Abstract
Purpose of ReviewWe 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 FindingsIn 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.SummaryThe 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.
Highlights
This review focuses on the recent progress in remote sensing detection of early responses of plants to biotic and abiotic stresses
The highest spectral resolution in satellites with regular acquisition schedule is currently provided by MODIS while the highest spatial resolution is provided by Sentinel and the highest temporal range by Landsat
The spatial, spectral and temporal resolutions of satellite sensors constrain the reliability of monitoring plant biochemical variables such as pigment content or LAI at different spatial and temporal scales [109]
Summary
This review focuses on the recent progress in remote sensing detection of early responses of plants to biotic and abiotic stresses. Recent studies have demonstrated the capability of spectral data to detect physiological alterations and anticipate vegetation diseases such as Phytophthora [2], Xylella fastidiosa [3], Verticillium wilt [4] and almond red leaf blotch [5], as well as environmental stressors such as water stress [6]. These achievements represent a major step forward in the monitoring of vegetation health from airborne remote sensing imagery and its potential application to satellite scales. It describes four groups of physiological indicators (PIs) of critical importance in plant functioning for improving vegetation monitoring: (i) vegetation temperature, (ii) chlorophyll fluorescence, (iii) photoprotective pigments or the xanthophyll cycle and (iv) photosynthetic pigments (Fig. 1)
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