Final Lab

My first map displays the percentage of the Asian population of the contiguous United States from the 2000 Census statistics. The percentage is from the total population. By looking at this map, the first pattern that arises is that the are with the highest Asian population is California, particularly southern California. This is where the most clustering occurs as well as the highest percentage. There also appears to be a small clustering along the upper east coast.

In this next map, the percentage of the Black population around the United States is displayed. Rather than being clustered in a small area like southern California, the black percentage of the population is spread primarily around the south east portion of the country. This extends through several states, but is still clustered more towards the coast line. In addition, there still is a clustering in California, in the central to southern area.

This last map shows the percentage of the population that is American Indian and Alaskan. Here too is a clustering in California. On top of this, there is a strong clustering in the states between California and Texas; the percentage is higher here than it is in California. Unlike the other maps this one shows pockets of their population periodically throughout the entire United States.

Receiving the Census data on paper as numbers only tells you so much information. By joining this data with county lines of the United States, the geographic location of certain races takes a visible form. This shows clustering in certain areas. For example, each race has a clustering in California. This could be used to explore aspects of California such as policies, school systems, social characteristics, stereotypes, etc. as to why other races cluster here rather than other places.

In general, I really enjoyed my GIS experience. My biggest problem was that horrible red exclamation point telling me that my data was from the wrong place. I also had no idea how much creative license there is in GIS. I didn’t realize how many different projection types there were; I just assumed that maps were unbiased representations of the world. I also was not aware how much things like color ramps and label placement and color and font mattered, it really makes a difference in what you are trying to say with your map and what audience you have. I’m looking forward to continuing with GIS in future quarters.

Week 8 Lab 7

This reference map is to show the county line of Los Angeles and the fire perimeters over a period of time.

This thematic map is to place the fire perimeters on top of three major parks in Los Angeles county in order to find some sort of correlation between the parks, their fire policies, and the severity of the wildfire.


The 2009 Station Fire of Los Angeles burned over 160,000 acres as well as 80 homes and killed two firemen (O’Neil, 2010). Even though it has been over a year since the 2009 Station Fire, those harmed by the fire are not satisfied with how the event was handled (O’Neil, 2010). My exploration with this lab takes this further than simply saying the aftermath was not handled correctly, but rather that the fire policies in place before the fire were not adequate. I chose to examine the three major parks of Los Angeles County in terms of what type of vegetation was there and what kind of fire policy these parks practice.

Certain ecosystems require fire as a natural part of the health and growth of the vegetation in that ecosystem. For example, fire allows seeds to resprout and facilitates basal resprouting (when the biomass is underground so by the time spring comes around the plants resprout). Los Angeles County is in the Mediterranean ecosystem. In this, most plants are shrubs have unique characteristics to adapt to fire (Berg and Hager, 2009). The reason why fires spread quicker and are more dangerous to humans when they are prevented in an area where they are naturally occurring is because different levels of vegetation arise. The debris at the ground level builds up, catching on fire, reaching the next level of vegetation, and spreading to the higher levels that did not burn down the year before, etc. until the fire reaches levels very difficult to maintain (Berg and Hanger, 2009).

Since these parks all reside in a Mediterranean ecosystem, the fire policies are very important. For example, although fire prevention is promoted by the Santa Monica Mountains, they focus on cleaning up the highly flammable debris as well as educating the surrounding suburban development as to how to be safe from wildfires (such as buffer zones, etc.) (Santa Monica, 2010). In terms of the Los Padres National Forest, their fire policy contains the Brookshire Hazardous Fuels Reduction project. Since this forest is composed of mostly chaparral (vegetation where fire is a natural occurrence) this entails controlled burns over manageable conditions in order to cut back on dangerous wildfires that spiral out of control (Los Padres, 2010).

Since the station fire was located only in the San Bernardino National Forest and not the other major parks, the important part of this lab is to compare this fire policy to the above mentioned parks and make conclusions from there. First of all, on the United States Department of Agriculture website for this park there is a picture of Smokey the Bear under the section called "Fire Prevention." In all of my environmental science classes every professor has said the same thing: Smokey the Bear causes forest fires. Everything on this website is about fire suppression and prevention. There are no controlled burns or debris clean up like the Santa Monica Mountains (San Bernardino, 2010). As mentioned earlier, with this vegetation controlled fires are very necessary in order to both promote vegetation health (by keeping out invasive species, etc.) and decrease the severity of wildfires.

