Mapping Subsidence in Kolkata using DinSAR Interferometry
- Arpit Shah
- May 12, 2020
- 3 min read
Updated: Dec 4
You may have seen old, distorted houses where parts of the structure appear to have sunk—much like a miniature Leaning Tower of Pisa. An unstable foundation is often the primary cause of this distortion, and this instability is frequently linked to subsidence, i.e., the lowering of the ground level. Subsidence commonly arises due to excessive groundwater extraction, which vertically compresses the water-bearing sediments below, among other factors. In India, unplanned groundwater exploitation—driven by a growing population and erratic construction practices—is widely documented. As a result, subsidence is common, bringing significant cost and safety implications.
With Radar Remote Sensing, it is possible to detect changes in ground level (i.e., deformation) over time. The technique used for this is called Differential SAR Interferometry or DinSAR. Simply explained, it involves measuring the time taken for microwave signals—collectively called Synthetic Aperture Radar (SAR)—emitted by the satellite to return to the onboard receiver after interacting with Earth’s surface features.
By comparing this radar backscatter information across two or more time periods (the “differential” in DinSAR), one can determine whether the ground has subsided, remained stable, or uplifted. In addition to time-based differences, changes in backscatter intensity can reveal whether the structural characteristics of the surface have altered—a topic I’ve explained in more detail in my post on deformation mapping at volcanic sites. For those interested in learning more or practising Radar Remote Sensing and Interferometry, this excellent online course is a good starting point. The demonstration of performing DinSAR Interferometry can be seen here.
Below is my output for Subsidence Mapping in Kolkata between January 2019 and January 2020, derived from Sentinel-1A Single Look Complex imagery. The geographic extent of “Kolkata” in this map includes surrounding outskirts as well.
What can one infer from this output?
Large portions of Kolkata experienced subsidence during 2019–2020, with rates reaching as high as 6 cm—a discomforting figure. A clear pattern emerges: the north-to-central stretch of the city has sunk the most, as it historically has. The central-to-south zones have also subsided, though to a lesser extent (1–3 cm).
Interestingly, the rapidly developing zones of New Town and Rajarhat also show moderate-to-high subsidence (~3 cm). To my surprise, some areas on the city’s southern edge—Maheshtala and Berisha—exhibit ground uplift during the same period (0–3 cm).
The map does not extend to regions north of Barrackpore, but it is worth mentioning that subsidence in those areas—based on my analysis—exceeds 10 cm in the same year!
The blank pixels in the output represent areas with low coherence (<0.4) meaning the similarity between surface features in the two SAR images is poor. While this could indicate displacement, it could also arise from volume scattering—common in vegetated areas where crop growth or wind alters the orientation of leaves between image captures. This explanation is likely because the region west of the Hooghly River is less urbanized than the eastern side. Even so, one can mentally interpolate the presence and extent of subsidence based on surrounding pixels.
What did you observe?
Did you notice any additional patterns in the subsidence output? Does local knowledge help explain why certain areas have sunk more than others? Would you like me to extend the study over a longer timeframe?
I hope this analysis helps raise awareness about the literal pitfalls of reckless groundwater extraction—especially for construction. How we consume and manage water resources will profoundly influence the sustainability of our cities and our planet. I have written extensively on Water Management, and you may browse the full catalogue here.
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