Spectral–Spatial Generative Adversarial Network for Super-Resolution Land Cover Mapping With Multispectral Remotely Sensed Imagery

Spectral–Spatial Generative Adversarial Network for Super-Resolution Land Cover Mapping With Multispectral Remotely Sensed Imagery

Super-resolution mapping (SRM) can effectively predict the spatial distribution of land cover classes within mixed pixels at a higher spatial resolution than the original remotely sensed imagery. The uncertainty of land cover fraction errors within mixed pixels is one of the most important factors a...

Disgrifiad llawn

Manylion Llyfryddiaeth
Prif Awduron:	Cheng Shang, Shan Jiang, Feng Ling, Xiaodong Li, Yadong Zhou, Yun Du
Fformat:	Erthygl
Iaith:	English
Cyhoeddwyd:	IEEE 2023-01-01
Cyfres:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Pynciau:	Deep learning (DL) generative adversarial network (GAN) land cover fractions spectral–spatial errors super-resolution mapping (SRM)
Mynediad Ar-lein:	https://ieeexplore.ieee.org/document/9982425/

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