Propsal to Build Football Stadium at Drake Stadium Works Cited

Works Cited

Albertson, Patrick. "South Africa's Soundproof Stadium For the World Cup | Popular Science." Popular Science | New Technology, Science News, The Future Now. Web. 12 Mar. 2011. <http://www.popsci.com/science/article/2010-05/south-africas-soundproof-stadium>.

Crowe, Jerry. "Ucla On Campus Stadium - MORNING BRIEFING : CROWE'S NEST : UCLA Stadium Plan Quickly Became a Political Football - Los Angeles Times." Featured Articles From The Los Angeles Times. 16 Nov. 2009. Web. 10 Mar. 2011. <http://articles.latimes.com/2009/nov/16/sports/sp-crowe16>.

"Damping of Sound Level with Distance - Decibel DB Damping Calculation Calculator Distance versus Sound Reduction Free Field - Decrease Drop Fall in Sound over Distance versus DB Sound at Different Distances Microphone Calculator Distance Drop Ratio - Sengpielaudio Sengpiel Berlin." Forum Zur Mikrofonaufnahme Und Tonstudiotechnik ♪♫♪ Tontechnik Eberhard Sengpiel - Sengpielaudio = Sengspielaudio Und Sengpiel Ist Sengspiel Sengpielaudio.de Ebs Elektro-Akustik Audio Ausbildung Lehre Studio Tips Tipps Mikrofone Tonaufnahme Berlin. Web. 9 Mar. 2011. <http://www.sengpielaudio.com/calculator-distance.htm>.

Dolan, Jack. "Pauley Pavilion Renovation - UCLA Diverts Student Fees from Pauley Pavilion Renovation - Los Angeles Times." Featured Articles From The Los Angeles Times. 07 Apr. 2010. Web. 12 Mar. 2011. <http://articles.latimes.com/2010/apr/07/local/la-me-student-funds8-2010apr08>.

"NPC Law Library: Los Angeles Noise Ordinance." Noise Pollution Clearinghouse, Quieting Noise Pollution. Web. 11 Mar. 2011. <http://www.nonoise.org/lawlib/cities/losangel.htm>.

"Rose Bowl (stadium)." Wikipedia, the Free Encyclopedia. Web. 10 Mar. 2011. <http://en.wikipedia.org/wiki/Rose_Bowl_(stadium)#UCLA_Bruins_Football_home_stadium>.

"Stanford Stadium." Wikipedia, the Free Encyclopedia. Web. 9 Mar. 2011. <http://en.wikipedia.org/wiki/Stanford_Stadium>.

Propsal to Build Football Stadium at Drake Stadium Write Up

            Inroduction:   

In 1966 UCLA almost saw itself building a brand new football stadium on the location where Drake Stadium now is.  It could have become a legitimate powerhouse, riding the success of a Rose Bowl win the same year, as well as follow closely behind the building of Pauley Pavilion the year before.  No longer would UCLA be one of only a few major programs in the country required to go off campus for football games.  However, the political clout of only a few very wealthy and powerful people completely blocked the entire project (Crowe 2009).

The entire operation was shot down in 1966, however, as residents of Bel Air and Beverly Hills were able to prevent the building of the stadium with help from Governor Edmund Brown and University of California regent Dorothy Chandler.  Because Brown feared that he would lose endorsements from the wealthy residents of West Los Angeles, and Chandler felt indebted to the residents, the three interest groups were able to combine forces to put a hold on the stadium because of concerns of traffic and sound levels in the area (Crowe 2009).  I will attempt to show that in fact the stadium would be easy to build without affecting too much of the campus, that traffic and parking, while an issue, could be mitigated, and finally that the sound issue really is not an issue at all.

            Methods:

            I made three maps to solve the problem, spatial analyzing a shapefile of UCLA. The first map consists of where to put the stadium, how large it would need to be, and what would be affected or removed in the building of the stadium.  To do this I compared the needed square footage of similar sized stadiums in order to place a buffer around the current Drake Stadium to simulate the new stadium.  I also used the editing tool to show what would need to be removed.  The second map deals with the traffic and parking issue.  I placed a multiple ring buffer around each parking structure to assess where the best place to put a new structure would be, the minimum distance away being 50m, and the preferred distance being 100m.  The final map shows the projected sound levels based on both the city ordinances for how loud public events can be, and also for how far the estimated distance would be for the average sounds of a football game would need to dissipate to reach those levels.  To do this I created a multiple ring buffer around the stadium showing what the most likely distance would be, but also the absolute maximum distance for the loudest game in perfect conditions for sound to travel.

