4. APPROACH
• Exogeneity
• The attributes may be price-independent.
• Isolate the area-wide factors from property-dependent
factors.
• Hedonic
• Distances to certain facilities increase/decrease the value as
the level convenience of living increases/decreases
• Distances as attributes
• Distances to certain facilities contribute to the value of a block,
a lot, or a single property.
5. PLACE OF INTEREST (POI)
• Facilities that impact on surrounding area.
• POIs (in ArcGIS) present as points, lines, polygons, or raster.
• We select some facilities as POIs to test if the impact of each
POI is significant.
• We also summarize non-spatial factors as the zonal density of
noise as a POIs.
6. PROXIMITY(DISTANCE)
• Proximity:
• Attributes of each block
• Test the sensitivity of block-level scale.
• Measured as network distances
• Accessibility of facilities-dependent of road
network, such as walking distances
• Measured as Euclidean distances
• Externality of the facilities-independent from
road network
• Proximity to certain facilities may
positively/negatively impact on property values.
• Impacts diminish at certain rates as distances
increase.
• The diminishing rates may be non-linear.
https://en.wikibooks.org/wiki/Transportation_Geography_and_Network_Science/Circuity#/media/File:TGNS_NetworkDistance.png
https://en.wikibooks.org/wiki/Transportation_Geography_and_Network_Science/Circuity#/media/File:TGNS_EuclideanDistance.png
http://resources.arcgis.com/en/help/main/10.1/index.html#/Near/00080000001q000000/
8. •Block shapefile of each borough
•Use block suffix to identify
block of the same block
•POI shapefile
Input
•Network Analysis
•Find closest facilities
•Calculate Network Distance
•Generate Near Table
•Calculate Euclidean Distance
•Rasterize non-spatial attributes
•Calculate the number of
facilities within certain distance
of a block
Interim
•Distance Table
•Distance-Dummy Table
•Zonal Attribute Table
Output
PROCESS
9. INPUT-POI PREPARATION
Name Selection Standard and Action Source Feature
SubwayStation
Copy and Paste DOITT points
Copy and Paste DOITT points
SelectedPark_5a Acreage>=217800 (5 acres) DOITT polygons
Rail_grd ROW_TYPE=Elevated, Surface, Open Cut Depression, Embankment,Viaduct DOITT polylines
Bridge_Tunnel RW_TYPE=Bridges (across shoreline), dissolve, DOITT polylines
PublicAccessibleWaterfront Merge PAWS.shp and NYC_Waterfront_Parks.shp BYTE of BIGAPPLE polygons
WasteManagement Copy and Paste BYTE of BIGAPPLE points
College_3K SubGroup Type=13, Capacity>=3000 BYTE of BIGAPPLE points
College_10K SubGroup Type=13, Capacity>=10000 BYTE of BIGAPPLE points
CulturalFacilities_Others FacType=1601, Capacity>0 BYTE of BIGAPPLE points
Library_300K FacType=1401 and 1402, Capacity>300000 BYTE of BIGAPPLE points
RailStation Copy and Paste DOITT points
Hospital FacType=3102,Capacity>0 BYTE of BIGAPPLE points
HistoricDistrict Status=Designated NYC OPEN DATA polygons
Noise_311 Complaint_Type Contains Noise,Display XY data NYC OPEN DATA points
Noise_Den_25 Point Density, cell size=25, mask=nybb NA raster
Pharmacy Selected by Location (nybb), Amenity=Pharmacy/Name=CVS, Duane Reade, WALGREENS, Rite Aid OpenStreetMap points
Shelter FacType=4401,4402,4411,4412,4414,Capacity>0 BYTE of BIGAPPLE points
10. INPUT-BLOCK PREPARATION
Identify each
Block
•Newbase table
containing bbl and
block suffix
•Select index lot from
each physical block
•Sort by Boro, Block,
Block Suffix, Lot
•Exclude lot of:
•Pid <0
•Land size=0
•BC=T*, U*, R*
Select block
•Digital Tax Map
containing tax lot
features
•Table containing bbl
and block suffix
•Join by lot BBL
•Lot Feature
containing Boro,
Block, and Block
Suffix.
