2015-10-16 gic envisionalachua+121casestudy knowles+jones...
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1 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
����������� � ���� ��������������������������������������
Florida�Case�Studies�in�Alachua�&�Lake�Counties
Friday,�October�16,�2015Growth�&�Infrastructure�Conference�(Portland,�OR)
Pierce�Jones�&�Hal�S.�Knowles,�III
2 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
�� � �������� ����� �How�We�Started:�The�Restoration�Story�Adaptive�Planning�Visualizing�Dwelling�Density�Measuring�Impacts
� Indicator�1:�Water�Consumption�Baselines� Indicator�2:�Energy�Consumption�Baselines� Indicator�3:�Housing�and�Employment�Distributions
�Projecting�Impacts� Case�Study�1:�Three�Alternative�Plans�for�Envision�Alachua� Case�Study�2:�Three�Alternative�Plans�for�SR121�(Alachua�County)� Case�Study�3:�Heritage�Green�(Lake�County)
�Next�Steps
3 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
!" ����������#�� �������� ���������“Under�an�adaptive�model,�urban�plans�and�designs�can�be�understood�as�hypotheses of�how�a�policy�or�project�will�influence�particular�landscape�processes�or�functions�and�implemented�planning�policies�or�designs�become�‘experiments’ from�which�experts,�professionals,�and�decision�makers�may�gain�new�knowledge�through�monitoring�and�analysis…these�challenges�[of�urban�sustainability�and�community�resilience]�will�demand�a�higher�level�or�inter� or�transdisciplinary�collaboration�in�both�research�and�practice than�presently�exists.”� (Ahern,�2011,�p.�343).
Source:�Ahern,�Jack.�“From�Fail�Safe�to�Safe�to�Fail:�Sustainability�and�Resilience�in�the�New�Urban�World.”Landscape�and�Urban�Planning 100,�no.�4�(April�30,�2011):�341–43.�doi:10.1016/j.landurbplan.2011.02.021.
4 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
!" ����������#�� �������� ��������
Source:�Reidsma,�Pytrik,�Hannes�König,�Shuyi Feng,�Irina�Bezlepkina,�Ingrid�Nesheim,�Muriel�Bonin,�Mongi Sghaier,�et�al.“Methods�and�Tools�for�Integrated�Assessment�of�Land�Use�Policies�on�Sustainable�Development�in�Developing�Countries.”�Land�Use�Policy 28,�no.�3�(July�2011):�604–17.�doi:10.1016/j.landusepol.2010.11.009.
5 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
�$ ������ ����Visualizing�Alachua�County:Housing�Types�&�Patterns
6 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
� ����%�& ��� ������'&����(�)�*
7 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
� ����%�& ��� ������'+�$(�)�*
Turnberry Lake
8 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
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9 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
� ����%�& ��� ������'# ����(#),-.*
Hampton�Oaks
10 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
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11 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
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12 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
� ����%�#�2 ���� �'# ����*
Union�Street�Station
13 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
����� %��# ���������������Define�Key�Current�Resource�Usage�in�Alachua�County
� Building�and�landscape�potable�water�consumption� Residential
� Effect�of�in�ground�irrigation�systems� Effect�of�pools� Impact�of�Individual�wells
� Commercial� Selected�consumption�examples�over�a�wide�range�of�business�types
� Building�energy�consumption� Analysis�of�residential�energy�consumption�vs.�housing�density� Visualization�of�community�energy�use
�Measurement�Methods� GRU�Billing�Records
� Electric,�natural�gas,�water�billing�and�consumption�records� Alachua�County�Property�Appraiser
� Building�use�codes/characteristics� Property�use�codes/characteristics
14 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���������������'3-*Quantifying�&�Visualizing�Alachua�County:Water�Consumption�Baselines
15 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���� �%�4�� ���� �Location:
� Alachua�County,�FL�Dwelling�Units�in�Sample�� 5,180�:
