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Jean-Pierre Lagouarde
INRA, UMR 1391 ISPA, F-33140 Villenave d’Ornon, France

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Journal article
Published: 18 June 2019 in Remote Sensing
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Urban Heat Islands (UHIs) at the surface and canopy levels are major issues in urban planification and development. For this reason, the comprehension and quantification of the influence that the different land-uses/land-covers have on UHIs is of particular importance. In order to perform a detailed thermal characterisation of the city, measures covering the whole scenario (city and surroundings) and with a recurrent revisit are needed. In addition, a resolution of tens of meters is needed to characterise the urban heterogeneities. Spaceborne remote sensing meets the first and the second requirements but the Land Surface Temperature (LST) resolutions remain too rough compared to the urban object scale. Thermal unmixing techniques have been developed in recent years, allowing LST images during day at the desired scales. However, while LST gives information of surface urban heat islands (SUHIs), canopy UHIs and SUHIs are more correlated during the night, hence the development of thermal unmixing methods for night LSTs is necessary. This article proposes to adapt four empirical unmixing methods of the literature, Disaggregation of radiometric surface Temperature (DisTrad), High-resolution Urban Thermal Sharpener (HUTS), Area-To-Point Regression Kriging (ATPRK), and Adaptive Area-To-Point Regression Kriging (AATPRK), to unmix night LSTs. These methods are based on given relationships between LST and reflective indices, and on invariance hypotheses of these relationships across resolutions. Then, a comparative study of the performances of the different techniques is carried out on TRISHNA synthesized images of Madrid. Since TRISHNA is a mission in preparation, the synthesis of the images has been done according to the planned specification of the satellite and from initial Aircraft Hyperspectral Scanner (AHS) data of the city obtained during the DESIREX 2008 capaign. Thus, the coarse initial resolution is 60 m and the finer post-unmixing one is 20 m. In this article, we show that: (1) AATPRK is the most performant unmixing technique when applied on night LST, with the other three techniques being undesirable for night applications at TRISHNA resolutions. This can be explained by the local application of AATPRK. (2) ATPRK and DisTrad do not improve significantly the LST image resolution. (3) HUTS, which depends on albedo measures, misestimates the LST, leading to the worst temperature unmixing. (4) The two main factors explaining the obtained performances are the local/global application of the method and the reflective indices used in the LST-index relationship.

ACS Style

Carlos Granero-Belinchon; Aurelie Michel; Jean-Pierre Lagouarde; Jose A. Sobrino; Xavier Briottet. Night Thermal Unmixing for the Study of Microscale Surface Urban Heat Islands with TRISHNA-Like Data. Remote Sensing 2019, 11, 1449 .

AMA Style

Carlos Granero-Belinchon, Aurelie Michel, Jean-Pierre Lagouarde, Jose A. Sobrino, Xavier Briottet. Night Thermal Unmixing for the Study of Microscale Surface Urban Heat Islands with TRISHNA-Like Data. Remote Sensing. 2019; 11 (12):1449.

Chicago/Turabian Style

Carlos Granero-Belinchon; Aurelie Michel; Jean-Pierre Lagouarde; Jose A. Sobrino; Xavier Briottet. 2019. "Night Thermal Unmixing for the Study of Microscale Surface Urban Heat Islands with TRISHNA-Like Data." Remote Sensing 11, no. 12: 1449.

Journal article
Published: 27 May 2019 in Remote Sensing
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This work is linked to the future Indian–French high spatio-temporal TRISHNA (Thermal infraRed Imaging Satellite for High-resolution natural resource Assessment) mission, which includes shortwave and thermal infrared bands, and is devoted amongst other things to the monitoring of urban heat island events. In this article, the performance of seven empirical thermal unmixing techniques applied on simulated TRISHNA satellite images of an urban scenario is studied across spatial resolutions. For this purpose, Top Of Atmosphere (TOA) images in the shortwave and Thermal InfraRed (TIR) ranges are constructed at different resolutions (20 m, 40 m, 60 m, 80 m, and 100 m) and according to TRISHNA specifications (spectral bands and sensor properties). These images are synthesized by correcting and undersampling DESIREX 2008 Airborne Hyperspectral Scanner (AHS) images of Madrid at 4 m resolution. This allows to compare the Land Surface Temperature (LST) retrieval of several unmixing techniques applied on different resolution images, as well as to characterize the evolution of the performance of each technique across resolutions. The seven unmixing techniques are: Disaggregation of radiometric surface Temperature (DisTrad), Thermal imagery sHARPening (TsHARP), Area-To-Point Regression Kriging (ATPRK), Adaptive Area-To-Point Regression Kriging (AATPRK), Urban Thermal Sharpener (HUTS), Multiple Linear Regressions (MLR), and two combinations of ground classification (index-based classification and K-means classification) with DisTrad. Studying these unmixing techniques across resolutions also allows to validate the scale invariance hypotheses on which the techniques hinge. Each thermal unmixing technique has been tested with several shortwave indices, in order to choose the best one. It is shown that (i) ATPRK outperforms the other compared techniques when characterizing the LST of Madrid, (ii) the unmixing performance of any technique is degraded when the coarse spatial resolution increases, (iii) the used shortwave index does not strongly influence the unmixing performance, and (iv) even if the scale-invariant hypotheses behind these techniques remain empirical, this does not affect the unmixing performances within this range of resolutions.

