Friday, April 27, 2012

Proposition 8 Maps

In 2008, Proposition 8 changed the California state constitution to prohibit same-sex marriage but did you know that more in-state donations were made by those opposed to the ban? Prop 8 still passed by over a half million votes. These maps were created to draw a comparison between donations and votes to "no on 8" (oppose ban) and to "yes on 8" (support ban). The data comes from public financial records submitted to the California Secretary of State. 

The first map in the series shows the spatial distribution of donations for "no on 8" (oppose ban) in California by zipcode. The heights are based on total dollar amount and darker colors indicate a higher number of contributors. The subset maps compare donations in Northern and Southern California. Seven out of the top ten counties with the highest amount of pro-gay marriage donations came from Northern California. The county with the highest total donation and largest number of contributors to "no on 8" was Los Angeles. Interestingly, Los Angeles County voted for "yes on 8" (support ban) by a mere 0.20%.



The second map in the series shows the spatial distribution of donations for "yes on 8" (support ban) in California by zipcode. The heights are based on total dollar amount and darker colors indicate a higher number of contributors. The subset maps compare donations in Northern and Southern California. The top five counties with the highest amount of donations to “yes on 8” all came from Southern California. The county with the highest total donations to “yes on 8” was Orange County. In addition to being the county with the largest number of contributors to "no on 8" (oppose ban), Los Angeles was also the county with the largest number of contributors to “yes on 8”



The following maps show a comparison between donations to "no on 8" (oppose ban) and to "yes on 8" (support ban) in San Diego, Orange, Los Angeles, San Francisco, Alameda and Sacramento Counties. The heights are based on total dollar amount and darker colors indicate a higher number of contributors. Since there are donations to both no and yes in most zipcodes, I have included inset maps for each side. The larger county maps are a combination of donations to both no and yes; whether or not the region is colored blue or red depends on which side donated more. I have also included graphs that shows how the county voted and which side spent more money.

The donation and voting data shows San Diego County as predominantly against marriage equality. The largest amount of money donated to "no on 8" (oppose ban) came from Mission Hills followed by the 92104 and 92116 zipcodes in City of San Diego. Interestingly, the second largest sum of money donated to "yes on 8" (support ban) came from 92120 in City of San Diego, a zipcode adjacent to 92104 and 92116. The largest amount of money donated to "yes on 8" came from La Jolla from a small amount of contributors. Other areas with high contributions to "yes on 8" include El Cajon, Poway, Fallbrook, Carlsbad, Encinitas and Rancho Penasquitos. 


The donation and voting data shows Orange County is predominantly against marriage equality as well. Even the most liberal area of Orange County, Laguna Beach, received over three times as much money to "yes on 8" (support ban) as to "no on 8" (oppose ban). The largest amount of money donated to "yes on 8" came from Irvine and the highest number of contributors to "yes on 8" came from Fountain Valley, Laguna Niguel, Rancho Santa Margarita and Yorba Linda. The majority of Orange County donated to and voted for “yes on 8”.


Los Angeles County donated over 11 million dollars to "no on 8" (oppose ban), twice as much as was donated to "yes on 8" (support ban), but “yes on 8” prevailed by just 2385 votes. The largest sums of money donated to "no on 8" were from Beverly Hills, West Hollywood and Hollywood. The largest number of contributors to "no on 8" came from Long Beach, Santa Monica, West Hollywood, Hollywood and Beverly Hills. The largest sums of money donated to “yes on 8” came from La Canada & La Crescenta, Palos Verdes and La Verne. The largest number of contributors to “yes on 8” came from the City of Long Beach.


The donation and voting data shows that San Francisco County is predominantly in favor of marriage equality. Nearly 7 million dollars was donated to "no on 8" (oppose ban), five times as much money as was donated to "yes on 8" (support ban). "No on 8" voters outnumbered “yes on 8” voters 3 to 1. The largest amount of donation to "no on 8" came from the Financial District, Fisherman’s Wharf, The Castro District and Noe Valley. The largest number of contributors came from Mission District, Haight, Glen Park and Diamond Heights. In comparison, a marginal amount of money was donated to “yes on 8”.


