Evaluation of Different Methods to Retrieve the Hemispherical Downwelling Irradiance in the Thermal Infrared Region for Field Measurements

The thermal infrared hemispherical downwelling irradiance (HDI) emitted by the atmosphere and surrounding elements contributes through reflection to the signal measured over an observed surface by remote sensing. This irradiance must be estimated in order to obtain accurate values of land-surface temperature (LST). There are some fast methods to measure the HDI with a single measurement pointing to the sky at a specified viewing direction, but these methods require completely cloud-free or cloudy skies, and they do not account for the radiative contribution of surrounding elements. Another method is the use of a diffuse reflectance panel (usually, a rough gold-coated surface) with near-Lambertian behavior. This method considers the radiative contribution of surrounding elements and can be used under any sky condition. A third possibility is the use of atmospheric profiles and a radiative transfer code (RTC) in order to simulate the atmospheric signal and to calculate the HDI by integration. This study compares the HDI estimations with these approaches, using measurements made on four different days with a completely clear sky and two days with a partially cloudy sky. The measurements were made with a four-channel CIMEL Electronique radiometer working in the 8-14-μm spectral range. The HDI was also estimated by means of National Centers for Environmental Prediction atmospheric profiles introduced in the MODTRAN RTC. Additionally, the measurements were made at two different places with very different environments to quantify the effect of the contributing surroundings. Results showed that, for a clear-sky day with a minimal contribution of the surroundings, all methods differed from each other between 5% and 11%, depending on the spectral range, and any of them could be used to estimate HDI in these conditions. However, in the case of making surface measurements in an area with significant surrounding elements (buildings, trees, etc.), HDI values retrieved from the panel present an increase of +3 W·m-2·μm-1 compared with the other methods; this increase, if ignored, implies to make an error in LST ranging from +0.5 °C to +1.5 °C, depending on the spectral range and on surface emissivity and temperature. Comparison under heterogeneous skies with changing cloud coverage showed also large differences between the use of panel and the other methods, reaching a maximum difference of +4.6 W·m-2·μm-1, which implies to make an error on LST of +2.2 °C. In these cases, the use of the diffuse reflectance panel is proposed, since it is the unique way to capture the contribution of the surroundings and also to adequately measure HDI for sky changing conditions.

[1]  Miquel Ninyerola,et al.  Revision of the Single-Channel Algorithm for Land Surface Temperature Retrieval From Landsat Thermal-Infrared Data , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[2]  J. Salisbury,et al.  Portable Fourier transform infrared spectroradiometer for field measurements of radiance and emissivity. , 1996, Applied optics.

[3]  Ram M. Narayanan,et al.  Soil classification using mid-infrared off-normal active differential reflectance characteristics , 1992 .

[4]  Rune Storvold,et al.  In-situ measured spectral directional emissivity of snow and ice in the 8-14 μm atmospheric window , 2006 .

[5]  Christophe Pietras,et al.  A High-Accuracy Multiwavelength Radiometer for In Situ Measurements in the Thermal Infrared. Part II: Behavior in Field Experiments , 2003 .

[6]  Eva Rubio,et al.  Emissivity measurements of several soils and vegetation types in the 8–14, μm Wave band: Analysis of two field methods , 1997 .

[7]  John W. Salisbury,et al.  Infrared (8–14 μm) remote sensing of soil particle size , 1992 .

[8]  Yuan Li,et al.  Field measurement of Gobi surface emissivity using CE312 and Infragold Board at Dunhuang calibration site of China , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[9]  María P. Utrillas,et al.  Columnar aerosol properties in Valencia (Spain) by ground‐based Sun photometry , 2007 .

[10]  Ning Wang,et al.  Temperature and Emissivity Retrievals From Hyperspectral Thermal Infrared Data Using Linear Spectral Emissivity Constraint , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[11]  Paul G. Lucey,et al.  Infrared Measurements of Pristine and Disturbed Soils 2. Environmental Effects and Field Data Reduction , 1998 .

[12]  J. Salisbury,et al.  Thermal-infrared remote sensing and Kirchhoff's law: 2. Field measurements , 1999 .

[13]  K.Ya. Kondrat'yev,et al.  CHAPTER 3 – ABSORPTION OF LONG-WAVE RADIATION IN THE ATMOSPHERE , 1965 .

[14]  Simon J. Hook,et al.  The micro Fourier Transform Interferometer (μFTIR) : A new field spectrometer for acquisition of infrared data of natural surfaces , 1996 .

[15]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[16]  Thomas J. Schmugge,et al.  Comparison of Thermal Infrared Emissivities Retrieved With the Two-Lid Box and the TES Methods With Laboratory Spectra , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[17]  B. Rivard,et al.  Precise emissivity of rock samples , 1995 .

[18]  Julia A. Barsi,et al.  An Atmospheric Correction Parameter Calculator for a single thermal band earth-sensing instrument , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[19]  Enric Valor,et al.  An Atmospheric Radiosounding Database for Generating Land Surface Temperature Algorithms , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[20]  Vicente Caselles,et al.  Validation of Landsat-7/ETM+ Thermal-Band Calibration and Atmospheric Correction With Ground-Based Measurements , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[21]  V. Caselles,et al.  Estimation of atmospheric water vapour content from direct measurements of radiance in the thermal infrared region , 2012 .

[22]  Nigel P. Fox,et al.  CEOS comparison of IR brightness temperature measurements in support of satellite validation. Part I: Laboratory and Ocean surface temperature comparison of radiation thermometers. , 2010 .