HomeMy WebLinkAboutScenario Planning - Indicators Modeling Report - Placeways (2018)
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PROJECT DOCUMENT
CommunityViz for GP Comprehensive Update
Technical Report:
Tasks G (Indicator Modeling)
Date: DRAFT: January 19, 2018
Tasks: G – Indicator Modeling
Authors: Amy DeBay, Ian Varley
Deliverable: Yes
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INDICATORS: Description, Modeling Approach, and Data Sources 5
Conservation 9
Acres of Critical Habitat 9
Acres of Sensitive Ecological Areas 9
Residential development in Sensitive Ecological Areas 10
Residential development in viewsheds 10
Residential development near anchialine pools 11
Acres of open space 11
Residential development in open space and special management areas 12
New residential development near identified historic/cultural resources 13
Number of identified historic/cultural resources 13
Acres of Critical Habitat and Sensitive Ecological Areas outside Protected Lands 14
Hazards 15
Residential development in areas at risk of Sea level rise 15
Residential development in Volcano Hazard Zones 15
Development in 100-year floodplain 16
Development in Wildfire Risk Areas 17
Residential development in Tsunami Inundation Areas 17
Residential development in Recent Lava Flows 18
Energy 18
Residential Energy Use 18
Agricultural Land 20
Acres of agricultural lands of importance 20
development in Productive Agricultural Lands 20
Acres of Productive Agricultural Lands 21
Acres of Pasture Lands 21
Acres of Public Hunting Areas 22
Acres of Croplands 22
Rural Residential 23
Rural Residential lots 23
Housing Units on Rural Residential lots 23
Housing Units in unserviced subdivisions 24
Vacant lot ratio 24
Average distance to Urban Centers from Rural Residential (Weighted by Population) 25
Development outside urbanized areas 25
Water 26
Water demand 26
Number of homes by type of water service 27
Development near existing water infrastructure 27
Use rates versus sustainable yield 28
Wastewater 29
Residential Wastewater generation volume 29
Number of homes by type of wastewater service 29
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Count of Onsite Disposal Systems 30
Development near existing wastewater infrastructure 31
Residential development on small lots 31
Solid Waste 32
Solid waste generation 32
Existing waste by stream (landfill, recycling, compost) 32
Transportation 33
Road miles by jurisdiction/functional classification 33
Number of houses fronting on roads by Maintenance type 33
Miles of roads failing LOS 34
residential development Near congested roads 35
Housing Units, Jobs and Population Near Road Infrastructure 35
Average Distance to Bus Routes (weighted by Housing Units) 35
Residential Units Near existing Bus Routes 36
Miles of bike routes and sidewalks 36
Emergency Services 37
Number of Housing Units within response zones (1, 5 and 10 miles) 37
Average Distance to emergency services (weighted by Housing Units) 37
Parks 39
Acres of Park space per capita 39
Average distance to parks and coastal access points 39
Acres of parks by type, faciLITy 40
Number of people within 1 mile of a park 40
Residential 41
Housing units 41
Average residential density and standard deviation of density 41
Housing and transportation Affordablity 42
‘Ohana housing units 43
Residential development in urban areas 43
New residential development by capacity type 43
Commercial 44
Average distance to commerical centers 44
Square feet of commercial 45
Commercial jobs 45
Industrial 46
Square feet of industrial 46
Industrial jobs 46
Visitor 47
Number of visitor Units by Type 47
Employment 48
Jobs/housing ratio 48
General Interest 48
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Population, HOuseholds and Jobs 48
School Aged Children 48
Dashboard Indicators 49
Dashboard indicators 49
Appendix 1 Indicators Considered (But Not Addressed) 52
Appendix 2 Tier One Indicators 53
Appendix 3 Assumption Values 56
Appendix 4 Residential capacity types 60
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INDICATORS: DESCRIPTION, MODELING APPROACH, AND DATA SOURCES
Scenario planning represents the next generation of analytical processes created to evaluate the
Influence of different development types, locations, patterns and intensities on a wide range of topics of
interest. Visualizations of the interaction between land use, urban form and infrastructure decisions, as
well as the causational factors that explain the push-pull relationship between them, provides
community leaders with the information needed to evaluate the consequences of potential actions.
This report provides more detailed information on metrics called indicators that have been identified by
during the development of the County of Hawaii (CoH) growth scenarios. Indicators are impact or
performance measures that apply to an entire scenario. They summarize conditions using a single
summary statistic (e.g., a sum, average or ratio). Results are displayed in charts or tables for monitoring
conditions inside CommunityViz, and often become the criteria for ranking growth alternatives in a
scenario planning process. Indicators update automatically using formulas written in the software that
respond to changes made in other areas of the analysis.
Indicator values may be exported from CommunityViz to other software platforms (e.g.,
Microsoft Excel) for reporting or other analyses. This technical report serves to accompany a set of over
220 indicators that were created to compare and contrast different land use scenarios. This set of
indicators is assembled in a spreadsheet called the “Scenario Report Card”. In the Report Card, indicator
results make comparisons of potential futures in the form of scenarios and to compare future scenarios
with today. Some of the indicators that were initially proposed had to be shelved, usually due to lack of
available data. Appendix 1 has a complete list of these indicators that were not addressed.
The indicator values are grouped into categories based on different themes. Some themes have more
indicators than others. Over the course of the analysis many indicators were considered and some were
not developed. In most situations it was the lack of available information that made some indicators
impractical. In some cases, supplemental analyses were conducted to fulfill a particular need (e.g. the
development of viewsheds, address visitor accommodations, examine affordability, etc.).
Tiered Analysis
Using feedback from the technical workshops, public sessions, and information generated by the
planning process up to that point, discussions with CoH and consultant staff began to explore the
concept of three different tiers of analyses that would inform the comprehensive planning process.
Each tier would be oriented towards a different purpose, audience and level of expertise.
• Tier One. This tier consists of an expanded version of the analysis used in the Hawaii technical
workshops. This analysis has a set of indicators, most of which are similar to or identical to
indicators in the Tier Two analysis. Appendix 2 has a complete list of indicators in the Tier One
analysis and where the indicators coincide with indicators in Tier Two. The Tier One indicators
are described in the Evolution of Scenarios Technical Report. This analysis continues to be used
for workshopping scenario alternatives with staff and/or stakeholders.
• Tier Two. The tier two analysis refers to the CommunityViz analysis developed to house the full
set of indicators developed to support the CoH Comprehensive Planning process.
• Tier Three. The tier three analysis was conceived an analysis and set of techniques to “set up”
the tier two analysis in the case of a significant update, such as the development of new parcel
or reference data.
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This report will cover the development of the tier two analysis. The tier one and three analyses are
described in greater detail in separate technical reports.
Forecasts
To understand future growth and develop future land use scenarios, growth projections or forecasts
were estimate by SMS, a Hawaiʻi-based research and consulting company (see their report “General Plan
Comprehensive Review Trends and Forecast Analysis Final Report (2015)”). These projections are
broken out by 13 geographic areas called “forecast analysis zones” or FAZs and by use type (residential
dwelling units and non-residential square feet). In order to add additional land use information to the
allocation, the SMS forecasts were further broken down into two residential categories (single family
dwelling units, multifamily dwelling units) and two non-residential categories (commercial square feet,
industrial square feet). These four forecasts were inputs to a land use allocation model that also used
land capacity and market desirability to create future development scenarios. The forecasts, land
capacity and market desirability are all topics documented at much greater length in other technical
reports.
Scale
The County of Hawai’i CommunityViz indicators model is built on Real Property Tax (RPT) parcels and
provides countywide scale for most impact indicator calculations for project scenarios in the Scenarios
Report Card. This means that it is summarizing the impacts generated by scenarios at the countywide
scale, but most input calculations function at the parcel level. An example is energy use: The model
estimates energy use per day generated by a given parcel, but the overall indicator tracks total scenario
energy use, a combination of all parcels.
In addition to parcel and countywide level, most indicator values can be summarized at interim scales,
such as district or FAZ level.
Scale Countywide Districts FAZ/TAZ Neighborhood Parcel
Indicator
Summarized at
this Scale
The County model is an impact measurement tool. To calculate impacts, it often multiplies the number
of impact generators (i.e., residential dwelling units, non-residential square footage) by an impact
coefficient (e.g., trip generation per household for a given land use). When this calculation occurs in a
model, the number of impact generators comes from specific data about a site or property, but the
coefficients are often generalized at higher scale such as FAZs, districts (e.g. South Kohala) or at county
level. Whenever possible coefficient data from CoH subject matter experts, such as the County
Department of Water Supply. In some cases however, coefficients have been identified from a 3rd party
source such as a published study or rule of thumb. In most cases, coefficients represent current
conditions but in some cases (e.g. employees per 1,000 sq ft of commercial space) these coefficients
were forecast to estimate future values. A complete list of coefficient assumptions can be found in
Appendix 3.
Timeframe
Estimating future impacts involves a good understanding of present day conditions and historic trends.
Many of the calculations about future scenarios use existing information (e.g. energy use rates, water
use rates, trip generation rates, etc.) from published sources (e.g. US Census, County reports, State
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research, etc.). It’s possible that coefficient rates remain relatively constant, but the generators change:
population increases, businesses expand, etc.. Another possibility is that coefficient rates change, for
better or worse, based on some anticipated changes (e.g. energy efficiency increases, water use
decreases as conservation measures are implemented). Most likely, in the future both the generators
and the coefficient values change. Depending on the indicator and available information, the question
of “when” and “what” is being estimated is an important consideration. There will be times when all
three of the below options are reported. The following table will be used to identify the temporal level
for indicators.
Timeframe Existing Net New Overall (existing plus future)
Indicator Summarized at
this Timeframe
Indicators reporting on existing data will provide insight into current conditions, possible things which
may be of interest to change in scenarios, but may not be easily or appropriately measured for future
scenarios. An example might be traffic incidents. While data may be helpful for present day to
understand where traffic improvements might prevent future incidence, it will not be in the model’s
capability to predict the amount of future incidents.
