Comparison of three SeaWiFS atmospheric correction algorithms for turbid waters using AERONET-OC measurements

The use of satellites to monitor the color of the ocean requires effective removal of the atmospheric signal. This can be performed by extrapolating the aerosol optical properties in the visible from the near-infrared (NIR) spectral region assuming that the seawater is totally absorbant in this latter part of the spectrum. However, the non-negligible water-leaving radiance in the NIR which is characteristic of turbid waters may lead to an overestimate of the atmospheric radiance in the whole visible spectrum with increasing severity at shorter wavelengths. This may result in significant errors, if not complete failure, of various algorithms for the retrieval of chlorophyll-a concentration, inherent optical properties and biogeochemical parameters of surface waters.This paper presents results of an inter-comparison study of three methods that compensate for NIR water-leaving radiances and that are based on very different hypothesis: 1) the standard SeaWiFS algorithm (Stumpf et al., 2003; Bailey et al., 2010) based on a bio-optical model and an iterative process; 2) the algorithm developed by Ruddick et al. (2000) based on the spatial homogeneity of the NIR ratios of the aerosol and water-leaving radiances; and 3) the algorithm of Kuchinke et al. (2009) based on a fully coupled atmosphere-ocean spectral optimization inversion. They are compared using normalized water-leaving radiance nL_w in the visible. The reference source for comparison is ground-based measurements from three AERONET-Ocean Color sites, one in the Adriatic Sea and two in the East Coast of USA.Based on the matchup exercise, the best overall estimates of the nL_w are obtained with the latest SeaWiFS standard algorithm version with relative error varying from 14.97% to 35.27% for λ = 490 nm and λ = 670 nm respectively. The least accurate estimates are given by the algorithm of Ruddick, the relative errors being between 16.36% and 42.92% for λ = 490 nm and λ = 412 nm, respectively. The algorithm of Kuchinke appears to be the most accurate algorithm at 412 nm (30.02%), 510 (15.54%) and 670 nm (32.32%) using its default optimization and bio-optical model coefficient settings.Similar conclusions are obtained for the aerosol optical properties (aerosol optical thickness τ(865) and the Ångström exponent, α(510, 865)). Those parameters are retrieved more accurately with the SeaWiFS standard algorithm (relative error of 33% and 54.15% for τ(865) and α(510, 865)).A detailed analysis of the hypotheses of the methods is given for explaining the differences between the algorithms. The determination of the aerosol parameters is critical for the algorithm of Ruddick et al. (2000) while the bio-optical model is critical for the algorithm of Stumpf et al. (2003) utilized in the standard SeaWiFS atmospheric correction and both aerosol and bio-optical model for the coupled atmospheric-ocean algorithm of Kuchinke. The Kuchinke algorithm presents model aerosol-size distributions that differ from real aerosol-size distribution pertaining to the measurements. In conclusion, the results show that for the given atmospheric and oceanic conditions of this study, the SeaWiFS atmospheric correction algorithm is most appropriate for estimating the marine and aerosol parameters in the given turbid waters regions.     

SODA: A new method of in-scene atmospheric water vapor estimation and post-flight spectral recalibration for hyperspectral sensors: Application to the HyMap sensor at two locations

A new method of estimating per-pixel atmospheric column water vapor (ACWV) and potential differences in the reported band center wavelengths of the HyMap sensor has been developed. The new method uses variations of a second order derivative algorithm (SODA) to assess the impact of atmospheric residual features on calculated surface reflectance spectra after atmospheric compensation. The SODA method provides an alternative to the current band ratio techniques of ACWV estimation and also allows the same form of algorithm to be used for the estimation of possible band shifts. A comparison of in-situ measured surface reflectance at two field sites in Western Australia demonstrates improvement in the resulting spectra when post-flight updates are made to the reported HyMap band center wavelengths and applied during the atmospheric compensation process. The same SODA methodology was varied to estimate the ACWV on a per-pixel basis and found to significantly reduce the appearance of the underlying surface structure on the resulting ACWV images as well as improve the overall accuracy of the estimation. The ACWV estimated from the HyMap imagery at the two field sites was found to agree with in-situ atmospheric ACWV measurements to within 2% and represented a two fold increase in accuracy over a 3 band ratio Continuum Interpolated Band Ratio (CIBR) technique of ACWV estimation.     

核事故条件下的大气扩散模式及应用

本文介绍一个适用于核事故条件的大气扩散模式(粒子-烟团模式)的建立与调试。模式在模拟大气扩散的粒子随机游走方法中引入类似于扩散烟团的核函数概念，用以反映单个随机游走粒子所代表的污染物质的空间影响范围。模式解决了随机游走粒子与核函数“烟团”耦合后反映扩散物理真实过程的一致性问题，在约200km的范围内模拟结果与理论结果相一致。与代表实际大气典型扩散状况的高斯烟羽模式的结果进行定量比较，表明本模式结果在10km的范围内总体合理，但在近源处有系统偏小。模式瞬时浓度的涨落相对于平均轴线浓度大体控制在20％～30％的范围内。将模式应用于秦山地区的实际地形和气象条件进行实例测试表明，其结果可以反映当地复杂的大气扩散过程和特性。     

Simulation of hyperspectral and directional radiance images using coupled biophysical and atmospheric radiative transfer models

