Lab 8: Census 2000/2010

This map illustrates census data by county, while representing the spread of people who chose their race as Asian on the 2000 census, throughout the United States of America. This map illustrates a population distribution of Asian in percent per county within the United States. The map indicates a concentration of Asians on the coasts and with a somewhat surprising concentration through the "Bible Belt". A significant observation can also be found in the intervals of the legend. The percentages of concentration never reach above 20% in any given county. Though trends of concentration clearly exist, the concentrations on this map do not point to a specific area where the population seems to principally live. It is important to observe the tricks that the differing county sizes in the west coast from the east coast can play in deceiving the data. Viewers of this map may attempt to read overall population size out of this map which would be blurred greatly by not knowing the actual population of each county. This only represents percent of Asians per county in relation to overall county population.


This map also illustrates census data by county, while representing the spread of people who chose their race as Black on the 2000 census, distributed across the United States of America. As with the previous map, this map also shows the percent of Blacks per county. There is an obvious concentration of Blacks in the south and southeastern portion of the country. This concentration is quite high and worth noting in terms of the data intervals. The category with the highest percentage can reach as high as 87%. This is a significant difference when compared with the other two maps. Given the consistently high levels of concentration in the south one could almost surmise that one of those counties could hold a larger than 50% majority. If someone was so inclined to look further into this question they would be able to change the breaks to indicate it but given the rest of the US counties somewhat meager percentages, it would be easy to lose the significance of those counties with smaller representation.


This map once again illustrates census data by county, while representing the spread of people who chose their race as "Some other race" on the 2000 census, across the United States of America. The map shows the percentage of "Some other race" per county. "Some other race" is considered to be a "non-standard" category in respect with the other race categories on the census. This category is used to catch all other races that are not included within the other race categories such as many mixed racial backgrounds as well as nontraditional races. Given the intention of this category, "Some other race" is consistently considered to be dominated by people of Hispanic or Latino descent (according to the American Census Bureau). With this in mind, the mapped percentages of these populations make more sense in terms of the most concentrated locations, being that historically these are the regions with the highest representation of Hispanic and Latino races. Yet, the idea of this category holding many racial groups should always be considered when looking at "Some other race" maps.

My overall experience with the census mapping series has been eye-opening. The attention to detail that is necessary in order to properly present the information from the census requires a broad knowledge. It is important to understand the intentions behind the census itself as well as the methods through which they have chosen to carry out those intentions. Through this knowledge of the census, the GIS map creator can better represent the data at hand. This process has many pitfalls in terms of data acquisition, data manipulation (joining tables), and representation through the various types of data classification. Greater knowledge of these areas greatly benefits the quality of the map created through census data.

My GIS experience through this class has shown me the great potential that GIS has to offer. By gaining the foundational knowledge of working with GIS, I have been able to better orient myself in the realm of creating and viewing maps. This experience gained has shown me what a powerful tool GIS can be in trying to answer any geographically based questions. Though there is quite a steep learning curve associated with the use of GIS, this fact only proves the vast potential of the software and of the individual wielding it. Census data lends itself to the use of GIS as a software that can unearth important statistical characteristics of our population.

Lab 7: Mapping the Station Fire in ArcGIS

Wildfires, though a natural part of the ecosystem, can cause a variety of problems in graded urban areas. Landslides, debris flow, and flooding are just a few negative events that can result from wildfires that have burned over sloping terrain. Land, mud, or debris flow have a higher potential depending on the gradient of the slope, make-up of the soil, and water saturation. With increased slope gradient and water saturation, soil make-up is less of a factor in slides due to the overwhelming gravitational forces. Though these factors are commonly understood, wildfires effects on slides can be counter intuitive.

The problem with wildfires is when ,as mentioned by US Forest Service, the "intense heat... can cause the soil to 'seal' itself and water will not easily penetrate it." This act of sealing the soil causes the rain runoff to flow directly into creeks and watersheds without the normal absorption from soil and plant life. This additional water acts as a massive storm for the soil and plant life below the burn zones. This additional water can over saturate the soil below and cause land, mud, or debris flows.

This diagram from the Council of Geoscience shows some of the contrast between soil types, saturation levels, and speed of soil movement. The added water flow from the lack of absorption within burn areas can cause the levels of saturation to quickly increase for soils below the burn zones, regardless of the strength of the storm. Though according to the USGS's report on Post-Fire Debris Flow Hazards, the stronger and shorter duration storms have the potential to do the most harm. In order to better monitor the saturation levels in the soil along these target locations of the Angeles National Forest, the USGS has embedded water saturation sensors in the soil. These sensors upload information about the change in saturation in order to be aware of rapidly changing situations.

