LA County Fire (2009) Map Report

           The Lab work for the final week is to analyze some aspects of the August – September 2009 Station Fire in Los Angeles County. More specifically my study centralizes on the health impacts on the LAUSD school children and hospital patients in LA county area.

          Just to imagine to severity and the centrality of the fire you can refer to any of the figures. Those areas that share boundaries with wild land will be at increased risk for fire as the water consumption in those areas grows and the drought seasons continue to be more and more frequent. 

          To give some information about the severity and the magnitude of the fire, I’ll just mention some of the damages it caused it LA county. As was mentioned in LA Times (August 31, 2009), the fire doubled in size overnight to consume 85,000 acres and more structures. 18 houses lost to fire earlier in the Tujunga Canyon area; however officials expected this number to rise. Many neighborhoods were mandatory evacuated overnight as the fire continued to furiously spread in 3 directions. But the fire did not burn the top of the Mt. Wilson, where many crucial communication centers are located. “We are making progress. But it is very slow and very dangerous," incident commander Mike Dietrich of the U.S. Forest Service said at a news conference this morning. "We have to wait for the fire to come to us" (LA Times, August 31, 2009). “This fire is probably a week away from being fully contained,” Mr. Quintelier said. “It’s just a long marathon sort of job that lies ahead.” By the time the fire was evacuated more than 161,000 acres was burnt and 2 firefighters were lost to fire. 2,800 fire personnel from around the state were brought to battle the Station fire, also 12 helicopters and 8 air tankers were in action too.

           There are 2 theme maps in my report; one about schools and the other one about hospitals. Just to demonstrate couple of aspects of impact on the LA County population, I did a 1 mile buffer analysis on LA County schools and a 5 mile buffer analysis on LA County hospitals. Thanks God no schools or hospitals were burnt, but many of them were just at the edge of the fire and were under a real risk. Because the fire was mostly in an uphill area, the nearby schools and hospitals were covered under debris. However the biggest danger was the debris in the air, which might have had some toxic components in it.

          This simple analysis demonstrates how the zone analysis of residential areas is not thought trough. Planning should be done taking into account the fact that there are serious limitations to the effectiveness of policy - making. Financial means are restricted, if not limited. One other obstacle is that “there is very little undeveloped land to which zoning restrictions [can] be applied.” (Gardner, et al. 170)

1 mile Buffer Analysis on schools of LA County

5 mile Buffer Analysis on hospitals of LA County

          I also did aspect and slop maps of LA County which also show the area that the fire spread. It is done in different colors showing the area that was consumed by fire each day. It is easily visible in the maps that the fire area almost doubled every day. The maps show that the fire mostly spread uphill into the more forested area.

An Aspect Map with LA County Station Fire Perimeters

A Slop Map with LA County Station Fire Perimeters

A Hillshade Map with LA County Station Fire Perimeters

           To sum up my report I’ll mention more alarming information from the surveys. Communities that had been impacted by a fire were “more likely to assign lower probability of occurrence” than communities that had not been impacted. Basically, the findings “suggest a risk-dampening effect” where homeowners convince themselves that it will be ‘highly improbable’ for them to be hit by another fire again (Cortner, et al. 59). However, this serious miscalculation does not take into consideration the “reoccurring nature of the fires, especially in southern California (Cortner, et al. 59). This mentality has to change completely for the population to be better protected from fires and other natural disasters.

References

Bruce Quintelier (Fire information officer for the United States Forest Service). http://www.nytimes.com/2009/08/31/us/31fires.html?scp=1&sq=la%20county%20fire&st=cse


Cortner, Hanna J., Philip D. Gardner, and Jonathan G. Taylor. “Fire Hazards at the Urban-Wildland Interface: What the Public Expects .” Environmental Management . 12.1 57-62


Gardner, Philip D., Hanna J. Cortner, and Keith Widaman. “The Risk Perceptions and Policy Response toward Wildland Fire Hazards by Urban Home - Owners.” Landscape and Urban Planning. 14. (1987): 163-172


Mike Dietrich (U.S. Forest Service incident commander). http://latimesblogs.latimes.com/lanow/2009/08/la-county-fire-doubles-in-size-more-homes-list-mt-wilson-threatened.html

Paul Pringle. http://latimesblogs.latimes.com/lanow/2009/08/la-county-fire-doubles-in-size-more-homes-list-mt-wilson-threatened.html

Lab - Census 2000, Population maps

 

 

This map shows the distribution of Asian population across United States. It can be clearly seen  that almost 90% of United States has less than 1% Asian population. Most of the Asian people are concentrated in big industrial cities, so I had to be very careful while creating the color boundaries. There are 6 color classes that carefully separate 0% - 20% from 20% - 46% with different colors to emphasis on population above 9%.

