Spatial suitability assessment for vineyard site selection based on fuzzy logic

  • Golnaz Badr
  • Gerrit Hoogenboom
  • Michelle Moyer
  • Markus Keller
  • Richard Rupp
  • Joan Davenport


Developing a sustainable agricultural production system requires knowledge of the climate, soil, and topography of the area of interest. This is especially relevant for wine grape (Vitis vinefera L.) production. The main objective of this study was the development of a comprehensive system to aid in the selection of suitable areas for grapevine cultivation. Included in this system were several bioclimatic indices, such as Growing Degree Days (GDD), Frost Free Days (FFD), and the Huglin Index (HI) calculated over a period of 30 years using daily weather data obtained from the University of Idaho’s Gridded Surface Meteorological (UI GSM) dataset. Soil data and topographical data were also included in the system. The bioclimatic indices, soil, and topographic data were then transformed using fuzzy logic, and suitability maps with scores ranging from 0 to 1 were developed. The final vineyard-potential scores were obtained by combining the soil, weather, and topographic potential scores with a range from 0 to 1, where 0 pertained to non-suitable areas and 1 referred to optimal sites. The maps were evaluated by comparing the range of suitability scores of existing vineyards in Washington State. The evaluation indicated that 97% of the established vineyards have a vineyard-potential score that ranges from 0.8 to 1. The results of this study revealed that 11% of the total study area had a high potential for wine grape production. This study was able to successfully employ fuzzy logic to help decision-makers, growers, and others with conducting a precise land assessment for wine grape production.


Fuzzy logic Spatial suitability analysis Wine grape Vineyard Site selection 



This research was partially supported by Washington State University’s AgWeatherNet Program, the Northwest Center for Small Fruits Research, and an IBM Fellowship awarded to the corresponding author. The authors would like to thank the United States Department of Agriculture Geospatial Gateway website for providing access to the soil and topography datasets and the University of Idaho Gridded Surface Meteorological Data (UofI METDATA) for providing access to the raw weather data that were used in this study.


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Authors and Affiliations

  1. 1.AgWeatherNet ProgramWashington State UniversityProsserUSA
  2. 2.Cornell Lake Erie Research and Extension LabCornell UniversityPortlandUSA
  3. 3.Institute for Sustainable Food Systems, University of FloridaGainesvilleUSA
  4. 4.Department of HorticultureWashington State UniversityProsserUSA
  5. 5.Department of Crop and Soil SciencesWashington State UniversityPullmanUSA
  6. 6.Department of Crop and Soil SciencesWashington State UniversityProsserUSA

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