIN interpolation

Figure 7: Spline 3-D Interpolation

Figure 8 IDW 3D Interpolation 

Figure 9 Krigling 3D Interpolation

Figure 10: Natural Neighbor 3D Interpolation

Figure 11 TIN 3D Interpolation

Out of all of the different interpolation methods the most accurate one would be Natural Neighbor.  It really does the best at accurately representing the hill and the amount of relief.  The Krigling interpolation also did a decent job at representing the hill, but it did not do as well of a job at getting the amount of slope on the hill. The IDW interpolation method seemed to have too many holes or low spots in areas that were not actually lower, and the spline interpolation method was wavy and did not really do well with the edge of the slope on the hill.  The TIN did create a good image, but seemed to be edgy.  The 3D version of the IDW seemed to have some weird hills created at the top and some holes at the bottom.  This created a weird landscape that does not represent the surface well.

Conclusion

For making a continuous surface map it is important to collect enough points that would make the interpolation more accurate.  It is also important to accurately set up the GPS Unit, and it is important to have it level and upright.  This will create the most accurate data points.  It is also important to collect enough data points in the region with higher relief to represent the real world.  Using a dual band GPS also will create a more accurate point, but it does take longer than a cellphone or a consumer grade GPS.  

ArcCollector 2

Introduction

This project was looking at what kind of vehicles people drove on Hudson Street between 1st and 3rd Ave. in Eau Claire, WI.  It was also comparing the different types of vehicles to figure out which state, Minnesota or Wisconsin, has the more environmentally friendly vehicles parked on the road.  Proper design is very important when trying to answer questions using ArcCollector. If the design is not set up correctly, going into the field will become very difficult and the whole process will roll to a halt.

Study Area:

• November 29th 2016 41 Degrees and Overcast  
• Hudson Street in the City of Eau Claire from the 1st block to the last.  This area has many different types of people making the variation of cars higher.  There will be permanent families, renters, college students, friends or family, and any maintenance workers as well.

Methods

Creation of the Geodatabase

The first step to using ArcCollector is to come up with a question that has the ability to be answered by creating data points out in the field.  The next step before going out into the field is to set up a geodatabase, which houses and stores the data. Within the geodatabase a feature class needs to be created which will outline the mapping area.  That is strictly for appearance and makes it easier while being in the field.  Next, is to make a feature class that is for collecting the data.  This feature class needs to be a point feature class along with having a projected coordinate system of  WGS 84 Web Mercator, which is necessary to work with ArcGIS online.


Now setting up the point feature class there needs to be attributes to help solve the problem.  For this project the attributes used were Lisence Plates State, Car Type, Car Size, Wheel Size, which side of the street the car was parked on, and the quality of the car and this can be seen in Figure 1.  Then, in Figure 2, There are the domains that need to be set up.  Domains are used to limit the attributes to certain restrictions.  For example, The Car Type was set up to show a list of different car manufactures  within the domain to make it easy, and to stop mistakes from happening.

Figure 1: This figure is showing the different feature classes used to help solve the problem at hand.  

Figure 2: This figure shows the domains that were used for the attributes.  These are important because they reduce errors within  the field.  

Now, once everything is set up the main thing to do is to publish this as a service to be used on ArcGIS online. To do this Sign into ArcMap using an enterprise account or any other method.  Then, go File -> share -> publish as a service -> and basically follow the steps to publishing the material needed.  Once it is online the feature classes can be found on the website.  Once on the website it can be saved and shared to everyone, anyone with an enterprise account, or just the original publisher.  

The next step is to download ArcCollect for IOS or Android.  This is a very cool app because it allows the user to use the smartphone for the GPS and data collection rather than other equipment. Although, it really should only be used for data that does not need to be 100% accurate spatial wise due to smartphones not having the best GPS in them.  It gets the job done, but it should not be used when accuracy needs to be a priority.   On ArcCollector is is just adding data points when need be and entering the correct data.  If the domains were used properly this should be very easy on the smartphone.  

Next is uploading the data points into ArcGIS Online which can then be downloaded and manipulated to create maps in ArcMap.

