Identification and mapping of night lights' signatures using hyperspectral data

Fred A. Kruse; Christopher D. Elvidge

doi:10.1117/12.882191

20 May 2011 Identification and mapping of night lights' signatures using hyperspectral data

Proceedings Volume 8048, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVII; 80480T (2011) https://doi.org/10.1117/12.882191
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

"ProSpecTIR" Imaging spectrometer (hyperspectral imagery or "HSI") data were collected for the city of Las Vegas, Nevada, USA at 10:55 PM July 28, 2009 for the purposes of identification, characterization, and mapping of urban lighting based on spectral emission lines unique to specific lighting types. The ProSpecTIR sensor measures the spectrum in 360 spectral bands between 0.4 and 2.5 micrometers at approximately 5nm spectral resolution, and for this flight, at 1.2m spatial resolution. Spectral features were extracted from the data and compared to a spectral library of known lighting measurements. Specific lighting types identified based on spectral signatures using the ProSpecTIR data included blue and red neon, high pressure sodium, and metal halide lights. A binary encoding method was used to map the spatial distribution of lighting types based on simplified spectral signatures. Results were overlain on a Quickbird panchromatic 0.6m spatial resolution image. The observed locations of specific light types were compared to a 3-D Las Vegas building model, and airborne signatures validated against spectral library measurements. The ProSpecTIR data successfully identified and mapped different lighting types and distributions, allowing determination of the nature and spatial associations of specific lights. Results illustrate the potential for using imaging spectrometer data to characterize urban development.

Citation Download Citation

Fred A. Kruse and Christopher D. Elvidge "Identification and mapping of night lights' signatures using hyperspectral data", Proc. SPIE 8048, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVII, 80480T (20 May 2011); https://doi.org/10.1117/12.882191

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