Meteorological Technology International
  • News
    • A-E
      • Agriculture
      • Automated Weather Stations
      • Aviation
      • Climate Measurement
      • Data
      • Developing Countries
      • Digital Applications
      • Early Warning Systems
      • Extreme Weather
    • G-P
      • Hydrology
      • Lidar
      • Lightning Detection
      • New Appointments
      • Nowcasting
      • Numerical Weather Prediction
      • Polar Weather
    • R-S
      • Radar
      • Rainfall
      • Remote Sensing
      • Renewable Energy
      • Satellites
      • Solar
      • Space Weather
      • Supercomputers
    • T-Z
      • Training
      • Transport
      • Weather Instruments
      • Wind
      • World Meteorological Organization
      • Meteorological Technology World Expo
  • Features
  • Online Magazines
    • April 2025
    • January 2025
    • September 2024
    • April 2024
    • Archive Issues
    • Subscribe Free!
  • Opinion
  • Videos
  • Supplier Spotlight
  • Expo
LinkedIn Twitter Facebook
  • Sign-up for Free Weekly E-Newsletter
  • Meet the Editors
  • Contact Us
  • Media Pack
LinkedIn Facebook
Subscribe
Meteorological Technology International
  • News
      • Agriculture
      • Automated Weather Stations
      • Aviation
      • Climate Measurement
      • Data
      • Developing Countries
      • Digital Applications
      • Early Warning Systems
      • Extreme Weather
      • Hydrology
      • Lidar
      • Lightning Detection
      • New Appointments
      • Nowcasting
      • Numerical Weather Prediction
      • Polar Weather
      • Radar
      • Rainfall
      • Remote Sensing
      • Renewable Energy
      • Satellites
      • Solar
      • Space Weather
      • Supercomputers
      • Training
      • Transport
      • Weather Instruments
      • Wind
      • World Meteorological Organization
      • Meteorological Technology World Expo
  • Features
  • Online Magazines
    1. April 2025
    2. January 2025
    3. September 2024
    4. April 2024
    5. January 2024
    6. September 2023
    7. April 2023
    8. Archive Issues
    9. Subscribe Free!
    Featured
    April 15, 2025

    In this Issue – April 2025

    By Web TeamApril 15, 2025
    Recent

    In this Issue – April 2025

    April 15, 2025

    In this Issue – January 2025

    December 13, 2024

    In this Issue – September 2024

    August 8, 2024
  • Opinion
  • Videos
  • Supplier Spotlight
  • Expo
Facebook LinkedIn
Subscribe
Meteorological Technology International
Extreme Weather

NASA completes development of landslide hazard assessment model

Elizabeth BakerBy Elizabeth BakerOctober 27, 20234 Mins Read
Share LinkedIn Facebook Twitter Email
Credit: USAID’s Bureau for Humanitarian Assistance
Credit: NASA Scientific Visualization Studio
Credit: Pacific Disaster Center
Credit: Pacific Disaster Center
Credit: United Nations World Food Programme
Credit: USAID’s Bureau for Humanitarian Assistance
Credit: NASA Scientific Visualization Studio
Credit: Pacific Disaster Center
Credit: Pacific Disaster Center
Credit: United Nations World Food Programme
Credit: USAID’s Bureau for Humanitarian Assistance
Share
LinkedIn Facebook Twitter Email

After years of development and testing, NASA’s Landslide Hazard Assessment for Situational Awareness model (LHASA) has been integrated into the Pacific Disaster Center’s (PDC) multi-hazard monitoring, alerting and decision-support platform, DisasterAWARE.

LHASA enables researchers to map rainfall-triggered landslide hazards, giving DisasterAWARE users around the world a robust tool for identifying, tracking and responding to these threats. The aim is to equip communities with timely and critical risk awareness that bolsters disaster resilience and safeguards lives and livelihoods. Landslides cause thousands of deaths and billions of dollars in damage every year.

According to NASA, developing countries often bear disproportionate losses due to a lack of access to hazard early warning systems and other resources for effective risk reduction and recovery. Reports from the United Nations Office for Disaster Risk Reduction emphasize that early warning systems and early action are among the most effective ways to decrease disaster-related deaths and losses.

“Some local authorities develop their own systems to monitor landslide risk, but there isn’t a global model that works in the same way. That’s what defines LHASA: it works all the time and it covers most regions of the world,” said Robert Emberson, NASA Disasters associate program manager and a key member of the NASA landslides team. “Thanks to our collaboration with the Pacific Disaster Center, this powerful landslide technology is now even more accessible for the communities that need it most.”

LHASA uses a machine learning model that combines data on ground slope, soil moisture, snow, geological conditions, distance to faults and the latest near real-time precipitation data from NASA’s Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) product (which is part of the Global Precipitation Measurement mission). The model has been trained on a database of historical landslides and the conditions surrounding them, allowing it to recognize patterns that indicate a landslide is likely.

