Global Landslide Susceptibility

Update Frequency:Twice a day Summary:The global Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed to inform a wide range of users about landslide hazards. LHASA version 2.1 uses machine learning to show where and when landslides are most probable. Suggested Use:LHASA 2.1 was created to enable global monitoring of landslide hazard and is not a substitute for local site investigations. Red indicates high hazard and blue indicates low hazard.  LHASA nowcast "today": This map shows the relative probability of landslide occurrence today, based on rainfall estimates from GPM and forecasts from GEOS-FP. Satellite/Sensor:GPM, SMAP Resolution:30 arcseconds (~1 kilometer) Credits:NASA GSFC Users are requested to cite the following paper:Stanley, T. A., D. B. Kirschbaum, G. Benz, et al. 2021. "Data-Driven Landslide Nowcasting at the Global Scale." Frontiers in Earth Science, 9: [10.3389/feart.2021.640043]

Update Frequency:Twice a day Summary:The global Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed to inform a wide range of users about landslide hazards. LHASA version 2.1 uses machine learning to show where and when landslides are most probable. Suggested Use:LHASA 2.1 was created to enable global monitoring of landslide hazard and is not a substitute for local site investigations. Red indicates high hazard and blue indicates low hazard.  LHASA nowcast "yesterday": This map shows the relative probability of landslide occurrence within the last day, based on rainfall estimates from GPM.  Satellite/Sensor:GPM, SMAP Resolution:30 arcseconds (~1 kilometer) Credits:NASA GSFC Users are requested to cite the following paper:Stanley, T. A., D. B. Kirschbaum, G. Benz, et al. 2021. "Data-Driven Landslide Nowcasting at the Global Scale." Frontiers in Earth Science, 9: [10.3389/feart.2021.640043]

Dates Available: April 2021 - Present Update Frequency: Twice a day Summary: Landslides are a widespread and often underestimated natural hazard, causing thousands of deaths and significant economic damage each year. They routinely block roads, destroy infrastructure, and disrupt communities worldwide. While intense or prolonged rainfall is the most common landslide trigger, earthquakes and human activities can also cause them. The global Landslide Hazard Assessment for Situational Awareness (LHASA) model provides users with a comprehensive view of landslide hazard in near real-time. Using machine learning, LHASA combines rainfall data from the Global Precipitation Measurement (GPM) satellite with antecedent soil moisture from the Soil Moisture Active Passive (SMAP) satellite to identify areas currently at risk from landslides. The model shows where and when landslides are most probable, then calculates the exposed population and road length within each administrative district, helping users understand both the hazard and potential impacts on communities and infrastructure. To learn more please visit: https://landslides.nasa.gov/ Suggested Use: LHASA 2.1 was created to enable global monitoring of landslide hazard and is not a substitute for local site investigations. Red indicates high hazard and blue indicates low hazard. LHASA nowcast Hazard: "yesterday", "today", and "tomorrow": This map shows the relative probability of landslide occurrence yesterday, today, and tomorrow; respectively, based on rainfall estimates from GPM and forecasts from GEOS-FP. Satellite/Sensor: GPM, SMAP Resolution: 30 arcseconds (~1 kilometer) Credits: NASA GSFC Users are requested to cite the following paper: Stanley, T. A., D. B. Kirschbaum, G. Benz, et al. 2021. "Data-Driven Landslide Nowcasting at the Global Scale." Frontiers in Earth Science, 9: [10.3389/feart.2021.640043]

Update Frequency:Twice a day Summary:The global Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed to inform a wide range of users about landslide hazards. LHASA version 2.1 uses machine learning to show where and when landslides are most probable. Suggested Use:LHASA 2.1 was created to enable global monitoring of landslide hazard and is not a substitute for local site investigations. Red indicates high hazard and blue indicates low hazard.  LHASA nowcast "tomorrow": This map shows the relative probability of landslide occurrence tomorrow, based on rainfall estimates from GPM and forecasts from GEOS-FP. Satellite/Sensor:GPM, SMAP Resolution:30 arcseconds (~1 kilometer) Credits:NASA GSFC Users are requested to cite the following paper:Stanley, T. A., D. B. Kirschbaum, G. Benz, et al. 2021. "Data-Driven Landslide Nowcasting at the Global Scale." Frontiers in Earth Science, 9: [10.3389/feart.2021.640043]

