DSGNN: A Dual-View Supergrid-Aware Graph Neural Network for Regional Air Quality Estimation

arXiv:2404.01975v1 Announce Type: new
Abstract: Air quality estimation can provide air quality for target regions without air quality stations, which is useful for the public. Existing air quality estimation methods divide the study area into disjointed grid regions, and apply 2D convolution to model the spatial dependencies of adjacent grid regions based on the first law of geography, failing to model the spatial dependencies of distant grid regions. To this end, we propose a Dual-view Supergrid-aware Graph Neural Network (DSGNN) …

abstract air quality apply arxiv convolution cs.lg dependencies graph graph neural network grid network neural network public quality regional spatial study type view