            Results:

            The project was in fact quite possible.  Stanford recently built a stadium very comparable to the one that would be built on the UCLA campus.  Their stadium was built for a capacity of 50,000 people, while the UCLA stadium would be about 45,000 people.  Based on projected square footage of the Stanford stadium I was able to make a similar projection over Drake Stadium that takes up comparable space.  It would easily fit, and would only require slight modifications to attributes already in place on the campus (Stanford Stadium).  Bruin Walk would most likely need to be modified, but only slightly.  Most of the area is already available, and the only real modification would be a reduction in size of the intramural field, a sacrifice that I believe almost every student at UCLA would be willing to make.

            The other issue that would come up would be cost.  Stanford was able to build its facility at a cost of $90 million in 2006 (Stanford Stadium).  That is recent enough that it does not really have to be adjusted for inflation.  That money could easily be raised, as the renovation of Pauley is projected to cost $135 million (Dolan 2010).  The building of our stadium could cost more than Stanford’s but even so, when used as a model, cost would not be an issue. 

This also comes in light of the fact that we already have to pay $1.5 million a year to use the Rose Bowl (Rose Bowl).  That is a considerable amount of money that we could get back every year, on top of the fact that the facility could be used for far more than just football, which is all that Rose Bowl is used for.  Soccer and Track and Field would also benefit from a new stadium, and it could be used as the venue for many other events that occur on campus, increasing revenue across the board.

                        These issues may have been over exaggerated however.  The sound issue could easily be overcome, and is actually not nearly the issue it was originally presented as.  In my third map I have produced projections showing two layers of those affected by the sound that would be created during football games.  In the city of Los Angeles, sound ordinances state that noise levels shall not exceed 95Db for any public entertainment without proper certification (NPC Law Library).   Based on calculations for the dampening of sound levels across space, on a normal game day the distance removed to reach 95Db would be about 300m.  At its highest levels it would not exceed 500m. (sengpielaudio.com)  Based on the projection, this would affect almost exclusively the Bel Air golf course and only a few other buildings.  The complaint can hardly be sustained by most of the surrounding community. 

            Other modifications could be taken as well.  Seeing as there are only 6 home games a year, it would be incredibly simple to obtain the necessary documentation.  If it was truly a horrendous issue, the facility could be outfitted with sound dampening technology as used by South Africa during the 2010 World Cup (Albertson 2011).  This added structure is incredibly effective, and would reduce the distance away from the stadium that exceeds 95Db to less than 100m.  This technology was not available in 1966 and would increase the chances that the building of a stadium would be approved.

            The other major point that killed the original proposition was the traffic that would be created during games (Crowes 2009).  Again, seeing as it would be only six times a year, this is not a major issue.  But even so, I have taken steps to dramatically decrease traffic, while simultaneously increasing parking to facilitate the large amount of cars that would come to games.  I originally set up buffers around present parking structures to find an acceptable location away from already in place parking structures to reduce congestion in certain areas.  The minimum distance acceptable I decided was 50m, with a more preferable distance of 100 m.  I created both buffers, but neither one resulted in acceptable locations because UCLA is already such a dense campus there is little space that would be acceptable for a new parking structure, especially not one of the scale required to meet the needs of football games.

            Because of the space limitations I moved on to find already built parking structures that could be upgraded to facilitate large influxes of fans on game days.  The criteria needed were ones that are above ground, fairly well spaced from each other but still close to the stadium, and easily accessible.  The four that I chose are well spread out to also reduce the traffic congestion and minimize the complaints those living in the surrounding areas.  They are also close to major roads and not in the heart of the campus where congestion would become even worse.  They are right off of Veteran Avenue, Gayley and Strathmore Avenue, and Hilgard Avenue, the four major streets leading into UCLA that could handle an increase in traffic should one occur.  Finally, they are all above ground, with three of them already being multi-level structures.  Because of the cramped nature of the UCLA campus these could easily meet the needs of football games if there were to be increased in size.    

