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DART: An efficient 3D Monte Carlo vector radiative transfer model for remote sensing applications / Yingjie Wang (2022)  

Public Titre : DART: An efficient 3D Monte Carlo vector radiative transfer model for remote sensing applications Titre original : Modélisation 3D du transfert radiatif avec polarisation pour l'étude des surfaces terrestres par télédétection Type de document : Thèse/HDR Auteurs : Yingjie Wang, Auteur ; Jean-Philippe Gastellu-Etchegorry, Directeur de thèse ; A. Deschamps, Directeur de thèse Editeur : Toulouse : Université de Toulouse Année de publication : 2022 Importance : 248 p. Format : 21 x 30 cm Note générale : Bibliographie Thèse en vue de l'obtention du Doctorat de l'Université de Toulouse, spécialité Surfaces et interfaces continentales, hydrologie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF [Termes IGN] méthode de Monte-Carlo [Termes IGN] modèle de transfert radiatif [Termes IGN] modélisation 3D [Termes IGN] polarisation [Termes IGN] radiance Index. décimale : THESE Thèses et HDR Résumé : (auteur) Accurate understanding of the land surface functioning, such as the energy budget, carbon and water cycles, and ecosystem dynamics, is essential to better interpret, predict and mitigate the impact of the expected global changes. It thus requires observing our planet at different spatial and temporal scales that only the remote sensing (RS) can achieve because of its ability to provides systematic and synoptic radiometric observations. These observations can be transformed to surface parameters (e.g., temperature, vegetation biomass, etc.) used as input in process models (e.g., evapotranspiration) or be assimilated in the latter. Understanding the radiation interactions in the land surface and atmosphere is essential in two aspects: interpret RS signals as information about the observed land surfaces, and model the processes of functioning of land surfaces where the radiation participates. This explains the development of radiative transfer models (RTMs) that simulate the radiative budget and RS observations. The initial 3D RTMs in the 1980s simulated basic radiation mechanisms in very schematic representations of land surfaces (e.g., turbid medium, geometric primitive). Since then, their accuracy and performance have been greatly improved to address the increasing need of accurate information about land surfaces as well as the advances of RS instruments. So far, two types of improvements are still needed: 1. More accurate and efficient radiative transfer (RT) modelling (e.g., polarization, specular reflection, atmospheric scattering and emission, etc.) 2. Representation of land surfaces at different realism degrees and spatial scales. DART is one of the most accurate and comprehensive 3D RTMs (dart.omp.eu). It simulates the radiative budget and RS observations of urban and natural landscapes, with topography and atmosphere, from the ultraviolet to the thermal infrared domains. Its initial version, DART-FT, in 1992, used the discrete ordinates method to iteratively track the radiation along finite number of discrete directions in voxelized representations of the landscapes. It has been validated with other RTMs, and also RS and field measurements. However, it cannot simulate RS observations with the presently needed precision because of its voxelized representation of landscapes, and absence of some physical mechanisms (e.g., polarization). During this thesis, in collaboration with the DART team, I developed in DART a new Monte Carlo vector RT mode called DART-Lux that takes full advantage of the latest advances in RT modelling, especially in computer graphics. The central idea is to transfer the radiation transfer problem as a multi-dimensional integral problem and solve it with the Monte Carlo method that is considerably efficient and accurate in computing multi-dimensional integral such as the complex mechanisms (e.g., polarization) in realistic representations of 3D landscapes. For that, I implemented the bidirectional path tracing algorithm that generates a group of "source-sensor" paths by connecting two sub-paths, one is generated starting from the light source and another one is generated starting from the sensor. Then, the contribution of these paths to the integral is estimated by the multiple importance sampling. This method allows to accurately and efficiently simulate polarimetric RS observations of kilometre-scale realistic landscapes coupled with plane-parallel atmosphere, with consideration of the anisotropic scattering, the thermal emission, and the solar induced fluorescence. Compared to DART-FT, DART-Lux improves the computer efficiency (i.e., computer time and memory) usually by a factor of more than 100 for large-scale and complex landscapes. It provides new perspectives for studying the land surface functioning and also for preparing Earth observation satellite missions such as the missions TRISHNA (CNES and ISRO), LSTM and next generation Sentinel-2 (ESA), and CHANGE (NASA). Note de contenu : General introduction 1- Radiometry and radiative transfer 2- Numerical models for radiative transfer 3- DART-Lux: theory and implementation 4- Modelling of atmospheric effects 5- Modelling of polarization Conclusion and perspectives Numéro de notice : 24106 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Organisme de stage : CESBIO DOI : sans En ligne : https://www.theses.fr/2022TOU30173 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103060