Alameda County is also predominantly in favor of marriage equality based on the total donation and votes. The largest amount of money and number of contributors to "no on 8" (oppose ban) came from Berkeley and Oakland. The largest amount of money to "yes on 8" (support ban) came from Pleasanton and Dublin, while the largest number of contributors came from Livermore and Pleasanton.


The donation and voting data show that Sacramento County is predominantly against marriage equality. The largest amount of money donated to "no on 8" (oppose ban) came from Downtown Sacramento (location of the California State Capitol Building) and the 95841 zipcode in the City of Sacramento. The largest amount of contributors to "no on 8" came from Downtown Sacramento. The largest amount of money donated to "yes on 8" (support ban) came from Granite Bay and Folsom. The largest number of contributors to “yes on 8” came from Folsom, Elk Grove, Fair Oaks and Granite Bay. 


These maps are based on campaign finance reports submitted to the California Secretary of State. The raw data for these maps can be downloaded as a .CSV file from the LA Times Prop 8 Money Tracker. The voting data can be viewed on the California Secretary of State Prop 8 voting map.

Proposition 8 has since been ruled unconstitutional by the U.S. 9th Circuit Court of Appeals and is likely to be appealed to the U.S. Supreme Court in the next few years. There is currently a stay on the ruling by the 9th Circuit Court since supporters of prop 8 immediately petitioned for a rehearing. Gay marriage is still prohibited in the state of California. 

Comments or questions? If you don’t see it on the map and are interested in knowing how YOUR area donated, email me at kelsey.ck@ucla.edu






Tuesday, April 17, 2012

New Park Suitability Analysis for City of Los Angeles

New Potential Park Locations by LA River


This work was carried out for the City of Los Angeles as part of a class project. The city is interested in adding new parks in low income areas by the LA River. This map shows the results of the analysis. The required parameters for the project were:

1. Park may not be within .25 miles of an existing park
2. Must be within LA city limit
3. No more than .75 miles from the LA River
4. Median family household income must be less than $50,000 a year
5. Greater than 25% children in surrounding blocks
6. Must be a vacant lot greater than 1 acre in size
7. Densely populated location with greater than 8,000 people per sq. mile
Five sites fit all of the listed parameters and are proposed as suitable locations for a new park. The next step is for someone to go visit these sites and determine the best location to carry out park construction. 


Click HERE to View Slide Show of Each New Potential Park Site (created with ArcGIS Explorer Online).


This is a flow chart that I created using ArcGIS Model Builder. It outlines all of the steps to conduct this suitability analysis.

Blue = inputs
Yellow = tools
Green = outputs 






Cell Tower Analysis

Santa Barbara, Ventura and Los Angeles Counties 

 

 The first map shows the distribution of cellular towers in these 3 counties and the second map shows cellular coverage in Los Angeles County.

         
 Data for this map was acquired from Federal Communications Commission (FCC) Universal Licensing System (ULS) database. The database utilized is “Cellular - 47 CFR Part 22 ‘Licenses’”, last updated (from when map was created) on 4/8/12. This is a non-comprehensive database for keeping track of licensed cell towers in North America. The data is unreliable and these maps were created as a class mapping exercise rather than as a serious geo-processing analysis. Comprehensive reliable data is difficult to find, however it is estimated that there are about 4,000 cell towers in Southern California. Based on the database used to create this map, there are 41 towers in Los Angeles, 32 in Santa Barbara and 18 in Ventura. These numbers are inaccurate and are more likely to be in the hundreds. 




Cellular Coverage in Los Angeles County

 

  Assignment:

You have been given a $30,000 budget to improve cell tower performance. You can do one of the following:
1. Add three additional towers at optimal locations;
2. Increase all the tower heights by 10 meters;
3. Increase the towers’ power resulting in an increase of each tower’s range by 5 km.


