Lab 7: LA Station Fire

LA Station Fire Reference Map:


High Risk Schools Threatened by LA Station Fire:




LA Station Fire

During the span of six weeks (8/16/2009 to 10/16/2009) the Los Angeles Station Fire burned through 250 square miles, 90 homes, and claimed the lives of two firefighters (Pringle). Although fires are not uncommon to Los Angeles, the station fire is significant because it was one of the largest recorded since 1933 (inciweb). The fire was also the largest recorded in the Angeles National Forest since its establishment in 1892 (inciweb). In addition, over 3500 personnel from around the state were activated to extinguish the fire (Pringle).

As seen by the reference map, the fire was centered in the mountains. Because the main area of the fire occurred in a steep sloped area, firefighters could not readily nor safely suppress the fire in key locations early on. In the fire’s premature stages, commanders erred on the side of safety, opting to keep firefighters away from these prone areas since fire is much more dangerous in high gradient areas (fire travels extremely fast uphill) (Pringle). However, the strategy allowed the fire to spread which drew public criticism.

The fire came very close to reaching nearby cities—most notably Altadena, Flintride, Tujunga, Sunland, and La Crescenta (William-Ross). In order to gauge how many people were affected by the fire, I looked at how many schools were nearby the fire perimeter. Schools are good indicators of populated areas because they would most likely be established close to neighborhoods (Mapshare, seamless). Many schools, including all thirty five in the Glendale Unified and La Canada School Districts, postponed school as a precaution (City News). The schools that were shut down closest to the fire are listed above.

Many of the Glendale Unified schools that were shut down were more than 5 miles away from the closest fire perimeter (William-Ross). Rather, the schools probably chose to cancel school because students and staff may have been affected by the poor air quality. Wind can transport ash and other small dust particles very far distances that were unaffected by the fire (Knoll). Although the exact quantity of particles from the fire cannot be measured, an index exists to measure air quality for the public health. Any number exceeding one hundred is said to be hazardous. In the area above La Canada, the measured index was a 398 (Knoll).

The station fire destroyed large amounts of chaparral, a native Californian shrub. When large amounts of chaparral are burned on a hillside, it increases the likelihood of flooding, mudslides, and falling debris (Daily News). Flooding occurs because, when burned, the chaparral releases natural oils that percolate into the ground and accumulate beneath the topsoil. When rain falls, the permeability of the ground is very low because the oil retards the water from soaking into the Earth. Thus, the water continues to flow down the slope increasing the risk of communities being flooded. Chaparral is also key in providing structural support to hillsides and rock formations. Therefore, when chaparral is burned hillsides and boulders can move around more freely resulting in more falling rocks and landslides (Daily News).

Bibliography:

1. City News Service. "Schools remain closed because of Station fire". L.A. Now. Los Angeles Times, 1 Sept. 2009. Web. 23 Nov. 2009. http://latimesblogs.latimes.com/lanow/2009/09/schools-remain-closed-because-of-station-fire.html.


2. "InciWeb the Incident Information System: Station Fire." inciweb.org. Web. 23 Nov. 2009. http://inciweb.org/incident/1856/.


3. Knoll, Corina. “Air Quality at Hazardous Levels in Foothill Cities.” Los Angeles Times Blog. 31 August 2009. Los Angeles Times. 24 November 2009 http://latimesblogs.latimes.com/lanow/2009/08/air-quality-1.html


4. Mapshare. Web. 23 Nov. 2009. http://gis.ats.ucla.edu//Mapshare/Default.cfm.


5. The National Map Seamless Server. Web. 23 Nov. 2009. http://gis.lacounty.gov.


6. Pringle, Paul. "U.S. Forest Service blames steep terrain for Station fire's spread." LA Times 14 Nov 2009: n. pag. Web. 27 Nov 2009. .


7. "Rain after the Station Fire spells disaster for foothill residents." Daily News. 30 Aug 2009. Los Angeles News Group, Web. 12 Oct 2009. http://www.dailynews.com/opinions/ci_13546024


8. William-Ross, Lindsay. "Station Fire Update: Evacuations, School Closures & Other Info." Laist. 30 Aug 2009. Zach Behrens, Web. 27 Nov 2009. .

Lab 6: South Lake Tahoe

Slope Image:


Shaded Relief Image:


Aspect Image:


3D Image:


Description:

For Lab 6, I examined the area around South Lake Tahoe along the California-Nevada border. I chose this area because I regularly snowboard on the surrounding mountains every winter. Therefore, I knew the elevation gradient in the area would be high and the corresponding DEM would probably result in interesting maps. The mountains(grouped in a semicircle on the upper right of the aspect and slope images) surround the bottom portion of Lake Tahoe. The 3D image also makes it apparent that mountain peaks are generally taller when they are situated closer to the lake. Below is listed extent and geographic coordinate system (GCS) information applicable to the above images.

