Entry Name: CSUS-Padgham-MC1

VAST Challenge 2019

Mini-Challenge 1

Team Members:

Quinlan Padgham (Primary), quinlanpadgham@csus.edu

Ashka Soni, asoni@csus.edu

Hector Rios, hrios@csus.edu

Hung Quach, hungvinhquach@csus.edu

Andy Zhu, azhu@csus.edu

Margaret Davis, margaretdavis@csus.edu

Faculty Adviser: Anna Baynes, shaverdian@csus.edu

Student Team: Yes

Tools Used:

Tableau

Trifacta

Approximately how many hours were spent working on this submission in total?

200 hours

May we post your submission in the Visual Analytics Benchmark Repository after VAST Challenge 2019 is complete? Yes

Video

https://www.youtube.com/watch?v=l8qB_UJNCj8

Questions

1 – Emergency responders will base their initial response on the earthquake shake map. Use visual analytics to determine how their response should change based on damage reports from citizens on the ground. How would you prioritize neighborhoods for response? Which parts of the city are hardest hit? Limit your response to 1000 words and 10 images.

Figure 1: Medical Damage Over Different Districts

Figure 1 shows the sum of all reports towards medical damage at each point for each location in St. Himark. The purpose of this image is to evaluate the raw number of reports and their intensity at a quick glance, which helps gauge where focus should be spent at a high level. Areas with the greatest value have the largest raw sum of reported values, and are likely candidates for areas that have the most severely affected citizens. Adding the values of reports together helps to ignore oddities in reporting moment to moment where averages of reports or other similar metrics can vary wildly. This chart, along with others for the other reported categories, can be viewed here: Link

Figure 2: Average Damages seen in Medical, Roads, and Shake Intensity over all Districts

Figure 2 guides responders to critical data aspects that may be important for them to react quickly to the situation. The chart gives vital information such as the damages to roads/bridges so that they may navigate better to those most in need. Medical is also highlighted in this table to see the medical centers and/or medical needs of people. Lastly shake intensity is included here to give responders a quick view of how each district reported its shake intensity. Link

Figure 3: Reporting Quantities in Different Districts

Figure 3 displays each reporting element to the responders so they can be selective in what they want to focus on. From the averages of reporting of Buildings to Sewer/Water, the averages are displayed here. This table is meant to be adaptable to what the responders may want to see in the data, for example, certain events such as the relation of the reported power damage to the damage to buildings can be identified here. Link

Figure 4: The most impacted areas in the region.

Figure 4 shows the responders the level of severity reported in the overall reporting over time in each district. This helps guide responders to see the amount of reporting done for each district over time. The area seen in the table represents the proportion for each district. Overall, it is meant for responders to have a timeline which they can follow which highlights the reporting amounts for each district. Link 

Figure 5: City Influence in Reporting

Figure 5 shows responders the difference in reporting for districts that are affected by city projects that may affect reporting values. The blue area shows the sum of reports made that were not affected by city projects, while the gray area are the amounts of reporting in districts with city projects in them. This table helps responders see the increase in reporting in areas that may have been affected by city projects. Link

Figure 6: Shake Intensity versus Building and Medical Report Quantities among Different Locations during Earthquake

In summary, he emergency responders can prioritize their neighborhoods based on the number of reports each location received. From the graphs above, we can see that location 3 is highly affected along with the day and time. The affected areas can be pointed out with the shake intensity that is high.  Link

2 – Use visual analytics to show uncertainty in the data. Compare the reliability of neighborhood reports. Which neighborhoods are providing reliable reports? Provide a rationale for your response. Limit your response to 1000 words and 10 images.

Figure 7: Map of Relative Volume of Reports

The map above shows the relative volumes of reports (the size of the squares for each area) and the average value reported (color and number below) for shake intensity. This helps give an idea of how much each group is reporting, and can be viewed in relation to the perceived severity. One location of note is region 8, along the southeast shore. They have a relatively high volume of reports given the relatively low value for shake intensity.