• All�units�constructed�since�2000• Single�family�detached�in�28�neighborhoods�� 3,035• Apartments�in�10�complexes�� 1,420• Condominiums�in�18�associations�� 735
�Baseline�Metrics:• Metered�water�use�in�years�2009,�2010�and�2013• Average�gallons�per�day�(gpd)�per�household
Turnberry LakeHampton�Oaks
Union�Street
17 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���� �%�4�� ����
18 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
308
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Gallons�per�Day�per�Hou
seho
ld
Average�Daily�Water�Use�(Alachua�County,�FL):Single�Family�Detached�(SFD)�Homes
Average�Daily�Water�Consumption
Weighted�Average
# ���� �%�4�� ����
19 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���� �%�4�� ����
358
190
0
100
200
300
400
500
600
Gallons�per�Day�per�Hou
seho
ld
Average�Daily�Water�Use�(Alachua�County,�FL):SFD�Home�Irrigation�vs.�Non�Irrigation�Groups
Average�Daily�Water�ConsumptionGroup�AverageIrrigation�Group�AverageNon�Irrigation�Group�Average
20 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���� �%�4�� ����
116
0
100
200
300
400
500
600
Gallons�per�Day�per�Hou
seho
ld
Average�Daily�Water�Use�(Alachua�County,�FL):Apartment�Complexes�(MF�<�10�&�MF�>�10)
Average�Daily�Water�Consumption
Weighted�Average
21 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���� �%�4�� ����
94
0
100
200
300
400
500
600
Gallons�per�Day�per�Hou
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Average�Daily�Water�Use�(Alachua�County,�FL):Condominium�Complexes�(SFA,�MF�<�10,�&�MF�>�10)
Average�Daily�Water�Consumption
Weighted�Average
22 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���� �%�4�� ����
358
190
11694
232
0
50
100
150
200
250
300
350
400
SFD�Homes�w/�Irrigation(n=2,338)
SFD�Homes�w/o�Irrigation(n=697)
Apartments(n=1,420)
Condominiums(n=725)
Gallons�per�Day�per�Hou
seho
ld
Average�Daily�Water�Use�(Alachua�County,�FL):SFD�Homes,�Apartments,�&�Condos�(CY�2009,�2010,�2013)
Average�Daily�Water�Consumption
Weighted�Average
23 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���� �%�4�� ����
358 358 358
190116 94
172
81
0
100
200
300
400
500
600
SFD�w/�Irr�+�Well(n=5)
SFD�w/�Irr�+�Pool(n=499)
SFD�w/�Irr(n=2,338)
SFD�w/o�Irr(n=697)
Apartment(n=1,420)
Condo(n=725)
Gallons�per�Day�per�Hou
seho
ld
AVERAGE DAILY WATER USE (ALACHUA COUNTY,�FL):SFD�HOMES,�APARTMENTS,�&�CONDOS (CY�2009,�2010,�2013)
24 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
2���VISION,�GO
ALS�AND�PLAN
NING�PRIN
CIPLES
� Identify�and�protect�water�recharge�areas� Develop�communities�that�optimize�water�conservation�and�
achieve�a�50�percent�or�greater�reduction�in�water�usage�based�on�current�usage
� Apply�Florida�friendly�guidelines�for�landscaping� Demonstrate�leadership�in�resource�management�by�promoting�and�
adopting�innovative�ways�to�meet�water�needs� Capture,�treat�and�reuse�storm�water�to�the�maximum�extent�
feasible
Goal�DWaterAddress�long�term�needs�for�water�supply,�water�quality�and�water�conservation
25 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���������������'35*Quantifying�&�Visualizing�Alachua�County:Energy�Consumption�Baselines
28 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���� �%�6� ���� �'7��������� ������*
0
5,000
10,000
15,000
20,000
25,000
30,000
0 10 20 30 40 50 60 70
Energy�Con
sumption,�ekW
h/year
Dwelling�Units�per�Acre
Residential�Energy�Use�by�Housing�Density
Raw�Energy�Data Smoothed�Data
Source:�Tjindra,�Djundi.�“Residential�Land�Use�Density�and�Building�Energy�Consumption:�A�Case�Study�of�the�City�of�Gainesville,�Florida.”Master�of�Science,�University�of�Florida,�2013.�http://ufdc.ufl.edu/UFE0046365/00001.
29 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���� �%�6� ���� �'7��������� ������*
0
10000
20000
30000
40000
50000
60000
0 20 40 60 80 100 120 140 160
ekWh
Residen al med ekWh 2012 vs Land�Use Density (per House Type)
SFD Mul �Family SFA Source:�Tjindra,�Djundi.�“Residential�Land�Use�Density�and�Building�Energy�Consumption:�A�Case�Study�of�the�City�of�Gainesville,�Florida.”
