Using GIS to Incorporate the Spatial Dimensions of Nature and

Human Interaction Brent Read

Dept. of Forest, Rangeland and Watershed Stewardship

Colorado State University

Introduction

• Study of interactions between humans and aquatic species.

• Factors influencing where people will go for aquatic recreation.

• Methods for creating a cost surface model.

• Results (to date).

• Conclusions.

Factors influencing where people will go for aquatic recreation.

• Time

• Monetary Costs

• Origin/Destination

Factors influencing where people will go for aquatic recreation.

• Time– The single most important factor in

determining an individuals choice of destination (Juliao, 1999 and Bateman, Lovett & Brainard, 1999).

– Time spent in travel vs. time spent at the site.– Types if travelers: (Chesire and Stabler 1976)

• ‘Pure Visitor’• ‘Transit Visitor’• ‘Meanderer’

Factors influencing where people will go for aquatic recreation.

• Money– Travel Expenses: Gas

Consumption/Tollbooths– Fees– Permits

Factors influencing where people will go for aquatic recreation.

• Origin– 57.4% of visitors travel from San Juan.– 30.7% of visitors travel from rural areas near

the forest.– 11.9% of visitors travel from “Other” areas.

(Kartchner 2002)

Factors influencing where people will go for aquatic recreation.

• Destination (Nodes)– Site Characteristics

• Established Picnic Facilities• Waterfalls• Pools• Flora/Fauna• Vistas• Congestion• Regulations

Creating a Time Surface Model

1. Roads were attributed according to road classification.

2. They were then attributed according to travel speed.

Route Name/Classification Travel Speed (MPH)

Hwy 2 65.00

Hwy 3 50.00

Hwy 22 65.00

Hwy 52 65.00

Hwy 53 60.00

Route 185 40.00

Route 191 35.00

Big Tree Trail 1.05

La Mina Trail 1.12

Caimitillo Trail 0.69

El Yunque Trail 1.07

Mount Britton Trail 1.20

Bano de Oro Trail 0.90

Primary (other) 60.00

Secondary (other) 24.70

Tertiary 20.00

Class 4 15.00

Creating a Time Surface Model

3. Values were calculated for conversion to raster.

4. Preliminary testing of the model was done, comparing results to data from www.mapblast.com

10344.1609

60

TS

PCCT

344.1609

60

TS

PCCT

Where:CCT – Cell Crossing TimeP – Pixel Size (meters)TS – Traveling Speed

(MPH)

44.16093

60

TS

PCCT

Juliao (1999)

Results (To Date)

• GIS Travel Time Model predicts 76% of the visitors’ responses up to 60 minutes.

• GIS Travel Time Model predicts 57% of the visitors’ responses up to 120 minutes.

• GIS Monetary Cost Model predicts 26% of the visitors’ responses.

Time Model Mean S.E. Mean

St. Dev

Min Median

Max R2

Up to 60 minutes

Visitors' estimates 35.0 1.4 18.2 5 40 60

GIS calculation 25.4 0.8 10.8 6.1 24.6 50.5 0.76

Up to 120 minutes

Visitor's estimates 44.1 2.4 33.3 5 40 180

GIS calculation 26.6 0.86 11.7 6.1 25.2 68.4 0.57

Expense Model

Visitors' estimates 2.9 0.2 2.3 0 2.5 17.5

GIS calculations 4.8 0.2 2.2 1.2 4.9 10.7 0.26

Results (To Date)

• The GIS Model is significantly predicting the visitors’ responses for travel time.

• The survey location is not significant.• Further testing must be done to determine other

affects (i.e. road classification)

Source DF Type III SS Mean Square F Value P > F

GIS Predicted Time 1 254988.7 254988.7 625.03 < 0.0001

Survey Location 1 1043.4 1043.4 2.56 0.1109

GIS Predicted Time * Survey Location 1 9837.3 9837.3 24.11 < 0.0001

Model Parameters Estimate Standard Error t Value P > |t|

Intercept 2.0 1.5 1.36 0.1737

GIS Predicted Time 1.5 0.1 19.48 < 0.0001

Location (Rio Mameyes) 3.4 2.2 1.60 0.1109

Location (Restaurant) 0.0 . . .

