Lab 7: Using Arc Collector for Microclimate data

Introduction:

The purpose of this lab was to engage students with Arc Collector software on their mobile phones to gather data points.  Such devices typically have significantly more computing power than a standard GPS unit, and also are able to access online data, making data collection quick, easy and in real time.  High degrees of spatial accuracy can also be recorded when coupling Bluetooth with a GPS paired with Arc Collector.  Students downloaded Arc Collector on their phones and were thrown out into the field to test out the software.

Study Area: 
Students were assigned zones on University of Wisconsin Eau Claire's campus to record micro-climate data points.  On Tuesday, October 21st between 3:30-4:45 students ventured out to make their recordings.  Figure 1 below displays a map of the study area.  Zone 7 was the particular zone assigned to this student, who recorded 19 total points with another member of the class. 

Figure 1 - Study area divided into 7 zones

Methods:

After downloading Arc Collector to their smart phones, students signed into their enterprise accounts to join the class group.  This gave them access to the geodatabase for this particular assignment to update data points in real time.  Students were given a compass to measure wind direction and a Kestrel 3000 weather meter (shown in figure 2) to measure wind speed, wind chill, dew point, and temperature.  Points were added by selecting the "add point" tab within the app.  On top of just the geographic coordinates of the points, other attributes that were collected were Group (1-7), Temperature (F), Dew Point, Wind Chill, Wind Speed (mph), Wind Direction (Azimuth), Time, and Notes.  

Figure 2: Kestrel 3000

Once all the points were established, that data was ready to be transferred to ArcGIS online for mapping.  Proportional symbol maps and IDW interpolations were the two primary functions performed to produce the maps.  

Results:

The first map produced (figure 3) emphasized temperature recordings made throughout the study area.  The lowest temps on this map are near the river, rich is not suprising, as water bodies often times create a pocket of cool temperatures.  Warm areas seem to be near buildings and in parking lots, which might be influenced by solar absorption and heat emitted by the buildings.

Figure 3

   

The next map (figure 4) focuses on the distribution of the dew point throughout the study area.  This revealed the relative humidity depending on where one was on campus. 

Figure 4

Figure 5 below shows a multi-variable map of wind chill, speed and direction.  Graduated symbols were used for wind speed and were rotated according to the angle of the wind direction.  High wind speeds seem to be associated with low wind chill, especially on the bridge over the Chippewa River.

Figure 5

  

Conclusion:

This lab showed the simplicity and power Arc Collector has when coupled with a smart phone.  It is a great method of data collection in the field in real time, technology which has never been so freely accessible to geographers. There were a couple issues with recording errors during the process of data collection, but such points were deleted before producing the maps.  Overall, this application is quite easy to use and highly effective.   

Lab 6: Using Survey 123 to Gather Survey Data Using Your Smart Phone

Introduction 
The purpose of this activity was to create a survey through Survey123 for ArcGIS, followed by analyzing and sharing the survey data.  Survey123 is a form-centric data gathering service for creating and analyzing surveys, publishing them online.  It can be completed on both mobile and desktop platforms, capable of downloading data attached to spatial information and mapping it.  This post covers how to use the software to perform such duties through an ArcGIS online tutorial.    

Methods

Create a Survey:

The first step to creating a survey is by selecting "create a new survey" on the survey 123 website. The next step requires you to insert provided details given through the tutorial (name, tags, summary).  Questions are then added to the survey through the "Add" button, having the option of single choice, drop-down, multiple choice, etc.  Figure 1 below shows the list of options available for question types.

Figure 1

The survey the tutorial required users to create was composed of many different types of questions.  The first was about background details of the participant and their location, the second set of questions is composed of "safety checks", and third inquires of materials a homeowner has, such as fire extinguishers and if smoke alarms are up to date.  Once these survey questions are added, the list is previewed to ensure that all the questions are correct.  Figure 2 shows a mobile preview of the survey.

Figure 2

Once satisfied with survey content, it is published by selecting "Publish" in the bottom right corner.  Once the survey is published, it can no longer be edited.  It is now shared among the other members of the class within the shared database, and can be found in the gallery under "my surveys", which is displayed in the iOS app in figure 3.

Figure 3

.



















After survey is completed, the second part of the tutorial requires users to complete the survey both with a desktop browser and with the Survey123 mobile app.  The user is required to fill out the survey a total of 6 different times, mixing up the answers in order to get a variety of results to further analyse and project.  As you can see from figures 4-6 below, many different variables can be mapped after survey results are produced.

Figure 4 - A color themed column graph showing ages of people living in a household

Figure 5 - Age of houses owned by survey residents

Figure 6 - Pie chart of people living in a household

Figure 7 below shows a heat map produced out of the surveys.  This was done by choosing location as the variable and heat map as the drawing style.  The yellow in Los Angeles represents a higher concentration of survey takers, as two different mock survey takers resided in LA.

Figure 7

   

After performing some data analysis, the next step in the tutorial involves creating a map with custom pop-ups within ArcGIS Online. This was completed by opening the map viewer and navigating to Configure Pop-Up.  Figure 8 below displays the window.  

Figure 8 - Pop up window of one of the mock-survey takers

  

Lastly, a web app is created by selecting the share button and create a web app, figure 9 below shows the results. Color themes are also available for the headers and texts.

Figure 9 - Survey viewer map

Conclusion
Survey123 is a useful app that is capable of collecting meaningful data for spatially related questions.  It seems to be well suited for geographic techniques such as urban and general infrastructure planning.  Even though the data collected for this specific assignment was fictitious, it still shows the great potential and flexibility this application has in projecting various forms of data on a very accessible platform.

