IIT Delhi Researchers Develop Cutting-Edge Tool To Map Landslides from Sky

CIOTechOutlook Team | Tuesday, 01 October 2024, 04:13 IST

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Researchers from the Civil Engineering Department at IIT Delhi have developed a ground-breaking cloud computing and machine learning-based tool, ML-CASCADE, to map landslide extent using satellite data. This easy-to-use and publicly-available tool requires only two inputs -- an approximate date and location of a landslide event -- and accurately maps a complex cluster of landslides within five minutes and a simple landslide within two minutes, which is critical for post-disaster damage assessment. The underlying model is trained on a large amount of satellite, terrain, vegetation, and soil data, IITD said in a statement on Monday.

A research paper by PhD scholar Nirdesh Kumar Sharma and Prof. Manabendra Saharia of the HydroSense Lab at the Civil Engineering Department has been published in the prestigious ‘Landslides’ journal by the International Consortium on Landslides (ICL).

Traditionally, landslides have been mapped by manually digitizing over satellite imagery, which is costly, inaccurate, and time-consuming. Field surveys and geological data collection cannot be done in large and remote areas. Existing simple models developed using the thresholds of vegetation indices fail in areas with minimal vegetation. Machine learning on geospatial data offers an unprecedented opportunity to overcome the drawbacks of index-based methods and integrate multiple diverse datasets to map landslides with high accuracy, said Prof. Manabendra Saharia,Civil Engineering Department, IIT Delhi.

The landslide problem is treated as a binary image segmentation problem. A total of 19 features have been used to develop the model with Sentinel-2 bands (pre- and post-landslide), slope and aspect from NASA Digital Elevation Model data, Normalized Difference Vegetation Index (NDVI), and differential Bare Soil Index, which can detect fresh landslide development.

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