Terrain Surveying with a TOPCON Total Station

Introduction: In more critical and precise applications, a total station can be used to survey the surface of an area. The total station uses both distance and azimuth as well as an elevation to record and plot the points selected by the operators. The base stations location is plotted using a GPS receiver. Using that location as a reference, points in the survey area are captured using a laser and reflective prism by the base station. The base station emits a laser that hits the prism at the point location, then relays the information via Bluetooth to the GPS receiver. The distance to that point is recorded and automatically calculated into an x, y, z position based again on the base station’s original GPS location and the use of a backsight. The backsight provides the base station a reference to north. Without this reference, the points would only be relative to that single base station location and not real world location. In this exercise, a 1 hectare section of the University of Wisconsin-Eau Claire campus mall was to be surveyed to capture the micro-topography. A TOPCON GTS-250 series total station with GMS-2 receiver were used to collect the positions and elevation data from the hectare plot.

Figure 1: The new UW-Eau Claire campus mall was formerly the home of the old Davies Student Center. Now the space is used as a seating and performance area for campus events. 

Study Area: The campus mall of the University of Wisconsin-Eau Claire has undergone major construction in the last couple years. The area was previously occupied by the old Davies student center but now is a new green space with seating and performance areas. This opened up the center of campus for different events provided by the University’s numerous organizations (Figure 1). The seating area is a miniature amphitheater with a gentle slope down to the new brick staging area.

Methods:

Figure 2: When setting up the total station, one has to step with care around the legs of the tripod. This prevents the legs from settling more after the station is leveled. By course then fine adjusting the level using the legs, fine adjustment is quicker and easier with the adjustment knobs at the base of the total station. 

        Setting up: Before starting to collect data, the survey plot and base station need to be properly setup. The survey hectare was measured using a pace count. Since a hectare is 100 x 100 meters, the pace counts measured in the previous navigation exercise was applied. The pacer placed a flag at each corner of the survey area. This provided a rough measurement for what area needed to be captured using the total station. With the hectare now set, a location for the base station was selected. The tripod was then set and secured over that location. When setting up the tripod and total station, it is important to make sure that the legs of the tripod are wide enough to provide stability and the tripod is at a comfortable height to work with (Figure 2). Using the level on the tripod, the station was “rough” leveled then more precisely leveled using the fine adjustment tools on the TOPCON station. Once the station was level, the GPS location and backsight information can be set. It is important to check to make sure the Bluetooth is enabled on both the station and the receiver. The settings – parameters menu on the total station allows you to turn the Bluetooth on. The “B” icon will the visible on the home screen once the Bluetooth is connected to the receiver. Now using the GMS-2 receiver, the base station GPS location was collected. The averaged location named “OCC1” for occupied point 1 was then able to be selected from a list to be assigned as the base station’s location in the TOPSURV software on the GMS-2. Next was to set the backsight in the observation – total station menu. Using a land mark and flag, the azimuth from the base station to the point was measured. A TruPulse laser range finder provided a precise azimuth which was then set as the default backsight on the station. Since the goal of the exercise was to capture the micro-topography, it is also important to set a base height for the station and prism rod. Using a measuring tape and the designated mark on the TOPCON station, the height was measured then set in the menu. The height of the prism rod is marked on the rod itself which was kept at 2 meters.

        Data Collection: Before evening thinking about collecting points, make sure that the black locking knobs on the total station are facing away from the viewing lens. If they are on the same side you are working on, the station will not allow you to collect any data points. Now that is cleared up, the surface data can be collected. The rod operator will walk out to the corner of the hectare plot and hold the prism level facing the total station. The total station operator will then align the view finder cross hairs with the prism rod and collects the point with the GMS-2. Once the GMS-2 notifies that the point has been collected, the rod operator will move and the collection process with repeat. The area was surveyed at 6-7 pace intervals between collection points.

Figure 3: The data exported from the GMS-2 to a text file result in this form. The point name, y location, x location, and z locations are listed from left to right. When opening the text file in Excel, make sure to select the comma as the deliminator and not the default tab setting. This will keep each set of information values in their own columns, x in one, y in another and so on. 

        Exporting the Data: From the job menu on the GMS-2, select export – to file. Choose points and export as a text file. The text file keeps the x, y, and z information (Figure 3). If the file is exported as a shapefile, just the locations will be kept without the assigned x, y, and z coordinates. Without the coordinates, just the points would be able to be mapped not the surface model. Once the text file is created, transfer the file from the GMS-2 to the computer with Active Sync.

        Creating the Surface model: The new text file created from the GMS-2 was opened in Microsoft Excel. In the dialog box, make sure that the comma is used as the deliminator and NOT tab. The column headings were checked to ensure that the correct data values were listed. In the text file, the X and Y values were switched and needed to be labeled properly before the excel table was saved. Next the excel table with the point values was imported into ArcScene. This process is the same as described in the previous “Terrain Survey” exercise. Right click “Layers” under the table of contents. From the menu select “add data” and browse to find the excel table. Once the table has been added to the layer, right click the table and select “display xy data” from the menu. The default values will be set in the dialog box so verify that the x, y, and z values are all correctly assigned and selected to be displayed. Once the points are displayed in the map area, the feature class can be exported to save the display values with each point position. Without exporting the feature class, the individual point values are lost. Now using the point feature class, interpolation to create the surface model was completed. Based on the results from the interpolation methods explored in the previous “terrain survey” exercise, the Kriging interpolation was chosen to create the surface model. The Kriging interpolation was performed by running the “Kriging” tool from the ArcGIS toolbox. To run the tool, open ArcToolbox and expand the “3D analysis tools” toolset. From the “Raster Interpolation” toolset, select “Kriging”. The tool window will open. Use the point feature class as the “input features”. Make sure to select the Z field as the “Z value field” to make sure the tool uses the elevation values in the interpolation. Name the output raster, accept the all the default values, and select OK to run the interpolation.

