Advertisement

Spectral Library and Discrimination Analysis of Indian Urban Materials

  • Shailesh Shankar DeshpandeEmail author
  • Arun B. Inamdar
  • Harrick M. Vin
Research Article
  • 53 Downloads

Abstract

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.

Keywords

Hyperspectral library Urban spectroscopy Bhattacharyya distance Hyperspectral feature selection Urban materials Spectral discrimination analysis 

Notes

Acknowledgements

Shailesh Deshpande would like to thank Piyush Yadav, Priya Deshpande and Sachin Gupte for their eager support during the sample collection and field measurements.

References

  1. ASD FieldSpec portable spectroradiometer (2016). http://www.asdi.com/products/fieldspec-spectroradiometers. Acessed 11 Mar 2015.
  2. Baldridge, A. M. (2009). The ASTER spectral library version 2.0. Remote Sensing of Environment, 113, 711–715.CrossRefGoogle Scholar
  3. Biehl, L., & Landgrebe, D. (2002). MultiSpec-a tool for multispectral-hyperspectral image data analysis. Computers & Geosciences, 28(10), 1153–1159.CrossRefGoogle Scholar
  4. Clark, R. N., Swayze, G. A., Wise, R., Livo, E., Hoefen, T., Kokaly, R., & Sutley, S. J. (2007). USGS digital spectral library splib06a: U.S. Geological Survey, Digital Data Series 231.Google Scholar
  5. Das, B. S., Sarathjith, M. C., Santra, P., Sahoo, R. N., Srivastava, R., Routray, A., et al. (2015). Hyperspectral remote sensing: opportunities, status and challenges for rapid soil assessment in India. Current Science, 108(5), 860–868.Google Scholar
  6. Deshpande, S. S., Inamdar, A. B., & Vin, H. M. (2017). Urban land use land cover discrimination using image based reflectance calibration methods for hyperspectral data. Photogrammatric Engineering and Remote Sensing, 83(5), 365–376.CrossRefGoogle Scholar
  7. Fukunaga K. (1990a). Hypothesis Testing. In R. Werner (Ed.), Introduction to pattern recognition. San Diego, CA: Academic Press.Google Scholar
  8. Fukunaga K. (1990b). Feature extraction and linear mapping for classification. In R. Werner (Ed.), Introduction to pattern recognition. San Diego, CA: Academic Press.Google Scholar
  9. Goetz, A. F. H. (2012). Making accurate field spectral reflectance measurements, http://discover.asdi.com/Portals/45853/docs/Measurements-paper-10-26-12.pdf. Accessed 28 Jan 2015.
  10. Herold, M., Roberts, D. A., Gardner, M. E., & Dennison, P. E. (2004). Spectrometry for urban area remote sensing—development and analysis of a spectral library from 350 to 2400 nm. Remote Sensing of Environment, 91(34), 304–319.CrossRefGoogle Scholar
  11. IS 10262 (2009). Guidelines for concrete mix design proportioning, first revision, New Delhi 110002: Bureau of Indian Standards, July 2009.Google Scholar
  12. IS 1498 (1970). Classification and identification of soils for general engineering purposes, first revision, New Delhi 110002: Bureau of Indian Standards, March 1972.Google Scholar
  13. IS 15658 (2006). Precast concrete blocks for paving, New Delhi 110002: Bureau of Indian Standards, June 2006.Google Scholar
  14. IS 383 (1970). Specification for coarse and fine aggregates from natural sources for concrete second revision, New Delhi 110002: Bureau of Indian Standards, April 1971.Google Scholar
  15. IS 459 (1992). Corrugated and semi-corrugated asbestos cement sheets, third revision, New Delhi 110002: Bureau of Indian Standards, March 1992.Google Scholar
  16. IS 654 (1992). Clay roofing tiles, mangalore pattern-specification, third revision, New Delhi 110002: Bureau of Indian Standards, March 1992.Google Scholar
  17. IS 277 (2003). Galvanized steel sheets (plain and corrugated)-specification, sixth revision, New Delhi 110002: Bureau of Indian Standards, November 2003.Google Scholar
  18. Ledoit, O., & Wolf, M. A. (2004). Well-conditioned estimator for large-dimensional covariance matrices. Journal of Multivariate Analysis, 88, 365–411.CrossRefGoogle Scholar
  19. Manjunath, K. R., Kumar, A., Mehra, M., Renu, R., Uniyal, S. K., Singh, R. D., et al. (2014). Developing spectral library of major plant species of western Himalayas using ground observations. Journal of Indian Society of Remote Sensing, 42(1), 201–216.CrossRefGoogle Scholar
  20. Manolakis, D., Lockwood, R., Cooley, T., & Jacobson, J. (2009). Hyperspectral detection algorithms: Use covariances or subspaces? Imaging Spectrometry XIV, ed. Shen Sylvia S and Lewis Paul E. Proceedings of SPIE, 74570Q, 1–8.Google Scholar
  21. Ronak Tiles Pvt. Ltd. Pavement blocks (2014). http://ronaktiles.in/. Accessed 5 Jul 2016.
  22. Sahyadri Industries Ltd. Swstik, the roof of India (2015). http://www.silworld.in/Download/Products/SWASTIK_Brochure.pdf. Accessed 5 Jul 2016.
  23. Shwetank, J. K. & Bhatia K. (2011). Development of digital spectral library and supervised classification of rice crop varieties using hyperspectral image processing, Asian Journal of Geoinformatics, 11(3).Google Scholar
  24. SVC Field Portable Spectroradiometers 2016. http://www.spectravista.com/ground.html. Accessed 5 Jul 2016.
  25. Tata BlueScope Steel Ltd. Durashine roof and wall sheets 2016. http://tatabluescopesteel.com/Roof-and-Wall#Durashine%20Roof%20&%20Wall. Accessed 5 Jul 2016.
  26. Uttam Galva Steels Ltd. GP and GC 2016. http://www.uttamgalva.com/products/gp_gc.html. Accessed 30 Apr 2014.
  27. Vijay Agency Pvt. Ltd. Corrugated sheets 2015. http://www.vijayagency.co.in/corrugated-sheets.html#design-corrugated-sheets. Accessed 5 July 2016.

Copyright information

© Indian Society of Remote Sensing 2019

Authors and Affiliations

  1. 1.Tata Consultancy Services, Research and Innovation, Tata Research Development and Design CentrePuneIndia
  2. 2.Centre of Studies in Resources Engineering, Indian Institute of Technology BombayMumbaiIndia

Personalised recommendations