kbfi

Update [4.1.2015]

I'll start updating this blog with some of my work.

Final Lab: U.S. Census

          The above map is a choropleth map showing the percentage of the Asian population within each county. This data set was extremely skewed so ranking the data was difficult. In the end, I chose to use "Geometric Interval" because it seemed to sum up the data set rather well. According to this map, the Central U.S. has the lowest percentages of Asian populations while the eastern and western coasts, especially Southern California, have higher percentages of an Asian Population.

          This choropleth map shows the distribution of the Black population of each county. It shows higher percentages along the southwestern coast and even more pronounced percentages along the southeastern coast. Like the Asian population dataset, this too was skewed to the left so I decided to use "Geometric Interval" to rank the data set.

 

           "Some Other Race" describes multiracial individuals. This choropleth map shows the percentage of "some other race" population within each county. This population shows greatest percentages along the coasts and smallest percentages in the Central U.S. This data set was also extremely skewed so I ranked the data using "Geometric Interval."

           All three maps show the percentages of a race within a county, and all three use geometric interval to rank the data sets. All the data sets had extreme outliers that skewed the data sets as well as "tails" within the histograms. Unfortunately, this made it difficult to accurately represent the data sets. I would have liked to better portray the data but the vastness of the data sets as well as the distribution made this impossible. 

          Overall, I really enjoyed being acquainted with the ArcGis program. Learning these technical skills was a great experience. But the program itself was irritatingly slow a lot of the time and over the course of the quarter I realized that being a cartographer is just not for me. Being able to make maps asks for a lot spatial thinking, skills, and patience that I just do not have. This exercise especially has showed me that representing data through maps is a skill that's better suited for other people.

Week 8: Station Fire

Los Angeles County Station Fire

The Los Angeles County Station Fire occurred in the Angeles National Forest towards the end of August through October 2009.² Its burn area affected mostly Shrub, Conifer Forest, Hardwood Forest, Hardwood Woodland, and Urban and Agricultural land use: a variety of ecosystems were affected. And this large-scale fire gave birth to a crippled environment. A year after the fire and mitigation approaches can and should be taken to guide ecological growth in the right direction.

Angeles National Forest is largely untouched by urbanization but still within the grasps of human activities. Much of the burn area consisted of Shrub, then Conifer Forest. Forest fires are often seen as a bad thing but in reality, forest fires are healthy when occurring in small and patchy areas. In many mixed-conifer forests, fire is a keystone process promoting biodiversity by allowing varying successional species to establish and rare fire-seed trees to germinate.³ The Vegetation Map shows that some of the land burned by the fire was “Conifer Forest.” Other vegetation types affected were Hardwood Forest, and Hardwood Woodland. Each of these differing types of vegetation housed differing ecosystems and various species. 

The continuous burning of Station Fire not only destroyed the ecosystems present, but had many after-effects. This powerful fire created “competition-free” space for invasive species to establish themselves, altering the natural regime and decreasing biodiversity.⁴ The main after-effects of Station Fire were its topographical effects. Smoke still seen after the fire was said to have been put out indicated that the root systems of plants were burning⁶ and the strong interlocking mechanisms of these root systems that provided the necessary ecological service of anchoring the ground, no longer did.⁷ The Station Fire perimeters map shown over a hillshade model and the Slope Map show that the fire took place on steep slopes and crept up mountains. The effects of this, combined with barren land and wet conditions threatened many Californians with mudslides or landslides.⁸ The lack of anchoring vegetation on a steep slope compounded with a wet season, resulted with mudslides and landslides.

As the Station Fire Burn area recovers it is important to maintain and guide its growth in the proper direction. As the new species are setting in and as the ecosystem is recovering and growing it is important to learn from past mistakes and effectively use fuel reduction techniques. According to Potts et, al., fuel reduction strategies are important in shrubland community dynamics; and, as the land use map shows, a great majority of the burn area from Station Fire was “Shrub.” Both prescribed fires and mastication can help improve the biodiversity of the region.⁸ As the burn area is recovering it is important to guide its ecological growth in the proper direction and to adapt good forest management strategies.

The Station Fire was one of the largest wildfires in modern California history. It destroyed various types of vegetation and threatened a few urban areas. But its after-effects on the environment and on humans were even greater. It left open many opportunities for invasive species and left the land barren devoid of any anchoring system, resulting in many mudslides and landslides in the area during the rainy season. A year after the fire, and now is the time to implement improved forest management strategies and avoid the mistakes of the past.

________________________________

Bibliography 
² (September 31, 2009) Station fire doubles in size. Daily News Los Angeles. Retrieved from http://www.dailynews.com/news/ci_13239035

³ School, A. E.; Taylor, A. H. (2010) Fire regimes, forest change, and self-organization in an old-growth mixed-conifer forest, Yosemite National Park, USA. Ecological Applications. 20(2) 362-380

⁴ Cavallers, L; Raffaele, E. (2010) Fire enhances the ‘competition-free’ space of an invader shrub: Rosa rubiginosa in northwestern Patagonia. Biological Invasions, 12(10) 3395-3404

⁶ Holmes, B. (November 10, 2009) The station fire is out – or is it?. Los Angeles Times.  Retrieved from http://articles.latimes.com/2009/nov/10/local/me-station-fire10

⁷ Levinton, J. S. Marine Biology: Function, Biodiversity, Ecology (Oxford University Press, ed 3, 2009) p 175 – 176

