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Hyper-spectral characteristics and classiifcation of farmland soil in northeast of China

机译:东北地区农田土壤的高光谱特征与分类

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摘要

The physical and chemical heterogeneities of soils make the soil spectral different and complicated, and it is valuable to increase the accuracy of prediction models for soil organic matter (SOM) based on pre-classiifcation. This experiment was conducted under a controlable environment, and different soil samples from northeast of China were measured using ASD2500 hyperspectral instrument. The results showed that there are different relfectances in different soil types. There are statisticaly signiifcant correlation between SOM and relfectence at 0.05 and 0.01 levels in 550–850 nm, and al soil types get signiifcant at 0.01 level in 650–750 nm. The results indicated that soil types of the northeast can be divided into three categories: The ifrst category shows relatively lfat and low relfectance in the entire band; the second shows that the spectral relfectance curve raises fastest in 460–610 nm band, the sharp increase in the slope, but uneven slope changes; the third category slowly uplifts in the visible band, and its slope in the visible band is obviously higher than the ifrst category. Except for the classiifcation by curve shapes of relfectance, principal component analysis is one more effective method to classify soil types. The ifrst principal component includes 62.13–97.19% of spectral information and it mainly relates to the information in 560–600, 630–690 and 690–760 nm. The second mainly represents spectral information in 1640–1740, 2050–2120 and 2200–2300 nm. The samples with high OM are often in the left, and the others with low OM are in the right of the scatter plot (the ifrst principal component is the horizontal axis and the second is the longitudinal axis). Soil types in northeast of China can be classiifed effectively by those two principles; it is also a valuable reference to other soil in other areas.
机译:土壤的物理和化学非均质性使土壤光谱变得不同而复杂,因此提高基于预分类的土壤有机质(SOM)预测模型的准确性具有重要意义。该实验是在可控的环境下进行的,使用ASD2500高光谱仪对来自中国东北的不同土壤样品进行了测量。结果表明,不同土壤类型具有不同的相关性。在550-850 nm,0.05和0.01的水平上,SOM和相关性之间具有统计学上的显着相关性,而在650-750 nm,0.01的水平上,所有土壤类型都具有显着相关性。结果表明,东北地区的土壤类型可分为三类:第一类土壤在整个带上相对肥力低,相对低;第二个结果表明,光谱相关性曲线在460-610 nm波段上升最快,斜率急剧增加,但斜率变化不均匀。第三类在可见带中缓慢上升,其在可见带中的斜率明显高于第一类。除了通过相对曲线形状进行分类外,主成分分析是一种更有效的土壤类型分类方法。第一主要成分包括光谱信息的62.13–97.19%,它主要与560–600、630–690和690–760 nm中的信息有关。第二个主要代表1640–1740、2050–2120和2200–2300 nm的光谱信息。 OM高的样本通常在散点图的左侧,OM低的其他样本在散点图的右侧(第一个主成分是水平轴,第二个是纵轴)。可以通过这两个原理对中国东北的土壤类型进行有效分类。它对其他地区的其他土壤也具有参考价值。

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  • 来源
    《农业科学学报(英文版)》 |2015年第12期|2521-2528|共8页
  • 作者单位

    Key Laboratory of Crop Nutrition and Fertilization, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China;

    Key Laboratory of Crop Nutrition and Fertilization, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China;

    Key Laboratory of Crop Nutrition and Fertilization, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China;

    Key Laboratory of Crop Nutrition and Fertilization, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China;

    Key Laboratory of Crop Nutrition and Fertilization, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China;

    Key Laboratory of Crop Nutrition and Fertilization, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China;

    Key Laboratory of Crop Nutrition and Fertilization, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China;

  • 收录信息 中国科学引文数据库(CSCD);
  • 原文格式 PDF
  • 正文语种 eng
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