江西省红壤地区主要土壤类型的高光谱特性研究
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国家自然科学基金项目(41361049)、土壤与农业可持续发展国家重点实验室基金项目(0812201202)和江西省自然科学基金项目(20122BAB204012)


Hyper-spectral Characteristics of Major Types of Soils in Red Soil Region of Jiangxi Province,China
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the National Natural Science Foundation of China(No.41361049), The Project of State Key Laboratory of Soil and Sustainable Agricultural(No.0812201202) and the Natural Science Foundation of Jiangxi Province(No.20122BAB204012)

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    摘要:

    土壤光谱是土壤理化性质的综合反映,研究江西省红壤地区主要土壤类型的高光谱特性,对土壤的精准管理和土壤数字制图有重要意义。选择有代表性的吉安县、余江县、兴国县和湾里区,采集443个土壤表层土样,采用ASD光谱仪测量了其可见-近红外反射高光谱(350~2 500 nm)。对光谱进行连续统去除和二阶导数处理后,对四种主要红壤亚类及其土属的高光谱特性进行研究。然后选取反映成土母质、氧化铁(针铁矿和赤铁矿)、土壤有机质含量、黏土矿物等的光谱特征表现变量及高光谱反射率等共19个特征变量,对光谱进行Fastclus聚类分析。结果表明:红壤地区土壤不同亚类光谱反射率差异明显,620 nm~740 nm的特征吸收面积黄红壤>红壤>棕红壤>红壤性土,420 nm和447 nm的二阶导数差值黄红壤>棕红壤>红壤>红壤性土。棕红壤光谱在可见光-短波近红外光谱区域土壤反射率较高,位于1 900 nm范围的吸收强度较其他亚类宽浅。红壤性土光谱曲线最为陡峭,在近红外光谱区域土壤反射率最高,在1 400 nm、1 900 nm有较强的尖锐吸收峰,在2 200有超强吸收峰。红壤亚类光谱曲线整体走势与红壤性土亚类相似,但在900 nm、1 400 nm、1 900 nm和2 200 nm的吸收强度较红壤性土弱,反射曲线位置较高。不同亚类水稻土由于水淹时间的不同,其光谱特征差异较为明显,光谱反射率表现为淹育型水稻土>潴育型水稻土>潜育型水稻土,620 nm~740 nm的特征吸收面积潜育型水稻土>潴育型水稻土>淹育性水稻土,420 nm和447 nm的反射率二阶导数差值为淹育型水稻土>潴育性水稻土>潜育型水稻土,但均高于红壤。选取的特征变量对土壤进行亚类分类的准确率为86.23%,分类的准确度较高,而土属的准确率仅为66.37%。可见-近红外土壤光谱特征可以作为江西红壤地区主要土壤亚类划分的定量参考指标。

    Abstract:

    【Objective】Soil spectrum, as a comprehensive reflection of soil physical and chemical properties, is of important significance to soil quality management, digital soil mapping, analysis of soil properties and soil classification in the red soil regions. 【Method】 In this paper, a total of 443 surface soil samples were collected in the typical red soil regions, e.g. Ji’an County, Yujiang County, Xingguo County and Wanli District of Jiang Province, and visible and near infrared reflectance hyper-spectra (350~2500 nm) of the samples were measured with an ASD spectrometer in laboratory. After the treatment of the spectra with the continuum-removal and second order derivative methods, the spectra of the four major soil subgroups and their subordinate soil families in this region were characterized. Then, 19 characteristic variables, such as spectral reflection and absorption of parent materials, iron oxide (goethite and hematite) minerals, organic matter and clay minerals and hyper-spectral reflectance, were cited as indices for Fastclus cluster analysis of the spectra. 【Result】Results show that the soils in the region varied sharply in spectral reflectance from sub-group to subgroup. In terms of spectral characteristic absorption area, in the 620~740 nm spectral bands, the four subgroups exhibited an order of yellow red soil > red soil > brown red soil > weakly red soil, but in terms of the difference between second order derivatives at 420 nm and at 447 nm, they followed an order of yellow red soil > brown red soil > red soil > weakly red soil. The brown red soil was higher in reflectance in the Vis-NIR spectral range, but lower and wider in spectral absorption intensity in the range of 1 900 nm than all the other subgroups. The weakly red soil was the steepest in spectral curve and the highest in reflectance in the near infrared region, showing two relatively strong absorption peaks at 1 400 nm and in 1 900 nm, separately, and a super strong peak at 2 200 nm. In terms of the peak at 2 200 nm, the sub-group of red soil was similar to the sub-group of reddish soil in spectral curve variation tendency, but lower in absorption intensity at 900 nm, 1 400 nm, 1 900 nm and in 2 200 nm and higher in position of the curve. As a result of variation of the duration of flooding, paddy soils of the four sub-groups of red soils varied greatly in spectral characteristics, and they followed an order of gleyed paddy soil > waterlogged paddy soil > submergic paddy soil in terms of spectral reflectance; an order of submergic paddy soil > waterlogged paddy soil > gleyed paddy soil in terms of spectral absorption area in the range of 620 nm~740 nm; and an order of gleyed paddy soil > submergic paddy soil > waterlogged paddy soil in terms of difference between second order derivatives at 420 nm and at 447 nm. Classification, based on the 19 indices, of red soils in the region by soil subgroup reached 86.23% in accuracy and by soil family 66.37%. 【Conclusion】Obviously soil Vis-NIR spectral characteristics can be used as quantitative indices for reference in classification by sub-group of the red soils in Jiangxi Province.

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赵小敏,杨梅花.江西省红壤地区主要土壤类型的高光谱特性研究[J].土壤学报,2018,55(1):31-42. DOI:10.11766/trxb201705220571 ZHAO Xiaomin, YANG Meihua. Hyper-spectral Characteristics of Major Types of Soils in Red Soil Region of Jiangxi Province, China[J]. Acta Pedologica Sinica,2018,55(1):31-42.

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  • 收稿日期:2016-11-25
  • 最后修改日期:2017-07-27
  • 录用日期:2017-09-25
  • 在线发布日期: 2017-10-30
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