Sources:

https://learn.arcgis.com/en/projects/get-started-with-survey123/

Lab 3: Evaluation of UAS Platforms and GPS Units for Ground Control

Introduction
On September 30th, 2017, the Geography 336 class ventured to Litchfield Mine in Eau Claire, WI.  This field outing was a rare opportunity for students to utilize and evaluate a spectrum of highly sophisticated field equipment.  This activity required students to place Ground Control Points (GCPs) and use a variety of GPS units to gather coordinate data at each GCP.  The GPS units ranged from highly accurate to significantly less precise to display the variety of GPS markers available in today's market.  Unmanned Aircraft Systems (UAS) platforms were also utilized to gather aerial imagery over the study area.  The focus of this lab was to simply collect the data and become familiarized with the different types of surveying platforms.  The data results will be presented in the next lab.  Figure 1 below displays a segment of the study site.

Figure 1 - Litchfield Mine Site 

Study Area
The mine was located off of highway 37 south, the coordinates being 44.7741731, -91.5713886.  The Litchfield mine is regarded as an aggregate mine, consisting of coarse particulate material such as crushed stone, clay, sand and gravel.  Such materials can be used to establish concrete for the construction of roads, buildings and dams.  Figure 2 displays a satellite image of the study area.

Figure 2 - Aerial satellite image of Litchfield Mine (courtesy google maps)

Methods
The activities of this lab involved collecting GCPs throughout the study area, as well as obtaining aerial imagery and topographic data. Sixteen unique GCPs were distributed within the survey area in order to geo-reference the data captured by the UAS platforms.  All the data collected for this blog will be processed on a later date over ArcGIS.  Students were first instructed to establish 16 GCPs throughout the study area.  Figure 3 shows an example of a GCP marker. 

Figure 3 - GCP Marker

It was important that students did not cluster the GCPs, and areas with more terrain required a heavier concentration of points.  Once all 16 were established, the class broke off into separate groups in order to record the latitude and longitude of each point.  To illustrate the variability in precision, multiple GPS units were used.  Coordinates were recorded on Cellular devices, a Bad Elf GPS unit and a TopCon HiPer HR and SR.  Figure 4 below shows students positioning the Topcon HiPer on one of the GCPs. 

Figure 4 - Students and professor establishing Topcon HiPer on a GCP

It was essential that the pole was perfectly straight up and down to record an accurate reading.  When recording data with this particular GPS, one must wait until reads "fixed", then it will initiate collection.  Once it has collected thirty coordinates, selecting "Store" and "Save" will give one accuracy within a few millimeters accuracy.  Other coordinates were collected with Arrow GPS markers from Menet Aero.  These markers were solar powered GCPs, positioning with satellites and ranging in accuracy from 2 to 6 cm.   

After collecting GCP coordinates, the class was introduced to a variety of highly sophisticated UAS platforms from Menet Aero and TopCon Solutions.  Four different drones were utilized to record the spatial location of the GCPs via aerial imagery.  These models included the DJI Phantom 3 Pro, Sensefly eBee, C-Astral Bramor ppX and the M600 Pro.

DJI Phantom 3 Pro 
This was a small rotary wing UAS from Menet Aero.  On a full charge, the unit could fly for one hour.  It had a camera fixed on the bottom and ran on software called MOCO (minimum obstacle collision avoidance).  An app called "Drone Deploy" was used to operate the flight, enabling the user to control and direct the flight to collect coordinate data of GCPs as well as gather aerial imagery of the study site.  Figure 5 shows the Phantom.

Figure 5 - Phantom 3 Pro Unit

Sensefly Ebee
This particular aircraft (from Topcon Solution) was a fixed wing unit, composed of light weight Styrofoam.  The Ebee is able to handle wind speeds up to 28 mph, being programmed to return to the launch site under the circumstances of high wind speed, poor GPS signal or poor connection to the controller.  The Ebee was held in the air and then released once it starts up.  It captured images from 160 feet in the air, having a 40 mp camera.  In mid-flight, the aircraft began to spiral out of control, eventually crashing into the Chippewa River, where it was later recovered.   Normal landing procedure for this UAS would involve using a landing strip.  A disadvantage of this aircraft, then, is the fact that it needs a lot of space for landing.  Figure 6 below displays the Sensefly Ebee.

Figure 6 - Sensefly Ebee pre take-off

M600 Pro
The next aircraft flown was a larger, 6-rotor drone from Menet Aero.  It is capable of flights up to 40 minutes.  This particular drone used Real Time Kinematic (RTK) satellite, which uses coordinate data to navigate in flight.  It took off and landed smoothly.  Figure 7 displays the unit.

Figure 7 - M600 Pro awaiting take-off

C-Astral Bramor w/ Sony a6000
The last aircraft demonstrated to the class was the C-Astral Bramor w/ Sony a6000 from Menet Aero, shown in figure 8 below.  This was another fixed-wing drone, but with a much larger wing span than the Sensefly Ebee.  A sling-shot-like structure was used to launch the unit into the air.  Landing involves deploying a parachute to enable it to land carefully back to the launch site.  Unfortunately for this demo, the parachute failed to deploy, and the drone ended up crashing.

Figure 8 - Launch pad of Menet Aero's fixed wing

Conclusions
Although the coordinate readings are different for the cell phone and Bad Elf degree points, it is impossible to determine which one was more precise until the data has been processed. Figures 9 and 10 below show the coordinate readings for both devices.  It also appeared that Rotary-winged aircrafts proved their reliability over fixed-winged aircrafts on this outing, as they smoothly took off and landed, unlike the fix wings- which never successfully made it back to land.  Soon this coordinate data will be unified with the aerial images captured by the drones to create a map of the mine.

Figure 9 - Coordinate Readings from Bad Elf

Figure 10 - Coordinate Readings from Phones (Z=Elevation)