Abstract
Hyperspectral remote sensing is a relatively new development in remote sensing technologies, effectively measuring both spatial and high spectral information from surface materials and constituents within a single system. Compared to multispectral remote sensing, hyperspectral imagery can provide more accurate and detailed spectral information of the Earth’s surface, measuring hundreds of bands from the visible to the near infrared. Hyperspectral data can be obtained using either space-based or airborne platforms, with expanding applications on unmanned aerial vehicles (UAVs). This chapter discusses hyperspectral technologies and their vast applications focusing primarily on airborne and spaceborne systems, reviewing past and future directions of sensor technology developments. Hyperspectral imaging is a rapidly growing field of space-based remote sensing and will continue to expand in utility for various civilian and public-good applications. Various nations are planning hyperspectral remote sensing missions, which will see increased acquisition of hyperspectral data of the Earth’s surface on a more frequent and timely basis in the near future.
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References
Ames Remote, Precision Agriculture remote Sensing Information (1998), http://www.amesremote.com/. Accessed 6 Mar 2016
EARSeL (European Association of Remote Sensing Laboratories), Science Education through Earth Observation for High Schools (SEOS) (2016), http://www.seos-project.eu/modules/remotesensing/remotesensing-c01-p05.html. Accessed 6 Mar 2016
M. Elowitz, What is Imaging Spectroscopy (Hyperspectral Imaging)? (2015), http://www.markelowitz.com/. Accessed 6 Mar2016
ESA, Mission News: Proba-1 back in operation (2015), https://earth.esa.int/web/guest/missions/mission-news/-/article/proba-1-back-in-operation. Accessed 6 Mar 2016
Exelis, Vegetation analysis using vegetation indices in ENVI (2013), http://www.exelisvis.com/Learn/WhitepapersDetail/TabId/802/ArtMID/2627/ArticleID/13742/Vegetation-Analysis-Using-Vegetation-Indices-in-ENVI.aspx. Accessed 6 Mar 2016
A. Goetz, The portable instant display and analysis spectrometer (PIDAS), in Proceedings of the Third Airborne Imaging Spectrometer Data Analysis Workshop, vol. 87–30 (JPL Publication, Pasadena, California, 1987), pp. 8–17
A. Goetz, G. Vane, J. Solomon, B. Rock, Imaging spectrometry for Earth remote sensing. Science 228, 1147–1153 (1985)
L. Guanter, V. Estellés, J. Moreno, Spectral calibration and atmospheric correction of ultra–fine spectral and spatial resolution remote sensing data. Application to CASI–1500 data. Remote Sens. Environ. 109, 54–65 (2006)
NASA, Hyperion (2016), http://earthobservatory.nasa.gov/Features/EO1Tenth/page3.php. Accessed 6 Mar 2016
G.A. Shaw, H.K. Burke, Spectral imaging for remote sensing. Lincoln Lab. J. 14(1), 1–28 (2003)
M. Sunil Kumar, Multispectral and Hyperspectral Remote Sensing and Its Applications. Bapatla Class Seminar, Agricultural College, by Medida Sunil Kumar BAD-14-06 1 (2006)
F.T. Tamas Janos, Geoinformatics (2008), http://www.tankonyvtar.hu/en/tartalom/tamop425/0032_terinformatika/index.html. Accessed 6 Mar 2016
F.D. Van der Meer, H.M.A. van der Werff, F.J.A. van Ruitenbeek, C.A. Hecker, W.H. Bakker, M.F. Noomen, M. van der Meijde, E.J.M. Carranza, J. Boudewijn de Smeth, T. Woldai, Multi- and hyperspectral geologic remote sensing: a review. Int. J. Appl. Earth Obs. Geoinf. 14(1), 112–128 (2012)
G. Vane, M. Chrisp, H. Enmark, S. Macenka, J. Solomon, Airborne Visible/Infrared Imaging Spectrometer (AVIRIS): an advanced tool for earth remote sensing, in Proceedings of the 1984 IEEE International Geoscience Remote Sensing Symposium, SP215 (IEEE, New York, 1984), pp. 751–757
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Tan, SY. (2016). Developments in Hyperspectral Sensing. In: Pelton, J., Madry, S., Camacho-Lara, S. (eds) Handbook of Satellite Applications. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6423-5_101-1
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DOI: https://doi.org/10.1007/978-1-4614-6423-5_101-1
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