| File Name: | Landfill Site Suitability Mapping Using Remote Sensing |
| Content Source: | https://www.udemy.com/course/landfill-site-suitability-mapping-using-remote-sensing |
| Genre / Category: | Other Tutorials |
| File Size : | 428.6 MB |
| Publisher: | Earth’s AI |
| Updated and Published: | August 5, 2025 |
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.
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