Week 9: Mapping the Station Fire in ArcGIS

Reference Map

Erosion Map

The largest wildfire in the Angeles National Forest, and 10^th largest in California since 1933, happened on August 26^th, 2009. The wildfire occurred at the Los Angeles River Ranger District/ Angeles National Forest and was later found to be caused by arson. This arson contributed to severely burning more than 160,000 acres of forest and burned over 250 square miles of the San Gabriel Mountains. Though many places/aspects can be affect by this large of a wildfire, I was especially interested in the extent of erosion. ArcMap was essential to be able to map which areas result in more erosion after a wildfire, so that they can be controlled.

 For this week’s lab, I wanted to incorporate post-fire erosion around the Angeles National Forest area, where there was a tremendous wildfire in 2009. My map shows the fire extent of the 2009 wildfire and the rankings of erosion according to the methods gathered from CALFIRE.  The color scheme on my map shows tons/acres/year soil loss and ranks it that way from high to low. The high values (in umber) show the highest levels of erosion which appear to be located throughout most of the fire extent but mostly in the southwest region of the extent boundary. I wanted to base my map on erosion because I think it is a significant issue with hillside wildfires.

 I chose this data because it incorporated aspects of the area that I did not have to. Gathered from the post-fire erosion methods pdf from CALFIRE, it incorporated levels of vegetation and levels of fuel in an area, so places with low vegetation cover and high fuel would be more prone to erosion. Therefore areas with high levels of vegetation and low fuel, as shown in South LA County, will obviously have lower erosion rates.  I think it’s important because wildfires burn vegetation and destroy the litter layer (organic material) of the soil. Plant roots at this level are essential to stabilize the soil in hillslope areas, such as the Angeles National Forest. It also takes rainfall intensity into account, because as soil gets exposed to rain, the silt ends up in streams and rivers, which can affect main ecosystems and fish. What this map does not cover, however are other factors that affect soil erosion such as percent cover, contributing area, slope, soil texture, aspect, and precipitation that could be developed to predict sediment yields.

 In my second map, I only showed the rivers of LA County, not including the streams but all of these water sources can be extremely affected by erosion, which can threaten ‘life, property and water quality and water ecosystems.” The high runoff and erosion rates in headwater areas deliver large amounts of sediment to downstream channels. I think it’s crucial to map this because not only does erosion after fires cause many problems for vegetation and soils in the areas but it can also affect diverse ecosystems from small fish in estuaries to large animals that rely on them for drinking water.

I think my few maps show where more erosion control is needed in the future to protect against erosion from wildfires causing silt deposits in the rivers that are located in high threat locations. I think this information could be helpful for people in this field to prevent large devastation from erosion. Types of soil and vegetation would be much more effective to use for this project, if it were available for comparison before and after the 2009 wildfire.

Works Cited

“All Station Fire Perimeters (as of September 2, 07:02) – Complete set.” 

           http://egis3.lacounty.gov/eGIS/.

Mark Greninger, 2 Sep. 2009. Web. 28 Nov. 2012.

“LA County Boundary.” http://egis3.lacounty.gov/dataportal/2011/01/20/l-a-county- b

            oundary/drp_county_boundary/, 20 Jan 2011. Web. 29 Nov. 2012. 

“Los Angeles County Highways.” http://gis.ats.ucla.edu//Mapshare. ESRI, 1 April 

          2008. Web. 2 Dec. 2012.

“Los Angeles County Rivers.” http://gis.ats.ucla.edu//Mapshare. ESRI, 1 April

           2008. Web. 29 Nov. 2012.

MacDonald, Lee, and Peter R. RobiChaud. "Post-fire Erosion and the Effectiveness

           of Emergency Rehabilitation Treatments over Time." Stream Notes. 1-6. 

          Web. 13 Dec. 2012.

Moench, R, and J Fusaro. "Soil Erosion Control After Wildfire." . Colorado State

          University Extension, n.d. Web. 4 Dec 2012. 

“Post-Fire Erosion.” http://frap.fire.ca.gov/assessment2010/data.html. California 

           Department of Forestry and Fire Protection, 2010. Web. 29 Nov. 2012.

Pietraszek, Joseph H.  Controls On Post-Fire Erosion at the Hillscope Scale,

          Colorado Front Range. Diss. Colorado State University, 2005. Print.