This map shows the distribution of Black population across US.  This map clearly shows that almost 30% of United States has is heavily populated with African - American people. Most of them are concentrated in South - East part of U. S., so I had to be really careful while creating the color boundaries. There are 6 classes that carefully separate 0% - 30% from 30% - 90% with continuous gradient colors to emphasis on population above 30%.

This map here shows the distribution of Native American population across United States. This map clearly shows that the South part of mid - West of United States is heavily populated with Native American people. There 6 color classes that carefully separate 0% - 40% from 40% - 99%. There is also a big concentration of them in the state of Alaska, but it is not showing clearly on this map (the map is supposed to show the continental U. S.).

Lab 6 - DEM

The images here demonstrate the Mount Wilson in southern CA. I have chosen it because the whole area is covered by mountains and so it is a perfect territory to show all the DEM tools of ArcGIS. All the forms of demonstration are important and informative, but I think that the 3D model demonstration is the most informative because it really gives you a feeling of the topography of the area.

EXTENT INFO:

Spatial Reference:         GCS_North_American_1983

Datum:                         D_North_American_1983

TOP -                            34.33dd

BOTTOM -                  34.22dd

LEFT -                         -118.04dd

RIGHT -                      -117.83dd

Lab 5 - Projections

The first equal area projection that I have presented is the world-cylindrical projection. This is a map projection in which the surface of the globe is depicted as if projected onto a cylinder. A cylindrical projection produces a rectangular map with the equator in the middle and the poles at the top and the bottom. Distortion of the shape and scale is minimal near the equator and is maximal near the poles. The distance between Washington D. C. and Kabul, Afghanistan on this projection is 10200 miles.

         My second equal area projection is Bonnie projection. It is named after Rigobert Bonnie after he used it extensively in his 1752 maritime atlas. It is a pseudo-conic projection; the parallels are plotted as concentric, equally spaced arcs. This projection was very popular in the first half of the 20^th century, but it lost its popularity in the recent years, because the distortion around the edges limits its use in global maps. The distance between Washington D. C. and Kabul, Afghanistan on this projection is 6590 miles.

          My first equidistant projection is the equidistant-cylindrical projection. This is a fairly simple projection that maps meridians to vertical straight lines and circles of latitude to straight lines that are spread evenly. Equidistant-cylindrical projection has very little use in navigation or cadastral mapping. It is mainly used in thematic mapping and has become standard for computer applications because of its very simple relationship between the positions of the image pixels on the map and its corresponding location on Earth. The distance between Washington D. C. and Kabul, Afghanistan on this projection is 5066 miles.
          The second equidistant projection is the equidistant-conic projection. This projection is very simple to construct and are widely used in regional and national maps of temperate zones. However this projection is not so appropriate for world maps. The equidistant-conic projection has constant parallel spacement, so the scale is the same along all the meridians. The distance between Washington D. C. and Kabul, Afghanistan on this projection is 6950 miles.

          The first conformal projection presented here is the World-Mercator projection. On this map all the lines on constant bearing (rhumb lines) that make constant angles with meridians are represented by straight segments. This projection is widely used for navigational purposes at sea. Its 2 properties – conformality and straight rhumb lines make this projection uniquely suited to marine navigation. The distance between Washington D. C. and Kabul, Afghanistan on this projection is 10200 miles.
          The second conformal projection is the World-Gall-Stereographic projection. This projection is an improvement upon the Mercator projection. The northern and southern parts of the map are stretched horizontally; while the whole map is stretched vertically. World-Gall-Stereographic projection is mostly suitable to show the temperate countries. The distance between Washington D. C. and Kabul, Afghanistan on this projection is 7268 miles.

          As we can see from all these types of projections the shape and scale of the countries, the distance between two locations on Earth is widely dependent on the projection that has been used. This is shown by our lab work – the distance between Washington D. C. and Kabul, Afghanistan ranges between 5066 to 10200 miles on different projections, while the true distance is 7000 miles.