            Conclusion:

            I realize there are multiple other factors that go into the building of a stadium, and a lot of politics involved.  The school and the student body might even decide that they simply do not want a stadium on campus, making this all a moot point.  I simply wanted to display the fact should the school choose to take up the initiative; a stadium on the UCLA campus is more than possible.  It could easily fit in the size allotted, the sound would not be as large of a problem as originally assumed, especially with modern technology, and the issue of parking and traffic could be mitigated through intelligent use of space.  All in all the logistics of this endeavor are quite possible, and thanks to the analysis on ArcGIS I was able to succinctly show this.

Propsal to Build Football Stadium at Drake Stadium

 

 

           In 1966 UCLA almost saw itself building a brand new football stadium on the location where Drake Stadium now is.  It could have become a legitimate powerhouse, riding the success of a Rose Bowl win the same year, as well as follow closely behind the building of Pauley Pavilion the year before.  No longer would UCLA be one of only a few major programs in the country required to go off campus for football games.  However, the political clout of only a few very wealthy and powerful people completely blocked the entire project (Crowe 2009). 

            The project was in fact quite possible.  Stanford recently built a stadium very comparable to the one that would be built on the UCLA campus.  Their stadium was built for a capacity of 50,000 people, while the UCLA stadium would be about 45,000 people.  Based on projected square footage of the Stanford stadium I was able to make a similar projection over Drake Stadium that takes up comparable space.  It would easily fit, and would only require slight modifications to attributes already in place on the campus (Stanford Stadium).  Bruin Walk would most likely need to be modified, but only slightly.  Most of the area is already available, and the only real modification would be a reduction in size of the intramural field, a sacrifice that I believe almost every student at UCLA would be willing to make.

            The other issue that would come up would be cost.  Stanford was able to build its facility at a cost of $90 million in 2006 (Stanford Stadium).  That is recent enough that it does not really have to be adjusted for inflation.  That money could easily be raised, as the renovation of Pauley is projected to cost $135 million (Dolan 2010).  The building of our stadium could cost more than Stanford’s but even so, when used as a model, cost would not be an issue. 

This also comes in light of the fact that we already have to pay $1.5 million a year to use the Rose Bowl (Rose Bowl).  That is a considerable amount of money that we could get back every year, on top of the fact that the facility could be used for far more than just football, which is all that Rose Bowl is used for.  Soccer and Track and Field would also benefit from a new stadium, and it could be used as the venue for many other events that occur on campus, increasing revenue across the board.

            The entire operation was shot down in 1966, however, as residents of Bel Air and Beverly Hills were able to prevent the building of the stadium with help from Governor Edmund Brown and University of California regent Dorothy Chandler.  Because Brown feared that he would lose endorsements from the wealthy residents of West Los Angeles, and Chandler felt indebted to the residents, the three interest groups were able to combine forces to put a hold on the stadium because of concerns of traffic and sound levels in the area (Crowe 2009).

            These issues may have been over exaggerated however.  The sound issue could easily be overcome, and is actually not nearly the issue it was originally presented as.  In my third map I have produced projections showing two layers of those affected by the sound that would be created during football games.  In the city of Los Angeles, sound ordinances state that noise levels shall not exceed 95Db for any public entertainment without proper certification (NPC Law Library).   Based on calculations for the dampening of sound levels across space, on a normal game day the distance removed to reach 95Db would be about 300m.  At its highest levels it would not exceed 500m. (sengpielaudio.com)  Based on the projection, this would affect almost exclusively the Bel Air golf course and only a few other buildings.  The complaint can hardly be sustained by most of the surrounding community. 

            Other modifications could be taken as well.  Seeing as there are only 6 home games a year, it would be incredibly simple to obtain the necessary documentation.  If it was truly a horrendous issue, the facility could be outfitted with sound dampening technology as used by South Africa during the 2010 World Cup (Albertson 2011).  This added structure is incredibly effective, and would reduce the distance away from the stadium that exceeds 95Db to less than 100m.  This technology was not available in 1966 and would increase the chances that the building of a stadium would be approved.

