Lab 5

Mercator, type: conformal

Distance between DC and Kabul= 10,173 miles    

 

Gall Stereographic, type: conformal

Distance between Kabul and Washignton D.C.= 7,119 miles

Cylindrical Equal Area, type: equal area

Distance between Kabul and Washington D.C.= 10,147 miles

Bonne, type: equal area

Distance Between Kabul and Washington D.C.= 6,753 miles

Equidistant Cylindrical, type: equidistant

Distance Between Kabul and Washington D.C.= 5,061 miles

Equidistant Conic, type: equidistant

Distance between Kabul and Washington D.C.= 6 942 miles

         Map projections are a very important concept to understand when studying geography.  When most people look at maps they do not understand how it is created.  People often do not realize that there are different ways to project maps, most people are just used to one type of map and assume that there is only one correct way to represent the world.  However making maps
that accurately represent the world is much more complex then it may seem.
         The main challenge in creating maps that accurately represent the world is due to the fact the it requires representing a three dimensional world in only two dimensions. Because the world is spherical many problems arise when we try to create a flat, two dimensional representation of it.  The process of transforming the 3D world into a flat map is called map projection.  There are several ways to do map projections, each have their advantages and disadvantages.
         Each type of map projection preserves certain features and distorts others.  This is because it is not possible to create a completely accurate two dimensional representation of a three dimensional space.  There are some maps that accurately represent area, or distance, but usually when one feature is preserved it is at the expense of others.  So when creating maps it is important to consider what it will be used for a make sure that the features relevant to the use are preserved.  For example, when creating a map of land use area is probably an important feature to preserve.
         There are three main types of map projections: conformal, equidistant and equal area. Conformal projections preserve shapes and angles, so that things like shapes of the continents are preserved, such as in map the Mercator and Gall Stereographic maps above. Equidistant projections, on the other hand, preserve distance, which is important for taking accurate measurements.  However this comes at the expense of other features, as you can see
in the equidistant conic and equidistant cylindrical projections above.  And equal area projections preserve area, which is also important for certain purposes, but distorts shapes and distance, making it less commonly used for everyday purposes.  We can see this in the Bonne and cylindrical equal area maps above, where the shapes and distances are distorted. However, not all maps are one of these types, some are even a combination.

Week 8 Lab

This map shows the distribution of African Americans in the continental united states. The data used in the map comes from the 2000 census.  It is measured by asking people their race on a questionnaire, which means that this measure is completely based on how people chose to identity themselves. The map is broken down by county, each county is colored based on the percentage of the residents of that county that identified themselves as black on the census. The darkest blue colors represent the places with the highest percentages of blacks and the light yellow represents those places with the lowest percentages.  The maps shows that the areas that have the highest percentages of blacks are all clustered in the south.  Then in the rest of the county the areas with the next highest percentages are mostly on the coasts, and the middle of the county had very low percentages.

In this map we can see the distribution of the Asian population in the United States. It is also based on the data from the 2000 census.  The colors on this map represent the same thing as the map of blacks.  However, the distribution of Asians throughout the country is quite different than that of blacks.  The areas with the highest percentages of Asians are mostly on the West coast.  There are also some scattered areas with higher Asian populations on the east coast.  In comparisons to the map of blacks there are less areas with very low Asian populations than there are with very low black populations.

This map shows the same type of data as the ones above, except for this one shows the percentage of the population that identified themselves as some other race on the census. This category is vague and can mean a number of things, it is all about how people chose to identify themselves. On this map, the areas with the highest percentage of people who identify as some other race are clustered on the west coast and in the southwest. Then the rest of the country has moderate to low levels of people identifying as some other race.  

This data is very informative and interesting.  However, it is important to keep in mind the way that is has certain limitations.  Although the census data is good it is not perfect, it can never count every single person, so we always need to consider the fact that there is some margin for error.  An additional factor to remember is that all of the data is based on how people self identify, so people who may be considered the same race by others may consider themselves something else on the census.  These maps give a good visual representation of the distribution of people of various races thought out the continental United States.

Week 7 lab

 

 

 

            These maps show a region of Los Angeles County.  Each one shows a different aspect of this area.  The extent information for these maps is from 34.34 decimal degrees to 34.27 decimal degrees northing and -119.24 decimal degrees to -119.17 decimal degrees easting.  And the geographic coordinate system location is top:3802085, left: 294351, right: 300261, bottom: 3794683, and the Datum used is the North American Datum of 1983 As the maps show this area has a variety of elevation changes.  There are several peaks and valleys, as is reflected by the color change in all three maps.

Lab 4

Using the ArcMap program took some getting used to, but overall it is pretty
user friendly.   As with any computer program, getting used to the basic
interface of the software takes a little time, but once I figured that outW
most of it was straightforward.  The menus are pretty self explanatory, such
as file, edit, view, layout, etc.  Especially because many of them are
similar to the menus in other windows programs I found it easy enough to get
used to these menus.

