ArcCollector 2

Introduction

This project was looking at what kind of vehicles people drove on Hudson Street between 1st and 3rd Ave. in Eau Claire, WI.  It was also comparing the different types of vehicles to figure out which state, Minnesota or Wisconsin, has the more environmentally friendly vehicles parked on the road.  Proper design is very important when trying to answer questions using ArcCollector. If the design is not set up correctly, going into the field will become very difficult and the whole process will roll to a halt.

Study Area:

• November 29th 2016 41 Degrees and Overcast  
• Hudson Street in the City of Eau Claire from the 1st block to the last.  This area has many different types of people making the variation of cars higher.  There will be permanent families, renters, college students, friends or family, and any maintenance workers as well.

Methods

Creation of the Geodatabase

The first step to using ArcCollector is to come up with a question that has the ability to be answered by creating data points out in the field.  The next step before going out into the field is to set up a geodatabase, which houses and stores the data. Within the geodatabase a feature class needs to be created which will outline the mapping area.  That is strictly for appearance and makes it easier while being in the field.  Next, is to make a feature class that is for collecting the data.  This feature class needs to be a point feature class along with having a projected coordinate system of  WGS 84 Web Mercator, which is necessary to work with ArcGIS online.


Now setting up the point feature class there needs to be attributes to help solve the problem.  For this project the attributes used were Lisence Plates State, Car Type, Car Size, Wheel Size, which side of the street the car was parked on, and the quality of the car and this can be seen in Figure 1.  Then, in Figure 2, There are the domains that need to be set up.  Domains are used to limit the attributes to certain restrictions.  For example, The Car Type was set up to show a list of different car manufactures  within the domain to make it easy, and to stop mistakes from happening.

Figure 1: This figure is showing the different feature classes used to help solve the problem at hand.  

Figure 2: This figure shows the domains that were used for the attributes.  These are important because they reduce errors within  the field.  

Now, once everything is set up the main thing to do is to publish this as a service to be used on ArcGIS online. To do this Sign into ArcMap using an enterprise account or any other method.  Then, go File -> share -> publish as a service -> and basically follow the steps to publishing the material needed.  Once it is online the feature classes can be found on the website.  Once on the website it can be saved and shared to everyone, anyone with an enterprise account, or just the original publisher.  

The next step is to download ArcCollect for IOS or Android.  This is a very cool app because it allows the user to use the smartphone for the GPS and data collection rather than other equipment. Although, it really should only be used for data that does not need to be 100% accurate spatial wise due to smartphones not having the best GPS in them.  It gets the job done, but it should not be used when accuracy needs to be a priority.   On ArcCollector is is just adding data points when need be and entering the correct data.  If the domains were used properly this should be very easy on the smartphone.  

Next is uploading the data points into ArcGIS Online which can then be downloaded and manipulated to create maps in ArcMap.

Results

The results for this questions were actually quite indifferent.  It seemed to be that there was an almost even amount of more environmentally friendly on both sides.  This is a good result though because it shows that people are trying to take care of the environment. Figure 3 is showing the different brands of cars that were found.  This map is not the most beneficial to the question but it is interesting to see that there is not really any pattern or higher number of one brand of vehicles. Figure 4 is showing the quality of vehicles within the area.  This is important to see because it shows whether people are keeping their cars longer or getting newer ones.  in this map it is showing that more car owners have older cars based on the amount of rust/damage to the vehicle. In figure 5 it shows which side of the road the cars were on.  This attribute field was done to show how accurate the GPS is on the Iphone 6 used.  The map clearly shows many of the dots on the wrong side of the road of what they are supposed to be. If it was important to have very precise accuracy this type of GPS would not work. Figure 6 is just showing the size of the vehicle.  This includes the size of the car which is economic to sedan or small SUV to full size SUV for example. In Figure 7 the map is showing what kind of vehicle was found.  This was an important indication because a car would generally be more friendly toward the environment than a truck, but in this mapping area there were no trucks to be found.  Only SUVs, vans, and car were found.   Therefore, this is an environmentally friendly area.

Figure 3: This is a map showing the different brands of vehicles found within the area.  

Figure 4: This is a map showing the quality of cars.  This included New, Almost new, Some Rust, and Junker.

