CN109682762A - 一种基于高光谱的土壤有机质含量估算方法 - Google Patents

一种基于高光谱的土壤有机质含量估算方法 Download PDF

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CN109682762A
CN109682762A CN201710972022.8A CN201710972022A CN109682762A CN 109682762 A CN109682762 A CN 109682762A CN 201710972022 A CN201710972022 A CN 201710972022A CN 109682762 A CN109682762 A CN 109682762A
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朱桂华
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    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
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Abstract

本发明公开了一种基于高光谱的土壤有机质含量估算方法，该方法首先采集土壤样本，然后测定土壤样本光谱，接着对土壤反射率光谱进行一阶微分和倒数的对数两种变换，最后在提取特征吸收波段的基础上，运用偏最小二乘回归法建立相应的估算模型，从而估算出土壤中的有机质含量。通过基于高光谱的土壤有机质含量估算方法，在保留尽量多的光谱信息并维持光谱原有基本特征的前提下，对于减少数据量，尤其是去除冗余信息起到了很好的作用，能够快速估算土壤中的有机质含量。通过了解土壤养分的状况及动态变化，为指导农业生产及保护农业生态环境提供了科学依据。

Description

一种基于高光谱的土壤有机质含量估算方法
技术领域
本发明涉及土壤有机质含量估算领域，特别发明了一种基于高光谱的土壤有机质含量估算方法。
背景技术
土壤有机质是存在于土壤中所有含碳的有机物质，其含量的多少，是土壤肥力的一个重要指标。通过土壤有机质的高光谱遥感分析，了解土壤的现状，并据此进行农业生产管理，是保证农业高产、优产、高效的重要前提。
对土壤光谱与土壤有机质含量之间关系的研究发现，土壤光谱反射率与有机质含量呈显著负相关。尽管国内外对土壤有机质含量的光谱效应进行了大量的研究工作，但在认识上还存在一定的分歧，主要是由于大多研究基于多种土壤类型，不同的土壤，由于受气候、母质、地形、生物等成土因素不同和成土年龄的差异，以及人类活动的影响，其理化特性具有明显差别。土壤组成物质的多样性以及每种组成物质独特的光谱特性，使得各类土壤光谱具有自己的特点。因此，将研究结果应用到特定土壤时，都可能产生较大误差。
因此，迫切需要研究一种基于高光谱的土壤有机质含量估算方法，来快速估算土壤中的有机质含量。通过了解土壤养分的状况及动态变化，为指导农业生产及保护农业生态环境提供了科学依据。
发明内容
发明目的：通过基于高光谱的土壤有机质含量估算方法，能够快速估算土壤中的有机质含量。
技术方案：本发明公开了一种基于高光谱的土壤有机质含量估算方法，该方法包括以下6步骤：
步骤1：采集土壤样本；
步骤2：测定光谱；
步骤3：光谱数据数学变换；
步骤4：提取特征吸收带；
步骤5：光谱重采样；
步骤6：偏最小二乘回归分析，估算土壤中的有机质含量。
进一步的，步骤1中，土壤样本经风干、碾磨、过筛。
进一步的，步骤2中，将每个土样测得的10条反射光谱曲线经算数平均后作为土样的实际反射光谱数据。
进一步的，步骤3中，光谱数据的数学变换方法为，对光谱曲线作一阶微分变换和倒数的对数变换。
进一步的，步骤4中，利用去包络线法对反射率光谱曲线上的特征吸收带进行提取。
进一步的，步骤4中，对特征吸收带的光谱数据以10nm为间隔进行算术平均运算。
与现有技术相比，本发明具有如下有益效果：
通过基于高光谱的土壤有机质含量估算方法，在保留尽量多的光谱信息并维持光谱原有基本特征的前提下，对于减少数据量，尤其是去除冗余信息起到了很好的作用，能够快速估算土壤中的有机质含量。通过了解土壤养分的状况及动态变化，为指导农业生产及保护农业生态环境提供了科学依据。
具体实施方式
本实施例采集江西省余江县和泰和县34个红壤土样，土壤样本经风干、碾磨、过20目筛。采用美国ASD公司生产的ASD Field SpecPro型光谱测试仪，光谱范围为350-2500nm，其中350-1000nm光谱采样间隔为1.4nm，在1000-2500范围内光谱采样间隔2nm，重采样间隔为1nm。将每个土样测得的10条反射光谱曲线经算术平均后则为该土样的实际反射光谱数据。对土壤反射率光谱进行一阶微分和倒数的对数两种变换，最后在提取特征吸收波段的基础上，运用偏最小二乘回归法建立相应的估算模型，从而估算出土壤中的有机质含量。经验证，该方法可达到较高精度，因而具有快速估算土壤中有机质含量的潜力。

Claims (6)

1.一种基于高光谱的土壤有机质含量估算方法，其特征在于：包括以下6步骤：
步骤1：采集土壤样本；
步骤2：测定光谱；
步骤3：光谱数据数学变换；
步骤4：提取特征吸收带；
步骤5：光谱重采样；
步骤6：偏最小二乘回归分析，估算土壤中的有机质含量。
2.根据权利要求1所述的一种基于高光谱的土壤有机质含量估算方法，其特征在于：所述步骤1中，土壤样本经风干、碾磨、过筛。
3.根据权利要求1所述的一种基于高光谱的土壤有机质含量估算方法，其特征在于：所述步骤2中，将每个土样测得的10条反射光谱曲线经算数平均后作为土样的实际反射光谱数据。
4.根据权利要求1所述的一种基于高光谱的土壤有机质含量估算方法，其特征在于：所述步骤3中，光谱数据的数学变换方法为，对光谱曲线作一阶微分变换和倒数的对数变换。
5.根据权利要求1所述的一种基于高光谱的土壤有机质含量估算方法，其特征在于：所述步骤4中，利用去包络线法对反射率光谱曲线上的特征吸收带进行提取。
6.根据权利要求1所述的一种基于高光谱的土壤有机质含量估算方法，其特征在于：所述步骤4中，对特征吸收带的光谱数据以10nm为间隔进行算术平均运算。
CN201710972022.8A 2017-10-18 2017-10-18 一种基于高光谱的土壤有机质含量估算方法 Pending CN109682762A (zh)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113358584A (zh) * 2021-06-22 2021-09-07 浙江省农业科学院 一种利用光谱估算土壤有机质含量的方法
CN114509404A (zh) * 2022-02-16 2022-05-17 安徽农业大学 一种高光谱土壤有效硼含量预测方法

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113358584A (zh) * 2021-06-22 2021-09-07 浙江省农业科学院 一种利用光谱估算土壤有机质含量的方法
CN113358584B (zh) * 2021-06-22 2024-01-16 浙江省农业科学院 一种利用光谱估算土壤有机质含量的方法
CN114509404A (zh) * 2022-02-16 2022-05-17 安徽农业大学 一种高光谱土壤有效硼含量预测方法

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