Peter John LaPlaca
Nature Park Site Analysis in Fairfax County Virginia
Using the ArcView Spatial Analyst Extension
Abstract
Fairfax County, Virginia is experiencing rapid population growth
due to its proximity to Washington D.C. As more and more communities
develop in the county, it will be important to provide open space
for leisure and recreational activities. This paper explores using
the ArcView Spatial Analyst Extension to locate a new nature park
in Fairfax County. The Spatial Analyst Extension provides the
GIS analyst with powerful raster GIS processing that, until recently,
was only available with the ArcInfo GRID module.
Using what is known as suitability modeling , cost grids were
created based on the physical and human made parameters that people
find most attractive in a nature park. Suitability modeling transforms
raw data measurements such as elevation into numeric values (1-10)
that can be combined mathematically using map algebra expressions.
The result was a series of grids containing the same range of
values, resulting in an apples-to-apples comparison as opposed
to an apples-to-oranges comparison. A final cost grid was derived
that identified several areas for a new park.
Introduction
The purpose of this project, an outgrowth of some Ph.D. coursework,
was two-fold: to locate a new Nature park in Fairfax County using
raster GIS modeling, and to determine the robustness and ease-of-use
of grid processing using the Spatial Analyst Extension in comparison
to using ArcInfo GRID. All the work was done using ArcView with
the Spatial Analyst Extension under the Windows NT operating system.
Raster GIS is a software tool that can display, query, analyze,
and output geospatial information. The structure of a raster GIS
is based on a grid of some assigned resolution. Each grid square
or "cell" contains a numeric value. These values (and
their associated attributes) are stored in a database for easy
query and retrieval. The values may also represent raw reflectance
values, as in the case of satellite imagery, values that represent
certain attributes, such as all values of 1 are equal to "coniferous
forest," or values that represent actual real world physical
phenomenon, such as wind speed or temperature.
The primary use of raster GIS technology is to model discrete
(such as vegetation type, etc.) and/or continuous (such as elevation,
wind, etc.) data on the surface and in the atmosphere. To do this,
raster GIS supports the structure known as map algebra. Map algebra
is a high level language used to characterize cartographic spatial
analysis using gridded data. This high level language can be used
to construct weighted "cost surfaces" for various surface
conditions and atmospheric properties. A model may contain many
sub models or cost grids. These can be combined and manipulated
to determine the optimal location for a nature park.
Since the county has a preponderance of multi-purpose parks that
serve many uses, it was decided to model a "Nature Park".
The park is envisioned to be a place where people can come to
enjoy a natural, quiet setting, away from the near-urban environment
of Northern Virginia life. People may come to such a park to fish,
canoe, bird and animal watch, walk on nature trails, or visit
a nature center.
Study Site
The center of Fairfax County is located approximately fifteen
miles west of Washington D.C. The terrain in the county is somewhat
flat with some rolling land in the western half of the county.
The county is experiencing rapid growth, and can be considered
an urban/near-urban environment.
The primary land covers are urban and residential areas surrounding
the interstate 495 beltway. Urban or near-urban areas in the
county include Fairfax City, Herndon, Reston, Chantilly, Springfield,
and Tysons Corner.
There are several water bodies in the county, notably Lake Anne,
Thoreau, Audubon, Fairfax, Burke, and Accotink. The county is
partially bounded on the south by the Occoquan reservoir and its
watershed and on the north by the Potomac River. The western
half of the county is less densely populated, made up of residential,
forest, and farmland areas.
Modified Delphi Process - Establishing Utility Measures
In order to make the potential park site more realistic and useful
to people, a "Nature Park Survey Form" was circulated
to a sample of thirty five people. These people were asked to
rate the physical and/or human parameters that are most useful
in a nature park. The Delphi Process is a method used to assess
the usefulness of data. This is accomplished by determining utility
and/or setting weights. The results from a modified Delphi survey
of thirty-five people (see Appendix A) were tabulated and are
presented below.
