Week 10: My Own Map, Lab 8

DAVID PHILLIPS: LAB 8

The station fire devastated a fairly large area. It burned more than 90,000 acres. Two firefighters died and eighteen homes were burned. This fire completely deforested a huge area of wilderness. Deforestation in mountainous areas heightens the risk of mudslides. 

Southern California is an area that experiences a high amount of earthquakes. Deforestation creates an increased risk of landslides. Earthquakes can trigger landslides in unstable landscapes. Hospitals are inevitably located in areas that are not flat. The maps shown below will be used to determined whether or not hospitals are at risk. 

Map 1 is a 3 dimensional render of the area in question. A large portion of the area burned was contained in the 3D model. As can be seen, the burn area and surrounding regions are quite mountainous. Because it was deforested by the Station Fire, it is clear that this region had a higher risk of mudslide after the fire. In the map, the purple areas are the lowest, while the green areas are the highest.

Map 2 is a slope analysis model. The outline is of the total burn area over all the days. This map shows us that the most mountainous areas were the ones that were burned. The green areas are the lowest points. The red areas are the highest points. The more multicolored an area is in this map, the steeper the incline, or, more rapid the change in elevation. The green dots are documented earthquakes. There is a great number concentrated in the area, especially just to the east of the burn zone.

Map 3 brings everything together. The crosses displayed are hospitals. There is one hospital that is very near to the south edge of the perimeter. The area has a high amount of earthquakes. However, the area around directly around the hospital has not been burned. Therefore, it is unlikely that the stability of the soil will have a chance of directly effecting this hospital. In conclusion, these maps lead one to the conclusion that the Station Fire did not result in an increased risk of landslide for hospitals in the area. 

MAP 1

MAP 2

Break values for elevation raster by percent rise: 3 - 7 - 11 - 15 - 19 - 23 - 28 - 37 - 100 (Green to Red)

MAP 3

Works Cited:

31, August. "Station Fire Claims 18 Homes and Two Firefighters." Los Angeles Times. Los Angeles Times, 31 Aug. 2009. Web. 10 Dec. 2012.

Cannon, Sue. "Post-Wildfire Landslide Hazards." Post-Wildfire Landslide Hazards. USGS, 01 Aug. 2012. Web. 10 Dec. 2012.

Keeper, David K. "Landslides Caused by Earthquakes." Landslides Caused by Earthquakes. The Geological Society of America, 01 June 2012. Web. 10 Dec. 2012.

Trotter, Matthew. "Monument Fire Burn Areas Face High Probability of Mudslides, USGS Says." KNXV. Kronkite News, 1 Aug. 2011. Web. 10 Dec. 2012.-

USGS. "Landslide Hazard Information." - Causes, Pictures, Definition. United States Geography Society, Jan. 2012. Web. 10 Dec. 2012.

Week 8, Lab 7

LAB 7: DAVID PHILLIPS

 This map is county based. It displays the number of people in each county across the mainland United States. The lighter the shade of blue/purple, the fewer the people that live in the specified county. A scale bar and north arrow have also been included for reference purposes. The data used to create this map is from the year 2000. This data set is made publicly available by the U.S. Census Bureau.

 This map displays the difference in population by county. The pink areas saw a decline in population from 1990 to 2000. The darker the green, the more growth that the area experienced. A scale bar and north arrow have also been included for reference purposes. The data used to create this map is from the year 2000. The legend gives information in raw number form.

 This map shows the percentage change from 1990 to 2000 by county. The darker the purple, the more drastic the change after the ten year period. Negative values are displayed in hues of orange. The darker the orange, the more drastic the negative shift. This is a good map because it forces us to ask questions. Why did the populations change as they did? What factors could come into play? How can we test hypotheses explaining negative growth?

 This map displays the population density of the USA by county. The dark blue represents extremely dense counties. The green represents a medium population density. The off-white color represents sparsely populated counties. Creating this map was a challenge. Just before I finished, I made one of those critical errors. I had to recreate this map. That task took time and was the opposite of enjoyable.

