Remote Vegetation Diagnostics in Ghana with a Hyperspectral Fluorescence Lidar
Boateng, Rabbi ; Huzortey, Andrew ; Adolphe Gbogbo, Y. ; Yamoa, A. S. Doria ; Zoueu, Jérémie T. ; Brydegaard, Mikkel LU ; Anderson, Benjamin and Månefjord, Hampus LU
(2023)
In IEEE Journal of Selected Topics in Quantum Electronics
29(4: Biophotonics).
p.1-7
- Abstract
- Spectral imaging and lidar methods for the characterization of vegetation are vital for understanding plants and, in turn, food security, biodiversity, and vegetation health in a changing climate. While novel hyperspectral imaging, canopy lidar,and solar-induced fluorescence provide details on species, state, structure, and plant physiology, such data come from different instruments. Thus, post-processing and data fusion struggles with synchronization, spatial overlap, and resolution issues. Especially in the tropical regions of sub-Saharan Africa, these complex, expensive, and bulky instruments remain inaccessible. Here, in Ghana, we have built a low-cost, lightweight, and realistic instrument for simultaneously acquiring hyperspectral... (More)
- Spectral imaging and lidar methods for the characterization of vegetation are vital for understanding plants and, in turn, food security, biodiversity, and vegetation health in a changing climate. While novel hyperspectral imaging, canopy lidar,and solar-induced fluorescence provide details on species, state, structure, and plant physiology, such data come from different instruments. Thus, post-processing and data fusion struggles with synchronization, spatial overlap, and resolution issues. Especially in the tropical regions of sub-Saharan Africa, these complex, expensive, and bulky instruments remain inaccessible. Here, in Ghana, we have built a low-cost, lightweight, and realistic instrument for simultaneously acquiring hyperspectral data of vegetation fluorescence and canopy structure with perfect spatial overlap. In this paper, we demonstrate the application of the hyperspectral fluorescence lidar for diagnostics and species specificity of locally significant crops. We demonstrate simultaneous range and fluorescence measurements of forest canopy, conducted in full sunlight. Our results indicate that the upper side of the leaves shows a more substantial deviation for stressed plants, whilethe lower side shows greater contrast for plant species. This new and simple tool provides a combined method for hyperspectral classification and assessment of the physiological state while also reporting the vegetation height over ground and its diversity. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/c98ca963-da0e-4f39-a5b8-24b04ec5bf67
- author
- Boateng, Rabbi
; Huzortey, Andrew
; Adolphe Gbogbo, Y.
; Yamoa, A. S. Doria
; Zoueu, Jérémie T.
; Brydegaard, Mikkel
LU
; Anderson, Benjamin
and Månefjord, Hampus
LU
- organization
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- published
- subject
- in
- IEEE Journal of Selected Topics in Quantum Electronics
- volume
- 29
- issue
- 4: Biophotonics
- pages
- 1 - 7
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:85147199887
- ISSN
- 1077-260X
- DOI
- 10.1109/JSTQE.2023.3234022
- language
- English
- LU publication?
- yes
- id
- c98ca963-da0e-4f39-a5b8-24b04ec5bf67
- date added to LUP
- 2023-01-31 10:46:40
- date last changed
- 2023-12-16 04:03:22
@article{c98ca963-da0e-4f39-a5b8-24b04ec5bf67,
abstract = {{Spectral imaging and lidar methods for the characterization of vegetation are vital for understanding plants and, in turn, food security, biodiversity, and vegetation health in a changing climate. While novel hyperspectral imaging, canopy lidar,and solar-induced fluorescence provide details on species, state, structure, and plant physiology, such data come from different instruments. Thus, post-processing and data fusion struggles with synchronization, spatial overlap, and resolution issues. Especially in the tropical regions of sub-Saharan Africa, these complex, expensive, and bulky instruments remain inaccessible. Here, in Ghana, we have built a low-cost, lightweight, and realistic instrument for simultaneously acquiring hyperspectral data of vegetation fluorescence and canopy structure with perfect spatial overlap. In this paper, we demonstrate the application of the hyperspectral fluorescence lidar for diagnostics and species specificity of locally significant crops. We demonstrate simultaneous range and fluorescence measurements of forest canopy, conducted in full sunlight. Our results indicate that the upper side of the leaves shows a more substantial deviation for stressed plants, whilethe lower side shows greater contrast for plant species. This new and simple tool provides a combined method for hyperspectral classification and assessment of the physiological state while also reporting the vegetation height over ground and its diversity.}},
author = {{Boateng, Rabbi and Huzortey, Andrew and Adolphe Gbogbo, Y. and Yamoa, A. S. Doria and Zoueu, Jérémie T. and Brydegaard, Mikkel and Anderson, Benjamin and Månefjord, Hampus}},
issn = {{1077-260X}},
language = {{eng}},
number = {{4: Biophotonics}},
pages = {{1--7}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Journal of Selected Topics in Quantum Electronics}},
title = {{Remote Vegetation Diagnostics in Ghana with a Hyperspectral Fluorescence Lidar}},
url = {{http://dx.doi.org/10.1109/JSTQE.2023.3234022}},
doi = {{10.1109/JSTQE.2023.3234022}},
volume = {{29}},
year = {{2023}},
}