philadelphia's mural scene (1)

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Philadelphia’s Mural Scene This project covers a lot of criteria. In this image are potential sites for new murals. This feature will be expanded upon in the following pages; however, this feature is one of many for this project. Mitchell Walker ENVS 541 Professor Tomlin 19 Dec 2014

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Page 1: Philadelphia's Mural Scene (1)

Philadelphia’s Mural Scene

This project covers a lot of criteria. In this image

are potential sites for new murals. This feature will

be expanded upon in the following pages; however,

this feature is one of many for this project.

Mitchell Walker

ENVS 541

Professor Tomlin

19 Dec 2014

Page 2: Philadelphia's Mural Scene (1)

Project Description/Criteria

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Page 3: Philadelphia's Mural Scene (1)

The Divine Lorraine has been deteriorating over the years. The

image above was taken in 2004 and the one below in 2010. You can

see this by comparing the two images. However, also depicted is a

that fair amount of development has been underway. Thus,

Develacorp concluded this as prime real-estate, purchased it, and is

in the works of renovating it.

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Page 4: Philadelphia's Mural Scene (1)

The city has also offered a tax incentive to Develacorp if they agree to

develop the rather large lot immediately behind the Divine Lorraine.

However, in order to receive this tax-cut, the group must develop a

revenue generating establishment that will greatly benefit the community.

They have met with several organizations, but have found the proposal

offered by the Mural Arts Program most appealing. The proposal consists

of three features:

1) to build an Urban Arts Museum

2) to organize the inner city youths, living in the

communities surrounding their building, to

photograph and name existing murals in need.

3) to find areas to pain 100 new murals by 2017

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Page 5: Philadelphia's Mural Scene (1)

Above, in purple, is a drawing

of the new Urban Arts

Museum. The perimeter of

this lot is over 8 times larger

than that of the Divine

Lorraine—which is quite

large. A couple of near by

buildings were used as

templates to create the

shape of the new

Museum, both of

which are labeled to the right.

Above is a completed drawing of the

Urban Arts Museum, placed

immediately behind the Divine Lorraine.

This drawing consists of the actual

structure (in purple and aqua), a large

stairway, and courtyard surrounding a

fountain. The goal is to fill this museum

with every mural in Philadelphia—

roughly more than 3,600—along with

other works that will hopefully become

murals on sites identified by our group.

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Page 6: Philadelphia's Mural Scene (1)

Using Regression to Find Ideal

Locations to Paint Several

New Murals

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Page 7: Philadelphia's Mural Scene (1)

In the center of the above map is the development

site for the Urban Arts Museum. The yellow circle

surrounding it represents a mile out from the exact

center of the site. The eight regions—overlapped by

the mile sphere to varying extents—are zip code

areas. These areas originally contained the

communities of our interest—due to their proximity

to the development site; however, due to our finding

very few potential mural sites in the loser regions, we

reduced our search to the top four zip code areas.

Above, in blue, are 8,565 buildings within the

(original) region of our focus. To find what

buildings are ideal for murals, and where to

paint them, a considerably extensive

regression was formulated. Ultimately, we

narrowed our selection down considerably by

means explained on the following pages.

Buildings

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Page 8: Philadelphia's Mural Scene (1)

To the right are vacant lot and yard areas

colored—appropriately—green. These areas

were taken from a raster layer which created

these area shapes based on their color captured

from a photograph. As you can see in the

baseball field (right; top) the only thing

separating the significance of the diamond and

backfield from the infield is the color contrast,

of which the photo to raster deemed as

separate. Regardless, the green areas of this

photo works sufficiently for the task at hand

because our group is trying to identify vacant or

open lots in the vicinity of buildings (preferably

houses).

The reason is that these vacant areas could

potentially offer space for the mural artists and

youths in our program to work and, when

completed, offer a clear line of vision for

pedestrians and commuters passing on, and

near, the area’s respective roadway. The ideal

vacant area would be something like the areas

circled in the center of the image because both

lots are near to two potential mural sites (i.e.

between two walls), vacant lots, and a road.

