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Land surface temperature (LST) is a fundamental parameter within the system of the Earth's surface and atmosphere, which can be used to describe the inherent physical processes of energy and water exchange. The need for LST has been increasingly recognised in agriculture, as it affects the growth phases of crops and crop yields. However, challenges in overcoming the large discrepancies between the retrieved LST and ground truth data still exist. Precise LST measurement depends mainly on accurately deriving the surface emissivity, which is very dynamic due to changing states of land cover and plant development. In this study, we present an LST retrieval algorithm for the combined use of multispectral optical and thermal UAV images, which has been optimised for operational applications in agriculture to map the heterogeneous and diverse agricultural crop systems of a research campus in Germany (April 2018). We constrain the emissivity using certain NDVI thresholds to distinguish different land surface types. The algorithm includes atmospheric corrections and environmental thermal emissions to minimise the uncertainties. In the analysis, we emphasise that the omission of crucial meteorological parameters and inaccurately determined emissivities can lead to a considerably underestimated LST; however, if the emissivity is underestimated, the LST can be overestimated. The retrieved LST is validated by reference temperatures from nearby ponds and weather stations. The validation of the thermal measurements indicates a mean absolute error of about 0.5 K. The novelty of the dual sensor system is that it simultaneously captures highly spatially resolved optical and thermal images, in order to construct the precise LST ortho-mosaics required to monitor plant diseases and drought stress and validate airborne and satellite data. [ABSTRACT FROM AUTHOR]

The growing availability of global measurements of sun-induced chlorophyll fluorescence (SIF) can help in improving crop monitoring, especially the monitoring of photosynthetic activity. However, variations in top-of-canopy (TOC) SIF cannot be directly interpreted as physiological changes because of the confounding effects of vegetation biochemistry (i.e. pigments, dry matter and water) and structure. In this study, we propose an approach of using radiative transfer models (RTMs) and TOC reflectance to estimate the biochemical and structural effects on TOC SIF, as a necessary step in retrieving physiological information from TOC SIF. The approach was assessed by using airborne (HyPlant) reflectance and SIF data acquired over an agricultural experimental farm in Germany on two days, before and during a heat event in summer 2015 with maximum temperatures of 27°C and 34°C, respectively. The results show that over 76% variation among different crops in SIF observations was explained by variation in vegetation biochemistry and structure. In addition, the changes of vegetation biochemistry and structure explained as much as 73% variation between the two days in far-red SIF, and 40% variation in red SIF. The remaining unexplained variation was mostly attributed to the variability in physiological status. We conclude that reflectance provides valuable information to account for biochemical and structural effects on SIF and to advance analysis of SIF observations. The combination of RTMs, reflectance and SIF opens new pathways to detect vegetation biochemical, structural and physiological changes. • Vegetation biochemistry and structure have a large impact on TOC SIF. • Variations in observed TOC SIF were largely explained by reflectance. • A unique HyPlant dataset comprising reflectance and SIF was used. • Reflectance and SIF should be used together for plant physiology monitoring. [ABSTRACT FROM AUTHOR]

The photosynthesis of various species or even a single plant varies dramatically in time and space, creating great spatial heterogeneity within a plant canopy. Continuous and spatially explicit monitoring is, therefore, required to assess the dynamic response of plant photosynthesis to the changing environment. This is a very challenging task when using the existing portable field instrumentation. This paper reports on the application of a technique, laser-induced fluorescence transient (LIFT), developed for ground remote measurement of photosynthetic efficiency at a distance of up to 50 m. The LIFT technique was used to monitor the seasonal dynamics of selected leaf groups within inaccessible canopies of deciduous and evergreen tree species. Electron transport rates computed from LIFT measurements varied over the growth period between the different species studied. The LIFT canopy data and light-use efficiency measured under field conditions correlated reasonably well with the single-leaf pulse amplitude-modulated measurements of broadleaf species, but differed significantly in the case of conifer tree species. The LIFT method has proven to be applicable for a remote sensing assessment of photosynthetic parameters on a diurnal and seasonal scale; further investigation is, however, needed to evaluate the influence of complex heterogeneous canopy structures on LIFT-measured chlorophyll fluorescence parameters., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)