Early Diagnosis of Vegetation Health From High-Resolution Hyperspectral and Thermal Imagery

Lessons Learned From Empirical Relationships and Radiative Transfer Modelling

R. Hernández-Clemente (Corresponding Author), A. Hornero, M. Mottus, J. Penuelas, V. González-Dugo, J. C. Jiménez, L. Suárez, L. Alonso, P. J. Zarco-Tejada

Research output: Contribution to journalReview ArticleScientificpeer-review

Abstract

Purpose of Review: We provide a comprehensive review of the empirical and modelling approaches used to quantify the radiation–vegetation interactions related to vegetation temperature, leaf optical properties linked to pigment absorption and chlorophyll fluorescence emission, and of their capability to monitor vegetation health. Part 1 provides an overview of the main physiological indicators (PIs) applied in remote sensing to detect alterations in plant functioning linked to vegetation diseases and decline processes. Part 2 reviews the recent advances in the development of quantitative methods to assess PI through hyperspectral and thermal images. Recent Findings: In recent years, the availability of high-resolution hyperspectral and thermal images has increased due to the extraordinary progress made in sensor technology, including the miniaturization of advanced cameras designed for unmanned aerial vehicle (UAV) systems and lightweight aircrafts. This technological revolution has contributed to the wider use of hyperspectral imaging sensors by the scientific community and industry; it has led to better modelling and understanding of the sensitivity of different ranges of the electromagnetic spectrum to detect biophysical alterations used as early warning indicators of vegetation health. Summary: The review deals with the capability of PIs such as vegetation temperature, chlorophyll fluorescence, photosynthetic energy downregulation and photosynthetic pigments detected through remote sensing to monitor the early responses of plants to different stressors. Various methods for the detection of PI alterations have recently been proposed and validated to monitor vegetation health. The greatest challenges for the remote sensing community today are (i) the availability of high spatial, spectral and temporal resolution image data; (ii) the empirical validation of radiation–vegetation interactions; (iii) the upscaling of physiological alterations from the leaf to the canopy, mainly in complex heterogeneous vegetation landscapes; and (iv) the temporal dynamics of the PIs and the interaction between physiological changes.
Original languageEnglish
Pages (from-to)169-183
Number of pages15
JournalCurrent Forestry Reports
Volume5
Issue number3
DOIs
Publication statusPublished - 15 Sep 2019
MoE publication typeA2 Review article in a scientific journal

Fingerprint

early diagnosis
radiative transfer
imagery
heat
vegetation
modeling
remote sensing
sensors (equipment)
pigment
monitoring
chlorophyll
fluorescence
pigments
sensor
aircraft
upscaling
optical properties
image resolution
health
cameras

Keywords

  • Hyperspectral and thermal data
  • Physiological indicators
  • Radiative transfer models
  • Vegetation health
  • Vegetation indices

Cite this

Hernández-Clemente, R. ; Hornero, A. ; Mottus, M. ; Penuelas, J. ; González-Dugo, V. ; Jiménez, J. C. ; Suárez, L. ; Alonso, L. ; Zarco-Tejada, P. J. / Early Diagnosis of Vegetation Health From High-Resolution Hyperspectral and Thermal Imagery : Lessons Learned From Empirical Relationships and Radiative Transfer Modelling. In: Current Forestry Reports. 2019 ; Vol. 5, No. 3. pp. 169-183.
@article{d98e12c5257f4b99afee15e0e7694a51,
title = "Early Diagnosis of Vegetation Health From High-Resolution Hyperspectral and Thermal Imagery: Lessons Learned From Empirical Relationships and Radiative Transfer Modelling",
abstract = "Purpose of Review: We provide a comprehensive review of the empirical and modelling approaches used to quantify the radiation–vegetation interactions related to vegetation temperature, leaf optical properties linked to pigment absorption and chlorophyll fluorescence emission, and of their capability to monitor vegetation health. Part 1 provides an overview of the main physiological indicators (PIs) applied in remote sensing to detect alterations in plant functioning linked to vegetation diseases and decline processes. Part 2 reviews the recent advances in the development of quantitative methods to assess PI through hyperspectral and thermal images. Recent Findings: In recent years, the availability of high-resolution hyperspectral and thermal images has increased due to the extraordinary progress made in sensor technology, including the miniaturization of advanced cameras designed for unmanned aerial vehicle (UAV) systems and lightweight aircrafts. This technological revolution has contributed to the wider use of hyperspectral imaging sensors by the scientific community and industry; it has led to better modelling and understanding of the sensitivity of different ranges of the electromagnetic spectrum to detect biophysical alterations used as early warning indicators of vegetation health. Summary: The review deals with the capability of PIs such as vegetation temperature, chlorophyll fluorescence, photosynthetic energy downregulation and photosynthetic pigments detected through remote sensing to monitor the early responses of plants to different stressors. Various methods for the detection of PI alterations have recently been proposed and validated to monitor vegetation health. The greatest challenges for the remote sensing community today are (i) the availability of high spatial, spectral and temporal resolution image data; (ii) the empirical validation of radiation–vegetation interactions; (iii) the upscaling of physiological alterations from the leaf to the canopy, mainly in complex heterogeneous vegetation landscapes; and (iv) the temporal dynamics of the PIs and the interaction between physiological changes.",
keywords = "Hyperspectral and thermal data, Physiological indicators, Radiative transfer models, Vegetation health, Vegetation indices",
author = "R. Hern{\'a}ndez-Clemente and A. Hornero and M. Mottus and J. Penuelas and V. Gonz{\'a}lez-Dugo and Jim{\'e}nez, {J. C.} and L. Su{\'a}rez and L. Alonso and Zarco-Tejada, {P. J.}",
year = "2019",
month = "9",
day = "15",
doi = "10.1007/s40725-019-00096-1",
language = "English",
volume = "5",
pages = "169--183",
journal = "Current Forestry Reports",
issn = "2198-6436",
publisher = "Springer",
number = "3",

