Lab 8: Developing a Project for Arc Collector and Gathering Data

Introduction

In this week's lab we created geodatabases for use in Arc Collector where we can collect attribute data tied to GPS points on mobile devices using the Arc Collector app. Smart phones and mobile devices are perfect for collecting geospatial data in the app because they feature powerful computing power which is far higher than most GPS units and their connectivity allows for access to online data which is useful for syncing information and updating geodatabases on the fly. In order to have a working data collection map on Arc Collector there are several prerequisites. First you must have an ESRI online account and create a geodatabase with feature classes, domains, fields, and sub-types. Then this map must be published to ArcGIS online and transferred into a map document. Then if all the necessary feature services are set up right this map can be accessed via a mobile platform and new data points can be input to the automatically updating map. Having preset domains and sub-types speeds up the data acquisition and cuts down on human errors. In total for this lab we created three geodatabases. The first was an in class tutorial to get ourselves familiar with the basics. The second was an on campus feature collection geodatabase of our choice. Lastly the third was an off campus feature collection geodatabase of our choice.

Study Area/Methods

During the in class tutorial our professor showed us the basics of creating a new geodatabase by using domains and feature classes that are linked to the domains. To do so we selected a parent folder and chose the option "new/file geodatabase" and once this was created the domains could be created. Inside the properties menu of the geodatabase, under the Domains tab the domain names could be created and given a description of their function. Then in the domain properties section the field type could be chosen, as well as the domain type which is usually a single option. If coded values were chosen for the domain type, down under the coded values section the code values could be named and given descriptions. These are the values that can be quickly selected while using the Arc Collector App when filling in feature attribute information. Next inside that geodatabase we chose "new/feature class". Doing so will prompt you to name the feature class, give it an alias, and choose what type of feature is to be stored (in our case point features). Next a projection is chosen, in our case WGS 1984 Web Mercator (auxiliary sphere) was chosen. Then the x,y tolerance default is accepted and lastly the field names must be created. The field names are the attribute data of the features to be collected and can be any number of choices including numeric short integer or long integer, decimal point float, double, text, date, blob, guid, or raster. In the field properties the default values could be set, the length allowance set, and the domain value that is tied to the geodatabase could be denoted which allows for quick input by users. After accepting a few more default setting the feature class is now created. Before doing anything else the feature class has to be properly symbolized according to what is needed to be conveyed by the data points and size or color must be taken into account. This can then be shared with the ArcGIS online database that an ESRI online member has access to. In order to do so you must first be logged into an ESRI account and then choose the share as/ service option under the main file heading. Next publish a service is selected, followed by choosing a connection which is either the default hosted services server or another server can be connected to, the service is named, and then the next portion of the publishing ensues. Inside the service editor window that appears the tiled mapping option is turned off and the feature access is turned on, which is what allows end users to manipulate and add data to the service. Then in the feature access tab the options create, delete, query, sync, and update must all be selected to ensure full functionality. Lastly in the item description tab a summary and tags are required, and a description, access and use constraints, and credits are optional input. Then once this has all been finalized you can finally select the analyze button, and then the publish button, which will export the service to the users ArcGIS online account which can then be accessed from the ArcGIS online website.

The next step in the process is to access the ArcGIS online site and log into your account. Once in click on the map ribbon and zoom to the desired study area extent. Then after choosing a basemap select the add layer function and search for the previously published features in the My Content section. After testing if the edit function works properly and all the desired fields are usable for attribute input save the map and enter in the desired map title, tags, summary, and save folder destination. Lastly the application settings can be customized by selecting the "About this Map" icon selecting the share button it allows for either everyone, your organization, or subgroups of your organization to access the map and edit it. Once this is complete the map is full accessible from the Arc Collector app and can be used to gather spatial attribute points in the field.

By following the previously outlined methodology for creating and publishing custom geodatabases with point features, I then created two maps; one for on campus and the other off campus. My on campus map was a simple Garbage Receptacle marker but had several fields and domains linked to the geodatabase. The fields were material composition (combination of materials, metal exterior, cobbled aggregate rock exterior, wooden exterior, or plastic exterior), bin size (small, medium, large), date, recycling combo (either singular unit or combination recycling and trash) and smokers receptacle (if the unit was a smokers receptacle or contained one). The study area for this map was the general area of the UWEC lower campus from Hibbard to Davies.

