Introduction to Google Earth Engine (GEE) - AulaGEO

🚀 Introduction to Google Earth Engine (GEE) by AulaGEO Academy 🌐

Are you ready to embark on a journey through the vast universe of geospatial data? With Google Earth Engine, you can tap into a unique platform that combines the power of scientific analysis with rich visualization capabilities. Whether you're in academia, a non-profit, business, or government, GEE is your gateway to understanding our planet like never before.

🔍 What is Google Earth Engine? Google Earth Engine hosts an impressive array of satellite imagery, dating back over four decades. This public data archive is updated daily and is a treasure trove for global-scale data mining. GEE's powerful APIs and tools enable users to conduct complex analyses on environmental, agricultural, and natural resources issues.

🌍 Exploring Google Earth While Google Earth allows you to visually explore the world with interactive globe views, satellite imagery, maps, terrain, and 3D buildings, Google Earth Engine is designed for a more analytical approach. With GEE, you can assess forest coverage, monitor water bodies, analyze land use change, and much more—all using powerful geospatial data analysis techniques.

🎓 Course Overview In this comprehensive course by AulaGEO Academy, you'll dive into the world of GEE with a structured learning path. We'll cover:

• Introduction to Google Earth Engine

  • GEE background
  • GEE applications
  • Pre-requirements for GEE

• Basics of Google Earth Engine and JavaScript Programming Language

  • Understanding basic programming concepts
  • Getting familiar with the most commonly used GEE JS API syntax
  • Learning how to write efficient code with best practices

• Working with vector and raster datasets

  • Sources for acquiring various datasets in GEE
  • Techniques for importing and visualizing vector datasets
  • Methods for importing and visualizing raster datasets
  • Steps to import your own data into GEE

• Filtering the feature or image collection

  • The importance of filtering datasets for efficient analysis
  • Types of filters and how to apply them effectively
  • Techniques for reducing and clipping image collections for targeted analysis

• The role of reducers in Google Earth Engine

  • Exploring different types of reducers available in GEE
  • Learning to convert image collections into single images using reducers
  • Understanding the use of operators in GEE for advanced data manipulation

• Automating the analysis in Google Earth Engine

  • The significance of automation in large-scale geospatial analysis
  • Introduction to programming concepts like For-Loops, with a focus on Python syntax
  • Implementing For-Loops in GEE using the “.Map” function for repetitive tasks
  • Evaluating NDVI (Normalized Difference Vegetation Index) as a practical example of GEE analysis

By the end of this course, you'll have a solid understanding of how to navigate, analyze, and manipulate geospatial data using Google Earth Engine. You'll be equipped with the knowledge to conduct your own analyses, whether for environmental monitoring, agricultural assessment, or urban planning. 📊

Join us at AulaGEO Academy and unlock the potential of geospatial analysis with Google Earth Engine! 🌟

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