How to Detect Floods in Satellite Imagery, Case Study: Dubai Flooding | by Mahyar Aboutalebi, Ph.D. 🎓 | Apr, 2024


Detecting and monitoring flooded areas in satellite imagery with a simple classification approach

Towards Data Science

11 min read

2 hours ago

Over the weekend, as I scrolled through my Twitter feed, I saw the news about Dubai Airport getting flooded during a rare storm (more than 250 mm of rainfall in 24 hours!!). I hoped to find clear satellite images to demonstrate a simple method of separating flooded and non-flooded areas. Luckily, Sentinel-2 captured two images on April 7th (pre-flood event) and 17th (post-flood event), mostly free of clouds over Dubai. Those images sparked my interest in writing a story about detecting flood events using satellite images.

In this post, we begin by downloading Sentinel-2 imagery of a flooded location in Dubai using a Python script. Then, we’ll use the rasterio package to read the imagery and compute the Normalized Difference Water Index (NDWI) using near-infrared and green bands. Afterward, we’ll plot histograms of NDWI for both pre and post-flood images. Comparing these histograms will reveal how dry areas in the pre-flood image shifted to wet areas in the post-flood image. Finally, we’ll separate the flooded pixels using a threshold extracted from the histogram analysis and map the flooded regions. If this sounds interesting, keep reading!

  1. 🌅 Introduction
  2. 💾 Downloading Sentinel-2 Imagery
  3. ⚙️ Clipping and Stacking Multispectral Bands
  4. 📐 Calculation of NDWI
  5. 📊 NDWI Histogram
  6. 🗺️ Visualization of Flooded Areas
  7. 📄 Conclusion
  8. 📚 References

🌅 Introduction

Monitoring floods from the sky is quite a challenge, but it offers many benefits. The main challenge is that most flood events happen under cloudy skies, caused by heavy rainfall and overflowing rivers and canals. This cloud cover often makes it hard to get clear images in visible and infrared bands.

However, accurate flood detection offers numerous benefits for agencies and insurance companies. Accurately identifying flooded areas enables prioritization of evacuation plans. Insurance companies can also assess flood risk, informing their business strategies and determining insurance premium costs.

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