Lab Six: 2009 Station Fire: Fire Hazard Analysis

Tutorial: Slope Analysis

Tutorial: Fuel/surrounding Areas

2009 Los Angeles Station Fire: Fire Hazard Analysis

            The Los Angeles Station Fire of 2009 located primarily in the Angeles National Forest had a drastic effect on the surrounding environment, people and government.  According to the US Forest service, “the Station Fire burned 160,577 acres, destroyed 89 structures and killed two LA County firefighters.”  The fire, officially reported on August 26, 2009 burned and was not fully extinguished until October 16, 2009.  By studying the elevation, slope and vegetation values located within the surrounding areas of the station fire, I provide an analysis of places where fire hazards are highest, finding that much of the most hazardous locations are within the station fire’s parameter.

            I initially began the analysis by obtaining a digital elevation model of the area, vegetation information, and the extent of the fire.  By combining slope information, provided by the elevation, with the National Fire Protection Association’s (NFPA) standards of slope hazard, I created a map incorporating the station fire that shows which points are at the highest risk of fire according to their slope.  Next, I reclassified the vegetation/fuel information in a similar manner according to the NFPA’s standards on which fuels are at risk of perpetuating fire.  Through these two maps, it became evident where fire risks are most likely to occur.  However, most significant to the analysis of the fire hazards near the 2009 Station Fire, was combing both sets of data, by using the Raster calculator,  to create a final analysis showing where slope and fuel risks were highest.  The final analysis shows that some of the highest risk areas were within the confines of the station fire.  It also shows that for the most part, the type of fuel and the slope of the elevation are closely related.

            This type of spatial analysis, although frustrating at times, is very important in providing information as to where fire risks are most likely to occur and therefore where the most extensive preventative measures should be taken.  My personal issues with creating came with not having a solid knowledge of what exactly I was attempting to create at the beginning of the process.  However, as I began to work through it, I began to understand what the activity entailed.  I still wish I had more time to be instructed in these methods as I find them complicated and still do not fully understand the details.  But as it were, it is still yields quite an accomplished feeling when the output of your map reveals and addresses a spatial problem that can now be helped in order to lead to a solution.

References: 

http://gis.ats.ucla.edu/

http://egis3.lacounty.gov/eGIS/

http://frap.cdf.ca.gov/ 

Lab 5: Landfill Suitability Analysis Factors

In order to implement the large undertaking of establishing a landfill, it is necessary to consider many different factors.  This map shows the land suitability factors for a proposed landfill in Gallatin County in Montana.  Taking into consideration such factors as slope of elevation, distance to landfills, soil drainage, streams, and land cover, helps to address risk factors that come along with the establishment of landfills, as demonstrated by the LA times article addressing the health issues associated with the landfill in Kettleman City, California.

            GIS is an extremely useful tool that should be used to address such issues as health concerns.  If Kettleman City had applied the analysis shown here for Gallatin County, it could have avoided many of the issues that they have since faced.  GIS has the unique capability to combine a number of important factors in deciding where to place a landfill in order to produce a final report.    

By studying slope elevation, the ability for waste to flow and be transferred is addressed, and therefore promotes a landfill at an elevation with little slope.  An analysis of the location of current landfills in the county will also aid in determining where to place a new landfill.  By examining environmental factors, such as soil drainage and streams, the risk of contamination and in turn health risks is decreased.  And by combining all these factors with the type of land cover, the GIS is able to provide an analysis of where it seems most suitable to have a landfill.

Kettleman City’s main concern is the risk that the landfill in their area has upon their health.  While the above factors address this concern indirectly, GIS can be implemented to further address these concerns.  In an attempt to prove to the landfill companies that the landfills were indeed the main contributing factor to birth defects in the city, a GIS map can be created mapping the communities that reported birth defects.  Additionally, the commissioner of the map of Gallatin County could include other factors, such as distance from schools and other places in which children congregate in order to further prevent instances of health problems.

The possibilities for GIS and spatial analysis to prevent health risks are almost endless.  The more the government or private companies use GIS to help solve and prevent risks, the more the risks will decrease.  In such places as Gallatin County, the landfill is sure to be placed in a location that will have the least amount of risk because of its implementation of GIS, and in such places as Kettlemen City hopefully GIS can help prevent further issues with landfill and health risks in the future. 

