How Can Satellite SAR Data Be Used to Generate Landslide Susceptibility Maps?

In IAM News episode 10, we learnt that Synthetic Aperture Radar (SAR) data can be a valuable tool for generating landslide susceptibility maps. The process involves several technical steps that leverage SAR data’s characteristics and advanced analysis techniques. Let’s break down exactly how satellite SAR data can be implemented to improve susceptibility map accuracy.

Firstly, data must be acquired and go through the pre-processing phase. SAR sensors on satellites emit microwave signals towards the Earth’s surface, and these signals interact with the terrain before they are reflected back to the sensor, capturing information about surface properties, roughness, and deformations. The raw SAR data may then go through radiometric collaboration, speckle reduction (to mitigate noise), and co-registration (aligning multiple SAR images in the same area).

After such pre-processing, interferograms can be generated by comparing the phase difference between two or more SAR images acquired at different times. Phase information can be used to measure ground displacement along the radar’s line of sight, which is perpendicular to the satellite’s flight path. By analysing the interferograms, areas undergoing surface deformation, which could indicate potential landslides, can be identified.

At this stage, terrain, and environmental data are then extracted from other sources. Geospatial data such as topography, slope, aspect, lithology, and land cover patterns, as well as other data can be considered. Such data provide essential contextual information for the identifying factors contributing to the occurrence of landslides. and therefore integrating  them into the process of generating landslide susceptibility maps enhances the accuracy and reliability of results.

These ancillary information must be pre-processed, georeferenced, and integrated into the GIS environment alongside SAR-derived data. Building landslide susceptibility maps in this way offers numerous benefits. One significant advantage is the ability to regularly update these maps. Since SAR data can be collected at regular intervals, terrain changes can be monitored in near real-time. This means that the maps can adapt to changing environmental conditions and provide up-to-date information to decision-makers; an invaluable feature as the effects of climate change take their toll.

Next, the calibrated model is applied to the study area to generate a landslide susceptibility map. The resulting map categorises different areas based on their susceptibility to landslides, such as low, moderate, high, and very high susceptibility. Finally, the generated landslide susceptibility map is provided to policy makers and stakeholders, allowing them to interpret and utilise the information, helping them make informed decisions.

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