Wednesday, March 17, 2010

Final: Proximity of Fast Food Restaurants to Schools

Fast Food Restaurants Near Schools Presents a Public Health Problem

Introduction:

The county of Los Angeles should pass an ordinance forbidding the placement of fast food chains within one-half mile of any middle, intermediate, preparatory, or high school. For many years now, childhood obesity has been an increasing epidemic throughout America. In Los Angeles, this trend is no different.

This analysis will attempt to answer a basic question. I will analyze whether middle and high schools are especially susceptible to a “clustering” of fast food establishments. Are fast food joints generally within walking distance of schools?

There are numerous limitations in this project. For instance, it is difficult and unnecessary to geocode and include every single fast food chain location. I have chosen a sample of six fast food chains that I feel offer an exceptional sample size and distribution for the county of Los Angeles. Further, it is difficult to define “fast food” and discern this definition from unhealthy food in general. For this project, “fast food” will be defined by restaurants that provide extremely quick access to, for the most part, very unhealthy hamburgers, French fries, and other fried foods. Sandwich joints such as Subway and Quiznos are excluded, as they offer a much more healthy array of choices.


Method:


As evidence of this problematic trend, I have conducted and provided GIS evidence below. School data was gathered from UCLA’s GIS data repository. The original geocoded school data was from the Geographic Names Information System (GINIS), the Federal Government’s repository of location information. I then chose to record the addresses of six of the largest fast food chains in the nation. I recorded addresses for 10 Arbys restaurants, 54 Burger King restaurants, 27 Carls Junior restaurants, 169 Jack in the Box restaurants, 103 KFC restaurants, and 259 McDonalds restaurants. I found all of these exact addresses on the websites of the respective fast food chains, and then created an address locator based on a Los Angeles County shapefile. The source of the Los Angeles County shapefile is the 2003 Tele Atlas Dynamap. The locations of the above 622 fast food restaurant locations were then geocoded on the GIS.

The school data was carefully analyzed, and only middle and high schools were included in the final GIS. In the analysis, only schools including the key words “middle,” “junior high,” “intermediate,” “preparatory,” “academy,” and “high” school were placed on the map. All others were excluded. Most of the excluded schools were elementary, primary, and indistinguishable schools. In total, the final GIS includes 546 middle and high schools. I have chosen to focus purely on middle and high schools because it is these students that have the best access to transportation and money. Many middle and high school students walk home, whereas elementary age children are generally picked up by parents or caregivers after school. Also, many high school students work after-school jobs, leading to excess income that can easily be spent on fast food.

To conclude my analysis, I used a buffer analysis to discern which schools were located in close proximity to fast food restaurants. A one-half mile buffer was placed around all 546 middle and high schools. I also placed a one quarter mile buffer for more detailed analysis.


Results:


The below GIS analysis shows most of Los Angeles County, the 546 middle and high schools, along with the exact locations of the 622 fast food locations.



From my buffer analysis, there are 106 McDonalds restaurants contained within the one-half mile school buffer. Further, there are 48 KFC restaurants, 7 Arbys restaurants, 77 Jack in the Box restaurants, 29 Burger King restaurants, and 14 Carls Junior restaurants. In total, 281 of the 622 fast food restaurants are situated within a proximity of one-half mile of the 546 middle and high schools.

However, it is difficult to discern valuable information from a GIS of such an extensive area. I have created multiple insets of select regions of Los Angeles County that illustrate the same data in greater detail. Also in the following maps I have added a .25 mile buffer around every school, to enhance the detail. First off, I have created a map of the Santa Monica coastal region.



From looking at this map, it is clear that fast food restaurants are not concentrated in this region. However, almost every food location is within easy walking distance of a school. Olympic High School has an Arbys and a Jack in the Box within the quarter mile buffer. Santa Monica High School, Webster Middle School, and University Senior High School encounter similar situations. In the next map, we examine Torrance and Redondo Beach.



Bishop Montgomery High School located in the middle-left of the map is across the street from a Burger King, and is easily within walking distance of a McDonalds and a Jack in the Box. Almost every fast food joint in this inset has chosen a location within half a mile of a school. While there are numerous exceptions, there is an undeniable trend. Next we will examine a map of Van Nuys.



