Post on 08-Apr-2016
description
LEVY
MARION
CITRUS
SUMTER
Wildwood
Chiefland�
Legend
Final Turnpike ExtensionStudy Area
Chiefland�
Wildwood
Halfway PointI-75 HighwayMajor RoadsSurface WaterAgricultual ParcelsConservaton Ar eas�FloodZone 0 12,000 24,000 36,000 48,000
6,000
MetersHaving contracted with Florida Department of Transportation, we determined
the location of the planned expansion of roadways and the site of the accompanying service plaza. In spite of following the requirements of FDOT,
we captured the public concerns. Hence the factors that should be enrolled into
consideration consists of avoiding the surface water, wetlands ,flood zones
and conservation areas; areas with soils that do not readily support road and
building construction and steep slopes should be excluded from the proposal.
In addition, we will not involved any urban land uses into the construction
of the service plaza. The process of path finding and site selection are based on the professional advices from FDOT.
Recommended Service Plaza
Analysis for Turnpike Extension - Located from the current northern terminus west of Wildwood to the intersection with US 19
just south of Chiefland in Levy County- A good axis which creates a set of linkage with surrounding major roads.
- Avoiding water bodies, wetlands, conservation areas and flood zones.
- Passing through flat areas with soils that are mostly well-drained.
Legend
0 - .458811921
.458811921 - 1.261732782
1.261732783 - 2.064653643
2.064653644 - 2.982277485
2.982277486 - 4.014604307
4.014604308 - 5.391040069
5.39104007 - 7.799802653
7.799802654 - 12.61732782
12.61732783 - 29.24925995
Legend
Cost Raster
Value
High : 17.35
Low : 2
Legend
Final Service Plaza
Final Turnpike Extension
Final Sites Raster
<VALUE>
1.850000024 - 3.224313745
3.224313746 - 3.991372567
3.991372568 - 4.790392172
4.790392173 - 5.429607857
5.429607858 - 5.972941188
5.972941189 - 6.676078441
6.676078442 - 7.475098047
7.475098048 - 8.242156868
8.242156869 - 9.5
9.500000001 - 10
Agricultual Parcels
Service Plaza
Type of land use: TimberlandPrice: 453793 per acreArea: 32.07 acres
Analysis for Service PlazaThe proposed service plaza follows the basic requirements both from FDOT and public views.
-�Adjacent to the proposed turnpike extension, especially near the halfway point
-�Located on soils with proper drainage conditions-�Avoid flood zone and steep areas-�Maintaining a proper distance to urban land uses
0 460 920 1,380 1,840230
Meters
Legend
Final Turnpike Extension
County Boudary
Study Area
4 Counties
URP 6270 SECTION 5421 PROJECT 2 JINGRU ZHANG
0 72,000 144,000 216,000 288,000
36,000
Meters
Alternative2
Alternative1
Recommended
Solar Energy Reaesrch Park And Academy
LEGENDFinalSelection_Project
par_within500>25_final
Main_CONTROL
Parcel_Quiet_Selection
soil_Drainwell_selection
<all other values>
DRAINAGECL
EXCESSIVELY DRAINED
MODERATELY WELL DRAINED
WELL DRAINED
majrds_feb11
0
3,200
6,400
1,600
Meters
1 in = 2 miles
Alternative2
Alternative1
Recommended
LEGENDFinalSelection_Project
Parcel_Quiet_Selection
soil_Drainwell_selection
<all other values>
DRAINAGECL
EXCESSIVELY DRAINED
MODERATELY WELL DRAINED
WELL DRAINED
majrds_feb11
Potential locatio
n of the sit
es for th
e solar e
nergy
research
park and academy should be based on th
e
following cri
teria:
� - Located with
in 2.5 miles o
f the cit
y limits
of Masco
tte, FL
� - Must n
ot be with
in 3000 feet o
f any water f
eatures
� - Not w
ithin 1 m
ile of a school.
� - Not w
ithin 1 m
ile of any airp
ort.
� - Not w
ithin any co
nservatio
n lands.
� - Not w
ithin 1000 feet o
f a sinkhole.
� - Located on so
ils with
proper drainage.
� - Located with
in 500 feet o
f an existin
g major ro
ad .
� - Site m
ust be a m
inimum of 25 acre
s.
� - Proposed to
locate within agricu
ltutra
l landuse area.
- 25 acers i
n total
- Exce
ssively drained ground
- Price
: $24901.57 which
is relative
ly economic site
for in
vestment.
- Ideal dista
nce away from re
sidential places
- Right a
longside th
e mainroad
- Abundant sp
aces for fu
rther e
xpansion
- 25 acers i
n total
- Price
:$40257.33,which is
money-co
st
compaired with
the re
commended one.
- Very exce
ssively drained sy
stem.
- Located on th
e junction of tr
ansportatio
n
- Resid
ential nearby hinders expansio
n
- As it
is located on th
e boundary of the
chosen o
verall contro
lling area , it
might
activate th
e perip
hery high-tech development.
Text
- 25 acers i
n total .
- Price
: $32738.88.However it is
surrounded by
unavailable area so th
at outward expansio
n is
very lim
ited.
- Exce
ssively drained sy
stem.
