具有图像内容保持特性的小波域可见水印

根据图像的噪声掩蔽性设计了一种小波域可见水印算法，并根据水印图像的纹理特征对算法作了进一步改进。在此基础上，提出了具有内容保持的嵌入策略及改进算法。实验结果表明，该算法在保证水印具有较好可见性的同时，载体图像内容得到了保持。     

基于DFT幅度的矢量地理空间数据数字水印算法

基于矢量地理空间数据自身的特点,运用离散傅立叶变换技术,提出了一种基于离散傅立叶变换的矢量地理空间数据数字水印算法。首先根据矢量地理空间数据的顶点序列构造复数序列,然后对该复数序列做离散傅立叶变换,将水印信息转换为符合N(0,1)分布的伪随机水印序列嵌入到变换后的幅度中,再进行离散傅立叶逆变换得到含水印信息的矢量地理空间数据。提取水印时,通过比较嵌入水印的数据与原始数据之间的差异提取出原始水印信息。实验分析表明,该算法在抗矢量地理空间数据处理中常见的删点、数据格式转换、平移、旋转等方面具有较好的效果。     

一种鲁棒的矢量地图数字水印算法

通过分析矢量数据的特征,根据数据自身的奇异性,将水印嵌入到间隔的特征点中。在水印嵌入过程中,综合分析特征点在整个数据链中的奇异性,然后在奇异性较强的特征点中嵌入水印信息,并使嵌入水印的特征点的奇异性得到增强,而相对弱化其周围数据的奇异性,增强水印信息对数据的裁剪、融合以及随机添加和减少数据点的攻击的鲁棒性,从而在水印提取过程中得到正确的水印信息。     

Improving the prediction of arsenic contents in agricultural soils by combining the reflectance spectroscopy of soils and rice plants

Visible and near-infrared reflectance spectroscopy provides a beneficial tool for investigating soil heavy metal contamination. This study aimed to investigate mechanisms of soil arsenic prediction using laboratory based soil and leaf spectra, compare the prediction of arsenic content using soil spectra with that using rice plant spectra, and determine whether the combination of both could improve the prediction of soil arsenic content. A total of 100 samples were collected and the reflectance spectra of soils and rice plants were measured using a FieldSpec3 portable spectroradiometer (350–2500 nm). After eliminating spectral outliers, the reflectance spectra were divided into calibration (n = 62) and validation (n = 32) data sets using the Kennard-Stone algorithm. Genetic algorithm (GA) was used to select useful spectral variables for soil arsenic prediction. Thereafter, the GA-selected spectral variables of the soil and leaf spectra were individually and jointly employed to calibrate the partial least squares regression (PLSR) models using the calibration data set. The regression models were validated and compared using independent validation data set. Furthermore, the correlation coefficients of soil arsenic against soil organic matter, leaf arsenic and leaf chlorophyll were calculated, and the important wavelengths for PLSR modeling were extracted. Results showed that arsenic prediction using the leaf spectra (coefficient of determination in validation, R_v² = 0.54; root mean square error in validation, RMSE_v = 12.99 mg kg⁻¹; and residual prediction deviation in validation, RPD_v = 1.35) was slightly better than using the soil spectra (R_v² = 0.42, RMSE_v = 13.35 mg kg⁻¹, and RPD_v = 1.31). However, results also showed that the combinational use of soil and leaf spectra resulted in higher arsenic prediction (R_v² = 0.63, RMSE_v = 11.94 mg kg⁻¹, RPD_v = 1.47) compared with either soil or leaf spectra alone. Soil spectral bands near 480, 600, 670, 810, 1980, 2050 and 2290 nm, leaf spectral bands near 700, 890 and 900 nm in PLSR models were important wavelengths for soil arsenic prediction. Moreover, soil arsenic showed significantly positive correlations with soil organic matter (r = 0.62, p < 0.01) and leaf arsenic (r = 0.77, p < 0.01), and a significantly negative correlation with leaf chlorophyll (r = −0.67, p < 0.01). The results showed that the prediction of arsenic contents using soil and leaf spectra may be based on their relationships with soil organic matter and leaf chlorophyll contents, respectively. Although RPD of 1.47 was below the recommended RPD of >2 for soil analysis, arsenic prediction in agricultural soils can be improved by combining the leaf and soil spectra.     

抗高程平移和裁剪的格网DEM盲水印算法

针对DEM数据水印常见的攻击方式——高程平移和裁剪,该文提出了一种可有效抵抗攻击的格网DEM盲水印算法。该算法考虑了DEM数据的特点,对原始水印进行扩频处理,使其与高程差值形成映射关系;利用相邻格网的高程差值在高程平移攻击中的不变特性,以量化方式将扩频后水印按位嵌入到高程差值中,将扩张的差值分摊到相邻高程的后一位。实验结果表明,该水印算法具有良好的不可见性,对DEM数据精度影响较小,并且对抵抗高程平移和裁剪攻击具有良好的鲁棒性。     

一种鲁棒的矢量地图数据的数字水印

数字水印是多媒体数据版权保护的一种有效方法。为了将水印技术应用于矢量地图数据的版权保护,根据矢量地图数据各要素层所合数据的多少,设计两种不同的数据分类规则,以实现嵌入不同大小的水印信息。通过仿真实验,可以看出算法具有很好的不可感知性和鲁棒性,尤其是抵抗矢量地图数据最常受到的对数据正常的增加、删除、修改、局部裁剪等更新操作。     

Microphysical Properties of Convective Clouds in Summer over the Tibetan Plateau from SNPP/VIIRS Satellite Data

