Lab 7

Figure A

Figure B

The Station fire in L.A. County was considered to be the biggest and most damaging California wildfire in 2009. From Figure A above, we can see that the earliest affected area (the actual fire was reported at 3:30 p.m. of August 26, 2009) shown on the map, August 29, 2009 at 2:48a.m. started in the Angeles National Forest. The fire then spread North according to Figure A, resulting in huge amounts of damages including deaths of two firefighters and more than 2000 buildings and 10,000 residences were affected. From the reference map (Figure A), we can see how the fire expanded its boundaries from August 29 to September 2 of 2009 rapidly within a week. Since the Station Fire was so devastating, therefore I believe it would be beneficial to look at its effects in both micro and macro scales. Figure B above indicates both the populated areas within 2 miles of the fire perimeter, it also shows three different types of vegetation which had a lot to do with the spread of the fire and also its consequences. This thematic map helps to illustrate my points below.

I used a Digital Elevation Model for both of the maps. Since if we simply look at a map without its elevation information, then we would only be able to know that the fire spread in the Northern direction. But with the help of a DEM (Figure A), we can actually see how the fire expanded to the higher elevation areas in the mountains. On the other hand, Figure B illustrates the vegetation features within the perimeter of the fire. Within the wider boundary, it is densely packed with shrubs and there are also a vast area of conifer and hardwood forests. The Station fire did not spread to the urban areas in the South where there is a lower elevation and the vegetation pattern does not extend. The Northward spread of the fire was due to uphill wind and high temperature, but when we put this map into consideration, we can see that an important factor contributing to this spread was the presence of the dense vegetation layer. The burning of vegetation facilitated the rapid spread of the fire. In this figure, populated places within and near the fire perimeter are illustrated as well. Even though the area within the larger fire boundary consisted a lot of forest area and was not in the urban area, there were still people residing in this area, therefore we can see how the fire negatively affected people living in the area where the fire occurred, but at the same time, it also affected others who lived near the perimeter as illustrated in the figure.

On a micro scale, we can look at the local effects of the Station fire in terms of the population. The populated places illustrated in Figure B are defined as “places with clustered or scattered buildings and a permanent human population” by the Cal-Atlas website (http://atlas.ca.gov/). According to the reported statistics, more than 93 buildings were destroyed by the fire. Therefore people within these populated areas were being directly affected, having to relocate themselves due to the destruction of their buildings. On the other hand, I created a two mile buffer around the perimeter to locate the populated places within two miles of the fire. This would allow us to look at the population in close proximity of the affected area. The people in these areas together with those within the perimeter might be affected directly physically (by the fire itself or by smoke and ash) and psychologically. Overall, the Station fire was devastating to people in a local scale. On the other hand, although not being illustrated in this DEM, wildlife populations might also be affected. When we look at the affected area, the vast vegetation and forest areas suggest a suitable habitat for wildlife. After the fire, this area would be not suitable for wildlife to inhabit anymore, and due to the close proximity to the urban areas, they could not move Southward (it would be hard for them to adapt if moved there), thus they could only move to other vegetated area or Northward to even higher elevations.

On a macro scale, the burning of vegetation by the Station fire led to a wide range of consequences. Since the shrubs were so densely packed together, therefore the fire was able to spread rapidly. Hardwood forests were also present in the affected area, and they constitute a “fire-sensitive community” (http://www.forestencyclopedia.net/p/p162) since thicker trees are able to retain more heat, therefore the fire was able to expand quickly and persist. The burning of the area led to the emission of a lot of greenhouse gases including carbon dioxide. As the burnt area was so vast, more than 140686 acres, therefore the amount of “hundreds of years worth of stored carbon dioxide” would definitely be huge and devastating. The emission of aerosol on the other hand created smoke that hindered the rescusing process, but at the same time it could also “influence the formation of clouds and precipitation” (Janha”ll, Andreae, and Poschl 17185). Therefore the burning of dense vegetation could lead to larger climatic consequences.

The two DEMs above provide viewers an overview of how the fire spread and how the different features within and near the boundary of the affected areas could contribute to significant consequences in both micro and macro scales. Despite the simplicity of this map, it is able to provide a clear description of the natural landscape and features of the areas immediately related to area where the Station fire occurred.

