Study of Mn Content Inversion Based on Hyperspectral

DOI

10.2991/wartia-18.2018.6How to use a DOI?

Keywords

Hyperspectral, Mn Content Inversion, soil samples

Abstract

In this study, the contents of Mn in 44 soil samples were collected from Shaanxi Province and were used ASD FieldSpec HR (350 ~ 2500 nm), then the NOR, MSC and SNV of the reflectance were pretreated, and the different deviation and reflectance reciprocal logarithmic transformation were carried out. The optimal hyperspectral estimation model of nine heavy metal elements of Mn was established by regression method, comparing the reflection characteristics of different heavy metal contents and the effect of different pretreatment methods on the establishment of soil heavy metal spectral inversion model. The results show that: (1) The reflectance spectrum improves the signal-to-noise ratio of the reflectance spectrum after the transformation of NOR, MSC and SNV. Combining differential transformation can improve the information of heavy metal elements in the soil, and using the correlation band energy can significantly improve the stability and predictability of the model. (2) The modeling accuracy of the optimal model of Mn spectra of Mn by PLSR method were 0.7852.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jinbao Liu
AU  - Lei Shi
PY  - 2018/09
DA  - 2018/09
TI  - Study of Mn Content Inversion Based on Hyperspectral
BT  - Proceedings of the 4th Workshop on Advanced Research and Technology in Industry (WARTIA 2018)
PB  - Atlantis Press
SP  - 26
EP  - 29
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-18.2018.6
DO  - 10.2991/wartia-18.2018.6
ID  - Liu2018/09
ER  -