总电子含量赤道异常变化特性分析

利用国际GNSS服务组织提供的总电子含量格网数据,从全球角度分析了电离层赤道异常的变化规律,并结合相关研究结论做了比较分析。首先,利用2011年3月21日(春分)的总电子含量格网数据分析了电离层赤道异常区域随时间变化的规律;然后,利用2000—2012年的总电子含量格网数据和太阳黑子数据,统计分析了120°E上空电离层赤道异常出现的地理纬度和强度的变化规律,并以2002年(太阳活动高年)和2008年(太阳活动低年)为例做了进一步分析。结果发现:电离层赤道异常区域随太阳直射点位置的变化,自东向西移动,分布在地磁赤道的两侧,具有南北半球的非对称特性;电离层赤道异常出现在当地时间T 12:00:00—T 16:00:00,日落后持续2~3h;电离层赤道异常峰值强度与太阳活动强度存在正相关关系;电离层赤道异常具有明显的季节变化规律,表现出了"半年度异常"和"冬季异常"现象。     

平行轮廓线自适应插值的三维表面重构算法

针对稀疏点轮廓线在三维表面重构中存在的不够光滑、匹配易出错和难以交互等问题,提出了基于轮廓线插值的三维表面重构方法,并通过实验进行验证。文章分析了三维表面重构的形式化表达方法和准则,提出了基于虚跨距解决稀疏点轮廓线三维重构的基本思想;基于同步前进算法和虚跨距,设计了自适应等比例插值的同步前进三角面镶嵌算法;针对轮廓线插值违背三角表面重构拓扑准则的规律进行了分析,提出了相应的修正算法,保证了三角网的拓扑一致性。试验结果表明:本算法所构建的三角网表面更为光滑,各个三角面的大小更为均匀,具有更好的鲁棒性和交互性,对稀疏和稠密坐标点的轮廓线均能构建出更为理想的三维表面模型。     

抗差估计的多波束测深数据内插方法

针对传统多波束测深数据网格化内插方法抗差性不足的问题,该文将抗差估计理论应用于网格化内插方法中。基于不确定度指标建立了距离不确定度联合加权内插模型,在该模型的权函数中引入了等价权,同时给出了等价权设计方案及迭代初值确定原则,以增强模型的抗差性;介绍了一种节点邻域参考点合理选取方法,给出了改进内插法实现的基本步骤,最后通过实测数据对反距离加权法、联合加权法及改进方法内插水深质量进行比较。结果表明,改进方法内插结果要优于另外两种方法,可应用于多波束测深数据网格化处理中。     

Temporal replication of the national land cover database using active machine learning

Regional and national level land cover datasets, such as the National Land Cover Database (NLCD) in the United States, have become an important resource in physical and social science research. Updates to the NLCD have been conducted every 5 years since 2001; however, the procedure for producing a new release is labor-intensive and time-consuming, taking 3 or 4 years to complete. Furthermore, in most countries very few, if any, such releases exist, and thus there is high demand for efficient production of land cover data at different points in time. In this paper, an active machine learning framework for temporal updating (or backcasting) of land cover data is proposed and tested for three study sites covered by the NLCD. The approach employs a maximum entropy classifier to extract information from one Landsat image using the NLCD, and then replicate the classification on a Landsat image for the same geographic extent from a different point in time to create land cover data of similar quality. Results show that this framework can effectively replicate the land cover database in the temporal domain with similar levels of overall and within class agreement when compared against high resolution reference land cover datasets. These results demonstrate that the land cover information encapsulated in the NLCD can effectively be extracted using solely Landsat imagery for replication purposes. The algorithm is fully automated and scalable for applications at landscape and regional scales for multiple points in time.     

Study on the Global Carbon Assimilation System Based on Multisource Remote Sensing Data

The Paris agreement signed in April, 2016 aims to balance global anthropogenic carbon emissions and terrestrial carbon sinks by the middle of the 21^st century. To fulfill this goal, it is necessary to calculate carbon fluxes of different regions reliably. The global carbon assimilation system is an effective technique for achieving this goal. The Ministry of Science and Technology of China supports the project entitled as study on the global carbon assimilation system based on multisource remote sensing data through the national key research and development programs for global change and adaptation during the thirteen-five period. This project will develop synergic inversion techniques for retrieving key parameters of biological and atmospheric cycles and for assimilating multisource remote sensing and ground based data. Then, the high resolution global carbon assimilation system coupled with an ecological model will be constructed. This system is able to assimilate jointly multisource observation data and to optimize key model parameters, photosynthesis and respiration carbon fluxes of global terrestrial ecosystems, and anthropogenic carbon emission fluxes of key regions. This system will be used to study quantitatively the spatial and temporal patterns of carbon fluxes of global terrestrial ecosystems and anthropogenic carbon emission fluxes of key regions and to identify the mechanisms driving the global terrestrial carbon sinks and sources. The outputs of this study will be helpful for the fulfillment of the key research and development programs for global change and adaptation and provide valuable data and technical support for the decision-making in China.     

