Synthetic aperture radar with Sentinel-1: speckle filtering, flood and ship detection, crop monitoring, and InSAR ground and volcano deformation.
Build an SBAS InSAR time series in Python from 364 COMET LiCSAR Sentinel-1 interferograms of the Svartsengi volcano in Iceland. Check unwrapping with phase closure, invert pixel by pixel with weighted least squares, project GNSS east, north and up into the line of sight, and validate six inflation–eruption cycles against the SENG station.
Write the classic SAR speckle filters (boxcar, Lee, refined Lee, enhanced Lee, Frost and Gamma-MAP) in NumPy and SciPy, run them on Sentinel-1 over Rutland Water, and compare them by equivalent number of looks, edge preservation and speed.
Invert Sentinel-1 InSAR for a volcanic source in Python: write Mogi point-source and Okada (1985) sill forward models in NumPy, downsample ascending and descending LOS maps with a quadtree, fit depth and volume change by weighted least squares with scipy.optimize, and estimate uncertainties with a Monte Carlo of correlated noise, compared with published results.
Map volcano deformation with Sentinel-1 InSAR in Python: stream free COMET LiCSAR interferograms of the Svartsengi volcanic system in Iceland, read wrapped and unwrapped phase and coherence, count fringes, convert phase to line-of-sight millimetres, and combine ascending and descending tracks into vertical and east–west motion, checked against GNSS.
Map ground subsidence with Sentinel-1 InSAR in Python: stream 170 real interferograms of Mexico City, convert unwrapped phase to millimetres of line-of-sight motion, mask low coherence, invert a small-baseline network into a time series, and cross-check the velocity with MintPy.
Monitor crops through cloud with free Sentinel-1 radar. Build VV, VH and VH/VV ratio time series for 247 fields in Cambridgeshire, beat speckle by field-averaging, read the growth signatures of winter wheat and oilseed rape, and compare with the gaps that cloud leaves in Sentinel-2 NDVI.
Detect ships in free Sentinel-1 SAR imagery with a cell-averaging CFAR detector written in NumPy and SciPy: mask the land, set a threshold from a speckle model, cluster detections into targets, reject wind turbines, sidelobes and ambiguities, compare VV with VH and export the vessels as GeoJSON.
Map the 2022 Sindh floods with free Sentinel-1 radar from the Microsoft Planetary Computer: convert backscatter to decibels, remove speckle with a Lee filter, pick a water threshold with Otsu's method, and measure the flood extent and how it receded over seven months.