王秀妮, 张荣群, 周 德, 蔡思敏. 基于Markov链的土壤盐渍化动态变化预测[J]. 农业工程学报, 2010, 26(14): 202-206.
    引用本文: 王秀妮, 张荣群, 周 德, 蔡思敏. 基于Markov链的土壤盐渍化动态变化预测[J]. 农业工程学报, 2010, 26(14): 202-206.
    Wang Xiuni, Zhang Rongqun, Zhou De, Cai Simin. Forecast of soil salinization change trend based on Markov chain[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(14): 202-206.
    Citation: Wang Xiuni, Zhang Rongqun, Zhou De, Cai Simin. Forecast of soil salinization change trend based on Markov chain[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(14): 202-206.

    基于Markov链的土壤盐渍化动态变化预测

    Forecast of soil salinization change trend based on Markov chain

    • 摘要: 为揭示银川平原土壤盐渍化演变规律,该研究从2000年4月份TM影像、2004年4月份中巴资源卫星影像、2009年4月份中国环境卫星影像分别提取银川平原土壤盐渍化信息,获得三个时期的银川平原土壤盐渍化分布图;以2000年数据作为模型的初始状态、2000年—2004年数据建立银川平原土壤盐渍化概率转移矩阵,模拟银川平原土壤盐渍化变化趋势并进行精度检验。对模型的X2检验表明,模型2009年预测结果与实际值无显著性差异,两者吻合良好。模型结果表明,在当前驱动力下,100多年后,各盐渍化土壤面积趋于稳定,重度盐渍化面积、中度盐渍化面积、轻度盐渍化面积分别为450.23、451.66、1 469.84 km2,占研究区总面积的30.42%,比2000年(36.28%)降低5.86%。利用马尔科夫模型进行银川平原土壤盐渍化预测是可行的,预测结果可以为土壤盐渍化管理提供理论依据。

       

      Abstract: To reveal the law of soil salinization evolution in Yinchuan plain, In this study, the information of soil salinization of Yinchuan Plain was extracted from TM image in April 2000, CBERS images in April 2004,and China’s environmental satellite image in April 2009, which acquired the distribution figure of soil salinization of the Yinchuan Plain in three periods. The 2000 data was regarded as the model’s initial state. The data in 2000-2004 was used for establishing probability transfer matrix of soil salinization of Yinchuan Plain that was used for simulating dynamic trend of soil salinization in Yinchuan plain and testing its accuracy. Test for model X2 shows that there exists no significant difference between the model predictions and the actual values, these two being in good agreement. Model results show that under the current driving force, the saline soil area will be stable, the area of severe salinization, moderate salinization and mild salinization will be 450.23, 451.66, and 1469.84 square kilometers, respectively, accounting for 30.42% of total area, which will decrease by 5.86% than in 2000 (36.28%), 100 years later. Using markov model to predict the soil salinization in Yinchuan plain is feasible, and the prediction results can be used for providing the theoretical basis for soil salinization management.

       

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