Synergy of multi-temporal polarimetric SAR and optical image satellite for mapping of marsh vegetation using object-based random forest algorithm

Synergy of multi-temporal polarimetric SAR and optical image satellite for mapping of marsh vegetation using object-based random forest algorithm

The accurate classification of marsh vegetation is an important prerequisite for wetland management and protection. In this study, the Honghe National Nature Reserve was used as the research area. The VV and VH polarized backscattering coefficients of Sentinel-1B, the polarimetric decomposition para...

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Bibliographic Details
Main Authors: Fan, D. (Author), Fu, B. (Author), Gao, E. (Author), He, H. (Author), Huang, L. (Author), Liu, L. (Author), Sun, J. (Author), Xie, S. (Author), Zuo, P. (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2021
Subjects:
algorithm
Algorithm model
Backscattering
Backscattering coefficient
Backscattering coefficients
China
Decision trees
eigenvalue
Eigenvalues and eigenfunctions
forest
Geometrical optics
Heilongjiang
Honghe Nature Reserve
image classification
Image segmentation
Mapping
mapping method
marsh
Marsh vegetation
Marsh vegetation classification
Multi-scale inheritance segmentation
Parameter estimation
Polarimetric decomposition
Polarimetric decomposition parameter
Polarimetric decomposition parameters
Random forest algorithm
Remote sensing
Sentinel
Spectroscopy
synthetic aperture radar
Synthetic aperture radar
Variable selection
Variables selections
vegetation classification
vegetation index
vegetation mapping
wetland management
Wetland vegetation
Wetlands
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