BRDFs acquired by directional radiative measurements during EAGLE and AGRISAR

Radiation is the driving force for all processes and interactions between earth surface and atmosphere. The amount of measured radiation reflected by vegetation depends on its structure, the viewing angle and the solar angle. This angular dependence is usually expressed in the Bi-directional Reflectance Distribution Function (BRDF). This BRDF is not only different for different types of vegetation, but also different for different stages of the growth. The BRDF therefore has to be measured at ground level before any satellite imagery can be used the calculate surface-atmosphere interaction. The objective of this research is to acquire the BRDFs for agricultural crop types. A goniometric system is used to acquire the BRDFs. This is a mechanical device capable of a complete hemispherical rotation. The radiative directional measurements are performed with different sensors that can be attached to this system. The BRDFs are calculated from the measured radiation. In the periods 10 June - 18 June 2006 and 2 July - 10 July 2006 directional radiative measurements were performed at three sites: Speulderbos site, in the Netherlands, the Cabauw site, in the Netherlands, and an agricultural test site in Goermin, Germany. The measurements were performed over eight different crops: forest, grass, pine tree, corn, wheat, sugar beat and barley. The sensors covered the spectrum from the optical to the thermal domain. The measured radiance is used to calculate the BRDFs or directional thermal signature. This contribution describes the measurements and calculation of the BRDFs of forest, grassland, young corn, mature corn, wheat, sugar beat and barley during the EAGLE2006 and AGRISAR 2006 fieldcampaigns. Optical BRDF have been acquired for all crops except barley. Thermal angular signatures are acquired for all the crop

Retrieval of canopy component temperatures through Bayesian inversion of directional thermal measurements

Evapotranspiration is usually estimated in remote sensing from single temperature value representing both soil and vegetation. This surface temperature is an aggregate over multiple canopy components. The temperature of the individual components can differ significantly, introducing errors in the evapotranspiration estimations. The temperature aggregate has a high level of directionality. An inversion method is presented in this paper to retrieve four canopy component temperatures from directional brightness temperatures. The Bayesian method uses both a priori information and sensor characteristics to solve the ill-posed inversion problem. The method is tested using two case studies: 1) a sensitivity analysis, using a large forward simulated dataset, and 2) in a reality study, using two datasets of two field campaigns. The results of the sensitivity analysis show that the Bayesian approach is able to retrieve the four component temperatures from directional brightness temperatures with good success rates using multi-directional sensors (Srspectra˜0.3, Srgonio˜0.3, and SrAATSR˜0.5), and no improvement using mono-angular sensors (Sr˜1). The results of the experimental study show that the approach gives good results for high LAI values (RMSEgrass=0.50 K, RMSEwheat=0.29 K, RMSEsugar beet=0.75 K, RMSEbarley=0.67 K); but for low LAI values the results were unsatisfactory (RMSEyoung maize=2.85 K). This discrepancy was found to originate from the presence of the metallic construction of the setup. As these disturbances, were only present for two crops and were not present in the sensitivity analysis, which had a low LAI, it is concluded that using masked thermal images will eliminate this discrepanc

Observation and assessment of model retrievals of surface exchange components over a row canopy using directional thermal data

Land surface temperature is an essential climate variable that can serve as a proxy for detecting water deficiencies in croplands and wooded areas. Its measurement can however be influenced by anisotropic properties of surface targets leading to occurrence of directional effects on the signal. This may lead to an incorrect interpretation of thermal measurements. In this study, we perform model assessments and check the influence of thermal radiation directionality using data over a vineyard. To derive the overall directional surface temperatures, elemental values measured by individual cameras were aggregated according to the respective cover fractions/weights in viewing direction. Aggregated temperatures from the turbid model were compared to corresponding temperatures simulated by the 3D DART radiative transfer model. The reconstructed temperatures were then used in surface-energy-balance (SEB) simulations to assess the impact of the Sun-target-sensor geometry on retrievals. Here, the pseudo-isotropic Soil-Plant-Atmosphere-Remote-Sensing-of-Evapotranspiration (SPARSE) dual-source model together with the non-isotropic version (SPARSE4), were used. Both schemes were able to retrieve overall fluxes satisfactorily, confirming a previous study. However, the sensitivity (of flux and component temperature estimates) of the schemes to viewing direction was tested for the first time using reconstructed sets of directional thermal data to force the models. Degradation (relative to nadir) in flux retrieval cross-row was observed, with better consistency along rows. Overall, it was nevertheless shown that SPARSE4 is less influenced by the viewing direction of the temperature than SPARSE, particularly for strongly off-nadir viewing. Some directional/asymmetrical artefacts are however not well reproduced by the simple Radiative Transfer Methods (RTM), which can then manifest in and influence the subsequent thermal-infrared-driven SEB modelling.This work was supported by the ALTOS project (PRIMA 2018 - Section 2), with grants provided by ANR via the agreement n°ANR-18-PRIM-0011-02 as well as the CNES/TOSCA program for the TRISHNA project. First author acknowledges the financial support of his PhD from CNES and Région Occitanie. The field experiments were carried out in the context of the HiLiaise and ESA WineEO projects. Joan Boldu (proprietor) and David Tous (SafSampling) are also acknowledged for allowing/providing access to the site and other site related data. Nicolas Lauret’s help with preparation of the DART mock-ups is appreciated.info:eu-repo/semantics/publishedVersio

