Understanding volcanic systems and predicting their behavior through volcanophysical models constrained by in-situ and remotely sensed data is an area of increasing importance as the amount of data available grows. Ground-based monitoring data form the backbone of volcano monitoring, yet many volcanoes are poorly instrumented and/or the instrumental network is too sparse. On the other hand, space-based instruments offer complementary information thanks to their spatial resolution, broad coverage, and global reach, yet remain discrete in time. As remotely sensed data grow, particularly satellite multi-spectral and interferometric synthetic aperture radar (InSAR), the potential to constrain active magma sources, identify physical processes, and forecast volcanic behavior increases. When possible, combining both local and remote monitoring observations greatly increase our ability to advance scientific understanding and improve volcano monitoring. In particular, combinations of time series from satellite remote sensing observations (e.g., thermal infrared, TIR; visible-short-wavelength infrared, VSWIR; ultraviolet, UV; InSAR) with in-situ observations (e.g., seismic; gravity; Global Navigation Satellite System, GNSS; tilt meter) are proving increasingly relevant to test physical models of magmatic systems. When combined with model parameter estimation methods (e.g. Bayesian inference; Ensemble Kalman Filter), volcano system parameter forecasting on time-scales relevant to observatories become increasingly possible. In this session, we invite contributions focusing on the observations of unrest, eruptions, and longer-term volcanic processes, as well as contributions demonstrating the implementation of analytical, experimental, and numerical models to gain understanding of volcanic system physics towards improving hazard mitigation.Core connection between session and societal risk mitigation: Remote sensing satellite data (multi-spectral, InSAR) are increasingly being combined with in-situ data (if they exist) to improve both tracking unrest and constraining physical volcano models which have the potential to inform decision makers regarding eruption forecasts.