The trend in Van Nuys and the San Fernando Valley is not quite as evident, in fact in some areas it does not appear to exist at all. However, we still observe instances where fast food restaurants are located dangerously close to middle and high schools. Canoga Park High School is situated across the street from an Arbys. Taft Senior High School is located very near to a Jack in the Box. Even though the trend is not as evident in this map, there is a fast food joint within easy walking distance of every middle and high school shown. Next we will analyze South Central Los Angeles.



On the whole, it appears as though fast food restaurants have chosen not to open chains in South Central. This is completely opposite the effect noticed in other regions of the county. Yet, the trend can still be recognized, especially near Compton High School. A McDonalds is conveniently located within walking distance of Compton High School, Roosevelt Middle School, and Brethren High School. While the fast food joints are not as prevalent, the trend can still be recognized. Next we will analyze the West side of Los Angeles.



Fast food restaurants are incredibly prevalent in this region of the county. Almost every middle and high school shown on this map is situated near a fast food restaurant. In many cases, multiple fast food chains reside within the half and quarter mile buffers I have established. This map demonstrates the many public health concerns involving the proximity of schools to fast food chains. Our final map of Hollywood will further amplify this growing problem.



This map of the Hollywood region appears very similar to the map of West Los Angeles. Once again, the general trend is observed. Fast food restaurants consciously operate within walking distance of schools. Cutler Academy and Virgil Middle School are within half a mile of 5 of the 6 fast food chains I have chosen to analyze. In fact, KFC has 2 locations within half a mile of Virgil Middle School. Students who attend school in this region have ample fast food restaurants to choose from.


Conclusion and Discussion:


It is important to note that I have only chosen 6 of the most popular fast food chains to analyze. While these provide an excellent sample size, there are dozens of other chains, each with locations near middle and high schools. After conducting the GIS buffer analysis, it becomes clear that fast food chains prefer to situate themselves near schools to feed hungry students after school. It makes complete economic sense for these corporations.


Over the past few decades, student-age children have consumed increasing amounts of unhealthy foods from fast food establishments. Approximately three out of every ten children consume fast food for at least one meal on a daily basis. Dietary lifestyles such as these are unhealthy, as most fast food is consistently associated with dangerous fat and caloric intake. Further, a fast food diet lacks fruits and vegetables, leading to decreased intakes of iron, fiber, and other vital vitamins. Children that rely on a fast food diet are far more susceptible to obesity and as a result, diabetes (especially type II diabetes). The best way to address this growing problem is to focus on the dietary environment that schoolchildren are exposed to on a daily basis. It is incredibly important that children receive a balanced diet, and daily fast food consumption fails to supply this requirement.


The County of Los Angeles should seriously consider a proposition to prevent any new fast food chain from opening within one half mile of any middle or high school.


Sources:


www.jackinthebox.com

www.mcdonalds.com

www.arbys.com

www.burgerking.com

www.carlsjr.com

www.kfc.com

Wednesday, March 10, 2010

Final Quiz

1. Most Populous Countries

1. China (greatest population)
2. India
3. United States
4. Indonesia
5. Russia
6. Brazil
7. Pakistan
8. Japan
9. Bangladesh
10. Nigeria

2. 3 Most Populous Countries in Africa

1. Nigeria (most populated)
2. Egypt
3. Ethiopia

3. 5 Countries of South America with the Lowest Population

5. Ecuador (lowest population)
4. Chile
3. Venezuela
2. Peru
1. Argentina (greatest population of the bottom 5)

4. How many rivers are in the Amazon River System?

15 Rivers

5. What cities are within 500 km of the Amu Darya and Syr Darya rivers?
(in no particular order)
Leninobod
Jalabad
Zareh Sharan
Turgay
Zhezkazgan
Taldykorgan
Kyzylorda
Almaty
Bishkek
Talas
Karakol
Nukus
Shymkent
Dashkhovuz
Urgench
Naryn
Tashkent
Namangan
Andizhan
Osh
Gulistan
Fergana
Dzhizak
Navoi
Bukhara
Samarkand
Kashi
Chardzhev
Karshi
Dushanbe
Ashgabat
Kulob
Qurghonteppa
Mary
Termez
Feyzabad
Taloqan
Konduz
Mazar-E Sharif
Sheberghan
Aybak
Baghlan
Meymaneh
Mahmud-E Eraqi
Charikar
Qal eh-ye
Asadabad
Bamian
Mehtar Lam
Kabul
Chaghcharan
Mayda Shahr
Srinagar
Peshawar
Baraki Barak
Islamabad
Rawalpindi
Gardez
Ghazni
Dzhambul

