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Thematische Bibliographien / Temperature-Emissivity Separation (TES)

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Auswahl der wissenschaftlichen Literatur zum Thema „Temperature-Emissivity Separation (TES)“

Autor: Grafiati

Veröffentlicht am 4. Juni 2021

Zuletzt aktualisiert am 5. Februar 2022

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Zeitschriftenartikel zum Thema "Temperature-Emissivity Separation (TES)"

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Moscadelli, M., M. Diani, and G. Corsini. "TEMPERATURE – EMISSIVITY SEPARATION ASSESSMENT IN A SUB-URBAN SCENARIO." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W3 (October 19, 2017): 129–36. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w3-129-2017.

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In this paper, a methodology that aims at evaluating the effectiveness of different TES strategies is presented. The methodology takes into account the specific material of interest in the monitored scenario, sensor characteristics, and errors in the atmospheric compensation step. The methodology is proposed in order to predict and analyse algorithms performances during the planning of a remote sensing mission, aimed to discover specific materials of interest in the monitored scenario. As case study, the proposed methodology is applied to a real airborne data set of a suburban scenario. In ord

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Kim, Sungho, Jungsub Shin, and Sunho Kim. "AT2ES: Simultaneous Atmospheric Transmittance-Temperature-Emissivity Separation Using Online Upper Midwave Infrared Hyperspectral Images." Remote Sensing 13, no. 7 (2021): 1249. http://dx.doi.org/10.3390/rs13071249.

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This paper presents a novel method for atmospheric transmittance-temperature-emissivity separation (AT2ES) using online midwave infrared hyperspectral images. Conventionally, temperature and emissivity separation (TES) is a well-known problem in the remote sensing domain. However, previous approaches use the atmospheric correction process before TES using MODTRAN in the long wave infrared band. Simultaneous online atmospheric transmittance-temperature-emissivity separation starts with approximation of the radiative transfer equation in the upper midwave infrared band. The highest atmospheric b

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Miao, Xinyuan, Ye Zhang, Junping Zhang, and Xinyu Zhou. "Temperature and Emissivity Smoothing Separation with Nonlinear Relation of Brightness Temperature and Emissivity for Thermal Infrared Sensors." Remote Sensing 11, no. 24 (2019): 2959. http://dx.doi.org/10.3390/rs11242959.

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Aiming at low spectral contrast materials, the Optimized Smoothing for Temperature Emissivity Separation (OSTES) method was developed to improve the Temperature and Emissivity Separation (TES) algorithm based on the linear relationship between brightness temperature and emissivity features, but there was little smoothing improvement for higher spectral contrast materials. In this paper, a new nonlinear-relationship based algorithm is presented, focusing on improving the performance of the OSTES method for materials with middle or high spectral contrast. This novel approach is a two-step proced

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Payan, V., and A. Royer. "Analysis of Temperature Emissivity Separation (TES) algorithm applicability and sensitivity." International Journal of Remote Sensing 25, no. 1 (2004): 15–37. http://dx.doi.org/10.1080/0143116031000115274.

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Nardino, Vanni, Gabriele Amato, Donatella Guzzi, Cinzia Lastri, and Valentina Raimondi. "Experimental Tests on TIR Multispectral Images for Temperature-Emissivity Separation by Using the MaxEnTES Algorithm." Proceedings 27, no. 1 (2019): 10. http://dx.doi.org/10.3390/proceedings2019027010.

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Satellite images in the TIR are relevant for several Earth Observation applications. The retrieval of temperature and emissivity from the emitted radiance, however, requires the use of suitable algorithms, such as the MaxEnTES that uses the concept of maximum entropy to solve the Temperature-Emissivity Separation problem. Here we discuss the performance of MaxEnTES when applied to TIR images with a limited number of channels, specifically simulated HyspIRI multispectral images and real multispectral images by ASTER. The results were respectively compared with the original temperatures used for

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LAHAIE, PIERRE. "PERFORMANCE ESTIMATION TOOLS FOR: DECOUPLING BY FILTERING OF TEMPERATURE AND EMISSIVITY (DEFILTE), AN ALGORITHM FOR THERMAL HYPERSPECTRAL IMAGE PROCESSING." International Journal of High Speed Electronics and Systems 18, no. 03 (2008): 675–99. http://dx.doi.org/10.1142/s0129156408005667.

