Science & method
From radar phase to centimetres
Everything we show is computed from NASA-ISRO NISAR Level-2 products with open, tested code. This page explains each step, the corrections we apply, how we checked the result, and what it cannot tell you.
Results
In short
- What was measured. NISAR radar image pairs over California, Türkiye and the UK, June–October 2026, turned into centimetres of ground motion with tested, open code.
- The main result. Parts of California's Central Valley moved up to −7.8 cm away from the satellite in 108 days; depending on the stable area used as reference the value lies between −4.7 and −7.8 cm.
- How we checked it. Against 10 GPS stations (typical difference about 1 cm where the ground sinks) and against a second, independent satellite pass from the opposite direction.
- What it means. Uneven sinking tilts canals and roads; in Karapınar the ground sank faster close to documented sinkholes. Over London no movement above the noise was found.
- What it cannot tell. One summer only, so yearly rates are estimates; the satellite sees the ground at a slant; NISAR data are still provisional.
Key findings
1 · Data
| Product | What it is | Use here |
|---|---|---|
| GUNW (L2) | Geocoded unwrapped interferogram, 80 m UTM grid, HH polarisation, with coherence, connected components and ionosphere phase screen | Ground motion: Central Valley (track 34, 7 pairs; check with track 114, 8 pairs), Karapınar (track 7, 8 pairs), London (track 101, 9 pairs) |
| GCOV (L2) | Radiometrically terrain-corrected backscatter (γ⁰) | Radar view of the Fens (quick-look) |
| SME2 (L3) | Soil moisture | Irrigation timing vs sinking (data/central_valley/drivers.json) |
All products come from NASA's Alaska Satellite Facility DAAC (search: platform=NISAR). Measurements on the main page use only PROVISIONAL products (composite release P05023) whose two dates are on or after 17 June 2026.
2 · Phase → centimetres
dLOS = −λ / (4π) · (φunw − φiono)
negative dLOS = motion away from the satellite (subsidence)
The sign convention follows ISCE3 (interferogram = reference × conj(secondary)) and MintPy's NISAR reader. Pixels with coherence < 0.3 or connected component 0 are masked, as are small isolated patches and pixels that jump by half a phase cycle from their 720 m neighbourhood (unwrapping errors). From each pair a plane plus a linear elevation term (Copernicus DEM) is removed to reduce long-wavelength and height-dependent atmospheric delay. Every pair is referenced to the same stable, highly coherent area. Vertical estimates assume no horizontal motion: dvert ≈ dLOS / cos θinc.
3 · Time series
Consecutive pairs (12 to 24 days apart; 28 Jun → 14 Oct 2026 for track 34) are summed into a cumulative map. A chain with any gap is not joined. Headline numbers are the most negative median of ~1 km blocks with ≥ 50 % valid pixels and within-block standard deviation ≤ 2 cm, so single-pixel unwrapping errors cannot set the headline. Re-referencing the whole chain to up to two other stable areas at least 30 km away moves the Central Valley maximum between −4.7 and −7.8 cm (line of sight); we report the range. Two orbits looking from opposite sides (tracks 34 and 114) let us also separate vertical from east–west motion (data/central_valley/vertical.json).
4 · Validation against GPS
We compared the NISAR vertical estimate with daily "up" positions from 10 continuous GPS stations (Nevada Geodetic Laboratory) over the same dates.
| Station | Correlation r | RMSE (cm) | GPS end (cm) | NISAR end (cm) |
|---|
5 · Infrastructure risk index
For every canal, major road and railway segment from OpenStreetMap longer than 1 km, we sample the cumulative map along the line and compute the sinking gradient (mm per km) and the total sinking. High: gradient ≥ 10 mm/km with sinking ≥ 2 cm, or total sinking ≥ 10 cm. Medium: gradient ≥ 5 mm/km with sinking ≥ 1 cm, or total sinking ≥ 5 cm. Gradients matter because uneven sinking tilts canals and reduces their capacity.
6 · Limits
- Radar measures along its slanted line of sight; horizontal motion would bias the vertical estimate.
- Troposphere and ionosphere add centimetre-level noise per pair; summing pairs accumulates it.
- Over London's clay the same method found no motion above the 3σ noise level (about 3.6 cm): small seasonal clay movement is below what one summer of data can resolve.
- Yearly rates extrapolated from one irrigation season overstate the net annual rate, because part of summer subsidence recovers in winter.
- Data are provisional and may change when the NISAR project releases validated products.
7 · Calibration status
8 · Sources
Comparison with published studies
Uncertainty budget
Validation report
Infrastructure risk dossier
Global Atlas time-series QC (Top 5 check)
Learn more
- NISAR StoryMap: Land Subsidence — how radar sees sinking from groundwater pumping (Central Valley example).
- NISAR applications — NASA papers on subsidence, groundwater, levees and dams, sinkholes and food security.
- NISAR mission (NASA JPL) and the NISAR data user guide (ASF).
- What is synthetic aperture radar? (NASA Earthdata) — wavelength, polarisation, how radar sees the ground.
- NASA ARSET trainings — free online courses on SAR and NISAR.
- UAVSAR postcards — airborne L-band radar images, the predecessor of NISAR's view.
- SAR tutorial in Python (Canadian Space Agency).
- USGS: Land subsidence in California.
- Find and download NISAR data yourself: ASF Vertex · our guide “Reproduce our data in 5 steps”.