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Visible near-infrared reflectance spectroscopy as a predictive indicator of soil properties

机译:可见近红外反射光谱作为土壤性质的预测指标

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摘要

It is becoming increasingly important to improve spatial resolutions of soil maps as a fundamental information layer for studying ecological processes and to tackle land degradation. There is growing interest in the use of remote sensing technologies to assist the identification and delineation of spatial variation in soils. This paper investigates whether selected properties of extensively weathered, low fertility soils can be predicted using high-resolution reflectance spectra over the range 400-2500 nm. Clay content, carbonate concentration, organic carbon content and iron oxide content were analysed for 300 soil samples collected from the Jamestown, Belalie district, South Australia. The paper also examines the efficacy of this soil analysis methodology to supplement or replace traditional soil sampling in soil survey to increase sampling density and improve the spatial resolution of soil maps. Reflectance spectra were obtained from air-dried samples under controlled laboratory conditions using an ASD FieldSpec Pro spectroradiometer. Partial least squares regression was used to examine relationships between soil mineralogy, clay content and organic carbon and the reflectance spectra and identify the wavelengths contributing to prediction of these soil properties. Results show that it is possible to predict clay content, soil organic carbon, iron oxide content and carbonate content. Cross-validation R~2 values for all analyses were above 0.5 and the residual prediction difference (RPD) was acceptable for all soil properties. Carbonate and clay content were more accurately predicted than iron oxide and organic carbon. All samples were collected from the same geographical area such that they represented physical properties over a naturally occurring range and provide a prediction that could be related to subsequent image analysis or be used to carry out local scale soil survey. A rapid and reliable form of soil mapping could be developed from this methodology.
机译:作为研究生态过程和解决土地退化的基础信息层,提高土壤图的空间分辨率变得越来越重要。人们越来越关注使用遥感技术来帮助识别和描绘土壤中的空间变化。本文研究了是否可以使用400-2500 nm范围内的高分辨率反射光谱来预测广泛风化,低肥力土壤的选定特性。分析了从南澳大利亚州Belalie区Jamestown收集的300个土壤样品的粘土含量,碳酸盐浓度,有机碳含量和氧化铁含量。本文还研究了这种土壤分析方法在土壤调查中补充或替代传统土壤采样以增加采样密度和改善土壤图的空间分辨率的功效。使用ASD FieldSpec Pro分光光度计在受控的实验室条件下从风干样品中获得反射光谱。偏最小二乘回归用于检验土壤矿物学,粘土含量和有机碳与反射光谱之间的关系,并确定有助于预测这些土壤性质的波长。结果表明可以预测粘土含量,土壤有机碳,氧化铁含量和碳酸盐含量。所有分析的交叉验证R〜2值均大于0.5,并且所有土壤性质的残留预测差异(RPD)均可接受。碳酸盐和粘土含量比氧化铁和有机碳更准确。所有样本均从同一地理区域收集,因此它们代表了自然发生范围内的物理性质,并提供了与后续图像分析有关的预测,或可用于进行本地规模的土壤调查。通过这种方法可以开发出一种快速可靠的土壤测绘形式。

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  • 来源
    《Ecological indicators》 |2011年第1期|p.123-131|共9页
  • 作者单位

    School of Earth and Environmental Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia;

    rnSchool of Earth and Environmental Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia;

    rnSchool of Earth and Environmental Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia;

    rnSchool of Earth and Environmental Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    visible near-infrared reflectance; soil properties; partial least squares regression;

    机译:可见的近红外反射率;土壤性质;偏最小二乘回归;

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