- Located on th
e junction of tr
ansportatio
n
- Resid
ential nearby hinders expansio
nURP6270 Section5421 Project 1
Jingru ZHANG
0
450
900
225
Meters
´
JINGRU ZHAHG | URBAN & REGIONAL PLANNING
(352)283-2658 • zhANGjINGRU123@UfL.EdU
Sour
ce: E
sri,
Dig
italG
lobe
, Geo
Eye,
i-cu
bed,
Ear
thst
ar G
eogr
aphi
cs, C
NES
/Airb
us D
S, U
SD
A, U
SGS,
AEX,
Get
map
ping
, Aer
ogrid
, IG
N, I
GP,
sw
isst
opo,
and
the
GIS
Use
r Com
mun
ity
¯0
12
34
0.5
Mile
s
Graduate Thesis: A Parcel-Level Analysis of Coastal Hazard Impact on Manatee County’s Residential Lands: An Integration of GIS, HAZUS-MH and Land Use
Contact Info
GeoDesign: Spatial Implications of Sea-Level-Rise Policies on Future Development Patterns
Northeastern Florida Conservation Land Use Suitability Modeling • Lands Suitable for Maintenance of Ecological Process and Service
Using Census Longitudinal Employer-Household Dynamic Data to Assess RTS Transit Service Coverage
Estimate the impact of Miami-Dade Metro Rail System on Land Just Value
3
4
8
10
12
14
Sour
ce: E
sri,
Dig
italG
lobe
, Geo
Eye,
i-cu
bed,
Ear
thst
ar G
eogr
aphi
cs, C
NES
/Airb
us D
S, U
SD
A, U
SGS,
AEX,
Get
map
ping
, Aer
ogrid
, IG
N, I
GP,
sw
isst
opo,
and
the
GIS
Use
r Com
mun
ity
¯0
12
34
0.5
Mile
s
3
JINGRU ZHAHG (352)283-2658zhangjingru123@ufl.edu3415 SW 39th Blvd aPt 432gaineSville, fl, 32608
Ma, urBan and regional PlanninguniverSity of florida
BS,urBan and rural Planning & reSource ManageMent
huaqiao univerSity
Source: Esri, DigitalGlobe, GeoEye, i-cubed, Earthstar Geographics, CNES/Airbus DS, USDA, USGS,AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community
¯0 1 2 3 40.5
Miles
My study estimated buildings and building stock replacement value
exposed to projected coastal hazard scenarios. Residential properties are most vulnerable to the attacks of coastal hazards. Hence, my study summarized future residential land exposures and associated existing land uses by scenarios. Land use exposures were categorized by spatial locations with respect to the magnitude of sea level rises and associated storm surges. My study also developed a methodology to present the projected storm water depth at the parcel
level, and to identify the number of properties in each parcel. For categorized future residential capacities, my study supported the community developments while also reduced their vulnerability to coastal hazards. Suggestions were made in views of county’s land use plan, coastal elements, construction strategies and flood insurance.
HAZUS-MH was used to create 3 scenarios in terms of the conditions about sea-level-rises and associated storm surges. The techincal process included
delineating coastal floodplain, shoreline characterization with default dataset, producing storm water grids, and to produce the Hazard Event Report. The Event Report estimated the number of buildings in the study region, which havs an aggregated total replacement value and are also exposed to the storm surge. Additionally, the reports presented the distribution of the value with respect to the general land-use types by Study Region and Scenario respectively.
Parcels with storm water depths; darker colors represent higher average depths. Manatee County, FL 2040
RESEARCH FRAMWORK & INTRODUCTION OF HAZUS-MH
WILL cOAstAL fLOOd hAzARds AffEct thE cOUNty’s LANd dEvELOPmENt? WhAt stRAtEGIEs cAN hELP ImPROvE thE INtEGRAtION Of LANd UsE PLANNING ANd cOAstAL hAzARd AdAPtAtION?
4
Source: Esri, DigitalGlobe, GeoEye, i-cubed, Earthstar Geographics, CNES/Airbus DS, USDA, USGS,AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community
¯0 1 2 3 40.5
Miles“condominium improved,” is a land use category which has stacked parcels on exactly the same location. In this case, each parcel not only consists of multiple individual units, but also contains more than one census block. With the GIS-produced statistics of coincident events, we would be able to check parcels individually and to know the floods' impact based on the number of registered properties and the occupancy structures, as well as the local storm wave heights
arcGIS was proactively used in compiling and disaggregating the land use information into the parcel dataset. More importantly , it was also used for producing Zonal Statistics of the storm water depth. The zonal stats were then intersected with the parcels, in order to explore future residential lands and their existing condition, the special concerns about "stacked properties", as well as the vacant future capacities.
Parcels with storm water depth: a stillwater-elevation-based storm surge
An inundated Condo Complex with 212 Registered Properties within 187 building footprints
An inundated Condo Complex with 322 Registered Properties within 63 building footprints
An inundated Condo Complex with 46 Registered Properties and 23 building footprints
Parcels with storm water depth: a stillwater-elevation-based storm surge, with the average depth ≥ 4 feet
Residential parcels with storm water depth: a stillwater-elevation-based storm surge, with the average depth ≥ 4 feet
GIS ANALYSIS WITH STORM SURGE GRIDS PRODUCED BY HAZUS
5
GRAdUAtE thEsIs: A PARcEL-LEvEL ANALysIs Of cOAstAL hAzARd ImPAct ON mANAtEE cOUNty’s REsIdENtIAL LANds: AN INtEGRAtION Of GIs, hAzUs-mh ANd LANd UsE
County Boundary
Census Blocks
Vacant Lands inside a 100-r Stillwater SS and Inside Potential SLR ZonesSLRPCT40, LUC_DESCRI
1, Vacant Res. Common Area (1554)(New 2014),Vacant Res.Common Area (1554)(New 2014)
1, Vacant Residential w/Site Amen. (1554),Vacant Residential w/Site Amen (1554)
1, Vacant Mobile Home Lot Platted (1554)
1, Vacant Res.Common Area (1554)(New 2014),Vacant Res. Common Area (1554)(New 2014)
1, Vacant Condominia Residential (1554)
1, Vacant Non-Residential/Unusable (1555)
1, Vacant Residential Tract/Unusable (1554)
1, Vacant Residential Platted (1554)
1, Vacant Commercial (1555)
slr_1m
still_proValue
High : 18.2834
Low : 8.58307e-006
¯0 1.5 3 4.5 60.75
Miles
County Boundary
Census Blocks