"Station Fire." Inciweb. Angeles National Forest, 10 2009. Web. 4 Dec 2012.  

Lab 7: Mapping Census 2000

In this map, I used census data from 2000 to display the number of people per county. I used a North American Conformal Conic map projection and graduated purple color ramp to show the number of people in the United States as of the census of 2000. From this map we can tell that there are not as many people per county throughout the Midwest. Most of the Midwest such as Texas, Oklahoma, Nebraska, North and South Dakota usually have less than 25,000 people per county. Much of the 25,000-500,000 number of people per county are located elsewhere and around big cities in the U.S. Although some Midwest and central regions can also have large numbers of people, the highest numbers are mostly concentrated in the west and east coasts. Clusters of counties with the highest numbers of people are considerably dominant in Southern California  and the East coasts states such as Massachusetts, Connecticut, New York and the Northeast Metropolitan Region. 

This map showed the difference between the number of people per county from the 1990 census to the 2000 census. This map also was in the North American Lambert Conformal Conic Projection. The colors chosen for this map make it easy to understand, because the pink values show the greatest disparity of people per county. These pink counties have a negative value and this occurs mostly in the Midwest and scattered elsewhere throughout the U.S. The light green values show that the number of people per county has stayed or roughly the same on increased slightly. However, we can see great increases in the number of people over the decade in Southern California, Arizona, Florida, and the coastal regions of the East and Washington State. 

The percent change of the total population from 1990 to 2000 is different compared to the quantitative number of people map. This map, in North American Conformal Conic Projection demonstrates negative values in the Midwest, so there is a great percentage decrease in counties located there, especially in North Dakota. Much of the rest of the country seems to have very little percentage change in total population, except for a large part of Nevada and small counties throughout the U.S. 

My last and final map shows the population density as of 2000. Areas with little population are mostly located on the mid-west part of the United States. Even then, very few counties have less than a population density of 1. Many more counties with a population density less than 7 still continue in the midwest states of Nevada, Colorado, Nebraska, North Dakota, South Dakota, Idaho, and New Mexico. We can clearly see the great difference in the western and eastern United States. The eastern united states has many more counties with a population density ranging from 7 to 80. The most dense areas are definitely located on the eastern seaboard, Southern California, Florida, and places near bodies of water such as the great lake states, Washington, and the Bay Area. 

My census map series was a lot easier to do once I clearly understood the directions. I got confused following the lab instructions, but was able to make all four maps easy to read. I tried to make my maps neat, organized, aligned, and with symbols, neatlines and legends that were useful for someone else to understand. My overall impressions of GIS are that it is very useful for a variety of disciplines and uses.  I have enjoyed using this program so far and I am planning on working on my own GIS projects using my trial software during winter break. I plan to minor in GIS and am sure it will be advantageous for my future career.

Lab 6: DEMs in ArcGIS

DEMs in ArcGIS

 

The area that I selected for my four different maps of a DEM that was located near L.A. It was an area of digital elevation model ned_99839875. The extent on top was 39.8291666661 and on the bottom it was 39.3838888883 and left it was -105.788888889  and right it was  -104.969444445. The geographic coordinate system of my original DEM was GCS North American 1983. I used this coordinate system to display all 4 maps. 

Lab 5: Map Projection in ArcGIS

Equal Area Maps

1) Cylindrical Equal Area projection; distance: 10,011 mi

2) Berhmann projection; distance: 8683 mi

 

Equidistant Maps

(1) Equidistant conic projection; distance:7017 mi

2) Equidistant cylindrical projection; distance: 5066 mi

Conformal Maps

1) Mercator projection; distance: 9912 mi

2) Stereographic projection; distance: 10,068 mi

The significance of map projections can clearly be seen with the wide variety of options shown above. While trying to convey several aspects of maps that are conformal, equidistant and equal area, their projections are often very different from each other. They are significant because they can distort distance, shape, and size of land masses and oceans on the globe. For instance, if one uses a conformal projection such as the Mercator, land masses will not be true to their size. However, the projection might be useful for navigational purposes and to accurately depict shapes. Also, one might use an equal-area map to preserve area and the size of countries, in order for countries not to look like they are bigger than they really are. Others might use a conic equi-distant projection to preserve distance, which shows that these projections are the most true to distance between Kabul and Washington D.C.

