Mini Project: Mapping the Station Fire!

  

            This week, for my final mini-project, I explored data on the internet indicating the various locations and dates of LA County fires from August to September, 2009. I then input this data into Arc Map and utilized my knowledge of vectors and GIS modeling to create one reference and two thematic maps. I chose to display elevation and slope, and imported the DEM into my blog for you all to see! What I analyzed was the effects of topography, specifically slope and elevation, on the spread of fires in LA County.

             It is pretty apparent from my DEM that the fire spread increases and covers more area with increasing elevation. This is suggested by the contour lines, which illustrate that, for the fires that covered more surface area, the elevation was of mid to high level. This finding is actually quite interesting, because it contradicts the general trend of decreasing rates of fire spread with increasing elevation.

        Generally, elevation influences temperature, precipitation, and humidity. The consequence of this is its influence on fuel availability. However, at mid-elevations, thermal belts can occur. This causes the warm air to become trapped below cold air at any elevation level, and tends to happen at night. My thematic map illustrating elevation then suggests that thermal belts might have been the cause of increasing fire spread with increasing elevation.

       I additionally looked into the effect of slope on fire spread. Slope affects fire in the same manner as wind. Slope’s influence on the flame angle results in combustibility and an increase in the rate of fire spread. This general trend is pretty consistent with my DEM, as the largest fires occurred with slopes in the yellow/red category (moderate to high slope levels).

        While my hypothesis about the pattern of thermal belts may or may not be correct, it is definitely apparent that my DEM negates preconceptions of elevation’s affect on fire spread. At the same time, it is consistent with the findings presented on my map of the slopes, indicating that there was no interference with its consequential effect on flame angle and combustibility. I now have a better understanding of how GIS can be utilized to either confirm (or dispute) an accepted trend in environmental occurrences. Maybe it will help Smokey prevent some forest fires (or LA county ones) in the near future!

Works Cited

"DEM Derivative: Slope Gradient and Aspect." UBC Department of Geography. Web. 09 Dec. 2011.       
                 <http://www.geog.ubc.ca/courses/geog570/talks_2001/slope_calculation.html>.

"Effects of Topography on Fire Intensity and Rate of Spread —

Forest Encyclopedia Network." Encyclopedia Collection — Forest Encyclopedia Network. Web. 09 Dec. 2011.

<http://www.forestencyclopedia.net/p/p489>.

Gesch, Dean. "Fact Sheet 2009-3053: The National Map-Elevation." USGS Publications Warehouse. Web. 08 Dec. 2011.    

<http://pubs.usgs.gov/fs/2009/3053/>.

"GIS Manual: Spatial Information in Design Culture." HarvardUniversity Graduate School of Design. Web. 08 Dec. 2011.

<http://internal.gsd.harvard.edu/gis/manual/dem/>.

"USGS SDTS Format Digital Elevation Model Data (DEM)." FreeGIS Data - GIS Data Depot. Web. 09 Dec. 2011.   

<http://data.geocomm.com/dem/>.

Lab Seven: Census 2000!

 

For this week’s lab, I downloaded information from the Census Bureau website to construct three different maps. My map series displays percent population information from the year 2000. The first map displays population percentages for the Black only population. The second map displays population percentages for the Asian only population. My last map displays information for some other race. Prior to this lab, I was unaware of the level of availability and accessibility of information to the public. Because the census website was so accessible, I was easily able to construct my map series, which I will now describe.

As mentioned above, the first map in my series displays the percentage of Blacks in the continental United States. It is apparent that the Black population in 2000 is still heavily concentrated in the south.  While there is a slight population of Blacks in the southwest, the majority of the population resides in the southeast and eastern Untied States. This provides contrasting evidence to the stereotype that Blacks mainly reside in urban areas. It is interesting that, even after all the subjugation historically faced by Blacks in the south, they have, for the most part, stayed put.

The second map in my series displays the percentage of Asians in the continental United States as of the year 2000. Consistent with modern trends, it appears that the majority of the Asian population resides in California and along the west coast. There is also a significant portion of the population that inhabits the East Coast, and not so much within the Midwestern United States. The population patterns of Asians in the continental United States correlates with the settings of major research institutions. This substantiates the stereotype that Asians are very academically proficient, and wish to reside in a setting where they can utilize major academic institutions.

