Final Lab: Station Fire (Wk. 9)

Today's lab, Lab #8, is the capstone lab in this course. After learning the basics of maps and GIS for the past quarter, this lab test our knowledge and demonstrate the culmination of our GIS prowess. This week's goal, first and foremost, is to analyze the Summer 2009 Station Fire in Los Angeles County. In addition, we are to expand our knowledge about map-making in ArcGIS, and Southern California geography and wildfires. In fulfilling said objectives, we created both reference and thematic maps.

The Los Angeles Station Fire started on August 26th 2009 and burned for a month. It spread very quickly and was an immense challenge for firefighters to contain. Several days after the fire started, officials decided that all evidence pointed to the cause of the fire being arson. The arsonist has not been found to this day.

The first map I created was a reference map. One of the reasons the fire spread so quickly and was so difficult to fight was the terrain in area. This map displays Los Angeles county as well as the interstates and bodies of water within the county lines. This helps the viewer visually see what major traffic arteries the fire came close to. More importantly, however, the map shows the Station Fire perimeter over the course of a few days. The fire spread very rapidly and this is evident in Figure 1. A DEM was also layered onto the county map to show the kinds of terrain the fire encompassed and what firefighters had to deal with while trying to extinguish it. The fire was mostly in a higher-elevation, mountainous area, indicated by the lighter colors. The fire spread primarily North and West along the hills.

Figure 1 - Station Fire Reference Map

 The next two maps are thematic and present even more information on the fire. In Figure 2, I wanted to focus on a topic that hits close to home for many people. My first thematic map shows the distribution of schools around the changing Station Fire perimeter. The youth are the most cherished group in our society and we worry about them. Had the fire burned any schools or school children it wold have been a tragedy. The data on schools was found on the UCLA GIS database. To create this map, I put the Schools layer on top of all the other layers so that I could see any schools that were within the fire perimeter. Thankfully, through my map, we can conclude that although the fire came dangerously close to some schools, none seem to have been engulfed by it. There were likely several evacuations but few if any causalities. I would like to commend our firefighters in minimizing the danger to our schools and students. 

Figure 2 - Station Fire Thematic Map: Schools

My final map shows the movement of the fire but this time it is super-imposed on a Fuel Rank layer. Fuel Rank, as noted on the map, is a ranking system of fire potential based on the type of vegetation in the area and the topography. The ranking system ranges from 1 to 4. For my map, I translated this numeric system to a more descriptive ordinal arrangement. A rank of 1 corresponds to "Low Fuel Rank" and a rank of 4 corresponds to "Very High Fuel Rank." Based on my map, it seems that the Station Fire existed mostly in Very High Fuel Rank areas.

Figure 3 - Station Fire Thematic Map: Fuel Rank

Overall, Lab 8 achieved its objectives. Although I attended UCLA in 2009, I was not in Los Angeles during the summer, so I knew very little about the Station Fire. It was a huge deal and I am glad I am now much more educated on the topic. Additionally, I improved my skills working with Legends and various layers in ArcGIS, and am now very comfortable handling DEMs. I also demonstrated my understanding of reference and thematic maps and cartography. Throughout the course of this class, I have really begun to see the power of GIS. It is no wonder that companies pay millions of dollars for this type of data. I am glad I took this course as I believe I have added a valuable tool to my skillset.







Bibliography:


"Mapshare: UCLA's Spatial Data Repository." GIS at UCLA: Mapshare DB. University of California, 2006, Web. 01 Dec. 2012. <http://gis.ats.ucla.edu//Mapshare/Default.cfm>.


Winton, Richard. "L.A. NOW." Substance Found near Station Fire Ignition Point Is Key Evidence in Arson Probe [Updated]. Los Angeles Times, 04 Sept. 2009. Web. 01 Dec. 2012. <http://latimesblogs.latimes.com/lanow/2009/09/station-fire-ignition-arson-investigation.html>.



“Station Fire News Release.” InciWeb: Incident Information System. 31 August 2009.Web. 01 Dec. 2012. <http://inciweb.org/incident/article/9640/>



“All Station Fire Perimeters.” Los Angeles County Enterprise GIS. 28 September 2010. Web. 01 Dec. 2012.<http://egis3.lacounty.gov/egis>



“Fuel Rank.” California Department of Forestry and Fire Protection: FRAP. 2007. Web. 01 Dec. 2012.<http://frap.cdf.ca.gov/data/frapgisdata/download.asp?rec=frnk>

Lab 7 (Wk. 8)

Lab 7 - Working with Census Data

In this week's lab the objectives were to learn to find census data, use census data with ArcMaps, and learn to use GIS to create the three maps required.

The first map I have created below shows the Asian population in the United States by county in the year 2000. It helps use to see what the distribution of Asians is in our country. Some counties are as little as 0.0085% Asian, whereas other counties have as many as 46% of their residents from Asian descent. That is nearly half. By inspecting the map, we can see that more Asian people live on the coasts than southern or middle America. This makes sense as the West close is area of the United States closest to Asia and people came to find work. The New England region also so an influx of Asians immigrating to the United States through Ellis Island. I would be interested to see the same data for the latest census, to see if Asian Americans have spread over more of the country. 