For me one of the challenges with ArcMap is getting used to using the
windows operating system.  Although I have used it a lot in the past, I
currently use a Mac for my personal computer.  I have become accustomed to
it and started to like it much better, so it can be difficult to switch back
to Windows.  There is another challenge for me when working with ArcMap; I
am currently taking another class that requires computer mapping right now,
but it uses a different program, so it can be confusing for me to switch
back and forth between the two.  The other class is urban sociology, and we
use a program called MapInfo to map demographic data.  Because I had to
learn both these programs around the same time and use them simultaneously,
it was at times difficult for me to keep them straight, especially when
preforming similar functions.

When it came to the latter exercises, which were more complex I experienced
a little more difficulty.  This is when the step by step instructions came
in handy.  At first it took more time because I had to read through the
instructions completely then look at the screen and locate what they were
talking about, then refer back to the instructions in order to complete each
step.  But after doing the exercises a few times I became more used to the
software, and did not have to consult the instructions for each step
anymore.

I think the ArcMap software takes a little practice to learn, but for most
people who have experience with computers, and Windows, it shouldn’t be too
difficult to learn the basics.  However, to make complex maps, such as ones
sophisticated enough for government use must take much more training and
time.  The level of detail in these types of maps requires a lot of work in
a program like ArcMap.  For basic purposes Arc Map is a good program, that
is not too difficult to learn how to use.  I think that GIS has a great deal
of potential because the software is accessible to the average person.  I
think it will become more widely used in the future.

Lab 3

      For my neogeography map I decided to create a map showing a road trip from Southern California to Northern California.  This is a road trip that I have done many times to get from school at UCLA back to my hometown in Northern California.  Over the course of these many trips I have found a lot of good places to stop along the way.  The route used on this map follows highway 101.  Although highway 5 is a little bit faster, the 101 is much more scenic, so if you have a little extra time this is a great route to take.  Along the route I have indicated several points of interest.  There are fun places to stop, including restaurants, shopping, beaches and tourist attractions.  This route and the points of interest indicated along it make for a great road trip if you need to travel between Los Angeles and the San Francisco Bay Area.

      Making this map wasn’t too hard overall.  I struggled with a few problems, but in general google maps was fairly easy to work with.  Learning how to click and drag to create lines took a little practice but came pretty easily.  I did run into one more major issue.  When I first created my map I used the “draw a line along roads” feature in google maps, then when I saved my map and came back to it instead of saving the route that I had drawn out google had saved it as straight lines between each point, not following the curves of the highway.  So then I had to redo the lines, this time just using the “draw a line feature” and draw a series a straight lines that followed the curves of the road as closely as possible.  Another  issue I had was at first when I wanted to make a polygon I just outlined it with regular lines, instead of using the “draw a shape” feature, but I realized this eventually and corrected it as well.  So here is the final product of my efforts: 

View So-Cal to Nor-Cal Road Trip in a larger map

Lab 2

1.Beverly Hills, CA

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

3.  1966

4. North American Datum of 1927 and National Geodetic Vertical Datum of 1929

5.  1: 24,000

6.    a) 5x24,000=120,000 or centimeters  1,200 meters

       b) 5x24,000=120,000inches or 1.893 miles

       c)  1/24,000=4.16E-05 or 2.64 inches

       d)  3/24,000=.00125 or 12.5 cm

7.  20 feet

8.  a) easting: 118° 26' 10" or (0.43+0.0028) 118.4328 °   northing: 34° 4' 30 '' or (.067+.0083)              
         34.0753°

    b) easting: 118° 30' or 118.5° northing: 34° 00' 25 '' or 34.0069°
    c) easting: 118° 24' 35'' or  ( 0.4+0.0097 )  118.4097°   northing: 34° 7 ' 40 '' or (0.117+0.01) 34.127°

9.   a) 570 feet, 173.736 meters

      b) 140 feet, 42.672 meters

      c) 700 feet, 213.36

10.  Zone 11

11.  3763 Easting,  361.5 Northing

12.  1 square km or 1000 square meters

13.

14. North 14 degrees

15. From North to  South

16.

Lab 1

This map is from http://mappery.com/map-of/World-Happiness-Map.  It shows the average happiness of people in each country around the world.  The average happiness in each country is categorized into a range and then color coded accordingly. I think it's very interesting to see how happiness varies so dramatically around the world, and there are certain regions that are much happier than others.

This map is from http://psychology.wikia.com/wiki/Developed_countries, it show the average income in each country, broken down and categorized into different ranges, then color coded.  It's interesting because there are very large differences in incomes around the world, and the high income areas tend to be concentrated in the westernized countries.  It is also interesting because there is a strong correlation between the average income in countries and the average happiness; looking at these two maps we can see that the people with more money tend to be happier.

This map is from http://aidwatchers.com/2009/12/world-map-of-remoteness-vs-connectedness-ht-tyler-cowen/.  It shows the connectedness, or remoteness of every region in the world.  The time it takes to travel to a major city is calculated from each point and coded by hours or days.  The darkest colors are the most remote places and the lightest colors are the most urban areas.  Shipping routes are also shown by the blue lines.  I think this map is really interesting because it shows urbanization very clearly, which is an increasingly important factor in the world today.  Also remoteness or connectedness is related to population so this map shows a lot important things.