Girls Garage in San - University of California,...
Transcript of Girls Garage in San - University of California,...
zMz
Flow Charts & Maps
Fear Less.Build More.Finding a New Location for Girls Garage in San Francisco, California
Kelly Albers and Adrian RodriguezLandscape Architecture/Geography C1888 December 2017
IntroductionGirls Garage is a local design and building program for girls ages 9-17. There is currently one dedicated workshop in Berkeley, California that gives girls the opportunity to learn and develop skills in design thinking and engineering. The workspace equips girls with the confidence and creativity to transform their communities and confidently embark on a path towards higher education and career opportunities. As a safe and fun place for the empowerment of young girls, it is important to expand locations of the Girls Garage program so as to enact positive change in a society that is, more often than not, dominated by the male population.
Project AimOur aim is to pinpoint a new location for a second Girls Garage in San Francisco, California. Our client would like the new workspace to be located near neighborhoods with great diversity in race and income, near areas of mixed-use zoning, in close proximity to resources like restaurants, Home Depot, etc. and in close proximity to green spaces. Most importantly, the workspace should be located next to existing schools and public transit systems, so that it is easily accessible to the desired demographic.
ClientEmily Pilloton
Lecturer, UC Berkeley College of Environmental DesignFounder and Executive Director of the Non-Profit Project H Design & Girls Garage Program
MethodsSuitability Analysis: We analyzed ten opportunity and constraint factors. Since Girls Garage caters to young girls, we chose to identify areas with a greater youth population and areas where the female population is greater than the male population. In order to ensure that the workspace is used effectively, we selected close proximity to parks, retail areas, and public transit systems to be opportunities as well. As for our constraints, we chose to focus on areas where crime has occurred since our main concern is the safety and comfort of users. We also considered areas where the male population is greater than the female population and areas that are not zoned as mixed-use to be constraints. Lastly, we chose to map out seismic hazard and inundation vulnerability zones as constraints that could negatively impact our location in the long run.
2D & 3D TIN Models: We chose to map out slope in order to ensure the safety and stability of our prospective location in the future. With the imminent risk of climate change, we felt it was important to consider slope steepness as a constraint in our overall suitability analysis. We recognize that building on areas that are steep in slope (30 degrees or more) would not only increase chances of damage in the event of an earthquake, but would also affect the ability of users to reach the location.
Network Analysis: We decided to model a Service Area analysis of Public and Private Schools, Stores, Fire Stations, and Starbucks Locations. We utilized both types of schools to ensure that the workspace will serve female students from different educational facilities. We included Fire Stations to guarantee the safety of the students and faculty members since they will be utilizing welding equipment and working with flammable materials. The analysis includes Stores because the client requested that the workspace be located near supply/hardware storefronts for quick access to materials. Lastly, we decided to include Starbucks Locations because they are good indicators of popular retail areas.
Results & ConclusionsBased on our Suitability Analysis, the areas that can be considered suitable for our proposed workspace are mainly located on the Western side of the city, near Golden Gate Park. When comparing our TIN Model to our other two analyses, it makes sense as to why the most developed areas are located on the North-Eastern side of the city - it is has the lowest elevation, making it ideal for the construction of large buildings and roads. However, many of these areas are built on filled land, hence the concentration of constraining factors such as seismic hazard and inundation vulnerability zones. Based on our Service Area Network Analysis, areas that will have high accessibility to services are located in the downtown areas of San Francisco, in close proximity to Golden Gate Park, and in areas located West of the Twin Peaks neighborhood. After combining all three of our methods to create a Final Composite Suitability Map, we have determined the best location for a new Girls Garage workspace to be in the Lower Pacific Heights/Fillmore District (as indicated in Purple and in the Circle above) of San Francsico. Historically this area has been unaffected by earthquake and fire events and is known as one of the best commerical and cultural centers of the city.
