Transcript Washington State Parcel Data User Survey Results Luke Rogers Rural Technology Initiative College of Forest Resources University of Washington Seattle, WA.

Washington State Parcel Data User
Survey Results
Luke Rogers
Rural Technology Initiative
College of Forest Resources
University of Washington
Seattle, WA
Intent
• Qualify and understand the need for
parcel data
• Quantify current efforts by state, private
and federal organizations
• Assess the interest in a statewide parcel
database
• Build interest in a statewide parcel
database effort
ESRI UC Paper #1472, August 2006
Methodology
• Construct survey to collect quantifiable
data and anecdotal observations about
parcel data use
• Focus on state and federal agency use but
also solicit local government and private
organizations where possible
• Sent e-mail solicitations to UW-GIS,
WAGIC, FMG and CPS-GIS lists
ESRI UC Paper #1472, August 2006
Respondents
• 43 responses
representing:




12 state agencies
5 federal agencies
8 local agencies
8 private
Which of the following best
describes your organization type?
%
#
Answer
5 11.90%
Private
5 11.90%
City
2 4.76%
County
16 38.10%
State
8 19.05%
Federal
2 4.76%
Educational Institution
2 4.76%
Not for profit 501(c)(3)
2 4.76%
Other public
ESRI UC Paper #1472, August 2006
Response Types
Are you responding for multiple users in your organization/group or are users responding
individually?
Total responses (N): 36
Answer
I am responding as an individual in my organization
I am responding for multiple users in my organization
Frequency
16
20
Percentage
44.44%
55.56%
ESRI UC Paper #1472, August 2006
What software is most used?
What is the primary software your organization uses to
work with county parcel data?
Total responses (N): 36
Answer
Frequency
Percentage
29
80.56%
ESRI ArcGIS Desktop
6
16.67%
ESRI ArcInfo Workstation
0
0.00%
Autodesk AutoCAD
0
0.00%
ESRI ArcGIS 3.x
0
0.00%
MapInfo
0
0.00%
Microsoft Access
0
0.00%
Grass
1
2.78%
Other:
ESRI UC Paper #1472, August 2006
Reasons for parcel data use
• Most respondents had
multiple reasons for
collecting parcel data
• Land ownership is
clearly the most
motivating reason for
collecting parcel data
Why collect parcel data?
Answer
land ownership
analysis/research/monitoring/modeling
land use planning/change
mailing lists/owner contact
activity tracking/compliance/permitting
property value/taxes
city annexations
geocoding
legislative reporting
real estate concerns
risk assessment
conservation
guide field surveys
boundary delineation
georeferencing
critical areas
restoration
Frequency
15
6
5
5
5
5
3
3
3
3
3
2
2
2
1
1
1
ESRI UC Paper #1472, August 2006
Public agency rationale
• If you represent a
public agency, is
there a law or
mandate that
provides the rationale
for parcel collection or
use?
Is there a law or mandate for
data collection?
Total responses (N): 36
Answer
Yes
No
Not Directly
Frequency
21
6
2
ESRI UC Paper #1472, August 2006
Comments about reasons why
organizations collect parcel data
• Increased accuracy
• Decreased time associated with projects or
ongoing initiatives
• Corresponding decreased cost
ESRI UC Paper #1472, August 2006
How is parcel data collected?
How do you collect parcel data? Check all that apply.
Total responses (N): 41
Answer
Frequency
Percentage
Directly from the county assessor or GIS department
35
85.37%
Download from county website (FTP or HTTP)
34
82.93%
From a hired contractor
8
19.51%
Purchased from a consultant or commercial business
3
7.32%
12
29.27%
Other:
ESRI UC Paper #1472, August 2006
For what geographic extent is
parcel data needed?
• Geographic extent
varies widely among
respondents
• Many have project
specific needs which
range from subcounty to the entire
state
For what geographic extent is parcel data
needed?
Answer
Frequency
Washington State
26
Single county / sub county
9
Puget Sound
4
Forestlands
3
Western Washington
2
USFS land and neighbors
1
Southwest Washington
1
Eastern Washington
1
ESRI UC Paper #1472, August 2006
License agreements & Data
sharing agreements
• State and local agencies tend to have a
low percentage of license agreements
• Private companies tend to have a high
percentage of license agreements
• Federal agencies have almost no license
agreements or are not aware if they do
• Very few entities have data sharing
agreements. The disparity among users
may suggest proactive behavior.