I have attempted to address these target locations with my GIS maps. The first map indicates the complete burn area of the Station Fire as of September 2nd, 2009. I have complimented this data with a DEM, Digital Elevation Model, of the area as well as county names and boundaries to better orient the data. The second map illustrates the significant relationship between rainfall intensity and elevation. As stated, the importance between these two factors is clear and the overlay analysis can emphasize the target areas. The rainfall data is a compilation of 24 hour periods over a series of 50 yrs. This information becomes an averaged value of rainfall over the 50 year period, indicating a trend of heavier rainfall intensity at higher altitude. This trend is evidence for orographic lifting caused by the increase of moist air in reference to the mountains increase in altitude. An indicator on the map of this trend would be the areas of higher elevation receiving the highest rainfall intensity.

My third map, Slope Map, stands to serve as an indicator of extreme slope that could result in added gravitation force on the saturated soil. As mentioned, the gravitational forces caused by steep slopes can also contribute greatly to slides. In conjunction, these two maps can offer a very insightful view into potential land, mud, or debris flow locations.


Los Angeles County. "GIS Data." Los Angeles County Enterprise GIS. WordPress. 22 November 2009. <http://gis.lacounty.gov/eGIS/?page_id=117>.

U.S. Forest Service. "Post Fire Watershed Rehabilitation Activities." Inci Web - Incident Information System. 26 September 2009. U.S. Forest Service. 22 November 2009. < http://www.inciweb.org/incident/article/9512/ >.

Council for Geoscience. "Landslides and Slope Instability." Council for Geoscience. 14 March 2009. The Collective Advisory (TCA). 22 November 2009. <http://www.geoscience.org.za/index.php?option=com_content&task=view&id=996&Itemid=434&limit=1&limitstart=4>.

USGS. "Emergency Assessment of Postfire Debris-Flow Hazards for the 2009 Station Fire, San Gabriel Mountains, Southern California." 2009. 11 November 2009. <http://www.thecvcouncil.com/sitebuildercontent/sitebuilderfiles/USGS_report.pdf>.

USGS. "2009 Station Fire, Dunsmore Canyon, Glendale California." USGS - Science for changing the world. 13 October 2009. U.S. Department of the Interior. 11 November 2009. <http://landslides.usgs.gov/monitoring/dunsmore/>.

Lab 6: DEMs in ArcGIS

Shaded relief model (color-ramped DEM) layered
over the hillshade model of the Locaiton


Slope Map of Location


Aspect Map of Location


3D Image of Location


My selection area can be found in the Wasatch Mountains within north-eastern Utah. The dramatic changes in elevation drew me to this location. My goal was to locate an area that had peaks near areas of significantly lower altitude flats. This is well demonstrated in the 3D model of the area selected. The relevant metadata has been provided below.


NED_97153813

Datum: D_North_American_1983

Extent

* Top = 40.6441666662
* Left = -111.774999999
* Right = -111.251944444
* Bottom = 40.4241666662

Spatial Reference = GCS_North_American_1983

Lab 5: Projections in ArcGIS

Conformal Map Projections


Equal Area Map Projections


Equidistant Map Projections


The process of accurately transforming the spherical shape to flat surface, while preserving shape, size, distance, and area, has baffled cartographers and mathematicians a like for centuries. Since it is not possible to perfectly transform all points on a sphere to a flat surface while preserving all aspects of the image, various methods have been developed to accurately preserve characteristics of the sphere. These methods are called Map projections. These projections, named projections because early forms were created by projecting light from the inside of a sphere, are tools to create accurate flat maps based on the spherical earth. Since carrying a globe, or globes for that matter, around with you is not an option, projections have been the key in creating accurate flat maps. Projections are only able to preserve a number of spatial characteristics while no one projection can preserve them all at once. Three main classifications of map projections are the Conformal, Equidistant, and Equal Area projections. Each of these projections has its own advantages and disadvantages which are clearly displayed through the maps above.

These three projection categories, Conformal, Equidistant, and Equal Area, each have their own unique advantages. Conformal maps allow for shape to be preserved while making longitudinal and latitudinal gridlines to intersect at right angles. These examples of conformal maps can be seen in the Mercator and Gall Stereographic maps above. Equal Area maps preserve area as suggested by their name. The whole of the Equal Area map has the same equivalent area as the Earth as a whole. This element of Equal Area projections is well illustrated by the Mollweide projection map shown above. Equidistant maps show true distances along certain designated lines or from the center of the projection outward (or visa versa) but not between points that are not near the center. The Equidistant Conic projection above shows how true distance from Africa to Australia could not be easily measured using this map. These map projection categories have their key uses but also could be the wrong choice for certain location data depending on the elements of interest.