Near Work | Near Home | Near an Interstate | Near an existing park | Near a historic site | Near the metro/bus route | Near a police station | Near a hospital | Near a school | Boating | Fishing | Woods | Water / River / Stream | Water / Lake / Stream | Wetlands/
Marsh | Animals | |
1 | 2 | 10 | 5 | 2 | 6 | 5 | 8 | 3 | 1 | 8 | 1 | 8 | 5 | 8 | 3 | 7 |
2 | 1 | 9 | 1 | 4 | 9 | 2 | 3 | 3 | 8 | 8 | 6 | 10 | 9 | 9 | 6 | 10 |
3 | 1 | 9 | 1 | 6 | 5 | 1 | 4 | 1 | 6 | 8 | 7 | 10 | 10 | 9 | 9 | 8 |
4 | 6 | 6 | 1 | 1 | 3 | 3 | 3 | 4 | 4 | 8 | 8 | 10 | 10 | 10 | 3 | 9 |
5 | 6 | 10 | 4 | 4 | 4 | 9 | 7 | 3 | 9 | 10 | 5 | 10 | 10 | 10 | 9 | 10 |
6 | 1 | 4 | 3 | 6 | 1 | 4 | 2 | 4 | 6 | 7 | 7 | 9 | 10 | 8 | 9 | 10 |
7 | 1 | 8 | 1 | 6 | 7 | 1 | 7 | 7 | 9 | 10 | 10 | 10 | 10 | 8 | 3 | 10 |
8 | 3 | 7 | 1 | 2 | 1 | 2 | 5 | 2 | 1 | 5 | 5 | 10 | 6 | 9 | 4 | 8 |
9 | 1 | 6 | 2 | 1 | 4 | 2 | 2 | 3 | 4 | 6 | 4 | 8 | 9 | 9 | 1 | 9 |
10 | 4 | 6 | 3 | 5 | 6 | 1 | 4 | 2 | 1 | 10 | 10 | 10 | 10 | 10 | 10 | 10 |
11 | 10 | 10 | 1 | 7 | 7 | 1 | 2 | 5 | 3 | 9 | 9 | 10 | 9 | 9 | 9 | 8 |
12 | 3 | 9 | 1 | 1 | 7 | 1 | 3 | 3 | 1 | 10 | 10 | 10 | 10 | 10 | 7 | 10 |
13 | 1 | 10 | 8 | 8 | 9 | 1 | 4 | 5 | 1 | 2 | 7 | 9 | 9 | 9 | 9 | 10 |
14 | 2 | 8 | 2 | 2 | 2 | 2 | 6 | 2 | 8 | 7 | 7 | 7 | 7 | 7 | 2 | 2 |
15 | 6 | 9 | 8 | 1 | 3 | 6 | 6 | 6 | 8 | 6 | 6 | 10 | 10 | 10 | 5 | 9 |
16 | 3 | 8 | 3 | 3 | 6 | 1 | 2 | 2 | 2 | 6 | 9 | 10 | 9 | 10 | 7 | 6 |
17 | 7 | 9 | 4 | 1 | 1 | 7 | 6 | 2 | 1 | 4 | 4 | 5 | 3 | 3 | 3 | 5 |
18 | 1 | 8 | 4 | 7 | 7 | 6 | 6 | 6 | 7 | 10 | 8 | 10 | 10 | 10 | 10 | 10 |
19 | 6 | 10 | 1 | 6 | 4 | 3 | 1 | 1 | 9 | 6 | 6 | 10 | 10 | 10 | 8 | 10 |
20 | 6 | 9 | 6 | 6 | 9 | 6 | 5 | 5 | 5 | 8 | 8 | 9 | 9 | 9 | 9 | 9 |
21 | 1 | 6 | 1 | 6 | 2 | 2 | 1 | 1 | 8 | 9 | 9 | 10 | 10 | 10 | 10 | 10 |
22 | 2 | 9 | 3 | 3 | 6 | 3 | 7 | 4 | 9 | 5 | 5 | 10 | 10 | 10 | 8 | 10 |
23 | 1 | 10 | 6 | 1 | 1 | 1 | 1 | 6 | 8 | 8 | 8 | 8 | 8 | 8 | 6 | 10 |
24 | 6 | 6 | 1 | 1 | 9 | 7 | 10 | 10 | 10 | 1 | 1 | 10 | 10 | 10 | 10 | 10 |
25 | 1 | 10 | 1 | 1 | 7 | 8 | 6 | 4 | 6 | 10 | 10 | 10 | 8 | 6 | 4 | 10 |
26 | 3 | 10 | 1 | 4 | 8 | 6 | 1 | 6 | 8 | 10 | 10 | 10 | 10 | 10 | 10 | 10 |
27 | 2 | 7 | 9 | 5 | 9 | 9 | 9 | 7 | 8 | 6 | 6 | 10 | 7 | 7 | 5 | 9 |
28 | 1 | 4 | 3 | 1 | 5 | 1 | 1 | 1 | 1 | 6 | 1 | 9 | 8 | 8 | 8 | 8 |