Master�of�Science,�University�of�Florida,�2013.�http://ufdc.ufl.edu/UFE0046365/00001.
30 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���� �%�6� ���� �'7��������� ������*
Source:�Tjindra,�Djundi.�“Residential�Land�Use�Density�and�Building�Energy�Consumption:�A�Case�Study�of�the�City�of�Gainesville,�Florida.”Master�of�Science,�University�of�Florida,�2013.�http://ufdc.ufl.edu/UFE0046365/00001.
31 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���� �%�6� ���� �'��7�# �"��*
0
2000
4000
6000
8000
10000
12000
Time�Series Time�Series�NAC Time�Series�withComparisons
Community�Baseline
Annu
al�Ene
rgy�Savings�(ekW
h/yr)
2007�GRU�Duct�Sealing�Program�Savings�EstimatesUsing�Various�Analysis�Methods
2008 2009
Source:�Jones,�Pierce�H.,�Nicholas�W.�Taylor,�M.�Jennison�Kipp,�and�Harold�S.�Knowles.�“Quantifying�Household�Energy�Performance�Using�Annual�Community�Baselines.”International�Journal�of�Energy�Sector�Management 4,�no.�4�(2010):�593–613.�doi:10.1108/17506221011092797.
32 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���� �%�6� ���� �'��7�# �"��*
Source:�Jones,�Pierce�H.,�Ujjval K.�Vyas,�Nicholas�Taylor,�and�M.�Jennison�Kipp.�“Residential�Energy�Efficiency:�A�Model�Methodology�for�Determining�Performance�Outcomes.”Real�Estate�Issues 35,�no.�2�(Summer�2010):�41–47.�http://www.cre.org/publications/rei_absdetail.cfm?lid=1576.
�10.0%
�5.0%
0.0%
5.0%
10.0%
15.0%
20.0%
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Annual�Percent�Savings�Estimates�for1998�1999�Vintage�Mentone�Homes
Savings�Estimate
ENERGY�STAR®
33 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
# ���������������'38*Quantifying�&�Visualizing�Alachua�County:Housing�&�Employment�Distributions
34 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
Turnberry Lake
Hampton�Oaks
Union�Street
US�Census�– Longitudinal�Employer�Household�Dynamics�(LEHD)http://lehd.ces.census.gov/
35 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
Turnberry Lake Hampton�Oaks Union�Street
36 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
���9 �������������'3-*Modeling�Resource�Efficiency:Three�Alternative�Plum�Creek�Envision�Alachua�(EA)�Plans
37 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
38 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
6�%����9 �������������Modeling�Methods
� Geodatabase,�using�ESRI�ArcGIS�with�CommunityViz Scenario�360� Analysis�of�three�hypothetical�development�scenario�plans
1. Full�development�under�existing�zoning�in�large�lot�residential�(1�:�3�acres)2. Conventional�residential�lots�(3�DUs:�1�acre)�with�supporting�retail3. Proposed�scenario�of�mixed�residential,�commercial�&�manufacturing.
� Land�use�transect�grid�(~26,000�analysis�cells�@�1�hectare�each)� Site�suitability�analysis
� Impacts�Modeled�(for�each�future�scenario�plan)� Land�use�pattern�(developed�and�disturbed�areas)� Infrastructure� Energy�use�and�greenhouse�gas�emissions� Indoor�and�outdoor�water�use� Stormwater volume�and�surface�water�nutrient�loading� Vehicle�miles�traveled�(VMT)
�Disclosure:�Study�funded�by�Plum�Creek,�LLC
Plan�1
Plan�2
Inset�Next�Slide
Plan�3
OverallSuitability
Plan�3
44 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
6�%�& ��� ������'!� �:������*
0
2,000
4,000
6,000
8,000
10,000
12,000
Plan�1 Plan�2 Plan�3
Resid
ences�(Dw
elling�Units)
Rural Low Medium Med�High High Med�Mixed�Use High�Mixed�Use
45 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
6�%�;��/& ��� ���������� �'!� �:��� �*
0
2000
4000
6000
8000
Plan�1 Plan�2 Plan�3 Plan�3�(Mfg.)