ACS Style

Carlos Granero-Belinchon; Aurelie Michel; Jean-Pierre Lagouarde; Jose A. Sobrino; Xavier Briottet. Multi-Resolution Study of Thermal Unmixing Techniques over Madrid Urban Area: Case Study of TRISHNA Mission. Remote Sensing 2019, 11, 1251 .

AMA Style

Carlos Granero-Belinchon, Aurelie Michel, Jean-Pierre Lagouarde, Jose A. Sobrino, Xavier Briottet. Multi-Resolution Study of Thermal Unmixing Techniques over Madrid Urban Area: Case Study of TRISHNA Mission. Remote Sensing. 2019; 11 (10):1251.

Chicago/Turabian Style

Carlos Granero-Belinchon; Aurelie Michel; Jean-Pierre Lagouarde; Jose A. Sobrino; Xavier Briottet. 2019. "Multi-Resolution Study of Thermal Unmixing Techniques over Madrid Urban Area: Case Study of TRISHNA Mission." Remote Sensing 11, no. 10: 1251.

Post conference publication
Published: 18 December 2018 in Proceedings of the International Association of Hydrological Sciences
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EvapoTranspiration (ET) is an important component of the water cycle, especially in semi-arid lands. Its quantification is crucial for a sustainable management of scarce water resources. A way to quantify ET is to exploit the available surface temperature data from remote sensing as a signature of the surface energy balance, including the latent heat flux. Remotely sensed energy balance models enable to estimate stress levels and, in turn, the water status of most continental surfaces. The evaporation and transpiration components of ET are also just as important in agricultural water management and ecosystem health monitoring. Single temperatures can be used with dual source energy balance models but rely on specific assumptions on raw levels of plant water stress to get both components out of a single source of information. Additional information from remote sensing data are thus required, either something specifically related to evaporation (such as surface water content) or transpiration (such as PRI or fluorescence). This works evaluates the SPARSE dual source energy balance model ability to compute not only total ET, but also water stress and transpiration/evaporation components. First, the theoretical limits of the ET component retrieval are assessed through a simulation experiment using both retrieval and prescribed modes of SPARSE with the sole surface temperature. A similar work is performed with an additional constraint, the topsoil surface soil moisture level, showing the significant improvement on the retrieval. Then, a flux dataset acquired over rainfed wheat is used to check the robustness of both stress levels and ET retrievals. In particular, retrieval of the evaporation and transpiration components is assessed in both conditions (forcing by the sole temperature or the combination of temperature and soil moisture). In our example, there is no significant difference in the performance of the total ET retrieval, since the evaporation rate retrieved from the sole surface temperature is already fairly close to the one we can reconstruct from observed surface soil moisture time series, but current work is underway to test it over other plots.

ACS Style

Gilles Boulet; Emilie Delogu; Sameh Saadi; Wafa Chebbi; Albert Olioso; Bernard Mougenot; Pascal Fanise; Zohra Lili Chabaane; Jean-Pierre Lagouarde. Evapotranspiration and evaporation/transpiration partitioning with dual source energy balance models in agricultural lands. Proceedings of the International Association of Hydrological Sciences 2018, 380, 17 -22.

AMA Style

Gilles Boulet, Emilie Delogu, Sameh Saadi, Wafa Chebbi, Albert Olioso, Bernard Mougenot, Pascal Fanise, Zohra Lili Chabaane, Jean-Pierre Lagouarde. Evapotranspiration and evaporation/transpiration partitioning with dual source energy balance models in agricultural lands. Proceedings of the International Association of Hydrological Sciences. 2018; 380 ():17-22.

