Lab 8

The map above shows the percentage of Asian population across different counties across the United States. The map was created by layering the data from the 2000 Census over the shapefile of the counties of the United States.   The different colored areas represent different ranges of percentages, which are determined by natural breaks in the data.  The darker the color of the county, the greater the percentage of Asians that reside there.  The west coast has the greatest percentage of Asians,  but there are many areas with pockets of dark blue counties, most noticeably in Texas, Florida, and near the Great Lakes. 

The map above shows the percentages of black people in the different counties across the United States.  It was created by layering black population data over the shapefile of the counties of the United States.  The percentages are divided by the natural breaks from the data, and the darker colors represent greater percentages of blacks.  The population of blacks appears to be highly concentrated in the South, specifically along the Atlantic Coast and along the Gulf of Mexico.  There are also areas with a high population of blacks in Southern California.  It is interesting to note that there are many full states that have very low populations of blacks across all counties. 

The map above shows the percentage of some other race across the counties of the United States.  The map was created by layering the data regarding some other race from the 2000 census over a shapefile of the counties of the United States.  The darker colored counties represent a higher percentage of some other race.  The areas of the highest percentage are in the western United States, and most of them occur in California and Texas.  This makes sense because they are areas known for the diversity of their populations.  Within the Midwest, there are states with very little "some other race" populations.

Overall, this GIS course has been very interesting.  I think that the course material is very valuable and applicable to many different fields and a I am glad that I got at least an initial exposure to it.  However, I do not think I will be continuing with GIS classes, mostly because although I find the field very interesting, I do not feel that I am computer literate enough to pursue a career in the area.  Nonetheless, I did find the labs enjoyable and am glad that I learned a little bit about something new.  

Lab 7

The 2009 California Station fire was one part of the greater California wildfires.  From late July to early November, a series of 63 wildfires burned in California.  Over 336,020 acres were burned, destroying thousands of structures and killing two people.  The largest of these 63 wildfires was the Station Fire, which burned in the Angeles National Forest north of Los Angeles.  The Station Fire burned in late August, and continued burning until October 16th. It was responsible for the death of two firefighters on August 30th.  Cities threatened by the Station Fire included La Canada Flintridge, Glendale, Acton, and Altadena.  By itself, the Station Fire was responsible for the destruction of 160, 577 acres.  

The map directly above shows the temporal projection of the fire from late August to early September.  Each different colored area shows the perimeter of the fire for a specific date.  The map shows the growth of the fire and how it shrank as it was contained.  Many residents filed complaints that the fire was not contained as well as it should have been within the first 48 hours, and this progression shows that in fact, the fire grew dramatically within the first few days. 

The index map shows the area of the fire layered on top of a map of California.  This enables the map user to see where the fires were with respect to the California geography.  This is most helpful for people who are unfamiliar with California or where the county of Los Angeles is in California.  The index map helps create a visualization in a broader context.

The thematic map included shows the temporal projection of the fire, layered on a map of california with all of the major health facilities in the area.  It is interesting ti note that there are numerous health facilities near or just outside the perimeter of the Station Fire. This implies that although there were many facilities available for those affected by the fire, it also was a fire that placed many people and important structures in danger.  In fact, over five dozen homes were destroyed in the fire. 

Geographic information systems have made it possible to create visual representations of the extent of the fire, its perimeter given different dates and times, and the different facilities that it was near and potentially endangered, among other things.  In this particular context, they could potentially aid in better fire fighter responses.  In addition, it could become apparent through GIS what types of geographic areas were more predisposed to being involved in the wildfires that spread through California in 2009.  

References:

http://en.wikipedia.org/wiki/2009_California_wildfires

http://articles.cnn.com/2009-08-31/us/california.wildfires_1_mike-dietrich-firefighters-safety-incident-commander?_s=PM:US

http://blog.flickr.net/en/2009/09/03/station-fire-los-angeles/

http://www.sgvtribune.com/news/ci_16024995

http://www.boston.com/bigpicture/2009/09/wildfires_in_southern_californ.html

Lab 6

Aspect Model

Slope Model

3D Model

Hillshade

The portion of land is the big island of Hawaii.  

Lab 5

Projection: World_Equidistant_Conic
Distance from Kabul to Washington, D.C.: 6,972.48 miles

Projection: World_Equidistant_Cylindrical
Distance: 5,065.05 Miles

Projection: Equal Area Cylindrical
Distance: 10,115.52 Miles

Projection: Sinusoidal (Equal Area)
Distance: 8059.66 Miles

 Projection: Mercator (conformal)
Distance: 6,934.47 miles

Projection: Gall Stereographic (conformal)
Distance: 7,156.45



Different map projections use different ways of projecting the three dimensional world onto a two dimensional surface.  Because of this, every form of map projection is distorted in some way.  Equidistant maps are maps where all points on the map are the same distance from the middle of the projection.  Equal area maps are maps that maintain relative sizes.  Conformal maps are maps that maintain angular relationships and accurate shapes over small areas.  Different types of maps are useful for different purposes.  Equidistant maps and conformal maps are used for navigation, while equal area maps are used for mapping distributions.  In addition, a cylinder, cone, or plane may be used to translate the three dimensional sphere onto a two dimensional surface.  This is done by using a shape that can be flattened out.

As shown by the maps above, different map projections account for the same distance differently.  The distance from Washington, D.C. to Kabul, Afghanistan varies depending on what projection is used.  The purpose of the projection must be considered when deciding which projection is most useful.  For example, the equidistant conic projection is best used for navigation, because distances are equal.  However, it provides very little detail, so it would potentially be more useful for flight path navigation versus navigating a very specific area.  The equidistant cylindrical map preserves also preserves distance but looks completely different than the conic version.  Shape and area are presented differently, and areas that are larger are not necessarily shown true to size.  It is also interesting to note that the distances vary even for two equidistant maps.