I did a portion of extra work for this lab. This map displays the population distribution of blacks across the United States by county. The darker the purple, the higher percent of black population in the county. Areas with little or no black population are represented by very light shades of purple. I downloaded this data from the US Census Bureau. Creating this map was very challenging because there was not a tutorial to be followed. Also, data was not provided, I retrieved it myself.

extra credit?

Week 7: Digital Elevation Models

BY DAVID PHILLIPS

The area I selected is quite mountainous. I constructed a series of DEM's. A DEM is a Digital Elevation Model. DEMs contain a huge amount of information about the elevation (and other aspects) of the terrain portrayed on the map. The DEM here is a small range of mountains near the coast of California. A hillshade model (first in the sequence below) delineates the sort of terrain by using light and dark shades of grey. The color overlay enables the viewer to see that the terrain rises as you travel west to east. A slope model describes the type of slopes in the DEM.

EXTENT OF THE MAP:

39.8291666661 North to 39.3838888883 North
105.788888889 West to 104.969444445

HILLSHADE MODEL

 SLOPE MODEL

ASPECT MODEL

3D Render

Map Projections

Bonne: This equal-area projection has true scale along the central meridian and all parallels. The measured distance from Washington, DC to Kabul, Afghanistan is 6,731 miles. *

Cylindrical Equal Area: Lambert first described this equal-area projection in 1772. It is used infrequently.

The measured distance from Washington, DC to Kabul, Afghanistan is 10,108 miles.*

Azimuthal Equidistant: The most significant characteristic of this projection is that both distance and direction are accurate from the central point.

The measured distance from Washington, DC to Kabul, Afghanistan is 8,341 miles.*

Two Point Equidistant: This modified planar projection shows the true distance from either of two chosen points to any other point on a map.

The measured distance from Washington, DC to Kabul, Afghanistan is 6,649 miles.*

Hotine Oblique Mercator: This is an oblique rotation of the Mercator projection developed for conformal mapping of areas that do not follow a north–south or east–west orientation but are obliquely oriented.

The measured distance from Washington, DC to Kabul, Afghanistan is 9,629 miles.*

Stereographic: This azimuthal projection is conformal.

The measured distance from Washington, DC to Kabul, Afghanistan is 9,878 miles.*








***All measurements are planar.

 

When working with maps, projections are of usually of great importance. Map projections become negligible and irrelevant when working with extremely large scale (small area) maps. The smaller the map scale, the greater the importance of the projection. In all of the maps above, the scale is so small that different projections produce radically different measurements. For example, the measured distance from Washington DC, to Kabul, Afghanistan taken from the Two Point Equidistant map was 6,649 miles. From the Cylindrical Equal Area map, the distance measured was 10,108 miles. The measurements were taken from exactly the same points in exactly the same way. Yet, a difference in measurement of more than 3500 miles exists.

Different map projections are used for different purposes. The first pair of maps listed above are equal area projections. Equal area map projections are useful for a variety of purposes, but not for others. The Cylindrical Equal Area projection is very useful for gaining perspective. The mercator portrays the northern hemisphere, especially North America and Europe, as far more important than the land masses in the southern hemisphere. This is done by making North America and Europe look larger than they actually are relative to South America and Africa. When people see the Cylindrical Equal Area map for the first time, they are usually astonished. Certain projections, such as equal area, are very useful for gaining perspective.

Equidistant maps also have some very specific applications. Equidistant maps are point centric. This means that everything on the map will be the same distance from a certain point. For example, equidistant maps are currently being used to evaluate and analyze the North Korean missile crisis. These maps accurately depict the North Korean missile range. In the Azimuthal Equidistant projection, everything is the same distance from the center of the map. Additionally, in this projection, direction is also preserved in relation to the center. Preserving direction enables USGS to use this projection in the National Atlas of the United States of America.

Conformal maps, the last pair presented above, preserve size, direction, and spatial relations. Distances are very skewed in conformal projections. Above, measurements in the conformal maps differ by up to 3,000 miles. Most of the time, conformal projections are used when dealing with large scale maps. Small scale maps very rarely use conformal projections. In small scale applications, conformal maps are pretty to look at, but many times, are not useful mathematically. Despite this, they can still give the viewer a new perspective, aiding them in understanding the complex geographic relations of the world.

