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Process SAR & Multispectral

This course is part of Satellite Imagery, Remote Sensing & Machine Learning Specialization

Instructor: ansrsource instructors

Included with

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3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Process SAR imagery for flood mapping when clouds block optical data, applying speckle filtering to improve clarity
Detect post-disaster changes using multispectral imagery to identify areas where flooding altered surface conditions
Evaluate analysis reliability using accuracy metrics and identify limitations before sharing disaster response results

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

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This course is part of the Satellite Imagery, Remote Sensing & Machine Learning Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

Process SAR & Multispectral is a short course for learners who want to move beyond viewing satellite imagery and begin producing structured geospatial analysis. Designed for those with basic familiarity with maps and raster imagery, the course introduces practical techniques for interpreting and analyzing satellite data in a disaster-response scenario: estimating flood extent after a major storm.

You will first work with Synthetic Aperture Radar (SAR), learning why it is essential when clouds block optical imagery and how speckle filtering can improve interpretability while introducing analytical trade-offs. The course then transitions to multispectral imagery, where you explore change detection across time to identify areas where surface conditions may have shifted after the storm. Finally, you will evaluate whether your results are reliable enough to share by interpreting simple accuracy metrics and identifying limitations in your analysis. Through guided videos, applied exercises, and scenario-based assessments, you will build both technical understanding and analytical judgment—preparing you for more advanced geospatial analysis workflows.

Module details

In this module, you are introduced to SAR as a practical disaster-response data source that remains available even when optical imagery is blocked by clouds. You focus on one core barrier to using SAR confidently: speckle. Rather than treating speckle as a vague “noise problem,” you learn what it looks like, why it occurs, and how filtering changes interpretability. The module is designed to develop judgment: you learn to apply speckle filtering, compare outcomes, and reason about trade-offs because aggressive smoothing can hide meaningful edges while weak filtering may leave the scene unreadable.

What's included

2 videos1 reading1 assignment

In this module, you move from preprocessing to analysis. Using multispectral imagery captured across time, you perform change detection to identify where surface conditions shifted after a storm event. The module emphasizes interpretive reasoning: you learn that a “change map” is not automatically a flood map, and you must think about what the change signal could represent. You also learn how to structure your outputs so you can communicate results clearly, highlighting what changed, where confidence is higher, and what limitations remain.

What's included

1 video1 reading2 assignments

1 videoTotal 3 minutes

Change Detection That Means Something: Comparing Before and After3 minutes

1 readingTotal 6 minutes

Interpreting Multispectral Change: What Counts as Evidence and What Counts as Noise6 minutes

2 assignmentsTotal 25 minutes

Hands-on Learning: Detect Flood-Extent Change After a Storm Using a Multispectral Stack15 minutes
Practice Quiz: What Does This Change Signal Actually Mean?10 minutes

The final module teaches you the habit that makes your work trustworthy: evaluation. You learn that classification outputs can look convincing while still being wrong in critical ways. The module introduces beginner-friendly accuracy evaluation concepts and asks you to make judgment calls: is this accurate enough for the decision at hand, and what would you disclose as limitations? This module ties directly to operational credibility because in real flood response, the cost of being confidently wrong is high.

What's included

2 videos1 reading2 assignments

2 videosTotal 8 minutes

Accuracy Isn’t Optional: How to Know If Your Map Is Trustworthy5 minutes
Congratulations and Your Next Step in Geospatial Data Science3 minutes

1 readingTotal 10 minutes

Beginner Accuracy Evaluation: Confusion Matrix Thinking Without the Overwhelm10 minutes

2 assignmentsTotal 35 minutes

Hands-on Learning: Evaluate Classification Results for Flood Detection15 minutes
Graded Assessment: Flood Extent Evidence: Process, Detect, Evaluate20 minutes