Summary Map 1:

It's easy to find out that the majority of population of Asian locates in west coast, especially California. This can also been proved by the large proportion of asian students in our school. I think this situation can be explained by the large immigration hundreds of years ago. Besides, there're also a relatively high percentage of Asian in the northeast coast around MA. However, Asians in middle of the U.S. is very rare. Many of them are even lower than 0.5 percent. So we can conclude from this map that the population of Asian cross the U.S. is not equally distributed, and most of them converges to cost of two sides of the nation.

Summary of Map 2:

It's very obvious to detect that the majority of Black population converges to the southeast part of the nation and reduces as it goes northwest. I'm really surprised to see this distribution because I'm not very good at history of Black people. However, this map gives me a really useful information about it. Besides, it's interesting to see that both Asian and Black people are rare in middle of the U.S.

Summary of Map 3:

The majority of population converges to southwest part of the nation, which is opposite to Black population. Maybe it's due to it's close to Mexico?  I'm not pretty sure though. Besides, there are very high percentage of other races along the west coastline, indicating the popularity of immigration oversea. However, it's easy to detect that the distribution is strongly stewed to east, which means only few other races in the east part of nation. 

Conclusion:

    Basically, I can conclude that the majority of Asian, Black and other races converges to coastline around the U.S., it may be due to the large quantity of immigration of labors generations ago. Besides, middle north of the nation has a extremely low percentage of all other races.  Moreover, if we add up the percentage of all three types of picture, we can find that west coast of nation should have the lowest percentage of White in the U.S. And except west coast and middle north part, the variance of other races around nation shouldn't be high or it's equally distributed.

    From this lab assignment, I'm impressed by the power of GIS in analyzing different types of data in a uniform format. It's difficult to detect the relationship of three different data simply from tables. However, GIS provides us a new way to reveal them to public. I met some problem in tutorial part of this lab, but once I got the skill, I finished these three work very fast. So it's not that difficult to popularize this technology to public. It should be useful in the future. 

Lab HW6

Information: 

Top:37.5419444438.        Left:-121.832222222. 

Right:-121.084722222.    Bottom:37.0961111104. 

Datum: D_North_American_1983. 

Comment: 

    It's the Northeast Part of Sunol Regional Wilderness.  It's about 350 miles from our school and very close to San Francisco. From my data I find that it's a not very steep mountain. And I graph 3 2d maps and 1 3d maps to reveal the information I got. The slope map gives us the information of how steepness the mountain is. The aspect map shows the direction of the slope; Hillshade is also a overall description of the mountain. And there's also a 3D map, though lack of statistics, provides an entirely new impression of map and a visualized view of actual world which is pretty interesting. 

3D Map

Lab HW5

The real distance between two cities is 11195600m
 Conformal Projection Map:

Distance:16256949m

Distance: 16347217m

 Equal Area Projection Map:

Distance:12733317m

  

Distance:16277532m

 Equidistant Projection Map:

Distance:10821337m

 

Equatorial Azimuthal Equidistant Projection Distance: 13382251m

    This week's homework is make 6 different projection maps, it seems an easy work because we just follow the same procedure and just switch between different projections that are already stored in ArcGIS.

    However, I really find the importance of the choice of projection from it. Basically, the most obvious different between them is three different types: conformal, equidistant and equal area. I can conclude easily from the measure tool in ArcGIS to tell that with different projection distant between two points may vary significantly. As six projections I chose, the distance between them varies from 10821337m to 16347217m. However, the real distance turns out to be 11195600m and none of six projections above gives the true value(it may be also due to the error in my measure). So that it's hard to have same distance using different projections even they are divided into similar category.

    Besides, it really challenged my impression of map. Because I always using city or road map to find direction, I took for granted that maps look similar and every information in it is accurate. So I was truly surprised when I saw those lovely and rare, for me, projections such as two points equidistant. It's much better to know from lab than ppt in lecture because I can change myself, choose whatever I want and see their information. 

    Moreover, I find within same category, there's still very big difference. their functions are also significantly different. For example, Two Point Equidistant Projection Map and Equatorial Azimuthal Equidistant Projection Map are both equidistant map, but they have very different function. The former is  commonly used in National Geographic Society atlases for maps of Asia, and it sometimes appears in diagrams of air routes, the later is useful for showing airline distances from center point of projection and for seismic and radio work.

    Finally, I can see from those different projection maps that how significant projection is. Different choice of projection can result in totally different map with various functions. And I realize it's still a tricky problem in projection since no single projection can preserve all three types of data. Maybe 3D map can help, but it's still a long way to go because it require a very strong infrastructure, for now, to make it prevalent.