Introducing landscape accuracy metric for spatial performance evaluation of land use/land cover change models

Abstract

Performance evaluation is a critical step for land use/land cover (LULC) change modelling. It can be conducted through pixel quantity and its geographical location according to majority of current approaches. It is hence important to know to what extent spatial patterns of a given landscape are properly replicated in simulated LULC maps. Therefore, a new validation metric, named as landscape accuracy metric (LAM), is introduced by inspiration from landscape ecology. Unlike pixel quantity validation metrics, model performance is measured by LAM through quantifying spatial patterns including structure, composition and configuration attributes. The functionality of LAM was studied to assess the performance of the built-up change simulation under historical, ecological and stochastic scenarios, applying Cellular Automata Markov model. LAM is a flexible measure such that modellers can apply this metric through adding or eliminating various metrics of their interest in a selective manner and under different environmental circumstances.