                The perils of map projections are that instead of having one true map projection, in which size, shape and distance are preserved; they all have one of those elements missing. If one chose to use a Mercator projection, then the shapes of continents would be correct but the sizes of continents and distances between them would be very different. I would definitely not use this projection if I wanted to know the exact distance between two places. It might be easier for people to read maps if there was one common map projection, and not a variety to choose from.

I think the future of map projections will be crucial to serve different functions, occupations and uses. For instance, the conic equidistant map can display the spherical space of an area and zoom in on it.  An example would be showing Antarctica bigger than the rest of the globe. With the help of GIS, it can possibly display what we want know; such as how the ozone has depleted and thickened throughout several years with restrictions on CFC emissions. Different projections could help accurately preserve shape, size, or distance so people could discover things about earth and our climate. I think that map projections have the potential to grow and expand to different fields not just geography.

Just by conducting six different map projections, I was able to tell how different the world could look in other lenses. The properties of the projections, what they lack, and what elements they preserve can tell us a lot about how different disciplinaries use this to their advantage. These projections are used to showcase the element they want to be more precise and are able to in a variety of ways. 

Week 4: Introducing ArcMap

     I felt comfortable using ArcMap for this lab. I found that the ArcMap Tutorial made it very easy to navigate through the system. The tutorial gave step by step instructions of how to add layers to data frames and add other attributes to maps and tables. The fact that I had to do repeat some steps for different data frames helped me understand how to work with ArcMap myself without much tutorial help at the end. The things I had difficulty with were very minor,  but overall I think I understand this program well so far. It was interesting seeing how my maps came together at the end. I thought it was amazing to see how data can be so precise and display much more about regions than just physical characteristics.
     Some of the downfalls of ArcMap are that it is too precise for it to be too widely used and used by masses of people. If one misses a step or does not do it in order, it can alter the entire map. Also, it is very detailed so the person using it has to have clear knowledge of what they are doing. It is definitely not as user friendly as user-centric Google Maps, etc because the program  is not widely accessible or free. It is still prone to errors, but it's accuracy is increasing with better development of technology.
     The benefits of ArcMap far outweigh the pitfalls of it. There are many things one can do with ArcMap, such as show demographics, noise contour and other multi-disciplinary aspects. It helps companies, organizations, scientists, and engineers understand what they want to know about an area, demographics, and physical land. The great advantage of ArcMap is that if the data is accurate, then the maps will be very precise.
      I enjoyed using ArcMap because of the level of accuracy and if used right, how informative it can be about a variety of aspects, not just physical regions. This program is clear to understand and it is easy to change things. I think the more it is widely known, the better it will be for continued environmental and urban planning, as well as informing companies and organizations for better marketing and outreach.

Lab 3: Neogeography

                     
View MLB Teams in a larger map
     The advantages that neogeography has to offer are tremendous. This new phenomenon allows the public to have greater access to a variety of different things. They are able to discover where things are located and able to create maps for their personalize use. I personally found it interesting to make a map of all MLB teams and see where most of the stadiums are distributed. I included different color bookmarks relevant to the color of the baseball teams. I even included a video of SF Giants Buster Posey's grand slam in Cincinnati. I also added a picture of the newly remodeled Miami Marlins Stadium. The logos I put as bookmarks show which teams two teams are left to play in the World Series. I wanted to make a map that was very recent, and one could easily identify the different baseball stadiums. 
      Although neogeography is very helpful, one disadvantage of it is that information can be less accurate than if it were done by a professional/ GIS analyst. Since people are free to put any information that they please on a map, they may not be the most reliable means of data collection. It is not always the best idea to have this be so accessible. Google maps and other sites can also interfere with people's privacy. For instance, if people made a map of people's homes, such as celebrities or elected officials, it would be harmful to their safety. 