⁸ Potts, J. B.; Marino, E.; Stephens, S. L. (2010) Chaparral scrub recovery after fuel reduction: a comparison of prescribed fire and mastication techniques. Plant Ecology, 210(2) 305-315

Week 7: Digital Elevation Models

3-D Model (with DEM and hillshade layer)

3-D Model (DEM layer)

         













Extent (in decimal degrees):
Top: 38.44166            Bottom: 38.02722
Left: - 120.02138       Right: -119.31388
Coordinate System: North America GCS 1983
Datum: North American Datum 1983
           These models depict a small portion of the Sierra Nevada Mountain Range that lay on the eastern edge of California and the western edge of Nevada. This mountain range runs 400 mi North-to-South and 70 mi. east-to-west. It houses some amazing scenery and well-known attractions, like, Lake Tahoe, Mount Whitney, Yosemity National Park, Sequoia National Park, and Kings Canyon National Park. As you can see in the models, the Sierra Mountains' elevation gradually increases from east to west. The Sierra mountains are characteristic of California and offer great historical significance, as when the western coast of North America was first being explored.

Week 5: Map Projections

Pre-Lab:
How many degrees does the equator span?  
360.799 decimal degrees
How many degrees does the northern- and southern-most graticules span?
180.356 decimal degrees
These degrees represent the total distance in decimal degrees around latitudinally and longitudinally.
Distance from Washington to Kabul: 146.287 decimal degrees 
In the Mercator Projection: 
Alaska is not bigger than Brazil. 
Alaska is not bigger than Greenland.
Distance from Washington to Kabul: 16,289.05 km

        
          Map projections are essential when moving from the 3-D real world to 2-D projections of that world. When moving from 3-D to 2-D attributes of the real world are distorted,  and certain map projections can preserve certain metric properties, but not all. It would be impossible for one map to maintain all the same attributes and metric properties as the real world. 
         Map projections are significant because they are necessary to make maps, and it is essential to understand which map projections are being used while reading a map to fully understand it. In order to move from the real world and into the conceptual world, map projections are needed to relate the real world, a sphere, into a flat surface. And while reading a map, one should understand the effects certain map projections can have It would be illogical to read a map with a conformal projection when trying to determine the size of an area, or the distance between areas. In conformal maps above, there is a 3,000 mile difference between the distances measured between Washington and Kabul of each map, meaning that these maps, which maintain bearing and not local distance, would not be accurate it measuring distance.
          The perils of map projections is that all the attributes and metric properties of the real world are not maintained. This is an inevitable fact of map projections. Geographical information is lost in the transition from real world to maps. As with the Equidistant Conic projection, equidistant parallels are maintained, while area, size, and shape are compromised. Thus it becomes important for mapmakers to carefully choose the proper projection for their map. And it is equally important for the map reader to understand the effects of map projections.
          Map projections, though distorting real world data, are necessary to create maps. Map projections allow the three dimensional world to be scaled down into a flat, manageable surface. It also allows us to manipulate data. A skilled cartographer would also be able to cleverly manipulate a map and its readers. Maps, and their necessary map projections, offer cartographers a powerful tool. Though distorted maps are not ideal, they are what we are capable of making. Besides, to remedy a distorted map, multiple maps can be used, each preserving different properties.


         

Week 4: ArcGis

          First-time users trying to use ArcMap will most likely find themselves lost in the multiple toolbars, numerous buttons, and infinite possibilities that come with the software. My first experience using ArcMap with the tutorial was like a blind man following a single rope through the city of Los Angeles. Blindly following the tutorial, I felt like I learned the most when I couldn't edit the "Schools" data frame and had to improvise, remaking the data frame with accessible data layers. And although the tutorial was rather lengthy, after only one run-through it was obvious that what the tutorial went through was only a scratch on the surface of all the possibilities of ArcMap.
          The complexity of ArcMap can be its downfall, especially for novices. There were so many tasks, tools, and toolbars that it was overwhelming. I found myself lost in all the buttons available, though I'm sure a well experienced cartographer could easily navigate through the numerous buttons. The only other major problem I experienced while using ArcMap was the lag time in displaying a data frame. While zooming in and out, and while panning through the map in a zoomed in view, there was some lag time in displaying the proper image. The panning tool was also difficult to use. I would click elsewhere on the map by accident and it would automatically focus on that point. I for one, found that annoying. Luckily, advancement in computer technology can easily minimize that lag time. The overwhelming complexity and delay of the software can be remedied with experience with the software and advancement in technology.
          Ironically, the great thing about ArcMap was also its complexity. Expecting a simple cartographic program, it was very surprising that ArcMap also entailed statistical data and spatial analysis as well as data editing. Data frame layers were not simple images, but held specific data as a whole and for each attribute. Amazingly, ArcMap was able to use the underlying data of each layer for editing and analysis. This aspect of ArcMap may have been the only good thing that I encountered while doing the tutorial but I'm sure that there are countless possibilities and vast potential to the software.
          The complexity of ArcMap is both its strength and weakness. ArcMap is a very thorough geographical tool. It has so much potential that I only know a fraction of. Its ability to analyze, edit, and carry underlying data is a profound tool. The downside is that the software can be a little slow and overwhelmingly complex. Multiple toolbars, numerous buttons, and unending number of tasks and possibilities can make the software difficult to learn and use.  ArcGis can be a powerful tool after first learning how to use it properly and efficiently.