Urban Expansion Suitability Mapping Using Remote Sensing

This lecture introduces the core concepts of remote sensing, explaining how satellite and aerial imagery are captured and used to analyze the Earth's surface. Learners will understand different sensor types, spectral bands, resolution, and the importance of preprocessing data. The session covers how remote sensing supports environmental monitoring, urban planning, and resource management. Emphasis is placed on the practical application of remotely sensed data for mapping and analysis, setting a solid foundation for advanced geospatial techniques and integration with tools like Google Earth Engine.

This lecture focuses on how remote sensing data can be applied to site suitability analysis. It explains key criteria such as land cover classification, slope, elevation, and proximity to urban areas. Students will learn methods to mask unsuitable areas (e.g., water bodies, existing urban zones) and how to combine multiple environmental factors to generate a comprehensive suitability map. Practical examples demonstrate how these maps guide decision-making for urban expansion, infrastructure development, and environmental conservation.

This lecture provides an overview of Google Earth Engine, a powerful cloud-based platform for geospatial data processing. Learners will become familiar with the GEE interface, key datasets, and scripting environment using JavaScript. The session covers how GEE enables large-scale analysis of satellite imagery and integration of diverse spatial datasets. Students will explore basic functions, filtering image collections, masking, visualization, and exporting results, preparing them to implement geospatial analyses effectively.

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.

Building on previous lectures, this session guides learners through practical implementation of urban expansion suitability mapping using Google Earth Engine. The lecture walks through defining an area of interest, loading and processing elevation, slope, and land cover data, and calculating proximity to existing urban areas. Students will learn to combine these criteria with weighted factors to produce suitability scores and visualize them on interactive maps. The session also covers exporting maps for further use, enabling students to apply these skills in real-world urban planning scenarios.

This lecture introduces the Inspector Tool in Google Earth Engine, a powerful feature for examining pixel values in your visualized map layers. You’ll learn how to inspect elevation, land cover, suitability scores, and other attributes at specific locations. This tool helps validate your outputs and understand spatial variations in your data. Whether you're debugging or analyzing specific areas, the Inspector offers direct insight into how your geospatial model behaves across the landscape.