Conclusions

• The GIS Travel Time Model is capable of predicting 76% of visitors travel time, and can be used to predict travel time for other sites.

• The GIS Travel Expense Model poorly predicts travel expenses, and will not be useful ‘as is’ for prediction.

References• Bateman, I.J., A. A. Lovett and J. S. Brainard (1999). Developing a methodology for benefit transfers using geographical information systems:

modelling demand for woodland recreation. Regional Studies 33 (3), 191-205.• Bateman, I. J., G. D. Garrod, J. S. Brainard and A. A. Lovett (1996). Measurement issues in the travel cost method: a geographical information

systems approach. Journal of Agricultural Economics 47 (2), 191-205.• Bateman, I. J., I. H. Langford, R. K. Turner, K. G. Willis and G. D. Garrod (1995). Elicitation and truncation effects in contingent valuation studies.

Ecological Economics 12, 161-179.• Bockstael, N. E., I. E. Strand and W. M. Hanemann (1987). Time and the recreational demand model. American Journal of Agricultural Economics 69

(2), 293-302.• Boyle, K. J. and J. C. Bergstrom (1992). Benefit transfer studies: myths, pragmatism, and idealism. Water Resources Research 28 (3), 657-663.• Cesario, F. J. and J. L. Knetsch (1970). Time bias in recreation benefit estimates. Water Resource Research 6, 700-704.• González-Cabán, A. and J. Loomis (1999). Measuring the economic benefit of maintaining the ecological intergrity of the Río Mameyes in Puerto Rico.

USDA Forest Service Research Paper PSW-RP-240.• Juliao, R. P. (1999). Measuring accessibility using GIS. Proceedings of Geocomputation ’99.• Kartchner, S. C. (2002). Recreational use of montane streams of the Puerto Rican rainforest. Department of Forestry, Utah State University.• Knetsch, J. L. (1963). Outdoor recreation demands and benefits. Land Economics 39 (4), 387-396• Maidment, D, R. (2002). Arc hydro: GIS for water resources. Redlands, California: ESRI Press.• Walsh, R. G., D. M. Johnson and J. R. McKean (1989) Issues in nonmarket valuation and policy application: a retrospective glance. Western Journal of

Agricultural Economics 14 (1), 178-188• Departamento de Transportacíon Y Obras Públicas (DTOP). http://www.dtop.gov.pr (Nov. 18, 2003)• Department of Natural and Environmental Resources (DNER). “Río Fajardo at Fajardo, Puerto Rico Cap Section 205 Flood Control Study.” (1996)

http://www.saj.usace.army.mil/dp/puerto_rico/projects/rio_fajardo.htm (Sept. 26, 2003)• Department of the Interior (DOI), U.S. Geological Survey (USGS), National Mapping Division. “Standards for Digital Line Graphs” (Sept. 9, 1999)• http://rockyweb.cr.usgs.gov/nmpstds/dlgstds.html (Jan. 19, 2004)• Mapblast. www.mapblast.com (Nov. 18, 2003)• Mastrantonio, J. L. and J. K. Francis. “A Student guide to Tropical Forest Conservation.” USDA Forest Service International Programs (2000)• http://www.fs.fed.us/global/lzone/student/tropical (Oct. 28, 2002)• USDA Forest Service (USDAFS) – Southern Region, Caribbean National Forest http://www.southernregion.fs.fed.us/caribbean/ (Sept. 05, 2003)• Ramírez, A. “Streams in the Luquillo Mountains.” Luquillo Experimental Forest http://luq.lternet.edu/research/projects/streams_description.html (Oct.

28, 2002)• Luquillo Experimental Forest http://luq.lternet.edu (Oct. 28, 2002)• Gould, W. A., (Resident of Puerto Rico), Communicated via Email Nov. 3, 2003)• Wunderle, J. M. (Resident of Puerto Rico), Communicated via Email Oct. 27, 2003