Vacant Lands inside a 100-yr Stillwater SS but OUT of Potential SLR ZoneSLRPCT40, LUC_DESCRI
999, Vacant Mobile Home Lot Platted (1554)
999, Vacant Res.Common Area (1554)(New 2014),Vacant Res. Common Area (1554)(New 2014)
999, Vacant Acreage,Not Ag. 10+ Acres (1555),Vacant Acreage,Not Ag.10+ Acres(1555)
999, Vacant Institutional (1555)
999, Vacant Commercial w/Impv (1555)
999, Vacant Residential Platted (1554)
999, Vacant Residential Tract/Unusable (1554)
999, Vacant Residential w/Site Amen. (1554),Vacant Residential w/Site Amen (1554)
999, Vacant Condominia Residential (1554)
999, Vacant Res. Common Area (1554)(New 2014),Vacant Res.Common Area (1554)(New 2014)
slr_1m
still_proValue
High : 18.2834
Low : 8.58307e-006
¯0 1.5 3 4.5 60.75
Miles
County Boundary
Census Blocks
Vacant Lands inside a Half-Meter SLR Induced SS Surface but Out of Stillwater<all other values>
LUC_DESCRIVacant Condominia Residential (1554)
Vacant Res. Common Area (1554)(New 2014),Vacant Res.Common Area (1554)(New 2014)
Vacant Res.Common Area (1554)(New 2014),Vacant Res. Common Area (1554)(New 2014)
Vacant Residential Platted (1554)
Vacant Residential Tract/Unusable (1554)
Vacant Residential w/Site Amen. (1554),Vacant Residential w/Site Amen (1554)
half_proValue
High : 19.7381
Low : 1.43051e-005
¯0 1.5 3 4.5 60.75
Miles
Vacant Lands Exposure-Potential Future Residential Uses
County BoundaryCensus Blocks<all other values>
LUC_DESCRIVacant Condominia Residential (1554)Vacant Res. Common Area (1554)(New 2014),Vacant Res.Common Area (1554)(New 2014)Vacant Res.Common Area (1554)(New 2014),Vacant Res. Common Area (1554)(New 2014)Vacant Residential Platted (1554)Vacant Residential Tract/Unusable (1554)Vacant Residential w/Site Amen. (1554),Vacant Residential w/Site Amen (1554)
full_proValue
High : 22.2779
Low : 2.19345e-005
¯0 1.5 3 4.5 60.75
Miles
Vacant Lands Exposure-Potential Future Residential Uses
Class 4 - FullSSVacOther Vacant LandsVacant Residential
Class 3 - HalfSSVacOther Vacant LandsVacant Residential Vacant Residential
Class 2 - StillOutSLRVacSLRPCT40, LUC_DESCRI
Vacant ResidentialOther Vacant Lands
Class1 - StillInSLRVacSLRPCT40, LUC_DESCRI
Vacant ResidentialOther Vacant LandsCounty BoundaryCensus Blocks
full_proValue
High : 22.2779
Low : 2.19345e-005 ¯ 0 1.5 3 4.5 60.75Miles
Vacant Lands Exposure-Potential Future Residential Uses
Class 4 - FullSSVacOther Vacant LandsVacant Residential
Class 3 - HalfSSVacOther Vacant LandsVacant Residential Vacant Residential
Class 2 - StillOutSLRVacSLRPCT40, LUC_DESCRI
Vacant ResidentialOther Vacant Lands
Class1 - StillInSLRVacSLRPCT40, LUC_DESCRI
Vacant ResidentialOther Vacant LandsCounty BoundaryCensus Blocks
full_proValue
High : 22.2779
Low : 2.19345e-005 ¯ 0 1.5 3 4.5 60.75Miles
Vacant lands as residential future capacities: inside a 100-yr stillwater-based storm surge
area and will not be affected by a potential 1m sea-level-rise
Vacant lands as future capacities: inside a 100-yr stillwater-based storm surge area , the storm surges are induced by a 0.5m SLR
Vacant lands as future capacities: inside a 100-yr
stillwater-based storm surge area , the storm surges are
induced by an 1m SLR
Vacant lands as future residential capacities: inside a 100-yr stillwater-based storm surge area and might be affected by a potential 1m sea-level-rise
6
Vacant Lands Exposure-Potential Future Residential Uses
Class 4 - FullSSVacOther Vacant LandsVacant Residential
Class 3 - HalfSSVacOther Vacant LandsVacant Residential Vacant Residential
Class 2 - StillOutSLRVacSLRPCT40, LUC_DESCRI
Vacant ResidentialOther Vacant Lands
Class1 - StillInSLRVacSLRPCT40, LUC_DESCRI
Vacant ResidentialOther Vacant LandsCounty BoundaryCensus Blocks
full_proValue
High : 22.2779
Low : 2.19345e-005 ¯ 0 1.5 3 4.5 60.75Miles
Vacant Lands Exposure-Potential Future Residential Uses
Class 4 - FullSSVacOther Vacant LandsVacant Residential
Class 3 - HalfSSVacOther Vacant LandsVacant Residential Vacant Residential
Class 2 - StillOutSLRVacSLRPCT40, LUC_DESCRI
Vacant ResidentialOther Vacant Lands
Class1 - StillInSLRVacSLRPCT40, LUC_DESCRI
Vacant ResidentialOther Vacant LandsCounty BoundaryCensus Blocks
full_proValue
High : 22.2779
Low : 2.19345e-005 ¯ 0 1.5 3 4.5 60.75Miles
Vacant Lands Exposure-Potential Future Residential Uses
Class 4 - FullSSVacOther Vacant LandsVacant Residential
Class 3 - HalfSSVacOther Vacant LandsVacant Residential Vacant Residential
Class 2 - StillOutSLRVacSLRPCT40, LUC_DESCRI
Vacant ResidentialOther Vacant Lands
Class1 - StillInSLRVacSLRPCT40, LUC_DESCRI
Vacant ResidentialOther Vacant LandsCounty BoundaryCensus Blocks
full_proValue
High : 22.2779
Low : 2.19345e-005 ¯ 0 1.5 3 4.5 60.75Miles
CATOGRIZATIONS OF CURRENTLY vACANT FUTURE RESIDENTIAL
7
GRAdUAtE thEsIs: A PARcEL-LEvEL ANALysIs Of cOAstAL hAzARd ImPAct ON mANAtEE cOUNty’s REsIdENtIAL LANds: AN INtEGRAtION Of GIs, hAzUs-mh ANd LANd UsE
hOW mUch Of thE BUILt ENvIRONmENt, If dEvELOPEd At thE cURRENt tRENd, WOULd BE POtENtIALLy INUNdAtEd WhEN sEA LEvEL RIsEs? hOW WOULd thE cOUNty’s LANd UsE PAttERNs chANGE cOmPARAtIvELy If POLIcIEs WERE PUt IN PLAcE tO LImIt URBAN dEvELOPmENt IN cOAstAL hAzARd AREAs?
This study explores the impacts on projected spatial development patterns based on restrictive land development policies, with the goals of mitigating potential economic loss resulting from the increased vulnerability of the coastline based on 1meter of sea level rise. GIS was used along with population projections and current land use data to analyze growth and potential development at a regional scale.
We modeled a projection of Hillsborough County’s current trend of land- use patterns into 2045, and analyzed how much of the new development would fall within future storm surge projections. An alternative land-use scenario was created to discourage new development in high risk areas.
In ArcMap, we used per-acre densities from the County's future land-use plan to visualize the proportional allotment of development occurring on parcels suitable for redevelopment, infill areas, as well as parcels with conservation priorities.