Indicators reporting on future changes (net new) are generally helpful to understand and compare
change. For example, sometimes a value like water use may be estimated for future additional
development. Since existing water use is a measurable given for all scenarios, the net change is what will
most influence a scenario performance.
Indicators reporting on overall future will be presenting the total gross impact, existing plus future
changes. When the overall value will be more beneficial to understanding policy or other necessary
actions. For instance, the net new number of homes in a volcanic risk zone helps a planner compare how
different scenarios perform as each scenario places a different number of new homes in risk areas.
However, emergency management planners will want to know the total number of homes (existing plus
new) within a lava flow zone to comprehensively assess risks and address potential needs.
In sum, while the formula or model for each indicator variation above will usually be the same, the data
used may vary:
• For the existing scenario, the data is based on some existing data source. For example, the US
Census, RPT data, CoH or other source which reports on current or recent conditions.
• For future scenarios, the land use patterns will change as the amount of new residential and
non-residential (i.e. the generators) development in any given location will fluctuate.
• The data for impact coefficients (e.g., water use per household) is estimated from best
available sources.
In the indicator descriptions below:
• Description is general and refers to all variations of the indicator (scale and timeframe)
• Methodology provides a description of the actual calculation steps.
• Formula or Model is general but uses example names for impact generators, such as parcels or
buildings, whose source may vary across indicator variations
• Timeframe as described above, reflects the temporal application of the indicator
• Unit is the spatial unit of the indicator, where applicable
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CONSERVATION
Conservation indicators examine factors such as critical habitat, watersheds, viewsheds, open space and historic
and cultural sites.
ACRES OF CRITICAL HABITAT
Description: Critical habitat as defined by the US Fish and Wildlife Service1 designation for
threatened and endangered species. This indicator summarizes areas within this definition.
Methodology: Sum acres of critical habitat layer.
Formula or Model: Sum ( [Attribute : Critical Habitat : Acres] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: Acres
ACRES OF SENSITIVE ECOLOGICAL AREAS
Description: Summary of sensitive ecological areas, including:
o Reserves2
• National Parks
• National Wildlife Refuge
• Natural Area Reserves
• Forest Reserves
• Marine Life Conservation Districts
o State Land Use Conservation District
o Watershed Protection Areas
Methodology: Sum acres of sensitive ecological areas.
Formula or Model: Sum ( [Attribute : Sensitive Ecological Areas : Acres] )
Timeframe:
1 http://www.fws.gov/endangered/what-we-do/critical-habitats.html
2 http://files.hawaii.gov/dbedt/op/gis/data/reserves_fgdc_metadata.html
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Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: Acres
RESIDENTIAL DEVELOPMENT IN SENSITIVE ECOLOGICAL AREAS
Description: This indicator summarizes existing and future added dwelling units to areas previously
defined as sensitive ecological areas.
Methodology: Using CommunityViz spatial functions, sum the overlapping area with SEAs. Assume a
proportional share of dwelling units on a feature is within the SEA based on overlap.
Formula or Model: Sum ( [ Attribute : Parcels : dwelling units within SEAs] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: count of dwelling units
RESIDENTIAL DEVELOPMENT IN VIEWSHEDS
Description: Viewsheds are spatial representations of areas that are visible from one or multiple
points. They are useful measuring change (especially urbanization) that may impact scenic places.
Planning Consultants of Hawaii (PCH), a contractor to the County, identified a set of viewpoints from
which an initial set of viewsheds was developed. CoH staff decided to refine the viewsheds using the
following criteria:
• Exceptional Viewsheds. PCH had assigned ratings to all the views they inventoried. A decision
was made to include only those viewsheds ranked as exceptional.
• Protected and undevelopable lands. Many of the most spectacular views in the island are
already protected or have little capacity to develop because state zoning would preclude it.
These lands were removed from the viewsheds in order to focus on viewsheds that are at
greater risk of developing.
• Removing developed neighborhoods. Neighborhoods that had largely been built out or
neighborhoods that consisted of underserved subdivision were removed from the viewsheds.
These refinements created a set of viewsheds that were largely undeveloped, in private hands and
were at some risk of land use change leading to a degradation of the viewshed. The indicator counts
the number of dwelling units found in the refined viewsheds.
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Methodology: Based on results of the scenic study, this measures the count of dwelling units with
potential to impact highly rated viewshed areas.
Formula or Model: � viewshed area
total parcel area�× Number of buildings
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator Summarized at
this Timeframe
Unit: count of dwelling units
RESIDENTIAL DEVELOPMENT NEAR ANCHIALINE POOLS
Description: Anchialine pools are small bodies of water, typically adjacent to the ocean but not
directly connected to it. These brackish pools often support an high amount of endemic and rare
aquatic species, especially crustaceans and other invertebrates. As wetlands, they provide important
habitat for native waterfowl. Anchialine pools are threatened by land use change and nonnative
species. Residential development that encroaches on anchialine pools would be detrimental to their
health.
Methodology: Using a minimum distance function, with a default value of 500 ft, dwelling units are
counted that fall within the minimum distance to anchialine pools.
Formula or Model: Sum ( [ Attribute : Parcels : Dwelling Units ], where ( [ Attribute : Parcels :
Distance to Place ] < 500 feet ) )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: count of dwelling units
ACRES OF OPEN SPACE
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Description: This indicator will estimate overall open space areas, both protected lands (State Land
Use conservation, conservation easements3, publicly owned conservation areas4, and TNC5 and TPL6
owned lands) and general (includes protected areas and privately owned lands and agricultural
areas over 5 acres).
Methodology: Sum acres of open space by type (protected, general).
Formula or Model: Sum ( [ Attribute : Open Space : Acres] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator Summarized at
this Timeframe
Unit: acres
RESIDENTIAL DEVELOPMENT IN OPEN SPACE AND SPECIAL MANAGEMENT AREAS
Description: This indicator considers development on two types of open space: protected and
unprotected (i.e. general open space) as well as Special Management Areas. Protected open space
will be treated as no growth areas in scenarios but a small amount of growth may occur. General
open space may allow for new development. Special Management Areas, or SMAs, are areas of the
island that are in close proximity to the shoreline. This indicator will report on any areas currently
defined as open space where future scenario development is shown to occur.
Methodology: Using data on where scenario development has occurred (new dwelling units > 0),
sum dwelling units.
Formula or Model: Sum ( [ Attribute : Parcels : dwelling units] , where ( open space ) )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
3 http://conservationeasement.us/reports/easements?report_state=Hawaii&report_type=All
4 http://dlnr.hawaii.gov/ecosystems/llcp/projects/
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http://www.nature.org/ourinitiatives/regions/northamerica/unitedstates/hawaii/placesweprotect/index.htm?sitel
inks=ProtectedPlacesinHI&src=sea.AWP&gclid=CjwKEAiAhaqzBRDNltaS0pW5mWgSJADd7cYDSjE6W5t8G3qGNIuaa8POvL-GpIBoycRSEH5XAvYeohoClT_w_wcB
6 https://www.tpl.org/our-work/land-and-water/hawaiian-heritage-lands
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Indicator Summarized at
this Timeframe
Unit: count of dwelling units
NEW RESIDENTIAL DEVELOPMENT NEAR IDENTIFIED HISTORIC/CULTURAL RESOURCES
Description: This indicator looks at registered historic places and districts7 and identified historic
and/or cultural sites and trails and summarizes the amount of new development within a certain
distance (default is 500 feet – historic districts measure “within” district, or zero feet).
Methodology: Using a minimum distance function, with a default value of 500 ft, dwelling units are
counted that fall within the minimum distance to places, sites, districts and trails.
Formula or Model: Sum ( [ Attribute : Parcels : Dwelling Units ], where ( [ Attribute : Parcels :
Distance to Place ] < 500 feet ) )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: count of dwelling units
NUMBER OF IDENTIFIED HISTORIC/CULTURAL RESOURCES
Description: Taking into account known and mapped historic and/or cultural resources, this
indicator will count the number of places, sites and districts. Historic trails are measured in miles of
trail.
Methodology: Count historic/cultural resources in GIS data layer.
Formula or Model: Count ( [ Layer : Historic/Cultural Sites ] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
7 GIS data based on draft digitized data from the historic registry, Planning Division, Hawaii County Planning
Department.
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Indicator Summarized at
this Timeframe
Unit: count of historic or cultural resources
ACRES OF CRITICAL HABITAT AND SENSITIVE ECOLOGICAL AREAS OUTSIDE PROTECTED
LANDS
Description: Critical habitat and sensitive ecological areas are not necessarily protected under fee
simple ownership or conservation easements. This indicator looks at the areas protected (State Land
Use Conservation or conservation easement) and summarizes the remainder.
Methodology: Sum of land area where conservation designation and/or easement does not exist.
Formula or Model: Sum ( [ Layer : SEA : Acres ] , where ([attribute : SEA : IsConserved ] = 0 ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: acres
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HAZARDS
This category of indicators addresses the multitude of hazards affecting the County of Hawai’i related to
the General Plan. Hazards addressed include: sea level rise, volcanic activity, wildfire, tsunamis, floods,
and tsunami inundation in addition to sea level rise.
RESIDENTIAL DEVELOPMENT IN AREAS AT RISK OF SEA LEVEL RISE
Description: Summary calculation of housing units that are within the NOAA projected area of sea
level rise8. Projections cover 1 to 6 feet of sea level rise. Recent projections show as much as 1 foot
of rise by 2050 and a between 2.5 and 6.3 feet of rise by 2100. The NOAA elevation model has some
known issues for the Big Island, so calculations add 1 foot of rise per time interval to account for
issues in elevation. Sea level rise for 2050 is measured as 2 feet (1 foot actual) from the NOAA data.