Looking at the fire policies for each park, a conclusion can be reached that the dissatisfaction on how the fire was dealt with stems more from the fire prevention policies before the fire struck rather than the post fire action (although this did still play a role). There are other factors, such as high elevation variation, the Santa Ana winds, and highly flammable vegetation (due to the turpentine in the shrubs), that contribute to the extremity of wildfires but the fact that the Station Fire was here rather the other National Forests with similar elevations and vegetation shows that there must be another force at play (Berg and Hager, 2009).

Works Cited:
Los Padres National Forest. United States Department of Agriculture, Forest Services, 2010, Web. 23 Nov. 2010.

San Bernardino National Forest. United States Department of Agriculture, Forest Services, 2010, Web. 23 Nov. 2010.

Santa Monica Mountains. National Park Service, Department of the Interior, 2009, Web. 22 Nov. 2010.

O’Neil, Megan. “Anger, frustration still flaring over Station fire.” La Cañada , 25 Aug. 2010, Web. 22 Nov. 2010.

Berg, Linda R., and Mary Catherine Hager. “Visualizing Environmental Science.” New Jersey: Wiley & Sons, Inc, 2009. Print.

For this lab I chose one of the Hawaiian islands to map. More specifically, the island of Maui. The reason I chose this particular is because of the volcanoes. I felt like a volcano would create a more dramatic 3D image to demonstrate the large changes in elevation, emphasizing the point of this lab better than other geographic aspect that may have a large elevation but not much variation. The geographic coordinate system information was obtained from NAD 1983 UTM Zone 4N. The coordinates in decimal degrees are as follows: 2331439.2804 Top, 734374.27277 Left, 819063.418264 Right, and 2270032.06128 Bottom.

Week Six Lab

Before this class I assumed that maps were pretty much always the same these days. Before I knew how map projections worked I thought that there was pretty much one standard way to project them so that all maps reflected the same distances and areas and whatnot. I never took into account that the earth is not a perfect sphere and on top of that there are more ways than one to transform a 3D object into 2D. While doing this lab and recording the distances I was astounded at how different some of them were, some have over 1,000 miles of difference.

For this lab the true distance (the no projection map) between Washington D.C. and Kabul is approximately 6,976.426 miles. The projection furthest from the true distance was the conformal Mercator measuring a distance of 10,198.004 miles. This could be accounted for by the fact that the conformal mercator projection maps preserve the angles, distorting distance the most (more specifically over exaggerating the distance). However, the other conformal projection I used (conformal Gall Stereographic) recorded a distance of 7,229.78 miles. This shows that even within the same type of projection type there are differences.

Comparing the equal area and the equidistant projections they both have a variation of a little less than 2,000 miles between the different types within the projection. For the equal area I used the Hammer projection which measured a distance of 8,398.08 miles and the Bonne projection which measured a distance of 6,898.32 miles. In terms of the equidistant projections I used the equidistant Conic (which measured 7,058.30 miles) and equidistant Cylindrical (measuring 5,149.77 miles). The fact that these have a similar difference may be significant, or it might be coincidence.

Map projections can be misleading. Certain projections may be used to manipulate the data being presented. These maps actually look different, they are even shaped differently -- some being rectangular, some shaped like an ellipsoid, etc. Maps are not unbiased or objective, they too are subject to their creators subjectivity and own interests they have in mind. If you want to emphasize the closeness of an area like from the nations capital to Kabul, Afghanistan to show the threat of that area as being closer to home you are not going to use the conformal Mercator projection; instead you would be more likely to use something like the equidistant Cylindrical or equal area Bonne projection. This demonstrates the importance of checking what map projection is used on the map you are looking at.

ArcMap Tutorial

I did not think this was going to be a difficult lab because I was just following very specific instructions, but I ran into a lot of trouble. I ended up doing a few parts about 5 times, and had to completely start over about half way through. I completed exercise 1 during lab section and saved the data on my flash drive thinking that it would be simple to use remote access to finish it at home, but it turned out not to be that simple. I did not originally use the data from the correct location (I thought I had, but I thought wrong). The source of my data came from the S: drive, obviously creating issues. I did also have issues figuring out how to properly navigate between Remote Access and my flash drive, I still don't know exactly where to save everything.