THE GEODESIGN PROCESS
GEOdEsIGN mEthOd: LANd-UsE cONfLIct IdENtIfIcAtION stRAtEGy (LUcIsPLUs). "A PROcEss Of LANd UsE ANALysIs ANd POPULAtION ALLOcAtIONs UsING tRAdItIONAL sUItABILIty tO IdENtIfy cONfLIcts."
3D visulization of Tampa Bay area and central business district.
ArcScene and ArcGlobe
8
Comparing residential allocations. The trend scenario: 37,775; SLR
scenario: 30,280 (Acres)
Comparing Residential Allocations. Trend scenario: 55,183; SLR Scenario: 33,052 (Acres)
Retrieving from coastal hazard areas: combined residential and employment allocation.
The trend of land development: combined
residential and employment allocation
EMPLOYMENT DENSITY , HILLSBOROUGH COUNTY 2050
9
GEOdEsIGN: sPAtIAL ImPLIcAtIONs Of sEA-LEvEL-RIsE POLIcIEs ON fUtURE dEvELOPmENt PAttERNs
Objective 6.1: Lands proximal to hazadous waste sites
Objective 6.2: Lands significant for the process of wildfire movement
Objective 6.3: Lands important for maintaenance of the process of flooding and flood storage
Objective 6.4: Lands proximal to both fire and flooding processes
GOAL 6: IDENTIFY LANDS SUITABLE FOR ECOLOGICAL PROCESS AND SERvICES
10
NortheasterN Florida CoNservatioN laNd Use sUitability ModeliNg • laNds sUitable fOR mAINtENANcE Of EcOLOGIcAL PROcEss ANd sERvIcE
THE GOAL OF CONSERvATION
dEtERmINE thE LANds mOst sUItABLE fOR mAINtAINING EcOLOGIcAL INtEGRIty IN thE 5 cOUNtIEs Of NOtthEAstERN fLORIdA
This project focused on developing decision-making skill at the regional scale using Spatial Analyst, Model Builder,w and land use suitability analysis techniques within a group and individual setting. Our group defined goals and objectives for future land use decisions as they relate to the region's conservation priority. Our goals and objectives were intended to be used to guide a regional GIS analysis to identify future suitability for the conservation category within the study area.
The goal of conservation consists of my Goal 6 and 7 other goals with regard to water quality, landscape integrity, biodiversity, and the economic feasibility of development.
11
¯
Blocks Covered by Service AreasTrasit Supportiveness Status
Both
Home Yes Work No
Neither
Work Yes Home No
City Limit
0 0.8 1.6 2.4 3.20.4Miles
¯
City Limit
Census Block Group Transit Supportiveness
3 - Both Supportive
2 - Job- Based Supportive
1 - Home-Based Supportive
Areas within a 1/4 Mile Network Distace of a Stop
0 0.8 1.6 2.4 3.20.4Miles
"thE PLANNING mEthOd"
"thE ALtERNAtIvE mEthOd"
¯
Census Blocks with LEHD InformationBlocks Serving as Home Places
9999 - Neither Supportive
-3 - Both Supportive
-2 - Job-Based Supportive
-1 Home-Based Supportive
City Limit
0 0.8 1.6 2.4 3.20.4Miles
¯
Census Blocks with LEHD InformationBlocks Serving as Work Places
9999 - Neither Supportive
-3 - Both Supportive
-2 - Job-Based Supportive
-1 - Home-Based Supportive
City Limit
0 0.8 1.6 2.4 3.20.4Miles
The “Home” locations (block groups) covered by RTS's service, with respect to level of transit supportiveness.
RTS's network-based service areas intersected with the transit-supportive block groups
¯
City Limit
Census Block Group Transit Supportiveness
3 - Both Supportive
2 - Job- Based Supportive
1 - Home-Based Supportive
0 0.8 1.6 2.4 3.20.4Miles
¯
City Limit
Census Block Group Transit Supportiveness
3 - Both Supportive
2 - Job- Based Supportive
1 - Home-Based Supportive
Areas within a 1/4 mile Distance from a Stop
0 0.8 1.6 2.4 3.20.4Miles
The “Work” locations (block groups) covered by RTS's service, with respect to level of transit supportiveness.
The transit-supportive census block groups,
city of Gainesville.
The transit-supportive block groups intersected with buffer-based RTS's service areas
Block groups, both transit-supportive and covered by RTS's service as either the "wotk" or "home” location
12
75% 49%
“thE PLANNING mEthOd"BAsEd ON A qUARtER-mILE EUcLIdEAN dIstANcE Of thE tRANsIt stAtION
thE ALtERNAtIvE mEthOdBAsEd ON A qUARtER-mILE NEtWORk dIstANcE Of thE tRANsIt stAtION
of the land area within the RTS’s buffered quarter-mile service areas can be defined as “transit supportive” based on either job or housing density
of the land area within the RTS’s network-based quarter-mile service areas can be defined as “transit supportive” based on either job or housing density
hOW WELL Rts's tRANsIt sERvIcE cOvERs REsIdENtIAL, ANd EmPLOymENt LOcAtIONs ANd hOW WELL It mEEts thE tRAvEL dEmANd BEtWEEN thE PLAcEs WhERE PEOPLE LIvE ANd WORk?
This research is to understand the service quality of the Gainesville Regional Transit System by analyzing the transit service coverage, or the proportion of regions served by RTS transit. "The Planning Method" evaluated RTS's service coverage based on the share of transit-supportive land acreage covered by RTS transit service. The GIS Buffer tool was used to produce the service area. Census blocks were coded with the level of transit supportiveness, based on residential and employment densities.
The alternative method measured RTS's service coverage based on the number of commutes covered by RTS transit service. This method identified that a pair of Census Blocks (the places where people live and work) shares a “job” or a
trip to work and back. ArcGIS Network Analyst was used to produce service areas. The result shows the share of commutes (the job flows) covered by RTS's network service areas
GIS ANALYSIS WITH STORM SURGE GRIDS PRODUCED BY HAZUS
The estimation of the service coverage was conducted in a crossed table. Every commute was identified either as the home location or the work location. And each of the locations has fields showing its transit accessibility (“within “or “not within” the quarter-mile buffer of network service area) and its level of transit supportiveness.
