Modelling Best Oil Palm Site Planting in Njimom, West-Cameroon: A GIS-Analysis Combining Weighted Linear Combination, Fuzzy Analytical Hierarchy Process and Utility Function

Abstract

Oil Palm (Elaeis guineensis Jacq.) has recorded a boom production the last decades and its main productive zone is inside the tropics that meet the best biophysical conditions. Investors as well as geospatial practitioners are increasingly interested on the best growing and harvesting conditions. So said, the aim of this paper is to select the best oil palm planting site through the best methods combination. The study area is the district of Njimom located in the west-Cameroon, transitional between the equatorial and the climatic zones. In the same GIS environment, the Weighted Linear Combination (WLC) and Fuzzy Analytic Hierarchy Process (FAHP) respectively highlight the subtle differences between capability and suitability, while the Utility Function (UF) helps to assess the consideration of sustainability aspects. The first results consist in eight layers representing natural conditions, that is rainfall, temperatures, sunshine, slope, elevation, soil richness, soil moisture and forest cover, recoded in six classes ranked from 5 to 0 according to the FAO standardised scale. They are crossed using the straightforward method of WLC to give the “Capability layer”. The second results consist in three layers related to the social-economical constraints for production, as built-up area, distance to road and distance to rivers. These layers are recoded in binary with 1 and 0, they are weighted by the FAHP priority vector and membership approach to give the “suitability layer”. Then, the number of occurrences of each aspect of the sustainability is counted in each of the two preceding processes to perform the UF. The resulting value, that is 0.542 for the capability process and 0.315 for the suitability process, serves to weight their respective layers, and their sum gives the final map with the best oil palm site planting in the northern part of the study area, on about 34,950 ha, representing 44.8% of Njimom district.