Figure 1: Garbage Receptacles data table after collection

My second off campus map was one of the sidewalk features lining a block on water street. The first field was the feature type (sitting bench, stop sign, parking sign, no biking sign, garbage bin, street lamp, or tree), the second field was its condition (either well maintained, minimal wear and tear, or unkempt weathered or vandalized). The final field was the position on side walk (either closer to the road of further from the road).

Figure 2: Off campus water street side walk features data table after collection

Results

On campus trash bins map

http://uwec.maps.arcgis.com/home/webmap/viewer.html?webmap=9494669fa20648419b1160299e73d5e1

Figure 3: On Campus Trash Bin collector map after data collection, in ArcGIS online map viewer

Off campus water street sidewalk features

http://uwec.maps.arcgis.com/home/webmap/viewer.html?webmap=58dbfd8153fa4733bbd0d54513c000a7

Figure 4: Off campus water street sidewalk features after data collection, in ArcGIS online map viewer

Conclusion

Fields and domains in geodatabases make data collection in the field an extremely efficient and easy task so long as they are properly formatted. With the use of Arc Collector we were able to quickly make a working map and utilize it in the field with limited programming knowledge. One major bonus of this method of collecting data to an automatically updating database is the added mobility and processing speed of having the app directly on our smart phone devices as opposed to having a bulky GPS device with. The intuitive app interface made for quick data acquisition. Overall the Arc Collector app seems to be a very powerful medium for collecting geospatial data, and the option of having multiple users and simultaneous data syncing allows for a highly efficient platform for projects.

Lab 7: Conducting a Topographic Survey with a Dual-Frequency GPS and Topcon Total Station

Introduction

In these two conjoined labs we were introduced to the procedures and units involved in survey grade GPS analysis. The four units we used were the Tesla (on the fly sub-centimeter accuracy gps capable handheld unit with touch screen interface), HIPER (high accuracy GPS receiver), MIFI (4G modible hotspot device) and Topcon Total Station (survey grade optical laser distance and bearing measurement deice). Using all four of the units, my lab partner and I were to survey out a roughly 25 x 25 meter study area and plot out 100 points (first lab) and 25 points (second lab) over its surface area. The resulting data would be akin to our first and second labs where we used rudimentary surveying methods in our topographic sandbox's, but in this lab's case the x,y,z points would be highly accurate survey grade data. After all our classmates had collected their data, our data set would be capable of being combined with other group's data sets if they were in the same study area.

Study area/Methods

Dual frequency GPS

The study area for this lab was (for my group) the campus mall extent inside the surrounding sidewalk at UWEC. Once we had collected the neccessary equipment from out department storage room (HIPER, TESLA, MIFI, and Mounting Tripod) we set out to the mall and began setup. Once the Tesla handheld was powered on we entered the Magnet Field Program used for surveying and created a new Job with our groups identification information. Then we configured the GPS to use the HIPER SR RTK NET OC to ensure we were getting the highest possible accuracy for our location and elevation data. The Projection were kept as UTM North Zone 15 90w, as well as the same Datum NAD83(2011) and GeoID. After continuing through the rest of the options set to default and okaying the selection we hit the home button to return to the main menu screen. Then we entered the Connect sub menu and chose to connect to the HIPER, beforehand ensuring the MIFI device was turned on and connecting to the HIPER device which would further enhance localization accuracy by having a pinpointed 4G hotspot. After returning to the home menu we then began the process of collecting data points by entering the Survey menu, and then the Topo menu. We were group 1 so our data points began at 100 and would go to 200. The height of the unit was denoted as 2m and the code for the data points was set to elev (elevation). To ensure the accuracy of the data points we set the number of averaged points collected per single end result data point to be 10. Once these prerequisite fields were filled out we began the process of collecting a points, and relocating to other parts of the campus mall, making sure we covered the whole extent of the mall until we reached out 100 point cap. Due to the fact that the Tesla unit was stuck in demo mode and would cap our data points collected per job to 25 we actually ended up having to have four separate projects, which we would later merge into a master data set for use in ArcMap geoprocessing of topological elevation maps. The point data we acquired over the four data sets was then exported onto a thumb drive in a txt. file format which after slight alteration of the field names was easily compatible with ArcMap's create feature layer from x,y coordinates option.The feature layer was then used to create a topgraphic map of the campus mall using Spline interpolation and also exported as a tif for use in 3D analysis in ArcScene.

