Activity 8: Developing a Project on ArcCollector

Introduction

Smartphones now hold the same and more capabilities than some GPS units. They are able to locate coordinates and also access online information. With the development of the ArcCollector app, smartphones now enable you to map information and update it live online. The objective of this exercise was to gain practice in creating a map with appropriate features and domains and collect data points using the ArcCollector app. In my project, I mapped squirrels around lower campus to see if there was any distributional pattern between types of squirrels and if there were any behavioral tendencies. Data collection was done on Friday November 27, 2015 between the hours of 2pm and 3.30pm. The study area consisted of all of the University of Wisconsin-Eau Claire lower campus region on the southern side of the Chippewa River foot bridge and the southern path in Putnam Park behind Davies Center. Temperature was approximately 25 degrees F (-3.9 C) and the weather was sunny and calm.

Methods

To begin the activity, I first created a geodatabase to store the domains and then created domains and a feature class in ArcCatalog. I created domains to set acceptable values for attributes regarding the squirrels I would be mapping later. For each domain, I had to choose a type: range domain (set allowable range of values for an attribute) or coded domain (set codes as values for an attribute). I created a coded domain for the squirrel color (grey, red, black, or white), a range domain for date, a range domain for temperature, a coded domain for behavior (eating, watching, or burying food), and a coded domain for location (ground, tree, or garbage can).

To practice, I then created a point feature class from the domain and named it "Squirrels" as this feature class would later be used to collect data points in the ArcCollector app on squirrel locations and behavior. Once this was finished, I published the feature class on ArcGIS online by following the instructions on ArcGIS for preparing data. Once the feature class was published, I created a map on ArcGIS by simply adding a basemap and setting the address to the UWEC campus address so it would zoom in on the study area and added the published feature class to the map. The steps to prepare a map on ArcCollector can be found here. It was then ready for data collection.

The data collection process ran smoothly as it is as simple as clicking the plus symbol to add a point and choosing the correct coded value or entering the correct range value for each of the attributes set by  the domains created previously. I walked the entire area of the southern lower campus and added all the squirrels I could visually spot. I did not to add squirrels if I walked a particular route a second time. This was a measure taken to eliminate any double entries. However, I realized I had made my domains rather poorly. For instance, I had one variable labeled incorrectly and I observed more behaviors than just the couple I had set as codes for the behavior domain.

To fix this, I went back to ArcMap and edited my domains to re-label the incorrect domain and added the code "running" under the Behavior domain. I re-published the feature class to ArcGIS and created a new map on the ArcGIS website. I then collected data in the same manner as before with the new feature class (Fig. 1). Only 22 squirrels were found and mapped. This time, there was no error in the domains.

Fig. 1: Final Domains within the Database created into a Feature Class. This figure shows the Behavior domain highlighted at the top and its code values listed on the bottom.

Results

The resulting map showed 22 squirrels found throughout the University of Wisconsin-Eau Claire lower campus on November 27 (Fig. 2). Interestingly, The squirrels were found to be distributed in a clustered manner--squirrels were found in groupings rather than spread randomly across the study area. It also found that there is a potential territory based on color of the squirrel as black squirrels were found only in one area near Katherine Hall and little grey, red, or white squirrels were found in this area. Grey and red squirrels were found in all other groups in abundance while no black squirrels were found in these areas. The map can be found either by following this link: 

http://uwec.maps.arcgis.com/home/item.html?id=67ec369bb4d542a786ae164e0ad5fcdf or by logging on to ArcGIS online and locating the map in either the UWEC group or public. It is published as "Aumann_Collector_Map." Metadata for the squirrel feature class was created in ArcGIS (Fig. 3).

Fig. 2: Map of squirrels by color on the lower campus of UW-Eau Claire using the feature class and map published on ArcGIS online. Cartographic aids (legend, compass rose, etc..,) were added after online map was brought into ArcMap for desktop.

Fig. 3: Metadata of Squirrel feature class after the online map was brought into ArcGIS.

