Station Fire

It is believed that on August 25th 2009 that the Southern California's Station fire began. The fire claimed just over 160,000 acres of land, destroying 209 structures, of which 89 were homes. It is believed to have been started at a Ranger Station on Angeles Crest Highway. Amazingly only two firefighters were killed trying to escape the flames as their fire truck plunged off a cliff. This fire threatened 12,000 homes and cost 93.8 million dollars to fight. During this whole ordeal, many individuals were displaced from their homes on the surrounding areas.
The fire burned through La Canada, Flintridge, Glendale, Acton, La Crescenta, Pasadena, Littlerock, Altadena, Sunland, and Tujunga. Many of these areas had to be evacuated due to the high risk and danger of the fire. They closed down many roads and highways for the publics safety as the fire continued to burn dangerously close to both homes and highways. The greatest lost could have been the communication towers on top of Mount Wilson, for which all local television stations broadcast from, most of the radio stations broadcast from, and of course the radio relays that the Los Angeles fire department use. This could have been a devasting lost, had it not been saved.
On September 3rd, officials announced that the fire may have been caused by arson, as they found traces of a substance believed to have accelerated the fire. At that time, officials opened a homicide investigation to try to locate who started the fire. This fire is the largest fire in Los Angeles's modern history and the 10th largest in all of California's modern history. Many individuals are asking for a congressional investigation to why the fire was not contained within 48 hours, before it got to big.
As of now, the only highway closed is a 40 mile stretch of Angles Crest Highway due to damage not only to the guard rails and signs. The pavement is believed to be intact, but until it is deemed safe, it is closed. This is pretty remarkable knowing that this could have been much worse. As of September 6th all evacuation notices have been lifted and the fire seemed to be under control. By September 15th, the fire was 91% contained, and on October 16th it was deemed 100% contained.

As Supervisor Mike Antonovich said "I'm very sorry to say that much of the local television news coverage, that used to be covering fires live, is not covering this fire necessary to inform our people." He said this because it used to be that local news crews would cover the fire to keep an eye on homes, but now they are merely covering the fires because they feel they have to, but no longer want to. There is more an interview fire chiefs than report on what is actually burning. This leads to people only knowing that there is a fire, but not what individual homes are being threatened.

DEM's in ArcGIS

Orginal Elevation Map

Shaded Relief Map

Slope Map

Aspect Map

3-D Rendering

Top : 37.7372222215
Left : -119.133333333
Right : -118.242222222
Bottom : 37.1247222215
GCS : GCS_North_American_1983

While looking at the map of the United States, I decided that I wanted to choose an area that had high elevation differences, and so I chose an area located in Central California. The area I ended up choosing was where the following four counties met, Mona County, Fresno County, Madera County, and Inya County. Instead of telling a little about each county, I decided to write just about one. The one I chose was Fresno County. It was founded in 1856 and is currently just over 6,000 square miles. Fresno is also the tenth most populated county in California. It is considered to be the most agriculturally rich county in the United States and currently supplies food to companies such as Sun-maid Raisins, Del Monte Foods, and Kraft just to name a few. On the east is the Sierra Nevada mountain range, which is featured in the above maps. The Sierra Nevada mountain range currently stretches 400 miles and runs both in California and parts of Nevada. Development of the surrounding areas is highly regulated and much of it is protected by the National Park Service.

ArcGIS Map Projections

Map projections are amazing things, as they help us take our three dimensional world that we live in, and turn it into a two dimensional world that we can take in our pockets. There are many different map projections, and everyone has pros and cons to it. For example, we can first look at conformal map projections. They preserve shapes and angles to places. When we use this projection, we can get a sense of where we are going, but the further away from the equator we use this map, we can see just how inaccurate this can be. It does help locate ourselves in the world, but does not preserve area or distances that well. When we take a look at how far it is between Kabul and Washington D.C. we can see that both the Mercator and Gall Stereographic projections estimate the distance at somewhere ovr 10,000 miles when it should be closer to something like 7,000 miles. We see just how bad these maps can be, yet they give us a very familiar representation of the globe.