29 | 3 | 7 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 10 | 10 | 10 | 10 | 10 | 10 |
30 | 1 | 6 | 1 | 1 | 7 | 3 | 3 | 6 | 1 | 9 | 9 | 10 | 10 | 10 | 9 | 10 |
31 | 6 | 10 | 4 | 6 | 6 | 10 | 1 | 6 | 6 | 3 | 3 | 8 | 6 | 6 | 3 | 3 |
32 | 6 | 10 | 1 | 6 | 1 | 1 | 1 | 1 | 1 | 6 | 6 | 6 | 6 | 6 | 6 | 6 |
33 | 1 | 6 | 1 | 1 | 3 | 8 | 9 | 7 | 1 | 3 | 9 | 9 | 9 | 9 | 3 | 7 |
34 | 4 | 4 | 1 | 8 | 6 | 4 | 4 | 4 | 4 | 9 | 9 | 10 | 10 | 10 | 9 | 10 |
35 | 1 | 10 | 2 | 6 | 6 | 8 | 6 | 7 | 4 | 9 | 3 | 9 | 8 | 9 | 1 | 8 |
Tot | 110 | 280 | 96 | 130 | 178 | 136 | 147 | 140 | 170 | 250 | 236 | 324 | 305 | 306 | 228 | 301 |
Avg | 3.14 | 8.00 | 2.74 | 3.71 | 5.09 | 3.89 | 4.20 | 4.00 | 4.86 | 7.14 | 6.74 | 9.26 | 8.71 | 8.74 | 6.51 | 8.60 |
As one would expect, people seem to agree that woods, animals
(habitat), and water are useful and attractive attributes that
influence selecting a nature park site. This project focused on
aesthetic characteristics to determine a suitable site. Obviously
other attributes like land cost, construction cost, and other
economic factors are important and would be considered in an
actual study.
Data
All of the datasets, with the exception of the USGS DEM elevation
dataset, were initially vector ArcInfo coverages. Most of the
data were derived from county maps at a scale of 1:4000. The elevation
data is a USGS DEM at a scale of 1:250000. All of the data were
converted to GRID format, projected to State Plane, with units
in feet.
Park Site Analysis
Using the results from the nature park survey, cost surfaces,
or preference grids were created to help determine a suitable
park site. A total of thirteen cost grids were combined to create
the final cost-surface. Several requests in the Spatial Analyst
were used. Some of these were Spatial.Distance (same as
Euclidean distance in grid), Spatial.CostDistance, Reclassify,
and Slice. The utility scale of used was 1=worst to 10=best.
Below is a listing of the cost-surface grids along with a brief
description of how they were created.
1. Railroad
Because of noise and safety considerations, the park should not
be within 300 ft. of a railroad. The railroad cost grid was created
by running the Spatial.Distance request. Reclass was run and making
a one mile distance NO DATA, thereby excluding railroads from
the cost surface calculation. The rest of the grid was classified
as a 10, or best.
