Field Activity #5: Collecting Data Using ArcCollector

Introduction

In this assignment, our group collected microclimate data throughout the Lower Campus of UW-Eau Claire, using the Collector for ArcGIS application through ArcGIS online. Through this application, we collected data with a mobile device, a cellphone or tablet used by a student in our group, and created a database, domains, and feature classes from the surveying data collected. After collecting the microclimate data in groups, we merged all of our data into one dataset to use and create multiple maps depicting the data collected from our survey.

Methods

For these methods we used a Kestrel 3000 Pocket Weather Meter. This meter is an environmental tool for monitoring field conditions measuring dew point, wind speed, humidity, and temperature. Our microclimate data collection, included taking readings on this device for humidity, average wind speed, dew point, and temperature at 5cm and 2 meters above the surface.

For our group, we surveyed zone 2, located from Phillips Hall to Davies center and Campus Mall on Lower UWEC Campus. We began at the Parking lot in Davies Center, circling the building and through the Campus Mall, and ending at Phillips Science Hall. Armed with a Kestrel Weather Meter for each person, we compared data taken with each monitor. By doing this, we noticed that the weather meters would stop recording, and stopped at a certain number. From this point on, we noticed what monitors would take the correct measurements and reported the devices that were malfunctioning. 

This image depicts the different zones delegated to each group. The points illustrate each point taken collectively as a class, spanning the entire campus. The points covered a large portion of UW-Eau Claire campus, allowing variability in our data.

This image shows temperature (Degrees F) readings from 5cm across UWEC campus.

This image depicts temperature (Degrees F) readings from 200cm across UWEC campus.

This image displays wind speed (mph) readings across UWEC campus.

This image shows dew point readings (Degrees F) across UWEC campus.

This image depicts humidity (%) readings across UWEC campus.

Discussion

When analyzing the data collected in the field, there were multiple errors in the data. For example, a gust of wind occurs at the exact moment of recording data. Additionally, temperature variations for the few seconds holding and recording the data - which we had to calculate the average temperature as the device switched readings every second. This caused unwanted variation in our data, however, it does prove that the conditions were changing throughout our data collection process. The weather conditions however, were cloudy and slightly breezy at first, but towards the end of our collection, the wind had picked up, and the temperature seemed to be colder.

Conclusion

Overall, this exercise was a good introduction to using Collector through ArcGIS, and collecting data using your personal mobile device. For our group, it was important to be able to have the same goal when collecting data, and to do so in a timely manner. This exercise also introduced myself to assessing and surveying for climate data, and how to manage the data, and present it, by creating a geodatabase with domains, subtypes, feature classes, and fields in order to collect and analyze the data. After this field activity, I feel it is useful to those who want to conduct public science projects, and how to formulate a project and display data of a neighborhood or public area.

Field Activity #4: Conduction a Total Station Survey

Introduction

For this experiment, a survey was conducted within the campus mall of the University of Wisconsin – Eau Claire using a data collector and total station. Throughout this survey, we used the established control points, provided by the Eau Claire County Surveyor’s Office, and collected X, Y, and Z topographic points on campus. The area that we surveyed had relatively low topographic relief as well as a few planted trees and dolomite blocks to sit on provided by the university. The purpose of the experiment is to create a landscape model, using the TIN feature, of the UWEC Campus Mall using the X, Y, and Z points gathered.

Methods:

October 9, 2019

Sunny, ~ 21.3 degrees Celsius

After an introduction to the nature of the survey and the equipment we would be using, we headed from Phillips Hall to the UWEC Campus Mall. Our survey took place within the area below:

The equipment we used throughout this experiment included the data collector, dual frequency GPS unit, and the TopCon GPT Total Survey Station. Both tools were used to maintain data accuracy. Through using these two different methods, we had generated the same results. This allowed us to compare the methods used and which equipment is best suited for a given job.

The first tool that we used was the data collector, the HiPer GPS/ Tesla Handheld System as well as the dual frequency GPS unit. The tripod allows for leveling and allowed for a more accurate point. When taking each point, we averaged about 1 point every 50 feet for this exercise. It was important to listen to the instructor and the Surveyor’s instructions as we went through this process.

To start collecting data, you first start a new “Job.” This can be found by clicking on the “Job” icon and then renaming your file with a name. Next, when selecting “Edit” I manually entered the control point coordinates. In the field, select “Set Up” to orient the instrument. Select “Survey,” then “Topo” to start collection your X, Y, Z points.

The second method that we used was the T TopCon GPT Total Survey Station. This tool had to be set up at a leveled location before the points could be collected. This instrument was mainly used to measure the sloping distance of an object to the instrument, horizontal angles and vertical angles. The Total Station is an electronic/optical instrument used in modern surveying. This tool operates and collects data using an electronic transit theodolite along with an electronic distance meter (EDM). The data collected from this station can then be downloaded to the computer for further processing.

Using the established points provided by the Eau Claire County Surveyor’s Office, we collected the points automatically.  These points are entered into the data collector, and therefore, would be our zero-calibration line at 0⁰0’0’’. When taking a point, the total station then sends out a beam and the prism bounces it back. The instrument then takes the horizontal angle into account, and automatically calculates the correct XY location of the point of interest. The vertical angle is calculated by the data collector and takes a ground elevation point.

