Station Fire

A massive fire that started on August 26, 2009, north of La Canada-Flintridge, burned more than 160,000 acres by the time it was contained. This fire was the largest fire in the recorded history of the Angeles National Forest and was coined the Station fire. Twenty-two people were injured in the fire and two firefighters died as their vehicle careened off the road down 800 ft into a ravine. Officials have announced that the Station fire was caused by arson due to the discovery of incendiary material found in the area and have launched an investigation to find the culprits. Below is a reference map that shows the progression of the fire as well as the cities (Los Angeles, Glendale, La Crescenta, La Canada-Flintridge, Pasadena, and Altadena)affected by the fire.


Support for the theory that the Station fire was caused by arson include the fact that the area burned is not traditionally considered a high-risk fire hazard zone. Wildfire hazard is made of two components: probability and fire behavior. As shown below, much of the area that was burned in the Station fire is not actually labeled as a hazard area, further supporting the possibility that the fire was not started by natural causes.


The investigations of the arsonists have been stalled due to the difficulty of gathering relevant evidence. The only lead was a nigerian national who was charged in setting smaller fires a week earlier but officials were unable to connect him to the Station fire. Only about 10% of arson fires yield charges, mainly due to lack of eyewitnesses in the area where the fire started and the destruction of evidence due to the fire.

Following wildfires on federal land, the post-fire Burned Area Emergency Response (BAER) undertakes the rehabilitation of fire-affected land to minimize environmental impacts such as flooding, mudslides, and debris-flow caused by erosion. BAER released a report stating that debris-flow probabilities greater than 80% were calculated indicating that there is potential for significant debris-flow downstream from drainage areas. Given the amount of people living at the base of the mountains, preventing debris-flow will be a high priority. Besides lives and property, water quality, soil productivity, native historical cultural resources, and wildlife are also at risk. Below is a map that illustrates the areas of high potential for erosion in the areas affected by the Station fire.


An interesting use of GIS/mapping technology is to use unmanned NASA predator aircrafts equipped with infrared imaging sensor to take images of fire. These images were then superimposed over Google Earth and Microsoft Virtual Earth maps and then sent to the Forest Service. The maps can then be used by firefighters to develop strategies on how to best contain wildfires.

References
1) The Associated Press. (2009, November 24). NASA PRedator scans California burn areas. Retrieved from http://www.mercurynews.com/news/ci_13859409.

2) Bloomekatz, A. (2009, September 3). Station fire was arson, officials say; homiciee investigation begins. Retrieved from http://latimesblogs.latimes.com/lanow/2009/09/station-fire-was-arson-homicide-investigation-begins.html.

3) California Department of Forestry and Fire Protection. (2007, January). Guidelines for Fire Hazard Zoning Review and Validation. Retrieved from http://frap.cdf.ca.gov/projects/hazard/FHSZ_review_instructionsv1_3b.pdf.

4) Dain, D. (2009, September 9). Station Fire Could Cause Erosion. Retrieved from http://www.myfoxla.com/dpp/news/local/Station_Fire_Could_Cause_Erosion_20090909.

5) Incident Information System. (2009,November 10). News Release: BAER: Watershed Rapid Assessment and Response. Retrieved from http://www.inciweb.org/incident/1856/.

6) USDA-Forest Service. (2009, September 23). Station Fire BAER: Burned-Area Report.

7) Winton, R. (2009, November 20). Detectives still far from arrest in Station fire arson. Retrieved from http://latimesblogs.latimes.com/lanow/2009/11/detectives-still-far-from-arrest-in-station-fire-arson.html.

Mount Baldy: DEM

The image of Mount San Antonio, aka Mount Baldy (due to the absence of trees at its peak), has been with me ever since I was a child growing up in Diamond Bar. On a clear day the mountain was greet me as I went to school and traveled around town. The sentimental value of Mount Baldy was the reason I chose to make a map of this mountain for this lab.

