Integrating landscape amenities with historic parcelization
trends to better target landscape conservation efforts
Anna Haines, Ph.D. and Dan McFarlane
University of Wisconsin – Stevens Point
Introduction
Methods
Preliminary Results
Amenity Index vs Property Values
The process of rural land division provides an ongoing
challenge for planners targeting both habitat and
farmland preservation. In developing a research
approach that entailed mapping historic parcelization
patterns, we used past trends to understand key
factors driving land subdivision.
ƒ Research archival plat books and tax assessment
rolls, identifying parcel splits
Figures 2a and 2b illustrate the past and current parcel
pattern within the Town of West Point. One can see
that the trend is near-lakeshore lot development
(Figure 3).
Note the differences in the figures below to understand
our parcelization model at the sub-parcel level.
Communities rich with natural amenities, such as
lakes and forestland, are experiencing high growth
rates and, in these areas, land subdivision for
recreation and retirement are common. Surprisingly,
few people have accurately tracked the parcelization
process both spatially and over time.
Examining the spatial pattern of parcel creation and its
relationship to land use variables over time in six rural
Wisconsin communities allowed us to assess the
features that appeared to drive parcelization.
ƒ The current digital parcel layer was used to spatially
reconstruct accurate parcel boundaries at various
time periods
ƒ Historic land use/cover data was mapped by
analyzing historic aerial photos and the WI Bordner
Survey
ƒ Selected landscape fragmentation metrics will be
used to measure the degree of agricultural
perforation over time
ƒ Hypothesized amenity features will be combined in
a weighted overlay layer, assigned to parcels, and
tested for each time period
Most of the parcelization has been in the 0-2 acre size
class, indicating residential development (Figure 4).
Landscape metrics indicate that agriculture core areas
are being perforated by small lot creation and
subsequent residential development.
Land values were not used as an amenity surrogate
because:
• assessment criteria has changed over the years,
making land values difficult to track
• a single value per acre belies the potential amenity
gradient within a parcel (Figure 6)
Low
A weighted overlay of hypothesized factors driving
parcelization is being developed to identify areas of
candidates for subdivision policy (Figure 5).
Town of West Point, WI - 1953
Amenity Values
High
Normalized Land Values
Town of West Point Parcel Counts
1,800
Using the identified push/pull variables, we created an
amenity index and applied these values to parcels.
Undivided parcels were considered prime candidates
for targeting subdivision policy.
1,600
Figure 6. Amenity index (left) and normalized land values (by acre) (right). Our amenity
index has sub-parcel resolution, allowing us to precisely locate potential development
within a parcel.
1,400
1,200
"0-2"
Number
Figure 2a. Parcelization
pattern in 1953 for the
Township of West Point. At
this time, most tax parcels
were still forties, with some
subdivision along Lake
Wisconsin.
1,000
"2-5"
"5-10"
"10-20"
800
"20-30"
"30-40"
600
Town of West Point, WI - 2005
"40+"
Ultimately, this research should help us and others
design better local rules to accomplish identified
planning goals, such as farmland preservation.
400
Aim
200
0
1953
1961
1967
1972
1983
1991
This research is leading us to further questions and
how we might address them. Many of our current tools
use density as a measure of spatial closeness, but, are
other measures better? In addition, are current land
development techniques (zoning, land division
regulations, PDR, TDR, and others) the best tools to
use for development or are there others?
Town of West Point, WI
Amenity Index
Amenity Variables
Low
Number of Parcels and Distance to Water
600
550
Public land distance (distance to public
land)
500
Forest distance (distance to forest)
450
Water distance (distance to water)
High
400
350
300
250
Soil Limitations (percent of parcel
unsuitable for septic or basements)
[0.7; 0.75
0.7)
[0.9; 1.0)
1.0
[1.1; 1.2)
1.25 [1.3; 1.4) 1.5 [1.5; 1.6) 1.75[1.8; 1.8)
Distance to water (miles)
2005 parcels
[2.0; 2.1]
2.0
1953 parcels
Figure 3. Over 50% of all parcels are within a ¼ mile of water. This histogram shows
that water influences parcelization out to a ½ mile. After that, the number of parcels
level out.
•
•
•
•
Proximity to water
Travel time to Madison
View to water
Hydric soils / soil limitations
Infrastructure
[0.4;0.5
0.5)
th
er
[0.2;
0.250.3)
O
Figure 5. Weighted overlay amenity index based
on hypothesized push/pull forces (Table 1).
50
Contact:
Dr. Anna Haines ahaines@uwsp.edu
Dan McFarlane
dmcfa072@uwsp.edu
Eric Olson
eolson@uwsp.edu
Center for Land Use Education
(715) 346 - 3783
Slope (mean parcel slope)
Elevation (mean parcel elevation)
100
0
[0.0; 0.1)
Agriculture distance (distance to
agriculture)
Cover (percent of parcel in forest cover)
150
Columbia Co
2005
Some of our hypothesized amenities are dynamic (forest,
roads, services), therefore we will generate the index at
multiple dates (1940, 1968, 2005).
Note: Light green is forested land
White is agricultural
200
Figure 1. Counties participating
in parcelization study. We
included communities
representing WI’s northwood’s
lake region and southern
agricultural district. Three
townships were selected from
each county.
2000
Year
Figure 4. Actual number of parcels for the years 1953-2005, arranged by size class.
Natural Resources
Bayfield Co
Figure 2b. 2005 parcelization
pattern in the Township of
West Point. Subdivision has
occurred along much of the
Wisconsin River. Clusters of
small parcels away from water
also exist.
# of parcels
• Create a spatial record of historical parcel and land
use layers to establish baseline trends of parcelization
and fragmentation in two non-metro WI counties
• Use past spatial and temporal parcelization patterns to
identify key factors driving rural land subdivision
• Apply additive/weighted overlay amenity index to help
forecast future land parcelization
• Measure significance of each variable using spatial
autocorrelation analysis
• Identify likely prime candidates (parcels) that will
subdivide in the future
• Explore new rules for zoning and subdivision policy
• Provide community outreach on our research findings
Policy Implications:
http://www.uwsp.edu/cnr/landcenter/landcenter.html
Sewer/Water
Electricity
Travel time (travel time to Madison)
Road distance (distance to road)
Parent size (size of parent parcel at
beginning of time period)
Table 1. A list of variables for
generating amenity index. Historic
data was built using archived aerial
photos and public consultation.
Integrating landscape amenities with historic parcelization
trends to better target landscape conservation efforts
CONTRACT/GRANT/AGREEMENT NO: 2005-35401-15924
PROPOSAL NO: 2005-01393