Mall Site Suitability Mapping Using Google Earth Engine

Learn to analyze, map, and visualize the best locations for shopping malls using Remote Sensing, GIS, and GEE

Created byEarth's AI

Last updated 8/2025

English

What you'll learn

Understand remote sensing and GIS fundamentals to build a strong foundation for spatial data analysis and location-based decision-making.
Identify key criteria like roads, population, slope, and land cover for mall site selection through spatial data integration and evaluation.
Process and analyze geospatial datasets using Google Earth Engine, including raster operations, masking, and visualization techniques.
Generate and export mall suitability maps in GEE, combining multiple layers and applying weighted overlays for spatial decision support.

Course content

1 section • 6 lectures • 1h 6m total length

Lecture 1: Fundamentals of Remote Sensing13:19
This lecture introduces students to the foundational concepts of remote sensing, including electromagnetic spectrum principles, image acquisition, and satellite sensors. You will learn how different land features reflect or emit radiation and how this data is captured through various sensors. This session sets the stage for spatial analysis using satellite-derived imagery in environmental and urban planning applications.
Lecture 2: Site Suitability Mapping Concepts8:03
This session covers the core principles of site suitability mapping. You’ll explore how to define criteria like accessibility, population, terrain, and land cover, and how to assign appropriate weights to each. The lecture emphasizes multi-criteria decision analysis (MCDA) and introduces models commonly used in urban planning and infrastructure development for optimal site selection.
Lecture 3: Introduction to Geographic Information Systems (GIS)7:39
Learn how GIS works and why it’s crucial for spatial decision-making. This lecture explores key GIS components, including data types (raster and vector), spatial analysis, and coordinate systems. You'll understand how GIS integrates various datasets to help analyze geographic patterns and support real-world planning—laying the groundwork for further spatial modeling in GEE.
Lecture 4: Introduction to Google Earth Engine (GEE)9:25
Dive into the power of Google Earth Engine—a cloud-based geospatial analysis platform. This session guides you through the GEE interface, JavaScript API, importing datasets, filtering spatial/temporal ranges, and visualizing maps. By the end, students will be ready to begin writing scripts and exploring real-world spatial datasets.
Getting Started with the Google Earth Engine Interface3:38
This section introduces the Google Earth Engine platform, guiding learners through accessing the Code Editor, understanding its interface, and exploring key panels like the script editor, map viewer, inspector, and data catalog. It helps beginners get comfortable navigating GEE before writing any code or performing analysis.
Lecture 5: Mall Suitability Mapping in GEE24:47
This practical lecture walks you through the end-to-end implementation of mall site suitability mapping in GEE. You’ll integrate roads, slope, population, and land cover data, normalize variables, apply weights, and generate a final suitability index. You'll also learn how to visualize results, export maps, and validate outputs. This is where theory meets practice.

Requirements

No prior experience with Google Earth Engine is required — the course will guide you step-by-step.

Description

Urban development decisions like mall placement can have a major impact on accessibility, economic growth, and environmental balance. This course empowers you to make such decisions using modern geospatial tools. Through this hands-on learning journey, you will develop the skills to carry out site suitability mapping for shopping malls using Remote Sensing, GIS, and the cloud-based platform Google Earth Engine (GEE).

The course begins with a solid foundation in Remote Sensing—what it is, how satellite imagery is captured, and how it applies to urban analysis. You’ll then explore GIS fundamentals, including spatial layers, vector and raster data, and how they combine to model real-world locations.

Next, you’ll dive into the principles of site suitability mapping, learning how to translate real-world criteria into spatial rules. After learning how to use GEE, you’ll implement a complete mall suitability analysis using real datasets: roads (for accessibility), population density (for customer base), slope (for buildability), and land cover (urban zones).

By the end of this course, you’ll know how to:

Prepare and process geospatial data.
Normalize multiple suitability layers.
Combine them into a weighted suitability index.
Visualize and export your results from GEE.

Whether you're an urban planner, GIS student, or data enthusiast, this course will equip you with a powerful framework for spatial decision-making using scalable, cloud-based tools.

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.