Chicago/Turabian Style

Gilles Boulet; Emilie Delogu; Sameh Saadi; Wafa Chebbi; Albert Olioso; Bernard Mougenot; Pascal Fanise; Zohra Lili Chabaane; Jean-Pierre Lagouarde. 2018. "Evapotranspiration and evaporation/transpiration partitioning with dual source energy balance models in agricultural lands." Proceedings of the International Association of Hydrological Sciences 380, no. : 17-22.

Journal article
Published: 15 November 2018 in Remote Sensing
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Using surface temperature as a signature of the surface energy balance is a way to quantify the spatial distribution of evapotranspiration and water stress. In this work, we used the new dual-source model named Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) based on the Two Sources Energy Balance (TSEB) model rationale which solves the surface energy balance equations for the soil and the canopy. SPARSE can be used (i) to retrieve soil and vegetation stress levels from known surface temperature and (ii) to predict transpiration, soil evaporation, and surface temperature for given stress levels. The main innovative feature of SPARSE is that it allows to bound each retrieved individual flux component (evaporation and transpiration) by its corresponding potential level deduced from running the model in prescribed potential conditions, i.e., a maximum limit if the surface water availability is not limiting. The main objective of the paper is to assess the SPARSE model predictions of water stress and evapotranspiration components for its two proposed versions (the “patch” and “layer” resistances network) over 20 in situ data sets encompassing distinct vegetation and climate. Over a large range of leaf area index values and for contrasting vegetation stress levels, SPARSE showed good retrieval performances of evapotranspiration and sensible heat fluxes. For cereals, the layer version provided better latent heat flux estimates than the patch version while both models showed similar performances for sparse crops and forest ecosystems. The bounded layer version of SPARSE provided the best estimates of latent heat flux over different sites and climates. Broad tendencies of observed and retrieved stress intensities were well reproduced with a reasonable difference obtained for most of the points located within a confidence interval of 0.2. The synchronous dynamics of observed and retrieved estimates underlined that the SPARSE retrieved water stress estimates from Thermal Infra-Red data were relevant tools for stress detection.

ACS Style

Emilie Delogu; Gilles Boulet; Albert Olioso; Sébastien Garrigues; Aurore Brut; Tiphaine Tallec; Jérôme Demarty; Kamel Soudani; Jean-Pierre Lagouarde. Evaluation of the SPARSE Dual-Source Model for Predicting Water Stress and Evapotranspiration from Thermal Infrared Data over Multiple Crops and Climates. Remote Sensing 2018, 10, 1806 .

AMA Style

Emilie Delogu, Gilles Boulet, Albert Olioso, Sébastien Garrigues, Aurore Brut, Tiphaine Tallec, Jérôme Demarty, Kamel Soudani, Jean-Pierre Lagouarde. Evaluation of the SPARSE Dual-Source Model for Predicting Water Stress and Evapotranspiration from Thermal Infrared Data over Multiple Crops and Climates. Remote Sensing. 2018; 10 (11):1806.

Chicago/Turabian Style

Emilie Delogu; Gilles Boulet; Albert Olioso; Sébastien Garrigues; Aurore Brut; Tiphaine Tallec; Jérôme Demarty; Kamel Soudani; Jean-Pierre Lagouarde. 2018. "Evaluation of the SPARSE Dual-Source Model for Predicting Water Stress and Evapotranspiration from Thermal Infrared Data over Multiple Crops and Climates." Remote Sensing 10, no. 11: 1806.

