Accelerated RAPID Model Using Heterogeneous Porous Objects

Huang, Huaguo

doi:10.3390/rs10081264

Cited by 6 publications

(1 citation statement)

References 44 publications

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“…However, most RT models are either for the atmosphere (e.g., 4A/OP, MODTRAN, LBLRTM, RFM, ARTS) or for the Earth surfaces (e.g., Rayspread, RAPID3, FLiES, SAIL) (Berk et al, 2015;Buehler et al, 2018;Clough et al, 2005;Huang, 2018;Kobayashi and Iwabuchi, 2008;Scott, 1974;Verhoef, 1984;Vincent and Dudhia, 2017;Widlowski et al, 2006). DART (Discrete Anisotropic Radiative Transfer) is one of the few models that simulate RT in the Earth-atmosphere system.…”

Section: Introductionmentioning

confidence: 99%

DART: Improvement of thermal infrared radiative transfer modelling for simulating top of atmosphere radiance

Wang

Gastellu-Etchegorry

2020

Remote Sensing of Environment

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Land surface temperature (LST) is increasingly needed for studying the functioning of the Earth's surface at local to global scale. Radiative transfer (RT) models that simulate top of atmosphere (TOA) radiance are essential tools to derive accurate LST from thermal infrared (TIR) signals of Earth observation (EO) satellites. DART (Discrete Anisotropic Radiative Transfer) is one of the most accurate and comprehensive three-dimensional models that simulate RT in the Earth-atmosphere system. Up to version 5.7.3, the mean absolute error (MAE) of DART atmospheric TIR radiance of six standard atmospheres (USSTD76, TROPICAL, MIDDLATSUM, MIDDLATWIN, SUBARCSUM, SUBARCWIN) over 3.5 m -20 m was 3.1 K compared to the reference atmospheric RT model MODTRAN, which is much larger than the 1 K accuracy needed by most LST applications. Also, the radiance error reached 2.6 K for some TIR bands whereas the noise equivalent differential temperature (NeDT) of satellite TIR sensor is usually less than 0.4 K. Recently, the DART atmospheric RT modelling was greatly improved by (1) introducing the equivalent absorption cross-section of five most absorbing gases (H2O, CO2, O3, CH4, N2O), and (2) implementing a double-layer thermal emission method. The MAE of DART atmospheric TIR radiance of six standard atmospheres and actual atmospheres over France and the Mediterranean Sea is now better than 1.0 K. The band radiance error is less than 0.2 K in the EO satellite TIR bands. DART is still accurate if the temperature profiles of standard atmospheres are offset by less than 6 K and if the viewing zenith angle is less than 50°. In short, the improved DART meets the requirements of both LST applications, and present and future TIR EO satellite missions. It is already available to scientists (https://dart.omp.eu).

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Section: Introductionmentioning

confidence: 99%

DART: Improvement of thermal infrared radiative transfer modelling for simulating top of atmosphere radiance

Wang

Gastellu-Etchegorry

2020

Remote Sensing of Environment

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DART radiative transfer modelling for sloping landscapes

Wang

Lauret

Gastellu-Etchegorry

2020

Remote Sensing of Environment

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Topography is one of the key factors that impact remotely sensed data and their interpretation. Indeed, combined with the viewing geometry and neighbour effects, it strongly affects the direct, diffuse and multi-scattered scene irradiance, which in turn impacts the radiative budget and remote sensing signals of the landscapes. The increased availability of digital elevation models (DEM) and the advancement of 3D radiative transfer (RT) models allow us to better address these topographic effects. DART (Discrete Anisotropic Radiative Transfer) is one of the most accurate and comprehensive 3D RT models that simulate remote sensing observations of natural and urban landscapes with topography and atmosphere. It simulates environmental effects (i.e., impact of adjacent landscape on the observed landscape) using a so-called infinite slope mode that infinitely duplicates the observed landscape while ensuring the continuity of slope and altitude at the DEM edges. Up to DART version 5.7.4, this mode was slightly inaccurate and computer intensive, depending on the topography. This paper presents an innovative modelling strategy that greatly improves it in terms of accuracy, image quality and 2 computer efficiency. For that, a fictive auxiliary oblique plane, adapted to the landscape topography, is introduced for managing the scene illumination, the Earth-Atmosphere coupling and the storage of the radiation that exits the scene before being projected onto the sensor plane.Improvements and validations are illustrated both visually and quantitatively by DART images, radiometric products and radiative budget. For example, the observed reflectance of a Lambertian slope is equal to the expected analytical value. In addition, the solar plane reflectance of a forest on a mountain slope (experimental scene) has an average error of about 0.01% relative to the reflectance of the same forest stand in the reference scene (i.e., nine duplications of the experimental scene). This new modelling is already integrated in the official DART version (https://dart.omp.eu).

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