For 2100, it was assumed that 4 feet (3 feet actual) would represent the low end and 6 feet (5 feet
actual - the highest rise available) would represent the high end.
Methodology: Using CommunityViz spatial functions, calculate relationship between parcels and sea
level rise layers. Based on the amount of overlap area, this indicator is a sum of proportional units
that are in features which intersect the sea level rise areas (e.g. a parcel with 50% overlap with sea
level rise of up to 2 feet and containing 10 dwelling units would be calculated as having 5 units
affected by 2050 SLR).
Formula or Model:
Parcels:
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
RESIDENTIAL DEVELOPMENT IN VOLCANO HAZARD ZONES
Description: Summary calculation of housing units that are within high hazard zones (zones 1 and 2)
for volcanic activity9.
8 https://coast.noaa.gov/digitalcoast/tools/slr
9 http://files.hawaii.gov/dbedt/op/gis/data/vhzones_n83.txt
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Methodology: Using CommunityViz spatial functions, calculate relationship between hazard zones
(1 & 2) and parcels. Indicator is a sum of units that are in features which intersect high hazard zones.
Formula or Model:
Polygon (e.g. parcels):
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
RESIDENTIAL DEVELOPMENT IN 100-YEAR FLOODPLAIN
Description: Summary calculation of housing units that are within the 100-year floodplain10.
Methodology: Using CommunityViz spatial functions, calculate relationship between layer(s) with
building data and layer for flood data. Indicator is a sum of units that are in features which intersect
the flood areas.
Formula or Model:
Polygon (e.g. parcels):
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
10 Hawaii County’s 2nd preliminary DFIRM (Digital FIRM) and GIS shapefiles are available on the FEMA Map Service
Center, August 2015. Made available for planning purposes. Preliminary maps are used in County development
regulation, but FEMA has not made this data effective as of the date of this report.
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RESIDENTIAL DEVELOPMENT IN WILDFIRE RISK AREAS
Description: Summary calculation of housing units by wildfire risk zones11 classified as “high risk”.
Methodology: Using CommunityViz spatial functions, classify parcels by wildfire risk zone. Indicator
is a sum of dwelling units wildfire risk zone (low, medium and high).
Formula or Model:
Polygon (e.g. parcels):
Sum ( [attribute : dwelling units], where ( [attribute : wildfire zone] = “High”))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
RESIDENTIAL DEVELOPMENT IN TSUNAMI INUNDATION AREAS
Description: Summary calculation of housing units that are within tsunami inundation areas12.
Several similar indicators examine the amount of new development near tsunami inundation areas
(near is defined as within 50 ft but could be adjusted in the model) and the tsunami zones given an
additional 6 ft of sea level rise.
Methodology: Using CommunityViz spatial functions, calculate relationship between parcels and
tsunami inundation areas. Indicator is a sum of units that are in features which overlap the tsunami
inundation areas based on amount of overlap. Tsunami inundation zones plus 6 ft of sea level rise
were estimated by county planning staff using aerial imagery, sea level rise maps and elevation
contours.
Formula or Model:
Polygon (e.g. parcels):
Timeframe:
11 http://files.hawaii.gov/dbedt/op/gis/data/firerisk.txt
12 2010, based on 2-D inundation modeling by the University of Hawaii, School of Ocean and Earth Science and Technology (UH SOEST) - ftp://ftp.soest.hawaii.edu/volker/Tsunami/Hawaii_Final_Report/Hawaii_Report_2010.pdf
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Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
RESIDENTIAL DEVELOPMENT IN RECENT LAVA FLOWS
Description: Summary calculation of housing units that are within lava flow areas tied to date of
flow. For recent flows, the default value was set to 1990 and more recent.
Methodology: Using CommunityViz spatial functions, calculate relationship between parcels and
lava flow areas which occurred from 1990 (default) to present. Indicator is a sum of units that are in
features which overlap the recent lava flow areas based on amount of overlap. The default value is
an adjustable assumption and can be set as early as 1800.
Formula or Model:
Polygon (e.g. parcels):
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
ENERGY
Energy indicators look at usage and types of energy in use in the County of Hawai’i.
RESIDENTIAL ENERGY USE
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Description: Energy use is an estimate of the amount of energy consumed by residences in the
study area. Residential dwelling units are multiplied by assumptions about residential energy
consumption13. Commercial and industrial energy use information was unavailable.
The model assumes a residential energy rate of 14.7 kwh per housing unit per day based on an
average of one year (October 2014 through September 2015). The model does not assume a
different energy usage rate in the future.
Methodology: Energy rate estimate by land use type multiplied by the number of residential units.
Formula or Model: Residential example:
[attribute : dwelling units] x [assumption : kWh per dwelling unit]
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: kilowatt hours per day
13 http://dbedt.hawaii.gov/economic/energy-trends-2/
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AGRICULTURAL LAND
Agricultural land indicators looks at the available supply of viable agricultural land and impacts to areas
from future development.
ACRES OF AGRICULTURAL LANDS OF IMPORTANCE
Description: This indicator measures the existing land area classified as important agricultural lands
in the LUPAG.
Methodology: Sum parcel land area which overlaps GIS layer LUPAG IAL.
Formula or Model: Sum ( [ Attribute : parcels : LUPAG_IAL overlap] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: acres
DEVELOPMENT IN PRODUCTIVE AGRICULTURAL LANDS
Description: Summary calculation of housing units within defined productive agricultural lands
(PAL). PAL was defined using two separate sources: areas defined in the LUPAG as Important
Agricultural Lands plus pasture lands identified in a 2015 University of Hawai’i – Hilo (UHH) study
that mapped areas of active agricultural and ranching. This covered the existing General Plan policy
areas and expanded it to include pasture lands identified in the UHH study.
Methodology: Using CommunityViz spatial functions, calculate relationship between layer(s) with
building data and layer for productive agricultural lands. Indicator is a sum of units that are in
features which intersect the productive agricultural lands.
Formula or Model:
Polygon (e.g. parcels):
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
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Indicator Summarized at
this Timeframe
Unit: dwelling units
ACRES OF PRODUCTIVE AGRICULTURAL LANDS
Description: This indicator measures the existing land area defined as productive agricultural lands.
Productive agricultural lands comes from a scenario exploring agricultural land protection. This
includes LUPAG IAL and pasture lands identified by the 2015 University of Hawaii study14 on active
agricultural uses.
Methodology: Sum parcel land area which overlaps GIS layer Productive Agricultural Lands.
Formula or Model: Sum ( [ Attribute : parcels : PAL Area] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator Summarized at
this Timeframe
Unit: acres
ACRES OF PASTURE LANDS
Description: This indicator measures the existing land area within pasture lands identified by the
2015 University of Hawaii study15 on active agricultural uses.
Methodology: Sum parcel land area which overlaps GIS layer Pasture Lands.
Formula or Model: Sum ( [ Attribute : parcels : Pasture ] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
14 http://files.hawaii.gov/dbedt/op/gis/data/2015AgBaseline_meta.pdf
15 http://files.hawaii.gov/dbedt/op/gis/data/2015AgBaseline_meta.pdf
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Unit: acres
ACRES OF PUBLIC HUNTING AREAS
Description: This indicator measures the existing land area within public hunting areas16.
Methodology: Sum parcel land area which overlaps GIS layer Public Hunting Areas.
Formula or Model: Sum ( [ Attribute : parcels : Hunting Area ] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: acres
ACRES OF CROPLANDS
Description: This indicator measures the existing land area within crop lands identified by the 2015
University of Hawaii study17 on active agricultural uses.
Methodology: Sum parcel land area which overlaps GIS layer Crop Lands.
Formula or Model: Sum ( [ Attribute : parcels : Crop Area ] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: acres
16 https://www.arcgis.com/home/item.html?id=395f0231b98e412e9d79b8dab513b26d
17 http://files.hawaii.gov/dbedt/op/gis/data/2015AgBaseline_meta.pdf
23
RURAL RESIDENTIAL
Rural residential explores impacts of development outside of urbanized areas, including nonconforming
subdivisions and infrastructure access.
RURAL RESIDENTIAL LOTS
Description: This is a summary of rural residential properties based on the following criteria:
• Lot is not within the State Land Use Urban district
• Public water service is not available to the property
• Lot fronts on a private roadway
• Lot is less than 5 acres in size
This indicator is summarized by all rural residential lots and is also broke out into vacant and
occupied. Vacant rural lots is forecast in the future.
Methodology: Count lots which meet the above criteria.
Formula or Model: Count ( [ Layer : Parcels ], where ( [ Attribute : isRuralRes ] = 1 )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: number of lots
HOUSING UNITS ON RURAL RESIDENTIAL LOTS
Description: Based on the previous definition of rural residential, this indicator sums the existing
dwelling units on rural residential lots.
Methodology: Sum of dwelling units on rural residential lots.
Formula or Model: Sum ( [ Attribute : Parcels : Dwelling Units ], where ( [ Attribute : isRuralRes ] = 1
)
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
24
HOUSING UNITS IN UNSERVICED SUBDIVISIONS
Description: A subset of rural residential lots defined as unserviced or non-conforming subdivisions
(e.g., Hawaii Paradise Park (HPP), Orchidland, Hawaii Ocean View Estates). These places are of
particular concern to planners given their lack of municipal services, including water, wastewater
and public roads. These areas were identified by CoH staff. This indicator sums the existing dwelling
units in unserviced subdivisions.
Methodology: Sum of dwelling units in unserviced subdivisions.
Formula or Model: Sum ( [ Attribute:Parcels:Dwelling Units ], where ( [ Attribute:isUnserviced ] = 1 )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator Summarized at
this Timeframe
Unit: dwelling units
VACANT LOT RATIO
Description: There are numerous platted subdivisions where development has not come close to
build-out. This indicator explores the ratio of vacant properties with residential potential to the
overall development. While its calculated for the entire county, its primarily utility is at the
neighborhood or community scale.
