Skill Built 24x7: Online Courses

Google Earth Engine: Basic to Advanced (Recorded Class)

4.6 Basic to Advance Self-Paced (20 Hours of Recorded Content) Very Soon

Instructor - Highly Proficient in Remote Sensing, Geospatial Data Analysis, and GEE

Course Overview

Master Google Earth Engine (GEE) at your own pace with this comprehensive recorded course. Designed for beginners to advanced users, this course covers satellite image processing, spatial analysis, machine learning, and time-series analysis using GEE. You will learn to work with remote sensing datasets, develop geospatial workflows, and perform land cover classification efficiently using cloud computing.
With step-by-step tutorials and real-world case studies, this course provides practical knowledge for environmental monitoring, agricultural analysis, and disaster assessment.

Why Enroll in This Course?

Self-Paced Learning – Study at your convenience with recorded lessons.
Comprehensive Coverage – From basic GEE operations to advanced classification and ML applications.
Real-World Applications – Work on projects in agriculture, forestry, climate change, and urban mapping.
Downloadable Learning Materials – Access PDFs, PPTs, and ready-to-use code scripts.
Expert-Led Training – Learn from instructors with deep expertise in GEE and remote sensing.

Who Should Take This Course?

Students & Researchers – Utilize GEE for academic research and geospatial studies.
GIS & Remote Sensing Professionals – Enhance geospatial data processing skills.
Environmental Scientists & Land Managers – Perform geospatial analysis for sustainable planning.
Data Scientists & Machine Learning Enthusiasts – Implement ML techniques on satellite imagery.

Course Features

Full HD Recorded Classes – High-quality lectures covering basic to advanced GEE concepts.
Comprehensive Study Materials – Downloadable scripts, guides, and step-by-step tutorials.
Hands-On Learning – Work on practical geospatial projects using real-world datasets.
Multi-Device Access – Study anytime, anywhere on mobile, laptop, or PC.
Lifetime Access – Revisit lessons and upgrade your skills whenever needed.

Course Outcomes

By the end of this course, you will be able to:

Process, analyze, and visualize satellite data using GEE’s cloud-based platform.
Perform spatial analysis and land cover classification using machine learning models.
Use remote sensing techniques for environmental and agricultural applications.
Calculate and interpret vegetation indices (NDVI, EVI, SAVI) for monitoring vegetation health.
Conduct time-series analysis and change detection for land use and climate studies.

Enroll Now and become an expert in Google Earth Engine with Recorded Classes!

Topics of Course

Basic Topic :

Introduction to Google Earth Engine

Overview of Google Earth Engine (GEE) and its applications

Advantages of cloud-based geospatial analysis

Understanding the GEE Code Editor and Explorer

Accessing and visualizing global satellite datasets

Understanding Remote Sensing Data

Basics of remote sensing and its significance

Types of satellite imagery (optical, radar, thermal)

Spatial, temporal, and spectral resolution

Common satellite datasets available in GEE (Landsat, Sentinel, MODIS)

GEE Interface and Basic Functions

Navigating the GEE Code Editor

Using the JavaScript API in the code editor

Loading and displaying imagery on the map

Basic image and feature visualization techniques

Understanding image collections and feature collections

Basics of JavaScript for Google Earth Engine

Introduction to JavaScript syntax and GEE scripting

Variables, functions, loops, and conditionals in GEE

Working with GEE objects (Images, Collections, Features)

Filtering and reducing datasets

Exporting results (maps, tables, charts)

Advance Topics :

Working with Vector and Raster Data

Differences between raster and vector data

Loading, visualizing, and manipulating shapefiles

Clipping and masking raster datasets

Converting between vector and raster formats

GIS-Based Work on Google Earth Engine

Performing spatial analysis using GEE

Buffering, intersecting, and merging vector data

Zonal statistics and area calculations

Overlay and proximity analysis

Machine Learning Applications in GEE

Introduction to machine learning in remote sensing

Supervised vs. unsupervised classification

Preprocessing data for machine learning models

Implementing classification workflows in GEE

Supervised Classification (SVM, Random Forest)

Training data collection and feature selection

Implementing Support Vector Machine (SVM) classification

Applying the Random Forest algorithm in GEE

Accuracy assessment using confusion matrices

Unsupervised Classification (K-means)

Concept of clustering and unsupervised learning

Implementing K-means classification in GEE

Evaluating and interpreting classification results

Multiple Indices Analysis

Understanding spectral indices and their applications

NDVI, NDBI, NDWI, and other vegetation indices

Computing and visualizing indices using GEE

Advanced Data Analysis Techniques

Image compositing and mosaicking

Multi-temporal analysis and data fusion

Principal Component Analysis (PCA) in GEE

Time Series Trend Analysis

Understanding time-series remote sensing analysis

Extracting and visualizing temporal trends

Implementing Theil-Sen, Mann-Kendall trend analysis

Identifying seasonal and long-term changes

Change Detection Methods

Techniques for detecting land cover change

Image differencing, change vector analysis, and thresholding

Implementing change detection using supervised and unsupervised approaches

Case Studies and Applications

Real-world applications of Google Earth Engine

Environmental monitoring

Deforestation analysis, urban expansion monitoring

Custom project development and final review

999/-

ENROLL NOW

Course Name :-

Google Earth Engine Basic to Advance (Recorded Class)

Instructor:-

Highly Proficient

Category:-

Basic to Advanced

Level:-

Beginner to Advanced

Duration:-

Self-Paced (20 Hours of Recorded Content)

Mode:-

Recorded Sessions

Access:-

Mobile, Laptop, PC

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Requirements

At SkillBuilt 24x7, we welcome everyone who's ready to grow—no experience needed! Here's all you need to get started:

No need for basic coding knowledge – we start from scratch

Beginner-friendly – perfect for absolute newcomers

Just bring your curiosity and eagerness to learn new things

A laptop is a must – your gateway to hands-on learning

No prior concepts required – we’ll teach you everything step by step

Course