The Station Fire in San Gabriel Mountains in late 2009 was the largest wildfire in the area in on record.[1]  The fire spread over an area of 251 square miles just north of the San Fernando Valley communities of La Cañada Flintridge and Glendale.  It lasted for 21 days, destroyed 89 homes and killed two firefighters.  Of course, the fire did not begin instantly.  Rather, it started off small before it spread Northward and Eastward across the San Gabriel Mountains.  By examining the features of the land that supported the fire, one can gain insight into what geographical factors encourage fires to spread and what methodologies firefighters can and do use to contain the spread.  The below maps provide information for the analysis of why the Station Fire spread in the directions and to the extent that it did.

The reference map of the Station Fire Perimeters highlights the peculiar spread of the fire.  It shows that the fire spread northwest, along the ridge of the mountains against the valley.  Once it reached a certain latitude, it began to spread West and East, though it mostly spread East.  Eventually, it was contained in a circular region solely within the mountain range.  The fire reached the fringes of the populated valley, but never more than the very edge. 

The reference map and the Aspect Map explain some of the reasons why the fire spread in these directions.  The mountains on the East edge of the extended fire are relatively high in altitude, and thus provide a natural barrier to the continued spread of the fire.  In addition, this part of the mountain range has an aspect that predominantly points west, meaning that the fire would have to spread uphill in order to continue east.  High altitudes appear to quell the spread of a wildfire.

However, slope and aspect seem to be irrelevant to the pattern of the fire in every other direction, as evidenced by the fact that the fire did not spread into the valley, a region both lower in elevation and with an aspect that points south towards it.  In this latter case, it was likely the firefighters, and not the topography, that dictated the movements of the fire.  In addition, the Slope Map indicates little to no correlation between the ability of the fire to spread and the local topography.  The fire spread mostly over land with steep slopes.  This pattern was likely due to the fact that the more mountainous terrain was undeveloped and covered in trees than that it was sloped.

The reference map and the Land Use Patterns Map illustrate the success of the efforts of the firefighters to stop the fire from damaging populated communities.  The fire began very near the populated valley, and initially spread in all directions—including south.  But quickly, and despite the area’s south-facing aspect, the fire was re-routed to spread along the mountain ridge.  Because the fire so clearly avoided any populated areas, it appears that human efforts were able to control its path. 

The crew deliberately attempted to stop the fire from spreading across a populated region, as they were likely only able to stop its spread in one direction.  As the fire moved northwest, it once again began to reach homes, this time on its western edge.  And this time, the fire crew was able to stop its western spread.  By containing the fire on one side at a time, the crew ensured that the fire consumed land labeled by the US government as “Vacant Area.”  Ultimately, it was the firefighters, and not the topography, that dictated the spread of the Station Fire.

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[1] Bloomekatz, Ari.  “Station fire is largest in L.A. County's modern history.” Los Angeles Times 2 Sep. 2009.  <http://latimesblogs.latimes.com/lanow/2009/09/station-fire-is-largest-in-la-county-history.html>

Bibliography:

Los Angeles County Enterprise.  “All Station Fire Perimeters.”  2 Sep. 2009. <http://egis3.lacounty.gov/eGIS/2009/09/02/all-station-fire-perimiters-as-of-september-2-0702-complete-ste/>
 
USGS Seamless Data Warehouse.  “The National Map Seamless Server.” United States Geological Survey.
<http://seamless.usgs.gov/website/seamless/viewer.htm>
 
UCLA Mapshare.  “Los Angeles County Major Roads,” “Los Angeles County Local Streets,” “Los Angeles Interstate Highways,” and “2000 Land Use, Los Angeles County.” University of California, Los Angles. <http://gis.ats.ucla.edu//Mapshare/Default.cfm>
 
Bloomekatz, Ari.  “Station fire is largest in L.A. County's modern history.” Los Angeles Times 2 Sep. 2009.  <http://latimesblogs.latimes.com/lanow/2009/09/station-fire-is-largest-in-la-county-history.html>

Skelton, George.  “State help for firefighters ‘a heavy lift.’”  Capitol Journal 10 Sept. 2009.  <http://www.latimes.com/news/local/la-me-cap10-2009sep10,0,4019331.column>

 

 

This map displays the distribution of the African American population of the United States in 2000.  The data shows the percentage of each county's population that identifies as African American.  As is apparent, the South is predominantly black, while the West and Northeast have significantly smaller percentages of black residents.  The black population is particularly small in the Great Plains states of Minnesota, Iowa and Montana.