Discussion

After completing this activity, I found that using the mobile app for data collection is a great alternative to the GPS. It allows you to update the data on a basemap on the fly and is very user-friendly. However, you cannot edit domains once they are uploaded to ArcGIS and it is crucial to have a detailed and well-done feature class created before uploading it online and collecting data. Creating your own geodatabase, feature class, and setting domains is not as complicated as it may sound, though it is very easy to miss details when setting the domains. The biggest problem is not knowing what you could run into in the field and not taking account for all the unknown factors. I think it would be best practice to test the potential domains before creating the final product for your data collection process or at least add a couple fields to log locations of your study subject that has attributes not accounted for in the domains so you can go back and edit them after your data collection is completed. 

Conclusion

During this activity, I practiced creating a geodatabase with a feature class created by domains I set within the geodatabase and publishing this feature class to ArcGIS online for creation of a map. I took this map and collected data using the ArcCollector mobile App. I learned preparation is key before data collection and it is easy to forget or to not even be aware of factors needed for the data collection process when setting the domains. In future projects, I will make sure a preliminary test is done in the field before creating the final map or fields are added to the feature class in which I can store locations and edit the attributes after the data collection process is finished.

Sources:

My Map:http://uwec.maps.arcgis.com/home/item.html?id=67ec369bb4d542a786ae164e0ad5fcdf 

"Prepare your data in ArcGIS for Desktop" Instructions: http://doc.arcgis.com/en/collector/windows/create-maps/prepare-data-desktop.htm

"Create and Share Map For Data Collection" Instructions: http://doc.arcgis.com/en/collector/android/create-maps/create-and-share-a-collector-map.htm

Activity 7: Topographic Surveys with Dual-Frequency GPS and Total Station

Introduction

The goal of this activity was to learn how to set up and utilize both a Dual-Frequency GPS and a Total Station to run topographic surveys. During the first week of this activity, we used a Dual-Frequency GPS and created a TIN from the resulting topographic data. During the second week, we did the same with a Total Station. 

Our study area was within the campus common areas on the University of Wisconsin- Eau Claire campus. My groups surveyed the outskirts of the commons area along Little Niagara Creek in front of Davies Center. The first week, my group surveyed the eastern portion of the creek near Phillips Hall on the east side of the bridge (Fig. 1) and the second week, my group surveyed the western side of the same bridge. The first week, using the Dual-Frequency GPS unit, we surveyed on November 5 from 9am-11am. It was cloudy and chilly, but no wind. The second week, using the Total Station, we surveyed on November 12 from 12pm-2pm and there was a significant amount of wind.

Fig. 1: Study area for week one using the Dual-Frequency GPS to survey
the eastern side of the bridge crossing Little Niagara nearest to Phillips Hall.

Fig. 2: Study area for week two using the Total Station to survey
the western side of the bridge crossing Little Niagara nearest to Phillips Hall.

Methods

Equipment

Equipment used for surveying with a Dual-Frequency GPS included the TopCon HiPer S4, the TopCon Tesla, a MiFi portable hotspot, and a tripod stand on which to attach both TopCon devices (Fig. 3). The TopCon HiPer S4 served as the GPS receiver unit and it screwed in to the top of our tripod stand to assure the height from the ground was consistent. We used the TopCon Tesla to create our files and record our data. The MiFi portable Hotspot was used as such to assure we always had a connection. For week two, the total station included both the MiFi portable hotspot and Tesla as well as the TopCon Total Station all situated on a tripod stand and a prism (Fig. 4). With these pieces of equipment, we used the Tesla to record points, the Mifi to assure connection, and the Total Station to shoot points towards the Prism to gather the positional data. Because the Total Station did not record its elevation from the ground as a standard, we needed to measure the elevation of the Total station manually.

Fig. 3: TopCon HiPer S4 (left), TopCon Tesla (center), and MiFi Portable Hotspot (right) comprised the Dual-Frequency GPS unit from which we surveyed topography the first week.

Fig. 4: The TopCon Total Station (left) and the Prism (right) in addition to the equipment listed in use for the Dual-Frequency GPS survey were used to survey topography the second week.

Recording Points with the Dual-Frequency GPS

Fig. 5: Collecting points using the Tesla after leveling the tripod.