Though one category may work very well in one instance, it is certainly not guaranteed to work well next time. Conformal maps, though very good at preserving angles between gridlines, distort sizes of areas significantly. This is well demonstrated by the size of Antarctica in the Mercator projection above. Equal Area maps also have disadvantages in contrast with their ability to preserve area well. Equal Area maps can never offer the preservation of gridline angles while still sustaining accurate area. As shown above when comparing the Mercator projection to the Equal Area projections, you can see how the gridlines look nothing alike. Equidistant projections have trouble, as mentioned before, with measuring distances of locations outside of the center, or along the lines, designated. Another disadvantage to these types of maps is that they can never offer true distances while still preserving equal areas. This is illustrated well by the distortion in area within the Plate Carree projection above. These types of disadvantages come with all projections and are a necessary evil to properly presenting map data.

Map projections are a very important concept to be understood when working with or even reading any maps. This knowledge allows the map observer and creator to better understand how to decipher and construct accurate features. This understanding of both advantages and disadvantages to projections allows for a better realization of which projection is the best and most accurate choice for a two dimensional map.

Lab 4: Introducing ArcMap

ArcGIS is a very powerful tool for understanding geographical information. The introductory tutorial illustrated the great potential and difficulties that the revolutionary software holds. I enjoyed my overall experience with the program despite the moments of uncertainty. In the process of completing the tutorial I enjoyed many opportunities to put the knowledge learned from class lectures into action and better understand the complexities of the software. I found ArcGIS to have great potential within its capabilities to manipulate data while still having some pitfalls for new users.

The benefits of the ArcGIS software are wide ranging. The software’s overall attention to detail when dealing with attribute tables, beautification of the visual aspects, and organization of the data groups is very impressive. The user interface of the program is well designed to quickly negotiate general processes. This quality construction of the software allows the user to make quick and effective use of the many tools available within the program’s inner workings. Organization of data tables through joining data groups was very helpful, in addition to the potential to construct formulas for calculation within charts and graphs. Though these great benefits allow the user to control large quantities of tools, the difficulties for new users abound.

The tremendous benefits that ArcGIS offers to its users can pose severe complications for those new to the program. The advantages of having access to all levels of detail can also hold a steep learning curve. Complications can quickly arise when the user of the software is not extremely focused. One wrong click or box unchecked can set the new user back precious time. Yet, I believe these moments of confusion are only temporary for the new user who does not fully understand the methods of the program. With time and experience the benefits will out-weight the difficulties and simply leave an invaluable tool for the geographer.

Though difficulties loom around the use of the powerful ArcGIS program, I look forward to better understand its features and tools. I hope future labs will help me to better understand the techniques of using ArcGIS so as to lessen the difficulties of the new user. Though the tutorial was very helpful, I look forward to more independent research and development of maps.

Lab 3: Neogeography

Interactive Star Map

The techniques in creating a neogeographic map are fraught with pitfalls. Though the wide spread access and potential for mass contribution to the field of geography is great, the road to making a complicated dynamic map is paved with inaccuracy, in-efficiency, and technological complications. The process of creating my interactive star map started by using data provided on a local celebrity address website (http://www.hollywoodusa.co.uk/celebrity-homes.htm#B). Though the accuracy of these addresses are unknown, and with no way to authenticate any star's address if found, I settled on the impressive comprehensive nature of the data set. By importing this list of data into an excel spreadsheet I was able to achieve a format that would be geocode compatible. By accessing a free geocode website (http://www.batchgeocode.com/) that accepted .xls files, I was able to convert raw text addresses into geocoded locations. A group of addresses were lost in this process due to the formatting of the addresses and the website's algorithm not recognizing the locations. Geocoding the wrong locations to some of the data also took place. This was evident by some locations displayed outside of the US. By using Google Earth to convert this geocoded file to a more widely accepted format (.KML) I was able to import the data directly into Google My Maps. Now that I had my geocoded locations on a map, I geoparsed the addresses and geotagged videos to tell something about the mapped celebrities.

These common processes, though full of inadequacies, yielded a comprehensive map for the public's enjoyment. And although locations were lost through the geocoding process, the remaining addresses should still be fairly accurate. Also, given higher quality and properly formatted base data, this process could become even more efficient. This map could still offer benefits to the public even if the overall accuracy is not up to government requirements. These are the types of advantages and disadvantages in creating complex neogeographic style maps.


(If using Firefox, click "View Interactive Star Map in a larger map". Clicking on the locations within the embedded map will freeze the browser due to the geocoded media. This is a Firefox flaw, Internet Explorer works fine.)

View Interactive Star Map in a larger map

Lab 2: Topographic Map of Beverly Hills

1. What is the name of the quadrangle?

The name of the quadrangle is Beverly Hills Quadrangle.

2. What are the names of the adjacent quadrangles?

The names of the adjacent quadrangles, starting from the top left corner and listing in clockwise order, Canoga Park, Van Nuys, Burbank, Topanga, Hollywood, nothing noted in bottom left corner, Venice, Inglewood.

3. When was the quadrangle first created?

The quadrangle was first created in 1966. As noted on the map as “Topography compiled 1966”.

