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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    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating 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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