Journal article
Published: 01 September 2017 in Remote Sensing of Environment
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We investigated the use of multispectral thermal imagery to retrieve land surface emissivity and temperature. Conversely to concurrent methods, the temperature emissivity separation (TES) method simply requires single overpass without any ancillary information. This is possible since TES makes use of an empirical relationship that estimates the minimum emissivity ε-min from the emissivity spectral contrast captured over several channels, so-called maximum-minimum difference (MMD). In previous studies, the ε-min - MMD empirical relationship of TES was calibrated and validated for various sensor spectral configurations, where the proposed calibrations involved single or linearly mixed spectra of emissivity at the leaf or soil level. However, cavity effect should be taken into account at the vegetation canopy level, to avoid an underestimation of emissivity, especially for intermediate vegetation conditions between bare soil and full vegetation cover.The current study aimed to evaluate the performances of the TES method when applied to vegetation canopies with cavity effect. We used the SAIL-Thermique model to simulate a library of emissivity spectra for a wide range of soil and plant conditions, and we addressed the spectral configurations of recent and forthcoming sensors. We obtained good results for calibration and validation over the simulated library, except for full cover canopies because of the TES gray body problem. Consistent with previous studies, the calibration/validation results were better with more channels that capture emissivity spectral contrast more efficiently. Our TES calibrations provided larger ε-min values as compared to former studies, especially for intermediate vegetation cover. We explained this trend by the simulated spectral library that involved numerous vegetation canopies with cavity effect, thereby shifting up the ε-min - MMD empirical relationship. Consequently, our TES calibration provided larger (respectively lower) estimates of emissivity (respectively radiometric temperature) that were likely to be more realistic as compared to previous calibrations. Finally, SAIL-Thermique simulations permitted to show that increasing Leaf Area Index induced a displacement of the (ε-min, MMD) pairs along the empirical relationship. This was consistent with the TES underlying assumption, where any change in ε-min induces changes in MMD since ε-max is bounded on [0.98–1]. Further investigations should focus on validating the outcomes of the current study against ground-based measurements, and on assessing TES performances when accounting for instrumental and atmospheric perturbations

ACS Style

Frédéric Jacob; Audrey Lesaignoux; Albert Olioso; Marie Weiss; Karine Caillault; Stéphane Jacquemoud; Françoise Nerry; Andrew French; Thomas Schmugge; Xavier Briottet; Jean-Pierre Lagouarde. Reassessment of the temperature-emissivity separation from multispectral thermal infrared data: Introducing the impact of vegetation canopy by simulating the cavity effect with the SAIL-Thermique model. Remote Sensing of Environment 2017, 198, 160 -172.

AMA Style

Frédéric Jacob, Audrey Lesaignoux, Albert Olioso, Marie Weiss, Karine Caillault, Stéphane Jacquemoud, Françoise Nerry, Andrew French, Thomas Schmugge, Xavier Briottet, Jean-Pierre Lagouarde. Reassessment of the temperature-emissivity separation from multispectral thermal infrared data: Introducing the impact of vegetation canopy by simulating the cavity effect with the SAIL-Thermique model. Remote Sensing of Environment. 2017; 198 ():160-172.

Chicago/Turabian Style

Frédéric Jacob; Audrey Lesaignoux; Albert Olioso; Marie Weiss; Karine Caillault; Stéphane Jacquemoud; Françoise Nerry; Andrew French; Thomas Schmugge; Xavier Briottet; Jean-Pierre Lagouarde. 2017. "Reassessment of the temperature-emissivity separation from multispectral thermal infrared data: Introducing the impact of vegetation canopy by simulating the cavity effect with the SAIL-Thermique model." Remote Sensing of Environment 198, no. : 160-172.

Book chapter
Published: 01 January 2016 in Land Surface Remote Sensing in Continental Hydrology
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ACS Style

Nicolas Baghdadi; Alina L. Barbu; Monique Bernier; Karen Boniface; Gilles Boulet; Souhail Boussetta; Stéphane Calmant; Jean-Christophe Calvet; Jean-François Cretaux; Jean-Pierre Dedieu; Patricia De Rosnay; Yannick Duguay; Marie Dumont; Alejandro Egido; Frédéric Frappart; Pierre-Louis Frison; Simon Gascoin; Lionel Jarlan; Yann Kerr; Jean-Pierre Lagouarde; Delphine Leroux; Ramata Magagi; Erwan Motte; Eric Mougin; Thierry Pellarin; Guillaume Ramillien; Frédérique Remy; Nicolas Roussel; Lucía Seoane; Jean-Pierre Wigneron; Mehrez Zribi. List of Authors. Land Surface Remote Sensing in Continental Hydrology 2016, 449 -451.

AMA Style

Nicolas Baghdadi, Alina L. Barbu, Monique Bernier, Karen Boniface, Gilles Boulet, Souhail Boussetta, Stéphane Calmant, Jean-Christophe Calvet, Jean-François Cretaux, Jean-Pierre Dedieu, Patricia De Rosnay, Yannick Duguay, Marie Dumont, Alejandro Egido, Frédéric Frappart, Pierre-Louis Frison, Simon Gascoin, Lionel Jarlan, Yann Kerr, Jean-Pierre Lagouarde, Delphine Leroux, Ramata Magagi, Erwan Motte, Eric Mougin, Thierry Pellarin, Guillaume Ramillien, Frédérique Remy, Nicolas Roussel, Lucía Seoane, Jean-Pierre Wigneron, Mehrez Zribi. List of Authors. Land Surface Remote Sensing in Continental Hydrology. 2016; ():449-451.