Figure 4: The collected survey points were used to create a surface via Kriging interpolation. The occupy point, or location of the total station, is represented by the blue dot towards the center of the surface. Areas with larger changes in elevation were surveyed at higher point densities. This can be seen in the low lying area around what is Little Niagara Creek. 

Results/Discussion: The surface model generated by the Kriging interpolation did represent the real world surface of the UW-Eau Claire campus mall (Figure 4). Because the grade or slope of the hectare was gradual, there isn’t a drastic change in elevation which is mimicked in the model (Figure 5). The areas where the slope was steeper, more survey points were collected. This is demonstrated by the area surrounding the Little Niagara Creek. The banks of the creek were in the low-lying area of the mall, therefore the surrounding approach to the creek displayed most of the elevation change over the hectare.

Figure 5: The profile of the interpolated surface is relatively accurate to the real world area surveyed. The campus green space gradually slopes to the creek with seating on the slopes. The slope levels out towards the base of the creek due to a staging area for campus events. 

As noted before, we first had a problem with collecting survey points due to the locking knobs on the total station being on the same side we were viewing from. Once we rotated the view finder around to the other side, the points were able to be collected successfully. When importing the text file, the x and y coordinates were listed in y, x order. The table needed to be labeled properly before added to the map document in ArcScene. If the columns weren’t labeled it is quite possible to assign the wrong values to the x, y and z fields when displaying the data. This would result in a misrepresentation of the surveyed hectare on the mall.

Conclusion: The use of a total station when surveying a terrain is a very powerful tool, but the accuracy of the survey is only that of the GPS used to record the data. Because the location of the total station is used to reference all other measured points, the accuracy of that first point determines the accuracy of all the later collected data. The degree and precision at which the station collects data is extremely high regardless. The laser and prism allows the station to report high accuracy data points even if the prism rod is hundreds of feet or meters away from the station. This was not the case with TruPulse range finder which was used in the previous distance azimuth survey. The ability for the station to collect and automatically correct the data for x, y, and z positioning is a great feature to save computing and data prepping time.

UAS Field Day: 1

Unmanned aerial systems (UAS) are becoming more and more common place in the general public. Model rockets, helicopter kits, balloons, and even kites are possible systems to which a camera or sensor can be attached. Imagery (with some computer software processing) can be collected using low budget UAS and still be reliable to the user. Like all GIS projects, what the topic of interest and the area needed to survey determines how you will need to collect data. The images below are a few of the systems the class was able to see demonstrated at the soccer fields by the Eau Claire Indoor Sports Center. Plus, who doesn't like to be outside on a 60° day after a brutal Wisconsin winter in Eau Claire, WI.

Equipment:

Figure 1 (left) and 2 (right): In a multidisciplinary research venture between the geography and physics departments of UW-Eau Claire, the design and functionality of a roto-copter UAS was demonstrated for the geospatial field methods class. Both maneuverability and autopilot software were demonstrated in the 20 minute flight time.  

Figure 3 (left) and 4 (right): Roto-copters have several setup options. The figure 3 copter is the one designed by the joint research effort through UW-Eau Claire and the figure 4 copter is owned by Dr. Hupy. Dr. Hupy's copter is fitted with a gyroscope mount for a digital camera. This allows the camera to remain level to photograph while the copter is banking or turning to compensate for win or flight plans. 

Figure 5: A side-by-side comparison of the research copter (left) and Dr. Hupy's copter (right/back).  The research copter has 6 arms but only single bladed. Dr. Hupy's only has 3 arms but has double blades, one on the top and one on the underside of each arm. Depending on what the payload and flying conditions are, either setup could be beneficial. 

Figure 6 (left) and 7 (right): UAS aren't all high cost. Something as simple as a kite can capture images from the air on a small budget. This kite is 8 feet wide and as long as there's a steady wind, provides a stable option for aerial photos.

Figure 8 (left) and 9 (right): For this demonstration, a digital camera was attached to the kite string using less than 5$ worth of hardware supplies. A couple clips to wrap the kite string around, 2 flat mounting brackets, and some string is all it takes to built a digital camera sling. 

Figures 10 and 11: Once the digital camera is secure to the kite string, the kite string is let out to allow the camera to be carried high into the air. By setting the camera to take pictures in a set interval for a determined duration, all you have to worry about it flying the kite. We let about 300ft worth of string out for the kite.

Figure 12 and 13: Another type of UAS is a rocket. Model rockets come is single, double, or even triple stages. The stage determines how many engines the rocket can hold. The rocket shown is 2 stages, meaning it holds 2 engines. The first will be ignited by the electric ignition box, then the second will be ignited by the end burst of the first engine. We attached a small video camera to the body tube to record the flight from the sky. 

      Camera Results:

Figure 14: The photos above are still shots captured by the Cannon digital camera that we suspended from the kite. Even with the wind blowing strong, the kite provided a nice, stable positing for the camera to take clear photos of the surrounding area. 

Figure 15: This is the video captured by the small camera we attached to the rocket. Only the first stage fired correctly, but still made for an entertaining minute to watch. 

Database Creation for Micro-Climate Mapping

When starting a geospatial project, it is import to consider exactly what data you are going to be collecting for the project before you venture off into the field. By planning an organized geodatabase, the data collected from the field can be imported into ArcGIS in a more user friendly manner. In this GIS exercise, a geodatabase will be created to hold data about micro-climates around the University of Wisconsin-Eau Claire campus.

 How can a geodatabase be used in the field?