Results

The results for this questions were actually quite indifferent.  It seemed to be that there was an almost even amount of more environmentally friendly on both sides.  This is a good result though because it shows that people are trying to take care of the environment. Figure 3 is showing the different brands of cars that were found.  This map is not the most beneficial to the question but it is interesting to see that there is not really any pattern or higher number of one brand of vehicles. Figure 4 is showing the quality of vehicles within the area.  This is important to see because it shows whether people are keeping their cars longer or getting newer ones.  in this map it is showing that more car owners have older cars based on the amount of rust/damage to the vehicle. In figure 5 it shows which side of the road the cars were on.  This attribute field was done to show how accurate the GPS is on the Iphone 6 used.  The map clearly shows many of the dots on the wrong side of the road of what they are supposed to be. If it was important to have very precise accuracy this type of GPS would not work. Figure 6 is just showing the size of the vehicle.  This includes the size of the car which is economic to sedan or small SUV to full size SUV for example. In Figure 7 the map is showing what kind of vehicle was found.  This was an important indication because a car would generally be more friendly toward the environment than a truck, but in this mapping area there were no trucks to be found.  Only SUVs, vans, and car were found.   Therefore, this is an environmentally friendly area.

Figure 3: This is a map showing the different brands of vehicles found within the area.  

Figure 4: This is a map showing the quality of cars.  This included New, Almost new, Some Rust, and Junker.

s

Figure 5: This is a map which shows which side of the road the cars were parked on. 

Figure 6: This is a map showing what size of vehicle is found. 

Figure 7:  This is a map showing the type of vehicle found.  

Conclusion

ArcCollector is a great tool to use when collecting data due to is versatility in the field.  As long as it is set up correcting it can a great asset to data collection. Since both of the states had realitly the same amount  If this project was to be done differently it would be an asset to get the entire student housing area to see what the entire area is driving.  It would also be nice to set up a color option as well.  This could also be expanded into a different questions which could be trying to find out how environmentally friendly the student housing area is with their vehicles.  

Microclimate

Introduction

The field activity this week included using ArcCollector, which was downloaded onto our phones as an app.  The class was broken up into partners and set out into the different zones around campus to collect climate data including temperature, dew point, wind speed, and wind direction.  These can all be entered into a smartphone to instantly upload into ArcCollector.  The final part is to turn the data collected into a continuous surface map using the different types of data collected. The purpose of using ArcCollector is to generate a map that each student can download after each group uploads their data points.  This eliminates the need to share it on a share folder or have each student greater a different geodatabase with different domains which could make things more complicated than need be.

Study Area

• 9 November 2016 Sunny 50 degrees F.
• University of Wisconsin - Eau Claire Campus (Upper and Lower)
• Figure 1 Shows an aerial view of the study area. 

Figure 1: Area of Interest with the stations taken by each group.

Methods

Each of the 8 or so groups set off to their designated zone on campus to focus the most efforts in their area to ensure that most of the map has some kind of data points.  Each group was given a climate surveying device that calculated wind speed, temperature, and dew point, and to use ArcCollector on the app running on their Iphone or Android device.  Out class had the luxury of having a geodatabase already set up making the data entry easy when out in the field.  Since it was already all set up and each group was connected to it, all that needed to be done was to collect the information within the zones and come back to upload the data, therefore collecting all of the data was quick and painless.

Most groups seemed to be taking points about every 25 feet to get the outside of their zone before heading into the middle of their areas before making their way back inside to upload the data.  Then the data can be downloaded after everyone uploads theirs to create a set of feature classes that can be used by each individual.

Now that the data is downloaded and set up the fun process of interpolation is the next step.  Since there is not a pattern of points and not every point can be taken the choice for interpolation would be IDW (Inverse Distance Weighted).  This was chosen because this method weighs the points based on the distance from each other.  The farther away the next point the less weight that that single point will have.  This created Figure 2,3 and 4.

Results

There are most certainty some patterns that can be seen within the images created. The first patterns that are noticeable are with the wind speed (Figure 2).  Along the ridge or scarp, which separates upper campus and lower campus, there is a noticeable decrease of wind speed due to the scarp where the points are directly adjacent to.  Another pattern noticeable with the wind speed is around the river.  This is due to the river being a relatively open are allowing more wind to flow through that area.  Therefore, the area surrounding the river creates a zone of higher wind speeds.  Another area is the terrace, upper campus, which also has higher wind speeds because there are less trees within the area to slow it down.

Figure 2: Continuous map showing Wind Speed.  This map is also showing the wind direction taken at each station to show more patterns depending on the location. 

The temperature map (Figure 3) shows the pattern of having warmer temperature surrounding areas with buildings, compared to the areas that are heavily vegetated being cooler overall.  This could be due to the cement sidewalks absorbing the sun's rays, and emitting it to create a overall warmer climate. The vegetated areas are cooler because less of the sun's energy can reach the ground to emit its energy back into the surrounding atmosphere.

Figure 3: This is the Temperature version of the microclimate.  

