Sensors
- Sentinel-1 SAR (C-band, ESA): 10 m ground resolution in Interferometric Wide Swath mode, 6-day repeat at the equator (12-day per satellite, but two satellites give combined 6-day). Cloud-penetrating radar detects oil slicks as dark patches through Bragg-scattering suppression; cross-polarisation (VV/VH) helps distinguish biogenic films from crude. Free archive from 2014.
- Sentinel-2 MSI (ESA): 10 m visible and near-infrared bands, 20 m shortwave infrared. Five-day revisit with both satellites. Near-infrared (Band 8) and red-edge bands reveal vegetation dieback from hydrocarbon contamination as a suppressed NDVI signal. Cloud cover over the Niger Delta frequently blocks optical acquisition; usable scenes may arrive only every 2–4 weeks in the wet season.
- Landsat 8/9 OLI (USGS/NASA): 30 m multispectral, 16-day revisit per satellite (8-day combined). Longer archive (Landsat 8 from 2013, Landsat 9 from 2021) supports multi-year trend analysis of vegetation dieback and spill extent. Thermal Infrared Sensor (TIRS) can flag warm-water anomalies near refining activity, though spatial resolution (100 m resampled to 30 m) limits point-source attribution.
- Maxar WorldView-3: 0.31 m panchromatic, 1.24 m multispectral, 8-band VNIR plus 8 SWIR bands. Sufficient resolution to identify hoses, flexible pipelines, storage bladders and small tanker vessels when cloud permits tasking. Revisit over a fixed point is typically 1–4.5 days depending on latitude and collection angle, but cloud cover over the Delta makes guaranteed optical acquisition unreliable.
- VIIRS Day/Night Band (NOAA/NASA Suomi-NPP, NOAA-20): 750 m resolution nighttime visible band. Flaring and open burning at artisanal refining sites produce persistent light anomalies detectable nightly. Not useful for slick geometry, but effective for locating active refining clusters and tracking their persistence over time.
What a slick looks like to a radar satellite
Synthetic aperture radar works by measuring the roughness of a water surface. Wind-driven capillary waves, the centimetre-scale ripples that radar C-band energy interacts with through Bragg scattering, create a characteristically bright return. Crude oil suppresses those waves. The surface flattens, backscatter drops, and the slick appears as a dark patch against the surrounding water. Sentinel-1, operating at C-band with 10 m resolution in Interferometric Wide Swath mode, resolves slick boundaries clearly enough to estimate area and, with repeat passes, track drift direction.
The ambiguity problem is real and should not be understated. Biogenic films (algal surfactants, natural seeps), rain cells, low-wind shadow zones and certain current boundaries all produce similar dark patches. Cross-polarisation analysis, specifically the ratio of VV to VH backscatter, helps: mineral oil suppresses both polarisations differently from most biogenic films. Wind speed is the critical confound. Below roughly 2–3 m/s the whole surface flattens regardless; above about 10–12 m/s wave energy breaks up thin films. Detections outside that window require caution.
Vegetation tells a slower story
Crude oil that reaches soil kills mangrove and riparian vegetation. The signal is not immediate, but it is durable. Chlorophyll absorption in the red band and strong near-infrared reflectance from healthy canopy produce a high NDVI. Hydrocarbon-stressed or dead vegetation loses that near-infrared reflectance while red absorption also drops, pushing NDVI toward zero or below. Sentinel-2 Band 8 (NIR, 10 m) and Band 4 (red, 10 m) resolve this change at the scale of individual creek margins.
Published academic work on the Niger Delta, including studies using Landsat time series going back to the 1980s, documents persistent NDVI depression around known spill sites lasting years after the original release. That archive depth is analytically valuable: it allows an investigator to date the approximate onset of contamination, distinguish acute spill events from chronic seepage, and map cumulative impact across a watershed. The limitation is cloud. During the Niger Delta wet season, consecutive cloud-free Sentinel-2 acquisitions may be separated by weeks, which blurs the timeline of a fast-moving operation.
When optical resolution actually matters
Slick detection and vegetation dieback analysis tell you something happened. They do not tell you where the tap is, what infrastructure is present, or whether a vessel is actively loading. That requires sub-metre optical imagery. WorldView-3 at 0.31 m panchromatic can resolve hose connections at a pipeline crossing, a barge's deck equipment, and the colour contrast between crude and creek water. At 1.24 m multispectral, the eight VNIR bands add spectral discrimination that separates crude oil sheen from turbid sediment plumes.
The practical constraint is cloud. The Niger Delta sits in a humid tropical regime with persistent convective cloud cover for much of the year. A tasked WorldView-3 collect may return cloud-contaminated imagery on the first attempt, the second, and the third. Operational planning must account for this: SAR provides the all-weather baseline, and VHR optical is used opportunistically to confirm and characterise what radar has flagged. Treating optical as the primary sensor in this environment will produce gaps exactly when enforcement interest is highest.
Nighttime light as a refinery locator
Artisanal refineries in the Delta burn off light fractions and produce open flames visible to the VIIRS Day/Night Band at 750 m resolution. VIIRS overflies every point on Earth nightly. A persistent cluster of nighttime light anomalies in a creek area with no registered industrial activity is a meaningful signal. The VIIRS Nightfire product, produced by the Colorado School of Mines Earth Observation Group and publicly archived, provides temperature and radiant heat estimates for detected fires, which can help distinguish cooking fires and agricultural burning from hydrocarbon combustion.