13
UsING cENsUs LONGItUdINAL EmPLOyER-hOUsEhOLd dyNAmIc dAtA tO AssEss Rts tRANsIt sERvIcE cOvERAGE
!P
!P
!P
!P
!P
!P
!P
!P
!P!P
!P!P!P
!P!P
!P
!P
!P
!P !P!P
!P !P
!(
!(
!(
!(!(
!(
!(!(!(!(!(!(
!(!(!(!(!(!(!(
!(!(!(
!(
!(!(
!(!(!(
!(
!(!(!(!(!(!(
!(
!(
!(!(
!(
!(
!(
!(
!(!(!(!(!(
!(!(!(!(!(!(!(!(!(!(
!(
!(!(!(
!(
!(!(!(
!(!(!(
!(!(
!(
!(!(
!(
!(!(!(!(!(
!(
!(
!(
!(!(!(
!(!(!(!(!(
!(
!(
!(
!(!(
!(
!(!(!(!(!(!(
!(!(!(
!(!(
!(!(
!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(!(!(
!(!(
!(!(
!(!(
!(
!(!(!(
!(
!(
!(
!(!(!(
!(!(!(!(
!(!(
!(
!(
!(!(
!(
!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(
!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(
!(
!(!(!(!(!(!(!(
!(!(!(
!(!(
!(!(!(!(!(
!(!(!(
!(!(!(!(!(!(!(
!(
!(!(
!(!(
!(
!(!(!(!(
!(
!(!(!(!(!(
!(
!(
!(
!(
!(
!(!(!(
!(
!(
!(
!(!(!(
!(
!(!(
!(!(!(
!(!(!(!(!(
!(!(!(!(
!(!(!(!(!(
!(
!(!(!(!(!(
!(
!(
!(!(
!(!(!(
!(!(!(
!(
!(
!(
!(!(
!(
!(!(
!(!(
!(
!(
!(
!(!(
!(!(
!(
!(
!(!(
!(!( !(
!(
!(!(!(!(
!(!(!(
!(!(
!(!(
!(!(
!(
!(
!(!(!(!(!(!(!(
!(
!(!(!(
!(!(
!(!(!(
!(!(
!(
!(
!(
!(
!(!(
!(
!(!(!(!(!(!(!(!(!(
!(!(
!(!(
!(!(!(
!(
!(!(!(
!(
!(!(!(
!(!(!(!(!(
!(!(!(!(
!(!(
!(!(!(!(!(!(!(!(!(!(!(
!(
!(!(!(!(!(!(
!(!(!(
!(!(!(!(!(!(
!(!(
!(!(!(
!(!(!(!(
!(!(!(
!(!(!(
!(!(
!(!(!(!(!(
!(!(
!(!(
!(!(!(!(
!(!(!(!(!(!(!(!(
!(!(!(!(!(!(!(
!(!(!(!(!(!(!(
!(
!(!(
!(!(!(!(
!(
!(
!(!(!(!(!(!(!(!(
!(
!(!(!(!(!(!(!(
!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(
!(
!(!(!(
!(!(!(
!(!(!(!(!(!(!(!(
!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(!(!(
!(!(!(!(!(!(!(
!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(!(
!(!(!(!(!(!(
!(!(!(!(!(!(!(!(
!(!(
!(!(
!(!(!(
!(!(!(!(
!(!(
!(!(!(!(!(!(!(!(
!(
!(!(!(!(!(
!(
!(!(!(!(!(
!(!(!(
!(!(
!(!(!(!(
!(!(
!(!(
!(!(!(!(!(!(!(!(
!(!(
!(
!(
!(!(!(!(!(
!(
!(!(!(!(
!(
!(
!(!(!(!(!(!(!(!(!(
!(!(!(
!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(
!(
!(!(!(
!(!(!(!( !(
!( !(!(!(!(!(!(!(!(!(!(!(
!(!(!(!(
!(!(!(
!(!(!(!( !(!(!(
!(!(
!(!(!(
!( !(
!(!(
!(
!(
!(
!(!(
!(
!(!(
!(!(
!(
!(!(!(!(
!(!(
!(!(!(
!(
!(
!(!(!(!(!(!(!(!(!(!(!(
!(
!(
!(!(!(!(!(!(!(!(!(
!(
!(
!(
!(!(
!(
!(
!(!(
!(
!(
!(!(!(!(!(!(!(!(
!(
!(!(!(
!(
!(
!(!(!(
!(
!(!(!( !(!(!(!(!(!(
!(
!(
!(!(!(
!(!(!( !(!(
!(!(!(!(!(!(!( !(!(
!(!(
!( !(
!( !(
!(
!( Sources: Esri, H
ERE, DeLorm
e, USGS, In
termap, in
crement P Corp., N
RCAN,
Esri Japan, M
ETI, Esri C
hina (Hong Kong), E
sri (Thailand), T
omTom,
MapmyIndia, © OpenStre
etMap contributors,
and the GIS User Community
GWR Rail Statio
n Coefficient V
alue
C12_RailDi
!(-0.072023 - -
0.068120
!(-0.068119 - -
0.066363
!(-0.066362 - -
0.065069
!(-0.065068 - -
0.063871
!(-0.063870 - -
0.062282
!(-0.062281 - -
0.057677
!(-0.057676 - -
0.046761
!(-0.046760 - -
0.032140
!(-0.032139 - -
0.028836
!(-0.028835 - -
0.023681
MetroRail
!PRailStation_Pro
0̄
1
2
3
4
0.5
Miles
This research identified the factors that affect the housing value (just value) around the Miami MetroRail area, it sought to determine the spatial relationship between the metro-rail networks and the housing system. With ArcGIS Spatial Statistics extension and Geostatistical tools, mutiple variables were investigated through a l inear regression model (Ordinary Least Square) and Geographically Weighted Regression.