For each option, you will need to re-conduct the viewshed analysis in order to compare to your original results. (Remember to also compute the percentage of LA County that is able to receive cell signals from your analysis.) After you analyze and compare each of the above three options, which do you recommend. 
 The goal of this class assignment was to learn how to use the viewshed analysis technique. A viewshed identifies locations that can be seen from one or more observation locations. Since the data is inaccurate, this map is more about viewshed analysis techniques than the results. I ignored cell towers surrounding Los Angeles County and just focused on cell coverage in LA created by towers within the county boundary lines. If this analysis had been for a company, I would have taken into account that cell towers outside of the county lines may have a coverage range that overlaps into Los Angeles County, in which case this would have affected my statistics of total cell coverage percentage as well as my choice for placement of the three new towers. 

My first step in the analysis was to download digital elevation (DEM) model data of Los Angeles County from the USGS Seamless Data Warehouse. I then imported the DEM data into ArcMap and used the mosaic tool to link the two swaths together. I then overlaid the cellular tower point data and Los Angeles County boundary polygon on top of the elevation data and projected the layers into UTM Zone 11 (North American 1983 datum). I then appended the cell tower attribute table with the necessary parameters to conduct the viewshed analysis (OFFSETA, OFFSETB, AZIMUTH1, AZIMUTH2, VERT1, VERT2, RADIUS1, RADIUS2); I made the “normal coverage” OFFSETA (height of the tower) 20 meters, OFFSETB (height of cellphone user) 1.4 meters, and RADIUS2 (range of cell reception) 30,000 meters. I kept ArcGIS default values for the other parameters.

The next step was to conduct the viewshed analysis for each of the four scenarios (normal coverage, adding 10 meters to tower height, adding 3 new towers and increasing range of reception by 5000 m). I then used the extract by mask tool to only keep the viewshed data that was within the Los Angeles County boundary. The extract by mask tool only worked for the “normal coverage” and “add 3 new towers” maps for a reason unknown to me. I used a work around to accomplish the extraction for the “add 10 meters to tower heights” and “add 5 km coverage range” maps, I used the clip management tool and then integerized the raster output to obtain pixel counts. I created a hillshade of the DEM for map presentation purposes. 

Based on my final results, adding 3 new towers increased the coverage the most. The next most effective scenario was adding 10 meters to the tower heights closely followed by increasing cell range by 5 km. All three scenarios were improvements upon the results yielded by the original parameters.









View the presentation online here.

Santa Monica Mountains Topography & Vegetation Analysis

Comparing Slope, Aspect, Solar Radiation & Elevation Preferences In Plant Species




The first map that I created with ArcGIS shows the vegetation distribution in the Santa Monica Mountains.The second map shows topography (slope & aspect) of the region as well as solar radiation changes by season. The third map shows the correlation between topography and vegetation distribution for each of the four main vegetation types using statistical graphs about slope, aspect, elevation and solar radiation. The data sets utilized for this analysis are the National Elevation Data (NED) 1 Arc Second (30 m resolution) and California Vegetation data from USGS.
 
The third map of charts and graphs contains a lot of interesting information. The information was calculated using a zonal statistics tool which overlays the vegetation info on top of the slope, aspect, elevation and solar radiation maps and then computes a statistical breakdown for each vegetation type. The urban agriculture data lends itself to what intuition already tells us; it is most likely to be found in flat areas with low elevation, it also in places where it consistently receives the most amount of sunlight from season to season. The most interesting piece of information on the third map is the “Aspect Preferences” compass. All four of the main vegetation types are most likely to be found of the south facing side of the mountain. This potentially has something to do with sun exposure or the rain shadow effect.

There is a 1:1 correlation between slope and elevation preference for each plant type; the higher the plant is in elevation, the steeper the slope is that it’s found on. (In descending order from highest elevation and steepest slope: chamise-redshank chaparral, coastal scrub, annual grass and urban-agriculture).

Definitions: 
Slope - the steepness of an angle represented in degrees 
Aspect - the direction that the slope is facing (e.g. North)
Elevation - meters above sea-level 
Solar Radiation - sunlight measured in Watts per meters squared (W/m).