Floo
r�Area�(Tho
usand�Ft
2 )
Retail OfficeResearch/Institutional Advanced�ManufacturingConventional�Manufacturing Schools
46 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
6�%���<���+����'�� �*
0
5,000
10,000
15,000
20,000
25,000
30,000
Plan�1 Plan�2 Plan�3
Urban�Area�(Acres)
Residential Non�Residential�&�Mixed�Use Manufacturing
47 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
6�%�;��/��<���+����'�� �*
0
10,000
20,000
30,000
40,000
50,000
60,000
Plan�1 Plan�2 Plan�3
Non
�Urban�Area�(Acres)
Existing�Easement New�Easement Urban�Open�Space Agriculture
48 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
6�%�&����������������� �'+ ��"*
0
100
200
300
Plan�1 Plan�2 Plan�3
Road�Len
gth�(M
iles)
Residential Non�Residential
49 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
6�%�&����������������� �'�����*�
0
100
200
300
400
500
600
700
800
900
Plan�1 Plan�2 Plan�3
Infrastructure�Cost�(Million�$)
Roads Stormwater Potable�Water WastewaterCommunications Electric Natural�Gas
50 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
6�%�4�� ���� �'�������!����*
0
400
800
1,200
1,600
2,000
Plan�1 Plan�2 Plan�3
Water�Use�(M
illion�Ga
l/Yr)
Residential�Indoor Non�Residential�Indoor Outdoor�Irrigation
51 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
6�%�6� ���� �'& ��� ������� ��������*
0
2000
4000
6000
8000
10000
12000
Plan�1 Plan�2 Plan�3
Energy�Use�(e
kWh/Yr/Capita
)
Residential
52 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
6�%�6� ���� �'�������!����*
0
50
100
150
200
250
300
350
400
450
0
20
40
60
80
100
120
140
160
180
Plan�1 Plan�2 Plan�3
Energy�Use�(e
MWh/Yr)
Residential Non�Residential
53 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
6�%�������Units Plan�1 Plan�2 Plan�3
Urban�Land�Uses Acres 26,800 5,493 3,829
Conservation�Options Acres 24,000 55,440 53,790
Roads Miles 264 131 77
Infrastructure�Costs Million�$ 603 838 609
Water�Demand Mgal/Yr 1,147 1,502 850
Energy�(Residential)�Demand eMWh/Yr 158 143 107
Energy�(Total)�Demand eMWh/Yr 0 57 422
54 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
6�%������������������ ��������Study�Limitations:
� Comparative�scenario�plans�represent�three�possibilities�along�a�continuum�of�alternatives
� Model�only�resolves�direction�&�relative�magnitude� Manufacturing�impacts�are�industry�specific,�highly�variable,�&�beyond�study�scope
� Water�&�stormwater impacts�highly�dependent�on�design�&�policy�patterns�at�finer�resolutions�than�this�study
�More�Investigation�Needed:� Do�private�wells�&�no�cost�water�supply�in�rural�residential�result�in�higher�usage�than�public�supply?� (e.g.,�equestrian,�private�agriculture)
� Multi�modal�transit�&�detailed�transportation�networks
55 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
���9 �������������'35*Modeling�Resource�Efficiency:Three�Alternative�Plum�Creek�(SR121)�Plans
56 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
�&-5-%����9 �������������Modeling�Methods
� Geodatabase�using�ESRI�ArcGIS�with�CommunityViz Scenario�360� Analysis�of�three�hypothetical�development�scenario�plans�for�1,890�dwelling�units�on�1,778�acres�(1,016�acres�or�57%�wetlands)
1. Comparison�Plan:�Base�mix�SFD�/�SFA�/�MF;�25,000�ft2 office;�75,000�ft2 retail2. Vision�Plan�A:�Most�dense�mix�SFD�/�SFA�/�MF;�assisted�living�facility;�600,000�ft2
office;�180,000�ft2 retail3. Vision�Plan�B:�More�dense�mix�SFD�/�SFA�/�MF;�assisted�living�facility;�600,000�ft2