The resolution floor matters here. At 750 m, VIIRS cannot localise a refinery to a specific creek junction. It identifies a zone of interest, typically 1–3 km across, that then requires SAR or VHR optical follow-up to resolve. Used in combination, the workflow is tractable: VIIRS flags the active area nightly, Sentinel-1 maps the slick extent on a 6-day cycle, and a WorldView-3 task is placed for the next cloud-free window.
What multi-sensor fusion actually delivers to an enforcement client
The most useful analytic product is not a single detection but a change-detection time series that shows when a site became active, how its slick footprint evolved, whether nighttime light indicates refining rather than simple transshipment, and whether vegetation dieback is expanding. That combination makes it substantially harder for an operator to claim a slick is a natural seep or that a barge was moored innocently. Each sensor layer adds a dimension of evidence.
Satellize runs this kind of multi-source fusion on open constellations, with commercial tasking added on client licence. The Tonga crop-estimation programme is a different domain, but the underlying pipeline, ingesting Sentinel and Landsat time series, applying change-detection algorithms, and delivering georeferenced outputs, transfers directly to enforcement contexts. An honest caveat: satellite evidence identifies sites and tracks activity patterns. It does not, on its own, identify the individuals responsible or establish legal chain of custody. It is an intelligence layer that directs ground investigation, not a substitute for it.
Honest limits of the method
Several constraints deserve plain statement. Small taps on buried onshore pipelines may produce no surface slick if the crude is immediately collected; SAR will miss them entirely until a spill reaches water. Slicks smaller than roughly one Sentinel-1 pixel (10 m) are below reliable detection. Very fresh crude weathers quickly in tropical heat, reducing its film-forming properties and shrinking the detection window to hours in some conditions. And the 6-day Sentinel-1 revisit, while useful for trend analysis, means a bunkering operation that loads and disperses in under 48 hours may leave no radar trace at all.
None of these limits invalidate satellite monitoring. They shape what questions it can reliably answer. Persistent sites, chronic seepage, growing vegetation dieback, recurring nighttime light anomalies, and vessels that linger for days are all well within detection capability. Opportunistic, fast-moving operations that leave clean water behind them are not. Knowing which category a target falls into is the first question an enforcement client should put to any analyst.
Typical figures
| SAR spatial resolution (Sentinel-1 IW mode) | 10 m ground range |
| Optical spatial resolution (Sentinel-2 MSI) | 10 m (VNIR), 20 m (SWIR) |
| VHR optical resolution (WorldView-3) | 0.31 m panchromatic, 1.24 m multispectral |
| SAR revisit (Sentinel-1, two-satellite constellation) | 6 days at equator |
| Optical revisit (Sentinel-2, two-satellite constellation) | 5 days clear-sky; effective wet-season revisit in Niger Delta typically 2–4 weeks |
| Nighttime fire detection revisit (VIIRS DNB) | Nightly global coverage |
| Minimum detectable slick area (Sentinel-1 SAR) | Approximately 0.01 km² under favourable wind conditions (3–10 m/s) |
| Sentinel-1 archive depth | From 2014 (Sentinel-1A); Sentinel-1B data 2016–2021 |
| Landsat archive depth | Landsat 8 from 2013; Landsat 9 from 2021; earlier missions from 1972 |
| Delivery formats | GeoTIFF change layers, GeoJSON site polygons, PDF intelligence reports, GIS-ready vector alerts |
Analytics Satellize can run
| Oil slick detection and extent mapping | SAR dark-spot detection using Bragg-scattering suppression; cross-polarisation (VV/VH) ratio filtering to reduce false positives from biogenic films and low-wind zones | Georeferenced slick polygon layer per Sentinel-1 pass, with area estimate and confidence flag |
| Vegetation dieback time series | NDVI differencing on Sentinel-2 and Landsat OLI time series; anomaly detection against a pre-disturbance baseline | Annual and quarterly NDVI change maps with contamination-onset date estimates per affected creek segment |
| Persistent nighttime light anomaly alerts | VIIRS Day/Night Band and Nightfire product analysis; clustering of persistent anomalies against a no-industry baseline | Monthly report of active artisanal refinery zone candidates with coordinates and radiance trend charts |
| Vessel presence and loitering detection | VHR optical change detection (WorldView-3) on cloud-free acquisitions; vessel segmentation by size, shape and spectral contrast | Annotated image report with vessel position, estimated length, and mooring duration where multi-date imagery permits |
| Multi-sensor site dossier | Fusion of SAR slick history, NDVI dieback extent, VIIRS light anomalies and available VHR optical into a single site record; timeline reconstruction from archive data | PDF intelligence dossier per priority site, with evidence layers exportable to GIS |
| Change-alert feed for active monitoring | Automated SAR ingestion on each Sentinel-1 overpass; threshold-based slick detection triggering alert if a new or expanded dark patch appears within a defined area of interest | Near-real-time GeoJSON alert pushed to client platform within 24 hours of satellite overpass |
Who does the work
We can get this done for you. Satellize runs its own analyst desk and a strong science team. You do not buy a data feed and work out what it means; our people source the imagery, run the analysis described on this page, and hand you the answer with its confidence limits stated. Discuss this requirement.