ArcCollector: Creating a database, features and domains for deployment

Charlie Krueger

GEOG 336

Arc Collector 2: Creating your own database, features, and domains for deployment and use in Arc Collector

Introduction:

For this lab the class was given the task of creating a question that would then be answered by collecting data using Arc Collector. Arc Collector is a program that pairs well with Arc Map Online which is where the data points would be stored before moving them to ArcGIS. Arc Collector allows for a person to plot points on a map in real time and assign data for that point. The data would be analyzed on ArcGIS and then be made into maps showing the answer to the question. The question that was created for this lab was “Do more trucks and SUV have hunting stickers on them then cars?” which would also track other types of stickers such as sports stickers or political one on all different types of vehicles.

Study Area:

The study area for this lab would be the campus of the University of Wisconsin Eau Claire. More specifically the study areas would be limited to the parking lots around the campus. This is where the vehicles that would be studied would be located so the parking lots around the dorm buildings and teachings buildings would be the focus areas. Not every parking lot would be covered during the lab but the data that was collected would be sufficient to answer the question.

Map of the study area with the locations of the data entries

Methods:

To prepare for the collection of the data Professor Hupy told the class that ArcMap Online had a very good tutorial that would help the class set up a database to use and a map to share. This took quite a process to create a database that could then have data added to it in live time when the students were collecting data on Arc Collector.  The database had to be created using ArcMap and was placed into a specific folder where it would be stored. This database would be created to each student’s individual needs for what they were looking to answer with the data that was collected. The domains were where the students would customize things that they were looking for in the research. The domains for the question that was being investigated were the sticker domain, vehicle type, estimated age, and upkeep of the vehicle. Each one of these things would help tell me something about the question that was trying to be answered. The next thing that would be created from the database is the feature class that would be the actual points that would be plotted when using Arc Collector. The feature class that was used was the vehicle type class because this seemed to fit the best and had the least amount of options when defining the class.  Once the database was set up it was to be shared to ArcMap online was that it could be used on Arc Collector. The feature class could then be added onto the base map that was online and then the map was saved and was ready to have data added to it. This was then when the students could go out and add research data to the maps that were created.

Results/Discussion:

Table of the Data

             When first analyzing the data it was clear that the campus of UW Eau Claire has much more cars and SUVs than it does trucks. This makes sense for a college campus because cars are usually cheaper to purchase and to fill up with gas. So the data does not have that many trucks, jeeps, or station wagons which were thought to be the vehicles to have the hunting stickers on them. The data that was collected did show that trucks did have more hunting stickers on them then cars and SUV do. So going back to the question of the project it was answered by the data collected even though the data lacked more trucks in the survey. When collecting data, it shows that the upper campus was more of the main focus and this was because the bottom part of campus can always be changing with vehicles coming and going where upper campus has less movement of vehicles because the drivers live in those dorm halls where the vehicle is parked. An issue that did arise during the collection of data was the fact that many vehicles would have more than one sticker on them and then the decision of which category they would be put in came up. The way this was resolved was if a car had more type of one sticker than another type it was placed in the sticker group with the higher court of that sticker. Another thing that was noticed was issues such as a UW Eau Claire sticker that also had mention of a sports team on it. This was difficult because it represented two groups of sticker at the same time while only being one sticker. Overall the data that was collected was very representative of the campus but as always with more data comes a more accurate answer to the question that is being asked.

Interactive Map of the Original Data Collected

Map of the Vehicle Locations of the data

Sticker type and the locations on them in the study area

Conclusion:

               The need for proper project design is very big when looking to answer even simple question such as the one in this lab. There were issues when collecting data that were not thought of before and after the fact it was too late because the database was already created. Yes, the question did get an answer for the collection of the data but could be better when looking at the amount of data that was collected. If one thing that could have been different it would have been the classification of the stickers and to think about the fact that usually people have more than one vehicle sticker. Also if given another project such as this it would be good to make sure that Arc Collector is working properly before heading out to collect data and finding out that the domains are not in it.

Micro Climate

Charlie Krueger

GEOG 336

Arc Collector Part One: Microclimate

INTRODUCTION

In this lab the class was given the task of gathering data about things like temperature, wind speed, and dew point on campus through a program called Arc Collector. Arc Collector is a program that can be downloaded onto a smartphone or a tablet and allows the user to collect data that will be uploaded to a map in ArcMap Online. Everyone in the class had to create an ArcMap Online account so that the data that was collected could be uploaded to the class map so everyone could access the data. Professor Hupy had already created a map of the study area that the class would be using and dissected that area into five sections so that the data was not all from a small section. The class was separated into groups of two people and then sent into different sections of the study area.

