Azimuth Surveying

Introduction

                Technology is not 100% reliable and will fail sometimes. Given that instance one would have to come up with alternative means to forgo certain tasks that would be achieved using GPS technology. This assignment allowed for the use of other instruments in determining the location of an object.  The goal was to take points and find the standard distance and azimuth (degrees) of a point. These points were taken by a surveyor using a tool called TruPulse Rangefinder.

Study Area

                Wilson Park in downtown Eau Claire was the area that was surveyed. Wilson Park is situated in one city block that makes it possible to survey almost everything around. Readings were taken from three corners of the block to get multiple points. This park contained numerous points to be used in the survey. There were trees, park benches, signs, picnic tables, and even garbage cans that could be used.

Figure 1: The survey area of Wilson Park which is located in downtown Eau Claire and over 1 mile from UWEC campus.

Methods

                A survey area was chosen and this area was Wilson Park in downtown Eau Claire, Wisconsin. Three areas of the park were chosen to get as many points as possible. To take points the TruPulse Rangefinder tool was used. There were two methods that were needed to be able to map a point. Standard distance found how far away an object was in meters using a laser. The next method was to find the azimuth or degree at which the object was. The degree is at what point on earth the object was. Degree measures are based off of the north direction. North is set at 0 degrees and all measures are read in a full circle format. These readings were then recorded to be used in Excel and ArcMap.

                The points were manually transferred into Excel from the note records. For each point to work in ArcMap they had to be given a coordinate pair to work with. Initially, when taken the surveyor point was labeled either A, B, or C. For Excel these A, B, C points had to be given lat and long points. Using ArcMap Editor to place points on a basemap of Wilson Park coordinates were found. A points were given an X of 44.807475 and a Y of -91.494889, B points were 44.806898 and -91.494298, C points were 44.806485 and -91.495175. After making the data Arc compatible it was then transferred to an ArcMap document.

Figure 2: Table of points in X and Y decimal degree formatted for ArcMap

              The ArcMap document had an aerial imagery Bing basemap with decimal degrees being the reading. The table was opened in ArcMap and ready to run using the Bearing Distance To Line tool. Since there were three tables each had to exported as a single table. To do this the each X and Y coordinate group was selected separately in the table and under the dropdown table options menu export was chosen. Now that all three were separate a model was ran to create new features and view the data.

Figure 3: A model used to run tools that yielded point results. This is the first model. All 3 run the same process but with different inputs.

Figure 4: The collected points at Wilson Park. Numerous objects were chosen such as trees, picnic tables, benches, and garbage cans

Figure 5: Standard Distance lines added to the points to view how far from the surveyor.

Discussion

                Due to both human and technological errors there were some problems that arose. Because of an object being too small a reading could have be

en off by a certain degree or distance. This shows up on the maps. There are points that were taken that did not match up with initial data. Mathematical errors and number entering could have also been a problem. The biggest problem that could arise is that there is out of date data or that some of the features are too new to show on maps.

Conclusion

                Exploring these methods shows that there are numerous possibilities out there that can help when problems arise. These instruments though not 100% accurate do help with surveying. These methods are quick and easy and with limited human error can help with problems. To make sure high accuracy results are yielded surveying of the same points during different times would help.

Assignment 3: UAS Exercise

Introduction

For this assignment the class was given a real set of issues that have arisen and have been assisted with UAS. The class was challenged to think like a geographer to solve these issues. The scenarios that were given were detection of desert tortoise near a military testing range, monitoring of power lines, observing a pineapple plantation for health and harvesting, looking at a leaking oil pipeline in the Niger River Delta and its impact on agriculture, and measuring a mining company’s mine and how much is removed on a weekly basis. Solutions to these issues are to be solved by using hypothetical UAS ideas.

Desert Tortoise

The desert tortoise is a threatened species in the United States and is federally protected. This causes problems for military testing facilities. The facilities must plan out all exercises around the tortoise. This planning is usually in the form of ground-based surveys. The survey area is large and ground based surveys are cost ineffective and tedious. To make this easier we will use UAS to help out with the surveying.