Map 1: Asian Population Percentage. Data from 2000 Census.

The second map, provided below, is similar to the first map, except that I focused on African-Americans. Some counties in the United States are almost entirely African American, at roughly 87%. The county with the smallest percentage of African Americans has 0.01%. Unlike the Asian population, which is concentrated on the coasts due to logical immigration routes, the counties with the greatest black concentration are in the South. This can be attributed to history. Many Blacks were brought to this country long ago as slaves to work on plantation. The majority of these plantations were located in the southern United States.

Map 2: African American population  percentage by county. Data from 2000 Census.

Lastly, we come to the third map. The data in this map was provided by people who marked "Some Other Race" on the 2000 census. The distribution of these people is shown in Map 3. According to the census website, the vast majority of people who mark "some other race" are of Hispanic or Latino descent. The county with the highest percentage of Others reported about 39%. This translates to about 2 out of every 5 people. We can see that Others are heavily concentrated in the Southwest part of the US and Florida. This makes sense if most of the Others are of Latino. The Southwest United States like Arizona and California are very close to Mexico and South America and Florida is close to Cuba. People who emigrate from sadi countries generally stay in the areas of the US close to their home countries.

Map 2: People who marked "some other race." Percentage by county. Data from 2000 Census.

Overall, I had fun doing this assignment.  It is interesting to see how historical events which occurred well over 100 years ago greatly affect population distributions to this day. Once certain ethnicity are establish in an area they seem to stay there. Though many people may have traveled far to come to our great country, they seemed to not want to move anywhere once they arrived. It is also rather fascinating to see the huge range of counties with such little amounts of Blacks to such high amounts. 

The power of ArcMaps and GIS impressed me in this week's lab. The amount of data involved in these maps is not at all trivial, and ArcMaps handled it all quite gracefully. Even image rendering is done without any hiccups in the program. At this point, I have become very comfortable creating maps and changing projections and properties  as well as adding the basics like neatlines and legends. We also used the North American Lambert Conformal Conic projection this week, which made the information presented much clearer. 

Sources: www.census.gov/prod/2001pubs/c2kbr01-1.pdf
http://2010.census.gov/news/releases/operations/cb11-cn125.html

Lab 6 - Digital Elevation Models

Lab 6 (Wk. 7)

In this lab session, the goal was to become familiar with raster data and how to use it. The raster data we chose to focus on was a Digital Elevation Model (DEM). We made four maps using this data: an aspect map, a slope map, a shaded relief map, and a 3D map.
Elevation models are a great tool that allow people to present data in a realistic manner. It is an excellent way for people to be able to understand how elevation is changing in an area. It is much easier to use than a topographic map, for example. It is also more aesthetically appealing. The 3D map is very cool and interesting to play with. The virtual 3D effect is done well enough to not just be a visual gimmick, but is actually accurate and useful. When used in conjunction with the other maps I have posted here, it becomes very easy for the user to visualize what the mapped area actually looks like.  However, one must exercise caution because it can be very disorienting. It is very easy to lose your bearings while looking at the 3D map. The way I have presented the 3D map below, it is as if the viewer is looking towards the south from the north.

Lab 5 - Map Projections

Week 6 - Lab 5: Map Projections

As the title above states, this week's lab was all about different map projections. We learned how to create different map projections in ArcMap. Unlike last week, where we were given very explicit step by step instructions, this week we were more or less left to stumble our way through the software. Because it has been two weeks since our last lab, I had forgotten some of the things we had learned in ArcMap and had to spend some time re-learning general layout, controls, and functions.

The Earth, as we all know, is 3-D and spherical. Thus, it is impossible to create a two-dimensional representation of the Earth without some sort of distortion. Different projections distort different aspects of the map, and each projection is best for mapping certain things. Thus, depending on the situation, the "best" projection is usually a different one. It is for exactly this reason that ArcMap supports over 60 map projections.

There are three main categories or types of map projections: conformal, equal area, and equidistant. Conformal projections preserve angles. Equidistant projections maintain equal distances. Equal area projections maintain correct relative areas.

I will focus first on conformal projections. Conformal projections are characterized by the right angles at every intersection of a parallel and meridian. In order to preserve angles on the map, area and or distance are altered. For example, in the Mercator projection below, we see that Greenland appears much larger than it actually is. The distortion is very large near the poles. In the stereographic map neither distance nor area is preserved  Africa appears very small.  Conformal maps can be used in egocentric or propaganda maps to show certain areas as big and powerful or small and weak. They are also excellent for use in navigation.