 New hand-held GPS units are becoming portable computers. A user can create feature classes and log data directly into a database out in the field without needing a full version of ArcGIS. These features, however convenient they seem now, can be a double edged sword. If multiple feature classes are created “on the fly” in the field, data are separated into those separate feature classes. If the user considers what they want to record for data before leaving the lab to the site, all the data can be logged into a singular feature class. Creating feature classes out in the field also can lead to input data errors which can misrepresent information, costing more time in the future. Using a singular feature class that holds all the attributes one wishes to record in the field, stores all the information for each location together instead of separate feature classes. Separate classes open the possibility that data may be assigned to wrong locations or may be forgotten and not recorded. Also, by planning the geodatabase beforehand, all fields or attributes collected, can be assigned a range or code to help eliminate data entry errors to help improve the data integrity. These ranges or coded values are Domains. Domains ranges or codes can be applied to a field so only values that fall in that range or assigned code are allowed to be recorded into the feature class. The same domain may be set to multiple fields if those fields have the same data range or codes. Domains can also be associated with all different field types available in a feature class, which include: short integer (short), long integer (long), single precision floating point numbers (float), double precision floating point numbers (double), alphanumeric characters (text), data and time data (date). When assigning the domains, only those that match the field type of the field in question will be available to assign. This will be demonstrated below. As domains are created for the fields, they are saved inside the geodatabase and can be accessed or edited throughout the project. With all the domains set to the fields created in the single feature class, when the database is loaded onto the portable unit, data entry will be faster and more accurate for analysis later.

Using a Geodatabase in Microclimate mapping: What information needs to be collected?

• ·         Temperature
• ·         Dew point
• ·         Wind speed/direction
• ·         Snow depth
• ·         Relative Humidity
• ·         Time
• ·         Notes of the surrounding area  

 

Figure 1: From the geodatabase properties menu, two tabs are displayed. The domains are created here with all descriptions, codes, and ranges to later be assigned to feature class fields. 

Domains: To create new domains for use in feature classes, right click on the geodatabase and select properties. A new window will open having two tabs: general and domains (Figure 1). The domain tab is where you can name and assign parameters for each field you wish to collect. For the information listed above, the following domains were created:

• ·         Temperature – Float, type: range, minimum 0 maximum 99
• ·         Dew point – Float, range, 0-100
• ·         Wind speed/direction – float, range, 0-360
• ·         Snow depth – float, range, 0-36
• ·         Relative Humidity – float, range, 0-100
• ·         Time – short integer, range, 0-2400
• ·         Notes of the surrounding area – Text

Once all the needed domains are created, click OK. The domains will now be listed in the property field when created fields for a new feature class. Only those domains that match the data type for a field will be listed in the menu.     

Figure 2: The feature class properties will display all fields listed in the feature class along with any set parameters such as domains. 

Feature classes: For this project, each spot surveyed for microclimate data are going to be saved as a point feature. Since multiple features can be linked to a single point, it’s best to use a single feature class with multiple fields. Each piece of information listed above will have its own field in the feature class (Figure 2). To create a feature class right click on the file geodatabase you wish to add the data to. Then select new-feature class. A new window will open leading you through the process of creating the new feature class. 

Figure 3: When creating a new feature class in a geodatabase, a new window will open. Follow the prompts to define the projection then at this window the fields will be created. Each field has an assigned data type and domain associated with what is being collected.

You will first name and assign a coordinate system, then proceed to the window that prompts for field names and data types (Figure 3). This is where you will add the field title for each piece of data collected. The data type will depend on the field and can be text or numeric. Here is also where you will assign the domains created before to each field. In the Field properties box, click the area next to “Domain”. This will have a drop down box where you will be able to select the correct domain for each field in the feature class. Once all the fields are created and domains assigned, click finish to setup the feature class.

Navigation Part 1: Map Construction and Bearing Navigation

Introduction: The use of a compass as a tool to navigate the globe has spanned centuries. Without a good compass and map, sailors wouldn’t have been able to navigate seas limiting the extent of trade and expansion. The ability to use these tools to navigate has become somewhat of a lost art so to speak with the invention of global position systems or GPS. A location can be digitally entered and saved into these systems and the device will navigate the user to those logged locations; however, without the use of a map too, the path a user would travel may not be the most direct or advantageous. GPS also requires a strong satellite signal to operate with relative accuracy which isn’t always possible in dense vegetation or terrain one might find themselves in. This is where the simple compass beats out the fancy bells and whistles of GPS. Using a map and the bearings or directions of travel from a compass, one can successfully navigate as well or even better than a GPS. This exercise will demonstrate the time-tested method of compass navigation.

  

Maps: A navigator is only as good as their map. If the map representation of the area one wishes to navigate is incorrect, there is little chance that even with GPS navigation would be successful. For this exercise, we created our own maps as tools for later navigation races. The area where our navigation course is set up is called The Priory and is owned by the University of Wisconsin – Eau Claire Foundation. The Priory is 112 acres and is the home of a former monastery. The University foundation purchased and leased the land and structures to the University of Wisconsin – Eau Claire to provide a location for the Children’s Nature Academy and use the housing as a new resident hall for students. The area is mostly forested with stark topography created by the prehistoric ridge. Since the location wanting to navigate is local, a large scale map is best requiring a coordinate system and projection that has a high level of accuracy for these scales. It is also important to identify what information is necessary and what is noise. A navigation map needs to have essentials such as topography to see if in any mountains will be crossed in a path from point to point and several landmarks that a navigator can use as a reference. If the map is too busy or noisy, navigation is more difficult since the map is hard to read. You want to be able to quickly understand and find relatively where you are situated rather than spend hours just trying to find where you started. Data including a 5-meter topography and navigation boundary were acquired from a prepared database by the instructor Joe Hupy. A topography of an area could be acquired by using a 15-minute topographic map that is produced by the United States Geological Survey (USGS). The background satellite image was added in ArcMap using ESRI basemap datasets.  

