Lab 08 - Integrate Maps, Apps, and Scenes to Tell a Story - Dashboard, Web Scene, and Story Maps

Introduction

This geospatial lab activity was focused around the creation of various online cartographic elements to accurately and thoughtfully tell a story to a reader. This was accomplished through the completion of an ESRI ArcGIS Online tutorial tilted Integrate Maps, Apps, and Scenes to Tell a Story. Following the completion of this tutorial, the elements created, which included an ArcGIS Online Dashboard, a Web Scene, and a StoryMap, visualized the risks associated with the sample data from the tutorial, in this case California earthquake data, population density data, and proximity top fault lines data. The final product of this tutorial is a web map, app, and story that accurately portrays the earthquake risk for the state of California and helps those that live in these areas to be better prepared for a dangerous situation. Through the completion of this tutorial, the user gains greater experience in the use of Dashboards, Web Scenes, and StoryMaps.

Methods

The first step in the completion of this ESRI tutorial was to launch the pre-made ESRI California Recent Earthquakes and Earthquake Risk ArcGIS Online map. This map contains the data and layers to be used in the creation of the Dashboard for this assignment. Using this map, the Share>Create a New Web App>ArcGIS Dashboards option was selected to turn this map and the data within it into a Dashboard that can be edited and displayed.



Next, elements were added to the Dashboard that displayed the necessary information about earthquakes that had occurred recently and their magnitude. The first elements added was a Legend elements that was to be docked on the right side of the screen to display pertinent information about the map. The next element to be added was an Indicator element that was filtered to display the Magnitude for the past week Events by Magnitude. This filter only shows earthquake events that have taken place in the last 7 days, filtered by their magnitude. This Indicator element was then given some description text and docked on the right side of the Dashboard.



The next portion of this tutorial exercise was to create a Web Scene. This was done by searching for a Web Scene in the ArcGIS Living Atlas, the Urban Indicators – Population Density (U.S. only) Web Scene. This scene was then modified with another online data layer that visualized fault lines across the United States. The next step was then to add slides to this webs scene for each of the four largest population centers close to fault lines in California; Los Angeles, San Diego, San Jose, and San Francisco. These slides were saved and the edited Web Scene with the slides and added fault line data was saved.


The final step of this tutorial exercise was then to bring all of these elements together and create a ESRI StoryMap. The StoryMap was created with text, titles, and pictures provided by ESRI in the tutorial that made it visually appealing with the correct text information to assist readers. Content was then added to the StoryMap, with the Dashboard and the Web Scene App added respectively. Finally, additional information related to earthquake knowledge and how to stay safe in the event of an earthquake were added to the bottom of the StoryMap.

Link to completed StoryMap
https://storymaps.arcgis.com/stories/6c092d1fa9df432bb7836e8974f3454a

Discussion

The completion of this tutorial exercise shows the benefit of creating many of these ArcGIS Online resources such as Dashboards or Web Scenes to convey information about a variety of subjects in simple to understand and visually appealing ways. Creating such resources are valuable to those who need to know the information contained in them, such as how those living in Californian need to be aware of their proximity to fault lines and what to do in the event of a major earthquake so that they are able to stay safe and healthy. 

Conclusion

Through the completion of this tutorial exercise, I was able to gain further experience in the creation of ArcGIS Online Dashboards, Web Scenes, and StoryMaps. All of these resources and knowing how to create them are valuable pieces of information that will be useful in my continued development as a geospatial professional. 

Lab 07 - Oversee Snowplows in Real Time - ArcGIS Dashboard & Web AppBuilder

Introduction

This geospatial lab exercise was an introduction to working with real time data in AcrGIS Online, creation of a ArcGIS online Dashboard, and creation of a web app using Web AppBuilder. To accomplish these goals, an ESRI online tutorial, Oversee Snowplows in Real Time, was completed. This tutorial sets up a hypothetical situation where you are a GIS coordinator in Utah who needs to monitor the progress of snow removal after a snowstorm. To accomplish this monitoring, you need to create two different apps, one for citizens to view that shows information related to how much of the roads have been cleared so far, and one for city officials that shows additional information about the city's snow plow fleets so that city officials can better manage the situation. Both of these created apps use real time updating information about snow removal and snow plow location to create an up to date map for citizens and city officials. 

