Cargando…

Selection of the Optimal Spectral Resolution for the Cadmium-Lead Cross Contamination Diagnosing Based on the Hyperspectral Reflectance of Rice Canopy

This paper proposed an optimal spectral resolution for diagnosing cadmium-lead (Cd-Pb) cross contamination with different pollution levels based on the hyperspectral reflectance of rice canopy. Feature bands were sequentially selected by two-way analysis of variance (ANOVA2) and random forests from...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Shuangyin, Zhu, Ying, Wang, Mi, Fei, Teng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767059/
https://www.ncbi.nlm.nih.gov/pubmed/31505879
http://dx.doi.org/10.3390/s19183889
_version_ 1783454830126170112
author Zhang, Shuangyin
Zhu, Ying
Wang, Mi
Fei, Teng
author_facet Zhang, Shuangyin
Zhu, Ying
Wang, Mi
Fei, Teng
author_sort Zhang, Shuangyin
collection PubMed
description This paper proposed an optimal spectral resolution for diagnosing cadmium-lead (Cd-Pb) cross contamination with different pollution levels based on the hyperspectral reflectance of rice canopy. Feature bands were sequentially selected by two-way analysis of variance (ANOVA2) and random forests from the high-dimensional hyperspectral data after preprocessing. Then Support Vector Machine (SVM) was applied to diagnose the pollution levels using different feature bands combination with different spectral resolutions and cross validation was conducted to evaluate the distinguishing accuracies. Finally, the optimal spectral resolution could be determined by comparing the diagnosing accuracies of the optimal feature bands combination in each spectral resolution. In the experiments, the hyperspectral reflectance data of rice canopy with ten different spectral resolutions was captured, covering 16 pretreatments of Cd and Pb pollution. The experimental results showed the optimal spectral resolution was 9 nm with the highest average accuracy of 0.71 and relatively standard deviation of 0.07 for diagnosing the categories and levels of Cd-Pb cross contamination. The useful exploration provided an evidence for optimal spectral resolution selection to reduce the cost of heavy metal pollution diagnose.
format Online
Article
Text
id pubmed-6767059
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-67670592019-10-02 Selection of the Optimal Spectral Resolution for the Cadmium-Lead Cross Contamination Diagnosing Based on the Hyperspectral Reflectance of Rice Canopy Zhang, Shuangyin Zhu, Ying Wang, Mi Fei, Teng Sensors (Basel) Article This paper proposed an optimal spectral resolution for diagnosing cadmium-lead (Cd-Pb) cross contamination with different pollution levels based on the hyperspectral reflectance of rice canopy. Feature bands were sequentially selected by two-way analysis of variance (ANOVA2) and random forests from the high-dimensional hyperspectral data after preprocessing. Then Support Vector Machine (SVM) was applied to diagnose the pollution levels using different feature bands combination with different spectral resolutions and cross validation was conducted to evaluate the distinguishing accuracies. Finally, the optimal spectral resolution could be determined by comparing the diagnosing accuracies of the optimal feature bands combination in each spectral resolution. In the experiments, the hyperspectral reflectance data of rice canopy with ten different spectral resolutions was captured, covering 16 pretreatments of Cd and Pb pollution. The experimental results showed the optimal spectral resolution was 9 nm with the highest average accuracy of 0.71 and relatively standard deviation of 0.07 for diagnosing the categories and levels of Cd-Pb cross contamination. The useful exploration provided an evidence for optimal spectral resolution selection to reduce the cost of heavy metal pollution diagnose. MDPI 2019-09-09 /pmc/articles/PMC6767059/ /pubmed/31505879 http://dx.doi.org/10.3390/s19183889 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Shuangyin
Zhu, Ying
Wang, Mi
Fei, Teng
Selection of the Optimal Spectral Resolution for the Cadmium-Lead Cross Contamination Diagnosing Based on the Hyperspectral Reflectance of Rice Canopy
title Selection of the Optimal Spectral Resolution for the Cadmium-Lead Cross Contamination Diagnosing Based on the Hyperspectral Reflectance of Rice Canopy
title_full Selection of the Optimal Spectral Resolution for the Cadmium-Lead Cross Contamination Diagnosing Based on the Hyperspectral Reflectance of Rice Canopy
title_fullStr Selection of the Optimal Spectral Resolution for the Cadmium-Lead Cross Contamination Diagnosing Based on the Hyperspectral Reflectance of Rice Canopy
title_full_unstemmed Selection of the Optimal Spectral Resolution for the Cadmium-Lead Cross Contamination Diagnosing Based on the Hyperspectral Reflectance of Rice Canopy
title_short Selection of the Optimal Spectral Resolution for the Cadmium-Lead Cross Contamination Diagnosing Based on the Hyperspectral Reflectance of Rice Canopy
title_sort selection of the optimal spectral resolution for the cadmium-lead cross contamination diagnosing based on the hyperspectral reflectance of rice canopy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767059/
https://www.ncbi.nlm.nih.gov/pubmed/31505879
http://dx.doi.org/10.3390/s19183889
work_keys_str_mv AT zhangshuangyin selectionoftheoptimalspectralresolutionforthecadmiumleadcrosscontaminationdiagnosingbasedonthehyperspectralreflectanceofricecanopy
AT zhuying selectionoftheoptimalspectralresolutionforthecadmiumleadcrosscontaminationdiagnosingbasedonthehyperspectralreflectanceofricecanopy
AT wangmi selectionoftheoptimalspectralresolutionforthecadmiumleadcrosscontaminationdiagnosingbasedonthehyperspectralreflectanceofricecanopy
AT feiteng selectionoftheoptimalspectralresolutionforthecadmiumleadcrosscontaminationdiagnosingbasedonthehyperspectralreflectanceofricecanopy