Lab#8

Lab#7

        The first map is a representation of Black alone population in counties by percent. This data came from the 2000 census report. For this map, I chose shades of purple to show the distribution of black population throughout the United States. The legend showed a range of percent starting at 0 and topping at 86. The darker the shade the higher the population. For example,  counties with 0 to 3% Blacks are lighter in shade, which spreads over most Northern states. A darker shade would mean higher percent, so the darkest purple in the legend would represent 59 to 86% Black population. There is an overall a higher percent of Blacks in the Southern-east states, such as Alabama and Georgia.Then there is also a small cluster of high percentage of Blacks in California and states that border it.
         For the second map showing Asian alone population in counties by percent, I used shades of green. From the display, there isn't a significant pattern of Asian distribution by counties. The range of Asian along population starts at 0 and up to 46%. There is good percentage, ranging 9 to 46%, of Asian population residing near the Pacific Coast, mostly in the state of California. Other than that, there is scattering of low and high Asian population throughout the United States.
         The last map showed Other Race alone population distribution by counties in percent. The Other Race will be categorized with Hispanics because Black, Asian, White, Native American, etc had their own set of data. In this map, we can see a prevailing trend of high concentration of Hispanics along the Southern-west states, such as California, New Mexican, and Texas. This highly concentrated population can range from 11 to 39%.
          In this exercise, I enjoyed the free range of colors we can use to display our maps. The legend are especially helpful to inform the readers of where has the higher concentration of population. The coloration eases our visual understanding. The actual display of a map is much easier to comprehend the data than just by reading the tables. Thematic maps also allow us to make observation of areas that have the most or least of a certain population. We also can point out clusters and trends of population. Ultimately, colored maps are aesthetically pleasing unlike boring old numbers. To further elaborate on my maps, I include a legend, a scale bar, and a north arrow to help orient all my audience the same way.
         With the help ArcGIS, I can join shape files with tables thus making the maps appearing the way they are. In addition, the preset color ramp saved me time from choosing a color. The different way to sort data to make it look less messy and more presentable. For example, applying the same map projection to all layers to make the look reasonable. Throughout the weeks of doing labs, I gain a better understanding of how to combine data and join table to make maps meaningful. Each lab is mind refreshing and increase my efficiency in ArcGIS usage.

Lab #6

  

Extent:
Top:36.3199999992
Left:-112.341666666
Right:-111.721944444
Bottom:35.9616666659

Geographic Coordinate System:
GCS_North_American_1983
D_North_American_1983

    For this exercise, I pick a section of the Grand Canyon and did elevation analysis on it. Grand Canyon is a national park located in Arizona. This beautiful landscape runs 277 miles long, 18 miles wide, and up to 1 mile deep. It was believed that the land was slowly eroded and carved through by a river, what is now known as the Colorado River. A reason for having low elevations such as seen in the slope data. The deepest point of the canyon is over 6000 feet, while its highest elevation is at 8800. There are huge difference between its lowest and highest points of elevation is due to the river erosion and uplifting. I find this place to be noteworthy and interesting to do a digital elevation model on it because of its elevation differences. The 3D map was especially striking to me since I got a get a three-dimensional feel to the difference of the elevations as I move and rotate the map around.

Lab #5

 

     

     In this week’s lab, I got to test out different map projections. Map projections are putting a three dimensional earth on a two dimensional surface. Since there is no perfect representation of the 3D earth, we can only get different types of map projections for different purposes. Like said, all map projections can preserve certain properties and distort others. In this exercise, I get to generate two maps in each of the three major map projections categories: conformal, equidistant, and equal area.

       Conformal maps have its unique set of properties. Conformal maps preserve angles and direction but distorts shape. This meant the angle between any two lines on the sphere must be the same between their projected counterparts on the map and scale at any point must be the same in all directions. Conformal maps are mostly used for local purposes and seldom for world maps since angles can only be preserved to a certain extent, thus shape or area are greatly distorted when the area it trying to represent is too big. In Mercator, we can see that Antarctica is greatly stretched and looks as it got equal landmass as to all the combined continents. In Stereographic, instead of looking like a planar as in Mercator, it’s spherical and it looks like the upper border of Canada can almost touch the upper border of Russia.

        Equidistant projections, as suggested by its name, are maps that preserve distance. Such projection maintains scale along one or more lines, or from one or two points to all other points on the map. That said, we could measure the distance between two points more accurately than the other two projections, conformal and equal area. Equidistant projections are very important in aviation purposes; we would want to know the accurate distance when we are traveling. In comparison, we would travel 2,000 more miles using the Mercator map than if we were using Azimuthal Equidistant! Even though such projection is very effective in preserving distance, it distorts area like conformal projections. As seen in Equidistant Conic, we can see that Antarctica is distorted in such a way that it appears to stretch across the entire bottom globe.