My partner, Scott, and I set up our tripod stand in our study area with all necessary equipment attached. Because the TopCon HiPer S4 collected elevation data on its own, it was not needed for us to measure this manually. We simply created our job in the Tesla, leveled the tripod with attached equipment, and gathered the point with the Tesla. This was a fairly simple process once we created our job as all that was necessary was for us to level the tripod and press the "collect" button. We did this 100 times to collect a total of 100 points (Fig. 5). In this lab, one person leveled the tripod as the other person collected the points on the Tesla. However, because the Tesla was in demo mode, we were forced to create 4 jobs each collecting a maximum of 25 points, to complete the data set. While collecting points, we tried to stay fairly regular in spacing between each point except for areas the slope of the landscape was more drastic. In these areas, we tried to collect more points to accurately survey the slope.

Fig. 6: Screen shot of a portion of the resulting
combined text file table later imported to ArcMap.

At the end of the collection process, we saved our data and exported each job to a file. We then transferred the files from the Tesla to the computer via USB. The resulting text tables had to be combined then normalized to fit headings transferable from a text file to ArcMap on one single table. To do this, we simply copy pasted data from 3 of the text files from 3 of the jobs onto one text file from one of the jobs then altered the top row of text to include the name of the point, the latitude (N), longitude (E), and the height with appropriate commas separating each column (Fig. 6). To properly import it into ArcMap, we needed to specify our X value as Lat (N), our Y value as Lon (E), and our Z value as Ht (Z) in the Import XY Data Window.






Recording Points with the Total Station


For this portion of the activity, we were broken into groups of 3 as opposed to 2 like we were for the first portion of the activity. This is because it was easier to work the equipment with three people--one to shoot the Total Station at the Prism, one to hold the Prism over the area we were collecting a point for, and one person to collect the points with the Tesla.

To begin this survey, we first collected a back point in order to collect the location of the Total Station. We did this by collecting one point using the same method we used during the Dual-Frequency GPS survey and the same equipment. This back point was logged in the same job as the other collected points. We then began to set up the Total Station--the most time-consuming portion of the activity. We first positioned the Total Station atop the tripod and began to level it in such a manner that the laser from the Total Station facing the ground was over our desired point--the occupancy point (Fig. 7).

Fig. 7: The laser from the Total Station line
 up over the occupancy point.

Once the Total Station was leveled on the tripod stand over the
occupancy point, we leveled the Total Station itself. We swiveled the Total station in all three directions it allowed in ordert to point the laser on one of the faces of the Total Station with which we shot the Prism to record the data. We leveled the Total Station when it faced each of these directions by twisting the circular knobs on its base which we positioned at "neutral" to begin leveling properly (Fig. 8). We made sure to only twist one knob each time we re-directed the Total Station so as to not interfere with previous levelings.

Fig. 8: My group mate, Peter, leveling the Total Station by twisting the knobs at its base.

When we finished leveling the Total Station, we began shooting our points with the laser from the Total Station to the Prism. We made sure we were not too far from the Total Station and not too close so the laser could be received and sent back to the Total Station relatively quickly and without trouble. We sampled both sides of the rive and the edge of the river itself. This time, we only recorded 25 points on one job. The resulting able had to be normalized in the same manner as we normalized the text file table with the Dual-Frequency GPS (Fig. 8). We then imported the data as XY data and specified the Y, X, and Z values. From the resulting point data, I created a TIN and a break line to characterize the river edge.

Fig. 8: Total Station normalized text file table.

Results

I created a TIN for the Dual-Frequency GPS and a TIN for the Total Station survey points and displayed them on a map (Fig. 9). Metadata was added to each TIN (Fig. 10).

Fig. 9: TINs of the Dual Frequency GPS and the Total Station survey points.

Fig. 10: Metadata created for Dual Frequency GPS TIN (top) and Total Station TIN (bottom).

Discussion

Being that both the Dual Frequency GPS and the Total Station are both survey-grade instruments, I was interested in comparing the accuracy between the two. However, because we operated only on demo versions with the Tesla and the amount of time needed to do these tasks, I was not able to collect the same amount of points for both TINs. As we also had different groups from the Dual Frequency GPS portion of this lab and the Total Station portion, I also did not get the opportunity to survey the same area. However, I was able to survey an area in very close proximity and similar elevation characteristics for both portions of the lab. With this, I can at least say that both pieces of equipment detected very similar elevations around the bank of Little Niagara.

Because the back point was included in the TIN, however, I am inclined to say our result for the Total Station may be less accurate as there were not enough points to characterize the space between our study area and the back point included. This may be why the elevation near the side walk nearest the TINs in the North are so different.