2. Solid Waste
The park should be at least two miles away from any solid waste
site. This would cut down on any noise or smell. The solid waste
cost grid was created by running Spatial.Distance, and then the
grid was reclassified with a 1 mile area around the solid waste
sites as NO DATA so they would not be considered. Everything else
was coded as a 10.
3. Existing Parks
The "near an existing park" parameter only scored a
2.74 in the survey. Since most people in the survey seem to agree
that they do not want a new park too close to an existing one,
Spatial.Distance was run, followed by reclassing the existing
parks to NO DATA, and classing a half-mile NO DATA buffer around
them. This excluded existing parks and a small half-mile
area around them from being considered. The remaining area was
given a cell value of 10.
4. Police
From the public facility coverage, Police stations in the county
were selected. These were converted to a grid, and Spatial.Distance
was run. After this, the grid was reclassified by distance zones
based partly on survey results. "Near a Police Station"
averaged a score of 4.2 on the survey. Some people felt it was
important that the park be near a police station. The police station
grid was therefore reclassified as 10 = one mile distance from
stations, and 9 = two miles from station, and 6 for the remaining
area.
5. Historic Sites (4 protected points)
For historic sites, the four point locations were converted to
a grid and Spatial.Distance was run. Because two of the points
were "very significant" and two were of "minor
significance," the historic sites grid was reclassified to
create two NO DATA areas two miles and one mile respectively from
these sites. Areas within the 2 and 1 mile area were assigned
NO DATA values so that no parks could be built too close to these
historic sites. Areas outside the 2 and 1 mile cells were coded
a 10.
6. Historic Sites (Already Established)
Existing historic sites were selected from a public facility coverage.
"Near a Historic site" scored a 5.09 on the Delphi survey.
People seem to feel that it is somewhat important to have a new
nature park near an historic site. For that reason, Spatial.Distance
was run against existing historic sites, then reclassified one
mile and 2 mile areas as 10 and 9 respectively. All other grid
cells were coded as 8.
7. Industry (excluded)
Reclassed all industrial areas to NO DATA. Everything else to 10.
We do not want a nature park in an industrial area at all.
8. Street Center Line
Ran Spatial.Distance on the street grid. Then reclassed NO DATA
out to 500 ft to account for housing. Cells greater than 500 feet
were coded 10.
9. Airports and Government Facilities
Reclassed this grid to the following: Airports, Federal government,
and Lorton Prison areas were coded NO DATA. One does not want to build
parks here. Everything else got coded 10.
10. Public Facilities
Ran Spatial.Distance on all public facilities cells (points);
schools, shopping centers, etc. Reclassed NO DATA out to 300 ft.
Everything else coded a 10.
11. Universities
Ran Spatial.Distance on universities selected from the public
facilities grid (George Mason and Northern Virginia Community
College). Reclassed a one and 5 mile area around universities.
Coded 1 mile area 10, 5 mile 9, all other cells 7.
12. Landuse/Landcover
Landuse/landcover was one of the more interesting and important
grids to reclassify. Here's how attributes were coded. Survey
results whenever possible (for example, woods scored a 9.26 on
the survey, so all forest type were coded high).
13. Slope
Slope was created from the USGS DEM and reclassified into the
following:
Slope 1 = 9, 1-2 = 10, 3 = 7, 3-8 = 4, and >8 = 1
Final Park Site Cost Grid
After cost grids were created for these thirteen layers, a final
park cost grid, divided by thirteen, was created using the following
expression in the Map Calculator (see Final Park map)
([Reclass of Distance to Sldwaste] + [Reclass of Exclude Current
Parks] + [Railroad Reclass] + [Police Reclass] + [Historic Sites
(4 given)] + [Historic Sites already established] + [Industry
Excluded] + [Reclass of Distance to street center line] + [Reclass
of Airports and Govt, Facilities] + [Reclass of Distance to Pubfacilities
(300ft.)] + [Reclass of Universities] + [Reclass of Landuse/Landcover]
+ [Reclass of Slope of FCDEM]/13
A map of the final suitable nature park site is shown below.