Methodology: Count of vacant properties with residential potential (as defined by the capacity
analysis) divided by all residential lots (Count of developed (has a residence) residential (or
agricultural with residential) properties plus vacant).
Formula or Model:
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: not applicable (ratio)
25
AVERAGE DISTANCE TO URBAN CENTERS FROM RURAL RESIDENTIAL (WEIGHTED BY
POPULATION)
Description: This indicator measures proximity to urban centers (State Land Use District Urban) for
population within rural residential lots.
Methodology: Using CommunityViz spatial formulas, calculate distance to urban centers. Multiply
the distance times the parcel population. Sum the weighted distances and divide by total area
population to get weighted average distance.
Formula or Model:
∑𝑝𝑝𝑛𝑛𝑟𝑟𝑛𝑛𝑛𝑛∑𝑝𝑝𝑛𝑛𝑛𝑛
Where n is the number of features, p is the number of people within a feature, and r is the straight-
line distance from the feature to the nearest destination.
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator Summarized at
this Timeframe
Unit: miles
RESIDENTIAL DEVELOPMENT OUTSIDE URBANIZED AREAS
Description: This indicator summarizes the number of dwelling units outside of urban areas. Two
boundaries were used for this to compare results - LUPAG urban land classes and the State Land Use
District urban.
Methodology: Using CommunityViz spatial formulas attribute parcels which are outside of the
defined urban area boundary. Sum dwelling units outside of the urban area boundary.
Formula or Model:
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
26
Unit: dwelling units
WATER
Water indicators examine the usage and types of water service within the County and its potential
impacts to at risk aquifers It also considers the proximity of new growth to existing water infrastructure.
WATER DEMAND
Description: Water use is an estimate of the amount of water consumed per day by residential,
commercial, industrial uses. Residential and resort water use is estimated on a per unit basis,
schools on a per student basis and other uses on a per acre of land area basis.
Water Use Rates18
Name Rate Unit
Single Family Dwelling Unit Water Equivalent Unit - North
Kona, South Kohala
1000 GPD per unit
Single Family Dwelling Unit Water Equivalent Unit - South
Kona
400 GPD per unit
Single Family Dwelling Unit Water Equivalent Unit - All other
areas of the island
GPD per unit
Commercial Water Equivalent Unit 3000 GPD per acre
Light Industrial Water Equivalent Unit 4000 GPD per acre
Resort Water Equivalent Unit 400 GPD per unit
Multifamily Dwelling Unit Water Unit Discount 60% of Single Family Usage
Methodology: This value is calculated using a coefficient that estimates water consumption per
housing unit, resort unit or nonresidential structure. These coefficients are specific to land or
building use.
Formula or Model:
Residential Example:
([Attribute : dwelling units]* [Assumption : Potable Water Gallons Per Day Per Unit])
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at this Timeframe
18 Domestic Consumption Guidelines from the Water System Standards 2002
27
Unit: million gallons per day
NUMBER OF HOMES BY TYPE OF WATER SERVICE
Description: Many houses in the County are outside of water service areas. This indicator will
summarize housing units being served by municipal providers versus private means (well, storage,
etc.). Future parcels will be assumed to be on central service if on water lines (both existing and
planned future).
Methodology: Houses on water lines (measured using spatial overlap functions) will be assumed to
be on central water service.
Formula or Model:
Water Served Parcels Example:
Sum ( [ Attribute : Parcels : Dwelling Units ], where ( [ Attribute : On Water ] = 1 ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
DEVELOPMENT NEAR EXISTING WATER INFRASTRUCTURE
Description: The most likely expansion of water service will be within range of existing infrastructure
due to cost and capacity limitations. This indicator measures housing units and non-residential
square footage within close proximity to existing water service areas.
Methodology: Using CommunityViz spatial functions, measure distance from parcels to water
service areas. Summarize new housing units and non-residential space within a defined distance of
existing service areas (300 ft is default).
Formula or Model: Sum ( [ Attribute : Parcels : Dwelling Units ], where ( [ Attribute :
DistanceToServiceArea ] <= 300ft ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
28
USE RATES VERSUS SUSTAINABLE YIELD
Description: Understanding water service demand and the capacity of the County’s aquifers to
supply that demand is helpful for infrastructure planning and policy. This set of indicators compare
estimated water demand from residential, commercial and industrial uses to an estimated
sustainable yield by aquifer19. This comparison takes into account development with the geographic
limits of the “at risk” aquifers: Hawi, Keauhou, Kiholo, Mahukona, Waimanu and Waimea. It does
not account for basin transfers or interconnected systems which may take or supplement water in a
given aquifer. At risk aquifers were defined by County staff as those where long term estimates of
urban growth water usage might exceed the sustainable yield of the aquifer as estimated by the
Dept. of Water Supply. Only development connected to private and public centralized systems and
does not consider water demand by development that relies on catchments or residential private
wells. The indicators report the sustainable yield, estimated demand by scenario and remaining
yield.
Methodology: Add existing and projected water demand estimates (by aquifer). Compare with
system capacity (existing and potential planned).
Formula or Model: Existing Demand + New Proposed DemandCapacity
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: million gallons per day
19 Hawaii County Water Use & Development Plan. 2015.
29
WASTEWATER
The County of Hawai’i has limited central wastewater service. Much growth in recent times has
happened in areas where the only viable option is cesspool or septic system. These indicators will
examine wastewater generation and infrastructure options.
RESIDENTIAL WASTEWATER GENERATION VOLUME
Description: This indicator looks at average wastewater generation rates by residential uses and
estimates potential future generation from new residential development.
Methodology: Based on best available data on typical wastewater generation, assign coefficients to
each land use type. Residential generation is based on households connected to wastewater
treatment system. Wastewater generated by houses not connected to a wastewater treatment
system are not included here.
Formula or Model:
Residential:
Wastewater generation rate (378 gpd) * number of households (connected to treatment
facilities)
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: million gallons per day (mgpd)
NUMBER OF HOMES BY TYPE OF WASTEWATER SERVICE
Description: This indicator examines the type of wastewater service available to residential homes –
public centralized service, private centralized service, or onsite disposal systems by type. Onsite
disposal systems are broken into four classes:
• Class I - Any system receiving soil treatment. This includes disposal types listed as bed,
trench, and infiltration/chambers.
• Class II - Septic systems discharging to a seepage pit*. The effluent receives primary
treatment only.
• Class III - Aerobic units discharging to a seepage pit. The effluent receives primary and
secondary treatment.
• Class IV - All cesspools where the effluent receives no treatment.
*Note: A seepage pit is a dry well that disperses effluent from septic tanks. The effluent receives no
treatment other than settling of solids that occurs in the septic tank.
For purposes of reporting, classes 1-3 are labeled septic systems and class 4 represents cesspools.
30
Several locations where residential and non-residential development exist do not have identified
service, either public or OSDS. For the purpose of this analysis, it was assumed that parcels would be
using the service type closest to that property (i.e. my neighbor has a cesspool, I am likely to use a
cesspool). This same process was used to estimate future service types for allocated development.
Methodology: Based primarily on the location of homes, assign each parcel with the type of likely or
known wastewater service available. Sum houses by type.
Formula or Model:
Sum ( [ Attribute : Parcels : Dwelling Units ], where ( [ Attribute : WWType ] = “Cesspool” ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
COUNT OF ONSITE DISPOSAL SYSTEMS
Description: This indicator examines looks specifically at onsite disposal systems (OSDS) by class:
septic, cesspool and large private onsite systems (effluent per onsite disposal system is estimated to
be greater than 5,000 mgpd).
Several locations where residential and non-residential development exist do not have identified
service, either public or OSDS. For the purpose of this analysis, it was assumed that parcels would be
using the service type closest to that property (i.e. my neighbor has a cesspool, I am likely to use a
cesspool). This same process was used to estimate future service types for allocated development.
The average system per housing unit and system per 1,000 square feet of non-residential
development was used to estimate unknown or future OSDS. For existing identified systems, these
rates are:
• 1 OSDS per housing unit
• 0.5 OSDS per 1,000 square feet of non-residential
Methodology: Sum number of OSDS by class.
Formula or Model:
Sum ( [ Attribute : Parcels : OSDS ], where ( [ Attribute : WWType ] = “Cesspool” ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
31
Indicator Summarized at
this Timeframe
Unit: count of onsite disposal systems
DEVELOPMENT NEAR EXISTING WASTEWATER INFRASTRUCTURE
Description: The most likely expansion of water service will be within range of existing infrastructure
due to cost and capacity limitations. This indicator measures housing units and non-residential
square footage within close proximity to existing wastewater service areas.
Methodology: Using CommunityViz spatial functions, measure distance from parcels to wastewater
service areas. Summarize new housing units and non-residential space within a defined distance of
existing service areas (300 ft is default).
Formula or Model: Sum ( [ Attribute : Parcels : Dwelling Units ], where ( [ Attribute :
DistanceToServiceArea ] <= 300ft ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at this Timeframe
Unit: dwelling units
RESIDENTIAL DEVELOPMENT ON SMALL LOTS
Description: DOH rules restrict use of individual wastewater systems (IWS, also called septic
systems) on lots less than 10,000 square feet (unless the lot was created before August 30, 1991).
This indicator estimates the amount of new residential development on (currently) undeveloped lots
less than 10,000 sq ft in size and without any access to a centralized sewer service system. This set
of indicators counts the number of undeveloped parcels less than 10,000 sq ft and the number of
new residences estimated on these lots in each scenario.
Methodology: The indicator identifies existing parcels less than 10,000 sq ft and counts the number
of new dwelling units that are allocated to these parcels in each scenario.