This map shows the distribution of the Asian American population in the United States.  Much like the black population, the Asian population in heavily concentrated in a few counties.  These counties tend to be urban, such as Los Angeles County or San Francisco County, and they tend to be located on the West Coast.  This makes sense, as Eastern Asia is nearest to the western United States.  In addition, because the Asian population immigrated to the United States much more recently than the African American population, it makes sense that the former has tended to congregate in urban areas.

This map shows the distribution of Americans who identify as belonging to another race, other than Caucasian, black, or Asian.  These Americans are heavily concentrated in the Southwest, in the four states that border Mexico.  It can be inferred that the majority of these Americans identify as Latino, and are predominantly come from Spanish-speaking countries.  Thus, California, Arizona, New Mexico and Texas are the primary destinations for these immigrants.  A notable contrast between the distribution of this group and that of Asian Americans is that while the latter tends to congregate in cities, the former populates both urban and rural counties.

This map exercise was enlightening about the spatial settlement patterns of different American races.  It showed where African Americans, Asian Americans and--presumably--Latino Americans tend to settle, and brought up some intriguing similarities and contrasts.  One the the most striking similarities between the settlement patterns of the three races is that all three groups tend to concentrate in specific areas.  However, these areas were drastically different for each race.  African Americans tend to live in more rural counties of the south, a pattern which is likely a vestige of the institution of slavery.  Asian Americans do the opposite, concentrating in cities on the West Coast.  The Latino population is concentrated near the border with Mexico, which is likely due to a combination of the fact the those four states are accessible from the south and that those four states have string agricultural industries.

Ultimately, I believe that GIS has a lot of potential as a field.  Combining different types of data (county borders, census population, bordering regions etc.) can bring to light patterns in societal development that would otherwise go unseen.  Using GIS, government officials can gain insight into such simple issues as the negative noise effects of an airport to such complex issues as the regulation of immigration.  The inference that one makes with the data is still the most significant part.  With proper inference techniques, GIS can be a powerful tool.

       For this week's lab, I chose to map the city of Pittsburgh, Pennsylvania.  The hilly city is located at the intersection of three rivers and thus has unique topographical features.  For example, the city's steepest slops occur at the edges of the rivers.  All of the following maps depict the same region: the area bordered by 40.30303 degrees North and 40.58202 degrees North and by -80.16993 degrees and -79.64664 degrees longitude.   The final graphic on this blog is a three-dimensional map of the city's topography.  The USGS source data for the maps employed the GCS_North_American_1983 coordinate system.

                This assignment revealed many interesting aspects of the map projection process.  The first piece of information I learned was that there are several different ways to measure distance between two points on a map.  In addition, different map projections represent these distances with different values.  For example, using the planar measurement, Kabul to Washington DC was 10,141 miles in the Mercator Projection, 8,329 miles in the Hammer-Aitoff Projection, 9,919 miles in the Stereographic Projection, 8,341 miles in the Azimuthal Equidistant Projection, 8,763 miles in the Behrman Cyinder Projection, and 6,919 miles in the Two-Point Equidistant Projection.  Overall, the Great Elliptic and Geodesic measurements were the most consistent (and always identical to each other) while the Planar measurement was the least consistent.  The rest of the data is stored in the table below.

