Spectral Library and Discrimination Analysis of Indian Urban Materials

• Published in: Journal of the Indian Society of Remote Sensing 2019-05, Vol.47 (5), p.867-877
• Main Authors: Deshpande, Shailesh Shankar, Inamdar, Arun B., Vin, Harrick M.
• Format: Article
• Language: English
• Subjects: Algorithms; Concrete pavements; Covariance; Diagnostic systems; Discrimination; Earth and Environmental Science; Earth Sciences; Libraries; Remote Sensing/Photogrammetry; Research Article; Roofs; Soils; Spectra; Spectral analysis; Urban areas; Websites
• ISSN: 0255-660X; 0974-3006
• DOI: 10.1007/s12524-019-00942-6

In this paper, we present a spectral library of urban materials and its detailed spectral analysis. The primary focus of the research is spectral study of the local urban materials and their discrimination using field signatures. Further, we develop an algorithm for identifying the most important wavelength range, and its distribution. Instead of common analysis methods which focus on single wavelength, we focus on wavelength range as it is difficult for urban material to find out single diagnostic wavelength. Novelty of our algorithm is twofold: first we use Leodoit–Wolf covariance estimator for improving accuracy, and second we introduce two new metrics based on Bhattacharyya distance. The spectral discrimination analysis found that the significant wavelength ranges for discriminating urban classes are spread all over the spectrum with slight bias for visible range. Though it is challenging to discriminate materials belonging to the same class, for example, different types of concrete pavements, the broad-level classes such as soil, urban vegetation, metal roofs and concrete are well separable. The confusion between bright soil and concrete surfaces is difficult to overcome spectrally. The developed spectral library is available at OGC compatible website splibtarang.com/index.php.