Works Cited

Bloomekatz, Ari B. "Station Fire Is Largest in L.A. County's Modern History | L.A. NOW | Los Angeles Times." Los Angeles Times. 2 Sept. 2009. Web. 23 Nov. 2010. <http://latimesblogs.latimes.com/lanow/2009/09/station-fire-is-largest-in-la-county-history.html>.

Deioma, Kayte. "California Burning - Station Fire Looms Over LA." Los Angeles Travel - Guide to Los Angeles Travel. 29 Aug. 2009. Web. 23 Nov. 2010. <http://golosangeles.about.com/b/2009/08/29/station-fire.htm>.

InciWeb. "InciWeb the Incident Information System: Station Fire." InciWeb the Incident Information System: Current Incidents. 11 Oct. 2009. Web. 23 Nov. 2010. <http://www.inciweb.org/incident/1856/>.

Janha ̈ll, S., O. Andreae, and U. Po ̈schl. "Biomass Burning Aerosol Emissions from Vegetation Fires: Particle Number and Mass Emission Factors and Size Distributions." (2009): 17183-7217. 2009. Web. 23 Nov. 2010. <http://www.atmos-chem-phys-discuss.net/9/17183/2009/acpd-9-17183-2009.pdf>.

Konoplk, E. "Fire And Northern Hardwood Forests In The Southern Appalachians — Forest Encyclopedia Network." Encyclopedia Collection — Forest Encyclopedia Network. 14 Nov. 2008. Web. 23 Nov. 2010. <http://www.forestencyclopedia.net/p/p162>.

NASA. "NASA - Biomass Burning Fact Sheet." NASA - Home. Feb. 2001. Web. 23 Nov. 2010. <http://www.nasa.gov/centers/langley/news/factsheets/biomass.html>.

Saugus Union School District. "Station Fire Update for Friday, September 4th." Saugus Union School District. 4 Sept. 2009. Web. 23 Nov. 2010. <http://www.saugus.k12.ca.us/station-fire-update-friday-september-4th>.

Wapedia. "Wiki: 2009 California Wildfires." Wapedia. Sept. 2009. Web. 23 Nov. 2010. <http://wapedia.mobi/en/Station_Fire_(2009)>.

Lab 6

3D Images of the area

 

Area on google map illustrated by the blue pushpin

Extent information:

Top: 20.3255555537 Degrees

Left: -102.469444443 Degrees

Right: -100.839444443 Degrees

Bottom:  19.3866666648 Degrees

Information about GCS:

GCS_North_American_1983

This Digital Elevation Models above illustrate an area in the city of La Piedad de Cavadas, Mexico, which is located East of Laguna de Chapala. When comparing the DEM with the google map shown above, we can understand much more about the relief of the area. From the DEM images, we can infer that the area contains quite an amount of flat areas and even though there are also mountainous areas, they are not particularly high in elevation and only a few areas of slopes are steep. This might actually contribute to one of the advantages to the raising of livestock in La Piedad de Cavads, which is prominent in the area. The 3D images above can further enhance the topography of the area and allow us to see how the some areas are not only flat, but are indented. When combing all the images, we can conclude that the area is not highly dominated by mountain ranges nor flat land, rather, the flat land to protruded areas ratio is quite proportionate and it is also proportionate in terms of where they are located, and that the slopes are mostly gentle.

Lab 5 - Projections in ArcGIS

The process of map projection transforms the 3D world into a 2D model. It allows people to analyze the details on a 2D surface rather than a 3D globe because it can allow easier measurements. There are countless number of projections because they are all based on mathematics and coordinate systems, and these projections are then categorized into different groups including Conformal, Equidistant, and Equal Area. In fact, for every map projection, there will definitely be some sorts of distortions in terms of area, shape, distance, scale and direction, etc. Nevertheless, in different projections, some of the above properties are preserved and create benefits for different functions of the projections.

The Conformal projections as shown in the figures above, Stereographic and Mercator, show that this category preserves local shapes and angles. As we can see, the parallels and meridians intersect at 90 degrees angles. Therefore this type of projection is good for navigation including sailing. Since the angles do not shift while taking a bearing in certain directions. Nevertheless, Conformal projections are distorted in other ways to make it disadvantaged in certain areas. For example, shapes are not preserved within larger regions and that areas are not proportionate to the areas on Earth. When we refer to the Conformal projections figure above, we can see that Greenland in both conformal projections are elongated vertically and horizontally, for Mercator and Stereographic respectively. On the other hand, Antarctica in the Mercator projection appears to be much larger than the Antarctica in the Stereographic projection.

