Spatial Data and Intelligence

This book constitutes the refereed post proceedings of the 6th International Conference on Spatial Data and Intelligence, SpatialDI 2025, held in Xiamen, China, during April 1719, 2025.

The 17 full papers were carefully reviewed and selected from 100 submissions. The conference focuses on generative AI and spatial data intelligence, spatiotemporal knowledge graphs and large geographic models, digital twins and smart cities, government spatiotemporal big data and data governance, emergency disaster reduction and sustainable development, spatial humanities and social geography computing, spatiotemporal data management and analysis, and intelligent processing of remote sensing images.

Inhalt

.- BuildingView: Constructing Urban Building Exteriors Databases with Street View Imagery and Multimodal Large Language Model.

.- Urban fire risk prediction and spatiotemporal analysis based on machine learning.

.- Spatio-Temporal Diffusion Attention Networks for Vessel Flow Prediction.

.- Study on pollutants and greenhouse gases emission inventory making and emission prediction of Tianjin Port.

.- Automatic Landslide Identifification Based on High- Resolution Remote Sensing Images Using LightweightDeep Learning Network.

.- LCformer: Enhancing Multivariate Time Series Forecasting with Transformer Based on Lagged Correlations.

.- SignalingTraj: A Signaling Data based Trajectory Generation with Diffusion Model.

.- Research on Estimation Time of Arrival in Marine Traffic based on Large Language Model.

.- HTDiff: Self-Guiding Diffusion Models for Hand Trajectory Prediction.

.- A Method for Ship Trajectory Repair Based on Feature Correlation and SHAP Model Interpretability.

.- A Maritime Route Prediction Method for Large Oil Tankers Based on IMO-MMSI Matching and EncoderLSTM Model.

.- Learning Sequential Features of Check-ins for User Relationship Inference.

.- Spatial Optimization of Fire Stations in Beijing Based on Multi-factor Fire Risk Analysis and Covering Problem Model.

.- A Location Label Optimization Method for Crowdsourcing Trajectory Data.

.- Leveraging Data Augmentation through Contrastive Self-Supervised Learning for Next Point-of-Interest Recommendation.

.- Deductive Inference of How Urbanization Shaped by Governmental Policy in Beijing from 2005 to 2022.

.- LERI Evaluation and Driving Mechanism Analysis via GWRF Model.