The Tibetan Plateau (TP) plays an important role in formation and development of the East Asian atmospheric circulation, climate variability, and disastrous weathers in China. Among the many topics on TP meteorology, it is critical to understand the microphysical characteristics of clouds over the TP;however, observations of the cloud microphysics in this area are insufficient mainly due to sparse stations and limited cloud physical data. The Visible Infrared Imaging Radiometer Suite (VⅡRS), onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite, has an improved imaging spectroradiometer with 17 channels of 750-m moderate resolution and 5 channels of 375-m image resolution. The high-resolution instrument has an advantage for observing the small or initial convective clouds. Based on the methodologies that we proposed before for retrieving cloud microphysical properties from SNPP, an automated mapping software package named Automatic Mapping of Convective Clouds (AMCC) has been developed at the scale of satellite swath. The properties of convective clouds are retrieved by AMCC and their values are averaged over 0.33°×0.33° grids based on the SNPP/VⅡRS satellite data over the TP during the summers of 2013-17. The results show that:(1) the temperature of lifting condensation level (TLCL) at Naqu meteorological station and the cloud base temperature (Tb) retrieved from VⅡRS are linearly correlated, with a correlation coefficient of 0.87 and standard deviation (STD) of 3.0℃;(2) convective clouds over the TP have the following macro-and microphysical properties. First, the cloud base temperature (Tb) is about -5℃, the cloud base height above the ground (Hb) ranges between 1800 and 2200 m, and the cloud water content is low. Second, the cloud condensation nuclei concentration (NCCN) is between 200 and 400 mg-1 with 0.7% in maximum supersaturation (Smax);consequently, the condensation growth of water cloud droplet with less NCCN and higher Smax is fast. Third, because the precipitation initiation depth (D14) varies within 1500-2000 m and 500-1000 m at the Yarlung Zangbo River basin and southern Tibet, respectively, the clouds over these areas are more prone to precipitation. Fourth, mean height of the cloud top above sea level (Htop) is between 10 and 13 km, but the cloud depth (Dcld) is rather small, which is about 5000 m in southern TP and gradually reduces to 2500 m in northern TP. Fifth, the glaciation temperature (Tg) ranges from -30℃ in central and southern TP to -25℃ in northern TP, which, combined with the warmer Tg and the Tb less than 0℃, leads to the domination of ice process in the clouds;(3) the macro-and microphysical properties of convective clouds over the TP explain why rainfall there is frequent and lasts over a short time with small amount and large rain drops.     

利用快速反应码的矢量空间数据盲水印算法

针对传统的字符编码没有容错功能的缺陷,文章提出了基于快速反应(QR)码的矢量空间数据盲水印算法。该方法对要嵌入的字符应用QR码编码,生成QR码二值图像,并应用Logistic混沌系统对该QR码图像进行混沌置乱,对处理后的水印图像按位嵌入矢量空间数据的空域部分,水印被多次嵌入。实验结果表明,该方法不仅能够在裁剪后的部分数据中解码出字符,而且具有很好的不可见性,水印嵌入引起的矢量空间数据的误差很小,水印算法对常见的多种攻击具有较好的鲁棒性。     

A thin cloud removal method from remote sensing image for water body identification

In this paper,a thin cloud removal method was put forward based on the linear relationships between the thin cloud reflectance in the channels from 0.4 μm to 1.0 μm and 1.38 μm.Channels of 0.66 μm,0.86 μm and 1.38 μm were chosen to extract the water body information under the thin cloud.Two study cases were selected to validate the thin cloud removal method.One case was applied with the Earth Observation System Moderate Resolution Imaging Spectroradiometer(EOS/MODIS) data,and the other with the Medium Resolution Spectral Imager(MERSI) and Visible and Infrared Radiometer(VIRR) data from Fengyun-3A(FY-3A).The test results showed that thin cloud removal method did not change the reflectivity of the ground surface under the clear sky.To the area contaminated by the thin cloud,the reflectance decreased to be closer to the reference reflectance under the clear sky after the thin cloud removal.The spatial distribution of the water body area could not be extracted before the thin cloud removal,while water information could be easily identified by using proper near infrared channel threshold after removing the thin cloud.The thin cloud removal method could improve the image quality and water body extraction precision effectively.     

Observations of NO2 and O3 during thunderstorm activity using visible spectroscopy

Simultaneous observations for the total column densities of NO2, O3 and H2O were carried on using the porta-ble Spectrometer (438-450 nm and 400-450 nm) and the visible Spectrometer (544.4-628 nm) during premonsoon thunderstorms and embedded hail storm activity at Pune (18o32’N & 73o51’E), India. These observations confirm the fact that there is an increase in O3 and NO2 column densities during thunderstorms. The increase in O3 was observed following onset of thunderstorm, while the increase in NO2 was observed only after the thunder flashes occur. This implies that the production mechanisms for O3 and NO2 in thunderstorm are different. The observed column density of NO2 value (1 to 3 × 1017molecules · cm-2) during thunderstorm activity is 10 to 30 times higher than the value (1 × 1016molecules · cm-2) of a normal day total column density. The spectrometric observations and observations of thunder flashes by electric field meter showed that 6.4 × 1025molecules / flash of NO2 are produced. The increased to-tal column density of ozone during thunderstorm period is 1.2 times higher than normal (clear) day ozone concentra-tion. The multiple scattering in the clouds is estimated from H2O and O2 absorption bands in the visible spectral re-gion. Considering this effect the calculated amount of ozone added in the global atmosphere due to thunderstorm ac-tivity is 0.26 to 0.52 DU, and the annual production of ozone due to thunderstorm activity is of the order of 4.02 × 1037 molecules /year. The annual NO2 production may be of the order of 2.02 × 1035molecules / year.