Results:

After completing the survey, the points are then processed by the Eau Claire County Surveyor’s Office and sent back to us (as it is their equipment we used). The CSV file with the X, Y, and Z coordinates is then imported into ArcMap using the “Add XY Data” function, converting into a 3D point shapefile.

Next, I created a TIN model in ArcMap and edited the collected points. I then generated 2-ft and 1-ft contours using the TIN and “Contours” tool to create my final result. Within this map, I have also added the surveying points that were taken using both methods.

Discussion:

Through Total Station Surveying methods, there is a relatively easy and quick data collection process involved. When taking the measurements, it was relatively easy and efficient. However, although gathering information proved to be a breeze, the coordinates were gathered calculated on a rectangular grid system, and not taking into consideration the curvature of the Earth. The rectangular coordinates must be transformed into the correct geographic coordinates when projects are larger scale.

Conclusion:

During this experiment we used a few expensive surveying equipment when gathering our data during this survey, however, it’s important to keep in mind that using higher quality equipment doesn’t always mean that there will be no error or malfunction. Equipment that needs to be charged before using, could become useless if the equipment no longer works. In addition, if equipment is slow in the field, it could put a strain on a day in the field when working on a project. Overall, the purpose of this experiment was to familiarize ourselves with using tools in calculating spatial relations with coordinate systems and professional surveying equipment. These methods are useful in accessing accurate and precise data when surveying an area within the field.

Field Activity #3: Conducting a Distance Azimuth Survey

Introduction:

For this experiment, a survey was conducted using the concept behind distance and azimuth. Although this is a basic survey technique, it works in many different situations. In this instance, we used sampling techniques to map point features on the University of Wisconsin Eau Claire campus, specifically trees around Phillips Hall Science Building. With today’s technology and the ability to acquire very precise location data, it is important to understand the basic techniques and tools used in field methods in order to function effectively and independent from advanced technology, such as drones.

For this exercise, a TruPulse laser distance finder was used to record the distance and azimuth readings for the data points we chose. We also used a compass that allowed us to record separate distance and azimuth readings. Although as a class we did not use the compass data, it is important to make comparisons of different technologies. We also used a distance finder or tape measure to measure the distance from our first station to the point feature (trees).

The TruPulse 360B Laser Rangefinder that was used to record our final distance and the azimuth readings for our chosen features (above-right). We also used a compass to compare azimuth readings between the two technologies.

My team and I chose to survey trees within the courtyard and surrounding Phillip Science Hall of UW-Eau Claire. Before conducting our survey, we were advised to take not of the concept of magnetic declination and how it differs from magnetic north. This refers to the magnetic pull on the compass due to earth’s magnetic field at our location on the planet, rather than what is known as “true North.” Below is a link to a video that was shown to the class for more information on magnetic declination:

Luckily, Eau Claire, WI has a small declination value of 2, so we know it would not impact our data collection. We then calculated the point features without using any coordinates, however, we will assign our starting point with GPS coordinates so that the data is usable in GIS systems.

Methods:

October 2, 2019

Cloudy, Rainy, ~ 15 degrees Celsius

Our first survey area was located within the courtyard of Philips hall, facing south towards Putnam Park trail. Once we decided our station area, we took the coordinates of that area, and began surveying from that point. We set up the TruPulse and began by taking readings of trees from right to left. Due to the bad weather that had rolled in that afternoon, our only option was to take points from the exit doors on the northeast side of the courtyard and take our survey from there. There were also heavy winds that would cause the TruPulse to shake, not allowing us to receive valid distance or azimuth readings.

This made collecting data extremely difficult, and due to time constrains, we couldn’t collect as many points as we could have. During this survey, we gathered three features. Our second survey station area was located south of the Phillips building near the bike racks and west of the large sculpture. After collecting data from this area, we had gathered a total of six point features.

After returning to the classroom, we transferred our data into an excel spreadsheet document for later use in ArcMap. Our data is shown below:

Table showing our data collected. For each point, we collected the azimuth, the distance from the station, attribute information of the trees, and the elevation of the tree.

Next, the excel file was imported into the geodatabase where we then used the “Bearing Distance Line tool to convert its information into a line feature class. 

We then converted our data to the points, using the "Feature Vertices to Points" tool.

The results of the tool and our data is shown below.

Results:

Discussion:

When looking at our map and data, it doesn’t seem like there is any input error, but that the readings from the TruPulse were off, causing our data to shift. It seems that even the smallest amount of error when calculating the azimuth will impact the resulting points. It is also possible that errors occurred when measuring subsequent readings of distance (meters) of the prominent features, especially considering the weather conditions throughout the course of this survey.

In the map above, the laser’s accuracy seems to decline as the object is farther and farther away from their actual locations. This error comes from the TruPulse’s decreasing accuracy with distance, as well as the users’ error as distance increases.

Conclusion:

Although we did use an expensive tool in gathering our data during this survey, using higher quality equipment doesn’t always mean that there will be no error. Utilizing simpler equipment may have been easier. Overall, the purpose of this experiment was to familiarize ourselves with using tools in calculating spatial relations without a coordinate system. These methods are useful in areas where there is no access to advanced global positioning and in situations of technological failure.