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Population & employment projection maps:Salt Lake County & Kennecott Land
Dec 2006
prepared by Scott BridwellDIGIT Lab, University of Utah
Mapping & analysis objectives
• Create population and employment maps for Salt Lake County that seamlessly integrate:
– Projections for population and employment counts generated by Wasatch Front Regional Council at the TAZ level for 2010-2030 (based on the 2003 baseline)
– State projections for anticipated employment and population counts for the Kennecott Land development area as a whole for 2010-2059 (based on the 2005 baseline)
– Kennecott Land master plan detailing the distribution of anticipated land-uses as well as the time phases in which specific areas are expected to be developed
Mapping & analysis procedures
• Step 1: Spatially allocate GOPB prescribed population & employment within w/in the Kennecott development – For specified window years: 2010, 2020, 2030, 2040, 2050, 2059– Cumulative population/employment allocated must comply with GOPB
Kennecott totals– Allocated proportionally based on attributes w/in the master plan
(total dwelling units for population; total square footage for employment)
– Map population & employment at the resolution of the master plan
• Step 2: Reconcile the Kennecott totals with WFRC small area projections– For specified window years: 2005, 2010, 2020, 2030– Scale the small area totals to match 2005 GOPB baseline– Spatially join Kennecott totals w/ the TAZ projections– Re-scale TAZ totals such that cumulative population/employment
comply w/ GOPB county totals while maintaining Kennecott totals– Map the results for Salt Lake County & populated places at TAZ level
This map provides a reference of the Kennecott land development for later maps to come…
Source: West Bench Master Plan from Kennecott
Allocating GOPB projections among Kennecott planned development
• Kennecott planned units– Cell resolution: 150 x 150 meters– Attributes:
• Planned use: commercial, industrial, mixed use, mixed use – low, open space, public, residential
• Dwelling units at build-out• Square footage at build-out• Development phasing
• Spatial allocation method– Allocate projected population and
employment according to the cell attributes, timing of development phasing & GOPB projection trends
– Population determined from the # of dwelling units in a development cell
– Employment determined from the # of total square feet and planned land-use of a development cell
Kennecott master plan
This is the spatial distribution of development start and end times.
This produces 5 distinct phases…
Kennecott development phasing
• Phase 1: 2010 – 2019– Dwelling units: 19,789; square footage: 12,946,879
• Phase 2: 2010 - 2029– Dwelling units: 15,318; square footage: 6,046,356
• Phase 3: 2025 – 2039– Dwelling units: 54,314; square footage: 4,240,224
• Phase 4: 2025 – 2059– Dwelling units: 3913; square footage: 389,595
• Phase 5: 2040 – 2059– Dwelling units: 72,579; square footage: 37,232,910
Note: This is the distribution of dwelling units and square footage @ 2059 when the project completes
The following slides discuss how these units are distributed in time according to development phasing and GOPB projection controls
Kennecott population (2009 - 2059)
0
50
100
150
200
250
300
350
400
450
500
2009 2014 2019 2024 2029 2034 2039 2044 2049 2054 2059
year
po
pu
lati
on
(th
ou
sa
nd
s)
Source: GOPB 2005 baseline
The temporal distribution of the Kennecott population by year provides the starting points for allocating the population spatially.
