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 topography, urban elements and 3D vegetation. DART can use structural and spectral data bases (atmosphere, vegetation, soil, … ). It includes a LIDAR simulation mode. Simulation of the "Earth - Atmosphere" scene DART simulates radiative transfer in the "Earth-Atmosphere" system, for any wavelength in the optical domain (shortwaves : visible, thermal infrared, … ). Its approach combines the ray tracing 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 solar irradiance (Top of Atmosphere) and/or thermal emission within the scene. Context 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, energy and mass fluxes at the "Earth - Atmosphere" interface affect surface functioning, and consequently climatology. Major references 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. 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. 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. DART: A 3D Model for Remote Sensing Images and Radiative Budget of Earth Surfaces, Modeling and Simulation in Engineering, 2012, Gastellu-Etchegorry J.P., Grau E. and Lauret N., Catalin Alexandru (Ed.),, InTech, DOI: 10.5772/31315. Available from: URL 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, 3910-3921. 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. 131: 85-102. 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 213–223 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. 118: 1-16 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: 2639-2659 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, 1464-1468. Radiative transfer modeling in the "Earth - Atmosphere" system with DART model, 2013, Grau E. and Gastellu-Etchegrry, Remote Sensing of the Environment, 139, 149-170 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 Lewis, W Qin, M Schlerf, J Stuckens, D Xie, Journal of Geophysical Research 01/2013 1–22, doi:10.1002/jgrd.50497 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 Environment, 152: 235-250. 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: 10.3390/rs70201667. 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 press. 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 Environment, accepted.
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 topography, urban elements and 3D vegetation. DART can use structural and spectral data bases (atmosphere, vegetation, soil, ... ). It includes a LIDAR simulation mode. Simulation of the "Earth – Atmosphere" scene DART simulates radiative transfer in the "Earth-Atmosphere" system, for any wavelength in the optical domain (shortwaves : visible, thermal infrared, ... ). Its approach combines the ray tracing 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 solar irradiance (Top of Atmosphere) and/or thermal emission within the scene. Context 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, energy and mass fluxes at the "Earth – Atmosphere" interface affect surface functioning, and consequently climatology. Major references 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. 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. 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. DART: A 3D Model for Remote Sensing Images and Radiative Budget of Earth Surfaces, Modeling and Simulation in Engineering, 2012, Gastellu-Etchegorry J.P., Grau E. and Lauret N., Catalin Alexandru (Ed.),, InTech, DOI: 10.5772/31315. Available from: URL 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, 3910–3921. 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. 131: 85–102. 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 213–223 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. 118: 1–16 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: 2639–2659 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, 1464–1468. Radiative transfer modeling in the "Earth – Atmosphere" system with DART model, 2013, Grau E. and Gastellu-Etchegrry, Remote Sensing of the Environment, 139, 149–170 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 Lewis, W Qin, M Schlerf, J Stuckens, D Xie, Journal of Geophysical Research 01/2013 1–22, doi:10.1002/jgrd.50497 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 Environment, 152: 235–250. 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: 10.3390/rs70201667. 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 press. 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 Environment, accepted.
R
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...
R
…
...
R
-
–
R
…
...
R
…
...
R
-
–
R
131-156.
131–156.
R
1922-1926.
1922–1926.
R
3910-3921.
3910–3921.
R
85-102.
85–102.
R
-
–
R
1-16
1–16
R
2639-2659
2639–2659
R
1464-1468.
1464–1468.
R
-
–
R
149-170
149–170
R
235-250.
235–250.
R
1667-1701
1667–1701