Methods: 

Map Creation in ESRI ArcMap: As mentioned above, coordinate system and projection are the most important aspect to consider when creating a map. The local, large scale needed for a navigation map of The Priory required the accuracy and usability of a specific projection. The geographic coordinate system for North America updated in 1983 provided the base for the necessary projection. Using the North American Datum 1983 (NAD 83) Wisconsin Transverse Mercator projected allowed for the local level accuracy required. The state system provides better real world accuracy than just leaving the projection at NAD 83 since more local survey points were logged and referenced.

Figure 1: A navigation map including 5 meter topography and an aerial image background for the Priory was created using ESRI ArcMap. A measured grid displaying in UTM is overlaid to aid in locating destination points. 

The map units of meters also helps monitor traveling distance in the calculations later to come when planning a route. Now that the projection was chosen, the data were added. An ESRI aerial image base map was used as the background but was set to 70% transparency to keep the map readable but still be able to use the image as a reference. The navigation boundary, structure boundaries, and 5-meter topography provided from the prepared database were then added over the image. Like the aerial image, the structure boundary feature class was also displayed at a 50% transparency to reduce map noise. The topography class was also displayed with the elevation labels to keep slopes orientated in the field with those on the map (Figure 1). For plotting the destinations, a graticule and map grid were created to assist in the accuracy of the locations.

Figure 2: This is the same navigation map created before only is displayed using a decimal degree grid overlay. The decimal degree reference lines will aid in plotting points reported in degrees, minute, seconds or just decimal degrees.

Like mapping on a graph, the grids are used as a reference to help locate the positions or coordinates for the destinations and used to help determine the distance to those destinations. A grid using the Universal Transverse Mercator (UTM) measurements was added to plot locations given in meters or other UTM measurements (Figure 1) and another grid or graticule was added to help plot points given in decimal degrees from the Geographic Coordinate System (GCS) (Figure 2). The UTM grid lines always run vertically on the map regardless of where true north lies. This doesn’t always provide accurate locations for point destinations but at this large scale, won’t impact results greatly. Unlike the UTM grid, the GCS grid lines follow true north so are not vertical but are skewed to reflect the declination for the Priory location. This can provide better point locations when using a compass but, again, at this large scale, the discrepancies between UTM and GCS are minimized. The scale and representative fraction for the map were assigned and added by ArcMap. These are crucial in navigation as described shortly.

The Compass: The compass is an incredibly simple yet powerful tool. Compass navigation or orienteering is simple with a little bit of practice and knowledge of the compass itself. The most obvious feature is the bezel. The bezel is the rotating dial that holds the marked degree hashes used to determine bearings or direction you wish to travel. In the middle of the bezel you will find the needle as well as several index lines that will be explained in the Navigation section. The top of the compass has an arrow pointing away from the bezel this is your direction of travel. To use a compass, it has to be held flat in one’s hand parallel to the ground to allow the needle to rotate freely, and it is important to remember to keep the compass away from metal objects such as zippers in a jacket or a ring on your hand. The metal can affect the bearing from the needle. The needle has a red point and white point. The red always points to North therefore the white always to the South. The adage “keep red in the shed” refers to keeping the red north point in the designated red “shed” marked on the bezel. This is important for keeping the correct bearing when traveling.    

Navigation: First task to complete when navigating on foot is to determine a pace count. A pace is counted when a person is walking and the same foot is set on the ground, so for example 4 normal steps are actually 2 paces. For the later navigation, my pace count was 64 paces in 100 meters. Each person’s pace will be unique, so if you are going to count with a friend, don’t worry if you get different results. When pacing, it is important to try to take as normal sized steps as possible since this is how you will be walking on trails or through the woods. Depending on the terrain you wish to navigate, an addition of 20 or more paces may be necessary if steep slopes are going to be crossed. So after determining a pace count the next task is to plot your destination points on the maps. If the destination coordinates are known, a user can reference the grid or graticule that was added to the map to help accurately position the points on the map. If the coordinates are unknown but the destination is a landform, that’s okay too you can still use the compass to travel successfully. Not only do you have to know the destinations but also the starting location. This will be the first point where you will have to use a bearing and distance. Once all the points are plotted on the map, the compass can determine the bearings. To assign bearings, first draw a line connecting the starting point and the first destination point. Then place the compass side along the drawn line making sure the direction of travel arrow is indeed pointing toward the destination and turn the bezel to line the index lines inside up with the North and South grid lines on the map. The number or degree now lining up with the mark with the direction of travel arrow is the bearing to follow when traveling. When moving toward your destination you have to be careful to keep “red in the shed”. This is easier to accomplish if you choose objects or features that are in the line of travel and pace to them and check your bearing. By splitting the distance into chunks it helps to stay on line and not stray resulting in a different destination. BUT WAIT! Don’t head off into the woods yet, you need to know how far to walk! Measure the draw line between the starting and destination points, then using the map scale or representative fraction, figure how long the path is in real distance. Once you have the real world distance, convert that number into paces using your pace count. So if a map’s representative fraction is 1:100, 1 meter on the map would be 100 meters in the real world. This would mean a distance measured to be 250 meters would actually be 25,000 meters. Then using the pace count, 64 in 100 meters in my case, determine the real world pace count, 64*(25,000/100). So I would travel 16,000 paces if the topography was relatively flat. Remember if steep slopes are in the path of travel, additional paces should be added to compensate for the smaller step size. The generic equation for distance to pace is PACE*(REAL WORLD DISTANCE/ PACED DISTANCE). As explained earlier, not only is finding closer features that are on line better to follow a bearing but it also helps to break up the pace count since counting to 16,000 isn’t the easiest to remember when you’re wandering through the woods. When using features, just remember to log how many paces it was to that feature then subtract it from the initial pace count needed to reach your destination.          