Allocating Kennecott population
• Step 1: for each year and each phase:– Determine the total number of dwelling units that are likely to be
built– Essentially we are allocating the number of dwelling units that
will be built at a location at a given year– Conducted w/in a spreadsheet
• Step 2: for each year and location– Determine the total population that is likely to be at a given
location– Based on the total # of units built at the location (provided by
Step 1) for the given year and the aggregate population total for the given year
– Conducted w/in ArcGIS
Kennecott population growth contribution by year
0
0.5
1
1.5
2
2.5
3
2009 2014 2019 2024 2029 2034 2039 2044 2049 2054 2059
year
% g
row
th c
on
trib
uti
on
The following shows the % of population growth contribution for each year. If there was a single development phase then we could allocate the number of units built for a given year based simply on this (see the notes below). However, since there are multiple, overlapping phases…
Phase specific growth contributions
• Required to interpolate / allocate development units to years in between start and completion times
• Attempt to improve upon linear allocations (that produce irregular people per dwelling densities) by fitting the allocation to the population change distribution
• Growth contributions generated according to a specific interval of time, with the total population change indicating the total change within the temporal interval
• Intervals created by ‘intersecting’ overlapping development phases (e.g. 2010-2029 & 2025-2039)
• Intervals created– 2010 - 2019 (phases 1 & 2); population change: 63,565– 2020 - 2024 (phase 2); population change: 56,076– 2025 - 2029 (phases 2, 3 & 4); population change: 60,665– 2030 - 2039 (phases 3 & 4); population change: 112,600– 2040 - 2059 (phases 4 & 5); population change: 175, 951
Phase specific growth contributions
0
5
10
15
20
25
2009 2014 2019 2024 2029 2034 2039 2044 2049 2054 2059
year
% g
row
th c
on
trib
uti
on
Phase 1
Phase 2
Phase 3
Phase 4
Phase 5
Interval 163,565
Interval 256,076
Interval 360,665
Interval 4112,600
Interval 5175,951
*See the notes below for more info
Dwelling unit allocations by year
0
20
40
60
80
100
120
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160
180
2009 2014 2019 2024 2029 2034 2039 2044 2049 2054 2059
year
tota
l d
wel
lin
g u
nit
s (t
ho
usa
nd
s)
Phase 1
Phase 2
Phase 3
Phase 4
Phase 5
Total units
Applying the interval specific growth contributions to the total dwelling units that will be built yields the following (see notes)…
Dwelling unit allocation
0
20000
40000
60000
80000
100000
120000
140000
160000
180000
2009 2014 2019 2024 2029 2034 2039 2044 2049 2054 2059
year
dw
elli
ng
un
its
Growthcontributionallocation
Linear allocation
This following illustrates the differences between allocating the units linearly/uniformly with the fitting allocation. The differences seem negligible until looking @ the derived population densities…
Dwelling density / household density
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
2010 2015 2020 2025 2030 2035 2040 2045 2050 2055
year
peo
ple
per
dw
elli
ng
Grow th contributionallocation
Linear allocation
County averagehousehold size
This use of dwelling/household density provides a kind of the validation of what allocation approach provides the most realistic fit with the population, since we know there are reasonable upper and lower bounds. The growth contribution allocation is far from perfect but provides a little bit better fit than just allocating units linearly. This is especially true for our window years of 2010, 2020 & 2030.
Also, the lower densities previous to 2020 (over estimate of housing) followed by the spike in the early to mid 20s (under estimate in housing) probably is an artifact of the phasing and suggests that some of the development in phases are out of sync with the expected population.
Allocating population changes spatially
Phase StartEnd UNITS2010 UNITS2020 UNITS2030 UNITS2040 UNITS2050 UNITS2059 UNITSUM
Phase 1 2010_2019 920 19789 19789 19789 19789 19789 19789
Phase 2 2010_2029 237 6022 15318 15318 15318 15318 15318
Phase 3 2025_2039 0 0 29975 54314 54314 54314 54314
Phase 4 2025_2059 0 0 1439 2688 3451 3913 3913
Phase 5 2040_2059 0 0 0 4442 46917 72579 72579
This table was summarized for the window years from the growth contribution allocation. It will be joined with the Kennecott development units feature class to allocate the total dwelling units at a location for each window year. The tables are joined based on the ‘StartEnd’ attribute which uniquely defines a development phase.
The number of dwelling units at a location at a given time is obtained by multiplying the location’s total build-out units (field du_total in the attribute table) by the ratio of the total units allocated by a phase at the given time to the total units that will be allocated by the phase at build-out.
For example, if we have a location that has 10 dwelling units, is a member of phase 2, and we want to know the total units built by 2020 then we would do the following:
10 * (6022 / 15318) = 3.93
So 3.93 units are allocated to this specific location for the year 2020.