Methods

The first step in this ESRI tutorial was to create a real-time web map. This was done by simply creating an ArcGIS Online map and adding the provided data that was part of this tutorial. This data was symbolized to aid in visualization and the refresh interval was set to every 0.1 minutes or 6 seconds, the minimum refresh interval allowed. 

Data on the location of snow plows in the city were symbolized with arrows which were then rotated with the geographic heading option to show the direction in which the snow plows were currently heading. Snowplows were also labeled and filtered to aid in organization.

With this done, the next step was to create the ArcGIS Dashboard which displayed a list that updates in real time that contains the name and speed of each snow plow, a bar chart that displays plow's real time speeds, a pie chart that shows real-time percentages of clear vs. unclear roads, and a list that shows the street names with their plowed status. This Dashboard was set up with the provided title and summary from the ESRI tutorial and then was created using the Web Map created in the previous section. With this done, the first step was to create the list that shows plow information using the vehicle (latest) layer from the web map to display the real-time location of each plow. The plows in the list were then organized by plow name and speed and labels were added to the list.

Next, a Serial Chart was added to the map that used the vehicle (latest) layer as a data source and was set up in a way to display the real-time snowplow speeds as a bar graph.

With this completed, the next step was to add a pie chart to the Dashboard that uses the Streets Plowed Status data layer as its source. Data was categorized into plowed or unplowed status with additional label and filter information added top the pie chart.



Finally, a simple list element was added to the Dashboard that lists each of the streets as well as what their up to data plowed status is. 



Finally, using information from the Web Map and the Dashboard completed previously, a Web App was created using the WebApp Builder as part of ArcGIS Online. Title and summary information were entered in based on the information provided from the ESRI tutorial as well as a color scheme and theme. Finally, the Stream widget was added to the Web App which allows for the visualization of the real time data present in the Web Map and Dashboard created earlier. 

Discussion

This tutorial continued to increase my knowledge and experience with many of the online resources offered through the ArcGIS Online interface. I personally have very little experience with real-time data that updates as you work on it, so completing this tutorial definitely helped bolster my understanding and experience with such data types. Also as part of this tutorial, I was able to gain experience in the creation and use of both Dashboards and Web Apps, both of which I have only had limited exposure to before the completion of this tutorial. 

Conclusion

The completion of this ESRI tutorial certainly helped me better my understanding of both working with real-time data as well as some of the other online resources available when working with ArcGIS Online. I now feel more confident in working with real-time data as well as the creation of Dashboards and Web Apps. The knowledge that I have gained in the completion of this tutorial will certainly aid me in future classes and employment as I continue my training as a member of the geospatial field. 

Lab 06 - Fire Hydrant Inspection - Workforce for ArcGIS

Introduction

This geospatial lab exercise was an introduction to using Workforce for ArcGIS, an online GIS tool used to create and manage the completion of various projects. This introduction to Workforce was based off of the ESRI Workforce tutorial, "Manage Hydrant Inspections" where the user creates a hypothetical project to inspect fire hydrants in the San Diego area. This tutorial was broken into a variety of sections, each with their own goals and end products. These sections included "Create and configure a Workforce project," "Dispatch inspection assignments," "Prepare the firefighters," "Inspect a hydrant," and finally the optional "Complete additional inspections" to gain more experience. The completion of this ESRI tutorial allows for the user to gain valuable experience with Workforce for ArcGIS and some minor experience with Navigator for ArcGIS.

Methods

To begin this exercise, we first launched Workforce for ArcGIS and began by creating a project with the provided set up info. This info provided through the tutorial for the basic setup of our first project included info on a title and summary of the project, adding assignment types of work, and creating various roles such as dispatcher and mobile worker. 

Figure 1. Project setup window

With the project set up with users and tasks to get done, the next step was to customize the map for the tasks at hand. This was done by launching the map window within Workforce and adding the ESRI provided data on San Diego fire hydrants. With this done, we added pop up labels to each of the hydrants to aid in visual navigation. This was also done in the worker view of the map to allow field workers to look up hydrants by hydrant number to navigate to whichever hydrant needed maintaining. 

Next, we made sure that this project and its tasks were visible and accessible to the mobile workers who would be completing said tasks. This was done by making sure Navigator for ArcGIS was integrated to Workforce. This allows for the mobile workers to navigate to whichever hydrant needs inspecting. 