Formula or Model: Sum ( [ Attribute : Parcels : Dwelling Units ], where ([ Attribute:Parcels:Area ] <
10,000))
Timeframe:
32
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe * **
* Existing undeveloped lots, < 10,000 sq ft only
** New dwelling units on lots, < 10,000 sq ft only
Unit: dwelling units
SOLID WASTE
Much of the County’s waste is currently going to landfills. There are questions about capacity and
possible future efforts to increase recycling and reuse.
SOLID WASTE GENERATION
Description: This indicator uses average solid waste generation and diversion rates for population
and employment to estimate potential future generation from new development. This set of
indicators estimates the amount of waste Separate indicators report the amount of existing waste
being delivered to the county’s major landfills: South Hilo Sanitary Landfill and West Hawaii Sanitary
Landfill.
Methodology: Based on best available data on typical waste generation, assign waste generation
and diversion rates to population and employment.
Formula or Model:
Waste generation rate * number of persons-employees
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: tons per year
EXISTING WASTE BY STREAM (LANDFILL, RECYCLING, COMPOST)
Description: This indicator looks at best available data on how waste is streamed (landfill, recycle,
compost, reuse). Based on existing percentages and potential policies for future efforts, streams will
be assigned adjustable percentages so users can test effectiveness of policy choices.
Methodology: The indicator uses adjustable assumptions for each waste stream percent. Default
values to estimated existing streams. The total existing and estimated future waste stream is
multiplied by percentages proposed waste generation to yield stream quantities.
33
Formula or Model:
Percent recycled * Total Waste Generated
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at this Timeframe
Unit: tons per year
TRANSPORTATION
Transportation indicators analyze various transportation networks (roads, transit, bike, pedestrian) and
their service relative to new land use patterns.
ROAD MILES BY JURISDICTION/FUNCTIONAL CLASSIFICATION
Description: These indicators will summarize the road network by jurisdiction (State, County, Other
Government, Private, Roads in Limbo and Unknown) and by Functional Classification (Arterial,
Collector and Local).
Methodology: Bringing in data from Public Works. RPT and HDOT, build a road network layer with
jurisdiction and functional classification attributed. Sum length of each type.
Formula or Model:
Example Calculation:
Sum ( [ Attribute : Roads : Length ], where ( [ Attribute : FC ] = “Arterial” ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: miles
NUMBER OF HOUSES FRONTING ON ROADS BY MAINTENANCE TYPE
Description: Many existing and platted subdivisions have private road networks in varying levels of
maintenance. This indicator estimates how many housing units in these subdivisions are near roads
of various maintenance types (State, County, other government, private, road-in-limbo, unknown).
This indicator will reveal the number of residences who are dependent on certain road types.
34
Methodology: Using CommunityViz spatial formulas, parcels are attributed with the maintenance
type of the nearest road type, called the primary frontage road. Using this field, housing units on
these parcels are counted for each maintenance type.
Formula or Model:
Private Roads:
Count ( [ Layer : Parcels ], where ( [ Attribute : Frontage ] = “Private” ))
County Roads:
Count ( [ Layer : Parcels ], where ( [ Attribute : Frontage ] = “County of Hawaii” ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
MILES OF ROADS FAILING LOS
Description: This indicator focuses on roads maintained by the state, which is the only road type
with level-of-service (LOS) data available. The HDOT transportation models have run scenarios for
2007 baseline and projected 2035 growth. This indicator analyzes reports network conditions based
on the 2035 state transportation model scoring. The set of indicators simplifies the scores into three
categories:
• Under capacity, (passing LOS, roads graded A, B or C)
• Near capacity, (near failing LOS, roads graded D or E)
• Over capacity, (failing LOS roads graded F).
Methodology: Using the HDOT road network data, sum miles of roadway with failing LOS for
existing and future projections.
Formula or Model:
Sum ( [ Attribute : Roads : Length ], where ( [ Attribute : LOS ] = “F” ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: miles
35
RESIDENTIAL DEVELOPMENT NEAR CONGESTED ROADS
Description: This indicator summarizes the number of housing units by the closest road’s level of
service. This measure of congestion is based on the same categories used above (under, near and
over capacity) but rather than use the HDOT 2035 LOS scoring, it uses the current HDOT (2014) LOS
scoring.
Methodology: Using CommunityViz spatial formulas, parcels are attributed with the LOS score of
the nearest road (frontage road). Using this field, housing units on these parcels are counted for
each capacity category.
Formula or Model:
Over capacity roads:
Count ( [ Layer : Parcels ], where ( [ Attribute : ClosestRoadVolume ] = “F” ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
HOUSING UNITS, JOBS AND POPULATION NEAR ROAD INFRASTRUCTURE
Description: This indicator summarizes housing units, jobs and population near road infrastructure
(within 500 feet).
Methodology: Calculate distance to roads. Sum housing units within a specified distance (default
500 feet) of roads.
Formula or Model:
Sum ( [ Attribute : Parcels : Dwelling Units ] , where ( [ Attribute : Distance to Roads ] < 500 ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at this Timeframe
Unit: dwelling units, jobs, population
AVERAGE DISTANCE TO BUS ROUTES (WEIGHTED BY HOUSING UNITS)
36
Description: Using a weighted average distance, this indicator looks at how close housing units are
to the existing bus route network.
Methodology: The indicator is a weighted average distance for all housing units to the nearest bus
route.
Formula or Model:
∑𝑢𝑢𝑛𝑛𝑟𝑟𝑛𝑛𝑛𝑛∑𝑢𝑢𝑛𝑛𝑛𝑛
Where n is the number of features, u is the number of housing units within a feature, and r is the
straight line distance from the feature to the nearest bus route.
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: miles
RESIDENTIAL UNITS NEAR EXISTING BUS ROUTES
Description: This indicator summarizes housing units near bus routes (within ¼ mile, ½ mile and
beyond).
Methodology: Calculate distance to bus routes. Sum housing units within a specified distance
(default ¼ mile and ½ mile) of roads.
Formula or Model:
Sum ( [ Attribute : Parcels : Dwelling Units ] , where ( [ Attribute : Distance to Bus ] < 1320 ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
MILES OF BIKE ROUTES AND SIDEWALKS
Description: These indicators will summarize the amount of dedicated bike routes and sidewalks,
using the best information that the county has available.
37
Methodology: Sum length of each type.
Formula or Model:
Example Calculation:
Sum ( [ Attribute : Bike_Facilities : Length] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator Summarized at
this Timeframe
Unit: miles
EMERGENCY SERVICES
Emergency services include police, fire and ems. These indicators will look at how scenarios population,
households and employees are being served today and into the future.
NUMBER OF HOUSING UNITS WITHIN RESPONSE ZONES (1, 5 AND 10 MILES)
Description: Timely response in an emergency can be a matter of critical importance to life and
safety. This indicator will examine existing emergency facilities by their service areas to examine
timely coverage and any gaps in the network.
Methodology: Using CommunityViz spatial functions, attribute parcels with distance to each facility
type. Summarize housing units within 1, 5 and 10 miles distances.
Formula or Model:
Sum ( [ Attribute : Parcels : Dwelling Units ], where ( [ Attribute : Distance to Facility ] <= 1 Mile))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
AVERAGE DISTANCE TO EMERGENCY SERVICES (WEIGHTED BY HOUSING UNITS)
38
Description: Using a weighted average distance, this indicator looks at how close housing units are
to the existing emergency service facility (fire stations, police stations, hospitals).
Methodology: The indicator is a weighted average distance for all housing units to emergency
service facilities.
Formula or Model:
∑𝑢𝑢𝑛𝑛𝑟𝑟𝑛𝑛𝑛𝑛∑𝑢𝑢𝑛𝑛𝑛𝑛
Where n is the number of features, u is the number of housing units within a feature, and r is the
straight line distance from the feature to the nearest emergency service facility.
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: miles
39
PARKS
Parks in the CoH are a recreation and aesthetic asset for residents and a leading draw for visitors. These
indicators will look at how well the existing park areas are serving the population.
ACRES OF PARK SPACE PER CAPITA
Description: This measure will summarize total park area overall and by type (County, State,
National) divided by population.
Methodology: Sum acres of the parks GIS data layer by population.
Formula or Model:
Sum ( [ Attribute : Parks : Shape_Area ] ) / Sum ( [ Attribute : Parcels : Population ] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at this Timeframe
Unit: acres
AVERAGE DISTANCE TO PARKS AND COASTAL ACCESS POINTS
Description: This indicator estimates the minimum distance from Parcel features to their nearest
Park feature weighted by the number of residents in the Parcel feature.
Methodology: Using CommunityViz spatial functions, measure the minimum distance to Park
features from Parcel features. Multiply the distance times the parcel population. Sum the weighted
distances and divide by total area population to get weighted average distance.
Formula or Model:
∑𝑝𝑝𝑛𝑛𝑟𝑟𝑛𝑛𝑛𝑛∑𝑝𝑝𝑛𝑛𝑛𝑛
Where n is the number of features, p is the number of people within a feature, and r is the straight-
line distance from the feature to the nearest destination.
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
40
Unit: miles
ACRES OF PARKS BY TYPE, FACILITY
Description: This measure will summarize total park area by manager and type of park/available
facilities. Park managers include state, federal and county. Type of park/facility types include: active,
passive, regional, community, playground/neighborhood, beach/beach park, facility, district,
community center, general use, cemetery, scenic/undeveloped, senior facilities.
Methodology: Using attributed data in the Parks layer for type and facilities, summarize the various
types and available facilities.
Formula or Model:
Example Calculation:
Sum ( [ Attribute : Parks : Shape_Area ] , where ( [ Attribute : Type ] = “Beach Park” ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: acres
NUMBER OF PEOPLE WITHIN 1 MILE OF A PARK
Description: This measures looks at the number of people served by nearby parks. Similar to the
average distance, but this measure will provide for the overall percent of the population within 1
mile of parks.
