DART: a 3D model for simulating satellite images and studying surface radiation budget

By J. Gastellu‐Etchegorry, Emmanuel Martin, F. Gascon. 2004

331 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/a82c6a79deba4b5f8e1973c5b9c4c2ca90a9a56e

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Citations in the corpus

Applicability of the PROSPECT model for Norway spruce needles (2006, methodology): “…transfer model, e.g. the Analytic Radiative-Transfer Model for a Coupled Atmosphere and Leaf Canopy (Liang and Strahler 1995), the DART model (Gastellu-Etchegorry et al. 1996, 2004) or the INFORM model (Schlerf and Atzberger 2006), and inverting this coupled model using optical remote…”
Review of optical-based remote sensing for plant trait mapping (2013, methodology): “…transfer models (RTMs), which simulate light 246 absorption and scattering inside vegetation canopies accounting for leaf biochemical 247 composition and canopy structural properties (Gastellu-Etchegorry et al., 2004; Jacquemoud 248 et al., 2009; Rautiainen et al., 2010; Verhoef and Bach, 2007).”
Linking chlorophyll a fluorescence to photosynthesis for remote sensing applications: mechanisms and challenges. (2014, background): “Radiative transfer models have been developed to simulate the effects of leaf and canopy structure and geometry on the wavelength-dependent radiative fluxes, ranging from simple turbid medium approaches (Allen, 1964) to ray tracing in realistic vegetation models (Gastellu-Etchegorry et al., 2004).”
Discrete Anisotropic Radiative Transfer (DART 5) for Modeling Airborne and Satellite Spectroradiometer and LIDAR Acquisitions of Natural and Urban Landscapes (2015, background): “DART is a three-dimensional (3D) model computing radiation propagation through the entire Earth-atmosphere system in the entire optical domain from visible to thermal infrared parts of the electromagnetic spectrum (EMS) [30,31].”
Remote Estimation of Crop Chlorophyll Content Using Spectral Indices Derived From Hyperspectral Data (2008, neutral): “While some studies have used the inversion of physically based models [13], [20]–[23], others have expended considerable effort to improve the relationships between chlorophyll concentration and a variety of optical spectral indices [5], [9], [24]–[26], with Haboudane et al.”
Estimation of 3D vegetation density with Terrestrial Laser Scanning data using voxels. A sensitivity analysis of influencing parameters (2017, methodology): “However, while several models exist to simulate airborne or spaceborne lidar data (e.g. Librat by Disney et al., 2011; FLIGHT by North et al., 2010; or DART by Gastellu-Etchegorry et al., 2004, 2015a), only a few studies have investigated TLS simulations (e.g. Burt et al., 2013).”