Training on Big Data in Geospatial Analysis with Google Earth Engine

This course is designed for GIS specialists, data analysts, environmental scientists, urban planners, and policy professionals who want to leverage big data and cloud-based geospatial platforms to drive informed decisions. Participants will learn to access, process, and analyze massive spatial datasets using Google Earth Engine, enabling them to generate insights for environmental monitoring, urban development, climate assessment, and resource management.

Through practical exercises and real-world case studies, participants will develop the skills to convert large-scale geospatial data into actionable insights, visualize complex spatial patterns, and support evidence-based planning and policy decisions.

Duration

5 Days

Who Should Attend

• GIS and remote sensing professionals

• Environmental and climate analysts

• Urban and regional planners

• Data scientists working with spatial datasets

• Policy makers and research analysts in geospatial applications

Personal Impact

• Builds technical expertise in big data geospatial analysis

• Enhances skills in cloud-based GIS platforms and large dataset management

• Improves capability to interpret complex spatial patterns for decision support

Organizational Impact

• Strengthens data-driven planning and evidence-based project design

• Improves efficiency in environmental, urban, and climate analytics

• Enhances organizational capacity for advanced geospatial analysis and reporting

By the end of the course, participants will be able to:

• Access and manage large geospatial datasets in Google Earth Engine

• Analyze and visualize spatial and temporal patterns using big data

• Apply geospatial analytics to support environmental, urban, and climate-related projects

• Develop maps, reports, and dashboards for professional presentations

• Implement geospatial solutions to inform decision-making and strategic planning

Module 1: Introduction to Big Data and Google Earth Engine

• Overview of big data concepts in geospatial analysis

• Introduction to Google Earth Engine and cloud-based GIS platforms

• Types of spatial datasets and their applications

• Case Study: Large-scale environmental monitoring using GEE

Module 2: Data Acquisition and Preprocessing

• Accessing satellite imagery and open-source datasets

• Data cleaning, filtering, and validation

• Organizing datasets for analysis

• Practical Exercise: Import and preprocess Landsat or Sentinel imagery for analysis

Module 3: Geospatial Analysis Using Big Data

• Temporal and spatial data analysis techniques

• Change detection, trend analysis, and pattern recognition

• Statistical and computational approaches in geospatial analytics

• Case Study: Monitoring deforestation or urban expansion using GEE

Module 4: Visualization and Mapping

• Creating high-quality maps, graphs, and dashboards

• Effective communication of geospatial insights to stakeholders

• Customizing visual outputs for reports and presentations

• Practical Exercise:Generate a geospatial dashboard using big data outputs

Module 5: Application and Strategic Implementation

• Applying geospatial insights to policy, planning, and environmental management

• Decision-support frameworks using big data

• Integrating Google Earth Engine outputs into organizational workflows

• Practical Exercise:Develop a mini-project using GEE for a real-world geospatial problem