          Finally, equal area projections, the last of the three major projections, preserve area. Equal area maps are especially useful when comparing land area between places. For example, Antarctica looks more appropriate in size in both maps, Eckert VI and Mollweide. Even though it has advantage in maintaining area, it distorts shape. It become evident when we approach the poles; the shape of the poles can be flattened out as in Eckert VI or squeezed in Mollweide. 
            I had a lot of fun exploring different map projections and compare them to each other. This exercise teaches the different purposes of each map projections. Though each map projections have its own special preservative properties, they can also introduce distortion. Thus, I have to be extra careful to figure out what exactly I am looking at and what information I can draw from it. It’s also an important knowledge to have because now I know the usage of each map projections and save it for future references.

lab#4

     During the pass two weeks, I had the opportunity to get a first hand experience with the software application, ArcMap. Throughout the different exercises, I found out many pros and cons with using such program. ArcMap, created by ESRI, is a fantastic piece of technology that allowed geographers to manipulate data in such a way that can help ease the understanding for map users.

      I found a lot of potentials to ArcGIS. One advantage I found throughout the exercises is that I can easily go back and forth between layers of data. Data can be copied and extracted so I can edit it without overwriting previous data layer. In addition to data replication, I also found data organizing and managing is really easy thus making data analysis easier. I was very happy to have a wide range of tools to toggle my map and the ability to change content on the map easily. Another advantage to ArcGIS is the aid of visual analysis. Statistics can be viewed visually (i.e. filling areas of different colors to represent differences). I am very impressed with how it can handle complex and high volume of data while displaying it in a way that someone who doesn’t have good map knowledge can comprehend what the data is trying to say. Lastly, the maps that ArcGIS creates are aesthetically pleasing because the abundant range of colors, shapes, symbols, and orientations allowed users to make beautiful maps.

     As good as ArcGIS can be, I also found pitfalls along the way. It’s not the most user- friendly program that I have encountered due to the fact that it requires time, precision, and saving the data frequently. The first problem I had immediately with ArcGIS is that saving the data is extremely important because if I forget to save frequently and it accidentally freezes on me, I can potentially lose work that aren’t saved. Since it’s my first time access to this program, I spend a lot of time reading the tutorial.pdf to make sure I am doing the right thing before I can proceed. Sometimes, the tutorial can lead to frustration because some of its information isn’t orientated the same way in newer version of ArcGIS. With the time consumption, it requires a lot of patience. Patience is especially needed when inputting figures and commands because even when one symbol is typed wrong, the data won’t come out right or, worse yet, wouldn’t let you proceed to the next step because it required previous information to be entered correctly.

        ArcGIS can definitely improve with its user features to make it a better, faster, and more user-friendly. I am evermore fascinated by its technological progression with the fast upgrades that allow even wider range of user access. But, it can also led to frustration because such program requires a lot of time to understand its features, tools, and usage. In a way, users are required to use such program daily and very frequently in order to adapt to its functions. After the exercises, I already forgot some of the functions it can perform because it’s so vast. Despite the pitfalls, I believe ArcGIS got a lot more in its package and I will learn more about it with later labs.

Lab#3

View A Trip to New York in a larger map




          Neogeography opens up a wide array of tools that allow an easier access to gathering and compiling information for geographers to use. It is also a public good where most, if not all, people have access to. With the help of Web 2.0, people can create their own personal maps that's centered on places and objects that deems interesting and/or important to that particular individual. The creator can also allow friends and people to have public access to share and learn about a place that the creator have been to. For example, I used Google Map, an example of a mash-up tool, to help create my own personal map that track a place that I visited this Winter. Google Map made locating the place easier and have mini-trackers to pinpoint places I have been to. This tool also allowed me to incorporate descriptions, pictures, and videos to further illustrate my experience from the trip.
          There are also con's about having such an advance technology that allowed public access. There can be invasion of privacy because almost all that have Internet access can pull up information on people's address and location. It can be a very useful tool if used right, but if it falls on the wrong hands, people can plan attacks. Another shortfall could be the erroneous usage of information where the public have open access to. This is a question of authority and accountability because the public is most likely don't know where the source of information coming from. Also, it can greatly skew the point of view of the public to suit what the creator intended.
      

Lab#2

1.     Beverly Hills

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

3.     1966

4.     National Geodetic Vertical Datum of 1929, North American Datum 1927 and 1983

5.     1:24000

6.     a. 1219.2 meters

b. 1.894 miles

c. 2.64 inches

d. 12.5 cm

        7. 20 feet

        8. a.  118°26’30” W and 34°4’30” N      118.442° W and 34.075° N

            b. 118°30’30” W and 34°0’30” N    118.508° W and 34.008° N

            c. 118°24’30” W and 34°6’30” N    118.408° W and 34.108° N

      9. a.  560 feet, 170.69 meters

          b.  140 feet, 42.67 meters

          c.  620 feet, 188.98 meters

     10.  Zone 11

     11.  37,630,000 ft. N and 3, 615,000 ft. E

     12. 1,000,000 square meters

     13.

     

     14.  14° E

     15.  The stream flows South

     16.