ESRI UC Paper #1472, August 2006
How many counties do people
have data for?
• Again responses vary
widely having to do
mainly with project
specific work vs. ongoing
initiatives
• Some have attribute data
only and others have
linework only
Responses
Mean
Median
Mode
Min
Max
StDev
39
11.7
7
1
0
39
11.4
ESRI UC Paper #1472, August 2006
How many prohibit the sharing or
re-distribution of parcel data?
• No clear trend or
differential between
public/private.
Responses
35
Mean
30%
Median
0%
Mode
0%
Min
0%
Max
100%
StDev
40%
ESRI UC Paper #1472, August 2006
In what geographic data formats
do you receive data?
In what geographic data formats do you receive data from
parcel data providers? Check all that apply.
Total responses (N): 41
Answer
Shapefile
Frequency Percentage
38
92.68%
ESRI Coverage
21
51.22%
ESRI Geodatabase
17
41.46%
ESRI ArcSDE Export file
3
7.32%
AutoCAD
5
12.20%
Other: paper, tabular, web app
7
17.07%
ESRI UC Paper #1472, August 2006
How often does your organization
collect parcel data?
How often does your organization collect parcel data?
Total responses (N): 42
Answer
Frequency
3
Percentage
7.14%
Monthly
6
14.29%
Quarterly
5
11.90%
Annually
9
21.43%
19
45.24%
Weekly
Less than once a year or as needed
ESRI UC Paper #1472, August 2006
Comments about collecting parcel
and assessor data
• Needs tend to be project specific although there
are a few ongoing initiatives
• Many users unsure about license agreements
• Inconvenience of collecting data causes some to
utilize outdated information
• Appears to be a general perception of difficulty
or hassle associated with acquiring and
preparing parcel data
ESRI UC Paper #1472, August 2006
Is parcel feature geometry
important to your organization?
• Other:
Tax assessment
Compliance
Surveys
property lines
road planning
evaluation of forest fire
protection assessment
 identifying land owners at
specified points
 lease rights






If parcel feature geometry is
important to your organization, what
is it used for? Check all that apply.
Total responses (N): 42
Answer
#
%
not important
0
0.00%
37
88.10%
1
95.24%
generating mailing
lists
15
35.71%
geocoding
17
40.48%
7
14.29%
spatial analysis
mapping
Other:
ESRI UC Paper #1472, August 2006
Which assessor attributes are
important?
If assessor attributes are important which ones are used? Check all that apply.
Total responses (N): 40 93% say attributes are important
Answer
Frequency
Percentage
Answer
Frequency
Percentage
parcel ID number
35
87.50%
owner state
27
67.50%
owner name
32
80.00%
owner zip
27
67.50%
landuse
31
77.50%
land value
24
60.00%
site address
30
75.00%
owner country
23
57.50%
zoning
30
75.00%
total value
23
57.50%
parcel acres
30
75.00%
legal description
23
57.50%
site city
29
72.50%
building sq ft
23
57.50%
site zip
29
72.50%
timber acres
19
47.50%
owner address
28
70.00%
residence status
18
45.00%
building value
28
70.00%
Other:
14
35.00%
owner city
27
67.50%
timber expectation value
13
32.50%
ESRI UC Paper #1472, August 2006
Other important assessor
attributes
• mobile home, utility types, septic type, number of housing units,
year built, bedrooms, number of floors, structure type
• sales history, sale price, land and building values from previous
years
• forest fire protection assessment, fire district number, forest
patrol/protection acres
• building permit information if available, such as: permit ID, permit
type, permit issue date, permit completion date, issuing authority
• vacant/undeveloped status, boundary line adjustments, legal
descriptions, plat info, taxing jurisdictions, township-range-sectqtrsect, document numbers, water well number, special restrictions
on property, land type, site city (legal city), tax account numbers
ESRI UC Paper #1472, August 2006
How is parcel and assessor data
shared?
• Other ways data is
shared





Librarian
Email
FTP
CD/DVD
SQL Server
How is parcel and assessor data shared in
your organization?
Total responses (N): 43
Answer
Frequency
Percentage
8
18.60%
network file
system
26
60.47%
ArcSDE
11
25.58%
ArcIMS
4
9.30%
Other:
12
27.91%
not shared
ESRI UC Paper #1472, August 2006
Are derivative products created
from parcel data?