Allocating population changes spatially (2)
Now that we have assigned the total dwelling units at a location that will be built for the window years we can allocate the population by multiplying the total dwelling units at the desired time by the ratio of the total population at the time to the total number of dwelling units built at that time.
So for our location from the last slide with 3.93 dwelling units at time 2020, the total population @ the location at 2020 is:
3.96 * (73633 / 25812) = 11.21
So there are 11.21 people at this location during 2020
Year Kennecott population Total dwelling units allocated
2010 2,957 1,158
2020 73,633 25,812
2030 191,991 66,522
2040 303,675 96,552
2050 406,647 139,790
2059 468,857 165,913
Resulting population distribution for 2010.
Resulting population distribution for 2020.
Resulting population distribution for 2030.
Kennecott population by geographic sector
NORTHINGTotal dwellings
at build-out POP2010 POP2020 POP2030
South of 9000 South 61,734 0 0 67,200
Between 2100 South and 9000 South 54,282 1,117 28,442 68,465
North of 2100 South 49,897 1,837 45,189 56,323
Kennecott employment (2009 - 2059)
0
10000
20000
30000
40000
50000
60000
70000
80000
90000
2009 2014 2019 2024 2029 2034 2039 2044 2049 2054 2059
years
tota
l em
plo
ymen
tThe same process was applied to employment. Except here we are interested in allocating the amount of square footage that will be built and then using this to allocate employment.
Again we begin w/ the yearly distribution of projected employment…
Kennecott employment growth contribution by year
0
1
2
3
4
5
6
2009 2014 2019 2024 2029 2034 2039 2044 2049 2054 2059
years
% g
row
th c
on
trib
uti
on
Next we consider the % employment growth contribution by year…
Employment intervals
• 2010 – 2019 (phases 1 and 2)– Employment change: 11,379
• 2020 – 2024 (phase 2)– Employment change: 3,963
• 2025 – 2029 (phases 2, 3, & 4)– Employment change: 3,625
• 2030 – 2039 (phases 3, & 4)– Employment change: 10,282
• 2040 – 2059 (phases 4 & 5)– Employment change: 51,261
Phase specific employment growth contributions
0
5
10
15
20
25
30
35
40
45
2009 2014 2019 2024 2029 2034 2039 2044 2049 2054 2059
year
% i
nte
rval
gro
wth
co
ntr
ibu
tio
n
Phase 1
Phase 2
Phase 3
Phase 4
Phase 5
Interval 111,379
Interval 23,963
Interval 33,625
Interval 410,282
Interval 551,261
The employment intervals yield the following growth contributions…
Square footage allocation by year
0
10
20
30
40
50
60
70
2009 2014 2019 2024 2029 2034 2039 2044 2049 2054 2059
year
allo
cate
d s
qu
are
feet
(m
illi
on
s)
Phase 1
Phase 2
Phase 3
Phase 4
Phase 5
Total
This is the resulting allocated square footage by phase and year…
Derived square feet per employee
0
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1000
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1400
2009 2014 2019 2024 2029 2034 2039 2044 2049 2054 2059
year
sq f
t p
er e
mp
loye
e
Attempting to validate the resulting employment distribution is a little less intuitive than that of using population density as discussed above. However, it seems somewhat obvious in comparing the derived square feet per employee obtained here with the standard estimates of the Calthorpe associates (1000 industrial, 350 office, 750 retail) that there is somewhat of a discrepancy here w/ the number of planned square footage far exceeding those estimates.
Industrial
Office
Retail
Allocating employment spatially
This table was summarized for the window years from the growth contribution allocation. It will be joined with the Kennecott development units feature class to allocate the total square footage at a location for each window year. The tables are joined based on the ‘StartEnd’ attribute which uniquely defines a development phase.
The amount of square footage at a location at a given time is obtained by multiplying the location’s total build-out square footage (field sf_total in the attribute table) by the employee to square foot ratio of the square footage allocated by a phase at the given time to the total square footage that will be allocated by the phase at build-out.