The third map in my series displays the percentage of “some other population” in the continental United States as of 2000. Historically, Hispanics have identified with this classification, as they are not “Caucasian”, “Black”, or “Asian.” From this map, it is clear that the majority of “some other” resides in California, which coincides with the trend of Hispanic residents currently inhabiting our state. For the most part, the percentages of “some other” are highly concentrated in the western portion of the country. This substantiates the stereotype that the west is “less traditional” than the East, which is generally home to the traditionally conservative population.

Overall, I have found GIS to be a convenient tool in its availability for public use. However, prior to taking this class, I was not educated at all about GIS, and had no idea that it was something I could utilize from my home computer. As I mentioned previously, I was so surprised that the US census information was so readily available online. With tools such as ArcMap, ArcCatalogue,  GoogleMaps, etc, everyone can become a geographer! The only challenge presented by ArcGIS is maneuvering the various programs used for presenting geographic Information. But if you ask the right questions, you’ll definitely get it all down… Eventually!

Lab 6: DEMs in ArcGIS!

     The area I selected encompasses two regions of Nevada called Preston and White Pine. The approximate altitude is 1831 meters, which is about 6,007 feet. The area was taken from DEM "ned_54653618"and the extent was from 39.64 degrees to 38.91 top to bottom and 115.26 to -115.37 left to right. Based on these coordinates, my selected area falls under UTM zone 11. The geographic coordinate system used was GCS North American 1983.  

Lab Five: Projections in ArcGIS!

The Significance of Map Projections

            Depending on what one is looking for, map projections can either significantly facilitate or hinder the presentation of geographical data. The three main classifications for map projections are as follows: conformal, equal area, and equidistant. Conformal projections preserve angle measurements, equal area projections preserve areas, and equidistant projections preserve distances. However, each projection lacks the preservation of the other two dimensions, and greatly distorts their measurements. I was unsure of how significant these distortions were until completing this lab.

            The two conformal projections I chose were the Mercator Conformal Projection and the Eckert I Conformal Projection. It is quite evident that these two projections differ in their representation of the shapes of the continents. Because of this, the area of the continents is not preserved. Even more evident is the misrepresentation of distance: the Mercator reports the distance between Washington D.C. and Kabul to be over 10,000 miles and the Eckert I reports it to be just above 6,700 miles.

            The two equal area projections I chose were the Bonne Equal Area Projection and the Sinusoidal Equal Area Projection. These both obviously distort angle representation relative to the graticule. They distort the distance between the two cities as well. The Sinusoidal projection represents this distance as just above 8,000 miles while the Bonne projection represents this distance to be just above 6,700 miles. Furthermore, the shapes of the projections are notably unique, and might not be the most easily comprehended to a novice geographer.

            The two equidistant projections I chose were the Two-Point Equidistant Projection and the Equidistant Cylindrical Projection. Even while these two projections both claim to represent distance equally, there is still a discrepancy in the reported distances between the two cities. The Two Point Projection reports this distance to be just above 6,600 while the Equidistant Cylindrical Projection reports this distance to be just above 5,000 miles. Therefore, it is important to evaluate the strengths of various map projections; even within their relative classifications, there are still distortions. 

Lab Four: Getting Started with ArcGIS!

            This week, we were introduced to ArcGIS through the use of the ArcMap software.  In using ArcMap, we were able to create our own maps and data tables by adding and inputting attribute layers into the ArcMap software system. This was definitely a lengthy process, but it was definitely rewarding to see the end product! This was the first advantage I came across in ArcGIS—there are so many ways to customize and present information through programs such as ArcMap. These software systems certainly provide you with a lot of liberty in constructing and displaying geographical information, and making it specific to your preferences for display.

            However, ArcMap and ArcGIS also present a few pitfalls. Because not all computers are equipped with the software to run ArcMap, I was unable to do work on ArcMap outside of the lab. In our “Introduction to Neogeography” lab, I was able to edit my map as I pleased. If I had an idea, or wanted to add something after making changes, it was quite simple—all I had to do was log onto my “Google Maps” account and could start editing right from the comfort of my own room.