Future remote sensing satellite missions exploring the earth will feature advanced hyperspectral and directional optical imaging instruments. Given the complex nature of the data to be expected from these missions, a thorough preparation for them is essential and this can be accomplished by realistic simulation of the imagery data, years before the actual launch. Based on given spectral and directional capabilities of the instrument, and in combination with biophysical land surface properties obtained from existing imagery, the spectral and directional responses of several types of vegetation and bare soil have been simulated pixel by pixel using the radiative transfer models PROSPECT (for hyperspectral leaf reflectance and transmittance), GeoSAIL (for two-layer canopy bidirectional spectral reflectance), and MODTRAN4 (for atmospheric hyperspectral and directional effects). In this way, one obtains realistically simulated hyperspectral and directional top-of-atmosphere spectral radiance images, with all major effects included, such as heterogeneity of the landscape, non-Lambertian reflectance of the land surface, the atmospheric adjacency effect, and the limited spatial resolution of the instrument. The output of the image simulations can be used to demonstrate the capabilities of future earth observation missions. In addition, instrument specifications and image acquisition strategies might be optimized on the basis of simulated image analysis results, and new advanced data assimilation procedures could be validated with realistic inputs under controlled circumstances. This paper describes the applied methodology, the study area with the input images, the set-up of the actual image simulations, and discusses the final results obtained.     

遥感数字图像的大气辐射校正应用研究

卫星遥感数字图像成像过程中，由于电磁波受大气作用造成数据质量下降，影响遥感信息的提取及精度。介绍了大气辐射校正的一般原理和PCI软件ATCOR2模块的算法，研究了基于该模块的遥感数字图像大气辐射校正实现方法。根据研究区实际情况，选用1976年美国标准大气乡村气溶胶大气参数，对一景Landsat TM影像进行校正处理。对比处理前后图像和直方图，可知该方法增强了图像清晰度，提高了视觉效果，有利于遥感信息提取和专题解译。     

狭长区域内120m钢筋混凝土烟囱控制爆破拆除

在狭长区域内实施高烟囱定向爆破拆除,必须解决精确定向和落地冲击问题。本文结合峨眉铝业集团120m钢筋混凝土烟囱的爆破拆除,介绍了出灰口、后坐和偏心等几个重要问题的处理,提出了控制定向精度的方法和工艺手段。文中还介绍了爆破缺口参数的计算、震动安全距离的校核以及作者的体会。     

热风式大气湍流模拟装置的哈特曼测量

大气湍流是由于大气温度、压强的随机变化引起大气折射率随机改变而产生的。遵循这一原理,热风式湍流模拟装置对传输光束周围的空气加热,用风扇抽吸热空气产生湍流,通过改变加热温度和风扇的转速,模拟不同强弱的湍流。用哈特曼传感器对该装置进行测量并采集数据,通过波前斜率处理复原波前,在此基础上从时间域和空间域等方面分析所产生湍流的特点,并与理论进行比较。结果表明,该装置能产生基本符合大气湍流统计理论的湍流。     

强化作用在重油催化裂化中的应用

对常渣及其添加表面活性剂后的强化油进行了催化裂化反应对比实验研究,结果表明,由于表面活性剂对催化裂化反应的强化作用,改善了原料油与催化剂的接触状况,提高了原料的转化深度。在相同反应条件下,强化油的转化率比常渣高4～6个百分点,汽油产率提高2～5个百分点,液化气产率提高3个百分点左右,液收率增加4～6个百分点,干气产率增加近2个百分点,柴油产率下降1～2个百分点,焦炭产率下降2个百分点。在近似转化率下,强化油作为原料时的产品选择性优于常渣。     

Artificial intelligence implementation in the APS process diagnostic

Thermal spray process is a technique of coating manufacturing implementing a wide variety of materials and processes. This technique is characterized by up to 150 processing parameters influencing the coating properties. The control of the coating quality is needed through the consideration of a robust methodology that takes into account the parameter interdependencies, the process variability and offers the ability to quantify the processing parameter-process response relationships. The aim of this work is to introduce a new approach based on artificial intelligence responding to these requirements. A detailed procedure is presented considering an artificial neural network (ANN) structure which encodes implicitly the physical phenomena governing the process. The implementation of such a structure was coupled to experimental results of an optic sensor controlling the powder particle fusion state before the coating formation. The optimization steps were discussed and the predicted results were compared to the experimental ones allowing the identification of the control factors.     

Comparison of land surface emissivity and radiometric temperature derived from MODIS and ASTER sensors

This study compared surface emissivity and radiometric temperature retrievals derived from data collected with the MODerate resolution Imaging Spectroradiometer (MODIS) and Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) sensors, onboard the NASA's Earth Observation System (EOS)-TERRA satellite. Two study sites were selected: a semi-arid area located in northern Chihuahuan desert, USA, and a Savannah landscape located in central Africa. Atmospheric corrections were performed using the MODTRAN 4 atmospheric radiative transfer code along with atmospheric profiles generated by the National Center for Environmental Predictions (NCEP). Atmospheric radiative properties were derived from MODTRAN 4 calculations according to the sensor swaths, which yielded different strategies from one sensor to the other. The MODIS estimates were then computed using a designed Temperature-Independent Spectral Indices of Emissivity (TISIE) method. The ASTER estimates were derived using the Temperature Emissivity Separation (TES) algorithm. The MODIS and ASTER radiometric temperature retrievals were in good agreement when the atmospheric corrections were similar, with differences lower than 0.9 K. The emissivity estimates were compared for MODIS/ASTER matching bands at 8.5 and 11 μm. It was shown that the retrievals agreed well, with RMSD ranging from 0.005 to 0.015, and biases ranging from −0.01 to 0.005. At 8.5 μm, the ranges of emissivities from both sensors were very similar. At 11 μm, however, the ranges of MODIS values were broader than those of the ASTER estimates. The larger MODIS values were ascribed to the gray body problem of the TES algorithm, whereas the lower MODIS values were not consistent with field references. Finally, we assessed the combined effects of spatial variability and sensor resolution. It was shown that for the study areas we considered, these effects were not critical.