SARry polluters, you’re no match for Sentinel-1

A look at how radar imagery can detect offshore oil pollution in Nigeria

Sentinel Hub Blog
Published in
4 min readOct 27, 2021


A guest blog post by Line of Actual Control

Foreword by Sentinel Hub

This post is part of a series of guest blog posts written by authors talking about their entries to the Sentinel Hub Custom Script Contest. The author is one of the winners of our special edition of the Contest — Urban Growth in Africa — which ran from May to September 2021. A described story won the award for best written story using Earth Observation data.

I began researching oil spills in Nigeria earlier this year, after a Dutch court ruled Shell liable for damages caused by the company’s oil spills. I wanted to see if there was a way for remote sensing to help environmental activists, journalists, policymakers, and others keep an eye on this pollution. Unfortunately, the areas in which the spills occurred are quite cloudy and it was really difficult to find enough cloudless visual imagery to track the spills over time. Cloud shadows, river sediment, and an oil spill all mix together in this visual imagery, making it hard to distinguish one from the other.

Cloud shadows, river sediment, and an oil spill all mix together in this visual imagery, making it hard to distinguish one from the other. Credit: Google Earth

However, that was no obstacle for SAR imagery. As it turns out, SAR imagery and pollution tracking are a perfect match. The satellites’ cloud-piercing radar beams sensed where ocean water was slack and motionless — indicating that there might be oil on the surface in those areas — rather than windswept and choppy. While it’s sometimes tough to tell for certain, oil slicks are often smoother than the open ocean because oil absorbs the energy of ocean waves and wind can’t gain purchase over the slick, oily water.

While researching the piece, Sentinel Hub’s repository of custom scripts was a gold mine. I don’t have much experience building custom remote sensing scripts on my own, so being able to try a number of scripts to see what worked best in my visualizations was key.

After evaluating a few, I settled on a script originally built by Annamaria Luongo at SpaceTec Partners. I really liked how starkly it showed the difference between clean water and oil slicked water. However, it still rendered the image in greyscale. I added a pixel threshold to turn the land green, (most) of the sea blue, and the oil spill red. Simple, but hopefully effective.

var spill = Math.log(0.05/(0.018+VV * 3.5)); 
if (spill > 0.35) {
return [1,0,0]
return [0, VV * .7, spill * 2] }
From greyscale (top) to color (bottom). Data credit of Sentinel Hub, visualization by author. Unprocessed image linked here.

Sentinel Hub’s timelapse feature was one of the most crucial components of the piece. While showing one image at one point in time is great and all, I also needed a way to visually explain how the spills changed and grew over time.

Enter the timelapse. Using Sentinel Hub, it was a breeze to plot nearly 20 separate Sentinel-1 images. Not only did the timelapse allow me to show how the spills grew over time, but they actually allowed me to pinpoint the likely sources of the pollution.

Notice how the plumes of oil come from two different spots. Credit: Sentinel Hub.

Two final Sentinel Hub features helped support my piece as well. The area measurement tool allowed me to quantify the impact and extent of the spills far better than a simple eyeball measurement, while the line measurement tool helped me determine how far the source of the spill was from land. This distance, in turn, let me zoom in and find high-resolution imagery of the oil rig responsible for one of the spills.

Credit: Sentinel Hub. Unprocessed image linked here.

All together, Sentinel Hub was an indispensable tool in researching, writing, and designing this piece and I’m looking forward to incorporating more Sentinel imagery into my future writing. If you have suggestions or want to read more, feel free to comment below, sign up, or email me at Happy pollution spotting!

The Sentinel Hub team would like to thank LineofActualControl for their participation in our Contest.

To learn more about satellite imagery and custom scripts, we recommend the Sentinel Hub Educational page and the Custom Scripts webinar. If you are interested in how journalism can benefit from satellite imagery, read one of Pierre Markuse’s blog posts. You can also visit a dedicated topic in the Sentinel Hub Forum for more information. We’d also like to invite you to take a look at the other entries submitted to the Sentinel Hub Custom Script Contests, which can be found here and here.

Stay tuned for our next Contest which will highlight a burning issue in the world today. We look forward to receiving your submissions.

If you want to learn more about Sentinel Hub, make sure to listen the MapScaping Podcast:



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