STUDY AREA

The study area that was set by Professor Hupy consisted of the campus of the University of Wisconsin Eau Claire. The study area was separated into five sections so that the groups would get a wide range of data of the area because of the fact that the University does have a wide variety of setting on the campus. There was a section that included the walking bridge and the other side of campus also a section that had the large hill and the area with many dorm buildings in it.

Area of Study divided into the Sections. The section across the river is area 1, to the right of that is area 2, below that is area 3, section 4 is along the river, and section 5 is the farthest to the left. 

METHODS

The methods that were used in this lab were done so with smartphones and a hand held Kestrel 3000 Pocket Weather Meter. The smartphones which had the Arc Collector program on them were used to track the GPS position of the groups as they moved about the campus. Arc Collector was used to plot the point where data was collected and to enter the information that was gathered there. A table would pop up on the app and then things like temperature, dew point, wind speed and direction were entered into the table to then be used later. This data was gathered by using the Kestrel 3000 Pocket Weather Meter which has a small display screen of the information that it is displaying and has arrow buttons to change what is being viewed. Both of these tools were easy to use because smartphones are so widely used in today’s society and the Kestrel was also very easy once Professor Hupy demonstrated with it.

Kestrel 3000 Pocket Weather Meter

            So with both of these tools the groups took off around campus to gather data from all different locations. The group was set into section five of the area of study which was up the hill and around some of the building on campus. Some locations were in the sunshine and blocked by buildings from wind, while others were very windy and in the shade of a building. Certain sections of the study area gave access to different types of environmental features like being over the river to take a wind measurement. Some sections were on top of the hill on the campus which is a very steep incline and had more wind because of the elevation. All the data points and the information taken at those points was sent back to the map in ArcMap online for the class to use the data in making map. The information was saved by each member of the class and then was used to created map that would interpret the data the was gathered and also look for changes on them.

Map of the area with the different groups points in different colors

The information was brought into Arc Map and all that it contained was data points and the information that the class had gathered. From here the data would be placed onto a base map that showed where in the study area the points were taking at. The next step was setting up a mask for the interpolations. This meant creating an outline for the points so that when an interpolation was run it would only use the data from inside that outline. Otherwise the interpolation would not be showing the change of just the data points but of a much larger area where no data had been collected. The final step was running the interpolations for the temperature, dew point, and the wind speed. The interpolation that was used was nearest neighbor which selects the value of the nearest point and then uses that to determine a value for the space. The interpolation spline was not working in Arc Map and gave very strange outputs where nearest neighbor looked to follow the data that was provided.

RESULTS/DISCUSSION

Temperature Change Map

This is the first map that was created from the data and used the temperature that was gathered at the points. The data that was collected shows the how the temperature is different around campus and the minimum and maximum temperature that were found. As the maps indicates the highest temperature was found around the center of the campus. This could be from the lack of wind from the surrounding buildings and the possibility that the points collected were directly in the sun light. The coldest temperatures were found near the very steep hill of the campus which is also surrounded by forest which is shown by the dark blue area of the map. A section that also shows dark red which is high temperature is across the river on campus. This is kind of an outlier but could be because of the exposed area and the sun light hitting that area.

Dew Point Change Map

This was the map that was created from the data collected on dew points. Dew point is the temperature of the atmosphere below which water droplets begin to condense and dew can form. The map shows that the higher dew points were found near on higher elevation. The outlier of this map would be the area in the middle of the upper half of campus, the blue section surrounded by the light yellow area. This area may have been created by inaccurate measuring or by the program that was ran to create the map. There may have not been points here to show that the dew point was closer to the color yellow and not blue.

Wind Speed Map

This was the final map and was created by the wind speed information that was gathered. There are not outliers in this map because the dark red section would be the windiest spots on the campus. The upper campus is usually more windy because of the elevation and even with the buildings there can be very strong gust of winds that funnel between the buildings. The other very windy spot is on the campus walking bridge which is normally very windy because the wind blows right down the river and has nothing in the way to create a wind break.

CONCLUSION:

This lab was successful in showing the changes in temperature, dew points, and wind speed. The data that was collected and then made into maps shows the areas around the campus were these changes happen. Arc Collector was effective for this lab and allowed all of the groups to go into separate areas yet still send data to the same map. It also helped when transporting data in ArcMap because the data was easily downloaded from Arc Online. Overall this lab was a success for the class. 

