Purpose of Review: The successful application of thermal infrared (TIR) remote sensing in the agricultural domain, largely driven by the arrival of new platforms and sensors that substantially increased thermal data resolution and availability, has sparked interest in thermography as a tool for monitoring forest health. In this review, we take a step back to reflect on what physiological responses are reflected in leaf and canopy temperature and summarise research activities on TIR remote sensing of stress responses in forest environments, highlighting current methodological challenges, open questions, and promising opportunities. Recent Findings: This systematic literature review showed that whilst the focus still remains on satellite imagery, Uncrewed Aerial Vehicles (UAVs) are playing an increasingly important role in testing the capabilities and sensitivity to stress onset at the individual tree level. To date, drought stress has been the focal point of research, largely due to its direct link to stomatal functioning at leaf level. Though, research into thermal responses to other stressors, e.g. pathogens, is also gaining momentum. Summary: Disentangling stress-induced canopy temperature variations from environmental factors and structural influences remains the main challenge for broader application of TIR remote sensing. Further development and testing of approaches for thermal data analysis, including their applicability for different tree species and sensitivity under different climatic conditions, are required to establish how TIR remote sensing can best complement existing forest health monitoring approaches.

Vegetation water content, quantified as the leaf equivalent water thickness (EWT), can serve as an indicator of vegetation stress. The intensity data recorded by terrestrial laser scanning (TLS) instruments, operating at shortwave infrared wavelengths, can be used to estimate the three-dimensional distribution of EWT, after a full and rigorous calibration for the range and incidence angle effects. However, TLS instruments do not record the incidence angles automatically, making calibration challenging. In this study, intensity data from two commercially available TLS instruments (Leica P40, 1550 nm shortwave infrared wavelength, and Leica P20, 808 nm near-infrared wavelength) were combined in a normalized difference index (NDI). The NDI was found to minimize the incidence angle effects with no need for further calibration. A dry-down experiment was conducted using deciduous and conifer canopies. The NDI was found to be highly correlated to EWT at leaf level ( R ² of 0.91 and 0.74) and at canopy level ( R ² of 0.89 and 0.74) for the deciduous and conifer canopies, respectively. Three-dimensional distributions of EWT at canopy level were generated, which revealed some vertical heterogeneity.

Recently, terrestrial laser scanning (TLS) has shown potential in measuring vegetation biochemical traits in three dimensions (3D) by using reflectance derived from backscattered intensity data. The 3D estimates can provide information about the vertical heterogeneity of canopy biochemical traits which affects canopy reflectance but cannot be measured from spaceborne and airborne optical remote sensing data. Leaf equivalent water thickness (EWT), a metric widely used in vegetation health monitoring, has been successfully linked to the normalized difference index (NDI) of near and shortwave infrared wavelengths at the leaf level. However, only two previous studies have linked EWT to NDI at the canopy level in field campaigns. In this study, an NDI consisting of 808 and 1550 nm wavelengths was used to generate 3D EWT estimates at the canopy level in a broadleaf mixed-species tree plot during and after a heatwave. The relative error in EWT estimates was 6% across four different species. Temporal changes in EWT were measured, and the accuracy varied between trees, a factor of the errors in EWT estimates on both dates. Vertical profiles of EWT were generated for six trees and showed vertical heterogeneity and variation between species. The change in EWT vertical profiles during and after the heatwave differed between trees, demonstrating that trees reacted in different ways to the drought condition.

Leaf chlorophyll content is a major indicator of plant health and productivity. Optical remote sensing estimation of chlorophyll limits its retrievals to two-dimensional (2D) estimates, not allowing examination of its distribution within the canopy, although it exhibits large variation across the vertical profile. Multispectral and hyperspectral Terrestrial Laser Scanning (TLS) instruments can produce three-dimensional (3D) chlorophyll estimates but are not widely available. Thus, in this study, 14 chlorophyll vegetation indices were developed using six wavelengths employed in commercial TLS instruments (532 nm, 670 nm, 808 nm, 785 nm, 1064 nm, and 1550 nm). For this, 200 simulations were carried out using the novel bidirectional mode in the Discrete Anisotropic Radiative Transfer (DART) model and a realistic forest stand. The results showed that the Green Normalized Difference Vegetation Index (GNDVI) of the 532 nm and either the 808 nm or the 785 nm wavelengths were highly correlated to the chlorophyll content (R² = 0.74). The Chlorophyll Index (CI) and Green Simple Ratio (GSR) of the same wavelengths also displayed good correlation (R² = 0.73). This study was a step towards canopy 3D chlorophyll retrieval using commercial TLS instruments, but methods to couple the data from the different instruments still need to be developed.

Terrestrial laser scanning (TLS) instruments have been widely utilized in measuring vegetation canopy structural parameters, being capable of providing high density point clouds. However, less attention has been paid to using TLS intensity data in estimating vegetation biochemical attributes, and calculating water status metrics, that can help in early detection of vegetation stress and risk of wildfire. Water status metrics, such as the leaf Equivalent Water Thickness (EWT) and the Fuel Moisture Content (FMC), are being commonly estimated from optical remote sensing data. However, such estimates mainly reflect the water status of canopy top and ignore the vertical heterogeneity of water content distribution within the canopy. The estimates are also affected by canopy structure and understory reflectance. Such limitations can potentially be addressed using TLS intensity data, as observations are performed in three dimensions (3D). This study therefore investigated the potential of using dual-wavelength TLS intensity data to estimate FMC in 3D. The calculated Normalized Difference Index (NDI) of 808 nm near infrared and 1550 nm shortwave infrared wavelengths was found to be correlated to FMC at leaf level for four different tree species. The correlation was moderate, and the relationships were not consistent between species. NDI was subsequently used to estimate FMC at canopy level in seven trees in a small tree plot with an average error < 5 %. The 3D estimates of FMC revealed vertical heterogeneity in all trees measured, which varied between species and also between trees from the same species.