6. To the nearest 100,000 what is the total population of countries within 300 km of Iran?

516,500,000

7. Most and Least populated landlocked countries?

Least Populated = Vatican City
Most Populated = Ethiopia

8. Identify all countries within 300 kilometers of Veszprem, Hungary.

Poland
Czech Republic
Slovakia
Austria
Slovenia
Hungary
Romania
Croatia
Bosnia & Herzegovina
Yugoslovia

9. Which country has the 4th smallest area?

Tuvalu

10. What countries border Chad?

Libya
Niger
Sudan
Nigeria
Central African Republic
Cameroon

Bonus:

K
T
C
U
S
T
C

Tuesday, March 9, 2010

Week 9: Interpolation








As of March 3, rainfall totals measured at most of the Los Angeles weather stations was higher than the seasonal normal amount. This is especially significant as Spring is still almost a month away, and season-to-date rain totals are likely to further increase before the end of the rainy season. The interpolation graphs above illustrate the areas of Los Angeles that receive high and low precipitation totals. As can be observed, the season-to-date analysis and the normal seasonal totals are nearly identical, with the same stations measuring nearly identical amounts of rain. For instance in all six maps, it can be noticed that most rain falls in the mountains, with lower amounts falling in the high desert of Lancaster and the coastal regions, such as Santa Monica.

I find the process of interpolation to be particularly fascinating, and its wide-reaching effects are immediately noticeable. For instance, this lab project used real-world, real-time data to carry out a realistic analysis of Los Angeles rain totals. Interpolation is a method that uses data from certain geographical points, in this case rain totals. It then will use this data to fill in the gaps between points to illustrate a constant phenomenon. In this lab, I used the Inverse Distance Weighted (IDW) interpolation technique as well as the Kriging interpolation technique.

I believe that the IDW method is a more effective way of illustrating the pattern of rainfall totals in this circumstance. The IDW technique is heavily influenced by nearby points, and less influenced by data points at a greater distance. Los Angeles County is a compact region that does not cover extensive area, all of the data points are fairly close together. When comparing the IDW map and the Kriging map, the IDW output appears much more fluid and factual. The Kriging output is much more rigid and jumpy, almost as though it were unsure of its data predictions. While each technique is useful, the IDW method is superior in this particular situation.

Tuesday, February 23, 2010

Lab 7: Fire Hazard Map






Creating my fire hazard map of the Station Fire region was by no means an easy task. First, I had to track down all of the data. The primary components were vegetation data, which I found on the Cal Fire website, digital elevation data, which I found on the USGS seamless server, and the perimeter of the Station Fire. Once I had compiled all of these pieces of the puzzle, I placed each data set into the Arcmap document.

This is where the spatial analysis began. The first step was to create a hillshade of the original digital elevation model of the region. This hillshade would show in detail the physical geography of the region, including the peaks of the hills as well as the floor of the ocean. Next, I used spatial analysis to create a slope map of the region. This slope map would analyze which raster cells contained regions of extreme slopes, as well as those with minimal slopes. After analyzing this map, it became clear that the mountainous regions have high slopes, and the urban regions have minimal slopes. At long last, it was time to reclassify both the vegetation data as well as the slope data. Each of these data sets were reclassified based upon the NFPA standards provided in the tutorial.

After I had used the raster calculator to add together the reclassified slope data and the reclassified vegetation data, I produced a fire hazard map that showed which regions are most susceptible to a potential fire. As the final maps shows, the station fire region falls into the most dangerous category. Along the way, I encountered several challenges. For one, I was unsure how to reclass my vegetation data set. After collaboration, I discovered the most efficient way of completing this task. Also, many of my data sets were displayed in different projections, which often complicated my calculations and displays. Other than these minor complications, the entire spatial analysis project was relatively straight forward. I have definitely learned the real-world value of spatial analysis, and several of its most useful applications.

