InSAR: How Satellites Measure Millimeter Ground Movement from 700 km Up

In 2016, a series of InSAR maps of Mexico City went viral — not because of an earthquake, but because they showed the city sinking at rates of up to 30 centimeters per year due to groundwater extraction. The subsidence was invisible at ground level (too slow, too uniform), but from space, the deformation pattern was unmistakable.

That's the power of InSAR: detecting ground movement that's far too subtle for any other measurement technique to capture at this scale.

The Core Idea

SAR is unique among remote sensing techniques because it records not just the intensity of the returned radar signal, but also its phase — the position of the wave within its cycle when it returns to the satellite.

Phase is sensitive to the distance between the satellite and the ground, with extraordinary precision. A change in distance of just half the radar wavelength produces a full cycle of phase change. For Sentinel-1's C-band (5.6 cm wavelength), half a wavelength is 2.8 cm. If the ground moves 2.8 cm between two satellite passes, the phase shifts by exactly 2π (one full cycle).

Interferometry compares the phase from two SAR acquisitions. Subtracting the phase of one image from the other produces an interferogram — a map of phase differences that encodes:

1. Topographic phase: Height differences cause phase differences (this is how SAR-derived digital elevation models are created)
2. Deformation phase: Ground movement between acquisitions
3. Atmospheric phase: Variations in atmospheric delay between the two dates
4. Noise: Random phase contributions from temporal surface changes

The goal of InSAR processing is to isolate the deformation signal from the other components.

Differential InSAR (DInSAR)

The simplest InSAR approach subtracts the topographic phase contribution (using a known DEM) to isolate the deformation signal:

Deformation phase = Total phase − Topographic phase − Atmospheric phase − Noise

The result is a map of colored fringes, where each fringe (complete color cycle) represents one half-wavelength of ground displacement in the satellite's line-of-sight direction.

Reading an Interferogram

The characteristic "rainbow fringe" pattern in an interferogram has a specific meaning:

• Widely spaced fringes: Gradual deformation over a large area (regional subsidence)
• Tightly packed fringes: Rapid deformation gradient (fault rupture, localized collapse)
• Concentric fringes: Radially symmetric deformation (volcanic inflation/deflation, sinkhole)
• No fringes: No detectable deformation (or complete decorrelation)

The direction of the color cycle (e.g., blue→green→red) indicates whether the ground moved toward or away from the satellite. Convention varies by software, so always check the sign convention.

Coherence: The Quality Indicator

InSAR only works if the ground surface is stable enough between acquisitions to maintain a consistent phase relationship. Coherence measures this stability, ranging from 0 (completely random phase — no useful signal) to 1 (perfect phase preservation).

High coherence areas:

• Urban buildings, infrastructure, bare rock
• Arid terrain with minimal surface change
• Stable agricultural land (between growing seasons)

Low coherence areas:

• Dense vegetation (leaves and branches move between passes)
• Water surfaces (constantly changing)
• Snow-covered areas (melting and accumulation)
• Construction zones (surface physically altered)

In tropical forests, C-band coherence can drop below usable levels within days. This is why L-band systems (like ALOS-2 PALSAR and the upcoming NISAR) are preferred for InSAR in vegetated areas — the longer wavelength penetrates deeper into the canopy and maintains coherence longer.

Time Series InSAR: PS-InSAR and SBAS

Single interferograms are limited by atmospheric noise, which can mimic or mask real deformation. Time series approaches solve this by combining many interferograms:

Persistent Scatterer InSAR (PS-InSAR)

Identifies pixels that maintain high coherence across all acquisitions in a stack (typically 20-50+ scenes spanning 1-2 years). These "persistent scatterers" — usually buildings, rocks, or infrastructure — provide reliable phase measurements that can be analyzed as a time series.

The atmospheric contribution varies randomly from scene to scene but is spatially smooth within each scene. The deformation signal is temporally smooth but can vary spatially. By exploiting these different statistical properties, PS-InSAR separates the two.

Result: Deformation time series at each PS point, with typical precision of 1-2 mm/year for linear velocity and 3-5 mm for individual measurements.

Small Baseline Subset (SBAS)

Instead of requiring persistent high coherence, SBAS combines interferograms with short temporal and spatial baselines to maximize the number of usable pixels. This produces lower precision per pixel but much better spatial coverage, especially in semi-vegetated areas.

Real-World Applications

Earthquake Deformation

The 2023 Turkey-Syria earthquakes produced meters of horizontal displacement along the fault rupture. InSAR mapped the co-seismic deformation field within days of the event, revealing the fault geometry and slip distribution. This information fed directly into seismic hazard models.

Land Subsidence

Groundwater extraction, mining, and oil/gas production cause the ground to compact and subside. InSAR monitors this across entire cities and regions:

• Jakarta: Up to 25 cm/year in northern districts
• Mexico City: 20-30 cm/year in the eastern basin
• San Joaquin Valley, California: Extensive agricultural pumping subsidence

Volcanic Monitoring

Magma moving toward the surface inflates the volcanic edifice, producing a characteristic pattern in InSAR. Regular monitoring can detect pre-eruptive inflation months before surface activity begins. Multiple volcano observatories worldwide now include InSAR as a standard monitoring tool.

Infrastructure Monitoring

Buildings, bridges, dams, and railway lines all experience slow deformation that can indicate structural problems. PS-InSAR time series detect:

• Differential settlement of buildings
• Thermal expansion cycles
• Slope instability affecting transport infrastructure
• Dam deformation

Limitations

Line-of-sight measurement: InSAR measures displacement along the satellite's look direction, not purely vertical or horizontal. Decomposing into 3D deformation requires combining ascending and descending orbits.

Temporal decorrelation: In vegetated areas, coherence drops rapidly. C-band InSAR over forests is often limited to winter (leaf-off) periods.

Atmospheric artifacts: Turbulent atmosphere, especially in mountainous areas, creates phase patterns that resemble deformation. Time series analysis mitigates but doesn't fully eliminate this.

Ambiguity: Phase wraps every 2.8 cm (for C-band). Deformation larger than this per fringe cycle requires "unwrapping" — an algorithmic step that can fail in areas of rapid deformation or low coherence.

Processing complexity: InSAR processing is significantly more demanding than standard SAR analysis. Orbit precision, DEM quality, co-registration accuracy, and atmospheric modeling all affect the result.

Despite these limitations, InSAR remains the only technique capable of measuring ground deformation across hundreds of kilometers with millimeter precision, at regular intervals, without any ground-based equipment. For geoscientists, civil engineers, and hazard analysts, it has fundamentally changed what questions can be asked — and answered — about how the Earth's surface moves.