This report presents the work done to rank the importance of the GIS parameters used in EirWind’s spatial MCDA. This is a crucial step in ensuring transparency in the MCDA’s design. Because the GIS model is modular and its parameters’ weights can be modified, this document also helps guarantee the best possible performance of the model by its various end users. Thus, this work serves as a bridge between the EirWind researchers, the diverse experts who provided input used to inform the MCDA, and the users of the final GIS model. The importance of individual GIS parameters was assessed using Analytical Hierarchy Process (AHP) analyses on a set of nine criteria (the largest set likely to be viable for this type of assessment). AHP is a common technique for deriving scores of importance “weights” for sets of disparate parameters or criteria. For this research, AHP analyses were applied to survey responses from 25 experts in industrial or research positions. AHP results were assessed against more intuitive, general statistics for the same set of criteria. The validity of the AHP responses was assessed using a consistency ratio calculated from the pairwise response matrix of each respondent. When required, AHP responses were adjusted to increase consistency. Results are reported in sets that differentiate the adjusted results from others categorised by internal consistency of the responses. The values from the adjusted set of AHP calculations was deemed the most likely to balance validity and representativeness. These results reveal wind speed (energy) to be the most important criteria, followed by water depth and visual impact. Ocean currents and geological criteria were found to be the least important. The adjusted AHP scores for all criteria are summarised in Figure ES1. The AHP analyses are used to inform weights (i.e. relative importance) of individual GIS parameters that make up a geospatial multi-criteria decision aid (MCDA). The assessments presented in this report suggest that the adjusted AHP values are most correct for this purpose. However, these results are only an attempt to maximise objectivity in an otherwise subjective endeavour. End users of the MCDA are free to assign GIS weights as they see fit and the model has been designed to facilitate this. Thus, results on the ranking of criteria importance are presented from five different assessments in this report.