Détermination de la température de surface urbaine à partir des données à haute résolution spatiale

La température de la surface terrestre (LST) est un paramètre très important. Cependant, certains facteurs influencent encore la précision de la récupération du LST dans les zones urbaines, mais n’ont pas encore été bien pris en compte dans les algorithmes de récupération du LST existants: (1) l’effet d’adjacence dans la région spectrale infrarouge thermique (TIR); (2) l’impact des structures tridimensionnelles et de leur rayonnement; (3) la dépendance de la connaissance préalable de l’atmosphère et/ou de l’émissivité de la surface terrestre. Dans cette thèse, deux modèles de transfert radiatif et une nouvelle méthode de récupération du LST ont été développés pour traiter ces trois facteurs, sur ces modèles, une méthode de récupération du LST urbain à partir de mesures TIR à haute résolution spatiale a été donnée. Les résultats montrent que la précision de récupération du LST urbain pourrait être améliorée d'environ 2,0 K, indiquant les bonnes performances de la méthode proposée.Land surface temperature (LST) is an important parameter of the Earth surface. However, there are still some factors influencing the urban LST retrieval accuracy but have not been well addressed in existing LST retrieval algorithms: (1) the adjacency effect in the thermal infrared (TIR) spectral region; (2) the impact of the three-dimensional structures and their radiation on the TIR measurements; (3) the dependence of existing LST retrieval algorithms on the information of atmosphere and/or the Earth surface emissivity. In this thesis, two forward radiative transfer models and one new LST retrieval method have been developed to deal with these three factors, based on which, a preliminary exploration on developing an improved urban LST retrieval method from high spatial resolution satellite TIR measurements has been given. Results show that the urban LST retrieval accuracy could be improved by about 2.0 K, indicating the good performance of the proposed method

Détermination de la température de surface urbaine à partir des données à haute résolution spatiale

Land surface temperature (LST) is an important parameter of the Earth surface. However, there are still some factors influencing the urban LST retrieval accuracy but have not been well addressed in existing LST retrieval algorithms: (1) the adjacency effect in the thermal infrared (TIR) spectral region; (2) the impact of the three-dimensional structures and their radiation on the TIR measurements; (3) the dependence of existing LST retrieval algorithms on the information of atmosphere and/or the Earth surface emissivity. In this thesis, two forward radiative transfer models and one new LST retrieval method have been developed to deal with these three factors, based on which, a preliminary exploration on developing an improved urban LST retrieval method from high spatial resolution satellite TIR measurements has been given. Results show that the urban LST retrieval accuracy could be improved by about 2.0 K, indicating the good performance of the proposed method.La température de la surface terrestre (LST) est un paramètre très important. Cependant, certains facteurs influencent encore la précision de la récupération du LST dans les zones urbaines, mais n’ont pas encore été bien pris en compte dans les algorithmes de récupération du LST existants: (1) l’effet d’adjacence dans la région spectrale infrarouge thermique (TIR); (2) l’impact des structures tridimensionnelles et de leur rayonnement; (3) la dépendance de la connaissance préalable de l’atmosphère et/ou de l’émissivité de la surface terrestre. Dans cette thèse, deux modèles de transfert radiatif et une nouvelle méthode de récupération du LST ont été développés pour traiter ces trois facteurs, sur ces modèles, une méthode de récupération du LST urbain à partir de mesures TIR à haute résolution spatiale a été donnée. Les résultats montrent que la précision de récupération du LST urbain pourrait être améliorée d'environ 2,0 K, indiquant les bonnes performances de la méthode proposée

Détermination de la température de surface urbaine à partir des données à haute résolution spatiale

Land surface temperature (LST) is an important parameter of the Earth surface. However, there are still some factors influencing the urban LST retrieval accuracy but have not been well addressed in existing LST retrieval algorithms: (1) the adjacency effect in the thermal infrared (TIR) spectral region; (2) the impact of the three-dimensional structures and their radiation on the TIR measurements; (3) the dependence of existing LST retrieval algorithms on the information of atmosphere and/or the Earth surface emissivity. In this thesis, two forward radiative transfer models and one new LST retrieval method have been developed to deal with these three factors, based on which, a preliminary exploration on developing an improved urban LST retrieval method from high spatial resolution satellite TIR measurements has been given. Results show that the urban LST retrieval accuracy could be improved by about 2.0 K, indicating the good performance of the proposed method.La température de la surface terrestre (LST) est un paramètre très important. Cependant, certains facteurs influencent encore la précision de la récupération du LST dans les zones urbaines, mais n’ont pas encore été bien pris en compte dans les algorithmes de récupération du LST existants: (1) l’effet d’adjacence dans la région spectrale infrarouge thermique (TIR); (2) l’impact des structures tridimensionnelles et de leur rayonnement; (3) la dépendance de la connaissance préalable de l’atmosphère et/ou de l’émissivité de la surface terrestre. Dans cette thèse, deux modèles de transfert radiatif et une nouvelle méthode de récupération du LST ont été développés pour traiter ces trois facteurs, sur ces modèles, une méthode de récupération du LST urbain à partir de mesures TIR à haute résolution spatiale a été donnée. Les résultats montrent que la précision de récupération du LST urbain pourrait être améliorée d'environ 2,0 K, indiquant les bonnes performances de la méthode proposée