The dew point (Figure 4) is lower around the Chippewa River and higher around the buildings on campus.  This is expected because there is going to be a higher temperature around the buildings on campus making the dew point higher because temperature directly influences the dew point.

Figure 4:  This is a map of the dew point around the UWEC campus.  

Conclusions

ArcCollector is a very powerful app for collecting data in the field.  Using some kind of smartphone can really add a lot to the power when collecting data in the field with its ability to use Bluetooth to a GPS that displays the necessary information on the smartphone.  Therefore, using ArcCollector on a smartphone is very similar, just without the Bluetooth technology which could easily be substituted for a smartphone's GPS.  Using ArcCollector sped up the data sharing with the class much faster than having to share around an excel file or any other way of getting everyone to enter the data making this an invaluable tool for group work like this when accessing data.  This can be adventurous in the field while working as a professional if there are multiple people working on a project, they could just update the data every day when they would come back from the field.  Being able to collaborate with all of the class made this sharing of data a lot faster and accurate than any of the other labs.  This lab was very important in the understand of creating a geodatabase and creating domains before entering the field.

Priory Navigation: Part Two

Introduction

As the second part to last weeks lab group 6 was able to utilize the maps created to navigate through the heavily vegetated and steep topography to find five locations given out by Prof. J. Hupy.  The tools provided to complete this lab included a GPS to locate markers and track the path taken, the maps from the previous lab, and a baseplate compass.

Figure 1: Baseplate compass (not exact one used)

Study Area

• 2 November 2016 3-5pm
• Area surrounding the Priory Hall 1190 Priory Rd, Eau Claire, 54701 
• Conditions:  Partly Sunny Temp. 65F

Methods

After being assigned the points the groups split off to find their first location.  To do this, a starting point and a bearing was needed.  To get the bearing the baseplate compass needed to be used, and the most helpful trick with that was having red in the shed once the arrow pointed at the first location. Another trick with the compass is to make sure there is no metal around it which could affect the direction it is given off. Next, was to get a distance between each point.  Group 6 also needed to make sure all of the points were accurately pinpointed on the map to make the bearing and distance as accurate as possible. This was to help measure out pacing to know how many steps to take between points when using the bearing.  

Since there were only five sets of points and we were the sixth group we got stuck doing the course backwards starting at point 5.  This was absolutely the hardest point for our group.  This was the hardest to find due to being on the other side of a a large trench. which was very far off of the main path leading down into the area.  Although, it was only really thick around the trench it was easy to navigate between the path and where it got thick due to being mostly trees.  

Figure 2: First Location

The next location for our group was actually not nearly as hard to find as we had the compass down and we knew exactly where we were.  This involved a great trip back down into the trench to come up the other side.  to find a pink flag around a tree.

Figure 3: The second location on the other side of the trench

The third location was actually the easiest one to find as we had seen it earlier on the way to our first location.  This one was right on the path and just a quick walk through the pine trees.  

Figure 4: Location 3.

The next location actually gave us a bit of a hike back to the dreaded trench.  This time we were well prepared, except for the fact that we were too far east.  after correcting our position we finally spotted the flag in the distance.

Figure 5: Fourth Location.

With all the confidence built up after finding 4/5 points Group 6 was on a high to find the final point.  This is when disaster struck.  Our GPS died leaving us to fend for ourselves.  This actually lead us up a unneeded hill to figure out we needed to be at a lower elevation.  While getting back to the major path we headed back to the east.  We spotted the flag and found our final point without having to use a GPS.  

Figure 6: Final Location

Discussion

This lab really brought out true wilderness skills of only having a compass a map and a GPS to guide.  Having the track log brought up some great laughs to see how many times each group had to turn around or look around at an area to find the correct flag.  My group only had a few hickups which was not actually using and of the pacing due to not remember to keep track after leaving a point and only following the bearing.  This did not cause too many problems due to still heading in the correct direction and being able to check the GPS. In Figure 7 there are many paths that cross and a lot of places where there are clear turn around to get back on the path.  In Figure 8, which is Group 6's path, there are a lot of dots that are seen right around the trench in the south eastern part of the map.  This is generally were we got the most lost.  There is also the path at the most north part of our tack record which is our group going a little too far north before realizing we needed to turn around to head south west to get to the first point.  

Figure 7: Complete map that shows all of the groups paths taken.

Figure 8: Complete map showing only Group 6 path taken.  

Conclusion

Overall this lab taught a few different things.  First off it taught how important it is to make a navigational map that is in the correct coordinate system.  This can be the different of a few meters off to miles off which can be a huge problem under time restrictions.  Secondly, it taught how to use a baseplate compass while using a navigational map.  Also, for my group it taught us how to not rely on the GPS because the batter could die for no reason at any moment in the field.  

