ABSTRACT Cellular automata (CA) models are in growing use for land-use change simulation and future scenario prediction. It is necessary to conduct model assessment that reports the quality of simulation results and how well the models reproduce reliable spatial patterns. Here, we review 347 CA articles published during 1999–2018 identified by a Scholar Google search using ‘cellular automata’, ‘land’ and ‘urban’ as keywords. Our review demonstrates that, during the past two decades, 89% of the publications include model assessment related to dataset, procedure and result using more than ten different methods. Among all methods, cell-by-cell comparison and landscape analysis were most frequently applied in the CA model assessment; specifically, overall accuracy and standard Kappa coefficient respectively rank first and second among all metrics. The end-state assessment is often criticized by modelers because it cannot adequately reflect the modeling ability of CA models. We provide five suggestions to the method selection, aiming to offer a background framework for future method choices as well as urging to focus on the assessment of input data and error propagation, procedure, quantitative and spatial change, and the impact of driving factors.

中文翻译：

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土地利用变化与城市增长元胞自动机模型评估方法综述

摘要 元胞自动机 (CA) 模型越来越多地用于土地利用变化模拟和未来情景预测。有必要进行模型评估，报告模拟结果的质量以及模型再现可靠空间模式的程度。在这里，我们回顾了 1999-2018 年发表的 347 篇 CA 文章，这些文章由 Scholar Google 搜索使用“细胞自动机”、“土地”和“城市”作为关键字进行搜索。我们的审查表明，在过去的二十年中，89% 的出版物包括使用十多种不同方法的与数据集、程序和结果相关的模型评估。在所有方法中，逐细胞比较和景观分析最常用于 CA 模型评估；具体来说，总体准确率和标准 Kappa 系数在所有指标中分别排名第一和第二。最终状态评估经常受到建模者的批评，因为它不能充分反映 CA 模型的建模能力。我们对方法选择提出五点建议，旨在为未来方法选择提供背景框架，并敦促重点评估输入数据和错误传播、程序、数量和空间变化以及驱动因素的影响。