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Synthetic aperture radar (SAR) is an active imaging radar that sends microwave pulses from a satellite or aircraft and records the echoes to form an image of the ground. Microwaves pass through cloud, smoke, and darkness, so SAR collects images at any hour in any weather. Each pixel stores backscatter, the share of energy the surface returns to the antenna. The European Union's Sentinel-1 mission publishes SAR data free, and analysts use it to map floods, detect ships, and measure subsidence.
A SAR antenna transmits a microwave pulse to one side of the flight track and records the fraction the surface scatters back. Echo delay fixes each target's position in range, the direction across the track.
Resolution along the track, called azimuth, depends on antenna length. A real antenna fine enough for 10 m pixels from orbit would be kilometers long, a point NASA covers in its Earthdata SAR primer. SAR replaces that antenna with motion. Each target stays inside the beam while the satellite travels a stretch of its orbit, and a processor focuses every echo from that stretch into one pixel. That stretch of orbit is the synthetic aperture.
The side-looking geometry is what separates targets in range. It also distorts terrain in three ways:
Brightness depends on roughness, geometry, and moisture. Calm water reflects the pulse away from the antenna and appears dark. Fields and forests scatter part of it back and appear gray. Walls and the ground beside them form corner reflectors that return a double bounce, so cities, ships, and flooded forests appear bright. Wet soil and vegetation return more energy than dry.
Wavelength controls how far a SAR signal penetrates. Longer wavelengths pass through leaves to branches, trunks, and the ground, and shorter wavelengths scatter from the first surface they meet. The band ranges below follow NASA Earthdata.
Band choice drives interferometry. L-band phase stays stable over vegetated ground for longer than C-band phase, so L-band InSAR works in forests where C-band coherence is lost. Heavy rain attenuates X-band signals, so storms can mark X-band images.
Polarization is the orientation of the radar wave's electric field: horizontal (H) or vertical (V). A SAR labels each channel by transmit and receive orientation. HH and VV are co-polarized channels. HV and VH are cross-polarized channels.
Scattering type shows up in the channels. Rough bare surfaces return most energy in VV and HH. A tree canopy scatters the wave many times and rotates part of it, so cross-pol returns rise with vegetation volume. Double bounce from buildings and flooded trunks is strongest in HH.
Systems collect one channel (single pol), two (dual pol), or all four (quad pol, also called full polarimetry). Sentinel-1 acquires VV and VH over most land, and HH and HV over polar ice. Polarimetric SAR (PolSAR) decompositions split each quad-pol pixel into surface, double-bounce, and volume components, and the VH/VV ratio is a common crop growth index.
Providers distribute SAR data at several processing levels, named here as Sentinel-1 names them.
Sentinel-1 Level-1 products ship in the SAFE package, with measurement layers stored as GeoTIFF. Cloud archives repackage them as Cloud Optimized GeoTIFF. The Alaska Satellite Facility runs HyP3, an on-demand service that produces RTC and InSAR products from Sentinel-1.
SAR and optical imagery measure different physical properties, and most Earth observation programs use both.
Optical sensors such as Landsat and hyperspectral instruments identify materials by spectrum. SAR fills the dates clouds remove and adds structure and motion. The two sources can also measure the same event. In Wherobots' Strait of Hormuz analysis, Sentinel-2 hull counts showed "Traffic through the surveyed corridor fell 95%", and the post cites a separate study that fused Sentinel-1 radar with AIS ship positions.
Public missions supply most SAR data free:
Commercial operators fly constellations of small X-band SAR satellites and task them on request. ICEYE, Capella Space, and Umbra are three such operators, and each sells spotlight images at sub-meter resolution.
Each of these uses depends on change detection: comparing scenes of the same place over time.
Speckle. Every resolution cell holds many scatterers, and their echoes interfere. The result is a grainy salt-and-pepper texture across even uniform surfaces. Multilooking averages neighboring pixels, and filters such as Lee and Refined Lee smooth homogeneous areas while keeping edges. Both trade resolution for a cleaner signal.
Terrain correction. SAR records in slant range, so mountains appear to lean toward the sensor and slopes change brightness with their angle to the beam. Geometric terrain correction uses a DEM to place each pixel at its true map position. Radiometric terrain correction normalizes brightness for slope. The Copernicus DEM GLO-30 is a common elevation input, and itself derives from TanDEM-X radar interferometry.
Volume. Sentinel-1 has collected data since 2014 on a 6- or 12-day repeat cycle, so a decade over one region is hundreds of scenes per orbit track. SLC scenes carry phase at full resolution and run several times larger than the matching GRD scene.