Blocks with
blksuf
•Digital Tax Map tax
block feature
•Spatial Join the lot
feature with block
feature (get attributes)
•Dissolve to combine
the small block with
same block and suffix
number
•Generate centroid for
each block
11. PROCESS METHODS
•The accessibility of POI
relies on road network
•Active Access
•walking
•Driving
Network
Analyst
•The accessibility of POI
doesn’t rely on road
network
•Externality of
noise/pollution
•Passive Access
Nearest
Distance
•Summarize the non-
spatial variables
•Create spatial
distribution surfaces
Point
Density
Subway
Station
Rail
Stations
Universi
ties
Museu
m
Hospital
Shelter
Library
Pharmacy
Publicly
Accessible
Waterfront
Railroad
on the
ground
Park
Bridge
and
Tunnel
Waste
Manage
ment
Brownfield
Historic
District
Noise
12. METHOD LOGIC
If the POI should be
actively accessed from
each block…
Network Analyst
(5 nearest POIs)
Distance Table:
1st Nearest Distance
2nd Nearest Distance
3rd Nearest Distance
4th Nearest Distance
5th Nearest Distance
ArcGIS shapefile
If the POI should be
passively accessed
from each block…
Make Near Table
Nearest Distance Table
ArcGIS shapefile
If the non-spatial
attributes can be
presented
geographically…
Point Density/Raster/
Zonal Table
Zonal Table:
Non-spatial attributes
If the number of POIs
were to be
summarized at block
level…
Multiple Buffers/Spatial
Join
Count Table:
Numbers of POIs of each
block at distance_1
Numbers of POIs of each
block at distance_2
ArcGIS shapefile
13. INTERIM-NETWORK ANALYST
Incidents
-Blocks
•Block
centroid
shapefile
(OID)
•By boro
•Generate
IncidentID
•Reasonable
Check
Facilities -
POIs
•POI (Point
features only
•Generate
FacilityID
•From
incidents to
facilities
Use
Network
•Road
Network
• Generated
from CSCL
Centerline
(topology)
Solve
•Use incidents,
facilities, and
network feature
layers
•Find the Closest
Facility
•Number of POIs
to find=5
•Use trip length as
impedance
Save
results
•Save route
feature
class
•Save the 5
distance
values to
table
•Transpose
by incident
Join
Distance
back to
Block
•Distance
table with
IncidentID
•Blocks with
IncidentsID
•Blocks with
OID
15. Distance to the
1st nearest
Subway
Station
Distance to the
2nd nearest
Subway
Station
Distance to the
3rd nearest
Subway
Station
Distance to the
4th nearest
Subway
Station
Distance to the
5th nearest
Subway
Station
18. INTERIM-GENERATE NEAR TABLE
Input feature
-block
•Block centroid
shapefile
•Add OID to identify
each block
•By boro
Near feature
-POIs
•Polylines
•Polygons
•Points
•Euclidean distance
Generate
Near Table
Join Distance
back to Block
•Distance Table for
each block
19. • Input
• Tax block
• POI
• Park
• Larger than 5
acres
22. INTERIM-
CAPTURE SPATIAL RELATED VARIABLES
Input feature
-block
•Block centroid
shapefile
•Add OID to identify
each block
•By boro
Create Raster
-POIs
•Polylines
•Polygons
•Points
•Attributes: density
Create zonal
table to
summarize
the raster
attributes
into each
block
• Sum
• Area
• Sum/Area
Join zonal
table back to
Block
•Spatial attributes
for each block
25. INTERIM-
GIS PROCESS-GENERATE DUMMY VARS
Buffer
•Block feature
•Generate OID for
each block
•Generate Multiple
Buffers for each
block
•0.3-mile buffer
•0.5-mile buffer
Calculate
numbers of
facilities within
buffers of each
block
•Spatial Join with
the point POI
feature
•Field summarize
the number of
facilities
•Save the table
Generate
Dummy
Variables
•If none of the facilities
fall in 0.3-mile buffer,
then dist_030_var0=1,
else=0
•If 1 facility falls in 0.3-
mile buffer, then
dist_030_var1=1,
else=0
32. PROJECT DESCRIPTION
• Takeaway
• We create a pool of distance attributes for all blocks, and
distances will be classified into different groups based on future
modeling.
• The data can be collected at block/lot/property level.
• Reusable Python script tools enables distance calculation for
point/polyline/polygon POI feature classes.
• The next step may be creating an index based on areal attributes,
such as distance-value index system.
• The raw output as well as the index system can be input
variables for future models.