Back on the main page, the next step was to create assignments for the field workers to accomplish. To do this, the "Create Assignment" menu was opened and provided info from the tutorial was inputted. This includes the task which was hydrant inspection, a note on the location of the hydrant, the priority level, when this task is due by, and which worker it was assigned too. At this point, I also created optional additional assignments to gain more experience in the various settings and inputs that can be added to an assignment. These include images, higher or lower levels of priority, or even leaving certain fields of information blank.

Created and assigned task of medium priority to inspect a hydrant 

With this done, the final section of this tutorial was to launch the Workforce for ArcGIS app and complete some of the assignments we had created earlier. Downloading the app to my phone and logging in, I am able to see all of the assignments that I created earlier as well as a map of the area where the tasks are located. Clicking on one of the tasks, I am able to "Start" which allows the dispatcher to see where the workers are and what tasks are getting done. Also on this menu, you can pause the task and create a note to let the dispatcher know why you are pausing the assignment as well as finish the task once it is done. Within the main menu as a mobile worker, you are also able to go on break which pauses your location and means the dispatcher cannot send you additional tasks while on break. Finally, I completed the remaining assignments in the order of priority to get more experience using Workforce for ArcGIS.


Working on a task


Taking a break

Discussion

This tutorial further increased my experience with many of the online resources that ESRI offers. I especially enjoyed this tutorial as I can see this online resource being useful in possible future employment. The versatility and ease of use in working with Workforce for ArcGIS is also interesting as I would like to see what else can be accomplished with such a useful resource. 

Conclusion

Overall, this lab exercise and tutorial was a valuable addition to my ArcGIS experience and certainly worth the time spent on such a project. I now have the knowledge of how to both create and complete projects and tasks in Workforce if I was required to do so for a job or future class. By completing this tutorial, I feel confident in putting experience with Workforce for ArcGIS on my resume which will only help me in future employment. Knowing how to navigate and correctly operate this online resource is important in my growth as a geospatial worker and technician. 

Lab 05 - Introduction to Survey123 for ArcGIS

Introduction

This geospatial lab activity was an introduction into Survey123 for ArcGIS designed to give us all a basic understanding of what can be accomplished with Survey123 before we went on and developed our own survey. This introduction was given through the Survey123 tutorial as a part of ESRI's free online instructional tutorials. This tutorial has the user create a safety survey for their fictional Home Owner's Association (HOA) that would be distributed to all those living within the HOA. This tutorial then teaches the user how to analyze and share the survey that they had just created. Following the creation of this survey and the completion of the tutorial, I then went and designed my own survey designed to collect information on the types of crosswalks around UWEC campus and the overall level of pedestrian usage of said crosswalks.  

Methods

The first step of the ESRI Survey123 tutorial was to create a new survey and name it, add tags, and add a description with the provided information about HOA safety.

Next, a basic overview of the Survey123 interface was run through so that the user can understand the different tabs of information, what everything on the screen means, and how to add in the necessary survey elements. 

Next,it was time to add elements to the survey that will be important to obtain the necessary HOA safety information. These elements included a map, text boxes, check boxes, radio buttons, and photo uploads. All of these elements were labeled with appropriate questions and answers with some also being assigned hints to aid the survey user in determining what kind of information to fill in the survey with.

Some questions that were to be asked in the survey had various options for answers, with some questions being dependent upon the user's answer to a previous question. This sort of question dependency can be easily incorporated into a Survey123 survey through the use of the Set Rule button, which allows for a certain answer of one question to open up another possible question.

Continuing with this tutorial, many more questions were added with the provided label, hint, and answer information. Finally, the survey was saved and published online so that other members within my organization, in this case UWEC, can see the survey.

With the tutorial survey completed and a better idea on how to go about creating my own survey, I did just that. The survey that I created was one designed to assess the the level of safety that pedestrians have when using many of the common intersections in the area around UWEC campus. To do this, I created a survey with a map of the Eau Claire area that allows the user to pin a certain location on the map, a drop down selection with the various types of crosswalks found in the area, and a multiple choice radio button that allows to user to input the level of pedestrian traffic from low, medium, or high for that given intersection. This survey and the data attained from it can be used to craft a rough idea on what crosswalks may be the safest for pedestrians and which ones may be unsafe.