                While no map was perfect, each projection had strengths and weaknesses.  The Hammer-Aitoff Projection and the Behrman Cylinder Projection were both very good at preserving areas; Greenland was not bloated like it is on most maps, and Africa took up its due space.  However, in the Hammer-Aitoff Projection, the shapes of the Pacific Rim nations (such as China and the United States) are heavily bent.  In the Behrman Projection, Africa is stretched vertically and Greenland is squished vertically.  Both maps, in this sense, fail to convey the shapes of the world.

                The Stereographic Projection and the Mercator Projection both preserved the shapes of individual countries nicely.  In both projections, the United States looks like it does on the globe.  The same is true with Greenland and with China.  However, the relative areas of these countries differ greatly from reality.  In the Mercator Projection, Greenland looks bigger than the continent of Africa.  Even more peculiar is the Stereographic Projection, in which the United States was rotated on its side about seventy degrees and Australia appears several times the size of South America.  The planar distances in these two maps between Washington DC and Kabul also differ the most from the actual distance.  Likewise, the equidistant maps had shortcomings.  Both the Azimuthal Projection and the Two-Point Equidistant Projection reported relatively accurate planar distances between the two cities, but distances between more Pacific cities came out distorted and the shapes of countries were very inaccurate.

                For most applications, it seems a hybrid map style is most suitable to depict the world.  An equal area map will distort angles and distances.  A conformal map will distort distances and areas and an equidistant map will distort angles and areas.  In a few applications—such as examining the missile range of North Korea—one of these three partially perfect styles may be needed.  But in most cases, one must compromise in order to get a good depiction of the globe’s geography.  For most applications, the best map will have slightly inaccurate angles, distances and shapes.  That way, none of the three elements is too distorted.

Projection Type:	Hammer-Aitoff	Behrman	Stereographic	Mercator	Azimuthal	Two-Point
Planar Distance	8,329 miles	8,763	9,919	10,141	8,341	6,919
Geodesic Distance	6,934 miles	6,934	6,934	6,934	6,934	6,919
Loxodrome Distance	8,112 miles	8,112	8,112	8,112	8,112	8,093
Great Elliptic Distance	6,934 miles	6,934	6,934	6,934	6,934	6,919

               Geographic Information Systems have both potential and pitfalls.  One of the great aspects of GIS, and in particular ArcGIS, is that it can be precise with information.  For instance, on the airport map, the user can zoom in far enough to see if Northwestern Prep is within or not within the noise contour.  The ArcGIS is also precise with the parcel boundaries and the land use boundaries.  GIS allows for the precision of information that cannot be obtained without using computers.

                GIS also allows for the efficient synthesizing of data.  This is in part due to the fact that ArcGIS can hold lots of pieces of data: population counts, parcel boundaries, land use patterns, school names, arterial locations etc.  Such large volumes of data would be difficult to store with computer software.  What gives GIS so much potential, however, is that it can combine data sets with almost no effort.  For instance, the user can create a map of population density easily by combining the population-per-parcel table with the area-per-parcel table.  Such a calculation would be painfully tedious and easy to mess up without software.

                GIS does have some problems, though.  The first is that it is prone to user error.  The ArcGIS software is complicated, with many different toolbars and buttons.  It can be easy for a neo-geographer to get lost in all of the controls, even when using a tutorial.  He or she can easily spend more time and effort trying to figure out how to use the software than trying to analyze the geographic data.  In this sense, GIS software can be a potential distraction to the user if their task is simple.