Region 8 also had particular pattern of reporting. Whereas most regions at the beginning of a quake would have a sudden burst of reports that tapered off over time, region 8 instead often would start more slowly and build in intensity. This could suggest that region 8 had a spread of knowledge about the quake or potential damage and then would report it based on hearsay, rather than reporting first hand information.

The first image shows the number of reports by individual hours of the neighboring locations in the northern part of St. Himark that should be affected by the earthquake, based to the shakemap. The locations tend to follow the same reporting pattern throughout the day but most of the reporting from Location 3 is done in short intervals of 1-2 hours through all three days. The second image shows a positive correlation between shake intensity and damage among these locations. Location 3 stands out amongst the others by consistently having the greatest shake intensity and damage reported. It is also the only location which reports high shake intensity and damage across all days. The reason can be attributed to Location 3 being the historic center of the city with structures made of decorative brickwork which can be vulnerable to earthquakes. Location 3 also had ongoing utility projects, prior to the earthquake, in Power, Water and Sewer, and Roads and Bridges that could have affected the reporting. From the two images above, these neighboring locations seem to be providing reliable reports.

The image above shows the number of reports by individual hour of neighboring locations in the southern part of St. Himark. Despite being the two furthest locations from the earthquake, Location 8 and 9 have the most amount of reports. Similarly, to Location 3, Locations 8, 9 and 10 also have a sudden increase in the amount of reports on a given hour that is not reported on the same hour by any other of the nearby locations. A possible explanation of the inconsistent reporting from location 10 would be attributed to the locations rural lifestyle where damages are less likely to be noticed immediately. However, based on the shakemap, Location 3 was directly affected by the earthquake while Location 8 and 9 was not. Based on the shakemap and the inconsistency of the reporting, it is doubtful whether the reports from Location 8 and 9 are reliable.

The image above shows there is a negative correlation between shake intensity and damage amongst the reports from the neighboring locations in the southern part of St. Himark. Locations 12 and 13 are the closest locations to the source of the earthquake and reported an average shake intensity between 3 and 5. Despite having lower shake intensity, Locations 8, 9, 10 and 11 have high reported damage across all categories and days than Locations 12 and 13. Based off the shakemap and the above image, there exists doubt in whether the reports from Locations 8, 9, 10 and 11 accurately represent the damage caused by the earthquake.

3 – How do conditions change over time? How does uncertainty in change over time? Describe the key changes you see. Limit your response to 500 words and 8 images.

The chart above shows the standard deviation of reports during different intervals of time throughout the event. The grouped times of reports labeled at the bottom are: Pre quake 1, quake 1, pre quake 2, quake 2, post quake 2, quake 3, and post quake 3. Quakes are considered the one hour interval from the first major grouping of reports for each quake, and post quake periods are the reports from that hour mark on until the next quake. During any quake, the reporting is extremely consistent compared to periods of time outside quakes, but on the whole consistency in reports between individuals rose as they experienced more quakes. This suggests that reports given quickly are, while perhaps inflated, more reliable than reports that happen a significant amount of time afterwards.

This picture represents the median and average of how data has changed over time and the pattern of all data. The median and the average shares quitely the same fluctuation. However, there are two critical values showing uncertain data in the chart which are the location and medical. I think it could be an uncertain data in the excel. Also, the missing data on shaking intensity is cleaned by Trifacta, so the median data shows an accurate pattern when we compare with other variables. 

4 –– The data for this challenge can be analyzed either as a static collection or as a dynamic stream of data, as it would occur in a real emergency. Describe how you analyzed the data - as a static collection or a stream. How do you think this choice affected your analysis? Limit your response to 200 words and 3 images.

Since the responders are using the shake intensity for immediate decisions on how to deploy aid, we decided to provide a cumulative data analysis by treating the data as a static collection. The benefits of this approach are that we have more data to verify the trends we discover. Our goal for future work is to be able to provide the same level of insights but by treating the data as a stream of dynamic information.