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Full Description
This book constitutes the refereed post proceedings of the 5th China Conference on Spatial Data and Intelligence, SpatialDI 2024, held in Nanjing, China, during April 25-27, 2024.
The 25 full papers included in this book were carefully reviewed and selected from 95 submissions. They were organized in topical sections as follows: Spatiotemporal Data Analysis, Spatiotemporal Data Mining, Spatiotemporal Data Prediction, Remote Sensing Data Classification and Applications of Spatiotemporal Data Mining.
Contents
.- Spatiotemporal Data Analysis.
.- Multi-view Contrastive Clustering with Clustering Guidance and Adaptive Auto-en-coders.
.- Cloud-Edge Collaborative Continual Adaptation for ITS Object Detection.
.- Understanding Spatial Dependency among Spatial Interactions.
.- An Improved DBSCAN Clustering Method for AIS Trajectories Incorporating DP Compression and Discrete Fréchet Distance.
.- Structure and Semantic Contrastive Learning for Nodes Clustering in Heterogeneous Information Networks.
.- Accuracy Evaluation Method for Vector Data Based on Hexagonal Discrete Global Grid.
.- Applying Segment Anything Model to Ground-Based Video Surveillance for Identify-ing Aquatic Plant.
.- Spatiotemporal Data Mining.
.- Mining Regional High Utility Co-location Pattern.
.- Local Co-location Pattern Mining Based on Regional Embedding.
.- RCPM_RLM: A Regional Co-location Pattern Mining Method Based on Representa-tion Learning Model.
.- Construction of a Large-Scale Maritime Elements Semantic Schema Based on Hetero-geneous Graph Models.
.- OCGATL: One-Class Graph Attention Networks with Transformation Learning for Anomaly Detection For Argo Data.
.- RGCNdist2vec: Using Graph Convolutional Networks and Distance2Vector to Esti-mate Shortest Path Distance along Road Networks.
.- Self-supervised Graph Neural Network based Community Search over Heterogeneous Information Networks.
.- Measurement and Research on the Conflict between Residential Space and Tourism Space in Pianyan Ancient Township.
.- Spatiotemporal Data Prediction.
.- Spatio-Temporal Sequence Prediction Of Diversion Tunnel Based On Machine Learn-ing Multivariate Data Fusion.
.- DyAdapTransformer: Dynamic Adaptive Spatial-Temporal Graph Transformer for Traffic Prediction.
.- Predicting Future Spatio-Temporal States Using a Robust Causal Graph Attention Model.
.- Remote Sensing Data Classification.
.- MADB-RemdNet for Few-Shot Learning in Remote Sensing Classification.
.- Convolutional Neural Network Based on Multiple Attention Mechanisms for Hyper-spectral and LiDAR Classification.
.- Few-shot Learning Remote Scene Classification Based On DC-2DEC.
.- Applications of Spatiotemporal Data Mining.
.- Neural HD Map Generation from Multiple Vectorized Tiles Locally Produced by Au-tonomous Vehicles.
.- Trajectory Data Semi-fragile Watermarking Algorithm Considering Spatiotemporal Features.
.- HPO-LGBM-DRI: Dynamic Recognition Interval Estimation for Imbalanced Fraud Call via HPO-LGBM.
.- A Review on Urban Modelling for Future Smart Cities.