On the other hand, Equal Area projections preserve the area because the areas maintain proportional relationship with the Earth's. We can see from the two Equal Area projections above (Bonne and Mollweide) that the parallels and meridians are not like those in the Conformal projections, instead, they do not meet at 90 degree angles. Although the area is preserved, angles, shapes and scale are distorted. And we can see from both of the Equal Area projections above that the shapes of the regions along the margins are distorted the most, rather, the areas in the middle seem less distorted. This kind of projection is good for analyses interested in calculating areas where shape is not important.

Lastly, Equidistant projections preserve distances from the center point of the map outward. Since it is impossible for any projections to preserve all the distances, therefore distances are actually maintained at a few points only. Moreover, the scale at different areas of the projection would be different. The scale of other points would be sacrificed in order to preserve the distance between points relevant for the projection. Apart from these limitations, this kind of projection also distorts the area and shape. As we can see from the two Equidistant projection maps above (Plate Carree and Equidistant Conic), that Plate Carree projection stretches the shapes of the regions sideways and the shape of Antarctica in the Equidistant Conic projection is heavily distorted.

Lab 4 - ArcGIS

Using ArcGIS to create a map is far more complicated than using Googlemap or other tools for neogeographers. Instead of having a pre-existing map for us to plot the information that we have for each place, ArcGIS requires the users to import their own desired layers and compile them into a map with our previously recorded information that we are interested in. Although it seems more complicated than Googlemaps when so many different layers overlay each other, it is actually a benefit for users. Users thus have the ability to control each and every layer at a time and combine them afterwards to see the effect, moreover, the layers are shown very systematically on the left hand column and the users can turn them on and off at ease when working on each layer.

In the previous exercise in which we had to work on googlemaps, I did not encounter any problem exploring how to use the system myself. Googlemap is very user-friendly and very self explanatory. On the other hand, for this lab, if I did not have the 50-page guideline, I am sure it would be quite difficult for me to explore without guidance. Even though it might be easy to add data/layers and to add legends and titles, these are only basic steps to create a very basic map. In order to manipulate at a deeper level for example joining the different graphs and also drawing streets and editing information, I am sure it would not be easy for an amateur to figure it out. That is why ArcGIS is for professionals and googlemaps are for amateur cartographers. Although ArcGIS is very systematic, after repeating the steps on the guideline, I am now able to manage the basic use of it without constantly referring back to the steps. For example, adding frames, resizing frames, and shifting from frames to frames are relatively easy. I am sure after a few more uses, amateur users will be able to manipulate the system quite easily.

ArcGIS also has another benefit for creation of professional maps. It allows users to easily convert qualitative data as shown on the map into quantitative data on graphs and vice versa. Users can therefore make use of the numbers to create graphs and make relevant calculations to understand the relationship of a place and its attributes. For example, in this exercise, we can understand the relationship of the population density and a particular place with or within the noise contour area. Users can thus understand the situations and connections between these data and make possible changes or proposals for changes to improve the lives of the people. On the other hand, ArcGIS can also combine qualitative and quantitative data. For example the drawing of a street. The system allows us to plot the starting point on the map and then we get to enter the length of the street. This allows the accuracy of the location and length of the street.

Apart from these benefit, it has its other pitfalls too. When I used this program, I realized the undoing process is very troublesome. ArcGIS can only allow us to undo or redo the macro details like the movements of the frames and adding layers but not the micro details like the change of color and the inserting of words, for these changes, we have to reset them manually. Moreover, as I have mentioned in the first paragraph that we have to import the data from other folders (including ArcCatalog), I realized that ArcGIS does not allow us to search for a place by its address and area code. And it is different from googlemaps in that it does not allow us to have a street view of the places therefore ArcGIS is very technological and computerized.

Overall, there are aspects that I appreciate but there are also some that I dislike about ArcGIS. Even though it is very hard to manipulate at first, it is relatively easy to handle after a few tries by following the guidelines. And it allow us to do more than we can on neogeographic tools, for example we can be able to import different data we are interested in and allow the system to correlate them for us. Nevertheless, the using of the system is still very complicated because it includes a lot more than just the basic adding of streets and points at a superficial level. Rather, it includes a lot of quantitative and qualitative data which, although allow us to understand the attributes of a location, need a lot of interpretation and analyses.