Niversity, Xi’an 710054, China Guangdong Pearl River Talent Strategy “Local Innovation Team”, Zhuhai Surveying and Mapping Institute, Zhuhai 519000, China; [email protected] Crucial Laboratory of Geographic Information Science, Ministry of Education, School of Geographic Sciences, East China Regular University, Shanghai 200241, China; [email protected] Correspondence: [email protected]; Tel.: 86-1365-869-Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.Abstract: The spatial distribution of coastal GS-626510 Technical Information wetlands impacts their ecological functions. Wetland classification is actually a difficult job for remote sensing analysis due to the similarity of distinct wetlands. In this study, a synergetic classification method created by fusing the ten m Zhuhai1 Constellation Orbita Hyperspectral Satellite (OHS) imagery with eight m C-band Gaofen-3 (GF-3) full-polarization Synthetic Aperture Radar (SAR) imagery was proposed to give an updated and trusted quantitative description with the spatial distribution for the whole Yellow River Delta coastal wetlands. 3 classical machine studying algorithms, namely, the maximum likelihood (ML), Mahalanobis distance (MD), and assistance vector machine (SVM), had been applied for the synergetic classification of 18 spectral, index, polarization, and texture options. The outcomes showed that the all round synergetic classification accuracy of 97 is considerably greater than that of single GF3 or OHS classification, proving the overall performance of the fusion of full-polarization SAR information and hyperspectral information in wetland mapping. The synergy of polarimetric SAR (PolSAR) and hyperspectral imagery enables high-resolution classification of wetlands by capturing images all through the year, irrespective of cloud cover. The proposed method has the potential to supply wetland classification benefits with higher accuracy and far better temporal resolution in distinctive regions. Detailed and dependable wetland classification outcomes would deliver critical wetlands information and facts for greater understanding the habitat location of species, migration BMS-986094 HCV corridors, and the habitat adjust triggered by organic and anthropogenic disturbances. Keywords: Yellow River Delta; coastal wetland; synergetic classification; Gaofen-3; full-polarization SAR; Zhuhai-1 Orbita Hyperspectral Satellite; hyperspectral remote sensingCopyright: 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is definitely an open access short article distributed below the terms and conditions from the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ four.0/).1. Introduction Coastal wetlands play a pivotal role in offering numerous ecological services, like storing runoff, lowering seawater erosion, supplying food, and sheltering lots of organisms, such as plants and animals [1]. Most coastal wetlands have a crucial carbon sink function,Remote Sens. 2021, 13, 4444. https://doi.org/10.3390/rshttps://www.mdpi.com/journal/remotesensingRemote Sens. 2021, 13,2 ofwhich is crucial to decrease atmospheric carbon dioxide concentration and slow down global climate change [2,3]. Additionally, the mudflats [4], mangroves, and vegetation (e.g., Tamarix chinensis, Suaeda salsa, and Spartina alterniflora) [5] in coastal wetlands have robust carbon sequestration potential. Hence, the coastal wetland is known as the principle physique of the blue carbon ecosystem in the coastal zone [6]. The Yellow River Delta (hereinafter referred.