GeoAI for large-scale image analysis and machine vision: recent progress of artificial intelligence in geography
GeoAI, or geospatial artificial intelligence, has become a trending topic and the frontier for
spatial analytics in Geography. Although much progress has been made in exploring the …
spatial analytics in Geography. Although much progress has been made in exploring the …
MM-RNN: A multimodal RNN for precipitation nowcasting
Precipitation nowcasting, the high-resolution forecasting of precipitation in a short term, is
essential in various applications in the real world. Previous deep learning methods use …
essential in various applications in the real world. Previous deep learning methods use …
NowCasting-Nets: Representation learning to mitigate latency gap of satellite precipitation products using convolutional and recurrent neural networks
Accurate and timely estimation of precipitation is critical for issuing hazard warnings (eg, for
flash floods or landslides). Current remotely sensed precipitation products have a few hours …
flash floods or landslides). Current remotely sensed precipitation products have a few hours …
EfficientRainNet: Leveraging EfficientNetV2 for memory-efficient rainfall nowcasting
Rainfall nowcasting is critical for timely weather predictions and emergency responses,
particularly in flood-prone areas. Existing models, while accurate, often require substantial …
particularly in flood-prone areas. Existing models, while accurate, often require substantial …
CEMA-LSTM: Enhancing contextual feature correlation for radar extrapolation using fine-grained echo datasets
Accurate precipitation nowcasting can provide great convenience to the public so they can
conduct corresponding arrangements in advance to deal with the possible impact of …
conduct corresponding arrangements in advance to deal with the possible impact of …
LPT-QPN: A lightweight physics-informed transformer for quantitative precipitation nowcasting
D Li, K Deng, D Zhang, Y Liu, H Leng… - … on Geoscience and …, 2023 - ieeexplore.ieee.org
Quantitative precipitation nowcasting (QPN) is a highly challenging task in weather
forecasting. The ability to provide precise, immediate, and detailed QPN products is …
forecasting. The ability to provide precise, immediate, and detailed QPN products is …
STPF-Net: Short-Term Precipitation Forecast Based on a Recurrent Neural Network
J Wang, X Wang, J Guan, L Zhang, F Zhang, T Chang - Remote Sensing, 2023 - mdpi.com
Accurate and timely precipitation forecasts are critical in modern society, influencing both
economic activity and daily life. While deep learning methods leveraging remotely sensed …
economic activity and daily life. While deep learning methods leveraging remotely sensed …
Focal frame loss: A simple but effective loss for precipitation nowcasting
Precipitation nowcasting is an important but hard problem. Currently, with the landing of
deep learning, it has been treated as an image prediction problem based on radar echo …
deep learning, it has been treated as an image prediction problem based on radar echo …
Nowcasting-Nets: Deep neural network structures for precipitation nowcasting using IMERG
Accurate and timely estimation of precipitation is critical for issuing hazard warnings (eg, for
flash floods or landslides). Current remotely sensed precipitation products have a few hours …
flash floods or landslides). Current remotely sensed precipitation products have a few hours …
FsrGAN: A Satellite and Radar-Based Fusion Prediction Network for Precipitation Nowcasting
D Niu, Y Li, H Wang, Z Zang, M Jiang… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Precipitation nowcasting refers to the prediction of small-scale precipitation events at minute
and kilometer scales within the upcoming 0 to 2 h, which significantly impacts both human …
and kilometer scales within the upcoming 0 to 2 h, which significantly impacts both human …