Diagnostic statistics (adjust R-square) reveals that GWR as a local model better fits the dataset than the OLS model (a global model).The GWR results show that the age of building, other than the proximity to metro-rail stations, is the most significant factor that led to the variation of housing just value. Model diagnostic information shows issues of missing key variables. Hence, in order to better justify the model, it is important to further solicit input variables,
!P
!P
!P
!P
!P
!P
!P
!P
!P!P
!P!P
!P
!P
!P!P!P!P
!P
!P!P
!P
!P
!(!(!( !(!(!( !(!(!(!(!(!( !(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!( !(!(!( !(!(!(!( !(!( !(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!( !(!( !(!(!(
!(!(!( !( !(!(!(!( !(!(!(!(!(!( !( !(!(!(!(!( !(!(!(!(!(!( !( !(!(!( !( !(!(!(!(!(!(!(!(!( !( !(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!( !(!(!( !( !(!(!( !(!(!(!( !(!( !(!(!(!( !(!(!( !(!( !(!(
!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!( !( !(!(!(!(!(!(!(!( !(!(!( !(!(!( !(!(!(!(!( !(!(!(!(!(!( !( !(!( !(!(!(!( !(!( !(!(!(!( !(!(!( !(
!(!(!(!(!(!( !(!(!(!( !(!(!(!(!( !(!( !(!(!(!(!(!( !(!(!( !(!(!(!(!(!(!(!( !(!(!(!(!(!( !(!(!( !(!( !(!(!(!( !(!( !(!(!(!(!( !(!(!(!(!( !(!(!(!(!( !(!(!(!( !(!( !( !(!(!(!(!(!(!( !(!(!(!(!(!(!(!( !(!(!( !(!( !( !(!(
!( !(!(!(!(!(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!(!( !(!(!( !(!(!(!(!(!(!( !(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!( !(!( !(!(!(!(!( !(!(!(!(!(!(!( !(!( !(!(!( !(!( !(!(!(!(!( !(!( !( !(!( !(!( !(!(!(!(!(!(!( !(!( !(!(!( !(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!( !( !( !(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!(!(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!( !(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!( !(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!( !(!(!(!(!(!( !(!(!(!(!( !(!(!(
!(!( !(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!( !(!(!( !(!(!(!(!(!( !(!(!(!( !( !(!( !(!(!(!(!(!(!( !(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(!( !(!(!(!(
!( !(
!(!(
!(
!(
!(!( !( !(!(!(
!(!( !(!(!(!(!( !(!( !(!(!(
!(
!(
!(!(!(!(!(!(!(!(!(!(!(!( !(
!(!(!(!( !(!(!(!(!(
!(
!(
!(
!(
!(
!(
!(
!(!( !(!( !(!(!(!(!(!(!(!( !(!(!( !(
!(!(
!(!(!(!( !(!(!(
!(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!( !(!(!(!(!(!(!(!(!(
!( !(!(
!(
!(!(
!(
!(
Sources: Esri, HERE, DeLorme, USGS, Intermap, increment P Corp., NRCAN,Esri Japan, METI, Esri China (Hong Kong), Esri (Thailand), TomTom,MapmyIndia, © OpenStreetMap contributors, and the GIS User Community
OLS Standard ResidualStdResid!( < -1.5 Std. Dev.
!( -1.5 - -0.50 Std. Dev.
!( -0.50 - 0.50 Std. Dev.
!( 0.50 - 1.5 Std. Dev.
!( 1.5 - 2.5 Std. Dev.
!( > 2.5 Std. Dev.
MetroRail
!P RailStation_Pro0̄ 1 2 3 40.5
Miles
The OLS model explains 85.9154% of the variation in the dependent variable.
Residuals are clustered, showing mising variables
!P
!P
!P
!P
!P
!P
!P
!P
!P!P
!P!P
!P
!P
!P!P!P!P
!P
!P!P
!P
!P
!(!(!( !(!(!( !(!(!(!(!(!( !(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!( !(!(!( !(!(!(!( !(!( !(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!( !(!( !(!(!(
!(!(!( !( !(!(!(!( !(!(!(!(!(!( !( !(!(!(!(!( !(!(!(!(!(!( !( !(!(!( !( !(!(!(!(!(!(!(!(!( !( !(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!( !(!(!( !( !(!(!( !(!(!(!( !(!( !(!(!(!( !(!(!( !(!( !(!(
!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!( !( !(!(!(!(!(!(!(!( !(!(!( !(!(!( !(!(!(!(!( !(!(!(!(!(!( !( !(!( !(!(!(!( !(!( !(!(!(!( !(!(!( !(
!(!(!(!(!(!( !(!(!(!( !(!(!(!(!( !(!( !(!(!(!(!(!( !(!(!( !(!(!(!(!(!(!(!( !(!(!(!(!(!( !(!(!( !(!( !(!(!(!( !(!( !(!(!(!(!( !(!(!(!(!( !(!(!(!(!( !(!(!(!( !(!( !( !(!(!(!(!(!(!( !(!(!(!(!(!(!(!( !(!(!( !(!( !( !(!(
!( !(!(!(!(!(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!(!( !(!(!( !(!(!(!(!(!(!( !(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!( !(!( !(!(!(!(!( !(!(!(!(!(!(!( !(!( !(!(!( !(!( !(!(!(!(!( !(!( !( !(!( !(!( !(!(!(!(!(!(!( !(!( !(!(!( !(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!( !( !( !(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!(!(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!( !(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!( !(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!( !(!(!(!(!(!( !(!(!(!(!( !(!(!(
!(!( !(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!( !(!(!( !(!(!(!(!(!( !(!(!(!( !( !(!( !(!(!(!(!(!(!( !(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(!( !(!(!(!(
!( !(
!(!(
!(
!(
!(!( !( !(!(!(
!(!( !(!(!(!(!( !(!( !(!(!(
!(
!(
!(!(!(!(!(!(!(!(!(!(!(!( !(
!(!(!(!( !(!(!(!(!(
!(
!(
!(
!(
!(
!(
!(
!(!( !(!( !(!(!(!(!(!(!(!( !(!(!( !(
!(!(
!(!(!(!( !(!(!(
!(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!( !(!(!(!(!(!(!(!(!(
!( !(!(
!(
!(!(
!(
!(
Sources: Esri, HERE, DeLorme, USGS, Intermap, increment P Corp., NRCAN,Esri Japan, METI, Esri China (Hong Kong), Esri (Thailand), TomTom,MapmyIndia, © OpenStreetMap contributors, and the GIS User Community
StdResid!( < -1.5 Std. Dev.
!( -1.5 - -0.50 Std. Dev.
!( -0.50 - 0.50 Std. Dev.
!( 0.50 - 1.5 Std. Dev.
!( > 1.5 Std. Dev.
MetroRail
!P RailStation_Pro0̄ 1 2 3 40.5
Miles
The GWR model explains 86.7377% of the
variation in the dependent variable. However, Spatial autocorrelation test shows
model misspecification, which means that there are
important variables missing.
