1. Building a Land Development Suitability Model to be
Deployed as a Customizable Web Application
Eli Smith, University of Maryland College Park
Introduction & Background
• Working in Land Development always calls for new
potential residential development properties to be
identified.
• Opportunities to spend time conducting GIS based
suitability analysis to identify potential
development properties are seldom.
• Rodgers Consulting Methodology Committees are
internal work groups tasked to use individual
expertise to improve business efficiency and
decision making. A new GIS committee has been
established and I am the chair of the committee.
• A previous marketing committee project assembled
a foam core map with tacks stuck in it identifying
potential development land parcels.
• “Propertunities” was a prior committee project. It
was technically a GIS but was more of a database of
information on previously identified target sites but
did not involve suitability analysis.
• Land Parcel data availability has increased in recent
years helping to make projects of this type possible.
• Suitability Models are an effective way of taking a
large amount of data selecting a small group of
features which posses desired attributes.
• This project is unique because it will deliver
tangible legal land parcels as an output while many
suitability studies deliver more of a surface of hot
and cold spots.
Literature Review
• There is abundant useful research on land
development suitability.
• Land Planning industry time constrains were noted
as a impediment to GIS based suitability analysis.
(Joerin, et al. 2001)
• Use of AHP (Analytical Hierarchical Process), or
weighting of data input attributes ,was noted in
multiple studies.
• Land Suitability GIS Application can become overly
complex. (Klosterman 1998)
• Overall suitability model success was a resounding
theme with most of the studies.
Objectives
• Collect desired input parameters based on
literature review and input from managers.
• Obtain necessary data from trustworthy and high
quality sources.
• Use geoprocessing and other data processing
techniques to prepare suitability parcel data file
possessing data on percentage of forest cover,
average aspect, distance to highway, and overall
suitability score for each parcel in the file.
• Create web application with built in query tool to
allow for user interaction.
• Allow user to further narrow selection of suitability
parcels for output and export of data file.
Study Area
• Frederick County, Maryland. (see Figure 2)
• More undeveloped land is available as compared to
Montgomery where Rodgers Consulting also works.
• More development friendly political landscape as
compared to Montgomery County.
• Reasonable proximity to multiple job markets ie.
Washington, D.C., Baltimore, City of Frederick.
• Focusing on one County to minimize amount of land
parcels and eliminates dealing with differing types
of planning and zoning conventions.
Data Sources
• Frederick County GIS Department: Click for Website
• Land Parcels, Zoning, Forest Cover
• State of Maryland GIS Department: Click for Website
• Maryland Highways
• USGS National Elevation Dataset: Click for Website
• Blanket DEM/DTM
Methods and Design
• Data Preprocessing
• Clip DEM and process aspect using “Clip” and
“Aspect” ArcMap tools.
• Intersect forest cover with parcels using “Tabulate
Intersection” tool then tabular join to join output to
parcels file. Eliminate parcels over 50% forested.
• Reclassify aspect using “Reclass” tool to score south
facing parcels highest and north facing lowest.
Intersect reclassified aspect with Parcels using
spatial join. Eliminate parcels more than 90 degrees
from south facing.
• Calculate distance to closest state or interstate
highway using “Near” tool, eliminate parcels more
than 5 miles from highway.
• Invert forest cover and distance to highway values
by an exponent on -1 using “Field Calculator” tool in
ArcMap attribute table.
• Add forest cover, aspect and highway distance
scores to calculate overall suitability score.
• Web Application
• Publish suitability parcel file as a root ArcGIS web
service dynamic layer.
• Develop Microsoft ArcGIS API for Silverlight web
application calling in suitability file web service.
• Define custom data query to take input of parcel
acreage between user defined values and user
chosen zoning type from dropdown menu.
Results and Discussion
• Data processing took parcel data set from over 80,000
parcels to just over 5,000 parcels which met acceptable
ranges of model parameter values.
• Parcels data set has been attributed with abundant
useful information and can be further built upon if
additional data attribution is desired in the future.
• Successful web application allows user to query
suitability parcel data set to select parcels within the
acreage range and zoning type they desire.
• Hot spot analysis shows clear clustering of highly
suitable land development parcels within the overall
data set of suitability parcels.
• Further work will involve incorporating water and sewer
planning classification into the suitability score.
(1) Data Input Layers
Works Cited
*Mohamed A. AL-SHALABI, Shattri Bin Mansor, Nordin Bin Ahmed, Rashid Shiriff (2006) GIS Based Multicriteria
Approaches to Housing Site Suitability Assessment, TS 72 – GIS Applications – Planning Issues, Shaping the Change, XXIII
FIG Congress, Munich, Germany, October 8-13, 2006
*Florent Joerin , Marius Thériault & Andre Musy (2001) Using GIS and outranking multicriteria analysis for land-use
suitability assessment, International Journal of Geographical Information Science, 15:2, 153-174
*Guillermo A. Mendoza (undated) A GIS-Based Multicriteria Approaches To Land Use Suitability Assessment And
Allocation, the International Arid Lands Consortium through a cooperative Agreement between the University of Illinois
and the University of Arizona
*Richard E. Klosterman (1999), The What if? Collaborative Support System, Environment and Planning, B: Planning and
Design, 26 (1999), 393-408
*Khwanruthai Bunruamkaewa, Yuji Murayamaa (2011) Site Suitability Evaluation for Ecotourism Using GIS & AHP: A
Case Study of Surat Thani Province, Thailand, Procedia Social and Behavioral Sciences 21 (2011) 269–278
(3) Overall
Model
Flowchart
(2) Study
Area
(6) Web Application Screenshot
(4) Processed Data Layers
(5) Hot Spot Analysis Link to Application