Figure 1: Campus Mall microtopography and x,y points in Arc Map  from Tesla/HIPER/MIFI  using spline interpolation

Figure 2: Campus mall microtopography in Arc Map from Tesla/HIPER/MIFI using spline interpolation

Figure 3: Campus mall 3D microtopography in Arc Scene from Tesla/HIPER/MIFI 

Topcon Total Station

On our second outing to the campus mall we were instructed to use the Topcon Total Station, Prism Rod, Tesla handheld unit, and the MIFI portable 4G hotspot to gather location and elevation data points. This time the major difference was that instead of using the Tesla as a GPS to gather the points, it instead would be bluetoothed to the Total Station which would be collecting the data from its distance and bearing data relative to the Occupied point and backsights. To gather the occupied point (exactly where the center of the Total Station would be positioned) and the backsights (denoted points which are used as a reference for true north in the Total Stations inner computer) we followed the same workflow used in the first lab outing by using the Tesla, HIPER, and MIFI. Once those points were collected the Total Station was constructed atop a sturdy tripod with adjustable legs. Care had to be taken in order to have the unit exactly level to the ground in order for the Total Station to function properly, and this process entailed adjusting two of the legs, and then the leveling screws, and then adjusting the legs again. Once the station was set up the Tesla had to be restarted and the Total Station turned on and bluetooth activated for the Tesla to sync to it. Before connecting the HIPER had to be disconnected, and once the Tesla and Total Station were connected we were then able to designate the backsight we would be using by doing the following workflow we used for the normal points. Afterwards we would begin collecting data points using the Total Stations Optical distancing laser. One of our group members (myself) had to move to the desired point with the Prism Rod while the second group member (Ally) would re-position the optical lens to aim directly at the Prism mirrors. The third group member (Matt) would then hit the record button on the Tesla and so long as the Optical laser hit directly within the Prism Rod's center the data point would be collected. This continued for 21 points (due to the demo mode cap of 25 and the already recorded Occupied point and three backsights) all across the campus mall and once we had finished and disassambled the Total Station we transferred the data points to a thumb drive in the form of a txt. file and renamed the attribute fields to better suit integration into ArcMap create feature class from x,y. This feature class was then also used to create a topographic map using Spline interpolation and also exported as a tif for use in 3D analysis in ArcScene.

Figure 4: Campus mall microtopography and x,y points in Arc Map from Total Station

Figure 5: Campus mall microtopography in Arc Map from Total Station

Figure 6: Campus mall 3D microtopography in Arc Scene using Total Station

Results/Discussion

Based on the results of spline interpolation in both data sets, it is hard to determine any reliable difference in accuracy that can be used for comparison. This is due to the fact that the first data set using the Tesla/HIPER/MIFI was a collaboration of several groups x,y data sets and has much higher accuracy due to a higher number of elevation points used during interpolation. The higher point density makes for a much more accurate representation of the campus mall as opposed to the low point density of the Total Station data set which produced an inaccurate and generalized topography due to only 16 points being taken (3 backsights and 1 occupied point took up 4 of the total 20 allowed in demo mode). The scale of the study area is also marginally smaller (data points do not extend to left 1/4 of the campus mall study area) due to the difficulty sighting the Total Station's optics to the prism during lowlight hours of the evening which caused us to have to take elevation points closer to the total station's occupied point.  These elevation points could not be collaborated with other groups due to the lack of groups sharing their data sets in our departments communal temp folder.

