Research and Data Analysis

Remote Sensing Data Processing with Google Earth Engine Training Course

Introduction

In the age of climate change, environmental degradation, and big data, remote sensing technology has become an indispensable tool for environmental monitoring, land use mapping, and disaster management. Remote Sensing Data Processing with Google Earth Engine Training Course is designed to equip researchers, analysts, students, and professionals with hands-on skills in using Google Earth Engine (GEE) for satellite data analysis, visualization, and processing. Leveraging GEE's powerful cloud-based platform, participants will learn to process large-scale geospatial datasets without the need for high-end infrastructure.

This course blends machine learning for Earth observation, cloud computing for remote sensing, and geospatial data analytics using JavaScript and Python APIs. Participants will gain real-world experience through case studies on deforestation, climate monitoring, agriculture, and urban development. By the end of the course, learners will be proficient in building, executing, and automating workflows using GEE, and applying them in diverse sectors including agriculture, water resources, disaster risk management, and sustainability science.

Programme Curriculum

Remote Sensing Data Processing with Google Earth Engine Training Course

Introduction

Course Objectives

Participants will be able to:

Understand the fundamentals of remote sensing and Earth observation data.
Navigate and operate Google Earth Engine’s code editor and platform.
Apply geospatial machine learning algorithms using GEE.
Conduct change detection and land cover classification.
Perform NDVI and other vegetation indices analysis.
Integrate Python and JavaScript APIs with Google Earth Engine.
Process multi-temporal satellite imagery using GEE.
Visualize and export geospatial datasets and outputs.
Analyze climatic trends using MODIS and Landsat data.
Automate data processing tasks using Earth Engine apps.
Evaluate case studies in disaster mapping and water monitoring.
Conduct urban heat island and LULC analysis.
Develop reproducible workflows and share geospatial applications.

Target Audience

Environmental Scientists and Ecologists
GIS and Remote Sensing Specialists
Disaster Risk Reduction Professionals
Data Scientists and Analysts
Researchers and Academic Scholars
Climate Change Analysts
Urban Planners and Geographers
Students and Educators in Earth Sciences

Course Duration: 5 days

Course Modules

Module 1: Introduction to Remote Sensing and GEE

Overview of Earth observation data types
Principles of remote sensing and satellites (MODIS, Landsat, Sentinel)
Navigating the GEE Code Editor interface
Data catalog exploration and filtering
Writing your first script in GEE (JavaScript)
Case Study: Mapping global forest cover trends

Module 2: Image Preprocessing and Compositing

Cloud masking and atmospheric correction
Temporal filtering and mosaicking
Image compositing techniques
Visualization enhancements and stretch
Exporting processed imagery
Case Study: Seasonal land surface temperature monitoring

Module 3: Spectral Indices and Vegetation Analysis

Understanding NDVI, EVI, SAVI, and NDWI
Calculating indices using GEE expressions
Time series trend analysis
Detecting vegetation health and changes
Visualizing vegetation indices on maps
Case Study: Drought monitoring in sub-Saharan Africa

Module 4: Land Cover Classification and Change Detection

Supervised and unsupervised classification
Random forest and CART classifiers
Accuracy assessment and confusion matrix
Change detection techniques
Reclassification and masking
Case Study: Urban sprawl mapping in Nairobi, Kenya

Module 5: Climate and Hydrological Applications

Accessing CHIRPS, ERA5, and MODIS climate data
Analyzing rainfall and temperature trends
Hydrological modeling using terrain data
Basin delineation and watershed mapping
Seasonal analysis of water bodies
Case Study: Flood extent mapping in Bangladesh

Module 6: Urban Analysis and Heat Mapping

Nighttime light analysis with VIIRS
Urban land use and land cover (LULC) detection
Urban heat island effect using thermal imagery
Built-up area classification
Zonal statistics in urban planning
Case Study: Heat vulnerability mapping in Phoenix, Arizona

Module 7: Integrating Python and JavaScript APIs in GEE

Setting up Python API environment
Running GEE scripts in Jupyter Notebook
Comparing Python and JavaScript syntax
Building interactive maps and dashboards
Batch processing and automation
Case Study: Automated NDVI change detection pipeline

Module 8: Building Earth Engine Apps and Sharing Results

Earth Engine app development fundamentals
UI widgets and user interaction
Hosting and publishing your application
Collaborating and version control
Sharing outputs with stakeholders
Case Study: Developing a drought monitoring web app

Training Methodology

Instructor-led live sessions
Hands-on coding exercises using real datasets
Interactive Q&A and troubleshooting
Downloadable practice scripts and data
Real-world case studies to reinforce skills
Certificate upon successful course completion

Bottom of Form

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

GEE remote sensing environmental monitoring

Programme Fee

Duration: 5 Days

Method: Online or Physical

Online Price: $1,000

Physical Price: $1,500

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Sep 21 2026

21 Sep — 25 Sep 2026

💻 Online / Virtual session

Online $1,000