Mastering Google Earth Engine: Geospatial Analysis & Remote Sensing for Impact

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Why Learn Google Earth Engine?

Google Earth Engine (GEE) is a cloud-based geospatial analysis platform that allows users to process massive datasets efficiently. It is widely used in environmental monitoring, land use planning, disaster management, and climate research. This course will help you leverage GEE for data-driven insights and impactful decision-making.

What You Will Learn

  • Fundamentals of Google Earth Engine and its cloud-based computing power
  • Accessing and visualizing satellite imagery and geospatial datasets
  • Writing and optimizing scripts using the JavaScript API
  • Performing raster and vector analysis for environmental and urban studies
  • Applying remote sensing techniques for land cover classification
  • Integrating Google Earth Engine with Python for advanced analytics
  • Using machine learning models to extract insights from geospatial data

Who Should Take This Course?

This course is designed for:
✔️ GIS professionals and remote sensing specialists
✔️ Environmental scientists and researchers
✔️ Urban planners and land management experts
✔️ Students and enthusiasts eager to explore geospatial technology
✔️ Developers and data scientists looking to integrate GEE into their workflows

Why This Course Stands Out

  • Hands-on Learning: Practical projects with real-world geospatial datasets
  • Step-by-Step Guidance: Beginner-friendly explanations progressing to advanced topics
  • Industry-Relevant Applications: Learn techniques used in climate studies, forestry, agriculture, and more
  • Python & JavaScript Integration: Enhance your scripting skills for automation and advanced analysis

Get Ready to Master Google Earth Engine!

By the end of this course, you will have the confidence to perform large-scale geospatial analysis, automate workflows, and extract meaningful insights from remote sensing data

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What Will You Learn?
  • Google Earth Engine (GEE) is a powerful cloud-based geospatial analysis platform that enables large-scale environmental monitoring, remote sensing, and spatial data processing. This course provides a hands-on approach to learning GEE, guiding you from the fundamentals to advanced applications such as machine learning, land cover classification, and time-series analysis.
  • Through interactive lessons, real-world case studies, and coding exercises, you’ll gain the skills to harness the full potential of GEE for geospatial data analysis. Whether you’re a beginner or an experienced GIS professional, this course will empower you to analyze, visualize, and automate geospatial workflows effectively.
  • 1. What Will I Learn?
  • By the end of this course, you will be able to:
  • ✅ Navigate and use the Google Earth Engine Code Editor
  • ✅ Import, process, and visualize satellite imagery and geospatial datasets
  • ✅ Apply remote sensing techniques such as NDVI, NDWI, and change detection
  • ✅ Perform spatial analysis with vector and raster data
  • ✅ Implement land cover classification using machine learning models
  • ✅ Integrate Google Earth Engine with Python for automation and advanced analysis
  • ✅ Work on real-world geospatial projects, including climate monitoring, deforestation tracking, and disaster response

Requirements

  • Prerequisites:
  • No prior experience in Google Earth Engine required (but helpful)
  • Basic knowledge of GIS, remote sensing, or programming (Python/JavaScript) is beneficial
  • A Google account to access Google Earth Engine
  • 🔹 Technical Requirements:
  • A computer with a stable internet connection
  • A modern web browser (Chrome, Firefox, or Edge recommended)
  • Optional: Python installed for GEE-Python API integration

Audience

  • Target Audience
  • This course is designed for:
  • ✔️ GIS professionals and remote sensing specialists
  • ✔️ Environmental scientists and climate researchers
  • ✔️ Urban planners and land management experts
  • ✔️ Students and geospatial technology enthusiasts
  • ✔️ Data scientists and developers looking to integrate GEE into their workflows
  • ✔️ Government agencies and NGOs working on environmental conservation

Course Content

Introduction to Google Earth Engine
Overview of GEE and its cloud-based computing capabilities Setting up your GEE account and navigating the Code Editor Understanding geospatial data types (raster vs. vector)

Geospatial Data Processing & Visualization
Accessing and visualizing satellite imagery Filtering, masking, and preprocessing geospatial datasets Working with time-series data and remote sensing indices (NDVI, NDWI)

Spatial Analysis & Machine Learning in GEE
Land cover classification using supervised and unsupervised learning Change detection analysis for environmental monitoring Integrating Google Earth Engine with Python for automation

Real-World Applications & Case Studies
Climate change monitoring and disaster response mapping Deforestation tracking and land use planning Agriculture monitoring and water resource management

Conclusion & Final Project
Applying acquired skills to a real-world geospatial problem Best practices for optimizing geospatial workflows in GEE Final project presentation and certification completion

A course by

MS
Martin Sure
Software Engineer

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Course Includes:

  • Price:
    Original price was: KSh100.00.Current price is: KSh34.00.
  • Instructor:Martin Sure
  • Duration: 32 hours 28 minutes
  • Lessons:0
  • Students:1
  • Level:Intermediate
KSh34.00 KSh100.00