Next we look at Equal Area projections, which as the name suggests represents equal area. As we can see from the photos, tends to squish the globe a little bit. It is good for keeping consistent area throughout the globe, and this may be useful to determine the amount of rainforest that was burned down or logged. These maps would be useful to map out and accurately measure area on the globe, however, they do not keep distance as well as they should. I chose to represent the sinusoidal and Hammer projections and the distance recorded from Kabul to Washington D.C. happens to be represented as just over 8,000 miles and just over 12,000 miles respectively. The only reason that the sinusoidal projection is close to the magical 7,000 miles is that it is also equidistant, which makes this map useful in more than one way. We can see that these maps do have a use, but representing distances is not one of them.

Our final map projection we look at is Equidistant, and as it sounds it represents distances from a centralized point as the same. The two projections that I chose are the Cylindrical and Conical projections. We first look and notice that the cylindrical projection tends to squish the globe, but maintains the equidistant relationship from a centralized point. As we look at the conical map projection, we see that the distance from a centralized point is pretty equal. These maps are the best for calculating distances, which turn out to represent the distance between Kabul and Washington D.C. as 5,000 miles for the cylindrical projection and 7,000 miles for the conical projection. Looking at the true distance between those two cities, we can note just how close that the conical projection came. As predicted, it did not distort the distance between those two cities too much.

These map projections have a lot of potential because if one wanted to misguide a community by just looking at a map, they could choose a projection in which their point of view is greatly exaggerated and raise concern for their point. Most of the time we accept the map for how it looks, without question, and this is where we could get into trouble. If one were to use a Mercator projection to look at farmland, and noticed that there was not too much compared to what was set aside for development, they might have to figure into account that the farther away from the equator you get, the greater the area distortion is. This can either be used for good or evil, as it can stir certain people into accepting certain facts, but one must be careful to note what they are doing with representing the information that they were given.

ArcGIS Photos

Here are some of the earlier photos as I made my progress through ArcGIS.

ArcGIS

Today I got my first look at ArcGIS. It took a little time to load, but once it was up and running we were good. The first thing I noticed is that it is set-up very similar to how you think it should be set-up. It has organized toolbars that we are so very much used to along with a very Microsoft like set-up, having the drop down menu’s. I then started the tutorial up to start my first project of an airport expansion. After the map loaded, I noticed that it then looked very much like Adobe Photoshop, as it was designed to have layers in which you could move, modify and choose which layers are to be seen. Once you go though the tutorial, you can see just how this software is indeed designed to work.

For this tutorial, I first started off with a general map of an airport with schools located nearby. I was then asked to locate the schools that would be affected by the noise due to the airport expansion, and was able to see that one school would be affected. From there, I was asked to see how the rest of the land was being used around the area of interest, from which I was able to make a bar graph. After I found out how the land was being used around the airport, I was asked to make a population density map to see just how many people would be affected with the new airport expansion. I was then asked to modify a road leading to the airport and highlight it on the map. Finally I was asked to clean up the maps and present it a clean fashion such that it may be used to present a point to City Planning. This was all done in a few short hours, showing me just how helpful this software can be.

This software has an amazing capability to get a message across in our universal language as human beings. We can then present our information in a reasonable fashion and get a clear message across. For example, we could make a map of forest fires are make reasonable predictions for which land might be susceptible to flooding during the rainy season. This could then serve as a preventive measure allowing people to either compact the soil, or be forewarned when there is a high chance that there could be flooding in that area. This is just one example of how this software can be used to help get a point across, and potentially save lives.

However, we must be forewarned that this software could also be used to drive bias points across as well. A good example of that is logging communities. Let's say that a portion of the amazon rain forest was cut down for lumber and another was burned down due to natural causes. If one were to make a graph showing the changes in tree density for that general area, one could omit the fact of the fire and make the conclusions that a big portion of that forest was lost due to logging. This example introduces a lot of bias towards the fact that logging is bad and that it is devastating the land, when a portion of that would have been done due to natural causes anyway. It over exaggerates the effects just to drive a point across. Even though this software has great potential, it must be checked. In the words of Uncle Ben from Spiderman, “With great power, comes great responsibility.”