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Pairwise-Comparison was used as the ranking method which provided accurate weights in determining the ideal site for Niagara Region. Site Selection for.

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Presentation on theme: "Pairwise-Comparison was used as the ranking method which provided accurate weights in determining the ideal site for Niagara Region. Site Selection for."— Presentation transcript:

1 Pairwise-Comparison was used as the ranking method which provided accurate weights in determining the ideal site for Niagara Region. Site Selection for a Soybean Farm in the Niagara Region with Biodiesel Considerations Andrew D. Meyer, Mark P. Chaput, Philip G. Dodds GEOG 3GI3: Advanced Raster GIS 5. Site Recommendation and Cartographic Model 6. Sensitivity Analysis Better quality Digital Elevation Model data. Reducing cell size to improve accuracy and precision of criteria. More efficient Climate data on temperature, rainfall and wind patterns Obtain Land parcel data; more accurate depiction of land use and property cost Winter Data; Snowfall and Frost days more accurately indicate the beginning of the growing season for different areas within the study area The purpose of this project is to locate a new soybean farm within the Niagara Region, Ontario, Canada for Biodiesel manufacturing by GIS raster analysis and multi-criteria decision weighting. 8. Data Sources 7. Project Improvements 4. Criteria and Sensitivity Weighting1. Background Information 2. Objective As the need for oil increases and supply of oil depleting, alternatives must be considered. Among many ideas, Biodiesel is an emerging market which blends soybean oils with petroleum which can then be implemented into the current infrastructure and lower emissions. The soybean’s overall crop yield is determined and influenced by many environmental factors. The Niagara Region is a desirable location for soybean farming due to the relatively flat land surface and suitable soils. 3. Decision Criteria To test the accuracy of the Pair-Wise Comparison results, Rank Reciprocal weighting was calculated. All areas determined to be undesirable were then removed from the selected locations. The overlapping results using different weighting techniques indicates the robust characteristics and accuracy of the cartographic model. Above: Solar Radiation values of the Niagara Region during the average number of days in a growing season. The escarpment is clearly visible as green indicating a steep slope. Left: Study area showing the majority of the optimal soybean land located in the South-Eastern quadrant of the Niagara Region with the highest density directly East of Port Colborne. Bottom: Final Site located at Wilhelm Road and Highway 3, Port Colborne, Ontario, Canada 9. References CriteriaConstraintFactorTool Soil TypeSandy/Gravely SoilN/AReclassify Elevation<=500 metersN/ADEM Slope<=5 DegreesN/ASlope Landuse Urban/Park Features Futher(m)Reclassify Solar Rad>2400 watts/m2Heat Units Area Solar Radiation Precipitation>120 mmPer MonthReclassify Accesibility<10 metersMajor RoadsEuclidean Wind Patterns>2km per hourVelocityReclassify Distributor Distance <50 KmBusiness Euclidean Distance Temperature>5 Degrees CMay-OctoberSpline Water Availability >600mmIrrigationSpline Area>100 Acres 2 Area Greater Than Equal DMTI Route Logistics v2010 Road Network and Accessibility DMTI Enhanced Points of Interest Elevation and Slope Data Agriculture and Agri-Food Canada Soil Survey, Reports and Interpretations Geobase Nation Hydro Network, Land Cover Environment Canada National Climate Data and Information Archive Dorff, E. (2009). The Soybean, Agricultures’ Jack-Of-All-Trades, is Gaining Ground ……..across Canada. Statistics Canada. Retrieved online from: ……..http://www.statcan.gc.ca/ Malczewski, J. (2006). GIS-based multicriteria decision analysis: a survey of the …….literature. International Journal of Geographical Information Science, 20(7), …….703-726 Yao, S., O’Brien, D. (2009) Soybean & Wheat Response to Climate Change. ……..Agricultural Research.57(10), 10-12. VariableRankingNormal WeightRelative WeightRank Reciprocal Soil10.214.7430.261 DEM20.17810.8480.229 Landuse30.1566.8450.171 Water40.1334.9380.125 SolarRAD50.1113.9750.091 Precipitation60.0892.5870.052 Accesibility70.0671.7780.039 Distributors80.0441.2110.021 Wind90.02210.013 SUM 1 1,


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