Conclusion

The two methods of collecting microtopography data using the "Dual Frequency GPS" and the "Total Station" each have differing pros and cons. The dual frequency gps method has much more mobility and is not impeded by line of sight from the Total station to the prism rod due to the ability of taking the Tesla/HIPER/MIFI to any location and setting up for point collection. This can also be a drawback though in cases of uneven or easily shifted terrain such as sand or loose gravel/dirt. The Total Station also suffers from lack of mobility but in this case from a single occupied point, but with practice the set up can and take down be greatly accelerated. From several occupied points it is capable of gathering more points at great distances in a shorter period of time which are not quite as impeded by uneven terrain so long as the occupied point is on sturdy ground. Each method had it's own technical difficulties such as connections between devices and data point collection (with the total station needing exact line of sight to the prism rod or else the point would not collect). Overall, each method of microtopography surveying has its preferred uses based on strengths and weaknesses but neither can render the other obsolete due to the vastly differing scope and goals of surveying projects which make use of both methods.

Lab 6: Navigation with Map and Compass

Introduction

In this weeks lab portion we did the second half of the navigation lab, using our previously constructed navigational maps in UTM an Decimal Degrees grid format as a means of navigating the UWEC Priory. In order to navigate we would be using course navigation points that had been mapped beforehand by past student which we could use in reference to our navigation maps and use the directional bearing, map distance, compass, and a GPS unit as a last resort reference to navigate our group's designated course. In a previous class session we measured out our pace, or average length per two steps, which would be used in calculations to find distances to points and determine our location in respect to our desired destinations.

Methods/Study Area

The study area for this lab encompassed the extent of the woodlands surrounding the UWEC Priory, as was denoted in our navigational maps by a feature class supplied to us by our professor. When we arrived at The Priory parking lot we were supplied with our printed maps we had submitted to our professor that he had printed for us, as well as our navigational course's points in decimal degrees which we then used to determine the location points on our navigation maps that we would be plotting a course to with our compass. After marking the 5 points A through B on the maps we measured the distances to each, starting from the corner of the parking lot which was easily noticeable on the navigation map and continuing to each subsequent point. The distance between points was measured using the centimeters markings on our compass and calculated to reflect the number of paces needed to be taken based on our group's pace counter's average pace per 100m. From the initial point to the desired destination point we then measured the bearing on our navigation map and then pointed the compass towards that azimuth relative to true north. My role in making it to each point in the navigation course was to be the azimuth control, which entailed staying back at the previous point and maintaining a straight line to the desired forward point, be it a landmark or the expected destination point. As our pace counter ventured outward and counted his paces he would relay his distance information back to me and I would log the total amount of paces taken, and then inform the pace counter and the "leap frogger" (who would be the secondary pace counter) how many paces remained before we reached our destination point. Trekking through the woods and maintaining a constant and reliable pace proved difficult and several times we missed our desired end location denoted on our maps and had to search for the bright orange/ pink marker showing where the navigation course points should be.

Results/Discussion

By the end of the class session we had only found two of the five points for our groups navigational course, some of the fault lying in our navigational abilities and our misplaced confidence in our ability to use a compass which caused us to take more time than initially planned to find the points, but also in the real life placement of the navigation point banners. After finding the two that we could, we checked our current GPS location and found that the coordinates were off by a large degree, which had misplaced our point on the navigation maps and thus made our bearing erroneous. In the end we as a class were not able to complete our second portion of the lab which would have involved running another part of the navigational course, using a GPS this time to hone in on the points, due to other groups having equal difficulty in navigating the rough terrain and finding the hidden or removed by locals navigation point ribbons.

Conclusion

Reflecting back on our experience in the field, our group should have double checked our methods wit our professor in setting a course using compass bearings in order to properly make use of our time in the field. Too much time was taken trouble shooting and second guessing our location which threw off the acquisition of the rest of our points, and in the end we gave up and headed back in frustration once we had run out of time to complete the first portion of the navigation lab. I was surprised that my time spent in Boy Scouts and the fact that I am an Eagle Scout did not help our situation, but to be honest we only rarely did orienteering so it had been several years since I had done any similar exercises with compass navigation.