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Page 9: Philadelphia's Mural Scene (1)

Moving forward, below is a depiction of the model built to perform our regression. We

began with centerlines, buildings, and lots all clipped to our (zip code) areas of focus, along with

buildings, we have found to be the ideal size, with a perimeter of 200-1,000 feet (orange; right).

From here, a buffer (= to 1 ft) was used on all our ideal sized buildings and the vacant lots, which

was then intersected, placing a padding on our buildings to place a mural site. A multilayer buffer

(of 30 ft in purple-50 ft in orange dashed marks; both right) was then used to erase insufficient pads

from our buildings, which then placed on our buildings the potential mural sites (highlighted in

aqua). Separate multilayer buffers (30-32 ft and 46-50 ft; both in black set to 50% transparency, and

also right) were then used to erase parts of these pads, separating them from the ideal site locations.

This was used to separate pads that ran around the front or back of our buildings. Any residuals

were then either selected and erased by the original buffer from the buildings or one of the various

multi-buffers selected/used. Additionally, any ideal building within a 20 ft buffer from another—

non-ideal—building (white hash marks), or 20 ft from another mural site (orange hash marks), were

not selected in their attribute table and removed following the use of a clip tool in which said area

was not included. Lastly, any sites that didn’t meet a certain area size requirement were then

selected out.

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Page 10: Philadelphia's Mural Scene (1)

This regression successfully reduced the original

1,360 ideal sized buildings (in yellow; left) to the

378 ideal mural locations high-lighted in aqua

below. These mural locations are better observed

in the portion of the map blown up at bottom

center. I removed the buffer from the mural

pads merely to make them more visible. As you

can also see, there are not many such locations in

the lower region of the map, leading us to then

only use the top four zip code areas (19121,

19122, 19123, and 19130).

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Page 11: Philadelphia's Mural Scene (1)

Legend

! Photo Needed

! Already Have Photo

Now, because we are trying to get our youth

program off to a productive start, the next part of

the project is to find the area most suitable to focus

on first. To do this, we wanted to find which area

has the most murals that have yet to be

photographed. Also, because many of the murals

have still not been given titles, we feel that this issue

should be corrected, and that the children from the

actual areas should participate in naming this pieces,

as well as helping us take the photos that will then

be displayed in the museum. Directly above is a map

portraying actual murals geocoded by their address

and zip code. However, because this does not

include those not yet named I scored the murals

based on their current state: titled and

photographed = 1, photographed or titled = 2, and

neither being equal to 3.

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Page 12: Philadelphia's Mural Scene (1)

Because the vast majority of the murals do not have either a title of a photo the interpolation of

the score is in reverse, showing that 3 of the four have very few, if any, murals with titles or

photos of them. As a result, all we know is that the one zip code area substantially pierced by the

interpolation—which is also the area where the museum is to be built—is the one area we should

most likely avoid. Still, because the remaining areas have so many murals that need our attention,

more calculating was needed to decipher which area will give us the most murals to work with.

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Page 13: Philadelphia's Mural Scene (1)

Score

194

102

50

64

Mural Score per Zip Code Region

19121 19122 19123 19130

190

180

170

160

150

140

130

120

110

100

90

80

70

60

50

40

30

20

10

0

With that, we spatially merged the

highest scoring murals to their

respective zip code regions,

followed by the second highest

scores, and so forth. We also

joined the count of the potential

mural sites, so that our youth

program team can also seek out

these sites in person. It would be

kind of like a scavenger hunt—just

a lot more interesting. Regardless,

the end result leans strongly

towards zip code region 19121,

which is the region we have

decided to begin our youth

program outreach. P 13

Page 14: Philadelphia's Mural Scene (1)

The Potential Liabilities our

Program Might Face Due to Crime

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Page 15: Philadelphia's Mural Scene (1)

