Udemy – Industrial Site Suitability Mapping with Remote Sensing

The course “Industrial Site Suitability Mapping Using Remote Sensing and GEE” is designed to equip learners with the skills to assess optimal industrial development sites using satellite data and cloud-based geospatial tools. Through a blend of theory and practice, participants will learn the principles of remote sensing, the importance of land use classifications, and the power of terrain and proximity analysis for planning purposes.

In the early modules, learners will gain foundational knowledge of remote sensing, understanding how data from satellites like Landsat and global datasets like ESA WorldCover can be used to interpret surface features. The course then introduces Google Earth Engine (GEE), a cloud-based geospatial analysis platform, where students will gain hands-on experience working with real-time data at scale.

The highlight of the course is the step-by-step creation of an industrial site suitability model, incorporating critical layers such as slope (from DEMs), land cover types, proximity to urban areas, water bodies, and forested regions. By assigning weighted importance to each factor, learners will build a composite suitability index to identify ideal industrial zones.

In the final module, learners will visualize their results on a map, style them appropriately, and export outputs as GeoTIFF files. By the end of this course, students will be able to confidently conduct land suitability analyses for industrial planning using modern, scalable tools—skills highly relevant for careers in urban development, environmental impact assessment, and spatial planning.

This course is ideal for planners, environmental analysts, GIS users, and university students interested in geospatial technologies.

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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