Source and pattern identification of ground deformation based on non?negative matrix factorization: a case study

摘要

Ground deformation caused by mining affects the safety of underground mining and buildings. High-resolution characterizationof ground deformation response to latent sources is a first step toward improved hazard forecasting. We rely on long-termGlobal Position System (GPS) displacement data and an improved non-negative matrix factorization (NMF) algorithm ofblind source separation to identify the sources driving ground deformation. The NMF identifies three sources (S1, S2, andS3) with distinctly spatial and temporal patterns of ground deformation. S1 captures horizontal Y-displacement related tohorizontal tectonic stress σ1 . S2 dominates vertical Z-displacement with a widespread isotropous deformation driven byself-weight body force. S3 controls horizontal X-displacement related to horizontal tectonic stress σ2 . Besides, the independentcontributions of these three sources can be resolved from the GPS data. The results show that the sharp change ofsource contribution and even the transformation of dominant source are highly related to the severe deformation belt. Thisphenomenon is time-independent, and helps us to select sites and find the potential risk area at an early stage.