Enhancing the interpretability of a GIS method with ordered weighted averaging (GIS-OWA): A case study on ecological constraints on urban sprawl

However, the GIS-OWA algorithm still lacks effective indicators to assist evaluators in judging which key inputs affect decision-making scenarios at specific spatial scales.

We thus propose location contribution (LOCC) and attribute contribution (ATTRC) to explore the interpretability of the GIS-OWA algorithm at the pixel-to-local scale. Taking the fast developing Golden Triangle urban agglomeration of Southern Fujian Province of China as the study area, the new approach identifies the contribution of ecological factors from GIS-OWA-based ecological constraints. Results show that the aggregation phenomenon of ecological factors in the OWA-ranked layers provides a novel perspective for interpreting the principle of spatial heterogeneity discussed by Anselin and Goodchild.