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Free Download EV Charging Station Site Suitability Analysis Using GEE
Published 8/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 1m | Size: 518 MB
Geospatial Analysis and Decision-Making for Optimal EV Charging Station Placement Using Google Earth Engine
What you'll learn
Understand the fundamentals of site suitability analysis and the key geographic and environmental factors influencing the location of EV charging stations.
Learn how to use Google Earth Engine (GEE) for geospatial data processing, including working with satellite imagery, population, road networks, and terrain data
Develop skills to integrate and analyze multiple spatial datasets (e.g., population density, proximity to roads, land cover, slope) to create a composite suitab
Gain practical experience exporting, visualizing, and interpreting suitability maps to support urban planning and sustainable infrastructure development.
Requirements
No prior experience with Google Earth Engine is required — the course will guide you step-by-step.
Description
With the rapid growth of electric vehicles worldwide, the demand for strategically placed EV charging stations has never been greater. This course offers a comprehensive, practical introduction to geospatial site suitability analysis specifically tailored for EV infrastructure planning, using the cutting-edge capabilities of Google Earth Engine (GEE).Learners will begin by understanding the core principles of site suitability—how multiple factors such as population density, road accessibility, terrain slope, and urban land cover affect the feasibility and convenience of charging station locations. The course focuses on integrating these diverse spatial datasets into a composite suitability model that highlights the best potential sites.Through step-by-step tutorials and real-world case studies, students will develop skills to process and analyze satellite imagery, global population datasets, and transportation network information within the GEE cloud environment. They will learn to normalize and weight criteria, perform spatial buffering, and apply logical masking to refine site recommendations.Visualization techniques will be covered to effectively communicate results, supporting evidence-based urban planning and sustainable development goals. Additionally, learners will gain experience exporting their final suitability maps for use in GIS software or presentations.By the end of the course, participants will be equipped to leverage geospatial technologies for infrastructure projects, ensuring efficient, equitable, and environmentally conscious placement of EV charging stations. This course is ideal for urban planners, GIS analysts, environmental professionals, and anyone interested in harnessing spatial data science for green transportation initiatives.
Who this course is for
Students, researchers and professionals in agriculture, environmental science, geography, or remote sensing looking to apply satellite data in real-world scenarios.
Homepage
https://www.udemy.com/course/ev-charging-station-site-suitability-analysis-using-gee/
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