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Start Over Author "Roupioz, Laure" Topic land surface temperature
3 results on '"Roupioz, Laure"'

1. CAMCATT: a multisensor experiment over Toulouse to validate TRISHNA urban products

Author

Briottet, Xavier, Roupioz, Laure, Barda-Chatain, Romain, Rodler, Auline, Guernouti, Sihem, Marjorie, Musy, Nerry, Françoise, Lemonsu, Aude, Michel, Aurélie, Poutier, Laurent, Barillot, Philippe, Deliot, Philippe, Cerbelaud, Arnaud, Albitar, Ahmad, Roujean, Jean-Louis, Sobrino, José, Gadal, Sébastien, Carroll, Eric, Bridier, Sébastien, Cassante, Charlène, Guilhem de Lataillade, Amaury, Doublet, Philippe, ONERA / DOTA, Université de Toulouse [Toulouse], ONERA-PRES Université de Toulouse, Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement (Cerema), Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement - Equipe-projet BPE (Cerema Equipe-projet BPE), Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Groupe de Météorologie à Moyenne Échelle (GMME), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), DOTA, ONERA [Salon], ONERA, Centre d'études spatiales de la biosphère (CESBIO), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre National de la Recherche Scientifique (CNRS), Universitat de València (UV), Études des Structures, des Processus d’Adaptation et des Changements de l’Espace (ESPACE), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Avignon Université (AU)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Aix Marseille Université (AMU), Délégation générale de l'armement (DGA), Ministère de la Défense, CNES TOSCA TRISHNA (URBAN CAMCATT), CNES, ISRO, GADAL, Sébastien, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
[SHS.STAT]Humanities and Social Sciences/Methods and statistics, [SHS.GEO] Humanities and Social Sciences/Geography, VISNIR-SWIR Hyperspectral sensor, Toulouse, Urban remote sensing, [SHS.GEO]Humanities and Social Sciences/Geography, Intercalibration, [SDE.ES]Environmental Sciences/Environmental and Society, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], Multi-spectral thermal infrared sensor, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [SHS.STAT] Humanities and Social Sciences/Methods and statistics, Multi-sensors, Airborne remote sensing, [SDE.ES] Environmental Sciences/Environmental and Society, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, Land surface temperature
Abstract

International audience; An extensive field experiment, CAMCATT-AI4GEO, was conducted for 15 days in June 2021 over Toulouse, to acquire an urban reference dataset combining airborne acquisitions and ground measurements. This presentation aims at introducing the campaign and describing the collected data, which will be used for the validation of tools developed to produce future TRISHNA products, such as algorithms used for atmospheric compensation and temperature emissivity retrieval, microclimatic models. The several workshops of this experiment will be detailed. Joint airborne multispectral thermal infrared and VISNIR-SWIR hyperspectral images were acquired along a 30 km transect centred over Toulouse. A second flight was devoted to calibrating these sensors with on-ground reference targets. During and between the flights, two cars acquired air temperature and relative humidity along a predefined itinerary across the city with sensors mounted on their roof. During the airborne acquisitions, land surface temperature measurements were performed in three locations in Toulouse for calibration purposes. They were completed outside the flight by spectral optical properties in the VISNIR-SWIR and thermal infrared domains over a large range of manmade and natural materials. A specific in lab session was dedicated to the intercalibration of the on-ground thermal sensors. Atmosphere composition data were monitored using radio soundings during the airborne acquisitions and completed with continuous measurements from on-ground stations. Finally, the last session was devoted to the validation of a thermo-radiative model. For this purpose, surface temperature sensors were installed at different locations of buildings walls supplemented by a thermal infrared images acquisition for one of the facades in order to continuously monitor its temperature during the 15 days of the experiment. The air temperature was also measured at different positions in the district (under trees, in flats, etc).

