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基于多維分形法的土壤養(yǎng)分空間預(yù)測
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國家自然科學(xué)基金資助項目(41071152、41471186)、公益性行業(yè)(農(nóng)業(yè))科研專項資助項目(201103005-01-01)和農(nóng)業(yè)部科研杰出人才及創(chuàng)新團(tuán)隊資助項目(2012)


Spatial Prediction of Soil Nutrients Based on Multi-dimensional Fractal Methods
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    摘要:

    采用多維分形克里格插值法(Multifractal Krige,Mkrige)對土壤有機質(zhì)、全氮、有效磷和速效鉀4種土壤養(yǎng)分進(jìn)行空間預(yù)測,并以普通克里格法為參照對比,從傳統(tǒng)統(tǒng)計學(xué)參數(shù)、積累曲線、多維分形圖像、多維分形參數(shù)和特異值等方面深入分析Mkrige法空間預(yù)測的效果。結(jié)果表明:無論何種分形程度的土壤養(yǎng)分,Mkrige法預(yù)測值的積累曲線、多維分形參數(shù)和多維分形圖像都與實測值最接近;Mkrige法較好地保持了原始樣本數(shù)據(jù)的特異值區(qū),真實反映土壤養(yǎng)分空間分布的混沌狀態(tài),空間預(yù)測效果較優(yōu)。土壤有效磷、有機質(zhì)、全氮和速效鉀分形程度依次降低;分形程度越高,Mkrige法空間預(yù)測效果越優(yōu)。

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    Soil is a continuous spatial-temporal heterogeneity with high spatial variability. Soil nutrients are important parts of soil,and scientific and effective spatial prediction of the spatial variability of soil nutrients is the foundation of sustainable utilization of soil. The multi-dimensional fractal (multifractal) Krige method (Mkrige) with Krige method as a reference was used to simulate four types of soil nutrients, i.e., soil organic matter, nitrogen, phosphorus and potassium. Effectiveness of spatial prediction of Mkrige method was deeply analyzed in terms of five aspects, i.e., the traditional statistics, accumulation curve, multi-dimensional fractal images, multi-dimensional parameters and specific values. The results showed that traditional statistics parameters, accumulated value curve, multi-dimensional fractal parameters and multi-dimensional fractal image of the predicted values by Mkrige method were closer to the measured values than that of the predicted values by Krige method for the considered four soil nutrients. Mkrige method can better maintain the specific value area of the original samples, which truly reflected the chaotic state of the spatial distribution of soil nutrients and had a better prediction effect. The fractal degrees of phosphorus, organic matter, total nitrogen and potassium were reduced in order. For Mkrige method, the higher the fractal degree was, the more excellent the prediction effects were.

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陳光,高然,張世文,張立平,葉回春,黃元仿.基于多維分形法的土壤養(yǎng)分空間預(yù)測[J].農(nóng)業(yè)機械學(xué)報,2015,46(8):159-168. Chen Guang, Gao Ran, Zhang Shiwen, Zhang Liping, Ye Huichun, Huang Yuanfang. Spatial Prediction of Soil Nutrients Based on Multi-dimensional Fractal Methods[J]. Transactions of the Chinese Society for Agricultural Machinery,2015,46(8):159-168.

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  • 收稿日期:2014-07-25
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  • 在線發(fā)布日期: 2015-08-10
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