                Although the mandated rule that marijuana dispensaries in the city of Los Angeles must not be located within 1000 feet of places in which children congregate has good intentions, it is not practical.  When examining the geographic elements of the question, it becomes clear that very few schools are in fact located within 1000 feet of the majority of marijuana dispensaries in the city.  A law, therefore, preventing the establishment of medical marijuana buildings would waste funds shutting down on a few marijuana locations.

 Additionally, it should be noted that the majority of these marijuana dispensaries do not promote themselves and do not intend to draw in children.  Many of these places are inconspicuous and unlike the tobacco industry, do  not rely on advertisements in order to gain revenue.  These places are in no way targeting youth, as shown geographically in that they do not intend to locate their establishments close to schools, and therefore, it should not be an issue as to whether or not they are within 1000 feet.  The issue of marijuana exposure to children is not a matter of the location of these dispensaries, more a matter of the prevalence of marijuana and if the city really wished to prevent the exposure, they would outlaw the dispensaries all together.  Making a small, useless legislation will not change whether or not children are exposed and can get a hold of marijuana, it will, once again, only waste the city’s money that should be going to schools anyways.
Also, elements of this law do not make sense and prove that it is not a well-thought out law and would again, wast the governments money.  It claims it aims to end the late-night life promoted by the dispensaries and make them shut down at 8pm, but this does not have anything to do with schools, since schools are not in session at this time anyways.  This therefore would increase traffic during school hours, actually going against what the law intended.

If, however, the Marijuana dispensaries continue to expand into areas that are increasingly nearby places in which children congregate, governmental action should be taken.  Since however, it is clear that they are not geographically nearby it would simply be a waste of money to implement such a law. 

References:

UCLA GIS Mapshare

Census.gov- TigerLines

maps.google.com

Lab 4- Digitizing Iraq Map

Brynn Kurtz: Lab 3: Geocoding

In recent news, gas stations have become the topic of many discussions.   There is constant dialogue regarding the increasing gas prices, as well as frequent mention about gas station robbery and fraud threats at gas stations.  And in conjunction with the growing "green" movement, there have been many concerns raised about the negative environmental impact and the effect that the fumes might have on human health.  In this geocoding lab, I chose to look at the relationship between gas stations and schools hoping to address  these questions and show that there is potentially a real danger by placing gas stations so close to schools.

The geocoded addresses presented in the map are gas stations in Contra Costa County, a diverse county in the San Francisco Bay Area.  In the map, I chose to highlight two different communities; Richmond, which  is generally poorer than the rest of the county, and Danville, which is where more affluent residents reside. I was hoping that there would be a discrepancy in the gas station relations to school, however there did not seem to be one.  However, this does not necessarily null my hypothesis that gas stations can have a negative impact on students.  My map simply presents the information, but a further project would actually be to collect data based on crime and health in young students in both of these areas.  Nevertheless, the process of geocoding aided was vital in gaining accurate distances from schools.  By using buffers around the geocoded points, I was able to determine which schools might have more risk factors than others.

Geocoding is not only beneficial for gaining address information but it also reveals significant information about the area that is being geocoded.   For example, in order to begin the process of geocoding, I needed to obtain road information about the area in question, Contra Costa County.  Once my points were then geocoded on the map, it was interesting to examine the trend of geocoded points, the gas stations.  I found that gas stations, as well as schools (which I obtained through a point shapefile of California) tended to be along the main roads.  Very rarely was there an outlier.  This information was a byproduct of my original question but can be very helpful in addressing further questions.  This proves that geocoding can be extremely beneficial in many ways that are not initially expected.

Although the geocoding process did not fully answer my question of whether or not gas stations have a negative effect on schools and students, it was still beneficial in understanding other trends in Contra Costa County and can aid in further research on this question.

References:
Contra Costa County road info: http://www2.census.gov/cgi-bin/shapefiles2009/national-files (contained address information in the attribute table)
Contra Costa Shapefile: http://gis.ats.ucla.edu/
Contra Costa School information:  http://gis.ats.ucla.edu/
Gas Station Address Information: http://www.automobilemag.com/31/california/contra_costa/gas_prices.html

Brynn Kurtz: Lab 2 Potential Wastewater Plant Sites

Brynn Kurtz: Week One Lab: Proposed Airport Expansion