Evaluation of coffee ecological adaptability using Fuzzy, AHP, and GIS in Yunnan Province, China

Comprehensive regionalization of fine farming could provide scientific evidence for the programming and distribution of coffee farming industry. Comprehensively considering three factors influencing coffee cultivation such as climate, topography, and soil, 11 evaluation indexes for ecological adaptability were chosen. Ecological factors were transformed to 0–1 by fuzzy membership function. The weighing coefficients of different factors were confirmed by Analytic hierarchy process. Ordinary Kriging interpolation and inverse distance-weighted interpolation in ArcGIS were used. Raster calculator was used for overlay analysis. Thus, the evaluation model of the comprehensive regionalization of coffee farming was established. There were four grades of coffee farming area in Yunnan Province, China by natural discontinuity point method breaks, including the most suitable, the suitable, the less suitable, and the not suitable. Results showed that the lowest average temperature in the coldest month and the altitude had the largest influence on coffee adaptability. Areas of four grades of Coffea arabica accounted for 16.28%, 23.19%, 28.71%, and 31.82% of the total area, respectively, wherein the most suitable area and the suitable area were mainly distributed in areas of Baoshan, Dehong, Puer, Lincang, Yuxi, Xishuangbanna, Honghe, Wenshan, etc. Areas of four grades of Coffea canephora accounted for 2.21%, 21.70%, 36.79%, and 39.30% of the total area, respectively, wherein the most suitable area and the suitable area were mainly distributed in areas of Xishuangbanna, Honghe, Puer, Dehong, Lincang, Wenshan, etc. Results could provide theoretical evidence of spatial planning and risk management of coffee production in Yunnan Province, China.