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首页> 外文期刊>International journal of remote sensing >Surface soil clay content mapping at large scales using multispectral (VNIR-SWIR) ASTER data
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Surface soil clay content mapping at large scales using multispectral (VNIR-SWIR) ASTER data

机译:使用多光谱(VNIR-SWIR)ASTER数据大规模绘制表层土壤黏土含量

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摘要

The potential of Visible Near-Infrared and Short-Wave Infrared (VNIR-SWIR, 400 nm-2500 nm) hyperspectral imagery for use in multivariate approaches and geostatistical techniques for mapping topsoil properties has been previously demonstrated. However, the use of VNIR-SWIR hyperspectral imagery remains costly, which limits the spatial scales over which it can be applied. This paper aims to evaluate the potential for substituting the more accessible Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) VNIR-SWIR multispectral data for hyperspectral imagery in mapping surface soil clay contents. This study used ASTER multispectral data (nine bands in the VNIR-SWIR spectral domain) acquired over the Cap-Bon region in Tunisia (2000 km(2)) and 262 surface soil samples collected within the ASTER scene that were subjected to laboratory analysis of the clay fraction (soil particles less than 2 mu m). The approach followed two steps: i) estimation of surface soil clay contents for bare soil areas using a Multiple Linear Regression (MLR) model built from the 9 ASTER VNIR-SWIR bands and ii) spatial interpolation (co-kriging) of the soil sampling of measured points and the ASTER-estimates over the whole study area. The MLR model for estimating clay contents using ASTER multispectral data performed correctly ( = 0.60). In addition, this performance is only slightly lower than that obtained using hyperspectral imagery (specifically, an Airborne Imaging Spectrometer for Applications (AISA-DUAL) dual hyperspectral sensor) in a previous study. Moreover, the co-kriging process appeared to yield encouraging results for capturing the large range of variability of clay content values, although it was not able to represent the short scale variability ( = 0.43). Finally, the ASTER multispectral data, despite being underused in the mapping of soil properties, may open up new ways to perform more extensive mapping of surface soil properties in semi-arid contexts characterized by extensive bare and dry soil surfaces.
机译:先前已证明了可见多光谱方法和地统计学方法用于绘制表土特性的可见近红外和短波红外(VNIR-SWIR,400 nm-2500 nm)高光谱图像的潜力。但是,VNIR-SWIR高光谱图像的使用仍然昂贵,这限制了可应用该图像的空间范围。本文旨在评估用潜在性更高的高级星载热发射和反射辐射计(ASTER)VNIR-SWIR多光谱数据代替高光谱图像绘制表层土壤黏土含量的潜力。这项研究使用了在突尼斯Cap-Bon区域(2000 km(2))上采集的ASTER多光谱数据(VNIR-SWIR光谱域中的9个波段)以及在ASTER场景中收集的262个表面土壤样品,并对其进行了实验室分析。粘土部分(土壤颗粒小于2微米)。该方法分两个步骤:i)使用从9个ASTER VNIR-SWIR波段建立的多元线性回归(MLR)模型估算裸露土壤区域的表层土壤黏土含量,以及ii)对土壤采样进行空间插值(共同克里金法)整个研究区域的测量点数和ASTER估计值。使用ASTER多光谱数据估算粘土含量的MLR模型正确执行(= 0.60)。此外,该性能仅比以前的研究中使用高光谱图像(特别是应用机载成像光谱仪(AISA-DUAL)双高光谱传感器)获得的性能稍低。此外,尽管不能代表短尺度的变化性(= 0.43),但共克里金法似乎获得了令人鼓舞的结果,以捕获大范围的粘土含量值的变化性。最后,尽管ASTER多光谱数据没有在土壤性质的制图中使用,但它可能会开辟新的方法来在以广阔裸露和干燥土壤表面为特征的半干旱环境中进行更广泛的表面土壤性质制图。

著录项

  • 来源
    《International journal of remote sensing》 |2019年第4期|1506-1533|共28页
  • 作者单位

    Univ Tunis El Manar, FST, Campus Univ, El Manar Tunis 2092, Tunisia|Ctr Rech & Technol Eaux CERTE, Technopole Borj Cedria, Soliman, Tunisia;

    INRA, IRD, UMR LISAH, SupAgro, Montpellier, France;

    INRA, UMR LISAH, IRD, SupAgro, Montpellier, France;

    Ctr Rech & Technol Eaux CERTE, Technopole Borj Cedria, Soliman, Tunisia;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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