                Lastly, GIS software helps the user organize the data, but it does not provide analysis.  The user still must interpret all of the maps that he or she creates.  Perhaps, the greatest pitfall of GIS is that it can give the user so many tools to create maps that he or she forgets to interpret them.  At the end of the day, the most valuable skill a geographer can attain is the ability to use maps to make policy decisions (or other types of decisions.)  GIS cannot do this for the user; it is simply a tool to make the analysis easier.

http://maps.google.com/maps/ms?msid=208586145485020522765.0004be37131319b4c4ba5&msa=0&ll=42.163403,-96.240234&spn=38.318629,79.013672

              For better or for worse, the US News and World Report rankings have become integral to how high school seniors view colleges.  The rankings, which are debatably arbitrary, create a hierarchy of universities that often dictates where students apply to and attend.  This map examines the university rankings from a geographic viewpoint in order to see if there are any geographic biases or trends in the schools that get the top rankings.  Evidently, the northeast has monopolized the rankings, as eight of the top twenty-five and all of the top four universities are located between Washington D.C. and Boston.  Another unexpected trend is the lack of highly ranked universities on the West Coast.  In fact, outside of California, there are no universities in the top twenty west of the United States’ geographic center.

               Most of the pit-falls of neogeography lay either incorrect interpretation of geographic data.  For instance, one could conclude from my map that higher education is simply better on the east coast, yet this is a flawed assertion.  This map is only a map of the top-ranked universities, which are not necessarily the twenty-five objectively best universities.  In addition, mashups cannot communicate certain data that might be influential to the interpretation of the map.  For instance, UCLA and the California Institute of Technology both appear as equal sized pins on the map, yet UCLA has over thirty times the undergraduate enrollment of Cal Tech.  In this way novice mapmakers can create misleading mas that lend themselves easily to false interpretations.

1.      What is the name of the quad?

Beverly Hills Quadrangle

2.      What are the names of the adjacent quadrangles?

Canoga Park, Van Nuys, Burbank, Topanga, Hollywood, Venice, and Inglewood

3.      When was the quadrangle first created?

This quadrangle was created in 1966.

4.      What datum was used to create your map?

The North American Datum of 1927, the North American Datum of 1983 and the National Geodectic Vertical Datum of 1929 were all used to create this map.

5.      What is the scale of the map?

The scale of this map is 1:24,000.

6.      A) 1200 meters.

B) 1.89 miles.

C) 2.64 inches.

D) 12.5 centimeters.

7.      What is the contour interval on your map?

The contour interval is 20 feet.  In particularly flat areas, the map uses supplementary contours of interval 10 feet.

8.      What are the approximate geographic coordinates in both degrees/minutes/seconds and decimal degrees of:

A)     the Public Affairs Building

118° 26’ 15” W, 34° 04’ 33” N;  or 118.44° W, 34.08° N

B)     the Tip of Santa Monica Pier

118° 30’ 0” W, 34° 00’ 26” N;  or 118.50° W, 34.01° N

C)     the Upper Franklin Canyon Reservoir

118° 24’ 35” W, 34° 07’ 12” N;  or 118.41° W, 34.12° N

9.      What is the approximate elevation in both feet and meters of:

A)     Greystone Mansion (in Greystone Park)

Greystone mansion is on hilly terrain of elevation 560-580 feet (170-180 meters).

B)     Woodlawn Cemetery

The elevation is 140 feet (40 meters).

C)     Crestwood Hills Park

The elevation of Crestwood Hills Park ranges from 600-840 feet (180-250 meters)

10.   What is the UTM zone of the map?

The subject of the map is located in UTM zone 11.

11.   What are the UTM coordinates for the lower left corner of your map?

The coordinates are 3,763,000 meters north and 361,000 meters west.

12.   How many square meters are contained within each cell (square) of the UTM gridlines?

Each cell represents an area of one million square meters.

13.   Obtain elevation measurements, from west to east along UTM northing 3771000, where the eastings of the UTM grid intersect the northing.  Create an elevation profile using these measurements in Excel.  Figure out how to label the elevation values to the two measurements on campus.  Insert your elevation profile as a graphic in your blog.

In the following graph, the x-axis represents UTM meters east and the y-axis represents feet of elevation.

14.   What is the magnetic declination of the map?

The magnetic declination of the map is 14°.

15.   In which direction does water flow in the intermittent stream between the 405 freeway and Stone Canyon Reservoir?

The water travels due south.

16.   Crop out UCLA from the map and include it as a graphic in your blog.