1 Spatial Analysis of Recreation Opportunity Spectrum and Travel/Tourism-Generated Revenues: A Case...
-
Upload
harvey-snow -
Category
Documents
-
view
216 -
download
0
Transcript of 1 Spatial Analysis of Recreation Opportunity Spectrum and Travel/Tourism-Generated Revenues: A Case...
1
Spatial Analysis of Recreation Opportunity Spectrum and Travel/Tourism-Generated
Revenues: A Case of West Virginia
Ishwar Dhami Division of Resource Management
Jinyang DengRecreation, Parks, and Tourism Resources Program
West Virginia University
Introduction
• Recreation Opportunity Spectrum (ROS) is a planning
framework developed in late 1970’s (Clark and Stankey
1979).
• The objective of ROS is to help managers to identify, classify,
and manage supply of recreational opportunities in an area.
• Preferred setting, preferred activities, preferred experience.
2
Introduction• Three settings
3
Setting Component
Physical Remoteness
Size
Evidence of humans
Social User density
Managerial Managerial regimentation and noticeability
Introduction-Physical SettingRemoteness Size Structures
Primitive >3 mi from all roads 5000 acres None
Semi-primitive Non-motorized
<3 mi from all roads and > ½ mile from unimproved roads
2500 acres Minimal
Semi-primitive motorized
<½ mile from unimproved roads > ½ mile from improved roads
2500 acres Minimal
Roaded Natural < ½ mile from improved roads
None Scattered (Public ownership)
Rural < ½ mile from improved roads
None Readily apparent (Private Ownership)
Urban < ½ mile from improved roads
None Dominant (Developed areas)
4
Source: Pierskalla et al., 2009
Rationale• Recreational resources: a major pulling factor to promote
the tourism industry.
• Assumed to be the most important assets for development
in rural areas (Baehler,1995; Snepenger et al., 1995).
• Rural areas with more natural and artificial resources
experience higher rates of economic growth (McGranahan,
1999; Deller et al., 2001)
5
Methods-Data and Software
Travel spending 2010 Dean Runyan Associates (2010)
Software: ArcGIS, Geoda
Data Source
Roads U.S census 2010 TIGER/Line 2012
Land ownership U.S Geological Survey 2012
Developed areas U.S Census 2010
6
7
Methods- GIS Modeling
8
9
10
Methods-Spatial Autocorrelation• Global spatial autocorrelation (Moran’s I) was calculated to
determine the clustering of ROS classes.
• Local Indicators of Spatial Association (LISA) was used to
examine the spatial distribution of clustered variables.
11
Methods-Spatial Regression• The relationship between travel spending and the ROS
classes was first estimated using Ordinary Least Square
(OLS).
• Lagrange multiplier (LM) diagnostics on the OLS for the
spatial lag dependence or the spatial error dependence
were used to determine spatial dependency.
12
13
Results -ROS Adjusted for Remoteness
14
Results -ROS Adjusted for Size
15
Results- Evidence of human/structures
16
Results- Final ROS
Class %
SPNM 2.5
SPM 7.2
RN 7.1
R 79.8%
U 3.3
Results- ROS for Pocahontas County
Class %
SPNM 11.8
SPM 13.6
RN 36.5
R 37.7
U 0.4
17
Variables
Moran’s I value P-value
Travel spending (2010) 0.01 0.25
SPNM0.34 0.00
SPM0.52 0.00
RN0.50 0.00
R0.41 0.00
U0.01 0.23
18
Results- spatial autocorrelation
Results- LISA Cluster Map
SPNM
19
Results- LISA Cluster Map
SPM
20
RN
21
Results- LISA Cluster Map
Rural
22
Results- LISA Cluster Map
Results- OLS model
Variables Coefficient P-value
Intercept -6.98* 0.06
SPNM 4.69 0.84
SPM 3.78 0.76
RN 0.78 0.92
R 0.29 0.91
U 13.89*** 0.00
F-value 3.13 0.01
Adjusted R square
Moran’s I
Lagrange Multiplier (lag)
Lagrange Multiplier (error)
0.24
0.76
0.04 0.06
0.44
0.850.81
23
Discussion and Conclusion• Most of the areas in West Virginia are Rural, followed by SPNM
and RN.
• Hot spots for SPNM, SPM and RN are found in the eastern or
central eastern part of state.
• Majority of areas in western part of state (mostly rural) are
suitable for culture based tourism.
• Areas in eastern part of the state are suitable for both nature
and culture based tourism (SPNM, SPM, RN and Rural).
24
Discussion and Conclusion• 5.35% of SPM and 1.10% of SPNM fall under private
ownership.
• Private land ownership can promote different kinds of
recreational activities.
25
• 2.45% of the state could cater to tourists who value
wilderness (SPNM).
• 14.36% of the state could be suitable who value
wilderness and amenities (SPM and RN).
• Areas under Rural (79.8%) are suitable for tourists who
value amenities and accessibility.
Discussion and Conclusion
26
• Regression analysis: Visitors’ travel spending were
significantly associated with the urban class.
• Counties with more of the other ROS classes but less of
the urban areas were found to have less visitors
spending.
Discussion and Conclusion
27
• Information to the visitors on the type of ROS available in the
area.
• Helps to determine the management practice that would
generate certain class.
• Information on existing recreation opportunities to assist
them in making decisions on appropriate land uses.
• Dealing with size of the ROS classes changes in the area
and trend of visitors could provide better planning of tourism.
Discussion and Conclusion
28
Thank You!