Assessment of sky diffuse irradiance and building reflected irradiance in cast shadows / Manchun Lei (2021)  

Public Titre : Assessment of sky diffuse irradiance and building reflected irradiance in cast shadows Type de document : Article/Communication Auteurs : Manchun Lei , Auteur ; Yulu Xi, Auteur ; Jean-Philippe Gastellu-Etchegorry, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2021 Projets : 2-Pas d'info accessible - article non ouvert / Conférence : IGARSS 2021, IEEE International Geoscience And Remote Sensing Symposium 11/07/2021 16/07/2021 Bruxelles Belgique Proceedings IEEE Importance : pp 6960 - 6963 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Physique [Termes IGN] bâtiment [Termes IGN] éclairement énergétique [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] ombre [Termes IGN] rayonnement électromagnétique [Termes IGN] réflectance de surface [Termes IGN] scène urbaine [Termes IGN] transfert radiatif [Termes IGN] zone urbaine Résumé : (auteur) Sky radiance field at the bottom of the atmosphere and building façades are invisible in the remote sensing images, but they are the two main light sources of ground surfaces in the shadows cast by buildings in urban areas. This work is interested in evaluating the impact of the anisotropic sky and the reflection of the building on the irradiance of shaded surfaces. The assessment is based on 3D radiative transfer simulations of urban scenes with different sky radiance distributions and different building façade reflectance. The results show that without taking into account anisotropic sky, the average error of sky irradiance estimation in cast shadows can reach 183.75% in a visible band centered at 550 nm. According to the geometry and reflectivity of the building façade, the contribution of the building reflection to the irradiance of the shaded surfaces varies from 0.95% to 84.23%. Numéro de notice : C2021-043 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS47720.2021.9553889 Date de publication en ligne : 12/10/2021 En ligne : https://doi.org/10.1109/IGARSS47720.2021.9553889 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99417

3D radiative transfer modeling over complex vegetation canopies and forest reconstruction from LIDAR measurements / Jianbo Qi (2019)  

Public Titre : 3D radiative transfer modeling over complex vegetation canopies and forest reconstruction from LIDAR measurements Type de document : Thèse/HDR Auteurs : Jianbo Qi, Auteur ; Jean-Philippe Gastellu-Etchegorry, Directeur de thèse ; Guangjian Yan, Directeur de thèse Editeur : Toulouse : Université de Toulouse 3 Paul Sabatier Année de publication : 2019 Importance : 154 p. Format : 21 x 30 cm Note générale : bibliographie Thèse en vue de l'obtention du Doctorat de l'Université de Toulouse, Surfaces et interfaces continentales, hydrologie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] couvert végétal [Termes IGN] données lidar [Termes IGN] forêt [Termes IGN] indice foliaire [Termes IGN] interface graphique [Termes IGN] milieu anisotrope [Termes IGN] modèle de transfert radiatif [Termes IGN] modélisation 3D [Termes IGN] rendu réaliste [Termes IGN] scène 3D [Termes IGN] semis de points Index. décimale : THESE Thèses et HDR Résumé : (auteur) Remote sensing is needed for better managing vegetation covers. Hence, three-dimensional (3D) radiative transfer (RT) modeling is essential for understanding remote sensing signals of complex 3D vegetation covers. Due to the complexity of 3D models, one-dimensional (1D) RT models are commonly used to retrieve vegetation parameters, e.g., leaf area index (LAI), from remote sensing data. However, 1D models are not adapted to actual vegetation covers because they abstract them as schematic 1D layers, which is not realistic. Much effort is devoted to the conception of 3D RT models that can consider the 3D architecture of vegetation covers. However, developing an efficient 3D RT model that works on large and realistic scenes is still a challenging task. Major difficulties are the intensive computational costs of 3D RT simulation and the acquisition of detailed 3D canopy structures. Therefore, 3D RT models usually only work on abstracted scenes or small realistic scenes. Scene abstraction may cause uncertainties, and the small-scale approach is not compatible with most satellite observations (e.g., MODIS). The computer graphics community provides the most accurate and efficient models (i.e., renderers). However, the initial renderer models were not designed for accurate RT modeling, which explains the difficulty to use them for remote sensing applications. Recently emerged advanced techniques in computer graphics and light detection and ranging area (LiDAR) make it more possible to solve the above problems. 3D RT can be greatly accelerated due to the increasing computer power and improvement of rendering algorithms (e.g., ray-tracing acceleration and computational optimization). Also, 3D high-resolution information from LiDARs and photogrammetry become more accessible to reconstruct realistic 3D scenes. This approach requires new processing methods to combine 3D information and 3D RT models, which is of great importance for better remote sensing survey of vegetation. This thesis is focused on 1) Development of a 3D RT model based on recent ray-tracing techniques and 2) Retrieval of 3D leaf volume density (LVD) for constructing 3D forest scenes. This first chapter presents the development of an efficient 3D RT model, named LESS (LargE-Scale remote sensing data and image Simulation framework). LESS makes full use of ray-tracing algorithms. Specifically, it simulates multispectral BRF and scene radiative budget with a weighted forward photon tracing method, and sensor images (e.g., fisheye images) or large-scale (e.g. 1 km2) spectral images are simulated with a backward path tracing method. In the forward mode, a "virtual photon" algorithm is used to simulate accurate BRF with few photons. The backward mode is used to simulate thermal infrared images and also atmosphere RT. LESS efficiency and accuracy were demonstrated with a model intercomparison and field measurements. In addition, LESS has an easy-to-use graphic user interface (GUI) to input parameters, construct and visualize 3D scenes. 3D forest reconstruction is done with a simulated LiDAR dataset to assess approaches that retrieve LVD from airborne LiDAR data. The dataset is simulated with the discrete anisotropic radiative transfer model (DART). Note de contenu : 1- Introduction 2- LESS: Ray-tracing based 3D radiative transfer model 3- Accuracy evaluation of LESS 4- Hybrid scene structuring for accelerating 3D radiative transfer 5- Physical interpretation of leaf area index from LiDAR data 6- Voxel-based reconstruction and simulation of 3D forest scene 7- Conclusions and perspectives Numéro de notice : 25915 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Surfaces et interfaces continentales, hydrologie : Toulouse 3 : 2019 Organisme de stage : CESBIO nature-HAL : Thèse DOI : sans En ligne : https://hal.science/tel-02498603 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96024

