Big Data Analytics In Gis Using Google Earth Engine Training Course

Introduction

As geospatial data grows in volume and complexity, Big Data Analytics in GIS has become essential for extracting meaningful insights. This Google Earth Engine (GEE) training course equips professionals with the skills to process, analyze, and visualize large-scale geospatial datasets using cloud-based computing. Participants will learn how to harness satellite imagery, climate data, and remote sensing analytics to make data-driven decisions. By integrating big data, machine learning, and spatial analysis, this course empowers learners to tackle real-world challenges in environmental monitoring, land use planning, disaster response, and more.

Target Audience

This course is designed for:
✅ GIS & Remote Sensing Professionals – Looking to scale their spatial data analysis using cloud-based GIS.
✅ Environmental Scientists & Climate Analysts – Using satellite data for monitoring land cover, deforestation, and climate trends.
✅ Urban Planners & Disaster Management Experts – Leveraging big data for real-time geospatial decision-making.
✅ Data Scientists & AI Specialists – Exploring geospatial big data with machine learning in Google Earth Engine.
✅ Researchers & Students – Seeking practical experience in handling massive geospatial datasets.

Course Objectives

By the end of this course, participants will:
✔ Understand Google Earth Engine (GEE) for Big Data GIS – Learn how cloud-based geospatial computing works.
✔ Work with Large-Scale Geospatial Datasets – Access and analyze satellite imagery, climate data, and land use records.
✔ Perform Advanced Remote Sensing Analytics – Process multi-temporal and multi-spectral satellite imagery for geospatial insights.
✔ Integrate Machine Learning with GIS – Use AI models for classification, change detection, and predictive analysis.
✔ Automate Geospatial Analysis – Develop scripts in GEE’s JavaScript and Python API for efficient data processing.
✔ Create Interactive GIS Visualizations – Build dynamic web maps and dashboards to present geospatial insights.
✔ Apply GIS Big Data Analytics to Real-World Problems – Work on case studies in environmental monitoring, agriculture, and disaster response.

This course empowers GIS professionals and data scientists to leverage Google Earth Engine for large-scale geospatial analysis, transforming raw geospatial data into actionable insights for smarter decision-making.

Duration

10 Days

Course content

This Big Data Analytics in GIS using Google Earth Engine (GEE) Training Course provides a structured, hands-on approach to processing and analyzing massive geospatial datasets using cloud-based computing. Below are 12 SEO-friendly course modules designed to equip GIS professionals, remote sensing experts, and data scientists with advanced geospatial analysis skills.

Module 1: Introduction to Google Earth Engine (GEE) & Big Data GIS

???? Overview of big data in GIS and remote sensing
???? Introduction to cloud computing for geospatial analysis
???? Setting up Google Earth Engine and navigating the platform

Module 2: Accessing & Managing Large Geospatial Datasets

???? Importing and processing massive satellite imagery datasets
???? Working with vector, raster, and time-series data in GEE
???? Cloud storage and data management best practices

Module 3: JavaScript & Python Scripting in Google Earth Engine

???? Understanding GEE’s JavaScript and Python API
???? Writing and executing scripts for geospatial analysis
???? Automating workflows for large-scale data processing

Module 4: Remote Sensing & Satellite Image Analysis in GEE

???? Accessing and processing Landsat, Sentinel, and MODIS imagery
???? Radiometric and geometric corrections of satellite images
???? Multi-spectral and multi-temporal data analysis

Module 5: Land Cover Classification & Change Detection

???? Supervised and unsupervised classification techniques
???? Detecting land use and land cover (LULC) changes over time
???? Applying classification algorithms in GEE

Module 6: Machine Learning & AI for Geospatial Big Data

???? Introduction to machine learning for GIS applications
???? Implementing random forests, decision trees, and deep learning models
???? Predictive modeling for spatial trend analysis

Module 7: Climate & Environmental Monitoring with GEE

???? Analyzing climate trends using remote sensing data
???? Monitoring deforestation, water bodies, and urban heat islands
???? Tracking carbon emissions and land degradation

Module 8: Disaster Risk Assessment & Early Warning Systems

???? Flood mapping and real-time disaster response using GEE
???? Earthquake and landslide risk modeling with satellite data
???? Wildfire monitoring and predictive analysis

Module 9: Agricultural & Vegetation Analysis Using GEE

???? Crop monitoring and yield prediction with satellite data
???? NDVI and vegetation index analysis for precision agriculture
???? Drought assessment and soil moisture mapping

Module 10: Spatiotemporal Analysis & Time-Series Forecasting

???? Tracking environmental changes over time
???? Trend analysis and forecasting using GEE
???? Temporal smoothing and anomaly detection in geospatial data

Module 11: Web-Based GIS & Interactive Visualization in GEE

???? Building interactive maps and dashboards
???? Data visualization techniques for big geospatial datasets
???? Web GIS applications with Google Earth Engine

Module 12: Real-World Case Studies & Final Project

???? Practical applications in urban planning, agriculture, and disaster response
???? Hands-on project using big data analytics in Google Earth Engine
???? Best practices for reporting and presenting geospatial insights

By the end of this course, participants will master Google Earth Engine for big data GIS analysis, automate geospatial workflows, and develop AI-powered GIS solutions for real-world applications.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.