Satellite and airborne optical sensors are increasingly used by scientists, and policy makers, and managers for studying and managing forests, agriculture crops, and urban areas. Their data acquired with given instrumental specifications (spectral resolution, viewing direction, sensor field-of-view, etc.) and for a specific experimental configuration (surface and atmosphere conditions, sun direction, etc.) are commonly translated into qualitative and quantitative Earth surface parameters. However, atmosphere properties and Earth surface 3D architecture often confound their interpretation. Radiative transfer models capable of simulating the Earth and atmosphere complexity are, therefore, ideal tools for linking remotely sensed data to the surface parameters. Still, many existing models are oversimplifying the Earth-atmosphere system interactions and their parameterization of sensor specifications is often neglected or poorly considered. The Discrete Anisotropic Radiative Transfer (DART) model is one of the most comprehensive physically based 3D models simulating the Earth-atmosphere radiation interaction from visible to thermal infrared wavelengths. It has been developed since 1992. It models optical signals at the entrance of imaging radiometers and laser scanners on board of satellites and airplanes, as well as the 3D radiative budget, of urban and natural landscapes for any experimental configuration and instrumental specification. It is freely distributed for research and teaching activities. This paper presents DART physical bases and its latest functionality for simulating imaging spectroscopy of natural and urban landscapes with atmosphere, including the perspective projection of airborne acquisitions and LIght Detection And Ranging (LIDAR) waveform and photon counting signals.

The radiation transfer model intercomparison (RAMI) activity aims at assessing the reliability of physics‐based radiative transfer (RT) models under controlled experimental conditions. RAMI focuses on computer simulation models that mimic the interactions of radiation with plant canopies. These models are increasingly used in the development of satellite retrieval algorithms for terrestrial essential climate variables (ECVs). Rather than applying ad hoc performance metrics, RAMI‐IV makes use of existing ISO standards to enhance the rigor of its protocols evaluating the quality of RT models. ISO‐13528 was developed “to determine the performance of individual laboratories for specific tests or measurements.” More specifically, it aims to guarantee that measurement results fall within specified tolerance criteria from a known reference. Of particular interest to RAMI is that ISO‐13528 provides guidelines for comparisons where the true value of the target quantity is unknown. In those cases, “truth” must be replaced by a reliable “conventional reference value” to enable absolute performance tests. This contribution will show, for the first time, how the ISO‐13528 standard developed by the chemical and physical measurement communities can be applied to proficiency testing of computer simulation models. Step by step, the pre‐screening of data, the identification of reference solutions, and the choice of proficiency statistics will be discussed and illustrated with simulation results from the RAMI‐IV “abstract canopy” scenarios. Detailed performance statistics of the participating RT models will be provided and the role of the accuracy of the reference solutions as well as the choice of the tolerance criteria will be highlighted.