33. FILE SYSTEM-
ORIGINAL DATA RawInput
DCP DOITT OPENDATA OpenStreet Collected
workflow_d
ocumentati
on
NYC_PubliclyAccessibleWater
Front_2014
NYC_SelectedFacilities_
2015
TANK Borough_Bo
undaries
cscl_pub.gdb NYC_Planim
etrics_2010
Noise_311_
07012014_0
7012015
TANK remedsitebo
rders
new-
york_new-
york.osm-
point.shp
Potential
Materials
nyc_paws_2
014shp
nyc_waterfrontp
arks_2014shp
nyc_facilities2015_shp Potential
Materials
nybb_15b CSCL SubwayStati
on.shp
NYC_DOITT_
Planimetric_
Seamless_2
010.gdb
Potential
Materials
Remediatio
n_site_bord
ers
PAWS.shp NYC_Waterfront
_Parks.shp
Facilities - 01 -
Schools.lyr
nybb.shp Centerline.s
hp
RailStation.s
hp
NYCPlanime
tric
Remediation
_site_border
s.shp
Facilities - 02 -
Recreational & Cultural
Facilities.lyr
Rail.shp PARK.shp
Facilities - 04 - Nursing
Homes, Hospitals,
Hospices and
Ambulatory Services.lyr
Subway.shp
Facilities - 10 - Food
Programs & Residential
Facilities for Adults and
Families.lyr
Facilities - 12 - Waste
Management
Facilities.lyr
Table File
Shapefile or Layer File
Tools and Documentation
Folder or Geodatabase
35. FILE SYSTEM-
CREATE DUMMY VARIABLE (BETA)
DistanceAnalysis
POI_buffer_inpu
t
POI_buffer_ouput table_input_Python
table_interim_S
AS
table_output_SAS table_tablejoin Tools_Python Tools_SAS
SubwayStation SubwayStation SubwayStation
condosuff_Subw
ayStation_count
.dbf
SubwayStation
condosuff_Subw
ayStation_count
.dbf
blk_boro*_Sub
wayStation_720
15_dummy.dbf
7_number_coun
t.py
buffer_count.sa
s
cdsuff_xy.csv
boro*_SubwaySt
ation_72015.gd
b
scratch.gdb
boro*_SubwayS
tation_72015_b
fct.dbf
boro*_SubwayStati
on_bfct.dbf
8_count_join.py
boro*_SubwaySt
ation_72015.shp
boro*_SubwaySt
ation_72015_bf
ct.shp
blk_boro*_Subw
ayStation_72015
_dummy.shp
Table File
Shapefile or Layer File
Tools and Documentation
Folder or Geodatabase
36. *FUTURE ACTIONS-
ADD POI
• Download original shapefiles in RawInput Folder
• Sort by the source of the files (DCP, DOITT, OPENDATA,
OpenStreetMap, or SelfCollection…)
• Put POI shapefiles in POI_inputPOI.gdb
• Select the Python Tools and SAS Tools to process
• Need to change POIs manually in each script
37. *FUTURE ACTIONS-
TOOLS AND RESULT TABLES…
• Network Analysis-
• Input
• POI_inputPOI.gdb
• POI_inputdtmblock.gdbblk(cent)
• Point Features only
• Tool_Python3_NA_NF.py
• dist_mean_inputPOI*dbf
• Tool_SASPOI_NetworkAnalystboro_macro
• dist_mean_outputPOI*dbf
• Tool_Python4_blkcent_dist_join
• NA_block_meandistPOI*dbf
• Generate Near Table-
• Input
• POI_inputPOI.gdb
• POI_inputdtmblock.gdbblk(cent)
• Point/Polyline/Polygon features
• Tool_Python5_make_near_table.py
• dist_mean_inputPOI*dbf
• Tool_SASPOI_MakeNearTable boro_macro
• dist_mean_outputPOI*dbf
• Tool_Python 6_near_Blkcent_dist_join.py
• NA_block_meandistPOI*dbf
38. *FUTURE ACTIONS-
SUMMARIZE THE RESULT
• Summarize the result in the master table of each boro
• Output_distDescriptiveboro*.xlsx
• Sort the result based on the method of distance calculation
• Near
• Sorted by ORIG_FID
• Network Analyst
• Sorted by ORIG_FID
• Mark the missing value with IncidentID
• Raster (Beta)
• Sorted by OID_12
• Mark the missing value with IncidentID