office;�140,000�ft2 retail� Imported�and�adapted�three�AutoCAD�community�plans�(Plum�Creek)
� Impacts�Modeled�(for�each�future�scenario�plan)� Land�use�pattern�(developed�and�disturbed�areas)� Infrastructure� Energy�use�and�greenhouse�gas�emissions� Indoor�and�outdoor�water�use� Stormwater volume�and�surface�water�nutrient�loading� Vehicle�miles�traveled�(VMT)
� Disclosure:�Study�funded�by�Plum�Creek,�LLC
57 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
�&-5-%��#!�'# �"���*� ArcGIS�10.1�network�analyst�tool�(shortest�path�via�O�D�matrices)� ITE�Trip�Generation�Spreadsheet�8th�Edition
� Mean�number�of�weekday trips� Trips�divided�into�three�categories�based�on�origin,�purpose,�&�residential�type
| Home�based�work�(HBW)�| Home�based�other�(HBO)�| Non�home�based�(NHB)�|
� Mixed�Use�Trip�Generation�Model�v�4.0�by�Fehr�&�Peers� %�household�weekday�mean�trips�to�destinations�within�proposed�development�(internal�
capture)� %�HBO�trips�to�internal�parks�derived�from�known�local�trips�by�purpose� HBO�and�NHB�distances�of�the�external weekday�trips�converted�known�mean�trip�duration�
(in�minutes) and�known�mean�trip�speed�(in�miles�per�hour) for�Alachua�County�into�localized�mean�HBO�and�NHB�trip�distances�(in�miles)
� HBW�distances�of�the�external weekday�trips�added�residence�to�closest�egress�point�distance�to�weighted�average�distance�from�the�egress�point�to�14�county�destinations�based�on�their�%�of�nearby�jobs�from�the�US�Census�LEHD�(using�“count�closest”)
Residences�(O)�to�Parks�(D)
Residences�(O)�to�Internal�Non�Residential�(D)
Residences�(O)�to�Egress�Points�(D)
Egress�Points�(O)�to�External�Destinations�(D)
Residence� Parks Residence Non�Res Residence Egress Egress ExternalBase�Plan 1218 2 1218 4 1218 12 12 15Vision�Plan�A 934 6 934 11 934 8 8 15Vision�Plan�B 1006 5 1006 7 1006 8 8 15
58 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
�&-5-%��#!�'6� ���� ����������*
59 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
�&-5-%��#!�'62�=�� ����������*
60 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
�&-5-%��#!�'074�# ���!����������� *External�Destination�Name1
Average�Distance�from�Egress�to�Destination�(Miles)
County�EploymentWeighted�Distance�from�Egress�to�Employment�
(Miles�x�%�jobs)
Base Plan�A Plan�BJobs�Near�Destination
%�Near�Destination
Base Plan�A Plan�B
Airport 7.60 7.05 7.05 5,086 4.8% 0.36 0.34 0.34Alachua 9.95 10.34 10.35 4,862 4.6% 0.45 0.47 0.47Archer 19.29 18.74 18.74 448 0.42% 0.08 0.08 0.08Butler�Plaza 8.47 7.92 7.92 12,218 11.5% 0.97 0.91 0.91Gainesville 7.05 6.50 6.49 23,797 22.3% 1.57 1.45 1.45Hawthorne�Square�Shopping�Center
22.81 22.25 22.25 627 0.59% 0.13 0.13 0.13
High�Springs 16.59 16.99 17.00 1,324 1.24% 0.21 0.21 0.21Lacrosse 8.11 8.77 8.78 244 0.23% 0.02 0.02 0.02Micanopy 17.84 17.29 17.29 376 0.35% 0.063 0.061 0.061Newberry 20.41 20.03 20.03 4,239 4.0% 0.811 0.796 0.796Oaks�Mall�&�N�FL�Medical�Center
8.43 7.88 7.88 17,734 16.6% 1.40 1.31 1.31
Santa�Fe�College 7.71 7.16 7.15 7,162 6.7% 0.52 0.48 0.48UF�and�Shands 7.66 7.11 7.10 21,598 20.3% 1.55 1.44 1.44Waldo�Flea�Market 0.000 17.27 17.26 352 0.33% 0.000 0.057 0.057Walmart�Super�Center 2.05 1.50 1.49 6,562 6.15% 0.13 0.09 0.09Total�Home�Based�Work�Trip�Average�Distance�(Miles) 8.27 7.79 7.78
[1] Distribution�of�Alachua�County�employment�centers�derived�from�the�US�Census�Longitudinal�Employer�Household�Dynamics�(http://lehd.ces.census.gov/).