Wednesday, February 17, 2010

Lab 6: Suitability Analysis 1

Health and safety is a basic right that should be guaranteed to all individuals within the border of our state. No person should ever be physically or mentally endangered by poor and selfish policy decisions. However, ultimately, politicians and other local lawmakers must make controversial decisions, such as where to construct a toxic waste landfill. By no means is this a simple decision for anyone involved. Quite often, controversial infrastructure projects such as landfills fall victim to NIMBY opposition - Not In My Backyard. No resident desires to live within just miles of a potentially dangerous toxic waste dump. This is where GIS software can be used effectively. Suitability analysis can help lawmakers determine the best possible location to construct a toxic landfill, taking into consideration multiple variables at once.

This very problem is currently occurring in the small, Central Valley farm town of Kettleman City. Currently, Chemical Waste Management operates a toxic waste landfill 3.2 miles outside of the town center. Plans have been proposed to expand this toxic landfill, already the largest in the state. However, light has recently been shed upon several babies that have been born with birth defects. Residents claim that the town's close proximity to the toxic waste dump is to blame. In fact, just last year the dump disposed of 400,000 tons of waste, much of which was material known to cause cancer. As a result of complaints, expansion of the waste site have been halted pending the results of the investigation into birth defects.

It is in a situation such as this where suitability analysis can be used most effectively. Suitability analysis can help lawmakers and city planners determine the absolute best location to construct controversial infrastructure. Suitability analysis can be used to analyze elevation slopes, distance, soil drainage, flood zones, land coverage, and countless other factors. Several of these variables are displayed below in the final outcomes of the suitability analysis tutorial. Such a visualization can shed a new light on a controversial issue. GIS provides the opportunity to combine existing and unique data sets into comprehensible visualizations. Ultimately, it provides lawmakers a tool to analyze and critique growth coalitions.

In the Kettleman City example, suitability analysis could be used to analyze the long-lasting effects of a potential landfill expansion. However, suitability is best used when determining the ideal location of a brand new facility. In the Kettleman City example, the toxic waste landfill already exists, and is unlike to be moved from its present location. Optimally, suitability analysis would be used to determine a new location to move the existing facility to. In terms of the investigation into the birth defects, suitability analysis would be ineffective. While suitability analysis will not effectively analyze the birth defects of children, other features of GIS can plot and point out certain patterns in data.

However, suitability analysis and GIS in general can only attempt to sway public opinion one way or another. Ultimately, the location of controversial and unwanted infrastructure projects such as landfills are determined by the activism of the residents. Communities with higher affluence and higher education levels generally will be able to ward off unwanted facilities. These communities will happily promote and exemplify the NIMBY approach. Environmental justice must be solved at a higher level of public opinion than GIS can provide. Ultimately, however, landfills are a necessary public good, and thus cannot be ignored. Suitability analysis, exemplified below, can combine numerous physical geographic factors to decide an optimum location for a new landfill. Social factors must be solved separately.



***My stream buffers would not buffer correctly - at some point they combined into one buffer as opposed to multiple buffers.

Wednesday, February 3, 2010

Quiz 1: Medical Marijuana Dispenaries

The Medical Marijuana Debate: Should Dispensaries Operate within 1,000 feet of where children congregate?

After extensively reviewing the geographic data of the city of Los Angeles, I agree that under no circumstances should medical marijuana dispensaries be permitted to operate within 1,000 feet of where children congregate. The locations where children most frequently gather are school zones and recreation zones, such as parks. On the map below, I have used ArcGIS software to plot the city of Los Angeles. Within the confines of the city, I have clearly plotted every school and every designated recreation zone. Further, I have constructed a 1,000 foot buffer around each point of interest.



After examining the map, it becomes clear that there are hundreds of schools within the city of Los Angeles, not to mention the many recreation areas. These points of interest in the city should remain safe from the negative influences of illegal substances such as marijuana. Children, especially children at the impressionable high school age, should be protected from the temptation of such substances. It is the job of the Los Angeles City Council to ensure the safety and well-being of all Los Angeles city residents.

