Earthquakes IV: Examining the temporal distribution

Objective: This exercise focuses on creating summary tables and plotting the data as graphs. 

Key Learning: After shocks vs Magnitude correlation. The two graph insets were surprising to me. They clearly show that while the number of aftershocks per day decreases over time, the magnitude does not necessarily weaken.

Background: By summarizing the data in a table, one can derive various summary statistics—including the count, average, minimum, and maximum values—and get exactly the information needed. Information gleaned from data sources such as tables and graphs complement a map because they convey information that would otherwise take more time to summarize and understand.  Using this map as an example, a user can quickly compare features to see which have more or less of a particular attribute.

Summary of Steps to "Get There"
1) Open Northridge3.mxd in ArcGIS
2) Open the attribute table for Earthquakes layer and summarize the DaysAfter column by maximum magnitude.
3) Save the output as Aftershocks.dbf, then add to map
4) Opened new table and under options clicked Create Graph
5) Create a graph setting the Value to Count_DaysAfter and the X field to DaysAfter and then created a graph with the Value as Magnitude and X field still Days after.
6) Rearranged figure to fit both the map and two graphs and exported

Review questions:

1. How can an earthquake scenario map be used to identify population and infrastructure that would be affected by the hypothetical event?
"By simply observing the point features, you can see that there are concentrations of building damage in certain places. A density analysis of the building damage will help to reveal additional patterns of concentrations that are not apparent when looking at the features alone. The Spatial Analyst Density function enables you to measure the number of features in a study area based on some standard unit of area. In this step, you will measure the number of damaged buildings per square kilometer" Earthquake Part II lab, page 4.

2. What GIS function would allow you to create a damage pattern map from a GIS layer of damaged buildings?
 "GIS, digital photogrammetry, and digital positioning data produce 3D earthquake fault maps, [therefore] fault rupture maps created with GIS software show the rupture pattern of the … earthquake[s] and how branching faults come together."Geologic Fault-Finding with GIS http://www.esri.com/news/arcnews/fall08articles/usgs.html  .


3. How can GIS help you visualize a fault plane after an earthquake.
There are several ways to visualize a fault plane.  A very comprehensive paper I found was "Various 3D angle views of the fault help scientists better understand earthquakes” Geologic Fault-Finding with GIS. http://www.esri.com/news/arcnews/fall08articles/usgs.html.

Earthquakes Part III: The Spatial Distribution of Aftershocks

Objective: learn how to import data from an earthquake catalog and then visualize the data in ArcScene™

Background: The Northridge 6.7 main shock produced thousands of aftershocks, smaller earthquakes that result in continued shifts of movement and settling along the fault plane. The spatial distribution of aftershocks often suggests the region and geometry of the fault plane along which the major earthquake occurred. Although not as strong as the original quake, these aftershocks posed a significant threat as they further damaged already weakened or partially destroyed structures, endangering the rescue workers frantically attempting to locate those trapped inside.

Summary of how to "Get There"

1) Open Northridge2.mxd

2) Import the NorthridgeAfter.csv text file.

3) Right-click the added file and Display x,y.
4) Ensure that longitude = x and lattitude = y
5) Export temporary file as a shapefile and add to map.
6) Open the attribute table for aftershock data and select the 6.7 magnitude feature and export this  as a new shapefile (.shp).
7) Query all aftershocks with a magnitude greater than 3.
8) Per the Lab directions, the features symbology was set using 3 class breaks (4,5, and 6)
8) Set the size and color per lab directions.  The final map output is as seen above.

Earthquakes Part II - Analyze the pattern of building damage

Objective: Determine the pattern of building damage using building tagging data collected in the aftermath of the Northridge Earthquake. Then compare the damage pattern to local geologic conditions and scientific measurements of ground shaking.

Back Ground: Immediately after the Northridge earthquake, Southern Californians raced to their televisions to find out where the earthquake occurred and how strong it was. From this information, most people assumed that there must be heavy damage in the Northridge area. But magnitude and epicentral location do not say much about the kinds of damage that might be found some distance from the epicenter. Damage patterns away from the epicentral region depend on a variety of factors including the location of the ruptured fault plane with respect to the ground surface, distance from the earthquake, local rock and soil conditions, and building construction

Lab Details
1. Open Northridge1.mxd
2. Turned on Spatial Analyst
3. Turned on Building Status then
4. Opened Building properties dialog box and Change building status tag symbology to:

     1. Red = Unsafe = Red color
     2. Yel = Limited Entry = Yellow color
     3. Grn = Safe = Green color
     4. Unk = Insufficient Data = Black

5) Select by Attribute to select Red and Yel from Building Status Tag
6) Chose two different ways to select the Tags.

