函数模型与随机模型双约束的GPS-InSAR数据融合方法建立三维形变场

针对InSAR技术研究地表三维形变时监测信息不足的问题，以GPS监测信息为先验信息，建立附有随机模型约束的地表三维形变模型。考虑到SAR卫星极轨方式运行导致LOS向观测量对南北向形变不敏感的问题，以GPS南北向形变观测值作为强约束，构建三维形变解算的函数约束条件。模拟数据与西安地区实测数据的计算结果表明，基于随机模型与函数模型共同约束的地表三维形变参数最小二乘解的精度优于仅有函数模型约束或仅有随机模型约束及无任何约束的参数解精度。     

一维综合孔径微波辐射计遥感海面温度的敏感性分析

一维综合孔径微波辐射计能够有效提高观测的空间分辨率，其观测入射角通常在0°~55°范围内变化。为了开发适用于一维综合孔径微波辐射计的海面温度反演算法，需要评估其观测亮温对海洋大气环境要素的敏感性。利用海面发射率模型和大气辐射传输模型，构建了适用于一维综合孔径微波辐射计的微波海洋大气辐射传输模式，研究了C波段垂直和水平极化微波辐射亮温在不同入射角下对海洋大气环境要素的敏感性变化情况，并定量计算了相应的敏感系数。结果表明:垂直和水平极化亮温对海洋大气环境要素的敏感性表现出不同的特性。随着入射角的增大，垂直极化亮温对海面温度的敏感性增强，对海面风场的敏感性相对减弱；水平极化亮温则相反。由大气水汽含量和云液态水含量误差引入的垂直和水平极化亮温误差随入射角增大而增大，但是，即使在55°的大入射角下垂直和水平极化亮温误差仍小于0.12 K。对于海面温度反演精度优于1 K的要求，一维综合孔径微波辐射计的测温精度需优于0.6 K。研究结果对于一维综合孔径微波辐射计海面温度反演算法的研究和载荷设计具有一定的理论指导意义。     

基于边际效应分析的海洋资源环境承载力评估

海洋资源环境的开发利用可视为将海洋资源环境作为生产投入要素的广义生产行为,因此受边际效应递减规律的制约。本研究基于资源环境边际效应的经济学视角,以对海洋资源环境破坏较大的填海造地建设为研究重点,通过基于GIS的海洋资源环境边际机会成本评估和基于边际效应分析的海洋资源环境承载力评估模型,建立海洋资源环境承载力的评估理论和方法,重新认识海洋资源环境承载力在海域管理绩效评估和科学决策中的重要作用,为区域海洋资源优化配置提供新的方法体系;关键成果是构建基于边际效应分析的海洋资源环境承载力评估模型,模型将海洋资源环境纳入宏观生产投入要素,由宏观要素的边际收益测算承载力极限阈值,其中对海洋资源环境的市场价值和非市场价值的正确评估是承载力评估的关键。     

Analysis of nonstationarity in low flow in the Loess Plateau of China

An approach for nonstationary low‐flow frequency analysis is developed and demonstrated on a dataset from the rivers on the Loess Plateau of China. Nonstationary low‐flow frequency analysis has drawn significant attention in recent years by establishing relationships between low‐flow series and explanatory variables series, but few studies have tested whether the time‐varying moments of low flow can be fully described by the time‐varying moments of the explanatory variables. In this research, the low‐flow distributions are analytically derived from the 2 basic explanatory variables—the recession duration and the recession coefficient—with the assumption that the recession duration and recession coefficient variables follow exponential and gamma distributions, respectively; the derived low‐flow distributions are applied to test whether the time‐varying moments of explanatory variables can explain the nonstationarities found in the low‐flow variable. The effects of ecosystem construction measures, that is, check dam, terrace, forest, and grassland, on the recession duration and recession coefficient are further discussed. Daily flow series from 11 hydrological stations from the Loess Plateau are used and processed with a moving average technique. Low‐flow data are extracted following the pit under threshold approach. Six of the 11 low‐flow series show significant nonstationarities at the 5% significance level, and the trend curves of the moments of low flow are in close agreement with the curves estimated from the derived distribution with time‐dependent moments of the recession duration and time‐constant moments of the recession coefficient. It is indicated that the nonstationarity in the low‐flow distribution results from the nonstationarity in the recession duration in all 6 cases, and the increase in the recession duration is resulted from large‐scale ecosystem constructions rather than climate change. The large‐scale ecosystem constructions are found to have more influence on the decrease in streamflow than on the increase in watershed storage, thus resulting in the reduction of low flow. A high return period for the initial fixed design value decreases dramatically with an increasing recession duration.     

2018?2019年舟山近海浮游动物群落结构春季年际变化及其与水团的关系

根据2018?2019年春季两个航次在舟山近海进行的浮游生物调查结果，对舟山近海的浮游动物群落结构(类群组成、优势种数量)年际变化进行了研究，利用典范对应分析(Canonical Correspondence Analysis, CCA)研究了两年春季浮游动物类群组成差异、优势种变化的原因，初步探讨了春季浮游动物群落结构动态变化的机制。结果表明:根据表层温度(Sea Surface Temperature，SST)、表层盐度(Sea Surface Salinity，SSS)的聚类分析，将该区域分为3个水团:杭州湾内水团(I区)、舟山本岛上升流水团II区)、舟山近海水团(III区)。不同水团对浮游动物类群组成影响显著，引起2018年和2019年春季3个水团区差异的主要贡献种(贡献率>10%)均为中华哲水蚤，同一水团两年间年际差异的贡献种如下:I区为捷氏歪水蚤(56.91%)和真刺唇角水蚤(12.34%)；II区为中华哲水蚤(72.64%)、五角水母(13.35%)；III区为中华哲水蚤(41.93%)、夜光虫(22.94%)。CCA分析表明，第1 CCA轴(CCA1)和第2 CCA轴(CCA2)共解释了两年春季浮游动物优势种累计方差的46.14%和物种?环境累计方差的97.82%。CCA1主要反映了空间(近海水团和湾内水团)的差异。CCA2主要反映了2018年和2019年站位的年际差异。盐度是影响春季浮游动物群落结构空间差异的主要因素，而温度、叶绿素a浓度是春季浮游动物群落结构年际差异的主要因素。     