61 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
�&-5-%��#!�'�����������*Base Plan�A Plan�B
Annual�Miles�Per�Household 24,270 19,780 20,870
%�reduced 19% 14%
Total�Annual�VMT,�Million�miles�
HBW�(Daily) 17.2 14.6 15.7
%�reduced 15% 9%
HBO�(Daily) 21.2 17.1 17.5
%�reduced 19% 17%
NHB�(Daily) 7.5 5.7 6.3
%�reduced 23% 16%
Total 45.9 37.4 39.5
%�reduced 18% 14%
62 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
�&-5-%�������Units Base Plan�A Plan�B
Urban�Land�Uses Acres 522 392 411
Conservation�Options Acres 1,256 1,386 1,367
Roads Miles 22.6 14.8 17.7
Infrastructure�Costs Million $ 65.8 44.3 50.3
Water�(Indoor)�Demand MGal/Yr 86.9 80.7 83.9
Water�(Outdoor)�Demand MGal/Yr 116.5 50.9 56.1
Water�(Non�Residental)�Demand MGal/Yr 12.2 62.8 56.5
Energy�(Residential)�Demand eMWh/Yr 19,270 16,780 17,200
Energy�(Total)�Demand eMWh/Yr 3,620 24,150 22,550
63 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
���9 �������������'38*Modeling�Resource�Efficiency:Three�Alternative�Heritage�Green�(HG)�Plans
64 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
; 2���� ��Philosophies�and�Practices�On�the�Horizon
65 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
; 2�%�4 <���� ��� ������������
Source:�http://www.costofsprawl.org/
Source:�h
ttp://www.iftf.org/our�w
ork/glob
al�la
ndscape/hu
man
�settle
men
t/the�future�of�c
ities�in
form
ation�an
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; 2�%�������+�<������� �
67 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
; 2�%����/7�� ����������������������
Source:�http://www.wired.com/2014/06/strava�sells�cycling�data/
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; 2�%����/7�� ���������������7�� ���
Source:�http://shareabouts�pbcambridge.herokuapp.com/page/about
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; 2�%�!" ��:�;�$>:�4����7 ?
Source:�http://www.dmarlin.com/uf�then�now/
70 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
4"��������������<����?�'7��������*�Most�widely�cited�=�sustainable�development�is�development�that�meets�the�needs�of�the�present�without�compromising�the�ability�of�future�generations�to�meet�their�own�needs� Gro Harlem�Bruntland,�1987
�Often�considered�too�general� So�vague�as�to�be�consistent�with�almost�any�form�of�action�(or�inaction)� Pearce�et�al.,�1994
Source:�Tainter,�Joseph�A.�“Social�Complexity�and�Sustainability.”�Ecological�Complexity 3,�no.�2�(June�2006):�91–103.�doi:10.1016/j.ecocom.2005.07.004.
71 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
4"��������������<����?�'!���� �*�Sustainability�is�the�capacity�to�continue�a�desired�condition�or�process,�social�or�ecological.� People�sustain�what�they�value,�which�can�only�derive�from�what�they�know.
�Sustainability�is�not�the�achievement�of�stasis…it�takes�continuous�work
�Challenges�to�sustainability�are�endless�in�number�and�infinite�in�variety
�Sustainability�is�a�matter�of�problem�solving� Science�is�humanity’s�ultimate�exercise�in�problem�solving
Source:�Tainter,�Joseph�A.�“Social�Complexity�and�Sustainability.”�Ecological�Complexity 3,�no.�2�(June�2006):�91–103.�doi:10.1016/j.ecocom.2005.07.004.