Methodology: Using CommunityViz spatial functions, measure the minimum distance to Park
features from Parcel features. Summarize population which is in Parcel features less than 1 mile.
Formula or Model:
Sum ( [ Attribute : Parcels : Population ] , where ( [ Attribute : Dist2Parks ] <= 5280 ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: persons
41
RESIDENTIAL
Residential indicators explore the existing and future residential supply and look at factors like
affordability, balance with jobs, mix, and context.
HOUSING UNITS
Description: Total housing units by type, single family or multifamily (apartment, condo, etc.).
Methodology: Sum housing units by type.
Formula or Model:
Sum ( [ Attribute : Parcels : Dwelling Units ] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator Summarized at
this Timeframe
Unit: dwelling units
AVERAGE RESIDENTIAL DENSITY AND STANDARD DEVIATION OF DENSITY
Description: This indicate examines residential density and the standard deviation (indicating the
extent of deviation of residential density as a whole). The area under consideration is not the area
of the entire island, but rather just the area of all parcels under development. This is provides a
metric of density more sensitive to additional development that is manifest in the future scenarios.
Methodology: Calculate the sum of housing units divided by area.
Formula or Model:
Sum ( [ Attribute : Parcels : Dwelling Units ] ) / Sum ( [ Attribute : Parcels : Area ] ,
Where ( [ Attribute:Parcels:ResDensityExistOnDevelopedParcels ] > 0 ))
StdDev([ Attribute:Parcels:ResDensityExistOnDevelopedParcels ],
Where ( [ Attribute:Parcels:ResDensityExistOnDevelopedParcels ] > 0 ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at this Timeframe
Unit: dwelling units per acre
42
HOUSING AND TRANSPORTATION AFFORDABLITY
Description: Housing affordability is an important theme in Hawaii. In order to address it within the
scenario planning context, several information sources were consulted. Both the US Department of
Housing and Urban Development (HUD) and the non-profit Center for Neighborhood Technology
have datasets reflecting housing affordability. Both sources include data on housing plus
transportation costs (H+T) which are fundamental to understanding costs borne by families by
considering the dual expenses of housing plus transportation. Both sources offered data at the
census block group level, the finest resolution available. Both data sources depicted affordability as
the percentage of income spent on housing (or spent on transportation or the combined H+T) rather
than the number of affordable units. The demographic and forecast consultant SMS Hawaii
provided data to CoH that estimated the number of affordable units but at the scale of forecast
analysis zone (FAZ) a much coarser spatial scale.
After consulting with CoH staff, it was decided that the HUD data showed a more accurate picture of
housing and H+T costs. These indicators show the number of new residential units in affordable
areas, by affordability type (housing, transportation and H+T). The percent of income spent on
housing, based on existing housing affordability patterns were also estimated for new residential
development. The cutoff levels were selected for affordability, using the industry standard of >30%
of income for housing, >20% for transportation and >50% for H+T. Where families were spending
less than this percentage for these items, these areas were deemed to be affordable areas. The
HUD data provided various options for calculating affordability based on family size and income and
a family of four making 80% of the area median income (AMI) was used as the best available
representation. For the estimate of percent of income spent on housing, transportation and H+T,
the family of four at 100% AMI was chosen.
This method does not predict the number of affordable units but rather uses the geographical
context to suggest more or less affordability of existing or new development. There are many
limitations to this method, including changes in geographic affordability (areas that are affordable
now, may not be in the future), the variation of costs within the census block group, the
development of affordable housing (by housing agencies), new transportation options, changes to
definitions of affordability (including income levels), among other limitations.
Methodology: Sum dwelling units in areas that are currently defined as more affordable by
affordability type (housing, transportation and H+T).
Formula or Model:
Sum ( [ Attribute : Parcels : Dwelling Units ],
Where ( [ Attribute:Parcels:HUDisHousingAffordable ] = 1 ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units, % of income
43
‘OHANA HOUSING UNITS
Description: In 1981 the State of Hawaiʻi passed a bill permitting second dwelling units called ‘ohana
units to be built on single-family lots as a means to improve the affordable housing market and
allow homeowners to accommodate extended family on their property. The counties were then
given the authority to regulate these accessory dwelling units. This indicator estimates the total
number of existing and new ‘ohana housing units.
Methodology: Sum ‘ohana housing units.
Formula or Model:
Sum ( [ Attribute : Parcels : Ohana Dwelling Units ] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
RESIDENTIAL DEVELOPMENT IN URBAN AREAS
Description: This indicator summarizes development that is within urban areas. Multiple boundaries
were used for this to compare results - LUPAG urban land classes, Urban State Land Use District and
infrastructure priority zones (IPAs).
Methodology: Using CommunityViz spatial formulas attribute parcels which are within the defined
urban area boundary. Sum dwelling units within the urban area boundary.
Formula or Model:
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
NEW RESIDENTIAL DEVELOPMENT BY CAPACITY TYPE
44
Description: Capacity was addressed in this analysis by primarily looking at two separate but related
factors: historical trends and density standards established by land use regulation. Quantifying
historic trends required analyzing the number and size of existing built structures on the landscape
and identifying general patterns of growth. Density standards were calculated using numerical
values taken from land use development regulations, primarily the CoH zoning. Capacity categories
were developed to look at capacity within the context of type of unit, subdivision status and
redevelopment potential. Capacity types were originally developed to calibrate and confirm that
the Trend scenario was in line with historic building patterns. It’s use expanded to explore and
describe the type and context of new development (e.g. development occurring in existing
subdivisions, as new subdivisions or as redevelopment of existing developed areas). A complete list
of capacity types are listed in Appendix 4 and discussed in greater detail in the Capacity Technical
Report.
Methodology: Sum dwelling units by capacity type.
Formula or Model:
For the “greenfield subdivided” type:
Sum ( [ Attribute : Parcels : Dwelling Units ],
Where ([ Attribute:Parcels:ResCapacityType ] = "Greenfield Subdivided"))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: dwelling units
COMMERCIAL
Commercial indicators looks at commercial services in terms of location and quantity.
AVERAGE DISTANCE TO COMMERICAL CENTERS
Description: This indicator measures how close residents (and visitors) are to commercial centers.
Commercial centers are defined by commercial zoning. This indicator measures distance to all
commercial centers and breaks it into types (General, Neighborhood, Village).
Methodology: Using CommunityViz spatial functions, measure the minimum distance to
Commercial Center features from Parcel features. Multiply the distance times the parcel population
(or visitors). Sum the weighted distances and divide by total area population to get weighted
average distance.
45
Formula or Model:
∑𝑝𝑝𝑛𝑛𝑟𝑟𝑛𝑛𝑛𝑛∑𝑝𝑝𝑛𝑛𝑛𝑛
Where n is the number of features, p is the number of people within a feature, and r is the straight-
line distance from the feature to the nearest destination.
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator Summarized at
this Timeframe
Unit: miles
SQUARE FEET OF COMMERCIAL
Description: This indicator will report how much commercial square footage is present in the
scenario. Commercial encompasses a wide range of employment types, including retail, office and
services.
Methodology: This calculates the sum of commercial jobs. Existing is defined from RPT data while
future is estimated for each scenario.
Formula or Model:
Sum ( [ Attribute : Parcels : Commercial Square Feet ] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: square feet
COMMERCIAL JOBS
Description: This indicator estimates the number of commercial jobs. Commercial encompasses a
wide range of employment types, including retail, office and services.
Methodology: This calculates the sum of commercial jobs. This analysis estimates jobs based on the
amount of commercial square footage, using a density assumptions, i.e., employees per 1000 square
feet by FAZ for both the existing and future scenarios. Existing and forecast jobs by FAZ were
provided by SMS Hawaii as a part of their 2040 forecast data.
46
Formula or Model:
Sum ( [ Attribute : Parcels : Commercial Jobs ] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at this Timeframe
Unit: square feet
INDUSTRIAL
Industrial indicators will look at industrial uses in terms of type, location and market.
SQUARE FEET OF INDUSTRIAL
Description: This indicator will report how much industrial square footage is present in the scenario.
Industrial encompasses a narrower range of employment types, including light industrial,
manufacturing, shipping and warehousing.
Methodology: This calculates the sum of industrial jobs. Existing is defined from RPT data while
future is estimated for each scenario.
Formula or Model:
Sum ( [ Attribute : Parcels : Industrial Square Feet ] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator Summarized at
this Timeframe
Unit: square feet
INDUSTRIAL JOBS
Description: This indicator will report how many industrial jobs are present in the scenario.
Industrial encompasses a narrower range of employment types, including light industrial,
manufacturing, shipping and warehousing.
47
Methodology: This calculates the sum of industrial jobs. This analysis estimates jobs based on the
amount of industrial square footage, using a density assumptions, i.e., employees per 1000 square
feet by FAZ for both the existing and future scenarios. Existing conditions and forecast jobs by FAZ
were provided by SMS Hawaii as a part of their 2040 forecast data.
Formula or Model:
Sum ( [ Attribute : Parcels : Industrial Jobs ] )
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: jobs
VISITOR
Visitation to the island is a major economic engine but visitors also create impacts and require extensive
infrastructure.
NUMBER OF VISITOR UNITS BY TYPE
Description: Based on a defined classification, summarize the type of visitor accommodation (hotel,
condo-hotel, timeshare, visitor rental unit (VRU). A VRU is a private apartment or house, used for
short term rent and typically advertised via a 3rd party internet site (VRBO, AirBnB, etc.). Visitor unit
estimates were provided by SMS Hawaii as a part of their 2040 forecast data but data was refined by
heads up digitizing based on online sources.
Methodology: Classify the type of visitor units by parcel and sum the number of visitor units by
type.