            Secondly, for people like me (those who are interested in GIS but not “techy”), using this system can become quite complicated. It is hard to navigate ArcMap because not all of the toolbars are visible automatically, and the intricacy of the software system can be a thing of confusion rather than simplification. Furthermore, the instructions for using ArcMap were consistent with an earlier version of the software. Thus, inputting layers and attributes became a technological nightmare, and I realized how much I missed creating mashups of the Loire Valley.

            Because of this, it is clear to see that technological innovation, which accompanies GIS, forces people to become “up with the times.” This means that, if you are interested in GIS but aren’t exactly familiar with the technology that accompanies it, you must become more proficient with the tricks of the trade. Thus, while a pitfall, the complications that come with GIS technology can also be a potential stimulus—one that can better equip the world with the means of creating GIS masterpieces like this one! 

Lab 3: Neogeography!

View The Loire Valley: The Best Place Ever! in a larger map

This lab was my first experience with dynamic mashups as a component of neogeography. Using Google Maps, I was able to construct an interactive map of the Loire Valley in France. I included many Châteaus, restaurants, a Cathedral, and even an amusement park in my map. Moreover, I was able to use the tools in Google Maps to construct routes between features and embed photo and video into the mashup.

This lab allowed me to see the potential for neogeography as a revolutionary tool in GIS. Its accessibility to any and everyone makes it a valuable tool for those exploring GIS, and provides people with an easy way to learn more about the world around them. Furthermore, it is puts a personal and artistic spin on GIS, which definitely makes it more appealing as a field of science and discovery.

Unfortunately, in constructing this mashup, I came to realize that there are pitfalls and potential negative consequences of neogeography. While its accessibility to any and everyone can be seen in a positive light, neogeography offers people liberties in the information they present to the public—much like Wikipedia. Thus, what one finds in a mashup or an interactive map may not be accurate. This is not always intentional—in trying to construct routes between Châteaus and restaurants, I was unable to place the start of the route directly on the icon that denoted the map feature. Thus, if someone were to use my mashup as a guide for their tour in the Loire Valley, they might have trouble navigating between these locations.  While these problems exist, neogeography is still revolutionary in the field of GIS, and will be even more beneficial once the kinks get worked out!

Lab Two: USGS Topographic Maps!

1. The Quadrangle is Beverly Hills, CA.

2. The adjacent quadrangles are Canoga Park, Van Nuys, Burbank, Topanga, Hollywood, Venice, and Inglewood.

3. The Quadrangle was first created in 1966

4. This map has three datums: the North American Datum of 1927, the North American Datum of 1983, and the National Geodetic Vertical Datum of 1929.

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

6. (a). 5 cm= 120,000 cm on ground. This is 1,200 meters.

(b).5 inches= 120,000 inches on ground. This is 1.8939 miles on the ground.

(c).1 mile= 63360 inches. We divide this by 24000, which equals 2.64 inches on the map.

(d). 3km= 300,000 cm. We divide this by 24000, which equals 12.5 cm on the map.

7. The contour interval on the map is 20 feet.

8. The approximate geographic coordinates of:

(a). Public Affairs Building= 34 degrees, 4 minutes, and 30 seconds N and 118 degrees, 26 minutes, and 50 seconds W.

(b). The tip of Santa Monica pier= 34 degrees and 37 seconds N and 118 degrees, 28 minutes and 26 seconds W.

(c). The Upper Franklin Canyon Reservoir= 34 degrees, 7 minutes, and 15 seconds N and 118 degrees, 24 minutes and 45 seconds W.

9. The approximate elevation in both feet and meters of:

a). Greystone Mansion: 620 feet (188.976 meters)

b). Woodlawn Cemetery: 140 feet (42.672 meters)

c). Crestwood Hills Park: 620 feet (188.976 meters)

10. The UTM zone of the map is 11

11. The UTM coordinates for the lower left corner of the map are 3763000 North and 362000 West.

12. 1x10^6 meters squared

13. Obtain elevation measurements, from west to east along the UTM northing 3771000, where the eastings of the UTM grid intersect the northing. Create an elevation profile using these measurements in Excel (hint: create a line chart). Figure out how to label the elevation values to the two measurements on campus. Insert your elevation profile: 

14. The magnetic declination of the map is 14 feet

15. The water in the intermittent stream between the 405 freeway and Stone Canyon Reservoir flows southward.

16. Crop out UCLA from the map and include it as a graphic: