IR Radiometry Optical System View Factor and Its Application to Emissivity Investigations of Solid and Liquid Phases

An optical system for fast IR radiometry designed for investigations of thin film thermal properties and pulsed laser melting was analyzed in this work. A methodology for determination of the view factor from calibration measurements was developed. The view factor (0.0255) of the optical system containing two paraboloid mirrors was determined experimentally from calibration measurements on pure metals and metallic alloys. The knowledge of the view factor was then applied to normal emissivity investigations at IR wavelengths. The emissivity of tungsten films prepared by magnetron sputtering was determined for different deposition conditions, varying between 0.036 and 0.071. Liquid phase emissivities of Cu, Mo, Ni, Si, Sn, Ti, and steel were also determined and were found to be higher than solid-state emissivities as predicted from the literature. A knowledge of the liquid-state emissivity of silicon enabled recalculation of the IR signal evolution to the temperature evolution, during and after a nanosecond laser pulse. This was not possible by use of the usual calibration because of silicon’s semi-transparent behavior in the IR range (1–10 μm) in the solid-state phase.     

红外隐身涂层材料及技术研究进展

随着红外探测技术的不断进步, 以红外辐射为信号源的武器装备（红外夜视仪、 红外制导导弹等） 的识别、 探测和追踪能力越来越强, 使战斗机、 车辆和坦克等武器装备极易受到攻击甚至摧毁。 为了应对这些红外威胁, 提高武器装备在战场上的生存能力, 多种技术手段被研发和应用, 其中红外隐身涂层发挥着越来越重要的作用。 本文将简单介绍红外隐身涂层的工作原理, 从涂层材料和制备技术两个方面综述目前红外隐身涂层的研究进展, 并对其未来研究发展方向提出展望。     

Radiometric normalization and image mosaic generation of ASTER thermal infrared data: An application to extensive sand sheets and dune fields

Data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) have a significant advantage over previous datasets because of the combination of high spatial resolution (15-90 m) and enhanced multispectral capabilities, particularly in the thermal infrared (TIR) atmospheric window (8-12 μm) of the Earth where common silicate minerals are more easily identified. However, the 60 km swath width of ASTER can limit the effectiveness of accurately tracing large-scale features, such as eolian sediment transport pathways, over long distances. The primary goal of this paper is to describe a method for generating a seamless and radiometrically accurate ASTER TIR mosaic of atmospherically corrected radiance and from that, extract surface emissivity for arid lands, specifically, sand seas. The Gran Desierto in northern Sonora, Mexico was used as a test location for the radiometric normalization technique because of past remote sensing studies of the region, its compositional diversity, and its size. A linear approach was taken to transform adjacent image swaths into a direct linear relationship between image acquisition dates. Pseudo-invariant features (PIFs) were selected using a threshold of correlation between radiance values, and change-pixels were excluded from the linear regression used to determine correction factors. The degree of spectral correlation between overlapping pixels is directly related to the amount of surface change over time; therefore, the gain and offsets between scenes were based only on regions of high spectral correlation. The result was a series of radiometrically normalized radiance-at-surface images that were combined with a minimum of image edge seams present. These edges were subsequently blended to create the final mosaic. The advantages of this approach for TIR radiance (as opposed to emissivity) data include the ability to: (1) analyze data acquired on different dates (with potentially very different surface temperatures) as one seamless compositional dataset; (2) perform decorrelation stretches (DCS) on the entire dataset in order to identify and discriminate compositional units; and (3) separate brightness temperature from surface emissivity for quantitative compositional analysis of the surface, reducing seam-line error in the emissivity mosaic. The approach presented here is valid for any ASTER-related study of large geographic regions where numerous images spanning different temporal and atmospheric conditions are encountered.     

Evaluation of ASTER and MODIS land surface temperature and emissivity products using long-term surface longwave radiation observations at SURFRAD sites

Land surface temperature (LST) and emissivity are key parameters in estimating the land surface radiation budget, a major controlling factor of global climate and environmental change. In this study, Terra Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) and Aqua MODerate resolution Imaging Spectroradiometer (MODIS) Collection 5 LST and emissivity products are evaluated using long-term ground-based longwave radiation observations collected at six Surface Radiation Budget Network (SURFRAD) sites from 2000 to 2007. LSTs at a spatial resolution of 90 m from 197 ASTER images during 2000-2007 are directly compared to ground observations at the six SURFRAD sites. For nighttime data, ASTER LST has an average bias of 0.1 °C and the average bias is 0.3 °C during daytime. Aqua MODIS LST at 1 km resolution during nighttime retrieved from a split-window algorithm is evaluated from 2002 to 2007. MODIS LST has an average bias of − 0.2 °C. LST heterogeneity (defined as the Standard Deviation, STD, of ASTER LSTs in 1 × 1 km² region, 11 × 11 pixel in total) and instrument calibration error of pyrgeometer are key factors impacting the ASTER and MODIS LST evaluation using ground-based radiation measurements. The heterogeneity of nighttime ASTER LST is 1.2 °C, which accounts for 71% of the STD of the comparison, while the heterogeneity of the daytime LST is 2.4 °C, which accounts for 60% of the STD. Collection 5 broadband emissivity is 0.01 larger than that of MODIS Collection 4 products and ASTER emissivity. It is essential to filter out the abnormal low values of ASTER daily emissivity data in summer time before its application.     