基于一维综合孔径微波辐射计的海面温度反演研究

Due to the low spatial resolution of sea surface temperature(T_S) retrieval by real aperture microwave radiometers,in this study, an iterative retrieval method that minimizes the differences between brightness temperature(T_B)measured and modeled was used to retrieve sea surface temperature with a one-dimensional synthetic aperture microwave radiometer, temporarily named 1 D-SAMR. Regarding the configuration of the radiometer, an angular resolution of 0.43° was reached by theoretical calculation. Experiments on sea surface temperature retrieval were carried out with ideal parameters; the results show that the main factors affecting the retrieval accuracy of sea surface temperature are the accuracy of radiometer calibration and the precision of auxiliary geophysical parameters. In the case of no auxiliary parameter errors, the greatest error in retrieved sea surface temperature is obtained at low T_S scene(i.e., 0.710 6 K for the incidence angle of 35° under the radiometer calibration accuracy of0.5 K). While errors on auxiliary parameters are assumed to follow a Gaussian distribution, the greatest error on retrieved sea surface temperature was 1.330 5 K at an incidence angle of 65° in poorly known sea surface wind speed(W)(the error on W of 1.0 m/s) over high W scene, for the radiometer calibration accuracy of 0.5 K.     

不同插值方法在海域气象参数估算中的可靠性评价

海域条件下的气象观测具有数据稀少、变化大且观测站点分布不均的特点,其插值精度受插值方法影响较大。首先对常规插值方法进行理论分析,进而选取了反距离加权法、克里金法和样条函数法三种插值方法进行了插值实验和精度分析。根据渤海湾某区域的气象历史数据,采用不同方法绘制了温度、压强和湿度的插值平面图,并基于交叉验证的方式对各插值方法进行了对比,给出了不同方法的插值估算可靠性评价。结果表明:温度、压强和湿度的插值精度均是基于反距离加权法的插值结果最优(MAE_(温度)=2.42,RMSE_(温度)=1.92,MAE_(压强)=2.05,RMSE_(压强)=1.30,MAE_(湿度)=11.394, RMSE_(压强)=6.43),同时基于反距离加权法的图形绘制可视化效果也要优于其他两种方法。研究结果可为海域气象参数估算提供理论和实践依据。     

无人化时代反水雷装备体系构想

根据我国海洋方向面临的战略安全环境、建设“海上丝绸之路”的要求，我国的反水雷作战范围将延伸到第一岛链以外的海域，反水雷任务除了传统的近岸/ 近海反水雷任务，还增加了海峡反水雷、交通线反水雷以及海外基地反水雷等任务。 为了满足我国反水雷作战需求，结合国际上反水雷技术装备发展方向，用信息化改造、无人化拓展现有反水雷装备，构建无人化时代反水雷装备体系，形成能够在近岸、近海、中远海实施快速、安全、高效的反水雷作战能力。     

高分辨率光学遥感场景分类的深度度量学习方法

针对高分辨率光学遥感影像场景具有同类型内部差异大、不同类型间相似度高导致部分场景识别困难的问题，本文提出了一种深度度量学习方法。首先在深度学习模型的特征输出层上为每类预设聚类中心，其次基于欧氏距离方法设计均值中心度量损失项，最后联合交叉熵损失项以及权重与偏置正则项构成模型的损失函数。该方法的目标是在特征空间上使同类型特征聚集并扩大类型间的距离以提高分类准确率。试验结果表明，本文方法有效地提升了分类准确率。在RSSCN7、UC Merced和NWPU-RESISC45数据集上，与现有方法相比，分类准确率分别提高了1.46%、1.09%和2.51%。     

Regional extreme‐dry‐spell frequency analysis using the L‐moments method in the middle reaches of the Yellow River Basin,China

In this research, the regional extreme‐dry‐spell frequency in the middle reaches of the Yellow River Basin (YRB) is studied by the L‐moments method. The research area has been divided into three subregions (regions 1, 2 and 3), which have been identified as homogenous regions. The results of a goodness‐of‐fit test indicate that a generalized normal distribution is the optimal regional model for regions 1 and 2 whereas a generalized Pareto distribution is the optimal regional model for region 3. The return period analysis figures out that the maximum length‐of‐dry‐spell (MxDS) values increase from south to north in the southern part and increase from northeast to southwest in the northern part of the middle reaches of the YRB under different return periods. The increments of quantiles of dry spell under different return levels indicate that drought risk in region 1 is higher than that in regions 2 and 3. The analysis of the occurrence day of MxDS shows that MxDS mostly occurred during winter of 1998 and spring of 1999 in most stations during the considered period. By comparing summer MxDS events, it can be found that mean MxDS values have slightly increased in regions 1 and 2 during the last five decades. The maximum mean MxDS values appeared in the 2000s for regions 1 and 2 and in the 1990s for region 3. The atmospheric circulation shows that the positive anomaly centre in the west of North China, negative anomaly centre in the east of North China and the strong western Pacific subtropical high led to the decrease of precipitation in North China during the summer of 1997. Copyright © 2013 John Wiley & Sons, Ltd.