Landfill Site Suitability Mapping Using Remote Sensing

Landfill Site Suitability Mapping Using Remote Sensing and Google Earth Engine

Created byEarth's AI

Last updated 8/2025

English

What you'll learn

Understand the fundamentals of remote sensing and its applications in environmental site suitability analysis.
Learn to process and analyze satellite data for identifying landfill site suitability using Google Earth Engine.
Gain skills in integrating terrain, land cover, water bodies, and urban proximity data for multi-criteria decision-making.
Develop practical experience in exporting and visualizing suitability maps for real-world landfill site planning and management.

Course content

1 section • 5 lectures • 54m total length

Lecture 1: Fundamentals of Remote Sensing13:19
This lecture introduces the basic principles of remote sensing, including the types of sensors, electromagnetic spectrum, and data acquisition methods. Students will learn how remote sensing captures earth surface information and how it is applied across various fields. The lecture covers satellite and aerial imagery, resolution types, and preprocessing steps. Understanding these fundamentals is essential for analyzing and interpreting geospatial data accurately.
Lecture 2: Remote Sensing Site Suitability Mapping8:03
In this lecture, students explore how to use remote sensing data to identify suitable locations for specific land uses. The focus will be on multi-criteria analysis combining factors such as land cover, elevation, and proximity to infrastructure. Techniques for masking unsuitable areas and generating suitability indices will be discussed. This lecture provides a foundation for practical site suitability assessments using satellite data.
Lecture 3: Introduction to Google Earth Engine (GEE)9:25
This session introduces Google Earth Engine, a cloud-based geospatial analysis platform. Students learn to navigate the interface, access diverse satellite datasets, and perform basic image processing. The lecture emphasizes GEE’s capabilities in handling large-scale spatial data, scripting with JavaScript, and visualizing results. Understanding GEE is essential for leveraging remote sensing data in scalable and efficient workflows.
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 4: Implementation in GEE for Landfill Site Suitability Mapping20:04
In this practical lecture, students apply their knowledge by building a landfill site suitability model using Google Earth Engine. Combining remote sensing datasets like elevation, land cover, water bodies, and urban areas, learners create weighted suitability maps. The session covers data processing, masking, normalization, and final mapping, culminating in exporting results for real-world applications. This hands-on experience equips students with skills to implement complex spatial analyses in GEE.

Requirements

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

Description

Landfill site selection is a critical task in environmental management, requiring careful evaluation of multiple geographic and environmental factors. This course offers a comprehensive guide to landfill site suitability mapping using remote sensing data and Google Earth Engine (GEE). Beginning with the fundamentals of remote sensing, students will grasp the key concepts of satellite imagery, land cover classification, and terrain analysis. The course progresses to cover how to identify and process essential datasets such as digital elevation models (DEMs), land cover maps, and water body information that influence landfill suitability.

A central focus of the course is Google Earth Engine, a powerful cloud-based geospatial processing platform. Students will be introduced to its interface, scripting language, and data catalog, gaining the skills to manipulate large datasets efficiently. Practical sessions will guide learners through creating suitability models by combining multiple factors—such as slope, distance from urban areas, and proximity to water—to generate maps indicating optimal landfill locations.

The course is designed for environmental scientists, urban planners, GIS professionals, and anyone interested in applying geospatial technology for sustainable land management. Through step-by-step tutorials, hands-on exercises, and real-world case studies, students will build confidence in integrating remote sensing data with GEE to solve complex spatial problems. By the end, they will have a solid understanding of both theoretical and applied aspects of landfill site suitability mapping, ready to implement these skills in academic, governmental, or commercial settings.

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.