Crime by Season

! Fall

! Spring

Because we were concerned about safety, first and foremost, we began researching crime in this area long

before we knew that we would be focusing on the one zip code area. Hence, all the original zip code regions

are back. Still, we thought that it would be interesting to see what the annual crime looked like in all of these

regions for reference purposes. Additionally, because our program will only be conducted during the Fall and

the Spring, we filtered all crimes that occurred in the alternate seasons. The result is below and, at first

glance, it might look rather alarming—regardless of my attempts at softening the map’s imagery with spring

and fall colors. Still, this is over the course of a year, so lets investigate further before we conclude that our

youth program is too big of a liability.

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Page 16: Philadelphia's Mural Scene (1)

So because Fall (top) and Spring were quite

similar after using the Kernel Density tool,

I ran them again via Kernel Density, only

together this time—producing the map top

center.

I also buffered the points and

spatially merged them on to

centerlines that were also

buffered. After adjusting the

map’s symbology, to produce the

join count, the map above

emerged.

To the right is the top (right) map

again, but with its base-heights

adjusted. To the left, its extrusion is

based on its count value.

1.

2.

3.

4.

5.

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Page 17: Philadelphia's Mural Scene (1)

I also took the map portraying the crime for both Spring and Fall (on the previous

page) and converted to a TIN (via Raster to TIN) to produce the map directly left.

This was an essential step to take in order to portray this map showing ramped

sidewalks and roads based on the crime in their respective areas, below. Essentially,

by using this TIN as the base-height setting it anchored the floating base-height

“bands”(depicted in the 4th from the previous page) to the ground—while keeping

the extrusion set to the count values. Ultimately, as you can readily observe, the

only red ramped roads/sidewalks (i.e. the high crime areas) are ironically located

around City Hall, far from the zone we are interested in starting our youth Mural

Arts Program (the zone in pink directly below).

Number of CrimesReported

0 - 2

3 - 9

10 - 23

24 - 57

58 - 113

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Page 18: Philadelphia's Mural Scene (1)

However, if the heinousness of the crime is factored into our risk assessment, our challenge

becomes more considerable. As you can see, the zip code area we chose to begin our youth

program has the most cases of high crimes (e.g. namely thefts and assaults with fire-arm) near to

the murals we need to photo and/or name:. Still, because our team is focused on improving

situations, and not running from them, our chosen region is still ideal for our mission. Still, some

considerable alterations regarding our strategies to retrieve our mural photos must be made.

Distance from High Crimein feet

! -1.000000 - 462.360656

! 462.360657 - 1258.932979

! 1258.932980 - 2067.138280

! 2067.138281 - 2761.775637

! 2761.775638 - 4336.597682

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Page 19: Philadelphia's Mural Scene (1)

Data Cited

Buildings. GIS Service Group. City of Philadelphia. OpenPhillyData. Shapefile. 1 Dec 2007.

Web. 20 Oct 2014.

Crime Incidents. Philadelphia Police Department. City of Philadelphia. OpenPhillyData. CSV. 12 Dec 2012. Web. 14 Dec 2014.

Curb Edges. Department of Streets. City of Philadelphia. OpenPhillyData. Shapefile. 1 Jan 2012.

Web. Oct 2014.

Mural Addresses. Mural Arts Program. Philadelphia NIS Mural Base. Web. 10 Dec 2014.

<http://apollo.cml.upenn.edu/murals/mbQueryRequest.asp>. Nov 2014.

My Map, ArcGIS. ESRI. Web. 11 Nov 2014

Philadelphia 2004 aerial photography Area 3 and 4. City of Philadelphia. Pennsylvania Spatial Data Access. 2004. Web. 8 Dec 2014.

Philadelphia Land Cover Raster. Parks and Recreation. City of Philadelphia. 19 Oct 2011. OpenPhillyData. Web. 12 Dec 2014.

Philadelphia zipcodes. City of Philadelphia. Pennsylvania Spatial Data Access. 2012. Web. 8 Dec 2014.

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