However, a 1,000 foot buffer zone will by no means eliminate the establishment of medical marijuana dispensaries. Referring back to the map, it is clear that while the school and recreation zone buffers eliminate many locations, they do not eliminate all locations. The city of Los Angeles, the second largest city in the United States, spans almost 500 square miles. This statistic, along with the aforementioned map, showcase the variability of possible locations that are far removed from the buffer zones. Los Angeles is immune from the issues of smaller cities, such as San Francisco, in which schools and parks are packed tightly together. Buffer zones are far more controversial in cities characterized by this.

Citizens in need of medical marijuana should continue to be able to fill their prescriptions at local dispensaries. Medical marijuana dispensaries should continue to receive operating permits. The above map proves that such dispensaries can easily operate outside of the 1,000 foot buffer zones. While some establishments will inevitably be forced to shut down or relocate, it is in the greater interest of the city as a whole to approve the removal of dispensaries within 1,000 feet of areas where children frequently congregate.

Ultimately, the cost of this initiative will fall primarily on those dispensaries that are forced to shut down or move. While this will be unfortunate for the businessman/woman, they will be able to find an alternate location to operate within the city. The above map showcases the many alternate locations available. Other groups who might be negatively affected are those who need to fill prescriptions, and may be forced to find a new dispensary. In contrast, this initiative will benefit the entire city and its residents as a whole. The negative influence and temptation for children will be removed. Parents will be able to safely take their children to parks without the fear of observing potheads wandering the streets. In a city as expansive as Los Angeles, there is no reason for marijuana outlets to operate in locations where children are often present. This initiative will, in the end, make the streets safer for all city residents.

In closing, the above map shows that medical marijuana dispensaries can operate in regions that are 1,000 feet away from school and recreation zones. I do not advocate shutting down and removing all dispensaries, just those that are a threat to our younger children.

Tuesday, February 2, 2010

Monday, January 25, 2010

Lab 3: Geocoding



As many can attest to, I am a serious coffee-drinker, oftentimes much too serious of a coffee drinker. Naturally, I chose to analyze the locations of certain coffee house locations throughout Los Angeles County. To analyze the spatial autocorrelation of these locations, I had to geocode the data using ArcGIS. The first task was to input 100 addresses into an Excel spreadsheet. In ArcGIS, I had to create a create an address locator based on the data of my Los Angeles County shapefile. After this step, I could then match my addresses to the map, and they would be clearly marked. I encountered several difficulties throughout this process. For one, many of my addresses were not recognized by the address locator. My shapefile may have been out of date, or the listed addresses may have simply been incorrect. Despite this problem, all of my addresses were eventually matched, and my geocoded GIS revealed some striking phenomena.

For this exercise, I thought that it would be fascinating to map and analyze which communities within Los Angeles are best served by Coffee Bean and Teal Leaf coffee house chain. As we can tell from the GIS, Coffee Bean explicitly chooses to focus on certain communities while neglecting others. For instance, the Coffee Bean chain represents itself very well in West Los Angeles, the San Fernando Valley, and Torrance, while much of South Central Los Angeles contains very few, if any, stores. It is clear that Coffee Bean has chosen its locations based on the affluence of the community that it serves. There are almost zero stores in the poverty-stricken communities of Compton and Watts, whereas it seems as though almost every block in Beverly Hills has multiple stores. It also becomes clear that the chain tends to only open branches on major streets. On the map, one can clearly notice such major streets as Wilshire Blvd, Ventura Blvd, and Sepulveda Blvd.

Working through this lab, I soon discovered the limitless possibilities of geocoding. In this lab for instance, I began with a serious question - Do coffee houses appear more frequently in affluent communities than in poorer communities? After finishing the geocoding, my map revealed my answer. In a broad sense, geocoding visually provides the answer to questions and hypotheses. It can be used as evidence, similar to what I have used my map for. Further, geocoding and GIS in general reveal patterns in data. While an excel spreadsheet filled with addresses is completely useless upon first glance, the manipulation of this data in software such as ArcGIS visually reveals the aforementioned patterns that can ultimately be used to answer countless serious questions. While my question may be simple, it is still legitimate, and GIS provided me an answer. With this lab, the many benefits and far-reaching influence of GIS software become apparent.