Sources:

http://www.mapworld.co.nz/comptype.html

USGS DEM to make Contour lines

Priory Navigation Maps: Part One

Introduction

Navigation is one of the most useful skills to have.  Today the most common way of using navigation is from a smartphone app or from a GPS.  There is not so much asking for directions anymore due to being lost. Creating a map for navigation has a few key elements that are needed to make sure it is accurate and readable.  Therefore creating maps needs to have a detailed constructed map.  This doesn't mean it needs to look fancy and have all the bells and whistles; this just means that the map needs to have all the correct information laid out to help aid in direction.  This means it needs to have a proper coordinate system to make sure the person reading the map will not be many meters to miles off from their actual location.  For this activity maps of the Priory, near Eau Claire, Wisconsin were created.

Methods

This week two navigation maps were created to guide us for next week through the forest.  The first was created using degrees minutes and seconds grid, whereas the other was created using a UTM grid style.

With most of the needed data supplied from Professor Joe Hupy, the maps were set up.  To get them set up each needed a little amount of tweaking.  Each map needed to have an essential list of elements that included a north arrow, scale bar, RF scale, legend, source, Title, Projection used, and a watermark.  The RF in these maps allows a little more information to understand what the measurements are on the map.  This will help to understand pacing and distance while walking through the woods.  For the UTM map the projection was NAD 1983 UTM Zone 15N Wisconsin Transverse Mercator. The other was put into WGS 1984 to accuretly represent the degree minutes and seconds.  The UTM map was also changed to have a grid marking every 50 meters.  The grid labels were also changed to make it more readable by making the first few numbers smaller because they do not change. The decimal degree grid was made using 5 second intervals.  The UTM navigation map is in Figure 1 and the Decimal degree map is in Figure 2.

Figure 1: UTM Map

Figure 2: Decimal Degrees

Discussion

Creating maps like these are crucial to navigating around unknown terrain.  They are important for a few reason.  First,  it shows detailed elevation of the region.  This is very helpful because it can help you avoid having to go up and down hill constantly.  Another reason is because there was a technique taught in the geology department at UWEC for finding your own location on a map.  This is based on triangulation.  To do this one would need to be able to pick out three points from the navigation map and then determine azimuth directions from all three points to where the person standing is.  This gives a triangle of intersection to give the location.  Therefore, these kind of maps are important to understand how to use. The projections used are important because they need to reflect the surface accurately.

The UTM coordinate system is broken up into roughly 10 zones throughout the United states.  This is important because it helps shape the zones into the shape of the earth.   The other coordinates system was chosen because WGS84 is common for GPS to use.  This will allow ease when navigating through the Priory location.

Conclusion

This excercise is important to understand how to accuretly create navigation maps to be alble to use in the field.  It also was important to teach how the different coordinates systems and projects affect the look of the map.  Even if it is very slight, it is important to have an accurate map because an easy day in the field can turn into a nightmare, and these maps will be great to use next week for our field experience with them.

Distance Azimuth Survey

Introduction



This weeks survey includes having to create survey plot that is going to be used to identify trees found within the area. This method is used when technology fails, and it is a good backup to use and understand how to use. To utilize this method for survey measurements of azimuth distance and GPS points will be taken.  The distance calculates how far the starting point is away from the tree and the azimuth calculates the distance off of 0 degrees the tree is. 





Study Area and Set Up

The survey area selected for the distance azimuth survey was located on Putnam trail, just east of Philips Hall on the University of Wisconsin - Eau Claire campus.  This area is generally a swamp region during the summer when the water table is at a higher elevation making it difficult to walk through the trees in the shallow spots.  It has a large population of many different species of trees along the trail, which is located at the bottom of the hill which is famous to the students and staff on campus.  This area was selected due to having a large amount of trees to take azimuth directions on. The study area can be seen in a map view located in Figure 1 showing the location of the three study sites.

Figure 1: These are the study areas selected due to the large tree population. In the Green box is study area 1, blue is study are 2, and the red box is study area 3.  North is in the upward direction.  

Once we got to the sites there was some confusion due to not having used any of the equipment before.  The equipment used was measuring wheel, measuring tape which converted into diameter (Figure 2), a compass with the ability to take an azimuth measurement (Figure 3), a laser distance finder that uses ultrasonic, and a distance finder that uses a laser (Figure 3). The class was broken up into three groups to each collect data in the three spots using a normalized method to make it easier to create a spreadsheet once back in the office. The attributes taken for each datapoint included:

1. Longitude (x)
2. Latitude (Y)
3. Distance (meters)
4. Azimuth (degree 
5. Diameter (Breast Height)
6. Tree Species
7. Sample Area Number

Figure 2:  Sarah Ward using the tape measure that converts it into diameter on the fly. 