Studies on the effect of temperature and time on the SS 304 surface for the properties degradation of the solar collector

The properties of emissivity (?) and absorptivity (α) of the surface of the material is an essential output for the solar collector. This paper highlights the work based on the RSM design expert, to study the effect of parameters’ temperature and time when the surface is exposed to sunlight and absorbing the properties of emissivity and absorptivity of the material SS 304. The temperature range of the SS 304 varied from 20°C to 356°C for various time intervals from 90 to 1100?h. From this experimental work, it is clearly seen that the emissivity rate increased when the surface is focused onto sunlight beyond the saturated level. The absorptivity of the surface of SS 304 increases till the optimum level and reaches the saturated level. As a result, after the optimum level, emissivity rate of the surface increases, and absorptivity of the surface decreases when it is focused onto sunlight.     

Methodology for spectral emissivity measurement by means of single color pyrometer

The application of non-intrusive optical devices, such as infrared pyrometers able to measure the temperature of surfaces, makes possible the evaluation of emissivity curve of the tested materials at different temperature values. In this paper the authors propose a methodology for the spectral emissivity measurement by means of a single color pyrometer providing a semi-empirical formula, obtained experimentally at CIRA’s laboratory. The semi-empirical formula allows to know the actual emissivity value of the sample’s surface for whatever emissivity value set up on the pyrometer. The agreement between the experimental emissivity and the emissivity predicted by semi-empirical formula was verified.     

红外陶瓷的研究进展及应用

红外陶瓷由于其良好的红外性能而受到越来越多的关注和研究。本文总结了近年来影响红外发射率的因素、改善和提高红外陶瓷的红外发射率的方法以及红外陶瓷材料的应用。     

Scaling of land surface temperature using satellite data: A case examination on ASTER and MODIS products over a heterogeneous terrain area

Land surface temperature (LST) is a key parameter in numerous environmental studies. Surface heterogeneity induces uncertainty in pixel-wise LST. Spatial scaling may account for the uncertainty, however, different approaches lead to differences in scaled values. Satellite-retrieved LST may be representative of the pixel-wise LST and useful for scaling analysis, but the limited accuracy of retrieved values adds uncertainty into the scaled values. Based on the Stefan-Boltzmann (S-B) law, this study proposed scaling approaches for LST over flat and relief areas to explore the combined uncertainties in scaling using satellite-retrieved data. To take advantage of simultaneous, multi-resolution observations at coincident nadirs by the Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) and the MODerate-resolution Imaging Spectroradiometer (MODIS), LST products from these two sensors were examined for part of the Loess Plateau in China. 90-m ASTER LST data were scaled up to 1 km using the proposed approaches, and variation in the LST was generally reduced after scaling. Amongst the sources of uncertainties, surface heterogeneity (emissivity) and different scaling approaches resulted in very minor differences, with a maximum difference of 0.2 K for the upscaled LST. Terrain features, taken as an areal weighting factor, had negligible effects on the upscaled value. Limited accuracy of the retrieved LST was the major uncertainty. The overall LST increased 0.6 K on average with correction for terrain-induced angular effect and 0.4 K for both angular and adjacency effects over the study area. Accounting for terrain correction in scaling is necessary for rugged areas. With terrain correction, the upscaled ASTER LST achieved an agreement of − 0.1 ± 1.87 K and a root mean square error (RMSE) of 1.87 K overall with the 1-km MODIS LST rectified by Wan et al.'s approach [Wan, Z., Zhang, Y., Zhang Q., Li, Z.-L. (2002b), Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data. Remote Sensing of Environment, 83, 163-180]. Refining the rectification approach resulted in a better agreement of − 0.2 ± 1.57 K and a RMSE of 1.58 K.     

土壤的热惯量测量方法研究

本文提出了一种土壤热惯量的对比测量方法;在野外,对两种普通土壤及长春净月遥感区内的两种典型土壤进行了实地测量。文中的理论计算采用N级近似,所测得的热惯量值与文献给出的值相符,并显示出热惯量在监测土壤湿度方面是可行的。     

Temperature and emissivity separation from ASTER data for low spectral contrast surfaces

The performance of Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) thermal infrared (TIR) data product algorithms was evaluated for low spectral contrast surfaces (such as vegetation and water) in a test site close to Valencia, Spain. Concurrent ground measurements of surface temperature, emissivity, and atmospheric radiosonde profiles were collected at the test site, which is a thermally homogeneous area of rice crops with nearly full vegetation cover in summer. Using the ground data and the local radiosonde profiles, at-sensor radiances were simulated for the ASTER TIR channels and compared with L1B data (calibrated at-sensor radiances) showing discrepancies up to 3% in radiance for channel 10 at 8.3 μm (equivalently, 2.5 °C in temperature or 7% in emissivity), whereas channel 13 (10.7 μm) yielded a closer agreement (maximum difference of 0.5% in radiance or 0.4 °C in temperature). We also tested the ASTER standard products of land surface temperature (LST) and spectral emissivity generated with the Temperature-Emissivity Separation (TES) algorithm with standard atmospheric correction from both global data assimilation system profiles and climatology profiles. These products showed anomalous emissivity spectra with lower emissivity values and larger spectral contrast (or maximum-minimum emissivity difference, MMD) than expected, and as a result, overestimated LSTs. In this work, a scene-based procedure is proposed to obtain more accurate MMD estimates for low spectral contrast materials (vegetation and water) and therefore a better retrieval of LST and emissivity with the TES algorithm. The method uses various gray-bodies or near gray-bodies with known emissivities and assumes that the calibration and atmospheric correction performed with local radiosonde data are accurate for channel 13. Taking the channel 13 temperature (atmospherically and emissivity corrected) as the true LST, the radiances for the other channels were simulated and used to derive linear relationships between ASTER digital numbers and at-ground radiances for each channel. The TES algorithm was applied to the adjusted radiances and the resulting products showed a closer agreement with the ground measurements (differences lower than 1% in channel 13 emissivities and within ± 0.3 °C in temperature for rice and sea pixels).