The desert tortoise’s habitat is predominantly desert (ergo its name). The tortoise will build burrows for shelter and protects them from the heat of the desert. These burrows are usually found near vegetation, near or underneath shrubs or bushes. The burrow has a distinct crescent moon feature which also be something to look for.  These are the features that will be looked for when using the UAS.

There are a few options that will be used with our UAS.  A fixed wing UAS type is chosen over a rotary UAS. The choice was made based on a few observations. These being the size of the area, and the potential for digital modeling and Lidar. All these have been taken into consideration for the project.

The definitive pieces on the UAS will be a GPS and hyperspectral camera. The possibility for a Lidar sensor is out there but that depends on the cost. The hyperspectral camera will include the visible spectrum for the human eye as well as near-infrared and infrared bands. The camera will take a picture every second with a high overlap so that we have a high accuracy. The GPS will tag coordinates to our images for closer observation. The flyover will take the images at each of the bands of the camera.

Our first option is the hyperspectral camera. As our flyover ends we will analyze the returned data from our hyperspectral camera. The image will be viewed in a remote sensing software program. What we are looking for is similar features throughout the area. These features are the distinct shape of the burrow and the vegetation that the tortoises usually build around. Once we have found these features and similar features a supervised classification will be used. A supervised classification is a process used in remote sensing in which a feature from an image is selected and that feature returns a certain color signature. All areas with similar returned spectral signatures will appear on the image. To verify that these areas are burrows some ground surveying may have to be done for as high an accuracy as possible.

The second option is to use a Lidar sensor. The Lidar sensor will be placed on the UAS just like the hyperspectral camera. The Lidar sends down light in a laser and collects the return values. The return values are calculated by the time it takes for the light to return to the sensor. This will give a 3D digital elevation model in our end process with some very accurate features. Lidar can penetrate foliage as well which will help with the location of burrows underneath the vegetation. When we collect our data we can place the X, Y, and Z values into a GIS program and get a 3D image of our area. With this we can see distinct features like the burrows.

Figure 1: A Leica ALS70 LiDAR scanner. Similar to one that would be used when taking an airborne survey. Source for scanner

These are the steps and processes that would be taken to help out with finding these burrows. Multiple flyovers may have to be done to assure for high accuracy. The best option would be to use the hyperspectral camera plus small ground based surveys.

Power Line

Using a UAS for power line inspection is a better solution than hiring a helicopter company to fly in from a distant airport. Use of a UAS will cut costs that would be factored in for fuel and transportation of the helicopter. The current process is to get as close to the power line as possible and have a person lean out and capture images. A technique which not only could result in poor images, but also cause serious injury and even death. With a UAS the risk for human injury is eliminated.

Figure 2: Here is an example of a rotary wing UAS that can be used. The site attached has many option on what to use.
Rotary Wing

The rotary wing UAS uses blades to navigate around. The blades propel the UAS up from almost anywhere. It does not need space to gain speed like that of a fixed wing UAS. With the ability to start from anywhere this eliminates the cost of having to fly in a helicopter. The UAS can move around the power line and its components very smoothly due to the stability of the blades. It can move in to take a closer picture of the power line and can hover to allow for accurate pictures. A camera is placed on the body of the UAS. It has the capabilities of taking video and still images. The video can be relayed back to a controller for immediate viewing of the condition of the power line.

The best option is to use a rotary wing UAS with a high resolution camera with video and image capabilities. The rotary wing is recommended because of the small area that is being viewed and the means of having to be able to get within a close proximity of the power lines which is helped by using the UAS’s hovering capabilities. We are eliminating the risk of human injury by removing the dangers that are presented with helicopter use. We are also eliminating helicopter transportation costs that are factored in with the choice of airport and high fuel costs. The only negative that is found is the timeframe that we are allotted. We must move quickly because of the rotary wing’s small window for fly time.