Conducting a Distance Azimuth Survey

Introduction: In the age of technology, surveying and mapping surface features has become more time efficient and digital. With the use of a GPS or rangefinder, a user can map an acre plot and record attribute data in one setting, however, as will all technology and field work, situations are unpredictable. If the technology were to fail, a user would then have to survey the plot by means of other techniques, one being measuring distance and azimuth to the selected features. Standing in a single spot and surveying using a compass and tape measure or paces, one can map the general arrangement of the features in question. When using a compass, it is important to remember that magnetic fields can affect the readings and true angles. The magnetic declination of a location needs to be accounted for and applied to the azimuth readings. This makes data processing more time consuming in the long run but when technology fails you, a little math can go a long ways.

Figure 1: Owen Park in the City of Eau Claire, WI is nestled next to the Chippewa River. The past site of an electrical plant, the 11-acre park now offers an assortment of recreational opportunities to the local community. 

Survey Location – Owen Park, Eau Claire, Wisconsin, USA: In 1913, lumber baron John S. Owen donated 11-acres of land to the city of Eau Claire as a hope to create a city of parks. Today, those 11-acres are still used as a park that bares Owen’s name. A band shell, state bike trail, numerous benches, tennis courts, and large trees cover the area. Owen Park is a community favorite location for festivals and gatherings throughout the year, from Blues concerts to the Eau Claire Marathon. Topography of the park is relatively flat, and is commonly flooded by Chippewa River.       

Methods:

Figure 2: The TruPulse 360B laser ranger finder was mounted on a tripod for stability. From the single location shown, 98 survey points were measured recording slope distance in meters, Azimuth in degrees, a point characteristic, and a count ID.

Collecting Survey Points: For the survey, we used a TruPulse 360 B Series laser rangefinder to record the slope distance and azimuth to the chosen points. The rangefinder was mounted on a tripod to limit movement to prevent discrepancies in the azimuth readings from point to point since only one survey location was chosen (Figure 2). The single location allowed all points surveyed to be assigned the same starting coordinates, removing the possibility of error. The location chosen as the survey point was the northeast corner of the tennis courts. This point is easily identifiable from an aerial photograph which is crucial to assigning starting coordinate values. Using the rangefinder, 98 features from trees to benches were surveyed with their distance, azimuth from the start, description of the point feature, and the count. 

Figure 3: The XY coordinate position for the survey location was assigned using aerial images and Google Earth. The position recorded by Google Earth was presented in Degrees Minutes Seconds and needed to be converted to decimal degrees before being assigned to each survey point. 

Finding Coordinates for the Starting Location(s): The coordinate position of the starting survey point needed to be assigned. Using Google Earth, a place marker was set at the northeast corner of the tennis courts in Owen Park (Figure 3). The assigned location was 44°48’9.1’N, 91°30’0.67”W. This location needed to be converted to decimal degrees to allow ArcGIS to read the coordinates. By multiplying the seconds by 60, they are converted into minutes. Adding the converted seconds to the minutes and dividing the new total minutes by 60 will result in degrees. This value is then added to the observed degrees to finish the conversion of the location to decimal degrees. This process is repeated for both the latitude and longitudinal coordinates resulting in the location 44.802531N, 91.500183W. In the conversion, make sure to hold at least 6 decimal values to allow proper and more accurate results in ArcGIS.

Figure 4: The data recorded from the laser range finder was organized into a Microsoft Excel data table. Each attribute or value was arranged into its own column for each point surveyed. 

Creating the Data Table:  The data collected from the survey was organized into a Microsoft Excel table to allow ArcGIS to import it. For the table, each attribute was listed in its own column: Number ID or count, Type, Slope Distance (SD) in meters, Azimuth in degrees, X (Longitude of shooting location), and Y (Latitude of shooting location) (Figure 4). The distances, and Azimuth values need to be extended to 6 decimals in the table to match those of the X,Y values of the shooting location calculated in the previous step.   

Importing the Table: A geodatabase was created to hold the files created in this exercise to help organize the project. To create a new geodatabase, right click a folder in ArcCatalog where you wish to store the database. From the menu select “New” – “File Geodatabase”. A new database will be displayed in the selected folder. Properties can be assigned to this new database by right clicking the database, selecting properties from the menu, then adding the desired information, but for this exercise the properties will be kept at the defaults. Once the database was created, the document work environments were set to add all new files to the database.

Figure 5: The map document properties window located under the file tab, allows the user to set a default geodatabase to store the output from tools or other processes. The properties window also provides a setting for ArcGIS to store the relative pathnames of data sources. This prevents information from being lost if moved from one folder to the next.  

By clicking File – Map Document Properties, a window opens allowing you to choose the default workspace. Under the default geodatabase section, click the folder and browse to set the workspace to the new geodatabase. Then before closing the map document properties window, check the box “store relative pathnames to data sources” (Figure 5). This allows the program to follow locations of files if they are moved from one folder to the next without having to reassign the pathways. To verify that the workspace was set to the new geodatabase, right click in ArcToolbox and select “Environments”. Under the workspace tab, two boxes should appear: “Current Workspace” and “Scratch Workspace”. Make sure that both read the location of the new geodatabase, if not browse and assign that location to the workspace. All output features from tools will now be added and stored in that location instead of a default “catch all” database. Now with the environments set and the database created, the data table can be imported directly to the geodatabase. Right click the geodatabase and select “Import – Table (single)”. The Table-to-Table tool will open. Browse and assign the excel data table as the “Input Rows” field. The output location is automatically set to the geodatabase so the table just needs to be named. After the table’s named, click “ok” to run the tool. The table should then be added to the database as well as the document.

Figure 6: The output feature class of the Bearing Distance to Line tool in ArcGIS results in a series of lines based on the distance and azimuth from the starting location to the survey point. The features were displayed over an aerial photograph for comparison. 

