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1.
对两种水体悬浮颗粒物吸收系数测定方法及相关计算进行对比研究.通过长江中下游湖泊典型藻类的实验室培养,利用T方法和T-R方法分别对藻类颗粒物、藻类泥沙混合悬浊液进行吸收系数测定.通过颗粒物光谱吸收系数与叶绿素a之间的相关性关系,对比了两种方法的测量稳定性.通过对不同比例的藻类和无机悬浮颗粒物(ISS)的混合悬浊液进行分析,获得了不同浊度水体悬浮物吸收光谱的变化情况.结果表明,在纯藻或者泥沙含量较少的水体进行颗粒物吸收系数光谱测定时,T方法和T-R方法均可以采用,并且均具有较高的测定精度.然而,在泥沙含量相对较高的浑浊水体,应尽量选取T-R方法进行颗粒物吸收光谱的测定,以提高测定精度.长江中下游浅水湖泊由于底泥易受风浪影响发生再悬浮,因此在颗粒物吸收系数光谱测定中,当水体中ISS含量超过30 mg/L时,应选择T-R方法.  相似文献   
2.
线翼截断方式对大气辐射计算的影响   总被引:2,自引:0,他引:2  
张华  石广玉  刘毅 《气象学报》2007,65(6):968-975
在大气辐射传输计算方法中,有3种基本方法,即,逐线积分方法,k-分布方法和带模式方法。其中,逐线积分方法是最精确的计算大气透过率的方法,本文根据透过率计算方式的不同,将逐线积分方法分为追线积分法和追点积分法。由于逐线积分计算需要耗费大量的计算时间,在大气遥感和大气探测业务中使用时,必须减少计算成本,提高计算速度。本文在追线积分法的基础上,给出了简化的逐线积分的基本方法,在保证同样计算精度的同时,大大提高了计算速度。对在精确的和简化的逐线积分下,不同线翼截断方式(CUTOFF)对吸收系数、大气透过率和冷却率的影响进行了更详细的探讨。通过数值试验发现,对谱线线翼的截断方式是影响辐射计算精度和计算速度的重要因子。在不同压力下,用CUTOFF=2计算的吸收系数误差最大;对CUTOFF=1,在大多数取样点上误差都小于2%;对CUTOFF=3或4,对绝大多数取样点上计算的吸收系数误差都在5%以内,但所用的计算时间却明显减少。大气低层的透过率对不同的计算方法和不同的线翼截断方式不敏感;对大气高层,无论是对精确的还是简化的逐线积分方法,当CUTOFF=2时的透过率结果与其他线翼截断方式的结果差别较大。通过比较,本文给出线翼截断的优选方案。  相似文献   
3.
单窗算法的大气参数估计方法   总被引:95,自引:10,他引:95  
根据地表热辐射传导方程,提出了一个简单可行且精度较高的专门用于从TM6数据中演算地表温度的方法——单窗算法.这一算法把大气和地表状态对地表热传导的影响直接包括在演算公式中.该方法需要两个大气参数进行地表温度的演算,即大气平均作用温度和大气透射率.本文论述这两个大气参数的估计方法:根据大气水分含量或地表附近空气湿度来估计大气透射率;通过分析标准大气剖面资料,尤其是大气水分和气温随高程的变化规律,根据地表温度推算大气平均作用温度.  相似文献   
4.
绿洲边缘内外大气中水汽影响辐射传输分析   总被引:2,自引:1,他引:1  
水汽是大气中影响辐射传输的重要因子之一,实验观测表明在绿洲内外近地层大气中水汽含量存在一定的差异,因此绿洲边缘内外在气中辐射传输特征也不同。本文通过应用MODTRAN辐射模式和“干旱环境综合研究计划95”(简称AECMP95)野外实验近地面观测资料,分析了局地大气对达到地面辐射通量密度或辐射率、透射的影响,并与地面观测结果进行了比较,同时对绿洲边缘内外太阳辐射近红外1.55 ̄1.7μm带和大气窗区  相似文献   
5.
简要介绍了碳酸盐源岩研究中的两个问题:有机质的赋存状态(分散且不均一)及确立成熟度的新指标透射色指数(TCI)的最新进展。  相似文献   
6.
针对MODIS近红外数据反演大气水汽含量研究   总被引:10,自引:0,他引:10  
遥感反演大气水汽含量对进行天气预报、遥感大气校正、气候变化及水循环等研究具有重要意义。首先,通过对大气辐射传 输方程的推导,改进了三通道算法; 然后,模拟了在不同传感器视角条件下,大气水汽含量与MODIS 17、18、19通道大气透过率之 间的关系,解决了传感器视角问题,提出了针对MODIS数据的大气水汽含量计算方法; 最后,在IDL 6.0环境下,编程实现了该方法 ,并对2003年6月14日的一景图像进行了反演,结果表明,本文提出的方法是可行的。  相似文献   
7.