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Figure 5: This is a map which shows which side of the road the cars were parked on. 

Figure 6: This is a map showing what size of vehicle is found. 

Figure 7:  This is a map showing the type of vehicle found.  

Conclusion

ArcCollector is a great tool to use when collecting data due to is versatility in the field.  As long as it is set up correcting it can a great asset to data collection. Since both of the states had realitly the same amount  If this project was to be done differently it would be an asset to get the entire student housing area to see what the entire area is driving.  It would also be nice to set up a color option as well.  This could also be expanded into a different questions which could be trying to find out how environmentally friendly the student housing area is with their vehicles.  

Microclimate

Introduction

The field activity this week included using ArcCollector, which was downloaded onto our phones as an app.  The class was broken up into partners and set out into the different zones around campus to collect climate data including temperature, dew point, wind speed, and wind direction.  These can all be entered into a smartphone to instantly upload into ArcCollector.  The final part is to turn the data collected into a continuous surface map using the different types of data collected. The purpose of using ArcCollector is to generate a map that each student can download after each group uploads their data points.  This eliminates the need to share it on a share folder or have each student greater a different geodatabase with different domains which could make things more complicated than need be.

Study Area

• 9 November 2016 Sunny 50 degrees F.
• University of Wisconsin - Eau Claire Campus (Upper and Lower)
• Figure 1 Shows an aerial view of the study area. 

Figure 1: Area of Interest with the stations taken by each group.

Methods

Each of the 8 or so groups set off to their designated zone on campus to focus the most efforts in their area to ensure that most of the map has some kind of data points.  Each group was given a climate surveying device that calculated wind speed, temperature, and dew point, and to use ArcCollector on the app running on their Iphone or Android device.  Out class had the luxury of having a geodatabase already set up making the data entry easy when out in the field.  Since it was already all set up and each group was connected to it, all that needed to be done was to collect the information within the zones and come back to upload the data, therefore collecting all of the data was quick and painless.

Most groups seemed to be taking points about every 25 feet to get the outside of their zone before heading into the middle of their areas before making their way back inside to upload the data.  Then the data can be downloaded after everyone uploads theirs to create a set of feature classes that can be used by each individual.

Now that the data is downloaded and set up the fun process of interpolation is the next step.  Since there is not a pattern of points and not every point can be taken the choice for interpolation would be IDW (Inverse Distance Weighted).  This was chosen because this method weighs the points based on the distance from each other.  The farther away the next point the less weight that that single point will have.  This created Figure 2,3 and 4.

Results

There are most certainty some patterns that can be seen within the images created. The first patterns that are noticeable are with the wind speed (Figure 2).  Along the ridge or scarp, which separates upper campus and lower campus, there is a noticeable decrease of wind speed due to the scarp where the points are directly adjacent to.  Another pattern noticeable with the wind speed is around the river.  This is due to the river being a relatively open are allowing more wind to flow through that area.  Therefore, the area surrounding the river creates a zone of higher wind speeds.  Another area is the terrace, upper campus, which also has higher wind speeds because there are less trees within the area to slow it down.

Figure 2: Continuous map showing Wind Speed.  This map is also showing the wind direction taken at each station to show more patterns depending on the location. 

The temperature map (Figure 3) shows the pattern of having warmer temperature surrounding areas with buildings, compared to the areas that are heavily vegetated being cooler overall.  This could be due to the cement sidewalks absorbing the sun's rays, and emitting it to create a overall warmer climate. The vegetated areas are cooler because less of the sun's energy can reach the ground to emit its energy back into the surrounding atmosphere.

Figure 3: This is the Temperature version of the microclimate.  

The dew point (Figure 4) is lower around the Chippewa River and higher around the buildings on campus.  This is expected because there is going to be a higher temperature around the buildings on campus making the dew point higher because temperature directly influences the dew point.

Figure 4:  This is a map of the dew point around the UWEC campus.  

