An Unsupervised Snow Segmentation Approach Based on Dual-polarized Scattering Mechanism and Deep Neural Network

Distribution of snow and its melting is a critical factor affecting local weather, avalanche and flood forecasting, livelihood of people residing, and hydropower production. Most of the existing dry and wet snow identification methods were based on expensive quad-pol SAR with finite generalizability...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing Jg. 61; S. 1
Hauptverfasser:	Liu, Chang, Li, Zhen, Wu, Zhipeng, Huang, Lei, Zhang, Ping, Li, Gang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Algorithms Artificial neural networks C band Clustering Dry and wet snow Dual polarization radar Feature extraction feature-weighted fuzzy C-means Flood forecasting Hydroelectric power Identification methods Melting Methods Neural networks polarimetric decomposition Polarimetry Radar polarimetry River discharge SAR (radar) Scattering Snow Snow avalanches Snowmelt sparse autoencoder Speckle Support vector machines Synthetic aperture radar Training Weather forecasting
ISSN:	0196-2892, 1558-0644
Online-Zugang:	Volltext
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