The Total Station was a lot more time consuming to set up than the Dual-Frequency GPS was. Set up time for the Total Station was approximately 1 hour, while the set up for the Dual-Frequency GPS was almost instant.However, because the Dual-Frequency GPS unit needed to be physically moved to each survey point and re-leveled for every point, the Total Station  may be a better choice if many points needed to be collected. Once set-up for the Total Station was complete, collecting the points only took approximately 1-1.5 minutes/point.

A draw back to the time-efficiency of the Total Station may be that it is fairly weather-dependent for its accuracy and efficiency. The Prism is held on a monopole and faced towards the laser on  the Total Station. The prism must not move otherwise the point will either not be collected or will be collected improperly. While we were out collecting points with the Total Station, my group had some difficulty at the beginning with the wind twisting the Prism face away from the Total Station resulting in its inability to collected. It is also rather difficult to keep the monopole steadied in such winds and occasionally, the pole would sway too much and result, again, in the Total Station's inability to collect the point. 

Conclusion

Though this exercise, I gained experience using the Dual-Frequency GPS unit and the Total Station unit to collect elevation data. Overall, both instruments have relatively accurate data collecting capabilities as both are survey-grade. However, they vary slightly in set up time and data collection time--the Total Station taking more time to set up but less time to collect individual points than the Dual-Frequency GPS. The Total Station is more touchy, though, and may not collect the data points if it is too windy or the person holding the monopole with the Prism is not steady enough. There exist advantages and disadvantages of both pieces of equipment and ultimately it is the data collector's choice on what they prefer to use. Knowledge of these differences, however, are important to be aware of before beginning a project.

Activity 6 Navigation: Priory Navigation

Introduction

This week's lab is a continuation of last week's development of navigational maps exercise. For this lab, the class was split in groups of 3 and used the maps created from last week's lab to navigate through the Priory in Eau Claire, Wisconsin. Our objective was to find 5 locations previously marked by the professor and other classes with pink ribbons labeled with a site number. To do so, we were limited to our maps and a standard compass equipped with a ruler, only using a GPS (Fig.2) to log our trail for later evaluation and in cases where no marked location could be found (as the locations were marked in previous years, ribbons may have fallen off or blown away by the wind). The intention of this lab was to help us gain experience using basic navigational tools for situations in which either newer technology fails or is inaccessible. We also used this lab to evaluate the effectiveness of our maps created from the previous lab.

Fig. 1: Standard compass (left) equipped with ruler on the edge to plan our routes and
navigate and a GPS unit (right) to log our track.

Methods

The first step was to mark on our maps the coordinates of the five locations given to us by the professor (Fig. 3). We then compared our mapped locations with each group members' locations to assure we correctly marked each location. We then chose a starting point from which to navigate to our first location. We chose to start from a tree near the access of the parking lot closest to the forested area of the priory as this was an easily found location on the map and we could correctly determine the distance and direction we would need to travel to find our first marked location.

Fig. 3: Mapping coordinates of our 5 locations and determining routes.

After mapping our locations and determining a starting point from which to navigate to our locations, we had to plan our routes to each of the 5 locations. This was done by using the compass edge to draw straight lines between each point location on the map and measuring the length of that route and convert it from centimeters to meters using the scale on the map (1 cm: 35 m) (Fig. 4). The pace count was determined as we navigated from point to point as the person counting paces and keeping direction using the compass switched periodically throughout the lab. This was important to determine pace count between locations on the fly as opposed to at the beginning of the lab as each person has a different pace count. For instance, I walked 67 steps per 100 meters while another groupmate, Katie, walked 65 steps per 100 meters.

Fig. 5: Scott connecting each point location and measuring route length to plan our routes.

Next, we began navigating through the forest to our 5 locations. We used our UTM map as opposed to our Decimal Degrees map as it was easier and more accurate to calculate our distances in meters and pace count conversions using UTM. It is important to note here that each group member played a different role during the navigation portion of this exercise. One person would count paces holding the compass close to their body to make sure they were walking in the correct direction while keeping track of the distance traveled. Another person would stay behind and make sure the person navigating would be traveling in the correct direction as sometimes if the person must avoid brush or trees, they can skew their angle of direction. The last person would either walk with the navigator keeping count of paces and assure direction or remove brush in the path ahead. Normally the third person would be holding the compass and walking with the person counting paces, however, we thought it was easier for the person counting paces to be looking at the compass themselves and for another person to help clear the path as the terrain was fairly rugged and we wanted to limit the amount of error coming from pace changes due to obstacles en route.

