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Machine Learning and Land Cover Mapping with Earth Engine

March 16 @ 9:00 am - 1:00 pm


Google Earth Engine is a cloud-based platform that enables large-scale processing of satellite imagery to detect changes, map trends, and quantify differences on the Earth’s surface. This course will introduce you to machine learning techniques for land cover mapping using the Earth Engine cloud computing platform. 

The course will cover the following topics

Module 1: Google Earth Engine Fundamentals

  • Sign up for Earth Engine Account
  • Hello World
  • Basic Javascript Data Types
  • Earth Engine Objects
  • ClientServer versus Servser Side Objects
  • Image Visualization
  • Filtering Image Collection
  • Image Composites
  • Export Image to Google Drive

Module 2: Introduction to Machine Learning

  • Why Machine Learning
  • Supervised versus Unsupervised Classification
  • Types of Supervised Classification
  • Supervised Classification Workflow
  • Accuracy Assessment
  • Change Detection

Module 3: Unsupervised Classification

  • Clustering with Landsat Data
  • Clustering with Sentinel Data

Module 4: Collect Training Data

  • Training Data Export to Google Drive
  • Training Data Export to EE Asset

Module 5: Supervised Classification 

  • Supervised Classification
  • Accuracy Assessment
  • Improve Model Accuracy
  • Export Model Results
  • Compute Classification Area

Module 6: Change Detection Analysis 

  • Temporal Change Detection
  • Post Classification Evaluation


March 16
9:00 am - 1:00 pm