Remote Sensing Inversion Method of Soil Iron Content in the Loess Plateau

doi:10.11873/j.issn.1004-0323.2019.2.0275

Remote Sensing Technology and Application

2019, Vol. 34

Issue (2): 275-283 DOI: 10.11873/j.issn.1004-0323.2019.2.0275

Remote Sensing Inversion Method of Soil Iron Content in the Loess Plateau

Ding Haining^1，2，Chen Yu²，Chen Yunzhi ¹

(1.Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education，National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology，Fuzhou University，Fuzhou 350116，China;
2.Institute of Remote Sensing and Digital Earth，Chinese Academy of Sciences，Beijing 100094，China)

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Abstract The information of soil composition and its spatial distribution could be obtained quickly and efficiently by using spectral technology.In order to accurately estimate the content and distribution characteristics of soil Fe elements in the loess plateau，the typical loess in the eastern part of Yulin was collected in the field.Laboratory physical and chemical analysis，spectral determination and pretreatment，analysis of the correlation between soil iron content and reflection spectrum，screening sensitive bands，using partial least squares modeling to determine the best estimation model.The spectral reflectivity and the selected sensitive bands are mainly distributed at 500 nm，870 nm，1 700 nm and 2 200 nm.The original reflectivity(Ref) modeling results are relatively stable and the prediction effect is the best.The prediction set correlation coefficient R² is up to 0.73 and the Root Mean Square Error(RMSEP) is the smallest.After derivative transform(FDR and SDR) and continuum removal of CR transform，the prediction set R² is 0.61 and 0.64，respectively.The optimal estimation model of soil Fe content(Ref) was applied to the Sentinel-2 multi-spectral remote sensing image to obtain the remote sensing inversion map of soil Fe content by band interpolation.It was found that the distribution characteristics of soil Fe content in the studied area were closely related to the strata.The results of this study can provide support for remote sensing analysis of soil Fe element content and realize rapid spectral mapping of soil iron in the Loess Plateau.

Key words: Loess plateau Hyperspectra Iron element Partial least square regression Sentinel-2 Remote sensing inversion method

Received: 04 May 2018 Published: 10 May 2019

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Ding Haining, Chen Yu, Chen Yunzhi . Remote Sensing Inversion Method of Soil Iron Content in the Loess Plateau. Remote Sensing Technology and Application, 2019, 34(2): 275-283.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2019.2.0275 OR http://www.rsta.ac.cn/EN/Y2019/V34/I2/275

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