Landslides are a widespread and often underestimated natural hazard, causing thousands of deaths and significant economic damage each year. They routinely block roads, destroy infrastructure, and disrupt communities worldwide. While intense or prolonged rainfall is the most common landslide trigger, earthquakes and human activities can also cause them. The global Landslide Hazard Assessment for Situational Awareness (LHASA) model provides users with a comprehensive view of landslide hazard in near real-time. Using machine learning, LHASA combines rainfall data from the Global Precipitation Measurement (GPM) satellite with antecedent soil moisture from the Soil Moisture Active Passive (SMAP) satellite to identify areas currently at risk from landslides. The model shows where and when landslides are most probable, then calculates the exposed population and road length within each administrative district, helping users understand both the hazard and potential impacts on communities and infrastructure. Daily global landslide exposure assessment from the LHASA (Landslide Hazard Assessment for Situational Awareness) model. Color-coded hazard levels range from red (very high exposure) to yellow (low exposure), helping users identify areas where landslides may occur. To learn more please visit: https://landslides.nasa.gov/

The landslide susceptibility map for current climate conditions highlights regions vulnerable to landslides caused by earthquakes or precipitation. This map was derived by combining the two susceptibility layers described below: for each cell, the highest value between the two was selected. Classes 2 and 3 are categorized as "Moderate", and classes 4 and 5 as "High". Class 1 denotes no susceptibility and is not shown. 1) The earthquake-induced landslide susceptibility map indicates the areas of the world that are more prone to landslides triggered by earthquakes. The landslide susceptibility is based on the model developed by NGI (Nadim et al., 2006, 2013; Jaedicke et al., 2013) but with improvements and refinements. The earthquake-induced landslides susceptibility map classifies the terrain into five susceptibility classes by combining slope, vegetation, lithology, and soil moisture information from global datasets. The weights of different susceptibility factors were calibrated to the information available in landslide inventories and physical processes. 2) The precipitation-induced landslide susceptibility map for the existing climate indicates the areas of the world that are more prone to landslides in the current climate conditions. The landslide susceptibility is based on the model developed by NGI (Nadim et al., 2006, 2013; Jaedicke et al., 2013) but with improvements and refinements. The precipitation-induced landslides susceptibility map for the current climate classifies the terrain into five susceptibility classes by combining slope, vegetation, lithology, and antecedent rainfall information from global datasets. Antecedent rainfall information has been obtained from the W5E5 dataset for the period 1979-2016. The weights of different susceptibility factors were calibrated to the information available in landslide inventories and physical processes. Note: This layer represents landslide susceptibility and not landslide hazard. It does not incorporate triggering factors (e.g., earthquake ground motion or rainfall intensity/return periods). Hazard can only be derived by combining susceptibility with a defined trigger scenario. The map has a resolution of 3 arc-sec. (~93 meters at the equator; east–west distance decreases with latitude). Background paper: A new model for global landslide susceptibility assessment and scenario-based hazard assessment (2003) Rosa M. Palau, Farrokh Nadim, Eivind Paulsen, Erlend Storrøsten https://giri.unepgrid.ch/sites/default/files/2023-06/20230615-NGI_manuscript_GIRI_landlside_hazard_model.pdf Release date: Sun Apr 30 2023 The layer was clipped to the geographic boundaries of 1) IDB Borrowing Member Countries, 2) Caribbean Development Bank (CDB) Borrowing Countries, 3) Organization of Eastern Caribbean States (OECS) Member Countries. VECTORIZED VERSION AVAILABLE HERE: Landslide Susceptibility