Detecting Ships with Sentinel-1 SAR and Earth Engine

Name: Detecting Ships with Sentinel-1 SAR and Earth Engine
Rating: 2.5 (2 reviews)

Detect ships from space using Sentinel-1 SAR imagery and Google Earth Engine in a fully cloud-based remote sensing

Created byEarth's AI

Last updated 7/2025

English

What you'll learn

Understand the fundamentals of Synthetic Aperture Radar (SAR) imagery and Sentinel-1 data, including its applications for maritime monitoring.
Use Google Earth Engine (GEE) to load, filter, and preprocess Sentinel-1 VV polarization images for ship detection.
Apply spectral thresholding and water masking techniques to isolate ship-like structures from radar backscatter data.
Convert detected ships from raster to vector format and export results as GeoTIFFs and shapefiles for further GIS analysis.

Course content

1 section • 5 lectures • 53m total length

Lecture 1: Fundamentals of Remote Sensing13:19
In this lecture, you’ll learn the basic principles of remote sensing, including how satellites collect data about the Earth’s surface. We will cover the electromagnetic spectrum, spatial and spectral resolution, and the differences between optical and radar remote sensing. Understanding these fundamentals will help you grasp why radar data is crucial for maritime applications, especially in challenging weather conditions. This foundational knowledge sets the stage for working with Sentinel-1 data and processing satellite imagery effectively in later lectures.
Lecture 2: Sentinel-1 Satellite: How It Works, Polarization, and Noise11:51
Explore the Sentinel-1 Synthetic Aperture Radar (SAR) satellite’s technical details in this lecture. You’ll learn how Sentinel-1 uses radar waves to image the Earth’s surface, its different polarization modes (VV, VH), and how these affect data quality. We’ll also discuss common noise and speckle in SAR images and strategies for minimizing their impact. This knowledge is critical for accurate interpretation and preprocessing of SAR data for ship detection tasks.
Lecture 3: Introduction to Google Earth Engine (GEE)9:25
This lecture introduces Google Earth Engine, a cloud-based platform for planetary-scale geospatial analysis. You’ll learn how to navigate the GEE interface, access satellite data, and write simple scripts for image filtering, masking, and visualization. By the end, you’ll be familiar with the core tools needed to manipulate Sentinel-1 data in GEE and prepare for advanced processing workflows.
Getting Started with the Google Earth Engine Interface3:38
This section introduces the Google Earth Engine platform, guiding learners through accessing the Code Editor, understanding its interface, and exploring key panels like the script editor, map viewer, inspector, and data catalog. It helps beginners get comfortable navigating GEE before writing any code or performing analysis.
Lecture 4: Ship Detection Using Sentinel-1 in Google Earth Engine14:49
Dive into practical ship detection techniques using Sentinel-1 SAR imagery within Google Earth Engine. This lecture covers water masking, brightness thresholding to isolate ship candidates, and converting raster detections to vector polygons. You’ll learn how to visualize detected ships, export results for GIS analysis, and optimize your workflow for accuracy and efficiency in maritime monitoring applications.

Requirements

No prior experience with Google Earth Engine is required — the course will guide you step-by-step.

Description

This course equips learners with the skills to detect ships in coastal and offshore waters using Sentinel-1 Synthetic Aperture Radar (SAR) data and Google Earth Engine (GEE). Ship detection is a vital component of maritime domain awareness, helping governments, researchers, and industries monitor vessel traffic, ensure maritime security, and manage marine resources effectively. By learning to analyze radar imagery, students can overcome limitations of optical satellite data, such as cloud cover and darkness, allowing for reliable monitoring in all weather and lighting conditions.

Applications of the techniques covered include tracking commercial shipping routes, identifying illegal fishing or smuggling activities, supporting search and rescue operations, and assessing environmental impacts of maritime traffic. The course also serves as a foundation for broader remote sensing applications in oceanography and coastal management, such as oil spill detection, marine habitat monitoring, and coastal erosion assessment.

Using Google Earth Engine’s powerful cloud computing platform, learners gain hands-on experience processing large satellite datasets efficiently without needing specialized local hardware. Graduates of this course will be prepared to contribute to maritime safety, environmental monitoring, and geospatial analysis projects by implementing automated, scalable workflows for ship detection and mapping in real-world scenarios. This knowledge is essential for professionals working in environmental agencies, maritime logistics, defense, and scientific research.

Who this course is for:

Students, researchers and professionals in agriculture, environmental science, geography, or remote sensing looking to apply satellite data in real-world scenarios.