Where to find rotary wing: Rotary Wing info

Pineapple Plantation

In consulting your plantation’s operation it is my best recommendation that you would look into using the USGS’s Landsat program. The Landsat program is a satellite operation that captures images of the Earth using multispectral band imagery. The current satellite is Landsat 8 which captures an image every 16 days. That means that it flies over a spot every 16 days and takes that image. The imagery of Landsat is free to download, but to use advanced systems one would need a photogrammetry/remote sensing software program. I suggest Erdas.

To download an image of your plantation you would navigate to the USGS global visualization viewer at http://glovis.usgs.gov/. Next is to find the area that is your plantation. Once that is found I suggest choosing from the Landsat 8 collection and setting your resolution to 240 meters for a closer view. Adding that to your cart is done by highlighting your area and selecting add at the bottom of the page.  You must register with the site first, which is free. The image will either be downloaded directly or start to be process in which you would receive it at a further date by email. The file will download a Zip file which needs to be extracted. That will breakdown the Zip file into TIFF files. There will be 11 or so images files. If you are using Erdas you would want to add layers 2 through 10 and combine those as a layer stack. The image band that will work best is the short wave infrared band which is band 6 and 7. These will show your healthy vegetation as a white color. This will also help you to determine when to harvest.

If the 16 day wait period is too much for you I suggest that you used a fixed wing UAS. This will cost more, but you will have a shorter wait time to view your plantation. I suggest placing a multispectral/hyperspectral camera on the UAS if you choose this path. The process is very similar to Landsat as the camera has bands as well.

The least cost effective path is to use the free downloads from GLOVIS, but if you are looking at time constraints using a UAS may work best.

Explanation of Landsat bands: https://landsat.usgs.gov/best_spectral_bands_to_use.php

Oil Pipeline

The Niger River Delta is one of the most polluted waterways in the world and with nearby agriculture being effected I suggest that using a UAS to monitor the situation is best. Knowing that the area is also very dangerous this only backs up my suggestion. With the potential of having your pipeline leaking I suggest that a rotary wing UAS be used.

Since you are looking for the leak in a specific area the rotary wing works best. The UAS can maintain contact remotely within miles of the controller. This is a benefit as we know of the dangers of the delta. The UAS operates with blades that balance the body which usually holds a camera that can take pictures or record videos. The UAS operates like helicopter which takes off vertically. Unlike a helicopter the maneuvering is very simply as one can move freely around objects. This allows for movement around the oil pipeline which allows for better observation for the like. Once the leak is found then the UAS can take a video or images. I suggest a high resolution camera for this task as it will best to have a small level of uncertainty in this project.

I hope this has helped out.

Mine

I have looked at the options for understanding the operation in which you are partaking. For this it is in my best judgment that for your mine you should consider using a fixed wing UAS. I understand that you do not have the funds for a LiDAR sensor. My suggestion is that you look into a point cloud system on a UAS. Point Cloud is a system which takes points of a surface and measures that surface using elevation.

I have suggested fixed wing because of your spatial area. I know that this mining operation is quite large and doing a quick fly over will suffice. With your fixed wing system I have suggested a point cloud feature. By doing this on a weekly basis you can measure how much you have removed by using a formula with the elevation difference. The process should be done using a DEM or digital elevation model. This model will be a 3D representation of your mine and again you can see what the changes are. 

Free point cloud processing and info

Terrain Modeling

Introduction

The second of our activities was to create 3D terrains using interpolation methods. The data for this activity was the X, Y, and Z coordinates from activity 1. The five interpolation methods were IDW, Natural Neighbors, Kriging, Spline, and TIN. The idea was to determine which of these five would yield the best view for the group’s results.

Figure 1: Here are the points in ArcScene to make a 3D image

Methods

The data was entered into ArcMap and ArcScene. To create the 3D terrain the Interpolation tool had to be utilized. This is found in the ArcToolbox under Spatial Analyst then Interpolation. The terrains started as 2D models but by using base heights in ArcScene they were changed to 3D scenes. The points were placed in ArcScene to make a 3D image. These points are the points that were taken and then placed into XYZ format.