Fast matrix treatment of 3-D radiative transfer in vegetation canopies: SPARTACUS-Vegetation 1.1

A fast scheme is described to compute the 3-D interaction of solar radiation with vegetation canopies. The canopy is split in the horizontal plane into one clear region and one or more vegetated regions, and the two-stream equations are used for each, but with additional terms representing lateral exchange of radiation between regions that are proportional to the area of the interface between them. The resulting coupled set of ordinary differential equations is solved using the matrix-exponential method. The scheme is compared to solar Monte Carlo calculations for idealized scenes from the RAMI4PILPS intercomparison project, for open forest canopies and shrublands both with and without snow on the ground. Agreement is good in both the visible and infrared: for the cases compared, the root-mean-squared difference in reflectance, transmittance and canopy absorptance is 0.020, 0.038 and 0.033, respectively. The technique has potential application to weather and climate modelling

Automated Directional Measurement System for the Acquisition of Thermal Radiative Measurements of Vegetative Canopies

The potential for directional optical and thermal imagery is very large. Field measurements have been performed with a goniometer on which thermal instruments were attached. In order to reduce dynamical effects the goniometer was adjusted to run in automated mode, for zenith and azimuthal direction. Directional measurements were performed over various crops with increasing heterogeneity. The improvements to the goniometer proved successful. For all the crops, except the vineyard, the acquisition of the directional thermal brightness temperatures of the crops went successfully. The large scale heterogeneity of the vineyard proved to be larger then the goniometer was capable of. The potential of directional thermal brightness temperatures has been proven

Estimation of vegetation cover at subpixel resolution using LANDSAT data

The present report summarizes the various approaches relevant to estimating canopy cover at subpixel resolution. The approaches are based on physical models of radiative transfer in non-homogeneous canopies and on empirical methods. The effects of vegetation shadows and topography are examined. Simple versions of the model are tested, using the Taos, New Mexico Study Area database. Emphasis has been placed on using relatively simple models requiring only one or two bands. Although most methods require some degree of ground truth, a two-band method is investigated whereby the percent cover can be estimated without ground truth by examining the limits of the data space. Future work is proposed which will incorporate additional surface parameters into the canopy cover algorithm, such as topography, leaf area, or shadows. The method involves deriving a probability density function for the percent canopy cover based on the joint probability density function of the observed radiances

Design, fabrication and evaluation of chalcogenide glass Luneburg lenses for LiNbO3 integrated optical devices

Optical waveguide Luneburg lenses of arsenic trisulfide glass are described. The lenses are formed by thermal evaporation of As2S3 through suitably placed masks onto the surface of LiNbO3:Ti indiffused waveguides. The lenses are designed for input apertures up to 1 cm and for speeds of f/5 or better. They are designed to focus the TM sub 0 guided mode of a beam of wavelength, external to the guide, of 633 nm. The refractive index of the As2S3 films and the changes induced in the refractive index by exposure to short wavelength light were measured. Some correlation between film thickness and optical properties was noted. The short wavelength photosensitivity was used to shorten the lens focal length from the as deposited value. Lenses of rectangular shape, as viewed from above the guide, as well as conventional circular Luneburg lenses, were made. Measurements made on the lenses include thickness profile, general optical quality, focal length, quality of focal spot, and effect of ultraviolet irradiation on optical properties

