Introduction to Google Earth Engine (GEE)

Get started with geospatial data by applying the JavaScript programming language

What you’ll learn
Google Earth Engine (GEE)
Basics of Google Earth Engine oriented JavaScript (JS) Programming language
Working with vector and raster datasets
Reducing and Clipping image collectionFiltering the feature or image collection
Automation
Requirements
Geographic information basics
Description
Google Earth Engine is a platform for scientific analysis and visualization of geospatial datasets, for academic, non-profit, business and government users.

Google Earth Engine hosts satellite imagery and stores it in a public data archive that includes historical earth images going back more than forty years. The images, ingested on a daily basis, are then made available for global-scale data mining.

Earth Engine also provides APIs and other tools to enable the analysis of large datasets.

Google Earth enables you to travel, explore, and learn about the world by interacting with a virtual globe. You can view satellite imagery, maps, terrain, 3D buildings, and much more.

Earth Engine, on the other hand, is a tool for analyzing geospatial information. You can analyze forest and water coverage, land use change, or assess the health of agricultural fields, among many other possible analyses.

While the two tools rely on some of the same data, only some of Google Earth’s imagery and data is available for analysis in Earth Engine.

#AulaGEO

In this course you will learn

Google Earth Engine Course overview

Introduction

GEE background

GEE applications

GEE Pre-requirements

Basics of Google Earth Engine oriented JavaScript (JS) Programming language

Basic programming concepts

Mostly used GEE JS API syntax

How to write efficient code guide

Working with vector and raster datasets

Where to get different datasets for GEE

How to import and visualize vector datasets

How to import and visualize raster datasets

How to import your own vector or raster dataset in GEE

Filtering the feature or image collection

The need for filtering datasets

Different types of filters

When and where to use filters

Reducing and Clipping image collection

The role of reducers

Different types of reducers

Converting image collections into single image

Operators

Use of operators in programming

Efficient use of Operators in GEE

Evaluating NDVI using operators

Automating the analysis in GEE

The need of automation in GEE

The concept of For-Loops (with reference to Python)

Implementation of For-Loops in GEE using “.Map” function.

Who this course is for
GIS users
GIS developers
Dadabase managers
Geospatial enthusiasts
Developers