Image Enhancement and Change Detection

This unit covers advanced image enhancement and transformation techniques, multi-temporal and SAR-based change detection, and the integration of remote sensing outputs into GIS for analysis and decision making. Students will practice deriving indices, performing neighborhood and raster/vector operations, generating 3D surface parameters, and applying standards, coordinate systems, and metadata to support hazard and land-use applications.

Learning Objectives

• Analyze and compare image enhancement and transformation techniques (HE, histogram matching, Gaussian stretch, ratio images, high-pass filtering, local contrast, decorrelation stretch, IHS/RGB and tasseled-cap transforms) by applying them to datasets and quantifying effects on feature separability
• Apply multi-temporal and SAR coherence change-detection methods (spatial de-correlation, ratio coherence, random change detection, and ground-motion estimation) to detect and map land surface changes
• Demonstrate generation and use of derived indices, neighborhood operations, raster algebra, and very-narrow baseline stereo matching to extract 3D surface parameters and integrate results into GIS with appropriate coordinate systems and metadata
• Evaluate and implement end-to-end remote sensing–GIS workflows for hazard and resource analyses (e.g., landslide susceptibility, vegetation/land-use change), including deriving weighting coefficients, post-classification smoothing, accuracy assessment, and documentation for interoperability