            The other major point that killed the original proposition was the traffic that would be created during games (Crowes 2009).  Again, seeing as it would be only six times a year, this is not a major issue.  But even so, I have taken steps to dramatically decrease traffic, while simultaneously increasing parking to facilitate the large amount of cars that would come to games.  I originally set up buffers around present parking structures to find an acceptable location away from already in place parking structures to reduce congestion in certain areas.  The minimum distance acceptable I decided was 50m, with a more preferable distance of 100 m.  I created both buffers, but neither one resulted in acceptable locations because UCLA is already such a dense campus there is little space that would be acceptable for a new parking structure, especially not one of the scale required to meet the needs of football games.

            Because of the space limitations I moved on to find already built parking structures that could be upgraded to facilitate large influxes of fans on game days.  The criteria needed were ones that are above ground, fairly well spaced from each other but still close to the stadium, and easily accessible.  The four that I chose are well spread out to also reduce the traffic congestion and minimize the complaints those living in the surrounding areas.  They are also close to major roads and not in the heart of the campus where congestion would become even worse.  They are right off of Veteran Avenue, Gayley and Strathmore Avenue, and Hilgard Avenue, the four major streets leading into UCLA that could handle an increase in traffic should one occur.  Finally, they are all above ground, with three of them already being multi-level structures.  Because of the cramped nature of the UCLA campus these could easily meet the needs of football games if there were to be increased in size.

            I realize there are multiple other factors that go into the building of a stadium, and a lot of politics involved.  The school and the student body might even decide that they simply do not want a stadium on campus, making this all a moot point.  I simply wanted to display the fact should the school choose to take up the initiative; a stadium on the UCLA campus is more than possible.  It could easily fit in the size allotted, the sound would not be as large of a problem as originally assumed, especially with modern technology, and the issue of parking and traffic could be mitigated through intelligent use of space.

Works Cited

Albertson, Patrick. "South Africa's Soundproof Stadium For the World Cup | Popular Science." Popular Science | New Technology, Science News, The Future Now. Web. 12 Mar. 2011. <http://www.popsci.com/science/article/2010-05/south-africas-soundproof-stadium>.

Crowe, Jerry. "Ucla On Campus Stadium - MORNING BRIEFING : CROWE'S NEST : UCLA Stadium Plan Quickly Became a Political Football - Los Angeles Times." Featured Articles From The Los Angeles Times. 16 Nov. 2009. Web. 10 Mar. 2011. <http://articles.latimes.com/2009/nov/16/sports/sp-crowe16>.

"Damping of Sound Level with Distance - Decibel DB Damping Calculation Calculator Distance versus Sound Reduction Free Field - Decrease Drop Fall in Sound over Distance versus DB Sound at Different Distances Microphone Calculator Distance Drop Ratio - Sengpielaudio Sengpiel Berlin." Forum Zur Mikrofonaufnahme Und Tonstudiotechnik ♪♫♪ Tontechnik Eberhard Sengpiel - Sengpielaudio = Sengspielaudio Und Sengpiel Ist Sengspiel Sengpielaudio.de Ebs Elektro-Akustik Audio Ausbildung Lehre Studio Tips Tipps Mikrofone Tonaufnahme Berlin. Web. 9 Mar. 2011. <http://www.sengpielaudio.com/calculator-distance.htm>.

Dolan, Jack. "Pauley Pavilion Renovation - UCLA Diverts Student Fees from Pauley Pavilion Renovation - Los Angeles Times." Featured Articles From The Los Angeles Times. 07 Apr. 2010. Web. 12 Mar. 2011. <http://articles.latimes.com/2010/apr/07/local/la-me-student-funds8-2010apr08>.

"NPC Law Library: Los Angeles Noise Ordinance." Noise Pollution Clearinghouse, Quieting Noise Pollution. Web. 11 Mar. 2011. <http://www.nonoise.org/lawlib/cities/losangel.htm>.

"Rose Bowl (stadium)." Wikipedia, the Free Encyclopedia. Web. 10 Mar. 2011. <http://en.wikipedia.org/wiki/Rose_Bowl_(stadium)#UCLA_Bruins_Football_home_stadium>.

"Stanford Stadium." Wikipedia, the Free Encyclopedia. Web. 9 Mar. 2011. <http://en.wikipedia.org/wiki/Stanford_Stadium>.