72 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
4"������& ���� �� ?�Resilience�is�the�ability�to�absorb�disturbances,�to�be�changed�
and�then�to�reorganize�and�still�have�the�same�identity�(retain�the�same�basic�structure�and�ways�of�functioning)� Ability�to�learn�from�the�disturbance� Forgiving�of�external�shocks
� Decreasing�resilience�increases�disruptiveness�of�ever�smaller�shocks� A�shifting�focus:
� From�growth�and�efficiency�(fragile�and�rigid)� To�recovery�and�flexibility�(novelty�and�opportunity)
�Resilience�vs.�sustainability� In�social�systems,�resiliency�can�mean�abandoning�sustainability�goals�and�the�values�that�underlie�them.
� A�fully�resilient�society�would�be�a�valueless�one,�which�by�definition�cannot�be� Degradation�is�a�social�construct�(Sander�van�der�Leeuw)
Source:�Tainter,�Joseph�A.�“Social�Complexity�and�Sustainability.”�Ecological�Complexity 3,�no.�2�(June�2006):�91–103.�doi:10.1016/j.ecocom.2005.07.004.
73 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
!" �&�� ��������� 2���Diversity�and�complexity�emerge�in�an�ecological�system�from�available�energy�and�water,�and�from�competition,�which�stimulate�speciation�or�support�immigration� Humans�are�not�prone�to�complexity�(&�are�often�averse�to�it)
�Every�increase�in�complexity�has�a�cost� Energy,�labor,�money,�or�time�needed�to�create,�maintain,�and�replace�systems�that�grow
� More�parts,�more�specialists,�more�regulation�of�behavior,�more�information
Source:�Tainter,�Joseph�A.�“Social�Complexity�and�Sustainability.”�Ecological�Complexity 3,�no.�2�(June�2006):�91–103.�doi:10.1016/j.ecocom.2005.07.004.
74 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
!" �&�� ��������� 2���Before�fossil�fuels�human�complexity�increased�in�direct�proportion�to�increased�and/or�higher�quality�human�labor
�Human�problem�solving�efforts�are�powerful�complexity�generators� Complexity�grows�as�problems�require�it� Problems�continue�to�arise,�thus�pressure�for�complexity�increases
�Complexity�is�an�economic�function� Early�efforts�are�simple�and�cost�effective� Past�the�point�of�diminishing�returns,�investments�in�complexity�can�lead�to�ineffective�problem�solving�and/or�collapse
Source:�Tainter,�Joseph�A.�“Social�Complexity�and�Sustainability.”�Ecological�Complexity 3,�no.�2�(June�2006):�91–103.�doi:10.1016/j.ecocom.2005.07.004.
75 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
������%�@ ����� ����What�is�sustainability?
� Active�condition�of�problem�solving� Not�passive�consequence�of�consuming�less� We�sustain�what�we�value
�What�is�resilience?� Ability�of�systems�to�adjust�form�&�function�in�response�to�disturbance
� Resilience�� sustainability� Values,�while�crucial�to�sustainability,�may�hinder�system�resilience
�Problems�are�subjective,�though�always�collective,�and�will�never�cease�arising� Solutions�have�consequences�and�form�the�foundation�of�new�problems…so�solve�wisely…and�know�the�cost�of�complexity
http://dx.doi.org/10.1016/j.ecocom.2005.07.004
76 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
��� �����':�+ ����������*�)����� �“Early�ideas�on�implementing�sustainability�focused�on�concepts�of�achieving�stability,�practicing�effective�management�and�the�control�of�change�and�growth�– a�‘fail�safe’�mentality.�More�recent�thinking�about�change,�disturbance,�uncertainty,�and�adaptability is�fundamental�to�the�emerging�science�of�resilience,�the�capacity�of�systems�to�reorganize�and�recover�from�change�and�disturbance without�changing�to�other�states�– in�other�words,�systems�that�are�‘safe�to�fail’”� (Ahern,�2011,�p.�341).
Source:�Ahern,�Jack.�“From�Fail�Safe�to�Safe�to�Fail:�Sustainability�and�Resilience�in�the�New�Urban�World.”Landscape�and�Urban�Planning 100,�no.�4�(April�30,�2011):�341–43.�doi:10.1016/j.landurbplan.2011.02.021.
77 |��GIC�2015:�Quantifying�Development�Impacts�Using�ArcGIS�&�CV
!"��A�B��CPierce�Jones�| piercejones@ufl.edu��| 352�392�8074Hal�S.�Knowles,�III��| hknowles@ufl.edu��| 352�273�0239
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