Title:
Future perspectives and challenges in hyperspectral remote sensing

dc.contributor.authorPrem Chandra Pandey
dc.contributor.authorHeiko Balzter
dc.contributor.authorPrashant K. Srivastava
dc.contributor.authorGeorge P. Petropoulos
dc.contributor.authorBimal Bhattacharya
dc.date.accessioned2026-02-07T09:25:44Z
dc.date.issued2020
dc.description.abstractRemote sensing (RS) technology has rapidly advanced in terms of radiometric, spatial, and spectral resolution. This trend has led to increasing complexity of data types ranging from low to high spatial and spectral resolutions and data dimensionality. In the chapters of this book, the state of the art has been presented, outlining the advantages of hyperspectral imaging (HSI) systems over multispectral data, and key future challenges and research directions with HSI have been illustrated. This chapter provides a perspective on the evolution of hyperspectral RS methods and applications along with challenges and barriers faced during research and innovation activities. The promise of upcoming missions with higher spatial and spectral resolution sensors in orbit in the near future will increase the utility of hyperspectral data in several research domains and will likely increase the number of users of HSI for soils, forestry, agriculture, urban, and cryosphere research. This chapter is intended as a resource to be aware of challenges and the future potential of hyperspectral RS to current and prospective users of high spectral resolution data to extract meaningful information for their research and applications. © 2020 Elsevier Ltd All rights reserved.
dc.identifier.doi10.1016/B978-0-08-102894-0.00021-8
dc.identifier.isbn978-008102894-0
dc.identifier.urihttps://doi.org/10.1016/B978-0-08-102894-0.00021-8
dc.identifier.urihttps://dl.bhu.ac.in/bhuir/handle/123456789/36386
dc.publisherElsevier
dc.subjectChallenges
dc.subjectClassification
dc.subjectData dimensionality
dc.subjectEndmember extraction
dc.subjectHyperspectral imaging system
dc.subjectSmile effect
dc.titleFuture perspectives and challenges in hyperspectral remote sensing
dc.typePublication
dspace.entity.typeBook chapter

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