      When doing this lab the actual lab was incredibly easy, but accumulating the data and processing it was the difficult part, which seems to be the common trend in GIS.  In doing the maps though i discovered just how different IDW and Splining truly are.  IDW attempts to generalize the entire map, creating a common thread throughout. Splining seems to overestimate values.  The differences in the two styles is very apparent when looking at the northeast corner of the map.  In IDW, where generalizations are made and values tend to lean toward the middle, the precipitation is believed to be between 12 and 16 inches a year, where as the Splining method values the area to be below 4 inches a year becuase it overestimates and leans toward extremes.  The massive difference between the two values shows just how inconsistent the entire method is, and how being able to display multiple methods can help realize what the true values possibly are.
     Another major issue is the bias towards areas with more points, which makes sense.  When there are more values it is easier to make assessments, but it also creates problems, for example the large discrepancy with the northeast corner of the map.  With IDW, because a majority of the values were in the 12-16 range, it valued any area without too many points to be in that general area.  Spline seemed to favor the nearest point in making the decision.  All in all, the major discrepancies make it necessary to both collect as much data as possible and understand the differences between the methods.
IDW- generalizes
Spline- overestimates
areas with few receptors will be over-generalized.  bias towards areas with multiple points.
compare and contrast styles of idw and spline

Fire Probability

 

     This was probably one of the most straightforward and  simple labs we have had this quarter, if everything had gone smoothly.  I was able to get the fuel layer from http://frap.cdf.ca.gov/data/frapgisdata/download.asp?spatialdist=2&rec=fmod, the elevation layer from  http://seamless.usgs.gov/website/seamless/viewer.htm, and the fire zone coverage layer from the the UCLA website for geography 7.  That was the easy the part. What normally would have only taken me a few hours to do the tutorial and then my own analysis ended up taking multiple hours because of all of the problems I encountered.  I first had difficulty converting the elevation map into percent.  I got ridiculously high values that I might have been able to work with but were not in fact correct and may have tripped me up at later points in the project.  To fix this I had to convert the elevation layer from the projection it was in to UTM zone 11 which proved to be the most difficult part of the entire venture. The file may have been to large, but every time I attempted to convert the layer, ArcGIS simply shut down.  This happened multiple times on multiple computer.  I eventually had to reload the file and attempt the entire process over from scratch.  

     Once I was finally able to convert the file and actually start the project, I had difficulty finding the metadata to reclassify the fuel values.  Because the values were not simply given to me as in the tutorial, I also had to more or less guess at what the values should be and hope that the values were correct.  Fortunately i was able to find a separate layer online that had already classified the values, and my own interpretation was fairly similar, giving me confidence that I had adequately valued the fuels.  Once I had the values all accumulated I ran into even more problems in attempting to use the Raster Calculator and determine the ultimate risk of fire.  The first couple of times I attempted to find the values, they did not come out as classified values but were rather discrete, which was not correct and did not give me anything to work with.  After manipulating a few aspects I was finally able to get everything together and finish the lab.  All in all this should not have taken me more than 3 hours to do everything, but because of the multiple obstacles it took more than twice as long as that.

     Ultimately all of the issues probably taught me more about ArcGIS than the actual lab did.  I had to deal with so many issues on my own that I learned two things.  First, how to deal with those specific issues in the future should they arise.  The second, and more important revelation, is that I can in fact figure out some of these problems on my own.  The fact that I do in fact have a bit of a GIS toolbox is reassuring, even if it is still rather basic.  I hope that in the future similar projects will not take quite as long, but if they do at least I can be assured that I will probably learn valuable skills in the process.  

     

Landfill Placement Analysis

                 

     The ability to assess the suitability of certain locations allows for difficult decisions to be looked at from a more concrete point of view as opposed to making guesses on what would most likely be the most desirable site.  By using cut and dry numbers the choice is removed and replaced by an obvious answer.  The maps allows for subjectivity to be removed and an objective decision to be made.

    The weighted values option also makes a huge difference, especially in this case.  Not all variables are equal, and in this case, when the weighted option was developed it made a completely different map.  Certain variables are much more important than others, especially when choosing the location of a hazardous waste site that could negatively effect whatever location was chosen. 

   The weighted options made a huge difference in the development of the map, which is a major improvement.  As we saw with the article, the waste site is incredibly hazardous, causing birth defects and cancer in the surrounding areas.  The safety of those around the area is a large component in choosing such a huge project.  The weighting of options could save people's lives who would have been put in jeopardy if the project had not decided that certain components were more valuable than others.