Next we come to Equal Area projections. The two I have chosen to highlight below are the Cylindrical and Sinusoidal equal area projections.  In order to preserve area, distance and angles are compromised. These projections are useful when the size of a country or continent is important. In the cylindrical equal area projection, the area along the equator is not distorted, but other areas appear compressed.  In the sinusoidal projection, distortion is minimal along the prime meridian and equator.

Lastly, we come to the equidistant projections. In both the cylindrical and conic equidistant projections shown, distances from some relative point or line  on the map remain accurate in these projections. These maps can be confusing if the user is not clear on where the reference location is. These maps can easily be used incorrectly. The equidistant cylindrical projection preserves distances along the meridians, but no where else. The equidistant conic is convenient when mapping small countries, or for countries that extend mostly east-west, such as the former Soviet Union.

Lab 4 - Proposed Airport Expansion

This week's lab is a two-week lab, as we have the midterm exam next lab session. Finally, in week four, we have really arrived at what is the real bulk of this Geography 7 class: ArcGIS. Specifically, we used ArcMaps to familiarize ourselves to the ArcGIS environment. In object of this lab session was to create a poster with numerous maps displaying information on a proposed airport expansion.

As expected, ArcMaps looks fairly complex and for a first time user, that means a big learning curve. Luckily, I am fairly computer savvy so I was able to pick things up quickly as I section wore on. Having worked with other powerful software such as SolidWorks and Photoshop, I knew what to expect and was not intimidated if something did not work immediately. However, I did run into a couple issues, but the TA was able to help me. For those who are not as familiar with computers and the Windows operating system, I think this lab would be very challenging. I would by no means call ArcMaps intuitive or easy to use. This is by far the greatest pitfall of GIS.

The map editor is another example of where GIS could cause misinformation. As I did in the computing lab, anyone could add roads and other information to the maps that do not actually exist. The general public needs to be careful when considering any user created maps.
The other students and I were all given a tutorial to follow that walked us through the lab. It was very straightforward and easy to follow, which helped make the experience much smoother. It was a great resource and really helped me learn, even if I was just reading through a tutorial.

Power is the strength of GIS. In a simple example, the lab demonstrated how relevant and useful GIS can be. Expanding an airport will cause more noise and residential neighbors will always complain about such things. The use of GIS in this situation could help designers expand the airport in such a way as to minimize the population density inside of the noise contour. And there are so many other areas in which it can be used. For example, the Professor uses it for studying populations of flora and fauna. The possibilities are endless with GIS.

Product of Lab 4

Lab 3 - Google Map

This week we made custom maps using Google Maps. I chose to focus on my month of vacation this past September. While this map is relatively small scale, many user-created maps are vastly complex and can become very disorganized and hard to read. In my opinion, this is one of the biggest pitfalls of neogeography. I believe that is it critical for any map to be easy to follow in order for the creator to be able to convey the information the map was intended to display. Another problem with neogeography is that is grossly subjective. Because all of the content is user-created, there is no way to ensure accuracy and  objectiveness. This is a problem because people may come to believe non-truths after seeing these maps and spread misinformation.
But let us turn to the positive aspects of neogeography. It allows users to share spatial information with each other. For example, people love to check in to places on Facebook and Yelp. These check-ins help people to remember where they have been as well as show their friends. One of my favorite parts of negeography is the geotagging of photos. It allows me to looks at restaurants before I go to see if I would like them, or use Street View to see where I'm headed.
Overall, I think neogeography is a great thing, as long as viewers remind themselves to always take  custom-made maps with a grain of salt.

Below is my map.
Link to Map



View September 2012 Travels in a larger map

Lab 2 - Beverly Hills Topgraphic Map

Lab 2


1. Beverly Hills
2.Adjacent are Topanga to the West,Venice to the South, the Pacific Ocean to the SW, Canoga Park to the NW, and Burbank to the NE.
3. 1966
4. National Geodetic Vertical Datum of 1929
5. Scale - 1:24,000
6
    a. 5cm * 1m/100cm *24,000 = 1200m
    b. 5 * 24,000 in =  120,000 in... * 1ft/12in * 1mile/5280ft = 1.893 miles
    c. 1mile *5280ft/1mile * 12in/ft * 1/24000 = 2.64in
    d. 3km * 100000cm/1km * 1/24000 = 12.5cm
7. 20 feet

8. 

   Public Affairs -  Lat: 34 degrees 4' 30" N     Long:118 degrees 26' 15" W     or       34.07, -118.439

   Pier - Lat: 34 degrees 0' 30" N      Long:118 degrees 30' W              or        34.008,  -118.5

   Reservoir -  Lat: 34 degrees 7' N   Long: 118 degrees 24' 50" W     or       34.117, -118.41

9. Center Point of:
       Greytsone Mansion - 560 ft or 170.7 m
       Woodlawn Cemetery -  140 ft. or 42.7 m
       Crestwood Hills Park - 700 ft or 213.4 m
10. UTM Zone 11
11. (37)63 Northing, 361.5 Easting
12. 1 km^2
13.

14. 14 degrees declination
15. Southwards flow
16.UCLA