Using a Navigation Map

GEOG 336

Charlie Krueger

Using a Navigation Map

INTRODUTCTION:

In the previous lab the class was assigned the task of creating a navigation map of the study area, which was the priory an area of land owned, by the University of Wisconsin Eau Claire. This area was not near the rest of the campus and was used to house overflow students and students who did not want to live in the dorms on campus. The maps that were created in the class would be used near the priory to locate points that Professor Hupy had marked in the woods. Each group was given a different set of coordinates that would lead them to the points if the maps were used correctly. Professor Hupy provided each group with a compass, a GPS, and a map print out for each of the members of the group. Each group had to decide which map would be most helpful when navigating and then send it to the Professor so it could be printed. The whole class gathered in the parking lot of the priory and started preparing for our adventures.

METHODS:

One of the first things that happened in this lab was the explanation in how to use a compass to successfully navigate a map and get to the coordinates. Professor Hupy gave each one of the groups a compass and explained to them how a compass works and then took them through the step-by-step process while the groups used it on the maps. There was the explanation of all the different parts of the compass and how to use each of them like the direction arrow and the bezel, which is the area that has the 360 degrees on it. Holding the compass to the chest was also crucial for navigation because that was the direction of movement. After the course on how to use the compass Professor Hupy had everyone in the class find their pace. This is when you take a standard length like 100 meters and count how many paces it takes a person to get to the end. The key to finding pace is to only count one of every two steps so each time the left foot hit the door would be a count. This pace would be used to keep track of distance covered when using the map. After the class had all found pace each group was given a GPS unit that would track the locations of the groups as they tried to navigate to the coordinates. These GPS units would then produce the trails that the groups followed to get to their navigation points. Professor Hupy then informed the class that each member of the group would have different tasks. The first was pace counter who would keep his pace during navigation; followed by azimuth control that sets the direction to travel in picking out landmarks to head towards, and finally the leap frogger who would move to the landmarks allowing the pace counter to move to it and then the azimuth control. Before leaving all the groups marked a rough estimate of where the coordinate points were thought to be on the map and then set off. The maps being used were set in the UTM coordinate system and so were the coordinate points.

Map with Group1 track to coordinate points

RESULTS/DISCUSSION:
So starting off was a difficult process because the group had to really guess where the starting point was on the map and just go from there. Finding the first point was a bit of a hassle for the group because of this fact and the issue of the vegetation was a problem from the start. Also the group did not yet now what the points were going to be marked with so looking for a specific color was not an option. This first point was difficult because no person really knew how to follow the individual tasks that were assigned. Counting pace became difficult when crossing over trees and debris. Also the group did not really use the leap frogger at the start, which probably would have helped find the point faster. Luckily it was realized that a correction needed to be made and that the point was more towards the left and still up ahead more. Finally the marker was found and it was florescent pink ribbon tied around a tree.

First Point Located and Planning for the Next

            

The next point was found very quickly and each of the group members preformed that task assigned to them. Point two was located and as seen on the map the line to the point was fairly straight and the best location that the group had. When trying to locate point three the group some how landed over near point four and then had to back track to hit point three. The location of point 3 was difficult because on the map the location looked to be surrounded by very steep raising hills that were not ever seen. So the whole group though this was interesting but when navigating to point three it was obvious that the point was not near hills but ravines. The hillside was very steep and not crossable by the group was going around was the only option which messed up pace and direction. The group then struggled to find point three at all but finally stumbled upon it. Here when the group looked at the GPS the coordinates that were given to the group and which were plotted on the maps in use were slightly off. This also added to the difficulty finding point 3. Finally point five was located after the longest walk of the whole navigation and a fun walk through some thorn bushes.

            The two items that defiantly effected the navigation of the group was vegetation and elevation. Both influenced paths that could be taken or not be taken which then messed with the navigation.

Finding point one and planning the next

Third flag Finally found!

SUMMARY:

The navigation of the priory was very interesting and was a great way to introduce these life skills like using a compass and map into an adventure. The map that was used could have always been more detailed if it could have been larger but for an 11x7 it was almost perfect for this activity. Using the assigned tasked defiantly worked when the group used them to navigate but it was still difficult to navigate like this. A compass is a tool that will never run out of batteries but it comes with a learning curve that can only be fixed by using it more.