Spatial StatiSticS: Modeling Spatial RelationShipS
14
!P
!P
!P
!P
!P
!P
!P
!P
!P!P
!P!P!P
!P!P
!P
!P
!P
!P !P!P
!P !P
!(
!(
!(
!(!(
!(
!(!(!(!(!(!(
!(!(!(!(!(!(!(
!(!(!(
!(
!(!(
!(!(!(
!(
!(!(!(!(!(!(
!(
!(
!(!(
!(
!(
!(
!(
!(!(!(!(!(
!(!(!(!(!(!(!(!(!(!(
!(
!(!(!(
!(
!(!(!(
!(!(!(
!(!(
!(
!(!(
!(
!(!(!(!(!(
!(
!(
!(
!(!(!(
!(!(!(!(!(
!(
!(
!(
!(!(
!(
!(!(!(!(!(!(
!(!(!(
!(!(
!(!(
!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(!(!(
!(!(
!(!(
!(!(
!(
!(!(!(
!(
!(
!(
!(!(!(
!(!(!(!(
!(!(
!(
!(
!(!(
!(
!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(
!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(
!(
!(!(!(!(!(!(!(
!(!(!(
!(!(
!(!(!(!(!(
!(!(!(
!(!(!(!(!(!(!(
!(
!(!(
!(!(
!(
!(!(!(!(
!(
!(!(!(!(!(
!(
!(
!(
!(
!(
!(!(!(
!(
!(
!(
!(!(!(
!(
!(!(
!(!(!(
!(!(!(!(!(
!(!(!(!(
!(!(!(!(!(
!(
!(!(!(!(!(
!(
!(
!(!(
!(!(!(
!(!(!(
!(
!(
!(
!(!(
!(
!(!(
!(!(
!(
!(
!(
!(!(
!(!(
!(
!(
!(!(
!(!( !(
!(
!(!(!(!(
!(!(!(
!(!(
!(!(
!(!(
!(
!(
!(!(!(!(!(!(!(
!(
!(!(!(
!(!(
!(!(!(
!(!(
!(
!(
!(
!(
!(!(
!(
!(!(!(!(!(!(!(!(!(
!(!(
!(!(
!(!(!(
!(
!(!(!(
!(
!(!(!(
!(!(!(!(!(
!(!(!(!(
!(!(
!(!(!(!(!(!(!(!(!(!(!(
!(
!(!(!(!(!(!(
!(!(!(
!(!(!(!(!(!(
!(!(
!(!(!(
!(!(!(!(
!(!(!(
!(!(!(
!(!(
!(!(!(!(!(
!(!(
!(!(
!(!(!(!(
!(!(!(!(!(!(!(!(
!(!(!(!(!(!(!(
!(!(!(!(!(!(!(
!(
!(!(
!(!(!(!(
!(
!(
!(!(!(!(!(!(!(!(
!(
!(!(!(!(!(!(!(
!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(
!(
!(!(!(
!(!(!(
!(!(!(!(!(!(!(!(
!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(!(!(
!(!(!(!(!(!(!(
!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(!(
!(!(!(!(!(!(
!(!(!(!(!(!(!(!(
!(!(
!(!(
!(!(!(
!(!(!(!(
!(!(
!(!(!(!(!(!(!(!(
!(
!(!(!(!(!(
!(
!(!(!(!(!(
!(!(!(
!(!(
!(!(!(!(
!(!(
!(!(
!(!(!(!(!(!(!(!(
!(!(
!(
!(
!(!(!(!(!(
!(
!(!(!(!(
!(
!(
!(!(!(!(!(!(!(!(!(
!(!(!(
!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(
!(
!(!(!(
!(!(!(!( !(
!( !(!(!(!(!(!(!(!(!(!(!(
!(!(!(!(
!(!(!(
!(!(!(!( !(!(!(
!(!(
!(!(!(
!( !(
!(!(
!(
!(
!(
!(!(
!(
!(!(
!(!(
!(
!(!(!(!(
!(!(
!(!(!(
!(
!(
!(!(!(!(!(!(!(!(!(!(!(
!(
!(
!(!(!(!(!(!(!(!(!(
!(
!(
!(
!(!(
!(
!(
!(!(
!(
!(
!(!(!(!(!(!(!(!(
!(
!(!(!(
!(
!(
!(!(!(
!(
!(!(!( !(!(!(!(!(!(
!(
!(
!(!(!(
!(!(!( !(!(
!(!(!(!(!(!(!( !(!(
!(!(
!( !(
!( !(
!(
!( Sources: Esri, H
ERE, DeLorm
e, USGS, In
termap, in
crement P Corp., N
RCAN,
Esri Japan, M
ETI, Esri C
hina (Hong Kong), E
sri (Thailand), T
omTom,
MapmyIndia, © OpenStre
etMap contributors,
and the GIS User Community
GWR Rail Statio
n Coefficient V
alue
C12_RailDi
!(-0.072023 - -
0.068120
!(-0.068119 - -
0.066363
!(-0.066362 - -
0.065069
!(-0.065068 - -
0.063871
!(-0.063870 - -
0.062282
!(-0.062281 - -
0.057677
!(-0.057676 - -
0.046761
!(-0.046760 - -
0.032140
!(-0.032139 - -
0.028836
!(-0.028835 - -
0.023681
MetroRail
!PRailStation_Pro
0̄
1
2
3
4
0.5
Miles
!P
!P
!P
!P
!P
!P
!P
!P
!P!P
!P!P
!P
!P
!P!P!P!P
!P
!P!P
!P
!P
!(!(!( !(!(!( !(!(!(!(!(!( !(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!( !(!(!( !(!(!(!( !(!( !(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!( !(!( !(!(!(
!(!(!( !( !(!(!(!( !(!(!(!(!(!( !( !(!(!(!(!( !(!(!(!(!(!( !( !(!(!( !( !(!(!(!(!(!(!(!(!( !( !(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!( !(!(!( !( !(!(!( !(!(!(!( !(!( !(!(!(!( !(!(!( !(!( !(!(
!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!( !( !(!(!(!(!(!(!(!( !(!(!( !(!(!( !(!(!(!(!( !(!(!(!(!(!( !( !(!( !(!(!(!( !(!( !(!(!(!( !(!(!( !(
!(!(!(!(!(!( !(!(!(!( !(!(!(!(!( !(!( !(!(!(!(!(!( !(!(!( !(!(!(!(!(!(!(!( !(!(!(!(!(!( !(!(!( !(!( !(!(!(!( !(!( !(!(!(!(!( !(!(!(!(!( !(!(!(!(!( !(!(!(!( !(!( !( !(!(!(!(!(!(!( !(!(!(!(!(!(!(!( !(!(!( !(!( !( !(!(
!( !(!(!(!(!(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!(!( !(!(!( !(!(!(!(!(!(!( !(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!( !(!( !(!(!(!(!( !(!(!(!(!(!(!( !(!( !(!(!( !(!( !(!(!(!(!( !(!( !( !(!( !(!( !(!(!(!(!(!(!( !(!( !(!(!( !(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!( !( !( !(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!(!(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!( !(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!( !(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!( !(!(!(!(!(!( !(!(!(!(!( !(!(!(
!(!( !(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!( !(!(!( !(!(!(!(!(!( !(!(!(!( !( !(!( !(!(!(!(!(!(!( !(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(!( !(!(!(!(
!( !(
!(!(
!(
!(
!(!( !( !(!(!(
!(!( !(!(!(!(!( !(!( !(!(!(
!(
!(
!(!(!(!(!(!(!(!(!(!(!(!( !(
!(!(!(!( !(!(!(!(!(
!(
!(
!(
!(
!(
!(
!(
!(!( !(!( !(!(!(!(!(!(!(!( !(!(!( !(
!(!(
!(!(!(!( !(!(!(
!(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!( !(!(!(!(!(!(!(!(!(
!( !(!(
!(
!(!(
!(
!(
Sources: Esri, HERE, DeLorme, USGS, Intermap, increment P Corp., NRCAN,Esri Japan, METI, Esri China (Hong Kong), Esri (Thailand), TomTom,MapmyIndia, © OpenStreetMap contributors, and the GIS User Community
GWR LocalR2LocalR2!( < -1.3 Std. Dev.
