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Discrete anisotropic radiative transfer (DART) calibration is an iterative inversion method that is applied to shortwave (SW) satellite images to get maps of spectral signatures (SS) of city materials at the satellite spatial resolution. Therefore, it is potentially a handy spectral unmixing tool. However, up to now, it has only been validated by comparing the time series of SW radiative budget Q*SW from a flux tower in Basel to DART simulated Q*SW using maps of SS derived from satellite images. This article thoroughly assesses the DART calibration accuracy with two synthetic case studies, called “ideal” and “nonideal,” for short wavelengths. In both cases, the satellite image is a DART simulated image of an urban scene with ground, buildings with various structures, water, and shrubs. In the ideal case, SS maps are the only unknowns in the inversion process. The mean absolute value of the relative errors over all bands for ground, roof, water, tree, and shrub maps were 0.013, 0.005, 0.027, 0.297, and 0.250. In the nonideal case, we considered an uncertainty on parameters assumed to be known in the ideal case: solar zenith angle (SZA); satellite image spatial resolution; pixel-shift; inaccuracy of landscape modeling; and modulation transfer function (MTF). It led to larger errors: for ground, roof, water, tree, and shrubs, the mean absolute value of the relative error was 0.233, 0.507, 3.088, 0.834, and 1.256, respectively. By descending order of importance, the parameters that most affect the accuracy of the retrieved SS of urban material were SZA, satellite image spatial resolution, pixel-shift, inaccuracy of three-dimensional urban scene modeling, and MTF.

Physical models simulating the radiative budget (RB) and remote sensing (RS) observation of three-dimensional (3D) landscapes are critical to better understand human and natural components of the Earth system and further develop RS technology. DART is one of the most comprehensive 3D models of Earth-atmosphere optical radiative transfer (RT), from ultraviolet (UV) to thermal infrared (TIR). It simulates the optical signal of proximal, aerial and satellite imaging spectrometers and laser scanners, the 3D RB and solar induced chlorophyll fluorescence (SIF) signal, for any urban or natural landscape and any experimental or instrument configuration. It is freely available for research and teaching activities (https://dart.omp.eu). Here, five recent advances are presented. 1) Atmosphere RT. 2) RT in non repetitive topography. 3) Monte Carlo modelling for fast RS image simulation of large landscapes. 4) SIF modelling for vegetation simulated as facets and turbid cells. 5) RS image inversion for mapping the optical properties of urban material and the urban radiative budget.

The potential of solar-induced chlorophyll fluorescence (SIF) to monitor photosynthesis and plant stress has attracted considerable interest in SIF remote sensing (RS). However, canopy SIF and RS observations are impacted by topography, vegetation three dimension (3D) structure, leaf orientation, non foliar elements (e.g., tree woody skeleton), … Physically based downscaling of canopy SIF RS data to leaf-level (i.e., to leaf photosynthesis) requires 3D radiative transfer (RT) models simulating canopy SIF and its observation. These models are necessary to better exploit the potential of SIF, by linking leaf SIF and SIF in RS observations as a function of canopy 3D architecture and experimental configurations (sun and viewing directions, etc.). The Discrete Anisotropic Radiative Transfer (DART) model is a comprehensive 3D radiative transfer (RT) model for urban and natural landscapes. This paper presents its SIF modeling for vegetation simulated with facets, its validation with the SCOPE/mSCOPE 1D models, and its recent extension to SIF modelling for landscapes simulated with 3D turbid medium.

Remote sensing (RS) dedicated to the study of land surfaces benefits from more and more advanced sensors. However, the interpretation of RS data is often is often inaccurate due to the complexity of the observed land surfaces. Therefore, RS models, in particular physical models, that simulate RS observations of the three-dimensional (3D) landscapes are critical to correctly interpret RS data. DART is one of the most comprehensive 3D models of Earthatmosphere optical radiative transfer (RT), from ultraviolet (UV) to thermal infrared (TIR). It simulates the optical signal of proximal, aerial and satellite imaging spectrometers and laser scanners, the 3D RB and solar-induced chlorophyll fluorescence (SIF) signal, for any urban or natural landscape and any experimental or instrument configuration. It is freely available for research and teaching activities (dart.omp.eu). After illustrating three significant sources of inaccuracy in RS interpretation, five recent DART advances are presented: RT in the atmosphere and topography, fast RS image simulation of large landscapes, SIF modelling, and satellite image inversion.