The cylindrical equal area map preserves area but distance and shape are distorted, and it is clear that european region is distorted in terms of shape.  The sinusoidal equal area map shows the entire globe and is better for representing information on a larger scale.  The conformal maps presented look similar, and the distance from Washington D.C. and Kabul on these two maps are very close.

Having different ways of projecting the 3D world onto a 2D surface is useful for different mapping purposes.  However, it is problematic because someone who uses a map may be misinformed if they are not aware of the projection they are using.  In addition, it creates confusion as to what is the "real" distance, shape, or area.

Lab 4

GIS has a lot of potential, in addition to many potential pitfalls.  The potential of GIS is the exploration of different geographic interactions.  For example, GIS has made it possible for businesses to find where things such as marketing, resources, and customers are most effective and/or readily available.  In addition, it helps policy-makers find where voters are active or donating money.  In addition, GIS links data and maps, and it  helps create a visual aid for various different types of information.  From showing where the most McDonald's are located in the US to where the most casualties in Iraq are, GIS enables the user to see data in a geospatial context. 

GIS has also allowed for the expansion of the types of information given in maps.  Topological maps include data about elevations in addition to the location of places, freeways, and waterways.  In addition geocoding allows finding locations based on ZIP codes or addresses.  Recently GIS has become available in cars and on mobile devices, allowing users to be able to access information about their location both nominally and absolutely almost any time they want to.  Furthermore, mapping things such as resource depletion and the occurence of crimes can help people live better and safer lives. 

The potential pitfalls of GIS include issues with privacy.  For example, the fundrace maps shown in lecture allow users to access the name, address, occupation, and dollar amount of political donations.  For more controversial issues such as California's prop 8, this type of information could lead to danger for the people featured in the map.  The growth of neogeography with software such as GoogleMaps, anybody can make a map of anything they want, and the validity of the information is hard to verify.  In addition, copyright and privacy issues can also arise.

Furthermore, as we know more and more about what is around us, we realize how little we know (the paradox of context).  We also like to know about others and the world around us but would rather others not know the same information about us (the problem of transparency).  These two issues are not easily reconciled by GIS, because it expands and visually represents the amount of information we have about the world around us.  It is an important tool for businesses, agriculture, education, and many other disciplines, but as with all of technology, the source and the information presented should be carefully looked at to ensure validity and protection of privacy. 

Lab 3

View La Liga Stadium Locations and Names in a larger map


http://maps.google.com/maps/ms?ie=UTF8&hl=en&msa=0&msid=101072126278466890908.0004926e6705ae6777e1f&ll=39.546412,-3.922119&spn=6.10677,9.876709&z=7

The Google Map I created shows the teams of the Spanish futbol league, La Liga. In this dynamic map, each icon represents a Spanish team, and shows the city the team plays in.  In the caption for each icon, the name of the stadium the team plays at is included.  There is a point on the map indicating Barcelona, because they are the defending La Liga champions.  There is also a line connecting Madrid and Barcelona, because they are the two major contenders for the La Liga championship, and are historically the strongest teams in the league.  There is a video link embedded for the Barcelona point, showing a video tour of Camp Nou (the video is shown as a link because the video was not embedding properly).  There is also an embedded image of the Real Madrid stadium under the icon that represents Real Madrid.

Pitfalls and potential consequences of neogeography include misinformation or potentially harmful information being presented.  Similar to the example given in class, if there are dynamic maps with the names of people who give political donations, it could lead to hate crimes or harassment.  In addition, when people make their own maps they can provide intentional misinformation.  My own map gives a good schematic of where each team plays, and locates them by the city they  play in, and names the stadium.  This provides someone with enough information to look up on their own the stadium and find its exact address, cost of tickets to games, etc.  The icons on the map do not show the stadium at its exact street location, because that is not the general purpose of the map, however, some may find that more helpful.  Nonetheless, neogeography has the potential to increase the information we have available immensely, as long as the user is aware and cognizant of the information being presented.

Lab 2

1. The name of the quadrangle is Beverly Hills.
2.  The names of the adjacent quadrangles are Van Nuys,Topanga, Hollywood, and Venice.
3. The first quadrangle was created in 1879.
4. The datum used to create this map includes: imagery taken in 1978, selected hydrographic data from NOS/NOAA chart in 1964, projection and 1000-meter grid, North American Datum of 1927 and 1983, California coordinate system of 1927, and Universal Transverse Mercator, zone 11. 
5. The scale of the map is 1:24,000.
6.  a. 120 Meters b. 1.89 miles c. 2.64 inches d. 12.5 centimeters
7. The contour interval is 20 feet.
8. a. Public Affairs Building - 118 degrees 26 minutes (longitude) 34 degrees 2 minutes 30 seconds (latitude) in degrees: 118.433 and 34.0367
b. tip of Santa Monica pier - 118 degrees 30 minutes 10 seconds (longitude)  34 degrees 0 minutes 30 seconds (latitude) in degrees: 118.503 and 34. 0083
c. upper Franklin Canyon Resevoir - 118 degrees 25 minutes 10 seconds (longitude) 34 degrees 6 minutes (latitude) 118.419 and 34.1
9. a. 580 feet b. 140 feet c. 700 feet
10. zone 11
11. 11S 0361250 3763050
12. 1000000 square meters
13.

14. The magnetic declination of the map is 14 degrees.
15. west to east
16.
.