ICARE-VEG: A 3D physics-based atmospheric correction method for tree shadows in urban areas / Karine R.M. Adeline in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 142 (August 2018) . - pp 311 - 327 Titre : ICARE-VEG: A 3D physics-based atmospheric correction method for tree shadows in urban areas Type de document : Article/Communication Auteurs : Karine R.M. Adeline, Auteur ; Xavier Briottet , Auteur ; X. Ceamanos, Auteur ; T. Dartigalongue, Auteur ; Jean-Philippe Gastellu-Etchegorry, Auteur Année de publication : 2018 Article en page(s) : pp 311 - 327 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] arbre (flore) [Termes IGN] correction atmosphérique [Termes IGN] détection d'ombre [Termes IGN] houppier [Termes IGN] image à très haute résolution [Termes IGN] image hyperspectrale [Termes IGN] Leaf Area Index [Termes IGN] logiciel de traitement d'image [Termes IGN] modèle de transfert radiatif [Termes IGN] modélisation 3D [Termes IGN] réflectance végétale [Termes IGN] zone urbaine Résumé : (Auteur) Many applications dedicated to urban areas (e.g. land cover mapping and biophysical properties estimation) using high spatial resolution remote sensing images require the use of 3D atmospheric correction methods, able to model complex light interactions within urban topography such as buildings and trees. Currently, one major drawback of these methods is their lack in modeling the radiative signature of trees (e.g. the light transmitted through the tree crown), which leads to an over-estimation of ground reflectance at tree shadows. No study has been carried out to take into account both optical and structural properties of trees in the correction provided by these methods. The aim of this work is to improve an existing 3D atmospheric correction method, ICARE (Inversion Code for urban Areas Reflectance Extraction), to account for trees in its new version, ICARE-VEG (ICARE with VEGetation). After the execution of ICARE, the methodology of ICARE-VEG consists in tree crown delineation and tree shadow detection, and then the application of a physics-based correction factor in order to perform a tree-specific local correction for each pixel in tree shadow. A sensitivity analysis with a design of experiments performed with a 3D canopy radiative transfer code, DART (Discrete Anisotropic Radiative Transfer), results in fixing the two most critical variables contributing to the impact of an isolated tree crown on the radiative energy budget at tree shadow: the solar zenith angle and the tree leaf area index (LAI). Thus, the approach to determine the correction factor relies on an empirical statistical regression and the addition of a geometric scaling factor to account for the tree crown occultation from ground. ICARE-VEG and ICARE performance were compared and validated in the Visible-Near Infrared Region (V-NIR: 0.4–1.0 µm) with hyperspectral airborne data at 0.8 m resolution on three ground materials types, grass, asphalt and water. Results show that (i) ICARE-VEG improves the mean absolute error in retrieved reflectances compared to ICARE in tree shadows by a multiplicative factor ranging between 4.2 and 18.8, and (ii) reduces the spectral bias in reflectance from visible to NIR (due to light transmission through the tree crown) by a multiplicative factor between 1.0 and 1.4 in terms of spectral angle mapper performance. ICARE-VEG opens the way to a complete interpretation of remote sensing images (sunlit, shade cast by both buildings and trees) and the derivation of scientific value-added products over all the entire image without the preliminary step of shadow masking. Numéro de notice : A2018-296 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.05.015 Date de publication en ligne : 01/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.05.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90415 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018081	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018083	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018082	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Building a forward-mode three-dimensional reflectance model for topographic normalization of High-Resolution (1–5 m) imagery: validation phase in a forested environment / Stéphane Couturier in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 1 (July 2013)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 51 n° 7 Tome 1 (July 2013) . - pp 3910 - 3921 Titre : Building a forward-mode three-dimensional reflectance model for topographic normalization of High-Resolution (1–5 m) imagery: validation phase in a forested environment Type de document : Article/Communication Auteurs : Stéphane Couturier, Auteur ; Jean-Philippe Gastellu-Etchegorry, Auteur ; Emmanuel Martin, Auteur ; Pavka Patino, Auteur Année de publication : 2013 Article en page(s) : pp 3910 - 3921 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] angle d'incidence [Termes IGN] classification par maximum de vraisemblance [Termes IGN] forêt tropicale [Termes IGN] image Ikonos [Termes IGN] modèle de transfert radiatif [Termes IGN] réflectance spectrale [Termes IGN] réflectance végétale Résumé : (Auteur) The aim of the topographic normalization of remotely sensed imagery (TNRSI) is to reduce reflectance variability caused by steep terrain and, subsequently, to improve land-cover classification. Recently, multiple-forward-mode (FM) (MFM) reflectance models for topographic normalizations of medium-resolution (20-30 m) satellite imagery have improved the classification of forested covers with respect to more conventional topographic corrections. We propose an FM 3-D reflectance (FM3DR) model, based on the Discrete Anisotropic Radiative Transfer simulator, for the topographic normalization of high-resolution (1-5 m) imagery. The feasibility of this approach was first verified on real IKONOS imagery for three forest types within major biomes (oak, pine, and high tropical forest) in Mexico. Next, we formalized the topographic normalization performance index and variability as relevant criteria to test TNRSI across incident angles in terms of maximum likelihood classification effectiveness. The FM3DR model outperformed five previously published topographic corrections (cosine, Minnaert, sun-canopy-sensor (SCS), Civco two-stage, and slope matching corrections), and image-based statistical strategies (Civco two-stage and slope matching corrections) tended to perform better than more analytical strategies (cosine, Minnaert, and SCS corrections). An asset of this approach versus former models is the realistic account of terrain-related variation of understory and crown cover within a cover type. On top of that, once validated across forest types, the model is sufficient for the application of a full MFM 3-D reflectance-based topographic normalization without additional field measurement. Numéro de notice : A2013-369 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2226593 En ligne : https://doi.org/10.1109/TGRS.2012.2226593 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32507 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2013071A	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Material reflectance retrieval in urban tree shadows with physics-based empirical atmospheric correction / Karine R.M. Adeline (2013)  