Chicago/Turabian Style

Nicolas Baghdadi; Alina L. Barbu; Monique Bernier; Karen Boniface; Gilles Boulet; Souhail Boussetta; Stéphane Calmant; Jean-Christophe Calvet; Jean-François Cretaux; Jean-Pierre Dedieu; Patricia De Rosnay; Yannick Duguay; Marie Dumont; Alejandro Egido; Frédéric Frappart; Pierre-Louis Frison; Simon Gascoin; Lionel Jarlan; Yann Kerr; Jean-Pierre Lagouarde; Delphine Leroux; Ramata Magagi; Erwan Motte; Eric Mougin; Thierry Pellarin; Guillaume Ramillien; Frédérique Remy; Nicolas Roussel; Lucía Seoane; Jean-Pierre Wigneron; Mehrez Zribi. 2016. "List of Authors." Land Surface Remote Sensing in Continental Hydrology , no. : 449-451.

Book chapter
Published: 01 January 2016 in Land Surface Remote Sensing in Continental Hydrology
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ACS Style

Jean-Pierre Lagouarde; Gilles Boulet. Energy Balance of Continental Surfaces and the Use of Surface Temperature. Land Surface Remote Sensing in Continental Hydrology 2016, 323 -361.

AMA Style

Jean-Pierre Lagouarde, Gilles Boulet. Energy Balance of Continental Surfaces and the Use of Surface Temperature. Land Surface Remote Sensing in Continental Hydrology. 2016; ():323-361.

Chicago/Turabian Style

Jean-Pierre Lagouarde; Gilles Boulet. 2016. "Energy Balance of Continental Surfaces and the Use of Surface Temperature." Land Surface Remote Sensing in Continental Hydrology , no. : 323-361.

Journal article
Published: 01 September 2002 in Agronomie
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Agronomy for Sustainable Development, An International Journal in Agriculture and Environment

ACS Style

Wenguang G. Zhao; Albert Olioso; Jean-Pierre Lagouarde; Jean-Marc Bonnefond; Mark Irvine; Yann Kerr; John McAneney; Olivier Marloie. Estimation of aerodynamic parameters under non-neutral stability conditions from Alpilles measurement data. Agronomie 2002, 22, 619 -625.

AMA Style

Wenguang G. Zhao, Albert Olioso, Jean-Pierre Lagouarde, Jean-Marc Bonnefond, Mark Irvine, Yann Kerr, John McAneney, Olivier Marloie. Estimation of aerodynamic parameters under non-neutral stability conditions from Alpilles measurement data. Agronomie. 2002; 22 (6):619-625.

Chicago/Turabian Style

Wenguang G. Zhao; Albert Olioso; Jean-Pierre Lagouarde; Jean-Marc Bonnefond; Mark Irvine; Yann Kerr; John McAneney; Olivier Marloie. 2002. "Estimation of aerodynamic parameters under non-neutral stability conditions from Alpilles measurement data." Agronomie 22, no. 6: 619-625.

Journal article
Published: 01 September 2002 in Agronomie
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Agronomy for Sustainable Development, An International Journal in Agriculture and Environment

ACS Style

Stephen Hobbs; David Dyer; Dominique Courault; Albert Olioso; Jean-Pierre Lagouarde; Yann Kerr; John McAneney; Jean Bonnefond. Surface layer profiles of air temperature and humidity measured from unmanned aircraft. Agronomie 2002, 22, 635 -640.

AMA Style

Stephen Hobbs, David Dyer, Dominique Courault, Albert Olioso, Jean-Pierre Lagouarde, Yann Kerr, John McAneney, Jean Bonnefond. Surface layer profiles of air temperature and humidity measured from unmanned aircraft. Agronomie. 2002; 22 (6):635-640.

Chicago/Turabian Style

Stephen Hobbs; David Dyer; Dominique Courault; Albert Olioso; Jean-Pierre Lagouarde; Yann Kerr; John McAneney; Jean Bonnefond. 2002. "Surface layer profiles of air temperature and humidity measured from unmanned aircraft." Agronomie 22, no. 6: 635-640.