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中国科学院大学学报 ›› 2007, Vol. 24 ›› Issue (4): 439-445.DOI: 10.7523/j.issn.2095-6134.2007.4.006

• 论文 • 上一篇    下一篇

松嫩平原主要土壤光谱特征分析

刘焕军 张柏 刘志明 宋开山 王宗明 段洪涛   

  1. 中国科学院东北地理与农业生态研究所

    中国科学院研究生院

    东北师范大学城市与环境学院

  • 收稿日期:1900-01-01 修回日期:1900-01-01 发布日期:2007-07-15

Spectral Analysis of Soils in Songnen Plain, Northeastern China.

LIU Huan-Jun, ZHANG Bai, LIU Zhi-Ming, SONG Kai-Shan, WANG Zong-Ming, DUAN Hong-Tao   

  1. Northeast Institute of Geography and Agricultural Ecology, Chinese Academy of Sciences

    Graduate University of Chinese Academy of Sciences

    College of Urban and Environmental Sciences, Northeast Normal University

  • Received:1900-01-01 Revised:1900-01-01 Published:2007-07-15

摘要: 为了揭示松嫩平原主要土壤反射光谱特性、探讨该区土壤参数光谱速测方法,利用地物高光谱仪室内测定松嫩平原农安县主要类型土壤的光谱反射率,运用统计分析方法分析土壤参数与土壤光谱反射率及其数学变换形式的关系,并得到土壤有机质高光谱预测模型。结果表明:⑴ 有机质是松嫩平原主要土壤反射光谱特性的主要影响因素,由于区域(母质、气候等)的差异,即使同类土壤的反射光谱特性差异也很显著;⑵ 铁对松嫩平原农安县主要土壤的反射率光谱特性的影响较小;⑶ 基于反射光谱特性的有机质含量模型可以用于该区有机质含量的速测;⑷ 松嫩平原主要土壤有机质含量与总氮含量有显著的相关性,利用有机质含量高光谱预测模型可以部分揭示土壤总氮含量状况。

关键词: 土壤, 光谱, 有机质, 铁, 松嫩平原

Abstract: To uncover the spectral characteristics of the main soils in Songnen Plain, northeastern China, and the spectral fast testing methods for soil parameters, the room hyperspectral reflectance of soil samples from Nongan county, Songnen Plain was measured. With the help of statistic analysis methods, the relationship between soil parameters and reflectance was analyzed and spectral predicting models for soil organic matter content were also achieved. The results are as follows: ⑴ organic matter is the main factor impacting on soil reflectance characteristics of Songnen Plain, and because of the differences of soil parent matter and mechanical composition, even the same type soils from different area have different spectral characteristics; ⑵ the impact of Fe on soil reflectance in Songnen Plain is not apparent; ⑶ organic matter predicting models basing on spectral properties can be used for fast testing; ⑷ the correlation between organic matter and total N is significant, so the overall total N status can be discovered with organic matter spectral predicting models.

Key words: soil, spectrum, organic matter, Fe, Songnen Plain

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