# Application of Acoustic Emission Technique in Landslide Monitoring and Early Warning: A Review
## 4 Discussion  
### Field Monitoring of Soil Slopes  
The primary goal of implementing AE monitoring in soil slopes is supported by foundational laboratory validations [109]. Early implementations encountered significant obstacles due to substantial wave attenuation in porous, unconsolidated soil masses, making remote detections impractical. To address these challenges, effective strategies utilize waveguides to enable localized self-emission generation and transmission, particularly along predefined embedded routes.  
Initial attempts monitored three active landslides in Colorado, USA, using steel waveguides in trench beds recording AE counts through portable recorders over months [118]. Despite technical limitations, relationships between increased AE and seasonal slope movements were qualitatively interpreted. Using similar setups, [PERSON] and [PERSON] [119] reported thresholds for evaluating stability through establishing activity gradients classified as low, moderate, and high.  
Subsequent studies optimized waveguide configurations. Steel tubes backfilled with sands and gravels as \"active\" waveguides transmitted emissions from deforming host soils towards attached sensors along borehole sections [120]. Cowden and Arseley coastal slopes were monitored quantitatively, establishing empirical proportionalities linking event rates linearly to displacement velocities between 0.001 and 1 mm/min for failure forecasting.  
The choice of waveguides for AE monitoring is crucial, as it involves balancing coupling efficiency with flexibility. The selection process is also influenced by the monitoring system's overall effectiveness. Aluminum waveguides outperformed steel ones in transmission efficiency, primarily due to their better compatibility with soil conditions owing to lower seismic impedance mismatch [110].  
Recent advancements have consolidated quantification schemes. Linear relationships describe normalized AE event rates directly scaling with real-time displacement ratesreproducibly for triaxial modeling, landslide flume, and field slope experiments [121]. Soil-type-dependent proportionality coefficients were proposed to enable early warnings based on gradient criteria of \"essentially stable\", \"marginally stable\", \"unstable\", and \"rapidly deforming\", according to linearly extrapolated velocities from AE trends.  
Multi-location arrays also located AE epicenters, validating that sources corresponded to slope shear planes and not noise. Slope deformation fronts and zones were successfully mapped using portable arrays of passive detectors linked to centralized recorders for spatially distributed sensing along potential failure courses ahead of morphological imprints left along displaced paths [122]. Data analytics established kinematic fingerprints like b-value variations indicative of preparatory damage build-ups facilitating slope behavior forecasting.  
Overall, AE provided subsurface non-contact access addressing major constraints of traditional geotechnical inclinometer readings strictly limited to post-failure stages. Well-designed active waveguides capable of generating localized measurable self-emissions from incipient deforming soils underpinned a fully fledged early warning system validated through decade-long developmental research and numerous successful landslide premonitory detections.