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Novel Intelligent Spatiotemporal Grid Earthquake Early-Warning Model
2021
Remote Sensing
The integration analysis of multi-type geospatial information poses challenges to existing spatiotemporal data organization models and analysis models based on deep learning. For earthquake early warning, this study proposes a novel intelligent spatiotemporal grid model based on GeoSOT (SGMG-EEW) for feature fusion of multi-type geospatial data. This model includes a seismic grid sample model (SGSM) and a spatiotemporal grid model based on a three-dimensional group convolution neural network
doi:10.3390/rs13173426
fatcat:gxdjg7743rhlldezaamus6t5ia