Lab1

 

 

 

Projection	Distance (meters) Seattle to Jacksonville	Distance (meters) San Francisco to Charlotte	Distance (meters) Chicago to Houston
Albers Equal Area Conic	3,843,066	3,510,351	1,553,676
Mercator	4,973,916	4,645,554	1,860,230
Plate Carree	4,917,233	4,640,934	1,589,918
Robinson	3,268,742	3,589,496	1,684,932

---

Q1 : What information does the Source tab provide about the states shapefile?
The Source tab provides information on data type, shapefile location, geometry type (point, polygon, line), presence of z-values, coordinate system, datum, prime meridian, and angular unit.

 

As indicated, the states shapefile is a polygon layer, containing z-values, utilizing the GCS_North_American_1983 coordinate system that corresponds with the Greenwich prime meridian and is measured by degree units.
Q2 : What coordinate system is this layer in? Is it a geographic or projected coordinate system? What is the difference between these two types of coordinate systems?

This layer uses the GCS_North_American_1983 Coordinate system, which is geographic and unprojected. A geographic coordinate system is fundamentally based on a datum that provides a point of reference used for measuring locations on the surface of the earth. In this case, the datum is D_North_American_1983. Locations within a GCS are measured using lines of longitude/latitude, while projections are based on feet/meters for units of measurement. Geographic systems are defined by 3-D data, while map projections are based on 2-D interpretations.

Q3 : Compare the different projections. How does the shape of the continental US change with each projection?
Albers Equal Area Conic:
Because this is a conic projection, the lower 48 shape is defined by the arc that surrounds the North pole. This arc is obvious when examining the northern boundery of the country; with Washington’s most North-Western point lying higher that Michan, then aligning with Maine.
Mercator:
The Mercator projection is a cylindrical projection. The linear scale is equal in all directions around any point, which preserves the angles and the shapes of small objects. The Mercator projection distorts the size of objects as the latitude increases from the Equator to the poles, where the scale becomes infinite. The projection is most accurate close the equator and thus there is less distortion in the southern area of the country compared to the northern states, which may appear larger than true size.

Plate Carree:
Considered the “unprojected” projection, the plate carree projection is heavily distorted, especially in the poles and bottom edges of the map. This projection is best for the entire Earth and larger scales, while there are higher levels of distortion for small-scale viewing. There is equidistance along meridians and the Equator, but distortion increases as distance from these points increases. The projection is very similar to the aforementioned Mercator, evidenced by the straight horizontal lines, however, with Plate Carree, there is less exaggeration of the Northern shapes.

Robinson
The Robinson projection is ideally a compromise between equal area and conformal. The lines curve gently, avoiding extremes, but also stretch at the poles into long lines instead of leaving them as point. Looking at the CONUS shapefile, the shape of the lower coterminous United States is obviously stretched in in the North-East direction; most evident when you look at the degree of the Eastern coast. Comparing the Robinson projection to the Mercator or Plate Carree, you can see a noticeable difference in the North-South state boundaries, as they are vertical in the latter projections.
Q4 : How does the position of the cities in relation to each other appear to change between projections (give an example of some cities)?

Albert Equal Area Conic
The cities appear to be closer together, compared to the latter projections. Especially when looking at the distance between East and West cities. Examining Las Vegas and Charlotte, it appear that the two cities align on the point of latitude, and span a shorter distance than what is evidenced in the Mercator or Plate Carree projections. Additionally, the cities in the central region, such as Louisville, Nashville, and Memphis seem closer together. Overall, the country seems to be more consolidated.

Mercator
The cities in the northern portion of the country span a greater distance than the cities in the south. The distance from San Antonio to Houston or San Diego to Los Angeles is quite small, whereas the distance from Portland to Seattle seems quite vast. Additionally, the lateral distances seem greater compared to the Albers projection; exemplified by the relationship of Memphis/Charlotte, which seems farther in the latter projection.

