A Generative Adversarial and Spatiotemporal Differential Fusion Method in Radar Echo Extrapolation

A Generative Adversarial and Spatiotemporal Differential Fusion Method in Radar Echo Extrapolation

As an important part of remote sensing data, weather radar plays an important role in convective weather forecasts to reduce extreme precipitation disasters. The existing radar echo extrapolation methods do not utilize the local natural characteristics of the radar echo effectively but only roughly...

Full description

Bibliographic Details
Main Authors:	Xianghua Niu, Lixia Zhang, Chunlin Wang, Kailing Shen, Wei Tian, Bin Liao
Format:	Article
Language:	English
Published:	MDPI AG 2023-11-01
Series:	Remote Sensing
Subjects:	radar extrapolation generative adversarial network difference spatiotemporal fusion
Online Access:	https://www.mdpi.com/2072-4292/15/22/5329

Similar Items

MLC-LSTM: Exploiting the Spatiotemporal Correlation between Multi-Level Weather Radar Echoes for Echo Sequence Extrapolation
by: Jinrui Jing, et al.
Published: (2019-09-01)

MCCS-LSTM: Extracting Full-Image Contextual Information and Multi-Scale Spatiotemporal Feature for Radar Echo Extrapolation
by: Huantong Geng, et al.
Published: (2022-01-01)

GAN-rcLSTM: A Deep Learning Model for Radar Echo Extrapolation
by: Huantong Geng, et al.
Published: (2022-04-01)

Towards a More Realistic and Detailed Deep-Learning-Based Radar Echo Extrapolation Method
by: Yuan Hu, et al.
Published: (2021-12-01)

A Radar Echo Extrapolation Model Based on a Dual-Branch Encoder–Decoder and Spatiotemporal GRU
by: Yong Cheng, et al.
Published: (2024-01-01)

Learnable Optical Flow Network for Radar Echo Extrapolation
by: Chengwei Zhang, et al.
Published: (2021-01-01)

MSLKNet: A Multi-Scale Large Kernel Convolutional Network for Radar Extrapolation
by: Wei Tian, et al.
Published: (2023-12-01)

A Novel LSTM Model with Interaction Dual Attention for Radar Echo Extrapolation
by: Chuyao Luo, et al.
Published: (2021-01-01)

Application of a Radar Echo Extrapolation‐Based Deep Learning Method in Strong Convection Nowcasting
by: Jian Yin, et al.
Published: (2021-08-01)

A Forecast-Refinement Neural Network Based on DyConvGRU and U-Net for Radar Echo Extrapolation
by: Jinliang Yao, et al.
Published: (2023-01-01)

Research on Radar Echo Extrapolation Method by Fusing Environment Grid Point Field Information
by: Yanqin Wen, et al.
Published: (2023-06-01)

The MS-RadarFormer: A Transformer-Based Multi-Scale Deep Learning Model for Radar Echo Extrapolation
by: Huantong Geng, et al.
Published: (2024-01-01)

An Long Short-Term Memory Model with Multi-Scale Context Fusion and Attention for Radar Echo Extrapolation
by: Guangxin He, et al.
Published: (2024-01-01)

Weather Radar Echo Extrapolation Method Based on Deep Learning
by: Fugui Zhang, et al.
Published: (2022-05-01)

Enhancing Radar Echo Extrapolation by ConvLSTM2D for Precipitation Nowcasting
by: Farah Naz, et al.
Published: (2024-01-01)

Extrapolation method of precipitation nowcasting radar echo based on GCA-ConvLSTM prediction network
by: Wei FANG, et al.
Published: (2023-08-01)

An Adaptive Multiscale Generative Adversarial Network for the Spatiotemporal Fusion of Landsat and MODIS Data
by: Xiaoyu Pan, et al.
Published: (2023-10-01)

Generative Adversarial CT Volume Extrapolation for Robust Small-to-Large Field of View Registration
by: Andrei Puiu, et al.
Published: (2022-03-01)

MLAM: Multi-Layer Attention Module for Radar Extrapolation Based on Spatiotemporal Sequence Neural Network
by: Shengchun Wang, et al.
Published: (2023-09-01)

Extrapolation methods : theory and practice /
by: Brezinski, Claude, 1941-, et al.
Published: (1991)

FsrGAN: A Satellite and Radar-Based Fusion Prediction Network for Precipitation Nowcasting
by: Dan Niu, et al.
Published: (2024-01-01)

3D-UNet-LSTM: A Deep Learning-Based Radar Echo Extrapolation Model for Convective Nowcasting
by: Shiqing Guo, et al.
Published: (2023-03-01)

Extrapolation-RELAX Estimator Based on Spectrum Partitioning for DOA Estimation of FMCW Radar
by: Sangdong Kim, et al.
Published: (2019-01-01)

Extrapolation methods : theory and practice /
by: Brezinski, Claude, 1941-, et al.
Published: (1991)

Spatiotemporal Prediction of Radar Echoes Based on ConvLSTM and Multisource Data
by: Mingyue Lu, et al.
Published: (2023-02-01)

MSSTNet: A Multi-Scale Spatiotemporal Prediction Neural Network for Precipitation Nowcasting
by: Yuankang Ye, et al.
Published: (2022-12-01)

Radar Echo Spatiotemporal Sequence Prediction Using an Improved ConvGRU Deep Learning Model
by: Wei He, et al.
Published: (2022-01-01)

Generative Adversarial Networks Capabilities for Super-Resolution Reconstruction of Weather Radar Echo Images
by: Hongguang Chen, et al.
Published: (2019-09-01)

Three-Dimensional Gridded Radar Echo Extrapolation for Convective Storm Nowcasting Based on 3D-ConvLSTM Model
by: Nengli Sun, et al.
Published: (2022-08-01)

Explicit and stepwise models for spatiotemporal fusion of remote sensing images with deep neural networks
by: Yaobin Ma, et al.
Published: (2021-12-01)

Strategy analysis of the extrapolation adjusted by model prediction (ExAMP) blending scheme for rainfall nowcasting
by: Chih-Chien Tsai, et al.
Published: (2023-09-01)

Multi-source deep data fusion and super-resolution for downscaling sea surface temperature guided by Generative Adversarial Network-based spatiotemporal dependency learning
by: Jinah Kim, et al.
Published: (2023-05-01)

Three Dimensional Image-Based Radar Cross Section Extrapolation via Planar Projective Transforms
by: Ling Pu, et al.
Published: (2019-01-01)

Strong Spatiotemporal Radar Echo Nowcasting Combining 3DCNN and Bi-Directional Convolutional LSTM
by: Suting Chen, et al.
Published: (2020-05-01)

A Hybrid Deep Learning-Based Spatiotemporal Fusion Method for Combining Satellite Images with Different Resolutions
by: Duo Jia, et al.
Published: (2021-02-01)

Weather Radar Echo Extrapolation with Dynamic Weight Loss
by: Yonghong Zhang, et al.
Published: (2023-06-01)

Evaluation of flood-producing rainfall nowcasting based on radar extrapolation with the variational optical flow method in the Yangtze River Basin in 2020
by: Gang TIAN, et al.
Published: (2021-06-01)

Accelerate spatiotemporal fusion for large-scale applications
by: Yunfei Li, et al.
Published: (2024-05-01)

Bagging-GPR method for ship RCS extrapolation in frequency domain
by: Muyu HOU, et al.
Published: (2023-08-01)

Prediction of Radar Echo Space-Time Sequence Based on Improving TrajGRU Deep-Learning Model
by: Qiangyu Zeng, et al.
Published: (2022-10-01)