At 10,068 feet, Mount Baldy is Southern California's tallest peak. This peaks marks the boundary between San Bernardino and Los Angeles County. Mount Baldy is the home of multiple sledding and ski runs, as it gets quite a bit of snow in the winter. Hiking Mount Baldy can also be quite a treacherous as the trails are covered with gravel and are adjacent to steep drops. I was able to hike up to the summit and saw a downed World War II era fighter plane that got lost and crashed into the mountain during a stormy day. The last couple miles to the summit were extremely difficult to climb due to the lack of switch backs. The trail pretty much went straight up to the top. The view from the summit was definitely worth the work as all of Los Angeles county can be enjoyed from the peak.

Extent
top: 34.3736111102
left: -117.791944444
right: -117.511944444
bottom: 34.139999991

Geographic coordinate system: GCS_North_American_1983


Shaded relief model


Slope map


Aspect map


3-d image

Lab 5 - Map Projections

Different map projections by type





The fact that the world is round and in a three dimensional space poses problems when converting them to a map on a two dimentional plane. Inevitably there will be distortions that may introduce errors into the data. Working through this lab allowed me to see the map projections first hand and how different they look compared to other projections. For example, the Mercator projection (3rd map layout)distorts the size of Antartica and Greenland dramatically compared to the Mollweide projection (2nd map layout)where Greenland and Antartica look much more resonable. This emphasizes the importance of using the correct map projection for the task at hand.

Since distortions occur for any projection, researchers need to use a projection that protrays the areas of interest with the least distortion. This would explain the plethora of projections available. So equal area maps would be used for reasearchers that are interested in problems involving land mass and conformal maps that preserve angles would be used for navigation.

Another dramatic different between maps is how the distance between Washington D.C. and Kabul changes. One of the more dramatic difference was the Equidistant Conic projection (1st map layout) which measured the distance between Washington D.C. and Kabul to be 4399 miles and the Plat carree projection (1st map layout) which only measures that distance to be 2341 miles. At first it was strange to me that even among equidistant projections the distance between two objects could be so different. I suppose the way the projections are created distorts the areas between two points and a straight line between those two points will have different lengths depending on the projection.

Although some map projectiosn look very different from each other, other map projections look very similar. An example are the Mollwiede and Hammer projections (1st map layout). They are both equidistant projections and they are also very similar in appearance. So researchers must always be careful when layering maps to always check the metadata to make sure all projections used are the same.

Lab 4

Maps from lab 4:

Exercise 1:


Exercise 2:


Exercise 3:


Exercise 4:


Exercise 5:


Experiences with GIS:
When Professor Shin, said that GIS had a steep learning curve he wasn't kidding! The first time I went through the tutorial, it took a long time to not just familiarize myself with the program but to also understand the tutorial itself. The second time I went through the tutorial, I already had an idea of what needed to be done so I was able to focus more on the computer program itself. The third and fourth times working through the tutorial consisted of me trying to figure out the different functions of ArcGIS without consulting the steps listed in the tutorial.

The steep learning curve, requires an individual to devote a considerable amount of time to become proficient with the software which limits accessibility to GIS. This in turn creates GIS "experts" whose services are in high demand due to the relatively few people who can use GIS. ESRI can also keep tighter regulations and quality control to provide professionals requiring spatial analysis with good quality data. The downside is that GIS may not innovate as fast as other mapping applications such as those found in neogeography, due to the sheer number of people using and improving on existing neogeographical tools.

One of the notable features of GIS is its ability to layer maps over each other and manipulate data embedded within those maps. This is very powerful in that using GIS, researchers can analyze relationships and associations between relevant entities and attributes. In the tutorial it was really helpful to see which parcels were located within the noise contour and the population density in relation to the contour. The fact that one is able to see these relationship rather than just reading tables will make it a lot easier to disseminate information.

One of the pitfalls of GIS is that like any other program the information that is outputted in only as good as the data that goes into it. GIS is a tool and it can be used correctly to provide new insights and answers to questions or it can mislead. Take for example, if the noise contour level was misrepresented somehow and is shown on GIS to be smaller than it truly is. If the city makes the decision to expand the airport based on faulty information, undesirable consequences may occur such as residents protesting the additional noise from overhead airplanes and the damaged credibility of city officials. Thus as a researcher or as a consumer of GIS derived information, it is of the utmost importance to make sure GIS data inputs are accurate.