Displaying the Survey Points: Now that the table is in the geodatabase, the survey features can be displayed on a map. Because the actual coordinate positions aren’t known for the features, the bearing distance to line tool will be used first to locate the features (Figure 6). Open ArcToolbox and select Data Management – Features – Bearing Distance to Line. Set the “Input Table” to the table containing the survey feature information. Since the table is in the geodatabase and in the document, it should be listed in the dropdown box. Then name the output feature class that will be added to the geodatabase. Set the “X” and “Y” field to the respective columns of the table. Make sure the Longitude coordinate is listed as X and Latitude as Y. Next the “Distance field” is the slope distance and “Bearing field” is the Azimuth both are the recorded values from the rangefinder. Before running the tool, make sure that the spatial reference is set to the same as the map document. This exercise used the default projection WGS84 Web Mercator (Auxiliary Sphere).

Figure 7: The Feature Vertices to Points tool in ArcGIS uses the vertex locations of a line or polygon feature to assign a point feature. By using this tool, the survey points could be added independently of the assigned lines from the Bearing Distance to Line tool.  

The “Feature Vertices to Points” tool will convert the line feature class created by the “Bearing Distance to Line” tool to a point feature class. Again in ArcToolbox – Data Management – Features, select “Feature Vertices to Points”. Set the output feature class from the bearing distance tool to the “input features” and name the new output feature class that will be added to the geodatabase. Before running the tool, switch the “point type” to “END” instead of “ALL”. This will instruct the tool to only place a point feature at the end or last vertex of each line instead of the start and end (Figure 7). This prevents the output feature class from having doubles for each survey feature. Once everything is set, click “Ok” to run the tool.

Displaying the Survey Locations (optional):  For cartographic purposes, the user could add a feature class that contains the locations of the stationary survey points. A table with the X,Y coordinates could be added then displayed using the method discussed in previous exercises, but since only 1 location was used, a point was created in a new feature class to mark the location with the help of aerial photographs. Add an aerial image base map from the “add data” button on the tool bar and locate the study area, Owen Park in Eau Claire, WI in this exercise. Then, right click on the geodatabase and select New – Feature Class. In the window, name the feature class and select “point” from the dropdown menu in the Type Field section. Click next to set the coordinate system, again, making sure that it is the same as the map document. Continue accepting the XY tolerance and storage configuration defaults. Click finish and the feature class will be added to the geodatabase and the map document. Right click on the new feature class and select “Edit Features – Start Editing”. To add a point in the survey location, click the “create features” button on the editor toolbar. From the Creature Features window, select the new point feature class then using the aerial image, click the position of the survey location, the northeast corner of the tennis courts. This will add the point to the feature class. Click the dropdown menu on the editor toolbar, “save the edits” then “stop editing” the feature class. Now the stationary survey location can be displayed as a reference on the map.  

Discussion:Using the laser rangefinder instead of a standard compass had several advantages. The electronic technology built into the rangefinder automatically accounts for variation in viewing pitch which allowed the azimuth to be measured at any angle. If a standard compass had been used, it would have to be held level to allow the needle to rotate. This can influence angles if survey points were being measured from a slope. Also declination from true north occurs more with the use of standard compasses rather than the electronic counterparts. Declination or deviation from true north occurs at different severities based on location on the Earth’s surface. Terrain, development or even metal objects can skew the reading of a compass. The declination in Eau Claire, WI is about 1°4’48”W or about 1.867°W from true north. This means that 1.867° should be added to any compass readings recorded to correct the value to reflect the true direction. The electronic rangefinder wasn’t a perfect recording tool and presented other complications however. As distance from the survey location to point increased, the accuracy of its real world location decreased (Figure 7). The trees and poles surveyed across the park ended up being located in the Chippewa River. It was also observed that the laser’s focus was less at greater distance. Several points were measured through openings between tree branches and the laser typically reported the distance to the object trying to survey through rather than the intended point. This limited the surveyed points to direct line of sight which won’t always possible in field situations. Another problem was encountered when assigning the starting survey location to the measured points.

Figure 8: A comparison of starting locations and results of the bearing distance to line tool from locations assigned by ArcGIS (yellow) and Google Earth (blue).

A location was assigned using values obtained from ArcGIS and values using Google Earth. The ArcGIS location when mapped with the tools described resulted in the points being plotted several meters incorrectly, but the Google Earth location converted from degrees minutes seconds to decimal degrees used the correct starting location as a reference for the measured points (Figure 8). It could be possible that the accuracy of the images used to assign the point location to the starting point was less than those of Google Earth and since all other points were measured from that single starting location, any variance in that location would cause a chain reaction in the rest. Sometimes technology isn’t as reliable as the “old school” methods of a compass and pace count or tape measure. Having the capability to me versatile and adapt to what is needed in the field will help provide the best quality information to a client.

 

Unmanned Aerial System (UAS) Scenario Evaluations

This is one of the many forms of an unmanned aerial system. Multicopters (pictured) can be used in situations that require precision in tight spaces. Vertical takeoffs and landings make multicopters one of the most versatile UAS.

Introduction: With the fast paced development of geospatial technology, applications of the new information systems are growing exponentially. The perfection of remote sensors in functionality and size has expanded the range of what vehicles or systems can be fitted to carry and capture information. Tasks that were once only capable on foot or in person are now able to be done via satellite or unmanned aerial systems (UAS). Unmanned systems are both used by the military as well as by civilian contractors and are capable of unpiloted flight. Several types of UAS exist and each can provide different sets of benefits to evaluate tasks quicker and, in most cases, provide a less costly alternative.   

Fixed-wing unmanned aerial vehicles require a strip to takeoff and land. The ability to glide and carry large payloads offers the consultant a wide range of options for sensors and other hardware to complete a survey.  