}

Early Diagnosis of Vegetation Health From High-Resolution Hyperspectral and Thermal Imagery : Lessons Learned From Empirical Relationships and Radiative Transfer Modelling. / Hernández-Clemente, R. (Corresponding Author); Hornero, A.; Mottus, M.; Penuelas, J.; González-Dugo, V.; Jiménez, J. C.; Suárez, L.; Alonso, L.; Zarco-Tejada, P. J.

In: Current Forestry Reports, Vol. 5, No. 3, 15.09.2019, p. 169-183.

Research output: Contribution to journalReview ArticleScientificpeer-review

TY - JOUR

T1 - Early Diagnosis of Vegetation Health From High-Resolution Hyperspectral and Thermal Imagery

T2 - Lessons Learned From Empirical Relationships and Radiative Transfer Modelling

AU - Hernández-Clemente, R.

AU - Hornero, A.

AU - Mottus, M.

AU - Penuelas, J.

AU - González-Dugo, V.

AU - Jiménez, J. C.

AU - Suárez, L.

AU - Alonso, L.

AU - Zarco-Tejada, P. J.

PY - 2019/9/15

Y1 - 2019/9/15

N2 - Purpose of Review: We provide a comprehensive review of the empirical and modelling approaches used to quantify the radiation–vegetation interactions related to vegetation temperature, leaf optical properties linked to pigment absorption and chlorophyll fluorescence emission, and of their capability to monitor vegetation health. Part 1 provides an overview of the main physiological indicators (PIs) applied in remote sensing to detect alterations in plant functioning linked to vegetation diseases and decline processes. Part 2 reviews the recent advances in the development of quantitative methods to assess PI through hyperspectral and thermal images. Recent Findings: In recent years, the availability of high-resolution hyperspectral and thermal images has increased due to the extraordinary progress made in sensor technology, including the miniaturization of advanced cameras designed for unmanned aerial vehicle (UAV) systems and lightweight aircrafts. This technological revolution has contributed to the wider use of hyperspectral imaging sensors by the scientific community and industry; it has led to better modelling and understanding of the sensitivity of different ranges of the electromagnetic spectrum to detect biophysical alterations used as early warning indicators of vegetation health. Summary: The review deals with the capability of PIs such as vegetation temperature, chlorophyll fluorescence, photosynthetic energy downregulation and photosynthetic pigments detected through remote sensing to monitor the early responses of plants to different stressors. Various methods for the detection of PI alterations have recently been proposed and validated to monitor vegetation health. The greatest challenges for the remote sensing community today are (i) the availability of high spatial, spectral and temporal resolution image data; (ii) the empirical validation of radiation–vegetation interactions; (iii) the upscaling of physiological alterations from the leaf to the canopy, mainly in complex heterogeneous vegetation landscapes; and (iv) the temporal dynamics of the PIs and the interaction between physiological changes.

AB - Purpose of Review: We provide a comprehensive review of the empirical and modelling approaches used to quantify the radiation–vegetation interactions related to vegetation temperature, leaf optical properties linked to pigment absorption and chlorophyll fluorescence emission, and of their capability to monitor vegetation health. Part 1 provides an overview of the main physiological indicators (PIs) applied in remote sensing to detect alterations in plant functioning linked to vegetation diseases and decline processes. Part 2 reviews the recent advances in the development of quantitative methods to assess PI through hyperspectral and thermal images. Recent Findings: In recent years, the availability of high-resolution hyperspectral and thermal images has increased due to the extraordinary progress made in sensor technology, including the miniaturization of advanced cameras designed for unmanned aerial vehicle (UAV) systems and lightweight aircrafts. This technological revolution has contributed to the wider use of hyperspectral imaging sensors by the scientific community and industry; it has led to better modelling and understanding of the sensitivity of different ranges of the electromagnetic spectrum to detect biophysical alterations used as early warning indicators of vegetation health. Summary: The review deals with the capability of PIs such as vegetation temperature, chlorophyll fluorescence, photosynthetic energy downregulation and photosynthetic pigments detected through remote sensing to monitor the early responses of plants to different stressors. Various methods for the detection of PI alterations have recently been proposed and validated to monitor vegetation health. The greatest challenges for the remote sensing community today are (i) the availability of high spatial, spectral and temporal resolution image data; (ii) the empirical validation of radiation–vegetation interactions; (iii) the upscaling of physiological alterations from the leaf to the canopy, mainly in complex heterogeneous vegetation landscapes; and (iv) the temporal dynamics of the PIs and the interaction between physiological changes.

KW - Hyperspectral and thermal data

KW - Physiological indicators

KW - Radiative transfer models

KW - Vegetation health

KW - Vegetation indices

UR - http://www.scopus.com/inward/record.url?scp=85071277202&partnerID=8YFLogxK

U2 - 10.1007/s40725-019-00096-1

DO - 10.1007/s40725-019-00096-1

M3 - Review Article

VL - 5

SP - 169

EP - 183

JO - Current Forestry Reports

JF - Current Forestry Reports

SN - 2198-6436

IS - 3

ER -