Joining. A flood mask becomes a decision once it is joined to the roads and buildings it affects, which means raster-to-vector joins across millions of features.
WherobotsDB runs the raster processing and spatial joins on SAR-derived layers in SQL, and it reads the data where it sits in cloud storage.
SAR backscatter stored as Cloud Optimized GeoTIFF loads as out-db rasters, read only in the tiles a query touches. Scenes indexed in a STAC catalog load through the STAC reader, one row per scene. RS_MapAlgebra thresholds backscatter into a water mask, and RS_ZonalStats summarizes that mask under each road segment or building. Partners for the join sit in Wherobots open data, including Overture transportation segments.
The AWS Glue Data Catalog announcement walks through this pattern for supply chain route disruption. A retailer ingests Sentinel-1 SAR imagery and NOAA HRRR precipitation forecasts, joins both to the Overture Roads network, buffers affected segments, runs zonal statistics, and writes a route disruption score per corridor to a Glue table.
RasterFlow runs PyTorch models over imagery a user supplies, so a custom ship or flood segmentation model applies to SAR scenes at scale. WherobotsDB is built by the original creators of Apache Sedona, 100% code compatible across all spatial functions.
The models people use every day were trained on text, documents, databases, and the internet, and none of those sources hold last week's flood extent. Through the Wherobots MCP Server, an AI agent can query a flood mask joined to the road network and return the closed segments.
-- Share of each road segment's 20 m buffer under open water in a post-event SAR scene -- Water threshold: VV gamma0 below 0.0158 (about -18 dB) WITH flood AS ( SELECT RS_MapAlgebra(rast, 'D', 'out = rast[0] < 0.0158 ? 1 : 0;', -9999.0) AS water FROM sar.s1_rtc_vv_post_event ), roads AS ( SELECT id, class, ST_Buffer(geometry, 20, true) AS buffer FROM wherobots_open_data.overture_maps_foundation.transportation_segment WHERE subtype = 'road' ) SELECT r.id, r.class, RS_ZonalStats(f.water, r.buffer, 1, 'mean') AS flooded_share FROM roads r JOIN flood f ON RS_Intersects(f.water, r.buffer);
Join SAR flood extents and ship detections to roads and buildings on the Wherobots free tier at cloud.wherobots.com.
In remote sensing, SAR stands for synthetic aperture radar: an imaging radar on a satellite or aircraft that combines echoes recorded along its path into the equivalent of a much longer antenna, producing high-resolution images of the ground with microwaves.
SAR data is the imagery a synthetic aperture radar produces. Each pixel holds backscatter, the strength of the microwave echo from that patch of ground, and complex products also keep the phase of the echo. Common SAR data products are Single Look Complex (SLC), Ground Range Detected (GRD), terrain-corrected backscatter, and interferograms.
A SAR antenna sends microwave pulses to one side of its flight path and records the returning echoes. Echo timing places each target across the track. As the platform moves, the same target returns echoes from many positions, and processing combines them into one sharp pixel, as if a single antenna as long as that stretch of the path had recorded them.
SAR is used for flood mapping, ship and oil spill detection, measuring ground deformation from earthquakes, volcanoes, and subsidence, charting sea ice, monitoring crops and forests, and mapping damage after disasters. Its main advantage is that it collects images at night and through cloud.
Synthetic aperture radar supplies its own illumination, so it images day and night, and its microwaves pass through cloud, smoke, and haze. It is sensitive to surface roughness, moisture, and structure, and the phase of its signal supports interferometry, which measures ground movement of centimeters or less from orbit.
Both are active sensors that measure echoes of their own signal. SAR uses microwaves with wavelengths of centimeters to a meter, images wide swaths from orbit, and works through cloud. LiDAR uses laser light, measures precise heights as a point cloud, and needs a clear line of sight, so clouds block it.
Bright pixels mean strong backscatter, and dark pixels mean weak backscatter. Calm water and smooth pavement appear dark because they reflect energy away from the sensor. Rough ground scatters energy back toward the sensor and appears brighter, vegetation appears in mid-gray tones from volume scattering, and buildings, ships, and flooded forest appear brightest from double-bounce reflections. Comparing images from two dates shows change.
Open SAR data is free. Copernicus distributes Sentinel-1 data through the Copernicus Data Space Ecosystem. NASA’s Alaska Satellite Facility DAAC distributes Sentinel-1 data and NISAR L-band data, and ISRO releases NISAR S-band data through its Bhoonidhi portal. Commercial SAR imagery from ICEYE, Capella Space, and Umbra is licensed.
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