顾及像面畸变的卫星视频稳像

卫星视频每帧影像外方位元素数值存在差别,相邻帧影像间的同名点在像面位置不同,且由于每帧影像均存在几何畸变,经典的帧间的投影变换模型、仿射变换模型等视频稳像的配准模型不能精确描述帧间的同名点关系。针对该问题,本文提出顾及像面畸变的卫星视频稳像算法,基于仿真的卫星视频,验证了该算法的可行性和精度。     

冰盖下矩形河道的综合糙率

综合糙率是采用曼宁公式确定河道水位和流量关系的关键参数。在河道冰封期,冰盖的出现增加了流动的阻力,明流条件下确定的综合糙率不再适用,需要重新估算。基于Einstein阻力划分过流断面的原理,冰盖下矩形河道的过水断面可划分为冰盖区、河床区和边壁区。根据总流的连续性方程,在确定各分区糙率系数、水力半径和断面面积的基础上,提出了冰盖下矩形河道综合糙率的计算公式。采用已有的试验水槽测量数据和天然河道实测资料对公式进行了验证,结果表明:公式计算的综合糙率与实测值吻合较好,与Einstein公式和Sabaneev公式相比,计算精度更高;对于冰封水流,宽浅河道采用分区水深代替水力半径进行简化计算的条件有别于明渠水流,在宽深比大于20时,计算结果才满足精度要求。     

Variations of Hydrodynamics and Submarine Groundwater Discharge in the Yellow River Estuary Under the Influence of the Water-Sediment Regulation Scheme

The “Water-Sediment Regulation Scheme” (WSRS) is critically important to the hydrologic evaluation of the Yellow River estuary since a huge pulse of water and sediment are delivered into the sea during a short period. We used the natural geochemical tracers radium (²²³Ra, ²²⁴Ra, ²²⁶Ra) and radon (²²²Rn) isotopes as well as other hydrological parameters to investigate the mixing variations and submarine groundwater discharge (SGD) in the Yellow River estuary under the influence of the 2013 WSRS. Dramatically elevated radium and radon isotopic activities were observed during this WSRS compared with activities measured during a non-WSRS period. Radium “water ages” indicated that the offshore transport rate nearly tripled when the river discharge increased from 400 to 3400 m³/s. We calculated the SGD flux in the Yellow River estuary based on a radium mass balance model as well as radium and radon time-series models. The SGD flux was estimated at 0.02~0.20 m/day during a non-WSRS period and 0.67~1.22 m/day during the 2013 WSRS period. The results also indicate that large river discharge tends to lead more intense SGD along the river channel direction with a large amount of fresh SGD.     

Bias estimation and correction for triangle-based surface area calculations

The calculation of surface area is meaningful for a variety of space-filling phenomena, e.g., the packing of plants or animals within an area of land. With Digital Elevation Model (DEM) data we can calculate the surface area by using a continuous surface model, such as by the Triangulated Irregular Network (TIN). However, just as the triangle-based surface area discussed in this paper, the surface area is generally biased because it is a nonlinear mapping about the DEM data which contain measurement errors. To reduce the bias in the surface area, we propose a second-order bias correction by applying nonlinear error propagation to the triangle-based surface area. This process reveals that the random errors in the DEM data result in a bias in the triangle-based surface area while the systematic errors in the DEM data can be reduced by using the height differences. The bias is theoretically given by a probability integral which can be approximated by numerical approaches including the numerical integral and the Monte Carlo method; but these approaches need a theoretical distribution assumption about the DEM measurement errors, and have a very high computational cost. In most cases, we only have variance information on the measurement errors; thus, a bias estimation based on nonlinear error propagation is proposed. Based on the second-order bias estimation proposed, the variance of the surface area can be improved immediately by removing the bias from the original variance estimation. The main results are verified by the Monte Carlo method and by the numerical integral. They show that an unbiased surface area can be obtained by removing the proposed bias estimation from the triangle-based surface area originally calculated from the DEM data.     

Molecular characterization of sulfate-reducing bacteria community in surface sediments from the adjacent area of Changjiang Estuary

Sulfate-reducing bacteria (SRB), which obtain energy from dissimilatory sulfate reduction, play a vital role in the carbon and sulfur cycles. The dissimilatory sulfite reductase (Dsr), catalyzing the last step in the sulfate reduction pathway, has been found in all known SRB that have been tested so far. In this study, the diversity of SRB was investigated in the surface sediments from the adjacent area of Changjiang Estuary by PCR amplification, cloning and sequencing of the dissimilatory sulfite reductase beta subunit gene (dsrB). Based on dsrB clone libraries constructed in this study, diversified SRB were found, represented by 173 unique OTUs. Certain cloned sequences were associated with Desulfobacteraceae, Desulfobulbaceae, and a large fraction (60%) of novel sequences that have deeply branched groups in the dsrB tree, indicating that novel SRB inhabit the surface sediments. In addition, correlations of the SRB assemblages with environmental factors were analyzed by the linear model-based redundancy analysis (RDA). The result revealed that temperature, salinity and the content of TOC were most closely correlated with the SRB communities. More information on SRB community was obtained by applying the utility of UniFrac to published dsrB gene sequences from this study and other 9 different kinds of marine environments. The results demonstrated that there were highly similar SRB genotypes in the marine and estuarine sediments, and that geographic positions and environmental factors influenced the SRB community distribution.     

Phylogenetic diversity of culturable bacteria in surface seawater from the Drake Passage,Antarctica

The Drake Passage is located between the Antarctic Peninsula and Tierra del Fuego in the south of South America. Surface seawater samples were collected at seven sites in the Drake Passage during the austral summer of 2012. The 16S rRNA sequences were analyzed from 187 isolated bacterial strains. Three phyla, 29 genera and 56 species were identified. The three phyla were Actinobacteria, Firmicutes and Proteobacteria; the Proteobacteria included α-Proteobacteria, β-Proteobacteria and γ-Proteobacteria. γ-Proteobacteria, Actinobacteria and Firmicutes were the dominant class or phyla in terms of quantity and species. Gram-positive bacteria (Actinobacteria and Firmicutes) accounted for 57.8% of all types identified. There were nine dominant genera, including Curtobacterium, Staphylococcus, and Halomonas, and 14 dominant species including Curtobacterium flaccumfaciens, Curtobacterium pusillum, and Staphylococcus sciuri. Of the strains identified, 87.2% were catalase positive or weakly positive.     

针对星敏感器非线性畸变的非参数化在轨检校方法

为了对星敏感器的非线性畸变进行在轨检校,本文提出了一种非参数化的检校方法,该方法以B样条格网的形式表达非线性畸变,不需要预先估计一个参数化的畸变模型,从而可以处理任何形式的畸变。针对星敏感器不同模式畸变的仿真实验表明,本文提出的方法有效、可靠并且具有鲁棒性。