Performance evaluation of land change simulation models using landscape metrics

Abstract

This study proposes a landscape metrics-based method for model performance evaluation of land change simulation models. To quantify model performance at both landscape and class levels, a set of composition- and configuration-based metrics including number of patches, class area, landscape shape index, mean patch area and mean Euclidean nearest neighbour distance were employed. These landscape metrics provided detailed information on simulation success of a cellular automata-Markov chain (CA-Markov) model standpoint of spatial arrangement of the simulated map versus the corresponding reference layer. As a measure of model simulation success, mean relative error (MRE) of the metrics was calculated. At both landscape and class levels, the MRE values were accounted for 22.73 and 10.2%, respectively, which are further categorised into qualitative measurements of model simulation performance for simple and quick comparison of the results. Findings of the present study depict a hierarchical and multi spatial level assessment of model performance.