Fixed-Wing Craft: Fixed wing vehicles are the most familiar or “search image” for what people think a UAV or UAS is. These crafts have two fixed wings as the name suggest that allow gliding and stable flight with greater payloads and longer flight times as compared to copters. The wings allow the craft to glide in an event of power failure which copters are not able to do providing a better peace of mind for the pilot; however, the fixed wings don’t allow the craft the ability to hover in a single spot or allow for a vertical takeoff. Like any standard gliders or airplane, a fixed wing craft requires a runway for takeoff and landing. Fixed wing crafts are available in gasoline or electric power. The gas powered flights can last about 10 hours and electric about 45 minutes to an hour depending on the payload.

Helicopters, with the ability to hover, provide the user to focus on a specific area of interest or reach areas quickly and precisely. Since they takeoff and land vertically, a helicopter can be launched in a confined space that a fixed wing craft would be unable to. 

Helicopter: Helicopters are operated by a single lifting motor with two or more blades. The lifting motor allows for a vertical takeoff and landing allowing the system to be launched in a limited area. The blades are able to be pitched to compensate for winds and directional change. For an operator, it is safer for the motor and radio equipment on board to have separate power sources. This not only helps to return the craft but also increases safety when working or performing maintenance on the system. Copters are fast and efficient but can create vibrations that can reduce quality of video or information. The location and mounting systems can limit the vibration allowing for accurate data. Helicopters are powered by either gasoline or electricity. Gas powered systems have a flight time of 4 to 5 hours while electric powered systems are limited to 20 to 90 minutes. Flight times are limited by payload as well as configuration of the system.

Multicopters provide yet an even more stable and controlled response in a UAS. With multiple arms, balance in winds and flight allow a multicopter to be the most versatile and reliable UAS. 

Multicopter: Multicopters utilize several rotating blades to achieve lift and control. Each blade set is controlled by a separate motor allowing the system to balance, provide lift, and have precise directional controls when hovering. The multiple arms allow for a higher degree of safety when performing maintenance tasks by operating at smaller radii than a helicopter. The multiple blades or arms of the system also require more powerful computer processors without which the craft can’t fly; however, the varying designs for multicopters offer a degree of flexibility unavailable to helicopters or fixed wing crafts in the location of sensors and other operating equipment. This variation also enables the multicopter to be more stable in high wind conditions compared to other aerial vehicles but with more arms on the multicopter, the shorter the flight time. The stability is great for beginner operators as well as those who need the stability to focus on an area in great detail.  

What do you need: There are several pieces of equipment that are required for every UAS, some more obvious than others. You will need to consider what you are trying to survey then determine the type of vehicle, autopilot, planning software, and payload the vehicle will be carrying. The vehicle, fixed wing, helicopter, or multicopter will determine which of the systems will be needed as well as determine the size of the payload. APM 2.6 autopilot hardware provides processors, gyroscopes, accelerometers, pressure sensors, and a GPS to any vehicle (ArduPlane for fixed wing ArduCopter for rotary wing) with a reasonable cost at $179.00. The ArduPlane or Copter software allows the user to pre-plan a flight pattern into the system allowing the pilot to monitor the system rather than solely focusing on flying the vehicle. The planning software also ensures that the necessary overlaps for images as well as insuring precise points of interest are located quickly and accurately. In the event of the vehicle flying out of the range of the manual controls or equipment failure, the software provides a failsafe by automatically returning the aircraft to the point of take off. The payload will vary with vehicle and duration of the flight. Longer durations of flight will require smaller payloads since more operating power will be needed. High definition cameras, thermal scanners, infrared scanners, or LiDAR are just a few possible sensors that are capable of being installed on a UAS. Again, which sensors are necessary will depend solely on what the subject of the survey will be.     

Scenarios: There are many real world applications of UAS. The following list provides several examples of those scenarios and provides possible solutions on which UAS and technology would be most helpful to meet the goals of the individual client.

The desert tortoise is a threatened species in the United States. Threatened species are not in danger of extinction but population sizes are small and if not monitored closely may become endangered. With this threatened title, the tortoise habitat is protected under the Endangered Species Act. 

Scenario 1: A military testing range is having problems engaging in conducting its training exercises due to the presence of desert tortoises. They currently spend millions of dollars doing ground based surveys to find their burrows. They want to know if you, as the geographer can find a better solution with UAS.

        Questions: What do we know about the tortoises? What can we use to locate burrows? How large is the testing range? How often are exercises conducted? What is the budget?

        Background: Desert tortoises are herbivores that feed on grasses, wildflowers, and cactus pads that are available in the deserts. Tortoises live in burrows to escape the extreme heat of the environment and lay dormant from November to February. 97% of tortoise burrows are associated with shrub vegetation allowing the tortoise to eat in the spring. The soil needed to create the burrows is also particular to the tortoise. Moisture and texture has to be perfect that it crumbles during digging but is firm not to collapse. Commonly burrows are found in sandy loam soils with gravel and clay not areas with a lot of sand.

        Solutions: With military operations possessing fixed wing aircraft, a possible solution to locate the burrows could be outfitting a UAV or manned aircraft with a few new sensors. The fixed wing UAS has a stable flight with the capability of long flight durations. With the burrows being typically located near dense vegetation, a near infrared scanner would be able to locate those vegetated areas. Next, the suitable soil could be located using variations in moisture content measurable by a short-wave infrared sensor. Areas with higher moisture content will display weaker in the sensor readings due to the absorbance by the water rather than reflectance by the dry sands. Once paired with the vegetation and suitable soil locations, a thermal imager may be capable of locating the entrances of the burrows. The cooler soil would stand out from the stark hot surface of the surrounding areas. An overlay analysis could be performed and those areas that are most suitable for burrows can be mapped providing a guide for later surveys. The use of these sensors can’t be 100% accurate so foot inspections may still be needed but much less intensive than without the UAS.