Conclusions

ArcCollector is a very powerful app for collecting data in the field.  Using some kind of smartphone can really add a lot to the power when collecting data in the field with its ability to use Bluetooth to a GPS that displays the necessary information on the smartphone.  Therefore, using ArcCollector on a smartphone is very similar, just without the Bluetooth technology which could easily be substituted for a smartphone's GPS.  Using ArcCollector sped up the data sharing with the class much faster than having to share around an excel file or any other way of getting everyone to enter the data making this an invaluable tool for group work like this when accessing data.  This can be adventurous in the field while working as a professional if there are multiple people working on a project, they could just update the data every day when they would come back from the field.  Being able to collaborate with all of the class made this sharing of data a lot faster and accurate than any of the other labs.  This lab was very important in the understand of creating a geodatabase and creating domains before entering the field.

Priory Navigation: Part Two

Introduction

As the second part to last weeks lab group 6 was able to utilize the maps created to navigate through the heavily vegetated and steep topography to find five locations given out by Prof. J. Hupy.  The tools provided to complete this lab included a GPS to locate markers and track the path taken, the maps from the previous lab, and a baseplate compass.

Figure 1: Baseplate compass (not exact one used)

Study Area

• 2 November 2016 3-5pm
• Area surrounding the Priory Hall 1190 Priory Rd, Eau Claire, 54701 
• Conditions:  Partly Sunny Temp. 65F

Methods

After being assigned the points the groups split off to find their first location.  To do this, a starting point and a bearing was needed.  To get the bearing the baseplate compass needed to be used, and the most helpful trick with that was having red in the shed once the arrow pointed at the first location. Another trick with the compass is to make sure there is no metal around it which could affect the direction it is given off. Next, was to get a distance between each point.  Group 6 also needed to make sure all of the points were accurately pinpointed on the map to make the bearing and distance as accurate as possible. This was to help measure out pacing to know how many steps to take between points when using the bearing.  

Since there were only five sets of points and we were the sixth group we got stuck doing the course backwards starting at point 5.  This was absolutely the hardest point for our group.  This was the hardest to find due to being on the other side of a a large trench. which was very far off of the main path leading down into the area.  Although, it was only really thick around the trench it was easy to navigate between the path and where it got thick due to being mostly trees.  

Figure 2: First Location

The next location for our group was actually not nearly as hard to find as we had the compass down and we knew exactly where we were.  This involved a great trip back down into the trench to come up the other side.  to find a pink flag around a tree.

Figure 3: The second location on the other side of the trench

The third location was actually the easiest one to find as we had seen it earlier on the way to our first location.  This one was right on the path and just a quick walk through the pine trees.  

Figure 4: Location 3.

The next location actually gave us a bit of a hike back to the dreaded trench.  This time we were well prepared, except for the fact that we were too far east.  after correcting our position we finally spotted the flag in the distance.

Figure 5: Fourth Location.

With all the confidence built up after finding 4/5 points Group 6 was on a high to find the final point.  This is when disaster struck.  Our GPS died leaving us to fend for ourselves.  This actually lead us up a unneeded hill to figure out we needed to be at a lower elevation.  While getting back to the major path we headed back to the east.  We spotted the flag and found our final point without having to use a GPS.  

Figure 6: Final Location

Discussion

This lab really brought out true wilderness skills of only having a compass a map and a GPS to guide.  Having the track log brought up some great laughs to see how many times each group had to turn around or look around at an area to find the correct flag.  My group only had a few hickups which was not actually using and of the pacing due to not remember to keep track after leaving a point and only following the bearing.  This did not cause too many problems due to still heading in the correct direction and being able to check the GPS. In Figure 7 there are many paths that cross and a lot of places where there are clear turn around to get back on the path.  In Figure 8, which is Group 6's path, there are a lot of dots that are seen right around the trench in the south eastern part of the map.  This is generally were we got the most lost.  There is also the path at the most north part of our tack record which is our group going a little too far north before realizing we needed to turn around to head south west to get to the first point.  

Figure 7: Complete map that shows all of the groups paths taken.

Figure 8: Complete map showing only Group 6 path taken.  

Conclusion

Overall this lab taught a few different things.  First off it taught how important it is to make a navigational map that is in the correct coordinate system.  This can be the different of a few meters off to miles off which can be a huge problem under time restrictions.  Secondly, it taught how to use a baseplate compass while using a navigational map.  Also, for my group it taught us how to not rely on the GPS because the batter could die for no reason at any moment in the field.  

Sources:

http://www.mapworld.co.nz/comptype.html

USGS DEM to make Contour lines