Solar-induced fluorescence (SIF) is a subtle but informative optical signal of vegetation photosynthesis. Remotely sensed SIF integrates environmental, physiological and structural changes that alter photosynthesis at leaf, plant and canopy scales. Radiative transfer models are ideally suited to investigate the complex sources of variability in the SIF signal to guide the interpretation of SIF retrievals from airborne and space-borne platforms. Here, we coupled the Fluspect-Cx model of leaf optical properties and chlorophyll-a fluorescence with the Discrete Anisotropic Radiative Transfer (DART) model to upscale SIF from individual leaves to three-dimensional (3D) structurally explicit canopies. For one-dimensional homogeneous (turbid-like) canopies, DART-SIF was nearly identical to SIF simulated in two existing models, SCOPE and mSCOPE (RMSE

Potential of solar-induced chlorophyll fluorescence (SIF) to track time variable environmental stress of vegetation explains high interest in SIF remote sensing. There is an increasing need for physical models that consider the 3D structure of Earth surfaces, in order to better understand the relationships between SIF, vegetation three-dimensional (3D) architecture, irradiance and remote sensing configuration at canopy level. The Discrete Anisotropic Radiative Transfer (DART) model is one of the most comprehensive physically based 3D models of Earth-atmosphere radiative transfer (RT), covering the spectral domain from ultraviolet to thermal infrared wavelengths. This paper presents the determination of the sun and shade adapted leaf elements of a 3D vegetation canopy in DART, which is required for accurate RT simulations of SIF in geometrically explicit 3D canopy representations.

Models that simulate the radiative budget (RB) and remote sensing (RS) observation of landscapes with physical approaches and consideration of the three-dimensional (3-D) architecture of Earth surfaces are increasingly needed to better understand the life-essential cycles and processes of our planet and to further develop RS technology. DART (Discrete Anisotropic Radiative Transfer) is one of the most comprehensive physically based 3-D models of Earth-atmosphere optical radiative transfer (RT), from ultraviolet to thermal infrared. It simulates the optical 3-D RB and signal of proximal, aerial and satellite imaging spectrometers and laser scanners, for any urban and/ or natural landscapes and for any experimental and instrumental configurations. It is freely available for research and teaching activities. Here, an application is presented after a summary of its theory and recent advances: inversion of Sentinel 2 images for simulating time series of urban radiative budget ‘Q* sw ’ maps through the determination of maps of urban surface material. Results are very encouraging: satellite and in-situ Q* sw are very close (RMSE ≈ 15W/m2; i.e., 2.7% mean relative difference).

The need of better accuracy for analyzing remote sensing (RS) data of complex Earth surfaces explains the increasing need of models that simulate RS data with physical approaches. Similarly, the study of Earth surfaces functioning requires physical models that simulate the 3D radiative budget (RB) of these surfaces. DART (Discrete Anisotropic Radiative Transfer is one of the most comprehensive physically based 3D models that model the Earth-atmosphere radiation interaction from visible to thermal infrared wavelengths. It simulates optical signals at the entrance of terrain / airborne / satellite imaging radiometers and laser scanners, as well as the 3D RB, of urban / natural landscapes for any experimental and instrumental configurations. Its licenses are free for research and teaching activities. Here, we present its major recent advances.

The need of better accuracy to analyze remote sensing (RS) data and radiative budget (RB) of Earth surfaces explains the demand of physical models of RS and RB data. DART (Discrete Anisotropic Radiative Transfer) model is probably the most comprehensive three-dimensional (3D) physical model. Indeed, with original ray tracking and Monte Carlo methods for tracking radiation in the Earth and atmosphere from visible to thermal infrared wavelengths, it simulates the 3D RB and acquisitions of terrain / RS imaging radiometers and laser scanners, for any urban / natural landscape and any experimental / instrumental configuration. Paul Sabatier delivers free licenses for research and teaching activities. After introducing DART theory, we present recent advances: simulation of LiDAR and airborne sensors, and modeling of specular interaction and polarization.

To better understand the life-essential cycles and processes of our planet and to further develop remote sensing (RS) technology, there is an increasing need for models that simulate the radiative budget (RB) and RS acquisitions of urban and natural landscapes using physical approaches and considering the three-dimensional (3-D) architecture of Earth surfaces. Discrete anisotropic radiative transfer (DART) is one of the most comprehensive physically based 3-D models of Earth-atmosphere radiative transfer, covering the spectral domain from ultraviolet to thermal infrared wavelengths. It simulates the optical 3-D RB and optical signals of proximal, aerial, and satellite imaging spectrometers and laser scanners, for any urban and/or natural landscapes and for any experimental and instrumental configurations. It is freely available for research and teaching activities. In this paper, we briefly introduce DART theory and present recent advances in simulated sensors (LiDAR and cameras with finite field of view) and modeling mechanisms (atmosphere, specular reflectance with polarization and chlorophyll fluorescence). A case study demonstrating a novel application of DART to investigate urban landscapes is also presented.