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principal modes of representation of the landscape: homogeneous or heterogeneous representation. For the models known as homogeneous (Idso and of Wit, 1970; Ross, 1981; Verhoef, 1984; Myneni et al., 1989), the landscape is represented by a constant horizontal distribution of absorbing and scattering elements (sheets, branches, etc...). On the other hand, for the models known as heterogeneous, the landscape is represented by a no uniform space distribution of unspecified elements of the landscape (North, 1996; Govaerts, 1998).
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The 4th radiation transfer model intercomparison (RAMI-IV): Proficiency testing of canopy reflectance models with ISO-13528, 2013, Widlowski J-L, B Pinty, M Lopatka, C Atzberger, D Buzica, M Chelle, M Disney, J-P Gastellu-Etchegorry, M Gerboles, N Gobron, E Grau, H Huang, A Kallel, H Kobayashi, P E
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DART model simulates, simultaneously in several wavelengths of the optical domain (e.g., visible and thermal infrared), the radiative budget and remotely sensed images of any Earth scene (natural / urban with /without relief), for any sun direction, any atmosphere, any view direction and any sensor
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A canopy radiative transfer scheme with explicit FAPAR for the interactive vegetation model ISBA-A-gs: impact on carbon fluxes, 2013, Carrer D., Roujean J.L., Lafont S., Calvet J.C., Boone A., Decharme B., Delire C., Gastellu-Etchegorry J.P., Journal of
Geophysical Research – Biogeosciences, Vol.
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The study of the functioning of
Continental surfaces requires the understanding of the various energetic and physiologic mechanisms that influence these surfaces. For example, the radiation absorbed in the visible spectral domain is the major energy source for vegetation photosynthesis. Moreover,
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Directional viewing effects on satellite Land
Surface Temperature products over sparse vegetation canopies – A multi-sensor analysis, 2013, Guillevic P.C., Bork-Unkelbach A., Göttsche F.M., Hulley G., Gastellu-Etchegorry J.P., Olesen F.S and Privette J.L., IEEE Geoscience and Remote sensing, 10,
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It simulates any landscape as a 3D matrice of cells that contain turbid material and triangles. Turbid material is used for simulating vegetation (e.g., tree crowns, grass, agricultural crops,...) and the atmosphere. Triangles are used for simulating translucent and opaque surfaces that makes up
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The difficulty in studying continental surfaces arises from the complexity of the energetic and physiologic processes involved and also from the different time and space scales concerned. It comes also from the complexity of satellite remote sensing space and from its links to quantities that
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The approaches used to simulate radiative transfer differ on 2 levels: mathematical method of resolution and mode of representation of the propagation medium. These two levels are in general dependent. The models of radiative transfer are often divided into 2 categories associated with the 2
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A LUT-Based
Inversion of DART Model to Estimate Forest LAI from Hyperspectral Data, 2015, Banskota A., Serbin S. P., Wynne R. H., Thomas V.A., Falkowski M.J., Kayastha N., Gastellu-Etchegorry J.P., Townsend P.A., IEEE Geoscience and Remote sensing, JSTARS-2014-00702.R1, in
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Retrieval of spruce leaf chlorophyll content from airborne image data using continuum removal and radiative transfer, 2013, Malenovský Z., Homolová L., Zurita-Milla R., Lukeš P., Kapland V., Hanuš J., Gastellu-Etchegorry J.P., Schaepman M., Remote sensing of
Environment.
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Investigating the
Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI, 2013, Banskota A., Wynne R., Thomas V., Serbin S., Kayastha N., Gastellu-Etchegorry J.P., Townsend P., Remote Sensing, 5:
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Discrete anisotropic radiative transfer (DART 5) for modeling airborne and satellite spectroradiometer and LIDAR acquisitions of natural and urban landscapes, 2015, Gastellu-Etchegorry J.P., Yin T., Lauret N., 2015, Remote
Sensing, 7, 1667–1701: doi:
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Building a
Forward-Mode 3-D Reflectance model for topographic normalization of high-resolution (1-5m) imagery: Validation phase in a forested environment, 2012, Couturier, S., Gastellu-Etchegorry J.P., Martin E., Patiño, P., IEEE, Vol. 51, Number 7,
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3D Modeling of
Imaging Spectrometer Data: data: 3D forest modeling based on LiDAR and in situ data, 2014, Schneider F.D. Leiterer R., Morsdorf F., Gastellu-Etchegorry J.P., Lauret N., Pfeifer N., Schaepman M.E., Remote Sensing of Environment, 152:
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and the discrete ordinate methods. It works with natural and urban landscapes (forests with different types of trees, buildings, rivers,...), with topography and atmosphere above and within the landscape. It simulates light propagation from
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Simulating images of passive sensors with finite field of view by coupling 3-D radiative transfer model and sensor perspective projection, 2015, Yin T., Lauret N. and
Gastellu-Etchegorry J.P., Remote Sensing of Environment,
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In this context, Earth observation from space (i.e., space remote sensing) is an indispensable tool, due to its unique potential to provide synoptic and continuous surveys of the Earth, at different time and space scales.
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A new approach of direction discretization and oversampling for 3D anisotropic radiative transfer modeling, 2013, Yin T., Gastellu-Etchegorry J.P., Lauret N., Grau E., Rubio J., Remote Sensing of Environment. 135, pp
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DART simulates radiative transfer in the "Earth-Atmosphere" system, for any wavelength in the optical domain (shortwaves : visible, thermal infrared,...). Its approach combines the
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The radiation transfer model intercomparison (RAMI) exercise, 2001, Pinty B., Gascon F., Gastellu-Etchegorry et al., Journal of Geophysical Research, Vol. 106, No. D11, June 16, 2001.
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Modelling radiative transfer in heterogeneous 3-D vegetation canopies, 1996, Gastellu-Etchegorry JP, Demarez V, Pinel V, Zagolski F, Remote sensing of Environment, 58:131–156.
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characterize Earth functioning. These remarks underline the need of models, because only these can couple and gather within a single scheme all concerned processes.
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Radiative transfer modeling in the "Earth – Atmosphere" system with DART model, 2013, Grau E. and Gastellu-Etchegrry, Remote Sensing of Environment, 139, 149–170
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Radiative transfer model for simulating high-resolution satellite images, Gascon F., 2001, Gastellu-Etchegorry J.P. et Lefèvre M.J., IEEE, 39(9), 1922–1926.
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topography, urban elements and 3D vegetation. DART can use structural and spectral data bases (atmosphere, vegetation, soil,...). It includes a
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energy and mass fluxes at the "Earth – Atmosphere" interface affect surface functioning, and consequently climatology.
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Lewis, W Qin, M Schlerf, J Stuckens, D Xie, Journal of Geophysical Research 01/2013 1–22, doi:10.1002/jgrd.50497
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223:. Developed at CESBIO since 1992, DART model was patented in 2003. It is freeware for scientific activities.
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FTM. It was designed to be precise, easy to use and adapted for operational use. For that, it simulates:
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255:General Information On Radiative Transfer
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