Below is my list of addresses:

ID NAME ADDRESS ZIP
1 Coffee Bean and Tea Leaf 801 W. 7th Street 90017
2 Coffee Bean and Tea Leaf 3183 Wilshire Blvd 90010
3 Coffee Bean and Tea Leaf 3726 S. Figueroa St 90007
4 Coffee Bean and Tea Leaf 670 S. Western Ave 90005
5 Coffee Bean and Tea Leaf 3810 Wilshire Blvd 90010
6 Coffee Bean and Tea Leaf 2081 Hillhurst Ave 90027
7 Coffee Bean and Tea Leaf 135 N. Larchmont 90004
8 Coffee Bean and Tea Leaf 209 S. Mednik Ave 90022
9 Coffee Bean and Tea Leaf 5555 Melrose Avenue 90038
10 Coffee Bean and Tea Leaf 6255 W. Sunset Blvd. 90028
11 Coffee Bean and Tea Leaf 260 S La Brea Blvd. 90036
12 Coffee Bean and Tea Leaf 7235 Beverly Blvd. 90036
13 Coffee Bean and Tea Leaf 5979 W. Third Street 90036
14 Coffee Bean and Tea Leaf 6922 Hollywood Blvd. 90028
15 Coffee Bean and Tea Leaf 7257 W Sunset Blvd 90046
16 Coffee Bean and Tea Leaf 7502 Melrose Ave 90046
17 Coffee Bean and Tea Leaf 6333 West 3rd Street 90036
18 Coffee Bean and Tea Leaf 700 Fair Oaks Ave 91030
19 Coffee Bean and Tea Leaf 8328 Wilshire Blvd. 90211
20 Coffee Bean and Tea Leaf 7915 W Sunset Blvd 90046
21 Coffee Bean and Tea Leaf 300 S La Cienega Blvd 90048
22 Coffee Bean and Tea Leaf 1200 N. Central Ave 91202
23 Coffee Bean and Tea Leaf 8500 Beverly Blvd. 90048
24 Coffee Bean and Tea Leaf 1500 Canada Blvd. 91208
25 Coffee Bean and Tea Leaf 8793 Beverly Blvd 90048
26 Coffee Bean and Tea Leaf 8735 Santa Monica Blvd. 90069
27 Coffee Bean and Tea Leaf 18 S Fair Oaks Ave 91105
28 Coffee Bean and Tea Leaf 8789 W Sunset Blvd. 90069
29 Coffee Bean and Tea Leaf 415 S. Lake Ave. 91101
30 Coffee Bean and Tea Leaf 9541 W. Pico Blvd. 90035
31 Coffee Bean and Tea Leaf 233 S. Beverly Dr. 90212
32 Coffee Bean and Tea Leaf 445 N. Beverly Drive 90210
33 Coffee Bean and Tea Leaf 160 N. Lake Ave 91101
34 Coffee Bean and Tea Leaf 10121 Riverside Drive 91602
35 Coffee Bean and Tea Leaf 10401 Venice Blvd. 90034
36 Coffee Bean and Tea Leaf 1940 Century Park E 90067
37 Coffee Bean and Tea Leaf 340 N. San Fernando Blvd. 91502
38 Coffee Bean and Tea Leaf 4444 Lankershim Blvd 91602
39 Coffee Bean and Tea Leaf 8550 Firestone Blvd. 90241
40 Coffee Bean and Tea Leaf 10401 Santa Monica Blvd. 90025
41 Coffee Bean and Tea Leaf 3470 S. Sepulveda Blvd. 90034
42 Coffee Bean and Tea Leaf 10800 W. Pico Blvd. 90064
43 Coffee Bean and Tea Leaf 3701 Ocean View blvd 91020
44 Coffee Bean and Tea Leaf 10897 W Pico Blvd. 90064
45 Coffee Bean and Tea Leaf 12050 Ventura Blvd 91604
46 Coffee Bean and Tea Leaf 8824 Sepulveda Blvd 90045
47 Coffee Bean and Tea Leaf 5300 Lankershim Blvd 91601
48 Coffee Bean and Tea Leaf 1500 Westwood Blvd. 90024
49 Coffee Bean and Tea Leaf 574 Hilgard Ave. 90024
50 Coffee Bean and Tea Leaf 11049 Santa Monica Blvd. 90025
51 Coffee Bean and Tea Leaf 10861 Le Conte ave 90024
