Journal of Remote Sensing, Environmental Science & Geotechnical Engineering ISSN: 3107-7366 (Online)

Authors : Dr. Aakash Verma, Ananya Singh

Abstract : Hyperspectral and multispectral remote sensing represent two complementary paradigms in Earth observation, each offering distinct trade-offs in spectral richness, spatial coverage, and operational complexity. Hyperspectral systems capture contiguous narrow spectral bands across broad portions of the electromagnetic spectrum, enabling detailed material discrimination, biochemical retrievals, and subtle change detection. Multispectral systems, in contrast, sample a limited number of broader bands optimized for general classification and monitoring tasks, enabling cost-effective mapping over large areas. This comparative analysis synthesizes historical developments, algorithmic advances, and practical considerations that guide the selection of hyperspectral versus multispectral approaches. It outlines key preprocessing steps, feature-extraction and classification methods, and common application areas, including agriculture, mineral mapping, environmental monitoring, and urban studies. The study emphasizes that the choice of sensor technology must be driven by the scientific question, required discrimination capability, budgetary constraints, and computational resources. Finally, the paper highlights recent trends—such as sensor miniaturization, data fusion, and machine learning—that are blurring traditional boundaries and opening new avenues for integrated spectral imaging applications.

Keywords: Hyperspectral sensing; Multispectral sensing; Remote sensing; Spectral resolution; Data fusion; Classification