The result is a landslide “nowcast” – a map showing the potential of rainfall-triggered landslides occurring for any given region within the past day. This map of hazard likelihood can help agencies and officials rapidly assess areas where the current landslide risk is high. It can also give disaster response teams critical information on where a landslide may have occurred so they can investigate and deploy life-saving resources.

Partnering to protect the vulnerable
Generating landslide nowcasts is merely the first step. To be truly effective, vulnerable communities must receive the data in a way that is accessible and easy to integrate into existing disaster management plans. That’s where the PDC comes in.

PDC is an applied research center managed by the University of Hawaii, and it shares NASA’s goal to reduce global disaster risk through the uses of science and technology. Its flagship DisasterAWARE software provides early warnings and risk assessment tools for 18 types of natural hazards and supports decision-making by a wide range of disaster management agencies, local governments and humanitarian organizations. Prominent users include the International Federation of Red Cross and Red Crescent Societies (IFRC), the United Nations Office for the Coordination of Humanitarian Affairs (UN OCHA) and the World Food Programme (WFP).

“The close pairing of our organizations and use of PDC’s DisasterAWARE platform for early warning has been a special recipe for success in getting life-saving information into the hands of decision-makers and communities around the world,” said Chris Chiesa, PDC deputy executive director.

The collaboration with PDC brings NASA’s landslide tool to tens of thousands of existing DisasterAWARE users, dramatically increasing LHASA’s reach and effectiveness. Chiesa notes that teams in El Salvador, Honduras and the Dominican Republic have already begun using these new capabilities to assess landslide hazards during the 2023 rainy season.

PDC’s software ingests and interprets LHASA model data and generates maps of landslide risk severity. It then uses the data to generate landslide hazard alerts for a chosen region that the DisasterAWARE mobile app pushes to users. These alerts give communities critical information on potential hazards, enabling them to take protective measures.

DisasterAWARE also creates comprehensive regional risk reports that estimate the number of people and infrastructure exposed to a disaster – focusing specifically on things like bridges, roads, and hospitals that could complicate relief efforts when damaged. This information is critical for allowing decision-makers to effectively deploy resources to the areas that need them most.

“The LHASA model is all open-source and leverages publicly available data from NASA and partners,” commented Dalia Kirschbaum, lead of the NASA landslides team and director of Earth Sciences at NASA’s Goddard Space Flight Center. “This enables other researchers and disaster response communities to adapt the framework to regional or local applications and further awareness at scales relevant to their decision-making needs.” Kirschbaum and her team were recently awarded the prestigious NASA Software of the Year award for their work developing LHASA.

To find out more about NASA’s latest developments, click here. 

Previous ArticleNCAR study could improve predictions of dangerous storms
Next Article Report card gives update on the Global Ocean Observing System

Read Similar Stories

Hydrology

Integrated model improves flood risk assessment in China

May 15, 20253 Mins Read
Climate Measurement

WMO releases State of the Climate in Africa 2024 report

May 12, 20255 Mins Read
Early Warning Systems

WMO strengthens Nepal’s early warning services

May 8, 20253 Mins Read
Latest News

Integrated model improves flood risk assessment in China

May 15, 2025

EXCLUSIVE INTERVIEW: Ramla Qureshi, McMaster University’s Department of Civil Engineering

May 14, 2025

Tianjin University AI model turns street cameras into rainfall sensors

May 14, 2025

Receive breaking stories and features in your inbox each week, for free


Enter your email address:


Supplier Spotlights
  • Meteorage
Latest Job Postings
  • Researcher/Engineer to support data-based weather forecasting (R2/RE2)

    • Barcelona
    • Barcelona Supercomputing Center - Centro Nacional de Supercomputación
    • Full Time
Getting in Touch
  • Contact Us / Advertise
  • Meet the Editors
  • Download Media Pack
  • Free Weekly E-Newsletter
Our Social Channels
  • Facebook
  • LinkedIn
© 2025 UKi Media & Events a division of UKIP Media & Events Ltd
  • Cookie Policy
  • Privacy Policy
  • Terms and Conditions
  • Notice and Takedown Policy

Type above and press Enter to search. Press Esc to cancel.

We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept”, you consent to the use of ALL the cookies.
Cookie settingsACCEPT
Manage consent

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the ...
Necessary
Always Enabled

Necessary cookies are absolutely essential for the website to function properly. These cookies ensure basic functionalities and security features of the website, anonymously.

CookieDurationDescription
cookielawinfo-checbox-analytics11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".
cookielawinfo-checbox-functional11 monthsThe cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".
cookielawinfo-checbox-others11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.
cookielawinfo-checkbox-necessary11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".
cookielawinfo-checkbox-performance11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".
viewed_cookie_policy11 monthsThe cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data.

Functional

Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features.

Performance

Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.

Analytics

Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc.

Advertisement

Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. These cookies track visitors across websites and collect information to provide customized ads.

Others

Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet.

SAVE & ACCEPT
Powered by