Discussion

While I have had extensive experience with ArcGIS online and many of its resources before, I did not have any experience with Survcey123 and thus greatly enjoyed this lab exercise as it provided me new and useful knowledge. The versatility and ease of use in creating a survey with Survey123 will most likely come in handy in future classes that I will take. I can see the potential for using these types of surveys to accomplish a wide variety of projects for many different types of classes, including those that are outside the field of geography. 

Conclusion

Overall, learning how to use Survey123 to create and implement a useful survey was an important and beneficial exercise to undertake. This lab exercise gave me insight into the fact that there are many useful methods and applications for such a survey that is overall, quick and easy to create and share. The wide variety of possible uses for such surveys leads me to believe that I could use such surveys for topics that I may not even be aware of yet. Using Survey123 left me with valuable knowledge about this tool and also valuable data that could be useful in the creation of future projects.

Lab 04 - Conducting a Distance Azimuth Survey

Introduction

The focus of this lab exercise was how to overcome problems encountered in the field related to properly conducting an accurate survey. In this lab exercise, we gained experience in conducting a distance azimuth survey using a variety of survey methods and technologies. These include higher tech options such as GPS and laser rangefinders, to simpler ones like compasses and measuring tapes. We employed this different methods and technologies to conduct a simple survey of a variety of trees spread around the University of Wisconsin- Eau Claire campus.

Methods

To begin this survey, we first familiarized ourselves with some of the equipment we would be soon using. Some of the simpler equipment like compasses and measuring tapes are quite self explanatory and we all had experience with them. Next we familiarized ourselves with how to use the GPS unit, in this case a Garmin eTrex Handheld GPS, and the laser rangefinder, a TruPulse 360B Laser Rangefinder which can measure both distance and azimuth.

Garmin eTrex Handheld GPS

TruPulse 360B Laser Rangefinder

Using this equipment, our lab group left Phillips Science Hall and headed out to the central area of campus to conduct the survey. Our group was assigned a starting point to the South side of Schofield Hall and then picked five trees to survey. We began by recording the latitude and longitude our starting point that the trees would be surveyed from. This data was recorded in the field at the time of data collection. Still using the GPS unit, the next step was to record the elevation value in meters of each of the trees that were being surveyed. With this data recorded, we then used the laser rangefinder to determine the azimuth in degrees to each of the trees from our initial survey point. This was done by looking through the rangefinder and depressing a button on the top of the unit which automatically determined the azimuth. The next data to be recorded was the distance from the starting point to each of the trees. The laser rangefinder was used for some of the measurements, but the low sun shining in created glare and the rangefinder struggled to get an accurate measurement past a certain point. To address this issue, we simply measured the distance from the starting point to each tree using a measuring tape. Finally, each of the surveyed trees circumferences were measured which was used to then calculate the tree's diameter and the tree's species was recorded as well.

With all the data collected, the groups returned inside to enter the data into an Excel spreadsheet, save it as a .csv, and import it into ArcGIS Pro for analysis. The first step of this analysis was to create a point using the collected lat/long that represented the initial survey point for each of the groups. With this done, the Bearing Distance To Line Data Management tool was run. This tool creates line features originating from a point based on a bearing, in this case the collected azimuth data, and a distance, in this case the measured distance from the starting point to the surveyed tree. 

With this tool run, line features originating from the original survey point to the surveyed trees were created. Next, the Feature vertices To Points Data Management tool was run. This tool creates a point at the end of each of the line features originating from the origin create earlier.

With these tools run, all of the necessary map features have been created. The next step was then to create cartographically pleasing maps that visualized the survey area, the survey origin point, direction from the survey point to each of the trees, tree species, tree diameter, and tree elevation.

Results

Conclusion

This field exercise proved troublesome to complete, as some of the equipment that was used either failed entirely or failed to work as well as it was supposed to. Luckily, we had the tried and true methods of simply measuring by hand using a compass and a tape measure that proved useful. Because these methods were not always foolproof, the data seen in the maps above is not 100% accurate and true to the real world. Some of the tree points appear to be slightly off of where they should be and the azimuth's may not be exactly what they are in the real world. In addition to these problems, two groups had difficulty with data collection and entering of said data into the .csv. These two groups failed to properly collect the data and also failed to correctly determine the proper azimuth from their original survey point to each of the surveyed trees, rendering their data useless for this exercise. Even with these errors and troubles, the field exercise was able to be completed well enough to visualize all of the collected data. As seen in the maps, there are a variety of tree species present on Eau Claire's campus. Using the collected data for tree diameter, it can also be inferred that there are trees of a variety of ages present on campus.