 Plate Carree
Looking at the position of cities, the plate carree projection is quite similar to the Mercator, with less distortion in the Northern portion of the country. The state boundary lines remain aligned with lines of latitude and there are many 90degee angles present. Looking to Seattle and Portland, the distance here is much more realistic and de-emphasized, and is more relatable to the distance between Los Angeles and San Diego, compared to the Mercator projection. Again, the lateral distance between cities such as Memphis and Charlotte seems to be slightly distorted and exaggerated.

Robinson
The cities seem to be much closer in the central corridor of the country; Memphis-Nashville and Chicago-Milwaukee are clustered more tightly than in previous maps. Furthermore, the cities in the South-West (San Antonio, El Paso, Tuscon), are much further from the cities in the North-East due to the tilt of the projection.

Q5 : What spatial properties (i.e. shape, direction, area) does each projection distort?

Projection	Properties Preserved	Properties Distorted
Albers Equal Area Conic	Area	Shape
Mercator	Shape, Angles, Distance	Area
Plate Carree	Shape, Angles, Distance	Area
Robinson	Compromise

Q6 : Use the measure tool to measure the planar distance between cities. How does this distance change between projections? Create a table with your findings.

Projection	Distance (meters) Seattle to Jacksonville (NWàSE)	Distance (meters) San Francisco to Charlotte (WàE)	Distance (meters) Chicago to Houston (NàS)
Albers Equal Area Conic	3,843,066	3,510,351	1,553,676
Mercator	4,973,916	4,645,554	1,860,230
Plate Carree	4,917,233	4,640,934	1,589,918
Robinson	3,268,742	3,589,496	1,684,932

Examining trends within the different distances measured, the Mercator projection presented the farthest values in all directions (diagonal, lateral, vertical), while Albers Equal Area presented the shortest distances for lateral and vertical, and Robinson for diagonal measurements. Plate Carree was a close contender for the longest distance laterally, only 5m shorter than Mercator, however, Plate Carree had significantly shorter distances when measured vertically.

Measuring diagonally from the northwest to the southeast, the Mercator projection presented the farthest distance, followed by Plate Carree, Albers Equal Area, and then the shortest distance presented by Robinson.

Measuring laterally at the middle of the country, the Mercator projection presented the farthest distance, followed very closely by Plate Carree, then Robinson, and the shortest distance presented by Albers Equal Area.

Measuring vertically, the Mercator projection presented the longest distance, followed by Robinson, then Plate Carree, and the shortest distance presented by Albers Equal Area.
Q7 : What variables does this dataset contain?
This dataset contains the following variables:

• Name
• State
• Population
• Race
• Age
• Median Age (M/F)
• # of Households
• Average Household Size
• # Married with Children
• # Non-Married with Children
• Family Size
• Housing Units
• Vacant Units
• Occupied Units
• # Rental Units
• # Owner Occupied Units

Q8 : What classification methods did you use? How does each classification method bias the interpretation of the data?
To display the concentration of federal lands, I utilized the natural breaks, equal interval, and standard deviation classification methods.

Examining the histogram spread of values for land area (square miles), the majority of individual parks or places are 800-5000m in size. The parks that are small in size are located prevalently in the South-East, while the Mountainous region and West coast contains predominantly large land masses, with a few small parks sparsely scattered. Looking to the attribute table, the majority of the larger land masses are designated to the Bureau of Land Management, the Bureau for Indian Affairs, and  Forest land,  while the smaller sites are Department of Defense, or Fish and Wildlife.

The natural breaks classification scheme is the most accurate in presenting the quantified concentration of land mass because it takes into consideration the stratified spread in the area values. This scheme displays the range of values, while preserving the integrity of the imbalance that exists between small and large park sizes.
The equal interval scheme presents a bias that seems to downplay or discredit the size of parks in the West. There is an abundance of light-colored land (smaller size), which credits the illusion that the federal land cover is much less significant than is actually true. This map indicates that the main location of large parks is between California and Utah, and minimizes the value of the lands spreading across the Rocky Mountains, as well as the land in southern Oregon/Idaho.