Journal of Integrative Agriculture ›› 2015, Vol. 14 ›› Issue (12): 2521-2528.DOI: 10.1016/S2095-3119(15)61232-1

• 论文 • 上一篇    下一篇

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

 LU Yan-li, BAI You-lu, YANG Li-ping, WANG Lei, WANG Yi-lun, NI Lu, ZHOU Li-ping   

  1. 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
  • 收稿日期:2015-10-13 出版日期:2015-12-01 发布日期:2015-12-16
  • 通讯作者: BAI You-lu, Tel: +86-10-82108673, E-mail: baiyoulu@caas.cn
  • 基金资助:

    This research was supported by the National Natural Science Foundation of China (41371292).

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

 LU Yan-li, BAI You-lu, YANG Li-ping, WANG Lei, WANG Yi-lun, NI Lu, ZHOU Li-ping   

  1. 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
  • Received:2015-10-13 Online:2015-12-01 Published:2015-12-16
  • Contact: BAI You-lu, Tel: +86-10-82108673, E-mail: baiyoulu@caas.cn
  • Supported by:

    This research was supported by the National Natural Science Foundation of China (41371292).

PDF

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-classification. This experiment was conducted under a controllable environment, and different soil samples from northeast of China were measured using ASD2500 hyperspectral instrument. The results showed that there are different reflectances in different soil types. There are statistically significant correlation between SOM and reflectence at 0.05 and 0.01 levels in 550–850 nm, and all soil types get significant at 0.01 level in 650–750 nm. The results indicated that soil types of the northeast can be divided into three categories: The first category shows relatively flat and low reflectance in the entire band; the second shows that the spectral reflectance 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 first category. Except for the classification by curve shapes of reflectance, principal component analysis is one more effective method to classify soil types. The first 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 1 640–1 740, 2 050–2 120 and 2 200–2 300 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 first principal component is the horizontal axis and the second is the longitudinal axis). Soil types in northeast of China can be classified effectively by those two principles; it is also a valuable reference to other soil in other areas.

关键词: soil type , spectral characteristics , principle component , classification

Abstract: 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-classification. This experiment was conducted under a controllable environment, and different soil samples from northeast of China were measured using ASD2500 hyperspectral instrument. The results showed that there are different reflectances in different soil types. There are statistically significant correlation between SOM and reflectence at 0.05 and 0.01 levels in 550–850 nm, and all soil types get significant at 0.01 level in 650–750 nm. The results indicated that soil types of the northeast can be divided into three categories: The first category shows relatively flat and low reflectance in the entire band; the second shows that the spectral reflectance 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 first category. Except for the classification by curve shapes of reflectance, principal component analysis is one more effective method to classify soil types. The first 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 1 640–1 740, 2 050–2 120 and 2 200–2 300 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 first principal component is the horizontal axis and the second is the longitudinal axis). Soil types in northeast of China can be classified effectively by those two principles; it is also a valuable reference to other soil in other areas.

Key words: soil type , spectral characteristics , principle component , classification