For years, utility companies have hired helicopters to fly along power lines to perform inspections. This is a very dangerous and therefore costly process that can be reduced with the help of a UAS. 

Scenario 2: A power line company spends lots of money on a helicopter company monitoring and fixing problems on their line. One of the biggest costs is the helicopter having to fly up to these things just to see if there is a problem with the tower. Another issue is the cost of just figuring how to get to the things from the closest airport.

        Questions: How often do problems occur along the power lines?  How much does it cost to get the helicopter out to inspect the line?  Are the lines accessible to ground crews to get close enough quickly enough?  What type of area are the power lines in, populated or rural?

        Solutions: A multicopter would be a good option to perform this task.  A ground crew with the multicopter would get close enough to the power lines that they wish to examine in order to use a multicopter. The UAV multicopter should be installed with a high quality camera and should be able to operate at a relatively low noise level to prevent disturbing wildlife or cattle that may be in the area.  It would also be advantageous to have some way for the copter to detect changes in the electrical field around it so it could detect anything that may be wrong with the power lines. This multicopter has high payload capacity (3kg) for high definition imagery, rotors covered for safety when flying near power lines, is equipped with excellent crash/accident avoidance technology such as its “coming home” function, very stable when holding position for excellent imagery, and comes with some of the best pre-mission programming.  It will cost around $30,000 per multicopter but this will pay off in the long run when considering the company cost paying a helicopter to go out to check the power lines repeatedly.  It’s not an inexpensive start up cost but will pay off in the end, as this is a very reliable model. It may also be a good idea to have a UAV helicopter along as well. If a power line needs to be looked at rapidly due to an emergency, the helicopter can be launched from further away due to its longer range.  The same considerations regarding weight, noise level, image quality, and maneuverability would need to be taken into consideration for the helicopter as for the multicopter.  

Pineapples are a short bush like plant that is commonly grown in tropical areas. As the fruit matures, it rises out of the center of the plant and gradually begins to turn a bright yellow. 

Scenario 3: 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.

        Questions: What type of area is the pineapple plantation in? What is currently being done to assess these problems?

        Background: Pineapple plants are read to harvest when they are in the late stages of their development.  This means that they have over 1/3 of their peel as a yellow color but they haven’t lost all of their green yet. Near infrared reflection has been tested to see whether or not it can be used to detect ripeness of a plant, as the plant gets riper, the NIR tends to decrease.  This fact combined with the fact that when pineapples are ready to harvest they shouldn’t be ripe yet and shouldn’t be harvested until their skin is 1/3 yellow and 2/3 green can help determine the best time to harvest the pineapple.  Using a multi-spectral approach with both visible wavelengths to try and determine color and NIR wavelengths to determine health and whether the plant is ready to harvest.

        Solutions: A gas powered UAV helicopter equipped with a near infrared (NIR) camera sensor which will detect higher reflectance of healthy vegetation will help locate the ripened fruit.  This UAS would require pre-mission software that would allow it to track and cover the whole field recording data spatially.  Ideally this would be done during the day when there is the highest amount of NIR reflection. A gas helicopter would provide the focus and maneuverability needed to survey the pineapples. The size of the field would limit a multicopter to short flights where the helicopter could fly for longer durations. The NIR camera has a high range of reflectance allowing the distinction of healthy and unhealthy vegetation. Healthy vegetation reflects significantly more NIR waves allowing the healthy plants to be displayed more prominently than the unhealthy vegetation.

The Niger River delta is one of the largest in the world and is also one of the most polluted. Stretching thousands of miles across western Africa, the river passes through several oil rich lands increasing the pollution risk. 

Scenario 4: An oil pipeline running through the Niger River delta is showing some signs of leaking. This is impacting both agriculture and loss of revenue to the company.

        Questions: What is the range of possible leaking points in the pipe? Will there be any restricted areas to avoid? Are there fire risks? Will the UAS be flying over populated areas? What time of year will surveying occur?

        Solutions: The survey area is large requiring a UAS with a large antenna which will allow for a longer flight range from the computer base. The best type of craft for this mission would be a gas powered fixed-wing craft. This would allow the payload capacity needed and provide the stability required. The main sensor required on the plane would be a small thermal imaging camera to record the thermal readings of the ground along the pipeline, just after sunset, from which one can deduce the thermal heat capacity of the ground. If there is a leak, the oil will produce a thermal reading that differs from the heat capacity of the surrounding materials.

Surface mines are those at which layers of earth are scraped and dugout then processed to separate the precious metals or stones. The earth is removed until the ore is depleted and operation is no longer profitable by the company. This Russian diamond mine is over 600 feet deep. 

Scenario 5: A mining company wants to get a better idea of the volume they remove each week. They don’t have the money for LiDAR, but want to engage in 3D analysis (Hint: look up point cloud)

        Questions: What is the project budget? How expansive is the mining operation? Is this an open pit mine?

        Solutions: Aerial photos need to be taken of the mine area with a high percent of overlap (>60%). Use of a multicopter or helicopter would provide the control and stability to capture quality images, however if the budget is constrained, the use of a kite may also serve well to photograph the area. From online servers such as Photosynth, the photographs can be uploaded to create a point cloud of the area. A point cloud is a set or fabric of dense points that hold elevation as well as coordinate information. From the point cloud, a digital surface model can be created and be capable of calculating changes in volume along that surface. Like the servers that create the point clouds, there are open source products such as Meshlab that allow the surface calculations to be done. If the budget allows, ArcMap with the 3D analyst extension will also allow the creation of the surface model from the point cloud. With use of the SurfaceVolume tool, ArcMap can also calculate the difference in the surface from a set reference plane allowing the changes in volume to be tracked over time.   

Information complied by: Jake Burandt, Tim Condon, and Brielle Cummings