Landslides and Engineering Geology

Collect, document, and maintain new and historical landslide data to expand and improve the KGS inventory database. 

Assess inventory mapping techniques, inventory database structure, feature mapping, database attributes, and quality control. Connect with other agencies who do landslide mapping and explore standardization possibilities. 

Map landslides with lidar, ortho imagery, lidar-based elevation differencing, and other remote sensing techniques, supporting hazard assessment as well as prioritizing response and informing stakeholders in the case of a landslide event. 

Leverage unmanned aerial vehicle (UAV) lidar and terrestrial lidar systems for landslide characterization and repeat elevation surveys. 

Evaluate and use AI/object identification techniques for landslide mapping. 

Leverage and research other remote sensing time series data and techniques such as InSAR, satellite data (for NDVI), and photogrammetry for landslide mapping. 

Explore research opportunities to establish the ages of historic and paleo landslides using geochronology techniques. 

Geomorphic statistics-based machine learning landslide susceptibility modeling. 

Data-driven model inputs and spatial statistics to bolster landslide susceptibility efforts. 

Keep up to date with other landslide susceptibility and hazard modeling methods, including physics-based models. 

Evaluation of landslide occurrence and mechanical deformation related to geology, structure, lithologic control, kinematic evolution, and geomorphology. 

Analyze landslide types and their relationships to susceptibility and potential impact. 

Explore methods of debris flow hazard assessment including landslide runout and debris flow modeling, evaluating conditions for debris flows initiation and the percentage of existing landslides that meet those conditions (e.g., evaluating which landslides move but do not runout). 

Incorporate KGS landslide inventories and susceptibility maps with the U.S. Geological Survey national Landslide Inventory and Susceptibility Map and other products. 

Approaches and methodologies for risk modeling and mapping. 

Explore how KGS susceptibility and hazard maps can be used for risk modeling. 

Analyze exposure, asset, and vulnerability data for elements at risk of landslides. 

Establish landslide damage and loss information. 

Establish methods and protocols for risk communication (see Hazard Response). 

Maintain the current EPSCoR CLIMBS Project 5 hydrologic monitoring network. 

Leverage CLIMBS hydrologic monitoring data for landslide hazard research including hydrologic data for scenario-based modeling, landslide forecasting, slope stability modeling, and other hazard mapping approaches. 

Connect landslide occurrence and weather, establish rainfall thresholds and weather context for landslides, leverage and improve inventory of landslides with known failure dates. 

Explore trends in climate science related to landslides, supporting solutions for climate resiliency. 

Evaluate UAV-based monitoring techniques (such as SFM models and lidar acquisition) and terrestrial handheld lidar of specific significant landslides in Kentucky. 

Engage with state NWS offices, the Kentucky Climate Center, and other weather-related groups to evaluate early warning communication. 

Explore landslide hazard and physics-based slope stability models, analyzing spatiotemporal data needs and scale questions. 

Work with the University of Kentucky Department of Civil Engineering to support laboratory testing and geotechnical analysis of soils and rock. 

Use and evaluate the use of shallow geophysics techniques such as electrical resistivity and seismic to investigate landslides. 

Explore leveraging KGS databases (e.g., coal borehole database) for support of landslide connections to specific lithologies, soil types, and soil thickness. 

Explore opportunities to address mine subsidence, this could include inventory, mapping, and mine subsidence hazard assessment. 

Leverage KGS laboratory services to better integrate the Team research and the lab capabilities (e.g. XRD or XRF for clay mineralogy analysis).