DAVID PHILLIPS
DAVID PHILLIPS
DAVID PHILLIPS

Proposed Airport Expansion

Week 4 Lab

To Hell and Back Again,
By David Phillips
ArcGIS product:

ArcGIS software is incredibly overwhelming, at first. Approximately 55 out of the 58 pages of the tutorial were a battle. For the most part, things did not become easier as time went on. Honestly, this was one of the most trying experiences I have at college thus far. However, as things were consistently challenging, I was consistently adapting and overcoming. On a personal level, I believe adapting and learning to be closely related terms.

As a result, I do not feel comfortable working with ArcGIS software. However, I learned a great deal from the lab, and am far more comfortable now than I was before. Creating multiple maps and changing between views has helped me greatly. I now realize that when I zoom in and out, I am not destroying the map I just created. Also, I learned that the "undo" button is incredibly useful. I clicked the undo button at least fifty times. Furthermore, ArcGIS is most likely bad for my heart. In many instances, when I did not understand what was happening and thought I lost all my work, my heart stopped. Thankfully, I never actually lost all of my work. Also, I am alive, and thankful to be finished with this painfully slow, GIS assignment.

There are many seemingly unexplainable things in ArcGIS. If I continue to work with this software, I hope to develop an understanding of its inner workings. In many parts of the tutorial, I did not understand what I was doing. I was simply clicking the buttons I was told to in a specific order. I understand few parts of the system. However, I successfully completed step five of the tutorial, in which not all of the steps were spoon-fed to the user. So, I probably have a more functional knowledge than I think I do.

The most frustrating part of the process was trying to complete my project on a different computer. Even if nothing was changed, the file pathways were severed. Repairing these takes approximately half an hour, if it is possible at all. In the end, I abandoned my attempts to finish this lab at that time and returned when I could work from my original workstation. Even though the map above looks somewhat meaningless and boring to most people, it was a huge challenge to create. For that reason, I am very proud of my finished product.

Neogeography - My Own Map

Neogeography

Over the past few years, neogeography's popularity has exploded. Without realizing, people use it almost every day. When someone uses google maps to find a route, the user is creating a map using neogeography. User interaction with maps enables people to accomplish many complex tasks. For example, a fisherman now has the ability to digitally map his daily route, compile the data of how many fish he caught at each location, analyze,  and maximize his future catch.

However, there are many serious implications to neogeography. As a result of the ease of access, many uninformed or unintelligent people can make maps and distribute them. If an uninformed person makes a map based on what they believe to be true, there is a chance that the map will not correlate with reality. Any number of bad things can happen in someone relies on a flawed map. Neogeography is so easy, everyone can do it. Thus, many fail to put ample time and effort into the creation of maps.



View Surfing in Los Angeles in a larger map

~ DAVID PHILLIPS

Beverly Hills Quadrangle

1. We are looking at the Beverly Hills Quadrangle
2. Adjacent Quadrangles:

1. Canoga Park
2. Van Nuys
3. Burbank
4. Topanga
5. Hollywood
6. Venice
7. Inglewood
3.  Year: 1966
4. National Geodetic Vertical Datum of 1929 (Also, North American Datum of 1927)
5. 1:24000
6.  
1. (A) 1200 meters
2. (B) 1.894 miles
3. (C) .379 inches
4. (D) 12.5 centimeters
7.  Contour Interval: 20 feet\
8. Coordinates:
1. (A) 34º 03' 40" N, 118º 26' 30" W
1. 34.0611 N, 118.4416 W
2. (B) 34º 20' 00" N, 118º 29' 55"
1. 34.3333 N, 118.4986 W
3. (C) 34º 07' 15" N, 118º 24' 45" W
1. 34.1208 N, 118.4125 W
9.  
1. 560 ft or 171 meters
2. 40 ft or 12 meters
3. 700 ft or 213 meters
10.  UTM Zone: S11
11. 3763000 mN, 362000mE
12. 1,000,000 square meters
13. Blank
14. 14º
15. South

BY DAVID PHILLIPS