Lab 2: USGS Topographic maps

  1. The name of the quadrangle is the Beverly Hills Quadrangle

  2. The names of the adjacent quadrangles are

                  (1) Canoga Park

(2) Van Nuys

            (3) Burbank

(4) Topanga

(5) Hollywood

(7) Venice

(8) Inglewood

  3. The quadrangle was first created in 1995. (Course website topographic map)

  4. The datum used was the National Geodetic Vertical Datum of 1929

  5. The scale of the map is 1:24,000 (inches)

  6. A. 5 centimeters on the map approximately equals 1200 meters

B. 5 inches equals approximately 1.89 miles on the ground.

C. One mile on the ground equals about 2.64 inches.

D. Three kilometers on the ground equals about 12.5 inches

  7. The contour interval on my map is 20 feet

  8.  The approximate geographic coordinates in both degrees/minutes/seconds and decimal degrees

            A. Public Affairs Building (34° 4’ 31” North; 118° 26’ 11” West; N 34.07527, 118.4363 W)

            B. Tip of Santa Monica Pier (34° 0’ 32” North; 118° 0’ 30” West; N 34.008, 118.0083 W)

            C. Upper Franklin Canyon Reservoir (34° 7’ 15” North; 118° 24’ 30”; 34.12083 N, 118.408

  9. The elevations of these places in feet and meters

            A. Greystone Mansion – 580 feet, 176.784 meters

            B. Woodlawn Cemetery – 131 feet, 39.928 meters

            C. Crestwood Hills Park – 698 feet, 212.7504 meters

  10. The UTM zone is 11

  11. The UTM coordinates for the lower left corner of this map are 3763000 mN and 3615000 mE

  12. Each square cell of the UTM guidelines is 1,000,000 meters

  13. 

  

  14. The magnetic declination is 14 degrees east

  15. The direction of the water flow in the intermittent stream between the 405 and Stone Canyon Reservoir is North to South

  16. UCLA

Lab 1: Maps

Map 1: World Ethnographic Map (1852)

This 19th century map shows divisions of the world by ethnographic groups. The races listed on here include Indo-European, Mixed Indo-European, American, Syro Arabian, Mongolian, Negro, Papuan-Negro, Mongolian, Malay, and Australian. It is also shows an enlarged map of Europe, separating the continent by subgroups of the Indo-European ethnographic group. This map has lines north and south throughout that are called 'limits of permanent habitation', which isolate the uninhabited Antarctic and Arctic regions. I found  the divisions of ethnographic groups in South America interesting because of the distinction between Americans and other ethnographic groups located on the coasts. This map shows that Central America was primarily inhabited by Americans however there are separate distinct, non-American groups on the coast of Colombia, Peru and Brazil. I like this map because it is an older map and it shows how classifications of race in this time period were a lot more specific and formal than they are today.

Source: 

Blackwood, William . Natural History World Ethnographic Map. 1852. Photograph. Hipkiss, Edinburgh & London. Web. 2 Oct 2012. <http://www.hipkiss.org/data/maps/blackwood-and-sons_keith-johnsons-physical-school-atlas_1852_natural-history-world-ethnographic-map_3029_2348_600.jpg>. 

Map 2: Physical Map of Argentina (2009)

This map of Argentina shows its borders, physical attributes and oceans. It shows that Argentina borders Chile,Paraguay,Uruguay, Brazil, the Southwest Atlantic Ocean, and even shows the relative depth of the water by color. The map also shows major cities such as Cordoba, Buenos Aires, and Mendoza. The main attribute of this map is that it separates Argentina's regions, showing that it has diverse landscapes. In the West, Argentina shares the Andes mountains with Chile, to the South is Patagonia, a very cold mountainous terrain near the Antarctic region, and the northwestern part of the country is pampa landscape. I find this interesting because typically people think Argentina is mostly flat, pampa landscape but it also has mountainous regions that are a major part of the country. I find it interesting to think about Argentina as a place with diverse land, which further indicates diversity with their people and ways of living.

Source:

Argentina Map-Physical Map of Argentina. 2009. Photograph. Ezilon MapsWeb. 2 Oct 2012. <http://www.ezilon.com/maps/south-america/argentina-physical-maps.html>. 

Map 3: Senate District Map of Southern California

 My third map is the senate district map of Southern California. It stretches from Ventura to San Diego, and includes two of the Channel Islands (Santa Catalina and San Clemente.) It shows colored areas for each district. I find this map interesting because it shows how district lines are divided and are in very odd shapes. I also like this map because it shows my district in Oxnard. Interestingly, it does not include Simi Valley, Thousand Oaks and other areas that are primarily Republican. It is intriguing to me to see how my district is a very thin stretch of the coast which demonstrates how distorted and manipulated district lines have come to be. 

Source: 

Senate Districts Southern California Area Detail. N.d. Photograph. California State LegislatureWeb. 2 Oct 2012. <http://www.legislature.ca.gov/legislators_and_districts/districts/assemblydistricts_LA1.html>.