Formula or Model:
Example Calculation:
Sum ( [ Attribute : Parcels : Visitor Units ], where ( [ Attribute : Visitor Unit Type ] = “Hotel” ))
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Unit: visitor units
48
EMPLOYMENT
Employment indicators focus on the ratio of jobs to housing.
JOBS/HOUSING RATIO
Description: Based on previous calculations for total jobs and total housing units, calculate the ratio
between jobs and housing. The indicator looks at two spatial scales, the jobs/housing ratio by the
entire FAZ and the jobs/housing ratio within just the infrastructure priority areas.
Methodology: Divide total jobs by total housing units.
Formula or Model: Jobs / Housing Units
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator Summarized at
this Timeframe
Unit: ratio of jobs to houses
GENERAL INTEREST
These indicators fall in no particular category but summarize basic information about each scenario.
POPULATION, HOUSEHOLDS AND JOBS
Description: These indicators display the total number of persons, households and employees for.
Methodology: Sum households, people and employment.
Formula or Model: Sum([Attribute:CensusBlocks:Households])
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator
Summarized at
this Timeframe
Units: population, households, jobs
SCHOOL AGED CHILDREN
49
Description: Using percentage rates from SMS data on children age groups, estimate existing and
future children.
• 2015 rate is 17.95%
• 2040 rate is 19.73%
Methodology: Children are measured as a percentage of population.
Formula or Model:
Sum([Attribute : Parcels : Children ])
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
Indicator Summarized at
this Timeframe
Units: school aged children
DASHBOARD INDICATORS
Dashboard indicators summarize multiple indicators by thematic area
DASHBOARD INDICATORS
Description: Dashboard indicators are a way of summarizing multiple indicators into one indicator
which represents a particular theme. Dashboard indicators were used to summarize information for
the public sessions along the following thematic areas: conservation, hazards, building blocks
(infrastructure), settlement patterns, affordability and mixed use. These indicators were displayed
in “double doughnut” charts for the public. Each scenario had a double doughnut chart. This style of
chart made it possible to compare current conditions (the inner doughnut) to future conditions
represented by the scenario (the outer doughnut) as well as compare one scenario to another. The
following table shows the dashboard indicator and the component indicators.
Conservation Residences in sensitive ecological areas Residences on open space Residences on productive agricultural land
Hazard Avoidance Residences in lava high hazard zones Residences in sea level rise/tsunami caution areas Residences in high wildfire risk zones
Building Blocks Residences in water service area
50
Nonresidential near water infrastructure Residences in wastewater service area Nonresidential on wastewater infrastructure Residences on public roads Residences within 1 mile of a County active park Residences within 1/2 mile of bus route New residences near congested arterials
Settlement Patterns Accessory and 'ohana units Number of vacant lots Development outside urban boundaries Housing units in underserved growth subdivisions
Affordability Housing affordability Transportation affordability Homes in areas that are currently H+T affordable
Mixed Use Centers Development outside urban boundaries Housing units in underserved growth subdivisions
Methodology: While the component indicators are calculated in the CommunityViz analysis, the
dashboard indicators indicated in this methodology were created in a separate excel spreadsheet in
order to take advantage of the charting tools available in that tool. Each dashboard indicator had
multiple component indicators. Each component indicator was turned into a percentage for each
scenario using the gross value (existing plus net new development). The maximum and minimum
percentages from a group of scenarios (e.g., Existing, Trend, CDP, Agriculture) could then be
identified. Using the maximum and minimum values, the indicator percentages can be rescaled to a
unitless scale from 0 – 100. Once in the unitless scale, the component indicators can be averaged
together by scenario to yield a final dashboard value.
Formula or Model:
1. Using the building block dashboard indicator as an example, for all scenarios and using the
component indicator Residences in Water Service Areas (WSAs): [Residences in WSAs] / [All
Residences] = [% of Residences in WSAs]
2. Find the maximum and minimum percentage values in all scenarios.
3. For all scenarios, rescale the values:, [% of Res in WSAs] – [Minimum of All Scenarios] / [Max of
All Scenarios] – [Minimum of All Scenarios]
4. Find the average of all component indicator values in the building block dashboard indicator (i.e.
Residences in WSAs, NonRes in WSAs, etc.)
Timeframe:
Timeframe Existing Net New Overall (existing plus future)
51
Indicator Summarized at
this Timeframe
Units: dashboard values are unitless
52
APPENDIX 1 INDICATORS CONSIDERED (BUT NOT ADDRESSED)
The following table lists indicators that were proposed but had to be shelved due to lack of available data or
methodological issues.
Indicator
Wastewater
CWDA Wastewater types
Solid Waste
Capacity of existing facilities by district
Transportation
Intersection density by neighborhood
Residential
Number of existing homes by cost
Jobs by wage category compared to housing by cost
Use Mix
Housing Mix
Income Mix
Commercial
Commercial occupancy rates
Industrial
Industrial occupancy rates
Visitors
Number of visitors
Number of jobs by type - accommodation
Visitor unit occupancy rates
Employment
Number of employees by job
Number of employees by wage bracket
Unemployment rate
Poverty rates
Public assistance rates
Gini coefficients
Mean travel time to work
Revenue-Planning-Finance Alignment
Current assessment revenue
Revenue from more “True” assessments
General Interest
School Capacity
School Demand (number of children) to School Capacity
53
APPENDIX 2 TIER ONE INDICATORS
The Tier One analysis has over 25 indicators which were established to guide and inform the development of
planner driven scenarios. Most of the Tier One indicators have an analogous indicator in the Tier Two analysis and
this is indicated in the table below. Because the two analyses operate at different scales (Tier One uses
neighborhoods called analysis units while Tier Two uses finer scaled parcels) there are some methodological
differences that could result in differences when comparing indicator results.
Tier One Indicator Present in
Tier Two? Description
Housing Adjustment Balance Shows the balance of allocated new residential units. For
sketching purposes and not applicable in the Tier Two analysis.
Distance to Emergency
Services
Three indicators displayed the average weighted distance of all
dwelling units (new and existing) to existing fire stations,
hospitals and police stations.
Adjusted Housing Units by
FAZ Shows the balance of allocated new residential units. For
sketching purposes and not applicable in the Tier Two analysis.
Urban vs. Rural
The number of new allocated units in areas of the island
classified as either rural or urban, using the existing LUPAG
urban growth boundaries to distinguish between the two types.
Rural Residential
Development
The number of new housing units located in underserviced
subdivisions, defined as older nonconforming subdivisions
without public water, public roads and with lot sizes between 1
and 5 ac.
Distance to Schools The average weighted distance of all dwelling units (new and
existing) to existing public schools.
Distance to Parks
Two indicators address this issue. The first indicator finds the
average weighted distance of all dwelling units (new and
existing) to existing public parks. The second indicators
identifies the number of existing and new residences within one
mile of a public park.
Distance to Public
Transportation
Two indicators address this issue. The first indicator finds the
average weighted distance of all dwelling units (new and
existing) to existing bus routes. The second indicators identifies
the number of existing and new residences within ¼, ½ and
more than ½ mile to existing bus routes.
Distance to Urban Centers This indicator finds the average weighted distance of all dwelling
units (new and existing) to identified urban centers.
Ag Land The number of new residential units estimated to be developed
on productive agricultural land.
Hazards
This consisted of three related indicators. The number of new
units estimated to be developed in areas with a high wildfire; in
areas of high volcanic (lava flow) risk and in areas at risk of sea
level rise.
New Houses near WW
Service
Two indicators showing the number of new housing units
located in areas that are served and not served by county
wastewater (sanitary sewer) service.
Development Costs This indicator estimates development costs for new residential
units, in millions of dollars. Provides an estimation of the costs
54
incurred by developers to provide services to new homes,
including water and wastewater tap fees, and other costs by
unit type and geographic location.
Solid Waste Estimates the solid waste generation for existing and new
residential development.
UGB Status The number of new and existing residential units inside the
LUPAG defined urban growth boundary.
SLUD Status The number of new and existing residential units inside the
State Land Used Urban designation.
Residential Unit Type The number of new and existing residential units by building
type, either single family or multifamily residence.
New and Existing
Nonresidential Sq Ft and Jobs
The Trend Scenario included models of both residential and
nonresidential development. This set of indicators displayed the
amount of new and existing nonresidential square footage.
Using the nonresidential square footage, the number of jobs
was estimated as well.
Parks Dedication
Requirement
The County’s Park Dedication Code (Chapter 8, Hawaii County
Code) provides standards for the dedication of land, facilities or
assessment of in-lieu fees for recreational purposes upon the
subdivision of land or the development of multiple family residential units. The code requires a minimum ratio of five
acres of land for park and playground purposes for every 1,000
persons in each district. This indicator was established to track
the attainment of this standard by planning district.
Nonresidential development
on Water and Wastewater
Service
In the workshop analysis, the number of existing and new
residences on public water and wastewater was displayed as a
charted indicator. This set of indicators was expanded to
encompass the number of nonresidential square feet (displayed
in KSF) that have and don’t have these public services.
New Dwellings in Unserviced
Subdivisions
While indicators in the workshop analysis looked at the number
of new houses in rural and urban areas, the unserviced
(sometimes called underserved or nonconforming) subdivisions
(e.g., HPP, Ocean View) represented a special class of land use.
These places are of particular concern to planners given their
lack of municipal services, including water, wastewater and
public roads.
Distance to Centers
This indicator identifies the distance from neighborhood analysis area and finds the distance to the nearest analysis area
that demonstrates the characteristic of being a central location.
The distance is weighed by the amount of existing and new
residential development in each analysis area. Three different
types of centers are defined: commercial, industrial and visitor
centers. What qualifies as a center is controlled by the user,
who can specify the amount of commercial or industrial space
or the number of visitor units which establish which analysis
area is a center. The amounts in each center include both
existing and new development in each center.
