A comprehensive review of hyperspectral data fusion with lidar and sar data

Kahraman S., Bacher R.

Annual Reviews in Control, vol.51, pp.236-253, 2021 (SCI-Expanded, Scopus) identifier

  • Publication Type: Article / Review
  • Volume: 51
  • Publication Date: 2021
  • Doi Number: 10.1016/j.arcontrol.2021.03.003
  • Journal Name: Annual Reviews in Control
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC
  • Page Numbers: pp.236-253
  • Keywords: hyperspectral (HS) image, Light Detection And Ranging (LiDAR), multi-modal data fusion, review, Synthetic Aperture Radar (SAR)
  • Istanbul Gelisim University Affiliated: Yes

Abstract

© 2021With the development of remote sensing techniques, the fusion of multimodal data, particularly hyperspectral-Light Detection And Ranging (HS-LiDAR) and hyperspectral-SAR, has become an important research field in numerous application areas. Multispectral, HS, LiDAR, and Synthetic Aperture Radar (SAR) images contain detailed information about the monitored surface that are complementary to each other. Thus, data fusion methods have become a promising solution to obtain high spatial resolution remote-sensing images. The main point of this review paper is to classify hyperspectral-LiDAR and hyperspectral-SAR data fusion with approaches. Moreover, recent achievements in the fusion of hyperspectral-LiDAR and hyperspectral-SAR data are highlighted in terms of faced challenges and applications. Most frequently used data fusion datasets that include IEEE GRSS Data Fusion Contests are also described.