Overall this field exercise provided us with a variety of useful field techniques that we can use in future classes or employment. These important skills of conducting a field survey under conditions that are not optimal, in this case because of failing technology, will prove very useful in the future because we are bound to run into some of these problems again.

Lab 03 Visualizations of the terrain survey data using ArcGIS both in 2D and 3D models

Introduction

            This second geospatial field activity is a continuation of the first field activity from two weeks ago where topographic data was collected at a small scale in a sandbox.  Using this collected topographic data that was entered into a .csv spreadsheet, a point-based feature was created in ArcGIS Pro. Various Spatial Analysis Interpolation tools were then run to create 3D models of the topographic data. These various interpolation methods included inverse distance weighted (IDW), Natural Neighbors, Kriging, Spline, and TIN.  The results of these interpolation methods were then compared to each other in ArcGIS Pro and ArcScene to determine which was the most effective compared to the actual site. To properly compare the results of each interpolation method, we went back out to the field site where initial data was collected and determined which interpolation method we as a group thought had done the overall best job at visualizing the topography at the site.

Methods

            The first necessary step was to import the .csv spreadsheet of collected topography data into ArcGIS Pro to be displayed at a point-based feature. This was done by using the XY Table to Point geoprocessing tool that takes an input table, assigns the data within the table to and X, Y, and Z variable, and then outputs a feature class with a desired coordinate system. The output result of this tool was a gird pf points where each point represented a point where topography data was collected from the sandbox. Each of these points have a Z value that is measured in centimeters, with some being a positive value and some being a negative value.

Figure 1. Example of table imported into ArcGIS Pro

IDW   

With the necessary grid data imported into ArcGIS Pro as a point feature, the various Spatial Analysis tools to create 3D interpolations of the data could be run. The first of these interpolation methods ran was the IDW interpolation. This method works by using a linearly weighted combination of sample points with the weight being a function of inverse distance. This method assumes that the influence a point has decreases with distance. Because this method uses an average for calculation, the average cannot be greater or lesser than the highest and lowest inputs, meaning this method cannot create ridges or valleys at the extremes of the input data.

Figure 2. Results from IDW interpolation method

Nearest Neighbor

The next interpolation method run was the Natural Neighbors Spatial Analysis tool. This method works by finding the closest subset of input samples to the point being calculated and weighs each of those samples based on the proportional area. This method can also not produce ridges and valleys unless they are from the value of a direct input because height values generated are within a range of the sampled values.

Figure 3. Results from Nearest Neighbor interpolation method 

Kriging

            The third interpolation method used was the Kriging Spatial Analysis tool. This method is considered an advanced geostatistical method that works by creating an estimated surface based off various points z-values. This method employs autocorrelation and assumes that the distance and/or direction of sampled points is indicative of a spatial correlation. Because of this, the Kriging model can not only create a predictive 3D surface but also determine the level of accuracy of said surface.

Figure 4. Results from Kriging interpolation method 

Spline

            The fourth interpolation method used was the Spline Spatial Analysis tool. This interpolation method works by estimating surface values using a function so that overall surface curvature is minimized and a smooth surface that passes directly through the data points is created.

Figure 5. Results from Spline interpolation method

TIN

The final interpolation method run is the Create TIN 3D Analyst tool. This tool creates a triangulated irregular network (TIN), which is a form of vector-based data created by triangulating sets of vertices. These vertices are the individual data points and their Z-values that were imported into ArcGIS Pro earlier. In this tools case, the connected vertices and their edges form non-overlapping, continuous facets which is ideal for capturing linear features such as ridges.

Figure 6. Results from TIN creation

           

With each of these tools run and the outputs saved, ArcScene was opened to view these outputs in a 3D environment. To do this, a base height for each of the 3D surfaces was set to a meters to feet floating on a custom surface value. Once all of the 3D surfaces that had been created were viewed in ArcScene, our lab group returned to the sandbox where we had collected topographic data and compared how the sandbox looked to the results seen from our created 3D surfaces.