    Also, the multiple variables going into the project makes this a complex and difficult project.  The raster calculator makes it much simpler and quicker to assess the potential of every single point within the entire county.  When there are such major issues with landfills, as they take up space, lower the value of the area and affect the health of the inhabitants in the area, the ability to include and process so many different aspects makes the project much less scary, as the consequences of choosing incorrectly could be incredibly detrimental.  

    Overall, this program makes the work much easier.  Every variable is accounted for, every possibility is assessed, and the choice becomes much less risky when viewed from every angle.  Ultimately, the ability to choose the safest possible location could save money, resources, and possibly even lives.

Medical Marijuana

 

     By creating this ordinance, a large number of dispensaries are found to be outside of compliance, which will force many of them to close, making this decision a negative one.  Due to time constrictions I was unable to accumulate a large sample of dispensaries, instead getting only a few major ones. While it is difficult to tell from this scale, many do in fact fall within the forbidden buffers upon zooming in.  This means that many of them would have to shut down due to the new law, as they fall within the buffers, seriously restricting those that rely on the them for medicine  Los Angeles is so densely populated and there is so little free space, that it is almost impossible to follow restrictions such as this, as the map clearly shows.  The few available areas within the city that do not fall under this law are difficult to access and much less populated.  .

   It appears from reading the article that the issue is not with the dispensaries themselves, but the ones that do not follow other laws about how they may distribute their products.  If all of the regulations are being followed, marijuana should not fall into the hands of children, who are not legally allowed to purchase from the clubs.  The problem instead appears to be with a few clubs who are not following regulations and allowing the product to either go to those who do not need it for medical usage but only for recreation, and the fact that it is becoming an activity in the clubs late at night as opposed to being used for medicine.

    Stricter restrictions need to be put on the distribution of the product, but the placement of them should not be an issue.  If the 1000 foot ordinance does come to fruition, it will cause many of the clubs to shut down unnecessarily and negatively effect many of their patients.

Iraq

Geocoding

 

   Geocoding allows for precise locations to be created within a map, allowing for spatial distributions to be better assessed.  By placing exact locations onto the map, trends become much more clear, and issues are easier to solve.  In this case, the problem with the Los Angeles public transit becomes an issue that is easier to grasp through geocoding and ARCGIS.

     In Los Angeles, the public transportation system is a mess.  It is incredibly slow and inefficient.  This is due mostly to the fact that it is so crowded and developed, no new development would really be possible.  But there is always room for improvement, and by mapping out the metro station stops we can see where there are potential gaps or places where new stations could do the most public good.

     By creating a buffer around each station, holes in the infrastructure becomes even more evident than they might have before.  I created a two mile buffer, which is quite large, in all honesty it should be smaller.  By making it smaller the holes would be even more evident, showing places where the stations are simply not accessible.  If population data had been made available, it would be good to see where the highest populated areas lacking a metro are located, and how that problem could be alleviated.