Does your organization produce derivative
products from parcel data?
Total responses (N): 43
Answer
yes
no
unknown
Frequency
29
Percentage
67.44%
10
23.26%
4
9.30%
ESRI UC Paper #1472, August 2006
Examples of derivative products
• impervious surfaces, land use, risk models and
assessments, planning priorities, build out
scenarios, developments, population estimates,
housing density
• conservation, suspected septic systems, habitat
improvement opportunities
• real estate classification/prospects, economic
development
• annexations, forestlands, crime analyses,
election maps, fire risk
• normalized statewide parcel database
ESRI UC Paper #1472, August 2006
Are derivative products publicly
available?
If your organization does produce products from parcel data are they
currently available outside your organization?
Total responses (N): 43
Answer
Frequency
14
Percentage
32.56%
no
19
44.19%
unknown
10
23.26%
yes
If derivative products are not publicly available, could they be made
available to the counties that provide parcel data?
Total responses (N): 32
Answer
yes
no
Frequency
28
4
Percentage
87.50%
ESRI UC Paper12.50%
#1472, August 2006
What prohibits organizations from
sharing products with counties?
If no, then what is prohibiting your organization from sharing the information back with
the counties? Check all that apply.
Total responses (N): 13
Answer
Frequency
Percentage
Lack of interest from the counties
4
30.77%
Legal issues
4
30.77%
Liability
4
30.77%
Metadata not completed, irresponsible to share
8
61.54%
Other:
7
53.85%
• Other: network security, incomplete products,
no mechanism to share/distribute, restrictive
license agreements, confidentiality, staff
resources, business advantage
ESRI UC Paper #1472, August 2006
Comments about the way parcel
data is used or shared
• Project specific data rarely shared due to
privacy/completeness/interest
• Map products may be shared but the underlying
data is not
• General suggestions that sharing is good and
should be encouraged but time/money, privacy
and liability are concerns
ESRI UC Paper #1472, August 2006
Cost estimates
Acquisition
Responses
Preparation Management
27
23
Mean
$ 10,937
$ 16,363
$
6,486
Median
$
$
4,800
$
1,000
Mode
$
-
$
1,000
$
-
Min
$
-
$
$
-
Max
$ 160,000
$ 180,000
$
60,000
StDev
$ 32,178
$ 38,281
$
14,996
1,500
-
23
ESRI UC Paper #1472, August 2006
Value of parcel and assessor data
to organizations
• Agencies tasked with legislative or legal
mandates view the data as critical and many
state it would not be possible to do their jobs
without it.
• General perception of efficiency and improved
accuracy
• “The associated value is intangible in that it is
both hard to value and invaluable.“
ESRI UC Paper #1472, August 2006
Assuming it met your needs and
was available for your use, what
dollar value would you place on an
integrated, normalized statewide
parcel database with a limited set
of assessor attributes?
Value if Available
Responses
25
Mean
$
25,258
Median
$
1,700
Mode
$
Min
Max
StDev
500
$
-
$
500,000
$
99,526
ESRI UC Paper #1472, August 2006
If an integrated database was
available for your use, how often
would updates be desired?
If an integrated, normalized statewide parcel database was
available for your use, how often would updates be desired?
Total responses (N): 41
Answer
Frequency
4
Percentage
9.76%
6
14.63%
Quarterly
17
41.46%
Annually
13
31.71%
4
9.76%
Weekly
Monthly
Other:
ESRI UC Paper #1472, August 2006
Any additional comments about
the costs of parcel data collection?
• Many organizations have no funds to acquire or
manage parcel data
• Many organizations acquire data infrequently
due to costs and hassle. Would get updates
more often if it was convenient.
• Consistency among counties desired
ESRI UC Paper #1472, August 2006
Additional comments
• Concern that a statewide database would
be large
 Desire to be able to acquire regions or subcounty areas
• Majority of respondents see value in
statewide database
• Some confusion with cost data expressed
ESRI UC Paper #1472, August 2006
Next steps
• Summarizing survey results into a brief
document
• Constructing a survey of county data
producers
• Drafting possible data standard
• Drafting a catch-all pass-thru license
agreement
ESRI UC Paper #1472, August 2006