🛰 SAR · Satellite Imagery
InSAR deformation

DS · SqueeSAR · NISAR roadmap

DSL-bandwiki/ds-insar-squeesar-nisar-roadmap
TL;DR

DS-InSAR statistically groups the Distributed Scatterers of vegetation, farmland, and mountains that PSI cannot see in order to extract displacement, and combining PSI (points) with DS (areas) yields SqueeSAR. Because roughly 70% of Korea is mountainous and vegetated, PSI alone is strong only in cities, so DS-InSAR is the next priority on the Lumir roadmap after DInSAR→SBAS→PSI. Canopy penetration is ultimately a sensor-band problem, so NISAR L-band (λ≈24cm) fills the forest decorrelation gap of C-band Sentinel-1; however, as of 2026-06 the data is still Pre-Calibration, so operational trust is projected for 2026 Q4~2027.

DS-InSAR fills the gap PSI leaves behind

  • PSI (Persistent Scatterer) is strong on cities and man-made structures, but PS points are sparse over mountains, farmland, and vegetation, so performance collapses there.
  • DS-InSAR (Distributed Scatterer) statistically groups homogeneous pixels to exploit vegetation, farmland, and mountains, thereby filling that gap.
  • SqueeSAR combines PS (points) and DS (areas), making it suitable for monitoring Gangwon Province, forests, dams, and landslides in Korea where ~70% of the land is mountainous.
🛰️Scatterer
PSI (Persistent)Cities, structures (points)
DS-InSAR (Distributed)Vegetation, farmland, mountains (areas)
SqueeSAR = PS + DStechnique combining both
SqueeSAR = PS + DS combined

Lumir InSAR expansion roadmap

  • The current position is DInSAR, SBAS, and PSI all built; the next step is almost certainly DS-InSAR, followed by SqueeSAR.
  • PolSAR and TomoSAR are technically interesting, but they are low priority from the standpoint of Sentinel-1-based commercial displacement expansion.
DInSAR
SBAS
PSIcurrently done
DS-InSARnext priority
SqueeSAR
InSAR expansion stages — after PSI (done) comes DS-InSAR

Why L-band — NISAR

  • Canopy penetration is a matter of sensor band, not multilooking — Sentinel-1 C-band (5.405 GHz, λ≈5.6cm) has a wavelength similar to leaf size, so forest coherence collapses.
  • NISAR L-band (1.25 GHz, λ≈24cm) passes through leaves and reflects off trunks, maintaining forest coherence and enabling DS-InSAR over mountains.
  • NISAR's true value is L-band itself rather than accuracy; it is a structural solution to C-band coherence collapse in Korea where 70% of the land is mountainous.
Sentinel-1 C-bandNISAR L-band
Freq / wavelength5.405 GHz · λ≈5.6cm1.25 GHz · λ≈24cm
Forest behavior~leaf size → coherence collapsespasses leaves → coherence kept
Mountain DS-InSARineffective over vegetationfeasible
C-band vs L-band — forest penetration
Pitfalls & gotchas

NISAR's true value is L-band itself rather than accuracy, and the real InSAR concern is not radiometric calibration but Coregistration, Phase Stability, Geolocation, and Ionosphere — since the NISAR team is still refining ionospheric phase in particular, mm-grade long-term time series is realistic only after 2027. The sensible split right now is to proceed only as far as NISAR RSLC/GUNW parsers, HDF5 structure analysis, and SNAP/MintPy testing, while holding off on a commercial displacement service.

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