Sourcesdata.sfgov.orgusgs.govmapzen.comGeoDataBases from LD ARCH/GEOG C188 Labs 5, 7, 8, 9 and 10Projection/Datum: California State Plane Zone III/D_North_American_1983
Suitability + TIN + Network Analysis Map
Load Public School, Private School, Stores, SF Fire
Stations, & Starbucks as Locations/Facilities
Set Service Area Breaks at 1, 2, 3, 4, & 5 minutes
Select New Service Area Option
Set “Merge by Break Value” & “Rings”
Assign Weight Values as 0-1 mins (2), 1-2 mins (1),
2-3 mins (0), 3-4 mins (-1), & 4-5 mins (-2)
Export Map into New Data Layer
Change Color Ramp, Green (Weight: 2) to Red
(Weight: -2)
UNION TOOL
Change Color Ramp from green (weight: 9) to Red
(weight: -10)
Remove Outlines & Set Transparency to 30%
Final Service Area Network Analysis Map
Field Calculatorequation=[publicschool_wt]+
[privateschool_wt]+[sfstores_wt]+[firestation_wt]+[starbucks]
Opportunity Factor #1:Youth Population (Ages
5-17)
Data Collection & Data Discovery
Factor Definiton
Data Compilation Projection & Datum
Opportunity Factors
Select by Attribute (“AGE_5_17” > 250)
Opportunity Factor #5:Close to Exsiting Public
Transit Routes
Opportunity Factor #4:Close Proximity to Retail/
Commercial Areas
Opportunity Factor #3:Close Proximity to Parks/
Green Spaces
Opportunity Factor #2:Female Population >
Male Population
Select by Attribute (“FEMALES”>“MALES”)
Buffer by 1000 ft & Add Weight Factor of (+1)
Buffer by 1000 ft & Add Weight Factor of (+1)
Select by Attribute (“type”=“retail”)
Select by Attribute (“type”=“bus_stop, station,
subway_entrance, tram_stop”)
Buffer by 500 ft & AddWeight Factor of (+1)
Buffer by 500 ft, Dissolve, &
Add Weight Factor of (+1)
Buffer by 1000 ft & Add Weight Factor of (+1)
Overlay--Union:Calculate Field
“Total_Opp”= [youth_wt] + [female_wt] +
[parks_wt] + [retail_wt] + [transit_wt]
Constraint Factor #1:Male Population > Female Population
Constraint Factors
Select by Attribute (“MALES”>“FEMALES”)
Constraint Factor #5:Non-Mixed Land-Use
Areas
Constraint Factor #4:Inundation Vulnerability
Zone Lines
Contraint Factor #3:Seismic Hazard Zones
Constraint Factor #2:Severe Crime
Select by Attribute (Assault, Missing Person, Forcible Sex
Offenses, Drug/Narcotic, Vandalism, Kidnapping)
Buffer by 1000 ft & Add Weight Factor of (-1)
Buffer by 500 ft & Add Weight Factor of (-1)
Select by Attribute (“gen”= “commercial, industrial,
public, residential”)
Buffer by 500 ft & AddWeight Factor of (-1)
Dissolve & AddWeight Factor of (-1)
Buffer by 500 ft & Add Weight Factor of (-1)
Overlay--Union:Calculate Field
“Total_Con”= [male_wt] + [crime_wt] + [seismic_
wt] + [flood_wt] + [nonmixed_wt]
Final Suitability Analysis MapOverlay--Union: “Suitable”= [Total_
Opp] + [Total_Con]
Project Layer in California State Plane
(US Feet) III
Download “sfcontours_10ft_sfd”
Data Layer
Display Contours in 3DCalculate Z-Values in Feet (equation: CONTOUR field
x 3.2810 ft)
Create TIN Model Change Slope Units from Percent to Degrees
Load “tin_10ft” into ARC Map
Create TIN Triangle
Final 3D TIN Model Map
Thematic Display of TIN(Face Slope with
Graduated Color Ramp)
Export Slope Data into a New Data Layer
Select by Attribute (“Slope_Deg” > 30)
Final 2D TIN Model Map
Create New Field (“Steep”) & Add Weight
Factor of (-1)
Change Display Properties & Reclassify
(6 Classes)
Download 1/3 ARC-Second
DEM Dataset of SF
Suitability Analysis:
3D & 2D TIN Models:
Network Analysis--Service Area:
Final 3D TIN Model Map
0 7,900 15,8003,950Feet
Final Composite Suitability MapLegendComposite MapSuitability
-14
-13
-12
-11
-10
-9
-8
-7
-6
-5
-4
-3
-2
-1
0
1
2
3
4
5
6
7
8
9
10
11
SF_bnd
Water
Shoreline
®