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Aurelie Michel
ONERA-DOTA, University of Toulouse, FR-31055 Toulouse, France

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Journal article
Published: 09 June 2020 in Remote Sensing
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TRUST (Thermal Remote sensing Unmixing for Subpixel Temperature) is a spectral unmixing method developed to provide subpixel abundances and temperatures from radiance images in the thermal domain. By now, this method has been studied in simple study cases, with a low number of endmembers, high spatial resolutions (1 m) and more than 30 spectral bands in the thermal domain. Thus, this article aims to show the applicability of TRUST on a highly challenging study case: the analysis of a heterogeneous urban environment with airborne multispectral (eight thermal bands) images at 8-m resolution. Thus, this study is necessary to generalize the use of TRUST in the analysis of urban thermography. Since TRUST allows linking intrapixel temperatures to specific materials, it appears as a very useful tool to characterize Surface Urban Heat Islands and its dynamics at high spatial resolutions. Moreover, this article presents an improved version of TRUST, called TRUST-DNS (Day and Night Synergy), which takes advantage of daytime and nighttime acquisitions to improve the unmixing performances. In this study, both TRUST and TRUST-DNS were applied on daytime and nighttime airborne thermal images acquired over the center of Madrid during the DESIREX (Dual-use European Security IR Experiment) campaign in 2008. The processed images were obtained with the Aircraft Hyperspectral Scanner (AHS) sensor at 4-m spatial resolution on 4 July. TRUST-DNS appears to be more stable and slightly outperforms TRUST on both day and night images. In addition, TRUST applied on daytime outperforms TRUST on nighttime, illustrating the importance of the temperature contrasts during day for thermal unmixing.

ACS Style

Carlos Granero-Belinchon; Aurelie Michel; Veronique Achard; Xavier Briottet. Spectral Unmixing for Thermal Infrared Multi-Spectral Airborne Imagery over Urban Environments: Day and Night Synergy. Remote Sensing 2020, 12, 1871 .

AMA Style

Carlos Granero-Belinchon, Aurelie Michel, Veronique Achard, Xavier Briottet. Spectral Unmixing for Thermal Infrared Multi-Spectral Airborne Imagery over Urban Environments: Day and Night Synergy. Remote Sensing. 2020; 12 (11):1871.

Chicago/Turabian Style

Carlos Granero-Belinchon; Aurelie Michel; Veronique Achard; Xavier Briottet. 2020. "Spectral Unmixing for Thermal Infrared Multi-Spectral Airborne Imagery over Urban Environments: Day and Night Synergy." Remote Sensing 12, no. 11: 1871.

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.