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IMERG and LHASA Global Landslide Exposure Maps 1.0

Published by NASA/GSFC/SED/ESD/TISL/GESDISC | National Aeronautics and Space Administration | Metadata Last Checked: February 21, 2026 | Last Modified: 2026-02-17
The Landslide Hazard Assessment for Situational Awareness (LHASA) model identifies locations with high potential for landslide occurrence at a daily temporal resolution. LHASA combines satellite‐based precipitation estimates with a landslide susceptibility map derived from information on slope, geology, road networks, fault zones, and forest loss. When rainfall is considered to be extreme and susceptibility values are moderate to very high, a “nowcast” is issued to indicate the times and places where landslides are more probable.This archive contains GeoTIFF Rasters that are a 16-year average (beginning of 2001 - end of 2016). The spatial coverage is from 72°N to 60°S latitude, and 180°W to 180°E longitude, based on IMERG Ver06B from the aforementioned time interval. The provided global maps of exposure to landslide hazards, are at a 30x30 arc-second resolution. These maps show the estimated exposure of population, roads, and critical infrastructure (hospitals/clinics, schools, fuel stations, power stations & distribution facilities) to landslide hazard, as modeled by the NASA LHASA model.The data collection consists of eight files, covering the aforementioned spatial and temporal ranges, totaling approximately 20.3 GB (~2.5 GB each): (1): Landslide hazard (annual average; Units: Nowcasts.yr-1) (2): Landslide hazard (annual standard deviation; Units: Nowcasts.yr-1) (3): Population exposure (annual average; Units: Person-Nowcasts. yr-1. km-2) (4): Population exposure (annual standard deviation; Units: Person-Nowcasts. yr-1. km-2) (5): Road exposure (annual average; Units: Nowcasts.km.yr-1.km-2) (6): Road exposure (annual standard deviation; Units: Nowcasts.km.yr-1.km-2) (7): Critical infrastructure exposure (annual average; Units: Nowcasts.element.yr-1.km-2) (8): Critical infrastructure exposure (annual standard deviation; Units: Nowcasts.element.yr-1.km-2)

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