Utilization of spatial decision support systems decision-making in dryland agriculture: A Tifton burclover case study

FSAW delineated Wyoming agricultural land into relative ranks for burclover establishment.Defuzzification produced final output map with crisp scores and calculated centroid.Calculated centroid map demonstrated efficacy of SDSS in agricultural decision-making.Effective land suitability ranking validated value of ex-ante agricultural technologies.Presented information has potential to determine burclover feasibility in Wyoming. Integrated Geographic Information Systems (GIS) and spatial decision support systems (SDSS) methods are important for relative ranking of suitability of agricultural land. This case study was conducted at the University of Wyoming in 2007 to demonstrate viability of integrated GIS and SDSS methods as useful ex-ante assessment technologies to help rank relative suitability of Wyoming agricultural land for optimum establishment of Laramie Tifton burclover Medicago rigidula (L.) Allioni in the Central High Plains agricultural region. The study uses fuzzy set logic methods and implements the fuzzy simple additive weighting (FSAW) method through modeling in GIS raster to analyze Wyoming State's agricultural land use, and the identified suitability attributes for optimum burclover establishment; the long-term summer diurnal temperature flux, September-October precipitation, and April-July precipitation. Further, the study uses one of the two categories of multiple criteria decision-making (MCDM) known as multiple attribute decision making (MADM), to combine the range of each attribute's possible suitability values in meaningful ways that allow suitability criteria to be evaluated on the basis of low, medium, and high suitability for optimum burclover establishment. The inverse distance weighting (IDW) interpolation technique interpolated the point shape files of the identified suitability attributes and produced surface maps that allowed characterization of long-term summer diurnal temperature flux and seasonal precipitation for the State of Wyoming. The fuzzy additive weighting and defuzzification methods transformed data from different sources into useful information that can be effectively used to enhance decision making in agriculture. Finally, defuzzification transformed fuzzy scores into useful crisp scores and produced the final output map with calculated centroid. The resulting calculated trapezoidal centroid map with useful crisp scores from transformed disparate fuzzy data demonstrates that spatial suitability analysis can be used effectively to enhance decision making in agricultural planning and management. Likewise, the effective ranking of relative suitability of Wyoming agricultural land for optimum establishment of Laramie Tifton burclover validates the value of using fuzzy set logic and additive weighting approaches for ex-ante assessment of the potential suitability of agricultural technologies.

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