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Inversion du modèle de transfert radiatif DART [discrete anisotropic radiative transfer] / P. Esteve (1998)

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Apport de la modélisation du transfert radiatif pour l'étude des écosystèmes forestiers par télédétection / V. Pinel (1997)

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Filtrage du speckle dans les images radar à synthèse d'ouverture polarimétriques et classification supervisée multi-source / Franck Sery (1997)

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An evaluation of spot capability for mapping the geology and soils of central Java / Jean-Philippe Gastellu-Etchegorry in International Journal of Remote Sensing IJRS, vol 11 n° 4 (April 1990)  

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An assessment of spot XS and Landsat MSS data for digital classification of near-urban land cover / Jean-Philippe Gastellu-Etchegorry in International Journal of Remote Sensing IJRS, vol 11 n° 2 (February 1990)  

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An assessment of spot capability for cartographic applications in Indonesia / Jean-Philippe Gastellu-Etchegorry in International Journal of Remote Sensing IJRS, vol 10 n° 11 (November 1989)  

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Une évaluation du potentiel cartographique et thématique de Spot en Indonésie / Jean-Philippe Gastellu-Etchegorry (1989)

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Cloud cover distribution in Indonesia / Jean-Philippe Gastellu-Etchegorry in International Journal of Remote Sensing IJRS, vol 9 n° 7 (July 1988)  

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Predictive models for remotely-sensed data acquisition in Indonesia / Jean-Philippe Gastellu-Etchegorry in International Journal of Remote Sensing IJRS, vol 9 n° 7 (July 1988)  

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