 Geocoded Data

	FID_	Status	Score	Match_type	Side	Match_addr	ARC_Street	Station_Na	Line	Address
	M	100	A	L	660 S FIGUEROA ST	660 S Figueroa St	7th St/Metro Center	Red	660 S Figueroa St
	M	100	A	R	6801 HOLLYWOOD BLVD	6801 Hollywood Blvd	Hollywood/Highland	Red	6801 Hollywood Blvd
	M	100	A	L	6250 HOLLYWOOD BLVD	6250 Hollywood Blvd	Hollywood/Vine	Red	6250 Hollywood Blvd
	M	100	A	L	5450 HOLLYWOOD BLVD	5450 Hollywood Blvd	Hollywood/Western	Red	5450 Hollywood Blvd
	M	100	A	R	5350 LANKERSHIM BLVD	5350 Lankershim Blvd	North Hollywood	Red	5350 Lankershim Blvd
	M	100	A	L	3891 LANKERSHIM BLVD	3891 Lankershim Blvd	Universal City	Red	3891 Lankershim Blvd
	M	100	M	L	301 N VERMONT AVE	301 N VERMONT AVE	Vermont/Beverly	Red	301 N Vermont Ave
	M	100	A	L	1015 N VERMONT AVE	1015 N Vermont Ave	Vermont/Santa Monica	Red	1015 N Vermont Ave
	M	100	A	R	1500 N VERMONT AVE	1500 N Vermont Ave	Vermont/Sunset	Red	1500 N Vermont Ave
	M	100	M	R	800 N ALAMEDA ST	800 N ALAMEDA ST	Union Station	Red	800 N Alameda St
	M	100	A	R	101 S HILL ST	101 S Hill St	Civic Center	Red	101 S Hill St
	M	100	A	L	500 S HILL ST	500 S Hill St	Pershing Square	Red	500 S Hill St
	M	100	A	R	3191 WILSHIRE BLVD	3191 Wilshire Blvd	Wilshire/Vermont	Red	3191 Wilshire Blvd
	M	100	A	L	395 N ALLEN AVE	395 N Allen Ave	Allen	Gold	395 N Allen Ave
	M	77	A	R	5150 POMONA BLVD	5150 E Pomona Blvd	Atlantic	Gold	5150 E Pomona Blvd
	M	100	M	L	901 N SPRING ST	901 N SPRING ST	Chinatown	Gold	901 N Spring St
	M	100	M	L	230 S RAYMOND AVE	230 S RAYMOND AVE	Del Mar	Gold	230 S Raymond Ave
	M	100	M	R	4780 E 3RD ST	4780 E 3RD ST	East L.A. Civic Center	Gold	4780 E 3rd St
	M	100	A	L	95 FILLMORE ST	95 Fillmore St	Fillmore	Gold	95 Fillmore St
	M	100	A	L	3545 PASADENA AVE	3545 Pasadena Ave	Heritage Square	Gold	3545 Pasadena Ave
	M	77	M	R	151 N AVE 57	151 AVE 57	Highland Park	Gold	151 AVE 57
	M	100	A	L	210 S INDIANA ST	210 S Indiana St	Indiana	Gold	210 S Indiana St
	M	100	A	R	340 N LAKE AVE	340 N Lake Ave	Lake	Gold	340 N Lake Ave
	M	77	M	L	370 W AVE 26	370 AVE 26	Lincoln/Cypress	Gold	370 AVE 26
	M	100	M	R	200 N ALAMEDA ST	200 N ALAMEDA ST	Little Tokyo/Arts District	Gold	200 N Alameda St
	M	100	M	R	4520 E 3RD ST	4520 E 3RD ST	Maravilla	Gold	4520 E 3rd St
	M	100	M	L	1831 E 1ST ST	1831 E 1ST ST	Mariachi Plaza	Gold	1831 E 1st St
	M	100	A	L	125 E HOLLY ST	125 E Holly St	Memorial Park	Gold	125 E Holly St
	M	100	A	R	905 MERIDIAN AVE	905 Meridian Ave	Mission	Gold	905 Meridian Ave
	M	100	M	L	1311 E 1ST ST	1311 E 1ST ST	Pico/Aliso	Gold	1311 E 1st St
	M	100	A	L	149 N HALSTEAD ST	149 N Halstead St	Sierra Madre Villa	Gold	149 N Halstead St
	M	100	M	R	2330 E 1ST ST	2330 E 1ST ST	Soto	Gold	2330 E 1st St
	M	49	M	R	4800 MARMION WAY	4600 MARMION WAY	Southwest Museum	Gold	4600 Marmion Way
	M	52	M	L	9998 GRANDEE AVE	10100 GRANDEE AVE		Blue	10100 Grandee Ave
	M	100	M	R	108 N LONG BEACH BLVD	108 N LONG BEACH BLVD		Blue	108 N Long Beach Blvd
	M	100	M	R	598 N LONG BEACH BLVD	598 N LONG BEACH BLVD		Blue	598 N Long Beach Blvd
