Decoding the Impacts of Space and Time on Honey Bees: GIS Based Fuzzy AHP and Fuzzy Overlay to Assess Land Suitability for Apiary Sites in Queensland, Australia

Published: 27 February 2023| Version 1 | DOI: 10.17632/wctk2nth2g.1
Sarasie Tennakoon,
Richard Dein Altarez


The aim of this study was to map and assess the suitability of an area for beekeeping with respect to spatial and temporal variations in melliferous floral resources and other biophysical factors using GIS based fuzzy AHP and fuzzy overlay. Eleven criteria including regional ecosystems, land cover, land use, slope, aspect, elevation, distance to water, distance to roads, rainfall, temperature, and solar radiation were used. Regional ecosystem, land use and distance to roads maps were downloaded from Queensland Spatial Catalogue: Queensland Government ( while land cover map was obtained from Esri Land Cover – ArcGIS Living Atlas of the World ( GEODATA 9 Second Digital Elevation Model (DEM-9S) Version 3, Geoscience Australia ( was the source of DEM data whereas slope and aspect were derived from the DEM layer. Distance to water map was created using Drainage, GEODATA TOPO2.5M from the Geoscience Australia ( and the climate data (temperature, solar radiation and rainfall) were downloaded from New South Wales (NSW) and Australian Capital Territory (ACT) Regional Climate Modelling (NARCliM) (Hutchinson & Xu, 2015). All the maps were resampled to 25x25 and projected to GDA2020 MGA Zone 56. Fuzzy AHP calculations are provided in excel sheets. Final maps were generated using fuzzy overlay and fuzzy AHP seperately.


Steps to reproduce

Data sources are mentioned in the article and above. The initial vector/raster layers were processed using ArcGIS 10.8.1 (resampling, reclassification and projection) Calculated fuzzy AHP weights using Geometric mean method Created fuzzy AHP outputs using weighted overlay in ArcGIS 10.8.1 Applied relevant fuzzy membership function or division function to each layer Created fuzzy overlay outputs using ARCGIS 10.8.1


Geographic Information Systems, Fuzzy Logic, Site Analysis