Land Use Change in the Yangtze River Economic Belt during 2010 to 2020 and Future Comprehensive Prediction Based on Markov and ARIMA Models

Haotian Zheng, Fan Yu, Huawei Wan, Peirong Shi, Haonan Wang
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Abstract

The key data for accurate prediction is of great significance to accurately carry out the next step of sustainable land use development plan according to the demand of China. Consequently, the main purposes of our study are: (1) to delineate the characteristics of land use transitions within the Yangtze River Economic Belt; (2) to use the Markov model and the autoregressive integrated moving average (ARIMA) model for comparative analysis and prediction of land use distribution. This study analyzes land use/cover change (LUCC) data from 2010 and 2020 using the land use transition matrix, dynamic degree, and comprehensive index model and predicts 2025 land use by the Markov model. The study identifies a reduction in land usage over 11 years, particularly in grassland. The Markov and ARIMA models' significance is 0.002 (P < 0.01), showing arable land and woodland dominance, with varying changes in other land types.
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基于马尔可夫和 ARIMA 模型的 2010-2020 年长江经济带土地利用变化及未来综合预测
准确预测的关键数据对于根据我国需求准确开展下一步土地利用可持续发展规划具有重要意义。因此,我们研究的主要目的是(1)明确长江经济带土地利用变化特征;(2)利用马尔可夫模型和自回归综合移动平均(ARIMA)模型对土地利用分布进行对比分析和预测。本研究利用土地利用过渡矩阵、动态程度和综合指数模型分析了 2010 年和 2020 年的土地利用/覆盖变化(LUCC)数据,并利用马尔可夫模型预测了 2025 年的土地利用情况。研究发现,11 年来土地使用量有所减少,尤其是草地。马尔可夫模型和 ARIMA 模型的显著性为 0.002(P < 0.01),表明耕地和林地占主导地位,其他土地类型有不同程度的变化。
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