	M	77	A	L	20220 S SANTA FE AVE	20220 Santa Fe Ave		Blue	20220 Santa Fe Ave
	M	100	M	R	1290 N LONG BEACH BLVD	1290 N LONG BEACH BLVD		Blue	1290 N Long Beach Blvd
	M	77	A	L	1920 S ACACIA AVE	1920 Acacia Ave		Blue	1920 Acacia Ave
	M	77	M	R	275 S WILLOWBROOK AVE	275 WILLOWBROOK AVE		Blue	275 Willowbrook Ave
	M	39	M	R	9501 GRAHAM AVE	8615 GRAHAM AVE		Blue	8615 Graham Ave
	M	53	M	L	7226 GRAHAM AVE	7225 GRAHAM AVE		Blue	7225 Graham Ave
	U	0	A			331 W Washinton Blvd		Blue	331 W Washinton Blvd
	M	100	M	L	128 W 1ST ST	128 W FIRST ST		Blue	128 W First St
	M	100	A	L	498 PACIFIC AVE	498 Pacific Ave		Blue	498 Pacific Ave
	M	100	M	R	1798 N LONG BEACH BLVD	1798 N LONG BEACH BLVD		Blue	1798 N Long Beach Blvd
	M	100	M	L	1236 S FLOWER ST	1236 SOUTH FLOWER ST		Blue	1236 South Flower St
	M	100	M	L	767 E WASHINGTON BLVD	767 EAST WASHINGTON BLVD		Blue	767 East Washington Blvd
	M	77	M	R	1700 E SLAUSON AVE	1700 SLAUSON AVE		Blue	1700 Slauson Ave
	M	75	A	R	4421 LONG BEACH AVE W	4421 Long Beach Ave		Blue	4421 Long Beach Ave
	M	100	A	R	3420 N PACIFIC PL	3420 N Pacific Place		Blue	3420 N Pacific Place
	M	75	A	R	1945 LONG BEACH AVE W	1945 Long Beach Ave		Blue	1945 Long Beach Ave
	M	77	A	R	2750 W AMERICAN AVE	2750 American Ave		Blue	2750 American Ave
	M	52	M	R	11701 WILLOWBROOK AVE	11611 WILLOWBROOK AVE		Green	11611 Willowbrook Ave
	M	77	A	R	11667 AVALON BLVD	11667 S Avalon Blvd		Green	11667 S Avalon Blvd
	M	100	M	L	11500 AVIATION BLVD	11500 AVIATION BLVD		Green	11500 Aviation Blvd
	M	77	A	R	11901 CRENSHAW BLVD	11901 S Crenshaw Blvd		Green	11901 S Crenshaw Blvd
	M	100	A	L	700 S DOUGLAS ST	700 S Douglas St		Green	700 S Douglas St
	M	100	M	R	2226 E EL SEGUNDO BLVD	2226 E EL SEGUNDO BLVD		Green	2226 E El Segundo Blvd
	M	100	A	L	11500 S FIGUEROA ST	11500 S Figueroa St		Green	11500 S Figueroa St
	U	0	A			11230 S Acacia St		Green	11230 S Acacia St
	M	77	A	R	12801 N LAKEWOOD BLVD	12801 Lakewood Blvd		Green	12801 Lakewood Blvd
	M	100	A	L	11508 LONG BEACH BLVD	11508 Long Beach Blvd		Green	11508 Long Beach Blvd
	M	100	A	L	555 N NASH ST	555 N Nash St		Green	555 N Nash St
	M	100	A	R	12901 HOXIE AVE	12901 Hoxie Ave		Green	12901 Hoxie Ave
	M	100	A	L	5301 MARINE AVE	5301 Marine Ave		Green	5301 Marine Ave
	M	100	A	R	11603 S VERMONT AVE	11603 S Vermont Ave		Green	11603 S Vermont Ave
	M	100	A	L	660 S FIGUEROA ST	660 S Figueroa St	7th St/Metro Center	Purple	660 S Figueroa St
	M	100	A	R	101 S HILL ST	101 S Hill St	Civic Center	Purpe	101 S Hill St
	M	100	A	L	3510 WILSHIRE BLVD	3510 Wilshire Blvd	Wilshire/Normandie	Purple	3510 Wilshire Blvd
	M	100	A	R	3775 WILSHIRE BLVD	3775 Wilshire Blvd	Wilshire/Western	Purple	3775 Wilshire Blvd
	M	100	M	R	800 N ALAMEDA ST	800 N ALAMEDA ST	Union Station	Purple	800 N Alameda St
	M	100	A	L	500 S HILL ST	500 S Hill St	Pershing Square	Purple	500 S Hill St
	M	100	A	L	660 S ALVARADO ST	660 S Alvarado St	Westlake/MacArthur Park	Purple	660 S Alvarado St
	M	100	A	R	3191 WILSHIRE BLVD	3191 Wilshire Blvd	Wilshire/Vermont	Purple	3191 Wilshire Blvd

 

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