52 Coffee Bean and Tea Leaf 950 Westwood Blvd 90024
53 Coffee Bean and Tea Leaf 12930 Ventura Blvd. 91604
54 Coffee Bean and Tea Leaf 1001 Gayley ave 90024
55 Coffee Bean and Tea Leaf 2675 Foothill Blvd. 91214
56 Coffee Bean and Tea Leaf 3601 E. Foothill Blvd. 91107
57 Coffee Bean and Tea Leaf 11727 W Olympic Blvd 90064
58 Coffee Bean and Tea Leaf 8601 Lincoln Blvd 90045
59 Coffee Bean and Tea Leaf 11913 W. Olympic Blvd. 90064
60 Coffee Bean and Tea Leaf 400 S. Baldwin Avenue 91007
61 Coffee Bean and Tea Leaf 4700 Admiralty Way 90292
63 Coffee Bean and Tea Leaf 4020 Lincoln Blvd 90292
63 Coffee Bean and Tea Leaf 7201 Greenleaf ave 90602
64 Coffee Bean and Tea Leaf 1644 Cloverfield Blvd 90404
65 Coffee Bean and Tea Leaf 14006 Riverside Dr. 91423
66 Coffee Bean and Tea Leaf 11698 W San Vicente Blvd 90049
67 Coffee Bean and Tea Leaf 3008 N Sepulveda Blvd 90266
68 Coffee Bean and Tea Leaf 2700 N Sepulveda Blvd 90266
69 Coffee Bean and Tea Leaf 2901 Main St. 90405
70 Coffee Bean and Tea Leaf 1413 Hawthorne Blvd. 90278
71 Coffee Bean and Tea Leaf 14440 Burbank Blvd 91401
72 Coffee Bean and Tea Leaf 200 Santa Monica Blvd 90401
73 Coffee Bean and Tea Leaf 321 Manhattan Beach Blvd. 90266
74 Coffee Bean and Tea Leaf 1133 Artesia Blvd. 90266
75 Coffee Bean and Tea Leaf 102 South Myrtle Avenue 91016
76 Coffee Bean and Tea Leaf 20301 Hawthorne Blvd. 90503
77 Coffee Bean and Tea Leaf 4105 Atlantic Ave 90807
78 Coffee Bean and Tea Leaf 702 E. Huntington Dr 91016
79 Coffee Bean and Tea Leaf 1227 Hermosa Avenue 90254
80 Coffee Bean and Tea Leaf 12560 Artesia Blvd. 90703
81 Coffee Bean and Tea Leaf 15278 Antioch St. 90272
82 Coffee Bean and Tea Leaf 21300 Hawthorne Blvd. 90503
83 Coffee Bean and Tea Leaf 3455 Sepulveda Blvd 90505
84 Coffee Bean and Tea Leaf 17301 Ventura Blvd. 91316
85 Coffee Bean and Tea Leaf 17840 Ventura Blvd 91316
86 Coffee Bean and Tea Leaf 1617 s Pacific Coast Hwy. 90277
87 Coffee Bean and Tea Leaf 6344 E Spring Street 90808
88 Coffee Bean and Tea Leaf 25345 Crenshaw Blvd. 90505
89 Coffee Bean and Tea Leaf 18505 Ventura Blvd. 91356
90 Coffee Bean and Tea Leaf 1212 n Bellflower Blvd 90815
91 Coffee Bean and Tea Leaf 19732 Ventura Blvd. 91364
92 Coffee Bean and Tea Leaf 20060 Ventura Blvd. 91364
93 Coffee Bean and Tea Leaf 4925 E. Second St. 90803
94 Coffee Bean and Tea Leaf 18010 Chatsworth Street 91344
95 Coffee Bean and Tea Leaf 6471 East Pacific Coast Highway 90803
96 Coffee Bean and Tea Leaf 5780 Canoga Ave. 91367
97 Coffee Bean and Tea Leaf 21851 Ventura Blvd. 91364
98 Coffee Bean and Tea Leaf 18705 Devonshire Street 91324
99 Coffee Bean and Tea Leaf 21909 Ventura Blvd 91364
100 Coffee Bean and Tea Leaf 6600 Topanga Canyon Blvd. 91303

Wednesday, January 13, 2010

Lab 1: ArcGIS Revisited

Exercise #1:



Exercise #2:



Exercise #3:

Exercise #4:



Exercise #5: Final Project