Process SAR & Multispectral

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Process SAR & Multispectral

Coursera · Beginner ·👁️ Computer Vision ·1mo ago
Skills: CV Basics80%
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.
Watch on External: Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related AI Lessons

Can AI Change an Entire Outfit in a Video at Once?
Learn how AI can change an entire outfit in a video at once with OmniTryOn, a revolutionary technology that enables virtual try-on capabilities
Medium · AI
I Built an AI Bot That Counts Calories From a Photo of Your Plate
Learn how to build an AI bot that counts calories from a photo of your plate using Python, leveraging computer vision and machine learning techniques
Medium · Python
Algo(31/40)Real-World Perception & Action: Pixels, Boxes & Trust (2015)
Learn how neural networks can be applied to real-world perception and action, enabling self-driving cars to detect and respond to their environment.
Medium · Deep Learning
Teaching a Logo Detector to Say “I Don’t Know”
Learn to build a brand recognition pipeline with uncertainty estimation using LogoDet-3K and Python, and understand the importance of handling unknown cases
Medium · Python
Up next
Unsupervised Learning: Uncover Hidden Patterns & Data Secrets!
The AI Standard
Watch →