Discussion

            Based on the results from each of the interpolation methods used compared to the actual sandbox where topographic data was collected, it appears that the Spline method produced the best representation of the real-world model. The reasons for this are that it is the smoothest of the four spatial analysis interpolations methods used for this example. The IDW method produced a pockmarked surface where each of the locations where data was collected are visible. The Nearest Neighbor method produced a surface very close to the Spline method but there was still a small amount of jaggedness present near some of the larger jumps in elevation.  Finally, the Kriging method did produce a surface model that was less vertically exaggerated but was still jagged in many ways and did not represent the smoothness present in the real-world model.

Conclusion

            At the end of this lab exercise, myself and my lab partners had gained valuable experience in collecting and analyzing topographical data. Of the many interpolation methods that we employed to convert our collected data to a 3D surface, some specific methods ended up working better than others, with the Spline method outputting the best surface model that was the most similar to the real world sandbox model. The various skills that I have gained through the course of this lab exercise will be valuable both in my future education and in my future geographic exploits.

Lab 02 - Familiarization With ArcGIS Desktop DEM Raster Tools and ArcScene

Introduction

The goal of this Field Methods lab activity was to familiarize us with the various spatial analysis tools that are commonly used on DEM raster files in ArcGIS desktop applications.  Understanding what each of these common tools does and the products that will be created upon running these tools was also an important goal of this lab.  Finally, another goal was to gain experience in the viewing of DEM raster data in a 3D platform such as ArcScene

Methods

To begin this lab, provided DEM data was copied into our individual class folders.  This data, had it not been provided for us, was obtainable through the WI DNR or through the USGS.  With this data, we opened ArcGIS desktop and created a file geodatabase to house the data in each of our individual folders.  With this done, the final step before processing the data was to turn on the Spatial Analyst extension under the Customize menu to allow for the use of Spatial Analyst tools.

With these set up steps complete, the first tool to be run was the Contour Tool found under Spatial Analyst>Surface>Contour.  This too creates contour lines at a user set interval, in this case 10 meters, and exports the output as a layer that can be added to a map document.

Figure 1. 10 meter contour interval of Eau Claire County DEM

The next Spatial Analysis tool to be run was the slope tool, found under Spatial Analyst>Surface>Slope.  This tool creates a raster file showing the relative steepness of slopes based off an input DEM.

Figure 2. Slopes of Eau Claire County DEM

The next tool after slope was the aspect tool, found under found under Spatial Analyst>Surface>Aspect.  This tool determines the aspect, or the cardinal direction, that each slope faces.

Figure 3. Slope Aspect of Eau Claire County DEM

The final Spatial Analysis tool to be run on this DEM is the Hillshade tool, found under Spatial Analyst>Surface>Hillshade.  This tool creates a shaded relief of a DEM that allows for better visualization of the topography of an area.

Figure 4. Hillshade of Eau Claire County DEM

Once all of the Spatial Analysis tools had been run, the next step was to visualize the DEM in ArcScene.  This was done to express the DEM in all three dimensions rather than in 2D like in ArcGIS desktop.  To do this, the DEM was set to 'floating on a custom surface' either by meters to feet, feet to meters, or based on a custom value.  These values determined the overall vertical exaggeration of the DEM.

Figure 5. Eau Claire County DEM shown with different levels of vertical exaggeration.

Discussion

This lab was very straight forward, with simple easy to understand directions that guided us students through the lab to accomplish the goals of the exercise.  

Conclusion

Overall this lab was very useful in developing my understanding of some of the spatial analyst tools present in ArcGIS desktop. this lab was also great in allowing us to gain more experience in working with DEM's both in ArcGIS desktop and ArcScene as well.

Evaluation

1.     Prior to this activity, how would you rank yourself in knowledge about the topic. 

         4-A good amount of knowledge

2.       Following this activity, how would you rate the amount of knowledge you have on the topic

         5- I am an expert)

3.       Did the hands-on approach to this activity add to how much you were able to learn.

         4-Agree

4.       What types of learning strategies would you recommend to make the activity even better?

          More in depth use of these spatial tools for a wider variety of applications.