Abstract Understanding and modeling of land use change is of great significance to environmental protection and land use planning. The cellular automata-Markov chain (CA-Markov) model is a powerful tool to predict the change of land use, and the prediction accuracy is limited by many factors. To explore the impact of land use and socio-economic factors on the prediction of CA-Markov model on county scale, this paper uses the CA-Markov model to simulate the land use of Anren County in 2016, based on the land use of 1996 and 2006. Then, the correlation between the land use, socio-economic data and the prediction accuracy was analyzed. The results show that Shannon’s evenness index and population density having an important impact on the accuracy of model predictions, negatively correlate with kappa coefficient. The research not only provides a reference for correct use of the model but also helps us to understand the driving mechanism of landscape changes.

中文翻译：

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景观格局及经济因素对县域元胞自动机-马尔可夫链模型预测精度的影响

摘要 土地利用变化的认识和建模对环境保护和土地利用规划具有重要意义。元胞自动机-马尔可夫链（CA-Markov）模型是预测土地利用变化的有力工具，其预测精度受到多种因素的限制。为探讨土地利用和社会经济因素对CA-Markov模型对县域尺度预测的影响，本文在1996年土地利用数据的基础上，采用CA-Markov模型对安仁县2016年土地利用情况进行模拟。和2006年。然后，分析了土地利用、社会经济数据与预测精度之间的相关性。结果表明，香农均匀度指数和人口密度对模型预测的准确性有重要影响，与kappa系数呈负相关。