Lab8: Mapping the Station Fire in ArcGIS

     The Station fire, which occurred from August 25 - October 16, 2009, destroyed over 100,000 acres of land, threatening over 12,000 structures and bringing havoc to neighboring urban regions. Originally started in the Angeles National Forest off the 2 Freeway near La Canada, the fire quickly spread over the mountainous regions affecting nearby communities, such as La Crescenta, La Canada, Glendale, Acton, and areas near Altadena as well. The map above represents a reference map, showing the general region of the wildfire as well as the spread of fire as a function of time. Starting with August 29 at 2:48, the legend demonstrates the spread of wildfire until September 2nd at 9:02. As one could see, as time progressed, the wildfire enlarged, engulfing more of the mountain and getting closer to the interstate highways represented by the white lines. The elevation shown by the DEM, noted in the blue to red progression in the background of the graph, correlates with the wildfire starting in the mountain regions at higher elevations and spreading to lower elevations where the communities were located. In using GIS, one could get a better and easier visualization of the progression of this disastrous fire over time and the effects of the wildfire on different aspects of life.
     The station fire holds particular significance in my life because I live in La Crescenta; I was evacuated twice during this time and was able to see the fire spreading first hand to my backyard. In particular, I chose to utilize GIS to analyze the effects of the wildfire on the threat of schools because my younger brother was attending highschool at Crescenta Valley High School at this time, which is located in La Crescenta and was one of the evacuation sites for residents in the area. As the fire spread, more homes were evacuated to nearby shelters, one of them being schools. Using GIS, I wanted to see the threat that the school evacuation site had as people were pouring into the gym with all their belongings.
     When it comes to fire threat, there could be a wide range of stories one could explore; I chose to see the fire threat as a function of school location as my parents and brother were being evacuated there at that time. I operationally defined fire threat as the distance of the fire in relation to the school, utilizing somewhat of a buffer analysis analyzing the distance at different miles from the fire. As represented below, purple regions reflect closer distances to the fire and thus a higher threat of being destroyed by the flames. As the colors change from purple to green to yellow, the distance from the fire increase witha  negatively correlating decrease in the threat of the fire.

    In particular, I chose to label Crescenta Valley High School for reasons I specified above; Crescenta Valley High School is located in the purple region suggesting a relatively high threat of fire. Knowing this information, I probably would have asked my parents to evacuate a further distance as to find a safer location with relatively lower risk of threat. One sign of relief that is shown in this thematic map is that as time progressed, the fire seemed to spread in a North Eastern direction, away from the high population of schools; in that particular direction, the map shows relatively no school in that region as the majority of that area is part of the National Forest.
     Also shown in the map are major roads or highways that may have been under threat; As I live in the highest street right below the mountain and North of the 210 Freeway, my house was under high risk of fire threat. My street was closed off and rather than having an optional evacuation as people living a couple blocks down from us had, we were forced to evacuate immediately to Crescenta Valley High School or other evacuation locations they had set up as time and the wildfire progressed. This thematic map provides much more information than merely the location of schools, highways, and fires, but one can really analyze and see the cause and effects of such hazards on the daily lives of people living in those particular areas. This thematic and reference map both demonstrate a greater insight as the how the station fire became so large and dangerous. As there was only brush and trees in the National Forest, it only makes sense that the Station Fire got so large in such little amount of time. From looking at this map, one can ask further questions and make suggestions as to prevent fire threats from reaching such close proximities to the neighboring communities; using the fire threat map, one may be able to suggest ways schools with the highest threat of fire can utilize to protect their students as well as the residents in that area from possible fires in the futures and ways to better effectively contain wildfires in this area. Although fires may not be unstoppable, using maps like this can provide mechanisms and motivation to help stop fires like these from getting so dangerous to the communities in the future.


Bibliography

Greninger, Mark. "All Station Fire Perimeters (as of September 2, 07:02) -€“ Complete Set." Los Angeles County Enterprise GIS: All Station Fire Perimeters (as of September 2, 07:02) – Complete Set. N.p., 2 Sept. 2009. Web. 15 June 2012. <http://egis3.lacounty.gov/eGIS/2009/09/02/all-station-fire-perimiters-as-of-september-2-0702-complete-ste/>.


"Mapshare: UCLA's Spatial Data Repository: Los Angeles County." GIS at UCLA: Mapshare DB" UCLA, 1 Apr. 2008. Web. 15 June 2012. <http://gis.ats.ucla.edu/Mapshare>.


"Mapshare: UCLA's Spatial Data Repository: Los Angeles County Highways." GIS at UCLA: Mapshare DB" UCLA, 1 Apr. 2008. Web. 15 June 2012. <http://gis.ats.ucla.edu/Mapshare>.


"Mapshare: UCLA's Spatial Data Repository: U.S. Geographic Names Information System Schools for Los Angeles County." GIS at UCLA: Mapshare DB" UCLA, 1 Apr. 2008. Web. 15 June 2012. <http://gis.ats.ucla.edu/Mapshare>.


William-Ross, Lindsay. "New Evacuation Orders Issued Due to Station Fire." LAist. N.p., 31 Aug. 2009. Web. 15 June 2012. <http://laist.com/2009/08/31/new_evacuation_orders_issued_due_to.php>.

Lab7: Census

    The above maps represent the distribution (ranked by percent) of three particular races across the United States; all data was based on the census data collected in 2000. The first map above (in purple) displays the distribution of percentage of Black Americans throughout the counties of the United States. The lighter purple colors display a smaller percentage of Black Americans while a darker purple shade reflects a higher proportion of Black Americans in that particular area. As shown, there is large, dense population of Black Americans in the Southeastern portion of the United States while some other portions in the Midwest and the North do not show the same dark shade, reflecting a smaller proportion of Black Americans living in that area. There are some darker areas near Wisconsin, but the majority of the Black Americans tended to live in the Southern regions of the United States in 2000.

     The second map reflects the percentage distribution of Asians living in the United States in 2000. In comparison to the first map, there seems to be a greater even distribution among the counties throughout the country in terms of percentage distribution; however, we do see highly populated regions in California as well as places like New York. The percentage of Asians living in an area tends to be greater near the coast as California, New York, some parts near Wisconsin, and other areas all sem to border the water or ocean. This may be due to migration from the motherland or merely just preference among this particular race.

     The third map shows the percentage distribution of some other race alone, representing the percentages of other races based on the 2000 census data of the United States. We can see the distribution of minority races in this map. We must note that in this map, the legend colors signify not a gradient shade from light to dark where light shades signify a lesser percentage of population but a two-colored legend signifying the percentage distribution. In this case, blue would represent a lesser populated percentage area while red signifies a heavily populated region. It is clearly shown that the Southwestern regions are more heavily populated by 'some other race' while the Northern most parts of the United States show the lightest percentage population.

     Mapping the data of 2000 census offers an easy visual representation for the every viewer to see the distribution of different races as well as other types of census data; It is easy to read and simple for many people to understand. GIS can easily map out these types of data and thus pose and address questions based on these maps, such as why there seems to be aggregates of particular races in certain regions of the United States and so forth. GIS also makes it simple for the viewer to compare between maps to see which counties have a higher percentage of one particular race over another. Given these maps created by GIS, one could possibly look deeper into other issues, such as the history of these particular races and/or migration patterns that have brought these races to the areas they are at in 2000. Also, GIS could show through dynamic mapping, changing from year to year when the next census data is collected. We could potentially see changes in the percentage distribution among these races, in terms of where the majority of the people moved to or any other changes possible.