Optimal Car Parking Site Selection Using Google Earth Engine

What you'll learn
Understand the fundamentals of remote sensing and GIS concepts essential for urban planning and spatial analysis.
Analyze slope, landcover, and road proximity data to identify suitable areas for car parking using real-world geospatial datasets.
Build and implement a parking suitability model in Google Earth Engine, combining multiple spatial criteria for scoring and classification.
Visualize and export suitability maps for urban decision-making using GEE tools and techniques.
Requirements
No prior experience with Google Earth Engine is required - the course will guide you step-by-step.
Description
Parking is a major challenge in urban environments, and smart solutions are needed to optimize space and accessibility. This course offers a hands-on guide to identifying optimal car parking sites using modern geospatial tools. You'll learn how to apply Remote Sensing, GIS, and Google Earth Engine (GEE) to solve real-world urban planning problems through spatial data analysis.The course begins with the fundamentals of remote sensing, giving you an understanding of how satellite imagery and elevation data are used to map the physical features of the Earth. You'll then move into the core concept of site suitability mapping, where you'll learn how to select and evaluate spatial factors such as land cover, slope, and road proximity.You'll be introduced to Geographic Information Systems (GIS) and how they help integrate and analyze multiple layers of spatial data. Following this, you'll dive into Google Earth Engine, a powerful cloud-based platform for analyzing geospatial data at scale. Using GEE, you'll write code to combine real-world datasets and score urban land areas based on suitability for parking infrastructure.In the final part of the course, you will implement a complete parking suitability model in GEE using San Francisco as a case study. You'll classify land based on accessibility and terrain, visualize suitability zones on the map, and export your results for use in planning or presentations.This course is ideal for urban planners, GIS students, smart city developers, and anyone interested in real-world geospatial applications. No prior coding experience is required-just a curiosity for spatial thinking and urban problem-solving.
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.
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