Our route to point one was calculated to be approximately 280 meters in length as the line drawn on the map from our starting point to point 1 was 8cm (8cm * 35m/1cm=280m). I was the first to count paces and navigate, so we used my pace count (67 steps/meter) to calculate the amount of paces it would take to reach 280 meters and determined it would take approximately 188steps (280m * 67/100m= 187.6m). After the bearing was set in the correct direction towards the first location, I started navigating towards the first point with the compass held to my chest and counting paces while my groupmates made sure I was heading in the same direction as I had started heading and clearing the path in front of me as best they could (Fig. 6). We followed this same method for locating the remaining 4 locations, but switching roles periodically.

Fig. 6: Navigating to the first location with Katie in front clearing the brush, myself counting paces and keeping an eye on the compass, and Scott making sure we did not alter our direction unknowingly.

Some routes between locations were across steep ravines. In these instances, we estimated approximately how much the slope would change our pace count by looking at the distance between our feet upon taking a first step on the slope and comparing it to the distance between our feet on a normal step in a flatter terrain.

In instances where trees both upright and fallen were creating obstacles in the direction we needed to travel, we would stop to visualize a path that was the most straight-lined possible and chose an easily recognizable feature in the line of bearing to assure we were staying true to the bearing and to help eliminate some pace count error while avoiding obstacles.

Results

We were able to successfully locate only 3 of our 5 marked locations and not all were found right away. For the first location, after walking the correct amount of paces in what thought to have been the correct direction, the marker was no where to be found. Katie had wondered ahead to find the marker while Scott and I stayed back to keep our current position so as to not get lost. Katie had found a marker. However, we figured, looking at the map contour lines, that this was not the correct marker we were searching for. We consulted the GPS unit and found we were headed in the correct direction, but we had not traveled enough steps in the direction to reach the correct marked location. We continued on to find another marker. From here, we calculated the amount of paces to the next location with Scott as the navigator and pace counter. However, upon arrival of the next location, we figured this was actually our location 1 marker as opposed to our location 2 marker. Because these locations were in a similar bearing from the origin location, we must not have traveled far enough still to get to our location 1 marker. From here, we readjusted our bearing and used the same pace calculations to reach our location 2 marker.

Upon reaching the supposed location of our second marker, it was no where to be seen either. We again consulted the GPS unit to discover our pace count was correct despite the steep ravines that were traversed in the process, but we had traveled slightly more to the west than was needed. We headed toward the correct direction, but was still unable to locate the marker until we used the GPS unit entirely as opposed to following the compass to find the marker.

Our 3rd location marker was found with little difficulty, having the correct distance in paces, but were only minimally off from the bearing. Our fourth marker was never found, however, we found a tree in the exact location the marker should have been--using the GPS to verify. This must mean that we had found the location without trouble, but the marker had disappeared. For location marker 5, we experienced the same problem--finding the location it was supposed to be in, but having no marker. From here, we navigated back to our origin point successfully. 

Discussion

After navigating to our designated locations, I felt the maps we used required adjusting. Though ornamental, the imagery basemap did not aid in helping our navigation through the wooded regions and was less important than I had originally assumed. Though it was help in finding an origin point from which to start the navigation process to each of our marked locations. However, our contour lines, which we relied on the most, could stand to be of higher precision as a big problem we faced was the accuracy of our pace counting over steep terrain. This could have also helped us locate the first and second marked locations as we should have been able to tell by the slopes of the terrain where we were in relation to the marked locations. 

Conclusion

This lab allowed us to practice useful navigation techniques using more traditional pace counting and compass methods and operation of GPS in the field. The more traditional methods of pace counting and compass reading can be used in situations where a GPS can not receive a signal. One thing to always consider when navigating using this technique is to always adjust estimated pace count distances according to the slope of the terrain and the amount of obstacles in your straight path. Using landmarks such as distinct trees and rocks is useful in maintaining a straight course. It is always useful to make sure prior planning is also done correctly and in a detailed manner. If you are selecting or creating your own map to navigate a study area, make sure the information and the type of projection is suitable for our study area.