4. What datum was used to create your map?

The datum used to create the Beverly Hills Quadrangle is the North American Datum of 1927 and later updated with the North American Datum of 1983.

5. What is the scale of the map?

The scale of the map is 1:24,000 which is fairly standard for 7.5 minute topographical maps.

6. At the above scale, answer the following:

a) 5 centimeters on the map is equivalent to how many meters on the ground?

5 centimeters on the map is equivalent to 1200 meters on the ground due to the scale of 1:24,000. 5 centimeters on the map is equivalent to 120,000 centimeters on the ground. Then by taking those centimeters and converting them to meters through the conversion of 1m = 100cm you get 120,000/100 = 1200 meters.

b) 5 inches on the map is equivalent to how many miles on the ground?

The same technique follows for this question. 5 inches on the map = 120,000 inches on the ground with consideration to the maps scale. Dividing those inches by the number of inches in a mile gives you the amount of miles on the ground. 120,000/63,360 = 1.8939 miles.

c) one mile on the ground is equivalent to how many inches on the map?

This is similar to the last two questions but instead working backward. One mile on the ground is 63,360 inches. By taking these inches and dividing the scale of the map you can get the number of inches necessary to find one mile on the ground. 63,360/24,000 = 2.64 inches of measure on the map equals one mile on the ground.

d) three kilometers on the ground is equivalent to how many centimeters on the map?

This question can be solved the same as the last. Three kilometers on the ground is equivalent to 300,000 centimeters (also on the ground). Take those centimeters and divide them by the scale of 24,000. 300,000/24,000 = 12.5 centimeters of measure on the map to equal 3 kilometers on the ground.

7. What is the contour interval on your map?

The contour interval for this map is 20 feet.

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

a) the Public Affairs Building;

34.08388ºN, 118.43749ºW
34º04’62’’N, 118º26’15’’W

b) the tip of Santa Monica pier;

34.00778ºN, 118.5ºW
34º00’28’’N, 118º30’00’’W

c) the Upper Franklin Canyon Reservoir;

34.1031ºN, 118.4231ºW
34º06’11’’N, 118º24’53’’W

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

a) Greystone Mansion (in Greystone Park);

560ft or 170.68m

b) Woodlawn Cemetery;

140ft or 42.67m

c) Crestwood Hills Park;

725ft or 221m

10. What is the UTM zone of the map?

Zone 11 is the UTM zone of the map.

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

Zone 11, Easting 3615000, Northing 3763000

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

1km x 1km = 1,000,000 square meters

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 as a graphic in your blog.



14. What is the magnetic declination of the map?

The magnetic declination of this map is 14º.

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

The water flows North to South.

16. Crop out (i.e., cut and paste) UCLA from the map and include it as a graphic on your blog.

Lab 1: 3 Maps

Map 1: Projected Global Water Scarcity, 2025

This world map was located through the link in Week 2: Map Anatomy and is located within the Perry-Castañeda Library Map Collection on the University of Texas' website. This is a thematic map showing what water resources and allocation might be like globally in 2025. The map also gives detailed reasons for why these locations have the projected water issues and what percent of water is being allocated for human purposes. The theme of water scarcity within this map stuck me as extremely relevant. Learning about Los Angeles' water scarcity issues of today worries many people, including myself, about how sustainable it will be tomorrow. This map illustrates other locations, like Los Angeles, that also will be experiencing extreme water scarcity in 2025.

(http://www.lib.utexas.edu/maps/world_maps/water_scarcity_2025.jpg)



Map 2: Landsat Station Fire

I browsed the Landsat Missions section on the USGS site to locate this map of the Station Fire in Los Angeles. This Landsat image has been falsely colored to emphasize the areas of interest. The result is quite stunning. The image shows the areas burned in orange and the areas burning at the time of acqusition in the bright multicolor areas. This picture was taken in the first stages of the Station Fire on August 30, 2009 and in turn only shows a portion of the actual area burned. The quality, coloring, and locality of the image drew me to it. The burnt, stilling burning and smoke filled skys are well emphasized by the quality and coloring of the image.

(http://landsat.usgs.gov/images/gallery/143_L.jpg)



Map 3: Wytfliet's Map of the World, 1598

This map was also located at Perry-Castañeda Library Map Collection on the University of Texas website. This map would be categorized as a historical map and offers a unique view of the world. I would assume the character at the bottom of the map would be the Greek mythological figure of Atlas, whose name became synonymous with collections of maps. This ornamental map of the renaissance abstracts the size of the world's land masses potentially due to the lack of exploration accomplished or lack of accurate methods for approximating size. Historical maps offer great interest due to their beauty and for the lessons they hold for modern cartographers.

(http://www.lib.utexas.edu/maps/historical/wytfliets_world_1598.jpg)