The retrieval of plant functional traits from canopy spectra through RTM-inversions and statistical models are both critically affected by plant phenology

Plant functional traits play a key role in the assessment of ecosystem processes and properties. Optical remote sensing is ascribed a high potential in capturing those traits and their spatiotemporal patterns. In vegetation remote sensing, reflectance-based retrieval methods are either statistical (relying on empirical observations) or physically-based (based on inversions of a radiative transfer model, RTM). Both trait retrieval approaches remain poorly investigated regarding phenology. However, within the phenology of a plant, its leaf constituents, canopy structure, and the presence of phenology-related organs (i.e., flowers or inflorescence) vary considerably – and so does its reflectance. We, therefore, addressed the question of how plant phenology affects the predictive performance of both statistical and RTM-based methods and how this effect differs between traits. For a complete growing season, we weekly measured traits of 45 herbaceous plant species together with hyperspectral canopy reflectance (ASD FieldSpec III). Plants were grown in an experimental setup. The investigated traits comprised Leaf Area Index (LAI) and the leaf traits chlorophyll, anthocyanins, carotenoids, equivalent water thickness, and leaf mass per area. We compared the predictive performances of PLSR models and three variants of PROSAIL inversions based on (1) all observations and based on (2) a phenological subset where flowering plants were excluded and only those observations most suitable for modeling were kept. Our results show that both statistical and RTM-based trait retrievals were largely affected by phenology. For carotenoids for example, R$^{2}$ decreased from 0.58 at non-flowering canopies to 0.25 at 100% flowering canopies. Temporal trends were diverse. LAI and equivalent water thickness were best estimated earlier in the growing season; chlorophyll and carotenoids towards senescence. PLSR models showed generally higher bias than the PROSAIL-based retrieval approaches. Lookup-table inversion of PROSAIL in combination with a continuous wavelet transformation of reflectance showed highest accuracies. We found RTM-based retrieval not to be as accurate and transferable as previously indicated. Our results suggest that phenology is essential for accurate retrieval of plant functional traits and varies depending on the studied species and functional traits, respectively

Theory of radiative transfer models applied in optical remote sensing of vegetation canopies

In this thesis the work of the author on the modelling of radiative transfer in vegetation canopies and the terrestrial atmosphere is summarized. The activities span a period of more than fifteen years of research in this field carried out at the National Aerospace Laboratory NLR.For the interpretation of optical remote sensing observations of vegetation canopies from satellites or aircraft the use of simulation models can be an important tool, as these models give insight in the relations between vegetation properties and observed remote sensing data.The models discussed here are first presented from a theoretical point of view. An attempt has been made to construct a framework in which all the discussed models, for vegetation as well as for the atmosphere, can be represented. After an introduction on basic radiometric quantities and relations (chapter 2), and a classification of radiative transfer models and solution methods (chapter 3), examples of existing models are discussed in chapter 4.In chapter 5 a new generalized theory of radiative transfer models for azimuthally isotropic media is presented, namely the (N+2)-stream theory. This theory describes radiative transfer in vegetation canopies or atmospheres to any desired numerical accuracy. In the formulation of the analytical solution of this model, which is based on eigenvector decomposition, much attention has been paid to possible numerical problems. Symmetry relations are exploited in order to reduce memory requirements and computation time, and expressions have been found for which the so-called reciprocity relations are automatically fulfilled. The numerical capabilities of this model for simulation of atmospheric radiative transfer are demonstrated in chapter 6.The theory of the vegetation canopy bidirectional reflectance models SAIL and SAILH are discussed in chapters 7 and 8. Both are four-stream models. In SAILH the so-called hot spot effect, which is related with the finite leaf size, is incorporated. After these more theoretic chapters, practical aspects of the radiative transfer models are discussed in the following chapters.In chapter 9 the application of a four-stream atmosphere model to the correction and calibration of Landsat Thematic Mapper images is demonstrated. This atmosphere model has been coupled with the SAILH model into an overall four-stream model of optical remote sensing observations from any altitude. This model is called OSCAR (optical soil-canopyatmosphere radiance) and is presented in chapter 10.Applications of radiative transfer modelling to optical remote sensing problems are illustrated in chapter 11, and chapter 12, summarizes the conclusions of this thesis