New Capital Expenses and
Capital Budget
The water, wastewater and road sketching activities all
estimated costs to be borne by CoH as capital expenses. In order
to frame the accumulation of these costs by the user, the 2015
annual capital budgets for DWS and Public Works/Wastewater
Treatment were included in the model, multiplied by the 20
year implementation horizon. These values provided a rough
55
“budget” for participants to plan their investments in future
infrastructure.
Dashboard Indicators
Dashboard indicators are a way of summarizing multiple
indicators into one indicator which represents a particular
theme. The dashboard indicators in Tier One are incorporated
into the CommunityViz analysis while in Tier Two, these are
incorporated into a separate Excel spreadsheet.
Jobs to Housing Ratio
Using Trend Scenario forecast amount of new (plus existing)
nonresidential square footage, the number of jobs is estimated
and compared against the number of new and existing
residences to provide the jobs to housing ratio for the entire
island.
56
APPENDIX 3 ASSUMPTION VALUES
Assumption Description/Source Details
Residential
Percent Income Spent on H
and T Threshold Income level spent on housing and
transportation, above which housing becomes a
significant burden on the household.
Type: Number
Range: 0 - 100
Default: 50
Units: %
Percent Income Spent on
Housing Threshold
Income level spent on housing, above which
housing becomes a significant burden on the
household.
Type: Number
Range: 0 - 100
Default: 30
Units: %
Percent Income Spent on
Transportation Threshold
Income level spent on transportation, above
which housing becomes a significant burden on
the household.
Type: Number
Range: 0 - 100
Default: 20
Units: %
Ratio of Existing Development
to Gross Capacity
This attribute is used to manage the ratio of
existing development to gross capacity for
purposes of identifying residential capacity
types.
Type: Number
Range: 0 - 1
Default: 0.5
Units: NA
Energy
Residential Energy Use
Estimated residential energy use, based on
assumed use per housing unit per day. Source:
DBEDT Hawaii (state energy trends)
Type: Number
Range: 10 - 50
Default: 14.7
Units: kwh per day
Transportation
Near Roads For estimating housing units close to existing
roads. Default is 500 feet.
Type: Number
Range: 0 - 1500
Default: 500
Units: feet
Solid Waste
Commercial Waste Percent
Island
Estimated waste originating from nonresidential
sources across the entire island. Source: CoH
Public Works
Type: Number
Range: 0 - 100
Default: 61
Units: percent
Commercial Waste Percent
SHSL
Estimated waste originating from nonresidential
sources estimated for the South Hilo Sanitary
Landfill. Source: CoH Public Works
Type: Number
Range: 0 - 100
57
Default: 52
Units: percent
Commercial Waste Percent
WHSL
Estimated waste originating from nonresidential
sources estimated for the West Hawaii Sanitary
Landfill. Source: CoH Public Works
Type: Number
Range: 0 - 100
Default: 67
Units: percent
Solid Waste Generation Rate
Coefficient rate of waste generation in tons per
person or per employee per year. Source: CoH
Public Works
Type: Number
Range: 0.2 - 2
Default: 0.77
Units: tons per person -
employee per year
Waste Diversion Rate
Estimated rate of waste diverted to recycling or
compost from the waste stream. Source: CoH
Public Works
Type: Number
Range: 0 - 75
Default: 25
Units: percent
Wastewater
Residential Wastewater
Generation Rate
Estimated wastewater generation rate. Source:
CoH Public Works
Type: Number
Range: 100 - 1000
Default: 378
Units: gallons per day
Wastewater Average Cost of
New Septic Tank
Estimated wastewater generation rate. Source:
CoH Planning
Type: Number
Range: 5000 - 12000
Default: 8500
Units: $
Wastewater WW Distribution
Cost per Linear Ft
Estimated of a linear foot of WW line, including
labor. Source: CoH Public Works
Type: Number
Range: 0 - 200
Default: 100
Units: $
Water
Commercial Water Equivalent
Unit
Estimated commercial water consumption.
Source: CoH Water Supply
Type: Number
Range: 1000 - 6000
Default: 3000
Units: gpd per acre
Housing Water Equivalent Unit
Estimated residential water consumption
(everywhere but South Kona, North Kona, South
Kohala). Source: CoH Water Supply
Type: Number
Range: 100 - 1000
Default: 400
Units: gpd per unit
Housing Water Equivalent Unit
SKNK
Residential water multiplier for South Kohala and
North Kona. Source: CoH Water Supply
Type: Number
Range: 0 - 1500
Default: 1000
Units: gpd
58
Housing Water Equivalent Unit
South Kona
Residential water multiplier for South Kohala and
North Kona. Source: CoH Water Supply
Type: Number
Range: 0 - 1000
Default: 600
Units: gpd
Light Industrial Water
Equivalent Unit
Estimated light industrial water consumption.
Source: CoH Water Supply
Type: Number
Range: 1000 - 6000
Default: 4000
Units: gpd per acre
Multifamily Residential Water
Use Adjustment
This assumption adjusts the housing water
equivalent consumption for multifamily units.
Multifamily units consistently use less water than single family houses due to the lack of outdoor
watering needs and their tendency to have a
smaller number of persons per household. The
default value is based on a 2014 study of water
usage in Tampa Bay, Florida but is widely
reflected in water studies across the continental
USA. No local source of information were
available.
Type: Number
Range: 0 - 1
Default: 0.6
Units: %
Water Catchment System Cost Estimated wastewater generation rate. Source:
CoH Planning
Type: Number
Range: 0 - 5000
Default: 3500
Units: $
Water Distribution Cost per
Linear Foot
Estimated of a linear foot of water line, including
labor. Source: CoH Water Supply
Type: Number
Range: 0 - 200
Default: 100
Units: $
Hazards
Caution Distance to Tsunami
Inundation
Distance from the tsunami inundation line to still
be considered "near" a tsunami inundation area
Type: Number
Range: 0 - 500
Default: 50
Units: feet
Recent Lava Flow Date which defines "recent" lava flow.
Type: Number
Range: 1800 - 2015
Default: 1990
Units: year
Conservation
Distance to Historic and
Cultural
Assumption used to establish the level of
"nearness" for historic, cultural and conservation
indicators. If features located less than this
threshold, they are considered near for the purposes of the indicators which depend on this
assumption.
Type: Number
Range: 0 - 5000
Default: 500
Units: feet
General
Type: Number
59
2015 Average Persons per
Housing Unit
Average number of persons per housing unit in
2015. Source: SMS Hawaii
Range: 2 - 3
Default: 2.62
Units: persons per
house
2015 Percent School Aged
Average percent of household members that
could attend primary or secondary school in
2015. Source: SMS Hawaii
Type: Number
Range: 0 - 100
Default: 17.95
Units: percent
2040 Average Persons per
Housing Unit
Average number of persons per housing unit in
2040. Source: SMS Hawaii
Type: Number
Range: 2 - 3
Default: 2.62
Units: persons per
house
2040 Percent School Aged
Average percent of household members that
could attend primary or secondary school in
2040. Source: SMS Hawaii
Type: Number
Range: 0 - 100
Default: 19.73
Units: percent
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APPENDIX 4 RESIDENTIAL CAPACITY TYPES
Capacity has been categorized using the types listed and summarized by acres of each type below.
These types are visible using the “HawaiiCapacity” CommunityViz Analysis. This classification is for the
internal review team to help understand the different types of capacity that the model is using.
• Greenfield Subdivided. There are no existing residential or nonresidential units on the parcel,
according to RPT records. The parcel can be developed to its full capacity but minimum parcel
areas prevent further subdivision.
• Rural Greenfield with Subdivision Potential. There are no existing residential or nonresidential
units on the parcel according to RPT records, and the parcel has agricultural type zoning (A, FA,
etc.). The parcel can be developed to its full capacity and the parcel can be further subdivided
(i.e., the parcel area is greater than two times the minimum parcel area).
• Urban Greenfield with Subdivision Potential. There are no existing residential or nonresidential
units on the parcel according to RPT records, and the parcel is not on in Agriculture,
Conservation, or Open zoning (i.e., C, M, R, V, etc.). The parcel can be developed to its full
capacity, and the parcel can be further subdivided (the parcel area is greater than two times the
minimum parcel area).
• Farm Dwelling Unit. In zones that allow an extra farm dwelling unit, there is one residential
structure on the parcel and capacity for one additional farm dwelling.
• Ohana Dwelling Unit. Residential only. In zones that allow an ʻohana dwelling unit, there is one
residential structure on the parcel and capacity for one ʻohana unit.
• High Additional Redevelopment Capacity. This class uses the term “redevelopment” very
loosely and describes areas where additional development could likely occur by subdivision of
the existing parcel or with very little change to the existing structure on the parcel. There are
one or more existing structures on the parcel and the zoning allows for greater density than
what currently exists. In this case, the existing residential or non-residential structures exist at
low densities relative to the gross capacity. Specifically, the existing development is less than ½
of the gross capacity .
• Low Additional Redevelopment Capacity. Similar to the category above, one or more structures
exist on the parcel, and the zoning allows for greater density than what currently exists. In this
case, the existing residential or non-residential structures exist at higher densities than found in
High Additional Redevelopment Capacity (the existing development is more than ½ of the gross
capacity).
• At or Over Capacity. The number of units (dwelling units or non-residential square feet) on the
parcel meets or exceeds the allowed capacity.
• Government or Conservation. The land ownership is government or dedicated to conservation
uses. Note that DHHL and HPHA properties are not included in this category for this analysis.
• Unbuildable. Physical limitations—either steep slopes or wetlands—are restricting the capacity
of the parcel.
• Other No Capacity. The parcel has no capacity. This is usually occurs for one of the following
reasons: 1) the zoning does not allow either residential or non-residential development; 2) tax-
exempt properties (churches, private schools, etc.) that have been excluded from the analysis
areas; or 3) the zoning type has not been established.