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The construction of very good hyperspectral sensors operating in the thermal infrared bands from 8 to 12 microns arouses much interest for the development of data exploitation tools. Temperature emissivity separation (TES) algorithms are very important components of a future toolbox, because they make it possible to extract these two fundamental targets’ parameters. The emissivity relies on the nature of the target's surface materials, while the temperature gives information related to their use and relationship with the environment. The TES technique presented in this paper is based on iterat

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Barreto, África, Manuel Arbelo, Pedro A. Hernández-Leal, Laia Núñez-Casillas, María Mira, and César Coll. "Evaluation of Surface Temperature and Emissivity Derived from ASTER Data: A Case Study Using Ground-Based Measurements at a Volcanic Site." Journal of Atmospheric and Oceanic Technology 27, no. 10 (2010): 1677–88. http://dx.doi.org/10.1175/2010jtecha1447.1.

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Abstract The land surface temperature (LST) and emissivity (LSE) derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were evaluated in a low spectral contrast volcanic site at an altitude of 2000 m on the island of Tenerife, Spain. The test site is almost flat, thermally homogeneous, and without vegetation cover or variation in its surface composition. ASTER data correspond to six scenes, under both day- and nighttime conditions during 2008. This case study analyzes the impacts of the sources of inaccuracies using the temperature–emissivity separation (TES)

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Pérez-Planells, Lluís, Enric Valor, Raquel Niclòs, César Coll, Jesús Puchades, and Manuel Campos-Taberner. "Evaluation of Six Directional Canopy Emissivity Models in the Thermal Infrared Using Emissivity Measurements." Remote Sensing 11, no. 24 (2019): 3011. http://dx.doi.org/10.3390/rs11243011.

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Land surface temperature (LST) is a fundamental physical quantity in a range of different studies, for example in climatological analyses and surface–atmosphere heat flux assessments, especially in heterogeneous and complex surfaces such as vegetated canopies. To obtain accurate LST values, it is important to measure accurately the land surface emissivity (LSE) in the thermal infrared spectrum. In the past decades, different directional emissivity canopy models have been proposed. This paper evaluates six radiative transfer models (FR97, Mod3, Rmod3, 4SAIL, REN15, and CE-P models) through a co

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Mushkin, Amit, Alan R. Gillespie, Elsa A. Abbott, et al. "Validation of ASTER Emissivity Retrieval Using the Mako Airborne TIR Imaging Spectrometer at the Algodones Dune Field in Southern California, USA." Remote Sensing 12, no. 5 (2020): 815. http://dx.doi.org/10.3390/rs12050815.

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Validation of emissivity (ε) retrievals from spaceborne thermal infrared (TIR) sensors typically requires spatial extrapolations over several orders of magnitude for a comparison between centimeter-scale laboratory ε measurements and the common decameter and lower resolution of spaceborne TIR data. In the case of NASA’s Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) temperature and ε separation algorithm (TES), this extrapolation becomes especially challenging because TES was originally designed for the geologic surface of Earth, which is typically heterogeneous even at

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Silvestri, Malvina, Vito Romaniello, Simon Hook, Massimo Musacchio, Sergio Teggi, and Maria Fabrizia Buongiorno. "First Comparisons of Surface Temperature Estimations between ECOSTRESS, ASTER and Landsat 8 over Italian Volcanic and Geothermal Areas." Remote Sensing 12, no. 1 (2020): 184. http://dx.doi.org/10.3390/rs12010184.

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The ECO System Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) is a new space mission developed by NASA-JPL which launched on July 2018. It includes a multispectral thermal infrared radiometer that measures the radiances in five spectral channels between 8 and 12 μm. The primary goal of the mission is to study how plants use water by measuring their temperature from the vantage point of the International Space Station. However, as ECOSTRESS retrieves the surface temperature, the data can be used to measure other heat-related phenomena, such as heat waves, volcanic eruptio

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Dissertationen zum Thema "Temperature-Emissivity Separation (TES)"

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Okyay, Unal. "Lithologic Discrimination And Mapping By Aster Thermal Infrared Imagery." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614549/index.pdf.

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In conventional remote sensing, visible-near infrared (VNIR) and shortwave infrared (SWIR) part of the electromagnetic spectrum (EMS) have been utilized for lithological discrimination extensively. Additionally, TIR part of the EM spectrum can also be utilized for discrimination of surface materials either through emissivity characteristics of materials or through radiance as in VNIR and SWIR. In this study, ASTER thermal multispectral infrared data is evaluated in regard to lithological discrimination and mapping through emissivity values rather than conventional methods that utilize radiance

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Konferenzberichte zum Thema "Temperature-Emissivity Separation (TES)"

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Mushkin, Amit, Lee K. Balick, and Alan R. Gillespie. "Temperature/emissivity separation of MTI data using the Terra/ASTER TES algorithm." In AeroSense 2002, edited by Sylvia S. Shen and Paul E. Lewis. SPIE, 2002. http://dx.doi.org/10.1117/12.478764.

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