首页> 外文期刊>Catena: An Interdisciplinary Journal of Soil Science Hydrology-Geomorphology Focusing on Geoecology and Landscape Evolution >Predicting particle-size distribution using thermal infrared spectroscopy from reclaimed mine land in the semi-arid grassland of North China
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Predicting particle-size distribution using thermal infrared spectroscopy from reclaimed mine land in the semi-arid grassland of North China

机译:在华北半干旱草原中,使用热红外光谱预测粒度分布在华北半干旱草地上的热红外光谱

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摘要

Particle-size distribution is one of the vital properties of semi-arid and reclaimed soils that closely correlates with desertification. The thermal infrared (TIR) spectrum between 8 and 14 mu m has the potential for particle-size monitoring in remote sensing. This study aims to investigate the characteristic TIR spectra of reclaimed mine soils and establish a particle-size prediction model. The characteristics of the reststrahlen band (8-9.5 mu m) could be used to distinguish the coarse soil content that occurs in various land use and reclamation areas. A significant negative correlation was noted between the coarse sand content and the TIR spectrum (8-14 mu m). The support vector machine calibration model exhibited a higher prediction accuracy for estimating the coarse sand content, with a cross-validated R-2 of 0.95 and root mean square error (RMSE) of 3.01%, than the partial least squares regression model. These outcomes provide a theoretical basis and technical support for particle-size distribution estimations using TIR spectroscopy in semi-arid and reclamation areas. Hence, this study proposes that the spectral characteristics and model undergo further testing and optimization before wider application for the observation of semi-arid and reclaimed mine land ecosystems.
机译:粒度分布是半干旱和再生土壤的重要性质之一,与荒漠化密切相关。 8至14μm之间的热红外(TIR)光谱在遥感中具有粒度监测的可能性。本研究旨在研究再生矿井土壤的特征TIR光谱,建立粒径预测模型。 RESTRAHLEN带(8-9.5μm)的特征可用于区分各种土地使用和填海区域发生的粗糙土壤含量。在粗砂含量和TIR光谱(8-14μm)之间注意到显着的负相关。支持向量机校准模型表现出估计粗砂含量的更高的预测精度,其交叉验证的R-2为0.95,均线平方误差(RMSE),比偏最小二乘回归模型为3.01%。这些结果提供了使用半干旱和填海地区的TIR光谱的粒度分布估计提供了理论基础和技术支持。因此,本研究提出了在更广泛的应用中进行了进一步的测试和优化,在更广泛的应用中进行了进一步的测试和优化,以观察半干旱和再生矿山土地生态系统。

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