Environmental Semantic Clustering-Guided Multimodal Fusion for Enhanced Interpretability in Methane Concentration Prediction - Dataset and Code

This dataset supports the research article "Environmental Semantic Clustering-Guided Multimodal Fusion for Enhanced Interpretability in Methane Concentration Prediction" Contents:- Ground-based air quality monitoring data from 4 WBEA stations in Athabasca Oil Sands Region (2024)- Satellite-derived methane concentration features from GHGSat SPECTRA platform- Preprocessed datasets with wavelet decomposition and environmental semantic clustering results- Complete ST-CAN model implementation and baseline comparison models (SVR, LSTM, Transformer)- Model prediction results and performance evaluation data The dataset enables full reproduction of experimental results presented in the manuscript and supports further research in methane emission monitoring using multimodal AI approaches. Keywords: methane monitoring, spatio-temporal fusion, cross-attention networks, environmental semantic clustering, oil sands monitoring, satellite data integration