As an additional experiment, an alternative cost model was also
produced which weighted the preferences by percentage of certain
parameters from the nature park survey form. That cost grid was
divided by fifteen, using the following expression in the Map
Calculator. The sum of the weights must add up to 100%.
([Reclass of Distance to Sldwaste] + [Reclass of Exclude Current
Parks] + [Railroad Reclass] + [Police * .10] + [Historic Sites
(4 given)] + [Historic Sites already established * .20] + [Industry
Excluded] + [Reclass of Distance to street center line] + [Reclass
of Airports and Govt, Facilities] + [Reclass of Distance to Pubfacilities]
+ [Reclass of Universities] + [Landuse/Landcover (Woods) * .30]
+ [Landuse/Landcover (Streams) * .15] + [Slope of FCDEM * .10]
+ [Landuse/Landcover (Lakes) * .15]/15
Conclusion
It is clear from this preliminary project work, that it is possible
to use the ArcView Spatial Analyst Extension as a powerful raster
analytical tool to determine suitable sites for a nature park.
Like any model, better data and methods yields better results.
In an actual study, I would have liked to have good population
information, at the district or even subdivision level. Also,
some of the datasets were out-dated. The land-use cover comes
to mind. Using aerial photo or satellite imagery to update the
landuse/landcover in the county would ensure a more accurate model.
Also, to fully exploit the Delphi process, a facilitator and several
expert(s) would need to be used, instead of me making judgment
calls on the utility of certain types of data.
Overall the approach, however, was well grounded and produced
good results. It is possible and desirable to use the ArcView
Spatial Analyst for park site determination. The power of raster
GIS has come full-circle with the addition of raster GIS processing
in the ArcView desktop environment.
Appendix A
FROM: Pete LaPlaca
TO: ISG Personnel
SUBJECT: Park Site Survey Form
Dear ISG Colleagues:
As part of my Ph.D. course work, I am using the ArcView
3 Spatial Analyst Extension Geographic Information Systems(GIS)
to determine a site for a new "Nature Park" in Fairfax
County. For this study, it is important to determine real world
information as to what people may find attractive in such a park.
For example, you may consider water as an important part of the
park, or lots of trees, or nature trails, etc.
Using what is known as suitability modeling (Delphi
Process), we can create a series of cost grids based on the physical
and human made parameters that people find most attractive in
a Nature Park. Suitability modeling transforms raw data measurements
such as elevation into numeric values (1-10) that can be combined
mathematically using map algebra expressions. The result is a
series of grids containing the same range of values, resulting
in an apples-to-apples comparison as opposed to an apples-to-oranges
comparison. By doing this for example, one can compare a slope
grid with a proximity-to-schools grid in the same geographic space.
Your Mission (should you choose to accept it)
Please take a couple of minutes to rate the following
parameters from 1 to 10, 1=least attractive, 10 = most attractive,
based on your idea of what the ideal Nature Park should be. Thank
you for your help.
For example:
Parameter
Importance
Water/Lake or Pond 9 (you feel it's pretty important
that your nature park have a lake or pond)
Water/River or Stream 4 (you feel that a stream/river
running through the park is not really important)
Your name (optional)_______________________________
Parameter | Importance (1=not important to 10= very important) |
Near work | |
Near home | |
Near an interstate | |
Near an existing park | |
Near a historic site | |
Near the metro/bus route | |
Near a police station | |
Near a hospital | |
Near a school | |
Boating | |
Fishing | |
Woods | |
Water/River/Stream | |
Water/Lake/Stream | |
Wetlands/Marsh | |
Animals(existing habitat - squirrels, deer, birds) |
Peter John LaPlaca
Department Research Analyst
TASC, Inc.
12100 Sunset Hills Road
Reston VA 20190-3233
Tel. (703) 834-5000
Fax. (703) 318-7900
pjlaplaca@tasc.com