     1. First was manual by opening the properties and manually selecting them. Then saved that as Manual_output.mxd.
     2. Then in a side-by-side operation I opened the original file and wrote a query in the properties dialog box that would show only red and yellow tagged buildings. (‘Tag’ = “red” OR ‘Tag’ = “yel”). This was more effective time wise and it provided a validation to the script.

7. I switched to the map view, added all the basic map elements
8. Saved this as a map.

EarthQuakes Part I: Analyze hazards associated with the New Madrid fault zone

Objective: Examine and analyze the hazards on a population if an earthquake, like the New Madrid quake of 1811-1812, were to happen today.
Back ground: During the winter of 1811 – 1812, four great earthquakes rocked the central Mississippi valley, near New Madrid, Missouri. In recent years, concern has been growing over the possibility of a similar event hitting the central United States in the future.  An examination of the data quickly reveals that highest magnitude zones (IX & X) are near Memphis Tennessee so it follows that it would sustain the most damage of any city.  The summary tool allowed me to see that there were 60,088,857 total people affected by the VI or more magnitude earthquake.

Detailed steps

1. Open the NewMadrid.mxd map document. 
2. Turn on Quakes 5 layer, showing earthquakes greater than magnitude 5.0 since 1800.
3. Turn on Urban Areas layer to view major urban areas.

Next we were asked to calculate population Density.

1. Turn on Counties layer, open attribute table and add a new field named Pop_Density, (Double) precision
2. Use the field calculator function, divide the 2001 population by the area of the county. [POP2001]/[Shape_Area].  This provides and answer in  persons per sq. meter. 
3. Use the Intersect tool in the ArcToolbox to intersect the data from the counties file with the NewMadrid MMI information and save it as County_MMI. 
4. In the new CountyMMI attribute table, add a long integer field named POP2001ADJ,
5. Calculate field using the expression [Pop_Density]*[Shape_Area] 
6. Right-click MMI field and select the summarize function. This will summarized MMI field by Pop2001ADJ sum, select "yes" to add new table to map.
   using the
7. keeping the attribute table open, I created the a bar graph showing the total population for each MMI.

Identify the most vulnerable interstates

1. Add a new field to the New Madrid attribute table that converts the roman numeral MMI to an integer, then select those MMI values greater than or equal to the intensity in which vehicle operation would be disturbed. (VIII+)
2. Turn on Interstates layer and clip to MMI features >= 8.
3. Turn off the Interstates layer
4. Turn on railroads layer and performed same clip process but  this time to the Rail road lines that are within MMI >=10
5. Make a map and upload to dropbox.
6. Turn Dams layer on and select MMI zones >=8
7. Select dams within that area to create a new layer file.
8. Save the map!

The Manatee Project

Wow this was such a challenging project. This project encompassed nearly everything we learned this semester. This required research. The primary tool was ArcGIS. Support tools included Erdas Imagine MS Excel, Powerpoint and Word.
A PowerPoint presentation accompanied by a written slide‐by‐slide summary is required as the final deliverables

Week 11 - Labels and Annotations

I learned a good bit about label and such but it took soooo much longer than the suggested times. 

In this exercise, We wrote VBScript code to customize the text string for labels. Then modified existing labeling properties to create dynamic label callouts. Finally, used a variety of techniques to manually add descriptive text to the map.

Along the way I discovered some of the differences between dynamic labels and manually-created text. I also learned how to troubleshoot my application to distinguish between the two once I've added them to a map.

I like this one too.  The red line is the hiking trail across Shivano

Week 10 - Using Raw Data

In this case we were tasked to work with raw data and tables to analyze property for a fictional developper.

It involved bringing in data and joining to our attribute table as a way of analysizing outside data within GIS. Then the four largest landowners in Gulf County, Florida needed to be located and symbolized. This was accomplished with data from the Florida Department of Revenue.

Here is where it got interesting to me.  In order to join tables with a shapefile - there needed to be a common field. The field names did need to be identical but they do need to hold the same data. After that it was quite straight forward.  It is a lab like this that reminds me how much I have learned this semester.