Extent Data Information(in degrees):
Top: 38.9913888883
Left: -120.541111111
Right: -119.8175
Bottom: 38.5019444438

Geographic Coordinate System Information:
Spatial Reference: GCS_North_American_1983
Angular Unit: Degree (0.017453292519943295)
Datum: D_North_American_1983

Lab 5: GIS Projections

Figure 1:


Figure 2:


Figure 3:


Lab 5 demonstrated how different map projections may cause variations in a map's characteristics. Although projections cause some discrepancies, they are the most efficient way of representing the real three dimensional world on a two dimensional surface. Even the most accurate representation (a globe) is imperfect because it models the Earth as a perfect sphere when it is a crude ellipsoid. Nevertheless, projections are invaluable because they help people objectify their spatial surroundings.

Different map projections have different strengths and thus are used for a variety of purposes. Conformal map projections, for example, preserve angles and relative shapes. Likewise, equal area projections preserve relative areas on a map and equidistant projections preserve distances.Since each projection type preserves only a few aspects (i.e. distance, angles, and area), the type of projection should be chosen only after the purpose of the map is defined. Further, the view may also change between map projections. Notice the view difference between the "Equidistant Conic" and the "Plate Carree" images (Figure 2). Although they are both equidistant projections, the perspective they take are obviously different. The equidistant conic takes more of a bird's eye approach from the pole whereas the plate carree excludes the poles.

Although three map projection types exist (conformal, equidistant, and equal area), two maps of the same type are often appear very different. For example, the "Mercator" and "Gall Stereographic" projections are both conformal maps which means they preserve local angles (Figure 3). However, they are mainly different in that the Mercator emphasizes the upper and lower thirty degrees, evidenced by the disproportionate sizes of Greenland and Antarctica. In contrast, the Gall Stereographic projection gives each 30 degrees of longitude equal space on the map. Even in the Gall Stereographic projection, however, Greenland and Antarctica are still disproportionate when compared to an equal area projection.

The disparity in distances between Washington D.C. and Kabul, Afghanistan were interesting to note. The measured distances between the two cities ranged from 6,973 miles to 10,082 miles depending on the map projection used. At first glance, it was surprising that the Plate Carree and Equidistant Conic projections (two equidistant projections) varied so widely in distance: 10,079 miles to 6,972 miles. On further inspection, I realized that simply drawing a straight line between the two points created two entirely different routes that could not be compared due to their difference in view. For example, the line connecting Washington D.C. and Kabul in the Equidistant Conic projection passed through the Arctic Circle whereas as in the Plate Carree, the line crossed the Atlantic Ocean. An important lesson from this lab is that maps should not be taken at 'face value'. A map's specifications (i.e. the type of projection), similar to any set of data, should be considered when being viewed.

Lab 4: GIS Data View

Lab 4: GIS Data Models

Before this lab, I only knew two things about GIS: it layered maps like a cake and it could be applied to many different fields. I was very excited to do this lab for hands on experience on a GIS program— the reason why I took this class. In particular, I was especially interested in learning exactly how GIS works to give scientists and policy makers a better understanding about climate change. For this lab, we primarily used ArcMap, the industry standard for GIS.

That said, using ArcMap GIS was my first time using a ‘technical’ program, but it was still relatively easy. Even after using ArcMap for a few minutes, I could tell that the developers tried making the program very user friendly. Although the GUI was not the most ‘pretty’, the functions were logical and easy to understand. However, the sheer volume of functions to memorize is likely responsible for the steep learning curve mentioned by Professor Shin. The only recurrent problem I had was with resizing a map (i.e. zooming in on a specific part of the map) to fit in a specific data layer.

The step by step instructions on the ArcMap tutorial were extremely easy to follow. A key advantage of ArcMap is that it is extremely dynamic. The software allows users to manipulate and identify many key relationships not noticeable with the bare eye. For example, new features can be added to maps quickly and neatly. However, the lab did not give directions in creating the data sets (i.e. the noise contour and creating the county boundaries). Although I cannot say for sure, I would imagine that this process would be very time consuming—a definite drawback of GIS.

A potential pitfall of ArcMap is that it is only as good as the data it is based on. For example, a small discrepancy in the inputted data may cause a large change in the ArcMap output. Although this is true for any computer program, the data cannot be easily checked since the output of ArcMap is normally a visual. In contrast, a graph or chart has numbers that can be readily checked against recorded data. In addition, I would imagine that the preson

I’m looking forward to learning more features and applications of ArcMap and GIS.