IDW

Figure 2: This is the IDW terrain. This looks to be one that should be used less than the others. IDW uses a weighted average to predict cell size.

Natural Neighbor

Figure 3: Natural Neighbor Interpolation finds the closest input samples and applies weight to them based on other cells that are proportionate.

Kriging

Figure 4: Kriging uses natural phenomena to predict the value of cells. It takes into account uncertainty. 

Spline

Figure 45 Spline uses a method that estimates values mathematically. The Spline method uses a curvature of the surface to estimate values.

TIN

Figure 6: TIN looks to be the most reliable and has a higher accuracy than most. Triangles are used to show elevation and the triangles can be placed in irregular areas.

Discussion

3D modeling of imagery is one of my favorite aspects of geography. I rather enjoyed looking at the images and analyzing them. That’s what got me through the data collection part. All in all our group worked well together. Everyone involved brought something to the table and we all agreed on almost everything. This part of the class did not really involve much group cooperation rather than talking with data.

Conclusion

This activity was rather an enjoyment and it helps with future endeavors. To have this knowledge and apply really works in the real world. The ability to run these tools is fairly easy if you enter the data correctly. For visualization purposes Kriging looks to be a better measure of accuracy. Kriging also takes into account natural phenomena in its algorithm to predict values. Using IDW and weighted average could skew areas because terrains that differ and are relatively close could skew the results. Natural Neighbor and looking at cells that have similar values could make a better view. Spline uses curvature to estimate values and by using that curvature could throw off results. A TIN is a very common DTM method because of its ability to place triangles in irregular areas that would be harder to measure.

Exercise 1: Creating Elevation Surface

Introduction

The first activity was to create an elevation surface and record points on the surface using X, Y, and Z fields. The elevation surface was made in a planter box/sandbox. Each group had to make land features. These features were a ridge, a hill, a depression, a valley, and a plain. The box was separated into grids which were the group’s X and Y points. The X points were either the highest point of a square or the lowest point depending on the elevation feature.

Methods

The first step for the activity was to create a coordinate system. Our group marked out 8 centimeter incriminates on the box. Our X coordinates were the width or the short-side of the box with the length or long-side being our Y coordinates. The group ended up with 13 points on the X and 29 on the Y. The top of the box was used as sea level.

Photo 1: The planter box before surface creation

The next step was to create the features. Again, these features were a ridge, hill, depression, valley, and plain. The group compacted the snow to higher elevations to create the ridge and hill, the valley was created by making a meandering feature at low elevations, the depression was created by digging down below the designated sea level, and the plain was made flat at sea level.

Photo 2: Completed surface

After the creation of our survey area the group made a grid. The grid was made using the 8 centimeter incriminates and string. The string ran across the X and Y coordinates. The grid was used to locate the elevation of the X and Y coordinates. The group used centimeters on a meter stick to record the elevation. The elevation range was from -12 cm to 14 cm. To measure the elevation our group used the base level and either added for the ridge and hill or subtracted for the depression and valley. The plain was consistent at 0 throughout.

After the data collection we entered all the data into an Excel spreadsheet and formatted it for importation into ArcGIS.

Photo 3: Completed surface with grid

Discussion

This was activity was very interesting and fun to do. Even though it was cold I feel that our group had a solid area made. I have never done anything like this before and it will be useful to have when I look for further endeavors. I think that using negative numbers worked well because then we can see the spread of elevations much easier in Arc. The toughest parts were the cold and the snow which had a hindrance of the project from the get go.

Conclusion

The exercise was a good learning experience which is always useful. Using a grid for X and Y coordinates a good idea. Collecting data like this brings a whole new knowledge and experience to people. I am willing to bet that not many have done this before. The next step is to place all the points into Arc and create various elevation models.