Synergetic Classification of Coastal Wetlands over the Yellow River Delta with GF-3 Full-Polarization SAR and Zhuhai-1 OHS Hyperspectral Remote Sensing

Synergetic Classification of Coastal Wetlands over the Yellow River Delta with GF-3 Full-Polarization SAR and Zhuhai-1 OHS Hyperspectral Remote Sensing

The spatial distribution of coastal wetlands affects their ecological functions. Wetland classification is a challenging task for remote sensing research due to the similarity of different wetlands. In this study, a synergetic classification method developed by fusing the 10 m Zhuhai-1 Constellation...

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Autores principales: Canran Tu, Peng Li, Zhenhong Li, Houjie Wang, Shuowen Yin, Dahui Li, Quantao Zhu, Maoxiang Chang, Jie Liu, Guoyang Wang
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
Yellow River Delta
coastal wetland
synergetic classification
Gaofen-3
full-polarization SAR
Zhuhai-1 Orbita Hyperspectral Satellite
Science
Q
Acceso en línea:https://doaj.org/article/7206cae6d6ab44239680e948e38167cf
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spelling oai:doaj.org-article:7206cae6d6ab44239680e948e38167cf2021-11-11T18:56:56ZSynergetic Classification of Coastal Wetlands over the Yellow River Delta with GF-3 Full-Polarization SAR and Zhuhai-1 OHS Hyperspectral Remote Sensing10.3390/rs132144442072-4292https://doaj.org/article/7206cae6d6ab44239680e948e38167cf2021-11-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4444https://doaj.org/toc/2072-4292The spatial distribution of coastal wetlands affects their ecological functions. Wetland classification is a challenging task for remote sensing research due to the similarity of different wetlands. In this study, a synergetic classification method developed by fusing the 10 m Zhuhai-1 Constellation Orbita Hyperspectral Satellite (OHS) imagery with 8 m C-band Gaofen-3 (GF-3) full-polarization Synthetic Aperture Radar (SAR) imagery was proposed to offer an updated and reliable quantitative description of the spatial distribution for the entire Yellow River Delta coastal wetlands. Three classical machine learning algorithms, namely, the maximum likelihood (ML), Mahalanobis distance (MD), and support vector machine (SVM), were used for the synergetic classification of 18 spectral, index, polarization, and texture features. The results showed that the overall synergetic classification accuracy of 97% is significantly higher than that of single GF-3 or OHS classification, proving the performance of the fusion of full-polarization SAR data and hyperspectral data in wetland mapping. The synergy of polarimetric SAR (PolSAR) and hyperspectral imagery enables high-resolution classification of wetlands by capturing images throughout the year, regardless of cloud cover. The proposed method has the potential to provide wetland classification results with high accuracy and better temporal resolution in different regions. Detailed and reliable wetland classification results would provide important wetlands information for better understanding the habitat area of species, migration corridors, and the habitat change caused by natural and anthropogenic disturbances.Canran TuPeng LiZhenhong LiHoujie WangShuowen YinDahui LiQuantao ZhuMaoxiang ChangJie LiuGuoyang WangMDPI AGarticleYellow River Deltacoastal wetlandsynergetic classificationGaofen-3full-polarization SARZhuhai-1 Orbita Hyperspectral SatelliteScienceQENRemote Sensing, Vol 13, Iss 4444, p 4444 (2021)
institution DOAJ
collection DOAJ
language EN
topic Yellow River Delta
coastal wetland
synergetic classification
Gaofen-3
full-polarization SAR
Zhuhai-1 Orbita Hyperspectral Satellite
Science
Q
spellingShingle Yellow River Delta
coastal wetland
synergetic classification
Gaofen-3
full-polarization SAR
Zhuhai-1 Orbita Hyperspectral Satellite
Science
Q
Canran Tu
Peng Li
Zhenhong Li
Houjie Wang
Shuowen Yin
Dahui Li
Quantao Zhu
Maoxiang Chang
Jie Liu
Guoyang Wang
Synergetic Classification of Coastal Wetlands over the Yellow River Delta with GF-3 Full-Polarization SAR and Zhuhai-1 OHS Hyperspectral Remote Sensing
description The spatial distribution of coastal wetlands affects their ecological functions. Wetland classification is a challenging task for remote sensing research due to the similarity of different wetlands. In this study, a synergetic classification method developed by fusing the 10 m Zhuhai-1 Constellation Orbita Hyperspectral Satellite (OHS) imagery with 8 m C-band Gaofen-3 (GF-3) full-polarization Synthetic Aperture Radar (SAR) imagery was proposed to offer an updated and reliable quantitative description of the spatial distribution for the entire Yellow River Delta coastal wetlands. Three classical machine learning algorithms, namely, the maximum likelihood (ML), Mahalanobis distance (MD), and support vector machine (SVM), were used for the synergetic classification of 18 spectral, index, polarization, and texture features. The results showed that the overall synergetic classification accuracy of 97% is significantly higher than that of single GF-3 or OHS classification, proving the performance of the fusion of full-polarization SAR data and hyperspectral data in wetland mapping. The synergy of polarimetric SAR (PolSAR) and hyperspectral imagery enables high-resolution classification of wetlands by capturing images throughout the year, regardless of cloud cover. The proposed method has the potential to provide wetland classification results with high accuracy and better temporal resolution in different regions. Detailed and reliable wetland classification results would provide important wetlands information for better understanding the habitat area of species, migration corridors, and the habitat change caused by natural and anthropogenic disturbances.
format article
author Canran Tu
Peng Li
Zhenhong Li
Houjie Wang
Shuowen Yin
Dahui Li
Quantao Zhu
Maoxiang Chang
Jie Liu
Guoyang Wang
author_facet Canran Tu
Peng Li
Zhenhong Li
Houjie Wang
Shuowen Yin
Dahui Li
Quantao Zhu
Maoxiang Chang
Jie Liu
Guoyang Wang
author_sort Canran Tu
title Synergetic Classification of Coastal Wetlands over the Yellow River Delta with GF-3 Full-Polarization SAR and Zhuhai-1 OHS Hyperspectral Remote Sensing
title_short Synergetic Classification of Coastal Wetlands over the Yellow River Delta with GF-3 Full-Polarization SAR and Zhuhai-1 OHS Hyperspectral Remote Sensing
title_full Synergetic Classification of Coastal Wetlands over the Yellow River Delta with GF-3 Full-Polarization SAR and Zhuhai-1 OHS Hyperspectral Remote Sensing
title_fullStr Synergetic Classification of Coastal Wetlands over the Yellow River Delta with GF-3 Full-Polarization SAR and Zhuhai-1 OHS Hyperspectral Remote Sensing
title_full_unstemmed Synergetic Classification of Coastal Wetlands over the Yellow River Delta with GF-3 Full-Polarization SAR and Zhuhai-1 OHS Hyperspectral Remote Sensing
title_sort synergetic classification of coastal wetlands over the yellow river delta with gf-3 full-polarization sar and zhuhai-1 ohs hyperspectral remote sensing
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/7206cae6d6ab44239680e948e38167cf
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