Quantification of the Adjacency Effect on Measurements in the Thermal Infrared Region

International audienceSensor-observed energy from adjacent pixels, known as the adjacency effect, influences land surface reflectivity retrieval accuracy in optical remote sensing. As the spatial resolution of thermal infrared (TIR) images increases, the adjacency effect may influence land surface temperature (LST) retrieval accuracy in TIR remote sensing. However, to our knowledge, few studies have focused on quantifying this adjacency effect on TIR measurements. In this study, a forward adjacency effect radiative transfer model (FAERTM) was developed to quantify the adjacency effect on high-spatial-resolution TIR measurements. The model was verified to be in good agreement with moderate resolution atmospheric transmission (MODTRAN) code, with a discrepancy 3 K in some cases. These findings indicate that the adjacency effect should be considered when retrieving LSTs from TIR measurements, at least in some specific conditions. The proposed FAERTM provides a useful model for quantifying and addressing the adjacency effect on TIR measurements

A new thermal infrared channel configuration for accurate land surface temperature retrieval from satellite data

International audienc

A self-adaptive wildfire detection algorithm by fusing physical and deep learning schemes

Currently, the spectra-based physical models and deep learning methods are frequently used to detect wildfires from remote sensing data. However, physical algorithms mainly rely on radiative transfer processes, which limit their effectiveness in detecting small and weak fires. On the other hand, deep learning methods usually lack mechanism constraints, thus generally resulting in false alarms of bright surfaces. It is promising to combine the advantages of them and correspondingly reduce the inherent error of a single algorithm. To this end, in this paper, both the local contextual and the global index method based on physical mechanisms are optimized, simultaneously, a new U-Net model is also establish to accurately detect fires. Moreover, YOLO v5 is incorporated for the first time to extract and remove the false alarms of objects with high exposure. Based on the above series of novel works, a self-adaptive fusing algorithm is finally proposed. Our results reveal that: (1) Short-wave infrared band of about 2.15 μm is crucial in fire detection for data with moderate-to-high resolutions. Taking Landsat 8 as an example, the band combinations of 7, 6, 2(SWIR + VI), 7, 6, 5(SWIR + NIR), and 7, 5, 3(SWIR + VI + NIR) show reasonable accuracy, with recall rate of greater than 81 %. The thermal infrared band can be used to assist in detecting the general location of the fire and serve as alternative choice in extreme cases. (2) The optimized physical algorithm can reduce false alarms and predict more accurate fire positions. (3) It is very effective to introduce the YOLO v5 framework to remove false alarms with high exposure in urban and suburban regions. (4) The proposed self-adaptive fusion algorithm integrates the advantages of various schemes, proving its better performance in terms of robustness, stability and generality compared to any single method. Even in extreme situations such as the Gobi Desert, thin cloud edges, and mountain shadow areas, the fusion algorithm still works well. The generality tests based on Sentinel-2A, WorldView-3, and SPOT-4 reveal the potential applicability of the newly proposed fusing algorithm, especially for data with fine spatial and spectral resolutions

Clerodendranoic Acid, a New Phenolic Acid from Clerodendranthus spicatus

Phenolic acid derivatives are typical constituents of Clerodendranthus spicatus which were considered to the active principles of this medicinal plant. These chemical constituents with their interesting frameworks and biological significance attracted our attention. As part of our ongoing chemical investigation of C. spicatus using various column chromatography techniques, a new phenolic compound, named clerodendranoic acid (1), was isolated from the aerial parts of C. spicatus together with five known ones, including rosmarinic acid (2), methyl rosmarinate (3), caffeic acid (4), methyl caffeate (5), ethyl caffeate (6). Their structures, including stereochemical configurations, were completely established by extensive spectroscopic methods, mainly inclvolving 1D, 2D NMR, as well as HRESIMS