高频地波雷达海杂波背景下的船只目标检测研究进展

针对海杂波对高频地波雷达目标检测的干扰问题,分目标处于海杂波谱区之内和之外两种情况综述了海杂波背景下的目标检测方法。对于海杂波内目标检测的难题,介绍了一种基于现场海态同步观测信息的检测新思路以及初步验证结果。对国内外相关研究进展的归纳总结和新思路的提出,为提出更加有效的海杂波干扰下的目标检测方法提供了重要的参考。     

热稳定κ-卡拉胶酶产生菌Bacillus sp. Car19的发酵条件优化

对一株分泌热稳定κ-卡拉胶酶印尼热泉菌进行了种属鉴定, 并采用响应面法对该菌发酵产酶条件进行了优化。鉴定结果表明, 该菌株属于芽孢杆菌属(Bacillus), 命名为Bacillus sp. Car19(GeneBank: KT865196)。发酵条件优化结果显示, 9个环境因子影响Bacillus sp. Car19产酶量。其中影响Bacillus sp. Car19产酶量的三个主要因素分别为培养温度、培养基中Cu²⁺浓度和培养基中NaCl浓度。综合次要因素对Bacillus sp. Car19产酶影响, Bacillus sp. Car19最佳产酶发酵条件为: 培养温度52.31℃、Cu²⁺浓度6.93 mmol/L、NaCl浓度37.03 g/L, 培养基pH为6, 接种量1%, 培养时间36h, 半乳糖浓度0.3 g/L,硝酸铵浓度7g/L, 卡拉胶浓度0.5g/L。优化后发酵上清液酶活力达到15.21 U/mL, 与优化前相比提高了1.5 倍。     

基于SMOS卫星数据的海表面盐度模型

海表面盐度是研究海洋对全球气候影响以及大洋环流的重要参量之一,而卫星遥感技术是获取海表面盐度数据的最有效方法.目前,L波段的SMOS和Aquarius/SAC-D遥感卫星正在用于探测海表面盐度,并根据卫星观测数据和物理机制反演出海表面盐度的产品.但在某些近陆地区域,由于淡水流入及陆地射频(RFI)等因素影响,卫星反演盐度的产品精度较低.文中利用“东方红2号”科学考察船的实测数据、SMOS卫星数据,首次针对中国南海海域提出了用贝叶斯网络模型计算海表面盐度,并用验证数据集(实测Argo盐度)对模型进行适应性评估.经过计算,模型误差和验证误差分别为0.47 psu和0.45 psu,而相应的SMOS Level 2产品的精度分别为1.90 psu和1.82 psu.此模型为海表面盐度的计算提供了一个新方法.     

淤泥质潮滩地貌演变中的水动力及生物过程研究进展

淤泥质潮滩对于海岸防护、增加土地资源、保持生物多样性等具有重要作用。从淤泥质潮滩演变的主要驱动因子——潮流、波浪、生物作用及地下过程四个方面回顾和总结了潮滩演变动力地貌过程的相关研究进展,提出应关注潮滩短期演变规律、波浪与浮泥作用机理、生物生长与潮滩演变定量关系,以及地下过程作用机理等。     

Land-surface segmentation as a method to create strata for spatial sampling and its potential for digital soil mapping

Sampling efforts are constrained by limited availability of resources. Therefore, methods to reduce the number of samples, while still achieving reasonable accuracy are needed. Land-surface segmentation (LSS) has proven a powerful technique to partition digital elevation models (DEMs) and their derivatives into relatively homogeneous areas, which can be further employed as support in soil sampling. Though topography is one of the main soil forming factors, a robust assessment of the potential of this technique to digital soil mapping (DSM) is still missing. In this study, we aimed at evaluating the potential of LSS in stratifying a landscape into relatively homogeneous areas, which can be used as strata for guiding the selection of sampling points in DSM. The experiments were carried out in two study areas where soil samples were available. Land-surface derivatives were derived from DEMs and segmented with a tool based on the multiresolution segmentation algorithm, into objects considered as homogeneous soil-landscape divisions. Thus, one sample was randomly selected within each segment from the existing sample data, based on which predictions of soil classes/sub-orders and properties, i.e. soil texture and A-horizon thickness, were made. Results were compared with predictions based on simple random sampling (SRS) and conditioned Latin hypercube (cLHS). The segmentation-based sampling (SBS) scheme performed better than SRS and cLHS schemes in predicting the A-horizon thickness, soil texture fractions and soil classes, showing a high potential of LSS in stratifying a landscape for the purposes of DSM. The novelty of this study is in the way strata are constructed, rather than in the sampling design itself. Further research is needed to demonstrate the value of a SBS design for practical use. The analyses presented here further highlight the importance of considering locally adaptive techniques in optimization of sampling schemes and predictions of soil properties.     

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.     

山东济宁许厂煤矿下组煤瓦斯与二氧化碳开发利用前景及存在的问题

许厂煤矿下组煤中蕴藏着较为丰富的瓦斯、二氧化碳资源。下组煤位于瓦斯风化带内,含瓦斯、二氧化碳和氮气等气体,瓦斯含量与埋藏深度呈正相关关系,主要存在低含量瓦斯、二氧化碳抽采率、二氧化碳资源化转换等技术方面的问题。从国家相关优惠政策、资源优势、煤与煤层气一体化开发技术、近水平长钻孔定向钻进技术、煤层压裂造缝技术、煤层注气增产技术和瓦斯、二氧化碳气体提纯技术等关键技术的发展程度,结合煤矿的下组煤层的开采方案,认为许厂煤矿有着较好的煤炭与瓦斯、二氧化碳一体化开发利用前景。     

基于高效生态农业布局导向性的资源环境承载力评价—以黄河三角洲高效生态经济区为例

该文在对研究区资源环境本底基本了解的基础上,建立了包括耕地资源、水资源、社会经济资源、土壤环境、极端气候发生率和地质环境6个二级指标的资源环境承载力评价指标体系,采用定性和定量相结合的方法,利用层次分析法确定相关指标权重,分别对6个要素进行承载力评价。在各单元要素评价基础上,结合黄河三角洲高效生态经济区农业发展要求,划分出了沿海湿地生态系统保护带、北部盐渍化土质特色种植区、南部优质粮食生产区和果蔬集中种植区4个生态农业布局适宜区,并提出发展建议。     

桩锚支护深基坑施工过程变形特征分析

以济南市某大型深基坑工程为依托,通过FLAC3D对深基坑工程不同施工阶段的变形特性进行了数值计算分析;桩锚支护深基坑,地表最大竖向变行产生在距离基坑边缘10 m位置处,且最大竖向变形量为46.16 mm;最大水平位移发生在桩顶冠梁位置处,最大水平位移为53.45 mm,是基坑支护最薄弱环节,基坑呈现三角形状向内侧滑动的趋势。     

大地电磁测深（MT）与土壤氡气测量在涡阳地区地热勘查中的应用

为了研究涡阳地区深部构造和热源条件,在高炉镇附近进行了大地电磁测深(MT)测量和土壤氡气测量工作。通过对大地电磁测深结果和土壤氡气浓度异常分布范围分析和解释,指导区内地热勘查工作。通过资料解释,基本查明区内构造的走向及其垂向延展特征,查明基底起伏变化情况并了解深断裂的控制性,预测地热成矿区有利地段。研究证明,利用MT与土壤氡气测量对隐伏断裂位置和地热异常具有较好的指示意义。