For example, if we have a location that has 15,000 total square feet, is a member of phase 2, and we want to know the total square footage built by 2020 then we would do the following:
15000 * (2297706.82 / 6046356) = 5700.23
So 5700.23 square feet are allocated to this specific location for the year 2020.
Phase StartEnd SF2010 SF2020 SF2030 SF2040 SF2050 SF2059
Phase 1 2010_2019 5043810.05 12946879.00 12946879.00 12946879.00 12946879.00 12946879.00
Phase 2 2010_2029 785174.33 2297706.82 6046356.00 6046356.00 6046356.00 6046356.00
Phase 3 2025_2039 0.00 0.00 2263418.54 4240224.00 4240224.00 4240224.00
Phase 4 2025_2059 0.00 0.00 138643.08 267147.82 337869.01 389595.00
Phase 5 2040_2059 0.00 0.00 0.00 2126723.25 22402822.61 37232910.00
Allocating employment changes spatially (2)Now that we have assigned the total square footage at a location that will be built for the window years we can allocate the employment by multiplying the total square footage at the desired time by the ratio of the total employment at the time to the total amount of square footage built at that time.
So for our location from the last slide with 5700 square feet at time 2020, the total employment @ the location at 2020 is:
5700 * (11934 / 15244586) = 4.46
So there are 4.46 jobs at this location during 2020
CAVEATS:- As noted before, the derived square feet per employee seems a bit a high.- Given the mixed-use component of the majority of the Kennecott plan, no attempt was made to explicitly incorporate land-use. Instead our strategy implicitly estimates this by fitting phase square footage to aggregate employment projections.
Year Kennecott employment Total square feet allocated
2010 4,433 5,828,984
2020 11,934 15,244,586
2030 19,662 21,395,297
2040 32,177 25,627,330
2050 60,092 45,974,151
2059 80,510 60,855,964
Resulting employment distribution for 2010.
Resulting employment distribution for 2020.
Resulting employment distribution for 2030.
Derived GIS attributes for Kennecott master plan
• GIS feature class: kennLandUse.shp
• Derived attributes:– Dwelling units allocated by year: DU2010, DU2020, DU2030,
DU2040, DU2050, DU2059
– Population by year: POP2010, POP2020, POP2030, POP2040, POP2050, POP2059
– Square footage allocated by year: SF2010, SF2020, SF2030, SF2040, SF2050, SF2059
– Employment by year: EMP2010, EMP2020, EMP2030, EMP2040, EMP2050, EMP2059
Reconciling WFRC TAZs & Kennecott counts
• Issue 1: WFRC TAZs controlled to 2003 baseline whereas Kennecott figures controlled to 2005 baseline
• Resolution: Scale the WFRC TAZs (based on the 2003 Baseline) to meet the GOPB 2005 baseline
• Scaled as follows:count(taz, t) = wfrcCount(taz, t) * (gopbSumCount(t) / wfrcSumCount(t))
Where: - count(taz, t) = count (employment or population) at a given TAZ for the given year scaled to the 2005 baseline- wfrcCount(taz, t) = count at a given TAZ for the given year as provided by the WFRC projections - gopbSumCount(t) = total count for GOPB 2005 baseline for the entire county for the given year- wfrcSumCount(t) = total count for all WFRC TAZ projections for the given year
Reconciling WFRC TAZs & Kennecott counts (2)
• Issue 2: How to assign the Kennecott count to the TAZs?
• Resolution:– For each Kennecott development cell:
• Obtain the cell’s centroid
• Use a spatial join to assign the centroid to the closest TAZ polygon
• Summarize the joined class based on the TAZ attribute to obtain a sum of the Kennecott population for each TAZ
• Join the TAZ polygon class to the Kennecott summary table and assign the total Kennecott counts for each year
Reconciling WFRC TAZs & Kennecott counts (3)
• Issue 3: How to reconcile the count w/in a given TAZ with the Kennecott summary count assigned to that TAZ?
