二温式多重PCR检测鉴别对虾白斑综合征病毒(WSSV)和传染性皮下及造血器官坏死病毒(IHHNV)的研究与应用

建立了一种同时检测对虾白斑综合征病毒（WSSV）、传染性皮下和造血器官坏死病毒（IHHNV）的二温式多重PCR技术。根据基因库中WSSV（AF369029）和IHHNV（NC002190）基因序列，设计了两对分别与WSSV和IHHNV某段保守基因序列互补的引物，用这两对引物对同一样品中的WSSV和IHHNVDNA模板进行多重PCR扩增，结果均同时得到了两条大小与实验设计相符的593bp（WSSV）和356bp（1HHNV）特异性多重PCR扩增条带，而对其他对虾疾病病原的PCR扩增结果均为阴性；敏感性测定结果表明，该多重PCR技术最低能检测到WSSV和IHHNVDNA各100pg。用该多重PCR对400份临床病料进行检测，结果230份检出WSSV，阳性率57．5％；96份检出IHHNV，阳性率24％；56份同时检出WSSV和IHHNV，阳性率14％。18份为阴性，阴性率为4．5％。结果提示了WSSV和IHHNV广泛存在于中国南方的养殖对虾中，作者建立的二温式多重PCR可以用于这两种病毒的临床快速检测和鉴别诊断。     

Sea surface temperature observation by Global Imager (GLI)/ADEOS-II: Algorithm and accuracy of the product

A sea surface temperature (SST) retrieval algorithm for Global Imager (GLI) aboard the ADEOS-II satellite has been developed. The algorithm is used to produce the standard SST product in the Japan Aerospace Exploration Agency (JAXA). The algorithm for cloud screening is formed by combinations of various types of tests to detect cloud-contaminated pixels. The combination is changed according to the solar zenith angle, which enables us to detect clouds even in the sun glitter region in daytime. The parameters in the cloud-detection tests have been tuned using the GLI global observations. SST is calculated by the Multi-Channel SST (MCSST) technique from the detected clear pixels. Using drifting buoy measurements, match-up data are produced to derive the coefficients of the MCSST equations and to examine their performance. The bias and RMSE of the GLI SST are 0.03 K and 0.66 K for daytime and, −0.01 K and 0.70 K for nighttime, respectively.     

利用二维活断层探测资料构建焦作地区浅层三维构造模型

运用专业地震解释及构造建模软件，综合利用焦作地区地震数据、钻孔数据、地质信息对活断层二维浅层地震剖面进行层位与断层解释，同时对断层平面组合与空间展布规律进行研究，实现地质资料与地震数据的有机结合，构建近地表Q₃地层底界面、Q地层底界面、N地层底界面分布模型和第四纪断层模型。以第四纪断层模型为基本骨架，以近地表地层分布为主要分层，模拟Q-Q₃地质体、N-Q地质体的构造形态和断层发育情况，系统反映近地表N地层底界面至Q₃地层底界面的空间结构特征。     

Classification method,spectral diversity,band combination and accuracy assessment evaluation for urban feature detection

Automatic extraction of urban features from high resolution satellite images is one of the main applications in remote sensing. It is useful for wide scale applications, namely: urban planning, urban mapping, disaster management, GIS (geographic information systems) updating, and military target detection. One common approach to detecting urban features from high resolution images is to use automatic classification methods. This paper has four main objectives with respect to detecting buildings. The first objective is to compare the performance of the most notable supervised classification algorithms, including the maximum likelihood classifier (MLC) and the support vector machine (SVM). In this experiment the primary consideration is the impact of kernel configuration on the performance of the SVM. The second objective of the study is to explore the suitability of integrating additional bands, namely first principal component (1st PC) and the intensity image, for original data for multi classification approaches. The performance evaluation of classification results is done using two different accuracy assessment methods: pixel based and object based approaches, which reflect the third aim of the study. The objective here is to demonstrate the differences in the evaluation of accuracies of classification methods. Considering consistency, the same set of ground truth data which is produced by labeling the building boundaries in the GIS environment is used for accuracy assessment. Lastly, the fourth aim is to experimentally evaluate variation in the accuracy of classifiers for six different real situations in order to identify the impact of spatial and spectral diversity on results. The method is applied to Quickbird images for various urban complexity levels, extending from simple to complex urban patterns. The simple surface type includes a regular urban area with low density and systematic buildings with brick rooftops. The complex surface type involves almost all kinds of challenges, such as high dense build up areas, regions with bare soil, and small and large buildings with different rooftops, such as concrete, brick, and metal.Using the pixel based accuracy assessment it was shown that the percent building detection (PBD) and quality percent (QP) of the MLC and SVM depend on the complexity and texture variation of the region. Generally, PBD values range between 70% and 90% for the MLC and SVM, respectively. No substantial improvements were observed when the SVM and MLC classifications were developed by the addition of more variables, instead of the use of only four bands. In the evaluation of object based accuracy assessment, it was demonstrated that while MLC and SVM provide higher rates of correct detection, they also provide higher rates of false alarms.     

