Drone-based area scanning of vegetation fluorescence height profiles using a miniaturized hyperspectral lidar system
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We have developed a compact hyperspectral lidar system based on a continuous-wave (CW) 445 nm diode laser and a double Scheimpflug imaging arrangement. The light-weight construction allows the integration of the system on a commercial drone. Airborne, range-resolved spatial imaging of vegetation fluorescence is demonstrated.
The authors gratefully acknowledge the continuing support from Professors Sailing He and Guofu Zhou. We are also very grateful to Ying Li, Ying Li, and Jinlei Wang for assistance in the measurements and Klas Rydhmer, Alfred Strand, and Mikael Ljungholm for contributions in the early work on hyperspectral Scheimpflug systems. This work was supported by the Guangdong Province Innovation Research Team Program (2010001D0104799318), the National Science Foundation of China (61705069), the Chinese Ministry of Science and Technology through the National Key Research and Development Program of China (2018YFC1407503), and by Spectraray Inc.
- 11.J. Joiner, L. Guanter, R. Lindstrot, M. Voigt, A.P. Vasilkov, E.M. Middleton, K.F. Huemmrich, Y. Yoshida, C. Frankenberg, Global monitoring of terrestrial chlorophyll fluorescence from moderate-spectral-resolution near-infrared satellite measurements: methodology, simulations, and application to GOME-2. Atmos. Meas. Tech. 6, 2803–2823 (2013)CrossRefGoogle Scholar
- 12.ESA, Report for mission selection, FLEX, ESA SP-1330/2, European Space Agency, Noordwiik, The Netherlands (2015)Google Scholar
- 18.V. Drozdowska, Seasonal and spatial variability of surface seawater fluorescence properties in the Baltic and Nordic Seas: results of lidar experiments. Oceanologia 49, 59–69 (2007)Google Scholar
- 20.A. Ounis, J. Bach, A. Mahjoub, F. Daumard, I. Moya, Y. Goulas, A new airborne lidar for remote sensing of canopy fluorescence and vertical profile, in EPJ Web of Conferences (2016), p. 25019Google Scholar
- 21.M.A. Lefsky, W.B. Cohen, G.G. Parker, D.J. Harding, Lidar remote sensing for ecosystem studies: lidar, an emerging remote sensing technology that directly measures the three-dimensional distribution of plant canopies, can accurately estimate vegetation structural attributes and should be of particular interest to forest, landscape, and global ecologists. Bioscience 52, 19 (2002)CrossRefGoogle Scholar
- 23.M. Maltamo, E. Næsset, J. Vauhkonen, Forestry applications of airborne laser scanning, concepts and case studies. Manag. Ecosyst. 27, 2014 (2014)Google Scholar
- 31.S.M. Zhu, E. Malmqvist, W.S. Li, S. Jansson, Y.Y. Li, Z. Duan, K. Svanberg, H.Q. Feng, Z.W. Song, G.Y. Zhao, M. Brydegaard, S. Svanberg, Insect abundance over Chinese rice fields in relation to environmental parameters, studied with a polarization-sensitive CW near-IR lidar system. Appl. Phys. B 123, 211 (2017). https://doi.org/10.1007/s00340-017-6784-x ADSCrossRefGoogle Scholar
- 33.G. Zhao, E. Malmqvist, K. Rydhmer, A. Strand, G. Bianco, L.-A. Hansson, S. Svanberg, M. Brydegaard, Inelastic hyperspectral lidar for aquatic monitoring and landscape plant scanning test, ILRC28. Bucharest 176, 1003 (2017)Google Scholar
- 34.J. Erdkamp, J. Marriage, Theodor Scheimpflug—the life and work of the man who gave us that rule. Photographica World 3, 29–38 (2012)Google Scholar
- 35.S. Svanberg, LIDAR, in Springer Handbook of Lasers and Optics, 2nd edn. ed. by F. Träger (Springer, Heidelberg, 2012), p. 1146Google Scholar
- 38.M. Brydegaard, E. Malmqvist, S. Jansson, J. Larsson, S. Török, G. Zhao, The Scheimpflug lidar method, in Proceedings of SPIE, vol. 10406 (2017)Google Scholar