• Two cases:– Kennecott summary count is greater than the TAZ count
– Kennecott summary count is less than the TAZ count
• Resolution:– For each TAZ:
• Determine the amount of the population that is not part of the Kennecott development
• Assign the reconciled population as the sum of the Kennecott population and the scaled not-Kennecott population
Determining the not-Kennecott population
• For each TAZ at a given time t:
– If the Kennecott population in the TAZ at time t is greater than the TAZ population at time t:
• Not-Kennecott population at time t = not-Kennecott population at time t – 1
• For example if Kennecott population in 2030 is greater than the TAZ then the amount of non-Kennecott population in 2030 is equal to the non-Kennecott population in 2020
• This assumes that all the new development taking place during this time is attributed to Kennecott
• This allows us to retain populations/employments that existed in the TAZ previous to the Kennecott development
Determining the not-Kennecott population (2)
• For each TAZ at a given time t:
– If the Kennecott population in the TAZ at time t is less than the TAZ population at time t:
• Not-Kennecott population at time t = TAZ population at time t minus the Kennecott population at time t
• This assumes that the growth occurring w/in the TAZ is a function of developments both within and outside of the Kennecott development
Script for determining the not-Kennecott population for 2020
out = 0
if [kenn2020] > [gopb2020] then out = [nkenn2010] else out = [gopb2020] - [kenn2020] end if __esri_field_calculator_splitter__out
For use with the ArcGIS field calculator:
kenn2020: attribute containing the Kennecott population from the master plan for 2020 for the given TAZnkenn2010: attribute containing non-Kennecott population in the for 2010 for the given TAZ gopb2020: attribute containing the scaled WFRC population for the given TAZ
Deriving the reconciled TAZ count
• The total count at a given TAZ for a given time t is then: count(taz, t) = kenn(taz, t) + [scaling(taz, t) * gopbNotKenn(t) ]
To determine the scaling factor:scaling (taz, t) = notKenn(taz, t) / gopbNotKenn(t)
Where:-count(taz, t): final count for a given TAZ for the given time-kenn(taz, t): Kennecott population within a given TAZ for the given time
-notKenn(t): total (sum of all TAZs) not-Kennecott for the given time -gopbNotKenn(t): total (sum of all TAZs) not-Kennecott population based on the GOPB baseline
Script for determining the final Kennecott population for 2020
notKenn = 1340337.305244scaling = [nkenn2030] / notKennnotKennGopb = 1189528out = [kenn2030] + (scaling * notKennGopb)__esri_field_calculator_splitter__out
For use with the ArcGIS field calculator:
notKenn: total not Kennecott population obtained by summing the nkenn attribute described in slides (37-40); for 2020 this value is 1,340,337nkenn2030: attribute containing the not-Kennecott population for the given TAZnotKennGopb: total not-Kennecott population based on the GOPB baseline; for 2020 this value is 1,189,528
GIS attributes for Salt Lake County• Population attributes (tazPopulation class)
– Original WFRC population: wfrc2005, wfrc2010, wfrc2020, wfrc2030
– WFRC population scaled to GOPB 2005 baseline: gopb2005, gopb2010, gopb2020, gopb2030
– Kennecott population obtained from master plan: kenn2010, kenn2020, kenn2030
– Not Kennecott population (slides 37 - 40) : nkenn2010, nkenn2020, nkenn2030
– Final population: pop2005, pop2010, pop2020, pop2030
– Final population change: chg05_10, chg10_20, chg20_30, chg_05_30
GIS attributes for Salt Lake County• Employment attributes (tazEmployment class)
– Original WFRC employment: wfrc2005, wfrc2010, wfrc2020, wfrc2030
– WFRC employment scaled to GOPB 2005 baseline: gopb2005, gopb2010, gopb2020, gopb2030
– Kennecott employment obtained from master plan: kenn2010, kenn2020, kenn2030
– Not Kennecott employment (slides 37 - 40) : nkenn2010, nkenn2020, nkenn2030
– Final employment: emp2005, emp2010, emp2020, emp2030
– Final employment change: chg05_10, chg10_20, chg20_30, chg_05_30