Retrieving the data from the correct location so that I could make and save corrections was the hardest part for me. By the second time around I was VERY careful about where every piece of data came from. I also did not save my work as often as I should have. I did periodically save my work, but there were times (particularly when I was doing the Field Calculation and messed that up) where I had to start over a certain part but did not save my previous work, making me start over even further back. It was very frustrating, and now it is Thursday night before my Friday morning lab and I just now have it all figured out and ready to go.

I have used GIS maps in previous classes, but not very thoroughly. I had no idea how interactive you can be with the layers and how much information you can show through graphs and shortcuts and street names, etc. It's easy to make a lot of mistakes with ArcMap, but the information provides a plethora of services to the user. The ability to turn some layers on and some off, to change the color, or to add legends and scales allow these maps to serve multipurposes.

However, as I said easier it is very easy to make mistakes. Something as easy to overlook as having one layer placed above another on the table of contents may change the view-ability of the map and obscure it's purpose. Although these maps are not made by amateurs, that does not make them perfect. Layers can be made with faulty data make them unusable and calculations may be performed wrong. Because so much is done by the computer, mistakes may not be as easy to catch (especially in the case of calculations).

Google Map

View Local Natives on Tour 2009 in a larger map

GIS systems used to be reserved for only military purposes; it was not distributed to the public. Today this technology has become more available to the general public. There are GPS systems to put in your car as well as in your phone, a recent phenomenon. Stemming off of this, there is neogeography - a way for amateurs to create their own maps and share information with others without GIS knowledge. Applications such as Google Maps allows the user to create their own map any way they want displaying any information they choose. For example, a user may map a vacation by placing photos they took while there on the map location of the place the photo was taken. All of this information is created voluntarily by the user.

Some concerns arise from this new technology in the are of privacy. With Google Earth, one may view any location as well as the people at that location. Some people expressed concern when people were caught doing things they did not want people to know about. This growing craze of updating the entire world of your whereabouts at every moment does indeed give reason for concern. Some people go even further than worrying about individual privacy and worry about terrorist organizations using this information to plan an attack. In addition to this, this volunteered information tends to lack documentation ( such as in terms of when it was created) reducing the legitimacy and trustable of sites that use this information. Because of this, there are no standards or rules to follow, so there is no way to know if the mapped information you are viewing is accurate. Neogeography is created by amateurs for amateurs, so naturally there are bound to be pitfalls and consequences.

Lab Two: USGS Topographic Maps

1. Beverly Hills Quadrangle

2. Canoga Park, Van Nuys, Burbank, Topanga, Hollywood, Venice, Inglewood

3. 1966

4. Horizontal datum: North American Datum of 1927 (NAD 27) and North American Datum of 1983 (NAD 83)
Vertical datum: National Geodetic Datum of 1929

5. Scale is 1:24,000

6. a. 5cm/ground=1/24000 => ground=120000cm=1200m
b. 5in/ground=1/24000 => ground=120000in=1.894mi
c. map/1mi=1/24000 => map=1mi/24000 => 6360/1in x 1/24000=2.64in
d. map/3km=1/24000 => map=3km/24000 => 300,000/3km x 1/24000=12.5cm

7. 20ft

8. (a) Degree/Minute/Seconds: 34° 03' 45''N, 118° 26' 20''W
Decimal Degrees: 34.0625°N, 118.4386°W
(b)Degree/Minutes/Seconds:34° 01' 12''N, 118° 29' 42''W
Decimal Degrees: 34.17°N, 118.495°W
(c) Degree/Minutes/Seconds: 34° 06' 43''N, 118° 25' 15''W
Decimal Degrees: 34.219°N, 118.4209°W

9. (a) 580ft and 176.83m
(b) 140ft and 42.627m
(c) 720 ft and 219.456m

10. Zone 11

11. Horizontal: ^3 61.5 easting
Vertical: ^37 63 northing

12. 1000000m^2

13.

14. +14 degrees

15. It flows south.

16.