!( -1.3 - -0.75 Std. Dev.
!( -0.75 - -0.25 Std. Dev.
!( -0.25 - 0.25 Std. Dev.
!( 0.25 - 0.75 Std. Dev.
!( 0.75 - 1.2 Std. Dev.
!( 1.2 - 1.7 Std. Dev.
!( 1.7 - 2.2 Std. Dev.
!( 2.2 - 2.7 Std. Dev.
!( > 2.7 Std. Dev.
MetroRail
!P RailStation_Pro
0̄ 1 2 3 40.5Miles
!P
!P
!P
!P
!P
!P
!P
!P
!P!P
!P!P
!P
!P
!P!P!P!P
!P
!P!P
!P
!P
!(!(!( !(!(!( !(!(!(!(!(!( !(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!( !(!(!( !(!(!(!( !(!( !(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!( !(!( !(!(!(
!(!(!( !( !(!(!(!( !(!(!(!(!(!( !( !(!(!(!(!( !(!(!(!(!(!( !( !(!(!( !( !(!(!(!(!(!(!(!(!( !( !(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!( !(!(!( !( !(!(!( !(!(!(!( !(!( !(!(!(!( !(!(!( !(!( !(!(
!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!( !( !(!(!(!(!(!(!(!( !(!(!( !(!(!( !(!(!(!(!( !(!(!(!(!(!( !( !(!( !(!(!(!( !(!( !(!(!(!( !(!(!( !(
!(!(!(!(!(!( !(!(!(!( !(!(!(!(!( !(!( !(!(!(!(!(!( !(!(!( !(!(!(!(!(!(!(!( !(!(!(!(!(!( !(!(!( !(!( !(!(!(!( !(!( !(!(!(!(!( !(!(!(!(!( !(!(!(!(!( !(!(!(!( !(!( !( !(!(!(!(!(!(!( !(!(!(!(!(!(!(!( !(!(!( !(!( !( !(!(
!( !(!(!(!(!(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!(!( !(!(!( !(!(!(!(!(!(!( !(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!( !(!( !(!(!(!(!( !(!(!(!(!(!(!( !(!( !(!(!( !(!( !(!(!(!(!( !(!( !( !(!( !(!( !(!(!(!(!(!(!( !(!( !(!(!( !(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!( !( !( !(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!(!(!(!(!(!(!( !(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!( !(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!( !(!(!(!(!( !(!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!( !(!(!(!(!(!( !(!(!(!(!( !(!(!(
!(!( !(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!( !(!(!( !(!(!(!(!(!( !(!(!(!( !( !(!( !(!(!(!(!(!(!( !(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(!(
!(!(!(!( !(!(!(!(
!( !(
!(!(
!(
!(
!(!( !( !(!(!(
!(!( !(!(!(!(!( !(!( !(!(!(
!(
!(
!(!(!(!(!(!(!(!(!(!(!(!( !(
!(!(!(!( !(!(!(!(!(
!(
!(
!(
!(
!(
!(
!(
!(!( !(!( !(!(!(!(!(!(!(!( !(!(!( !(
!(!(
!(!(!(!( !(!(!(
!(!(!(!(!(!(!( !(!( !(!(!(!( !(!(!( !(!(!(!(!(!(!(!(!(
!( !(!(
!(
!(!(
!(
!(
Sources: Esri, HERE, DeLorme, USGS, Intermap, increment P Corp., NRCAN,Esri Japan, METI, Esri China (Hong Kong), Esri (Thailand), TomTom,MapmyIndia, © OpenStreetMap contributors, and the GIS User Community
GWR Rail Station Coefficient ValueC12_RailDi
!( -0.072023 - -0.068120
!( -0.068119 - -0.066363
!( -0.066362 - -0.065069
!( -0.065068 - -0.063871
!( -0.063870 - -0.062282
!( -0.062281 - -0.057677
!( -0.057676 - -0.046761
!( -0.046760 - -0.032140
!( -0.032139 - -0.028836
!( -0.028835 - -0.023681
MetroRail
!P RailStation_Pro
0̄ 1 2 3 40.5Miles
GWR model shows that the local residual square is huge, which means that the model
is a good fit for the observed dataset. It
also indicates a large variation between the
observed and predicted just value.
The local R-squre map of the age of buildings, the independent
variable with the strongest spatial explanatory power
Spatial StatiSticS: Modeling Spatial RelationShipS
EstImAtE thE ImPAct Of mIAmI-dAdE mEtRO RAIL systEm ON LANd jUst vALUE
15
cURItIBA
WAshINGtON, d.c.
sAN fRANsIscO
RIO dE jANEIRO
My interests in regional land development and spatial analysis has fostered my love for panoramic views. I traveled and took photographs and notes of various infrastructures and urban development patterns adopted by different countries and cities, and the impact these development have on their citizens.
JINGRU ZHANG | (352)283-2658 • zhaNgjiNgrU123@UFl.edU