Trends in timing of low stream flows in Canada: impact of autocorrelation and long‐term persistence

The annual timing of river flows might indicate changes that are climate related. In this study, trends in timing of low flows for the Reference Hydrometric Basin Network were investigated under three different hypotheses namely: independence, short‐term persistence (STP) and long‐term persistence (LTP). Both summer and winter time series were characterized with scaling behaviour providing strong evidence of LTP. The Mann–Kendall trend test was modified to account for STP and LTP, and used to detect trends in timing of low flows. It was found that considering STP and LTP resulted in a significant decrease in the number of detected trends. Numerical analysis showed that the timing of summer 7‐day low flows exhibited significant trends in 16, 9 and 7% of stations under independence, STP and LTP assumptions, respectively. Timing of summer low flow shifted toward later dates in western Canada, whereas the majority of stations in the east half of the country (except Atlantic Provinces) experienced a shift toward earlier dates. Timing of winter low flow experienced significant trends in 20, 12, and 6% of stations under independence, STP and LTP assumptions, respectively. Shift in timing of winter low flow toward earlier dates was dominant all over the country where it shifted toward earlier dates in up to 3/4 of time series with significant trends. There are local patterns of upward significant/insignificant trends in southeast, southwest and northern Canada. This study shows that timing of low flows in Canada is time dependent; however, addressing the full complexity of memory properties (i.e. short term vs long term) of a natural process is beyond the scope of this study. Copyright © 2009 John Wiley & Sons, Ltd.     

Integrated edge detection and terrain analysis for agricultural terrace delineation from remote sensing images

ABSTRACT

Agricultural terraces are important for agricultural production and soil-and-water conservation. They comprise treads and risers that require manual construction and maintenance. If managed improperly, risers will collapse, causing soil loss, gully erosion, and cultivation threats. However, mapping terrace risers remains a challenge. This study presents a novel approach to automatically map terrace risers by combining remote sensing images and digital elevation models (DEMs). First, a terraced hillslope was extracted via a hill-shading method and edges in the image were detected using a Canny edge detector. Next, the DEM was used to generate the contour direction, and edges along this direction were searched and coded as candidate terrace risers via directional detection. Finally, the results of directional detection and the edge image obtained from the Canny detector were overlaid to backtrack complete terrace risers. The approach was validated using four study areas with different topographic characteristics in the Loess Plateau, China. The results verify that the approach achieves outstanding performance and robustness in mapping terrace risers. The precision, recall, and F-measure were 90.81%–97.57%, 88.53%–94.10%, and 90.13%–95.80%, respectively. This approach is flexible and applicable with freely available images and DEM sources.     

实时智能地震处理系统在2020年四川石渠M5.6地震序列中的应用

实时智能地震处理系统（RISP）是一套基于深度学习技术的新型地震实时处理系统,于2021年6月在四川开始试运行。为了评估该系统在四川台网稀疏区域的地震检测和处理能力,笔者等采用RISP系统对2020年4月1日四川甘孜州石渠县发生的M5.6级地震序列进行了回溯性分析,获得了较为可靠的自动处理地震序列目录,并与人工目录进行了对比分析。震后10d内,RISP系统自动处理获得了386个地震信号,地震数量是正式地震目录的1.98倍,匹配率为97.43%。分析显示,发震时刻偏差小于±1.0 s的地震占比71.05%,震中位置偏差小于10 km的地震占比96.31%,震级偏差小于±0.3级的地震占比99.47%。根据RISP系统检测地震序列分布特征和震源机制解,认为此次地震的发震断层为五道梁—长沙贡玛断裂北东侧的一条未发现的分支断层。研究结果表明,RISP系统的应用可以提升台网稀疏区域的地震检测能力,可快速产出地震序列目录,对大震应急、震后趋势判定和发震构造研究等具有重要意义。     

基于综合物探方法的公路不稳定边坡潜在滑面探测

为查明公路边坡滑面分布情况,采用瞬态面波和对称四极电测深法进行综合物探勘察,成功识别出滑动面以及潜在滑面位置、形态和范围,再结合钻孔,得出滑坡体地质剖面,高效准确的为滑坡处治设计提供了基础资料。工程实例应用表明,瞬态面波成像在滑动面以及潜在滑面识别中准确直观,且可以提供波速参数;电测深法能够提供不同地质体的电阻率参数,可以对瞬态面波进行有效补充;两种方法互相结合,可以较大限度的降低物探多解性,结合少量钻孔,能提供较为准确的滑坡体地质剖面,可在公路不稳定斜坡探测中发挥重要作用。     

成都市城市道路塌陷成因及快速探测方法

城市道路塌陷严重危害城市公共安全,对城市道路塌陷隐患进行快速、准确、绿色的探测,有助于减少城市地下病害发育,提升城市安全运营能力。通过调查分析,成都市城市道路塌陷的主要成因包括地质结构复杂、地下水丰富、人类工程活动频繁等。采用车载三维探地雷达对城市道路进行快速探测,建立了以探测、解译、验证、评估、成果及信息化管理为系统的探测体系。实践表明,车载三维探地雷达是快速探测城市道路塌陷隐患的有效方法。