Detecting the threat of landslides from space Today’s Video of the Day comes from NASA Goddard and features a look at how scientists can use satellites to detect the threat of landslides in advance.
Scientists have designed a new model called the Landslide Hazard Assessment for Situational Awareness which estimates which regions have a moderate to high chance of landslides every 30 minutes.
The model tracks global rainfall, which is the most widespread and frequent trigger of landslides, combined with a landslide susceptibility map identifying steep slopes, deforestation, and weak foundations. Previously, landslides used to be identified either by manual image interpretation process or by field investigations that demanded considerable amount of time and labour. Recently, a new technique using advanced object-based image classification method is developed to automatically detect landslides from satellite data.
The long baseline can increase false detection of landslides caused by the temporal decorrelation and land-cover changes such as deforestation. The original spatial resolution of the SAR data is approximately 6 m. Although interferometric SAR (InSAR) analysis is widely used to monitor landslides, it is difficult to use that for rapid landslide detection in mountainous forest areas because of significant decorrelation.
Video Credit: NASA Goddard