地基多波段遥感大气可降水量研究   总被引:3,自引:0,他引:3  
利用自动观测多波段CE 318太阳分光光度计,首先结合地面资料求出瑞利散射光学厚度,再用870 nm和1 020 nm非吸收通道内插出936 nm通道的气溶胶光学厚度。通过辐射传输模型MODTRAN模拟不同大气模式和观测角下的大气可降水量和透过率关系,利用改进的Langley 法计算出大气可降水量,分析了影响结果的误差源。  相似文献   
8.
In this research, a light transmission visualization (LTV) method was used to quantify dense non-aqueous phase liquids (DNAPL) saturation in two-dimensional (2-D), two fluid phase systems. The method is an expansion of earlier LTV methods and takes into account both absorption and refraction light theories. Based on this method, DNAPL and water saturations can rapidly be obtained point wise across sand-packed 2-D flow chambers without the need to develop a calibration curve. A single point calibration step is, however, needed when dyed DNAPL is used to account for the change in the transmission factor at the dyed DNAPL–water interface. The method was applied to measure, for the first time, undyed DNAPL saturation in small 2-D chambers. Known amounts of DNAPL, modeled by tetrachloroethylene (PCE), were added to the chamber and these amounts were compared to results obtained by this LTV method. Strong correlation existed between results obtained based on this method and the known PCE amounts with an R2 value of 0.993. Similar experiments conducted using dyed PCE showed a stronger correlation between results obtained by this LTV method and the known amounts of dyed PCE added to the chamber with an R2 value of 0.999. The method was also used to measure dyed PCE saturation in a large 2-D model following sparging experiments. Results obtained from image analyses following each sparging event were compared to results obtained by two independent techniques, namely gas chromatography–mass spectrometry (GC/MS) analyses and carbon column extraction. There was a good agreement between the results obtained by this LTV method and those obtained by the two independent techniques when experiments were carried out under stable light source conditions and errors in mass balance were minor. The method presented here can be expanded to measure fluid contents in three fluid phase systems and provide a non-destructive, non-intrusive tool to investigate changes in DNAPL architecture and flow characteristics in laboratory experiments.  相似文献   
9.
气象卫星HIRS/2各通道的吸收系数,透过率及权重函数与温度廓线一样随地点与时间而变化。把石广玉提出的指数和模式加上各通道仪器响应函数的修正,得出适合气象卫星HIRS/2各通道不同气体吸收系数的指数和模式,可以较快地计算HIRS/2各通道不同温度廓线下的透过率与权重函数。用修正的指数和模式计算CO2一些通道的透过率,与精确的逐线积分法的计算结果相比,CO2通道绝对差值小于0.0036;水汽1364 cm-1通道绝对差值小于0.0035。  相似文献   
10.
In order to provide a long time-series, high spatial resolution, and high accuracy dataset of land surface temperature (LST) for climatic change research, a modified Becker and Li's split-window approach is pro- posed in this paper to retrieve LST from the measurements of Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA)-7 to -18 and the Visible and InfraRed Radiometer (VIRR) onboard FY-3A. For this purpose, the Moderate Resolution Transmittance Model (MODTRAN) 4.1 was first employed to compute the spectral radiance at the top of atmosphere (TOA) under a variety of surface and atmosphere conditions. Then, a temperature dataset consists of boundary temperature Ts (which is one of the input parameters to MODTRAN), and channels 4 and 5 brightness temperatures (T4 and T5) were constructed. Note that channels 4 and 5 brightness tempera- tures were simulated from the MODTRAN output spectral radiance by convolving them with the spectral response functions (SRFs) of channels 4 and 5 of AVHRRs and VIRR. The coefficients of modified Becker and Li's split-window approach for various AVHRRs and VIRR were subsequently regressed based on this temperature dataset using the least square method. As an example of validation, one AVHRR satellite image over Beijing acquired at 0312 UTC 27 April 2008 by AVHRR onboard NOAA-17 was selected to retrieve the LST image using the modified Becker and Li's approach. The comparison between this LST image and that from the MODIS level-2 LST product provided by the University of Tokyo in Japan indicates that the correlation coefficient is 0.88, the bias is 0.6 K, and the root mean square deviation (RMSD) is 2.1 K. Furthermore, about 70% and 37% pixels in the LST difference image, which is the result of retrieved LST image from AVHRR minus the corresponding MODIS LST image, have the values within ±2 and ±1 K, respectively.  相似文献   
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