Published
2022

2. Land surface temperature retrieval over urban areas from simulated TRISHNA data

Author

Briottet Xavier, Michel Aurelie, Roupioz Laure, Granero Belinchon Carlos, ONERA / DOTA, Université de Toulouse [Toulouse], ONERA-PRES Université de Toulouse, and Centre National D'etudes Spatiales

Subjects
Daytime, 010504 meteorology & atmospheric sciences, Land surface temperature, [SDV]Life Sciences [q-bio], 0211 other engineering and technologies, 02 engineering and technology, 01 natural sciences, Surface urban heat island, [SPI]Engineering Sciences [physics], 11. Sustainability, Surface roughness, Emissivity, Urban areas, Thermal infrared, TRISHNA, Image resolution, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Remote sensing, Urban area, 13. Climate action, Environmental science, Satellite, TES, Urban environment
Abstract

International audience; The future space joint-mission TRISHNA (Thermal infraRed Imaging Satellite for High-resolution Natural resource Assessment, CNES and ISRO) will allow to retrieve LST at 60 m spatial resolution every 3 days, improving the urban environment monitoring capacities. Two methods can be used to derive LST from remote sensing TIR data, Split-Window (SW) or TES (Temperature Emissivity Separation). Even if proven efficient, the complexity and heterogeneity of urban areas limit the performance of those methods. This paper focuses on the TES algorithm. For TES, errors can be generated by the impact of the surface roughness on the data. In order to investigate the efficiency of the future TRISHNA mission, research was conducted to evaluate the TES algorithm. To do so, the impacts of using a representative material database when using TES were explored and validated based on airborne or satellite data, and the impact of the surface geometry on the TES estimations was evaluated using 3D thermo-radiative model simulations. This study shows that TES can be used for TRISHNA images with a mean difference of 1.6 K between validation measurements and the retrieved LST for both daytime and nighttime images and that neglecting the impact of the surface geometry while performing TES could lead to errors up to 4 degrees C in LST estimations.

Published
2019
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3. Correction for the Impact of the Surface Characteristics on the Estimation of the Effective Emissivity at Fine Resolution in Urban Areas.

Author

Roupioz, Laure, Nerry, Françoise, and Colin, Jérôme

Subjects
*LAND surface temperature, *METROPOLITAN areas, *SURFACE roughness, *PIXELS, *SURFACE geometry, *EMISSIVITY, URBAN ecology (Sociology)
Abstract

Most of the methods used to retrieve land surface temperature (LST) from thermal infrared (TIR) satellite data in urban areas do not take into account the complexity of the surface. Cities are characterized by high surface roughness and one of the main constraints to estimate LST over those areas is the difficulty to define an effective emissivity for a given pixel at a given scale. When working with mixed pixels, the emissivity used to estimate the LST is an effective emissivity composed of the emissivities of each basic element constituting the pixel. In urban areas, the surface geometry has a strong impact on this effective emissivity. Its estimation from TIR satellite data must be carried out considering multiple surface reflections and diffusions within the urban canopy in order to retrieve accurate LST values. The objective of this study is then to evaluate the impact of the surface geometry within the pixel on effective emissivity estimation and to propose a method to derive an effective emissivity corrected for those effects. Emissivity can be derived at 90 m of spatial resolution from the TIR data acquired by ASTER. To evaluate the impact of the geometry at the scale of an ASTER pixel, several urban canyon configurations are designed to develop and test the correction method. The basic principle behind the method is to accurately estimate the downwelling TIR radiation received by a pixel integrating contributions from both the atmosphere and the scene inside this pixel and then derive the corrected effective emissivity from ASTER data using the TES (temperature emissivity separation) algorithm. First, the total downwelling TIR radiation is estimated from the geometric characteristics of the scene, using morphological indicators and integrating the non-isothermal behavior of the pixel thanks to 3D thermo-radiative model simulations. The validation of those estimations for each canyon configuration provides a maximum RMSE (Root Mean Square Error) value of 2.2 W·m−2. The validation performed over a district extracted from the 3D numerical model of Strasbourg (France) shows a RMSE of 2.5 W·m−2. Once the method to estimate the total downwelling TIR radiation is validated, LSE and LST maps are retrieved from an ASTER image over three districts of Strasbourg, showing that accounting for the surface geometry highlights thermal behavior differences inside districts, and that the impact of the geometry seems more influenced by building height than street width or building density. [ABSTRACT FROM AUTHOR]

Published
2018
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