Figure 3: Jesse Friend and Kyle Roloff (myself) taken a distance measurement (Jesse) and an azimuth reading (Kyle). 

The attributes chosen are each needed to create a survey that uses azimuth data.  To use this data within ArcGIS there needs to be an X,Y point for each tree so the computer can determine based off of the azimuth and the distance where it is located within the survey grid.  Also getting the diameter could determine the age of the tree or another physical feature.  The type of tree could also be used in another application to show what kind of trees mostly populate the Putnam Dr trail.  The last point is just the survey number which helps keep straight which area that point belong too.

Methods

There are many steps that went into this survey which include:

Step one:  Locate the study area.  This was chosen by finding and area that has a large tree population and could easily be identifiable by google maps to make sure the accuracy of the project is close (Figure 1).

Step two: get a gps point of the starting point.  This means that all of the trees survey will be based off of this point therefore it is imperative to get an accurate GPS reading.
Step Three: Pick a tree to start the survey.

Step Four: Use an compass to get an azimuth by directing the compass at the tree.  Where the arrow   on the compass points gives the azimuth (Figure 3).

Step Five: Use a distance finder or the measuring wheel to get a distance from the original point to the tree being surveyed (Figure 3).

Step Six: Use information about trees to figure out what the species is.

Step Seven: Use the measuring tape that converts on the fly into diameter on the tree at breast height (Figure 2).

Step Eight: Record all the information down in a notebook to bring back to the office.

Step Nine: Use the Bearing Distance to Line command found in the data management tools in ArcToolbox. Before being able to use this the data needs to be imported and made into a points feature class.  This is done by creating a feature class and then right clicking on it to select import x,y coordinates.  Then once they are imported as points the next step is to super impose it over a basemap to access for accuracy.  This is important for the final creation so the views can see how accurate the points are.

Step Ten: Use the Bearing Distance to Line Command to create the lines that go in the direction of the trees


Point Eleven: Next use that feature class and use the Feature Vertices to Points tool. Make sure to use the End parameter on this because we do not need the starting point because that is not a tree.

Step Twelve: Create a quality looking map that shows all of the great data collected in the field.











Figure 4: Final Map showing location of Trees from all three survey areas.

Discussion/Results

There were a few problems that stood out right away when looking at the data when imported into ArcGIS.  First off, The x and y coordinates were backwards and luckily that is an easy fix.  The next was that the group with the red study area was having a problem with their gps.  This may have been due to the ridge which was right next to where the initial point was taken.  The solution to this was to move the point closer to the study area even though it may not be exact.  This will be taken into account to determine the accuracy.  If this was for a professional survey it would need to be redone, but should also have been confirmed from another source to make sure it made sense before continuing.  Using this technique can be very useful in some settings when technology fails.  It can be used during any data collection as long as there is one point known, a compass, and a measuring wheel.  It is easy to use as long as the table is set up correctly and and azimuth is set at the correct declination to the area in the world. This can be used to plot trees, plot bomb craters, or plot rock outcrops.  Technology that has replaced this technique includes using distance finders and carrying around a GPS to collect points.  The points can then be Bluetooth transferred over to a tablet that then can have attributes entered in it without having to write down all of the information in a field notebook. The results started off by being off because the points were located a few miles away.  The only way to really fix this was to move it to the correct location using an educated guess.  Next was that the trees and their directions looked really well on the map created.  For group three it looks exactly like the trees this group took.  The results are pleasing except they may not be the most accurate due to being off from the GPS.  Another problem with this is how hard it is to figure out exactly where the study locations were.  It is hard to see through the tree cover making it difficult to distinguish any of the trees.  It would be better to try this survey in an area with less trees to see if the lines actually point to the correct tree.  In my opinion using the newer technology it was very quick to go from point to point.  If using the older technology it was exponentially increase the amount of time spent on each tree to collect datapoints. 




Conclusion



This was a great lab to learn survey techniques that can be used when technology fails.  The only important part is to have a correct GPS point and all the other tools to take distance and azimuth measurements. It is also important to know this because there is no way to predict when technology will fail.  Luckily for us technology made the survey go quicker than having to use the measuring wheel for each tree. The accuracy was about 70% and could have been better if the points were not off due to the ridge.  Also, it can be tedious to do this with the older equipment, but at the end of the day the job needs to be done even if the technology fails.



Photo credits go to Google and Heather Wood.