Crustacean decapod assemblages associated with fragmented Posidonia oceanica meadows in the Alboran Sea (Western Mediterranean Sea): composition,temporal dynamics and influence of meadow structure

The decapod assemblage associated with a Posidonia oceanica meadow located near its western limit of biogeographic distribution was studied over an annual cycle. Fauna samples were taken seasonally over a year (five replicates per season) in two sites located 7 km apart, using a non‐destructive sampling method (airlift sampler) for the seagrass. The dominant species of the assemblage, Pisidia longimana, Pilumnus hirtellus and Athanas nitescens, were associated with the protective rhizome stratum, which is mainly used as a nursery. The correlations between decapod assemblage structure and some phenological parameters of the seagrass shoots and wave height were negative or null, which reflects that species associated with the rhizome had a higher importance than those associated with the leaf stratum. The abundance and composition of the decapod assemblage as well as the ecological indexes displayed a seasonality trend with maximum values in summer‐autumn and minimum in winter‐spring, which were related to the seawater temperature and the recruitment periods of the dominant species. The spatial differences found in the structure and dynamics of the assemblages may be due to variations in the recruitment of the dominant species, probably as a result of the influence of local factors (e.g. temperature, currents) and the high dispersal ability of decapods, together with the patchy configuration and the surrounding habitats. The studied meadows are fragmented and are integrated within a mosaic of habitats (Cymodocea nodosa patches, algal meadows, rocky and sandy bottoms), which promotes the movement of individuals and species among them, maintaining a high species richness and evenness.     

象山港海洋牧场示范区大型底栖生物的时空变化

根据象山港海洋牧场示范区建设前(2011年)、建设中(2012年)、建设后(2013年)对象山港全港区、邻近区、示范区11个站位,进行5个航次调查所获得的大型底栖生物的资料,对比分析建设前后大型底栖生物的时空变化。结果表明:共鉴定出大型底栖生物59种,建设后建设中建设前,优势种变化明显。大型底栖生物密度、生物量表现为:建设前建设中建设后;建设中建设后建设前。多样性指数H’、丰富度指数d均表现为:建设前建设后建设中,均匀度指数J则表现为建设中建设后建设前。多因子方差分析结果表明:建设前后,大型底栖生物种类数、栖息密度、生物多样性指数均存在显著性差异。根据群落聚类及n MDS排序分析,建设前后大型底栖生物群落组成存在明显差异,双因素相似性分析(ANOSIM)结果同时表明,群落建设前后存在显著性差异(综合检验R=0.215,P=0.004)。SIMPER分析,大型底栖生物群落的平均相似性建设前建设后建设中。根据调查站位的数据作出丰度/生物量比较曲线(ABC曲线)分析表明,建设中大型底栖生物受到了强烈的干扰,人工鱼礁投放、大型海藻移植、增殖放流会对其周围海域产生影响,但建设后扰动消失,表明随着时间的推移,海洋牧场建设过程中带来的扰动逐渐减小,并围绕鱼礁群逐渐形成新的人工生态系统。     

白令海夏季浮游植物的群落结构与时空变化

通过1999年和2010年夏季同期7月在白令海(169°E~166°W,50°N~67°N)获取的94份浮游植物样品分析,获得了近十年的始末两个时间节点的浮游植物群落结构与时空变化,探讨了浮游植物群落动态及其与环境因素的关联。研究结果显示,共鉴定浮游植物(>10μm)5门58属153种,分为3个生态类群。硅藻是浮游植物的主体,种类多丰度高,占总种类数目的66.7%,占总丰度的95.2%。鉴于样品属性和空间范围的不同,物种组成有细微差别,丰度有较大差异且空间分布明显不同,高丰度区受控于上层营养盐供给和表层环流系统。优势种从北方温带大洋性硅藻演变为广温广盐性与冷水性硅藻,1999年以西氏新细齿状藻为第一优势种,柔弱伪菱形藻次之;2010年以丹麦细柱藻为第一优势种,冷水性的诺登海链藻次之并在陆架和陆坡占优。浮游植物群落结构较为稳定,由深水群落和浅水群落组成。深水群落分布于太平洋西北部和白令海盆,种类组成以温带大洋性的西氏新细齿状藻、长海毛藻、大西洋角毛藻和广布性的菱形海线藻、扁面角毛藻、笔尖根管藻为主,丰度低,种间丰度分配均匀,优势种多元化,物种多样性高;浅水群落分布于白令海陆坡和陆架,主要由冷水性的诺登海链藻、叉尖角毛藻、聚生角毛藻和广布性的丹麦细柱藻、旋链角毛藻组成,丰度高,种间丰度分配不均匀,优势种突出,物种多样性低。白令海夏季浮游植物种类组成及丰度变化直接受控于表层环流、营养盐、春季冰缘线等环境因素。     

东山乌礁湾海滩表层沉积物粒度时空变化分析

为了进一步了解海岛岬湾海岸表层沉积物粒度的时空分布特征和形成机制,作者以福建东山岛乌礁湾为典型研究区,通过秋、春、夏3个不同季节海滩表层沉积物的采集和点位测量,综合应用激光法和筛析法进行粒度测定。结果表明,东山乌礁湾海滩表层沉积物以0.16～0.50 mm之间的中、细砂为主,并含有少量的粗砂和细砾,这与区域砂质沉积背景有关;湾内从南到北剖面沉积物粒径由粗砂到细砂逐渐变细,主要受剖面地形、局地物源、季节性风浪作用和近岸往复水动力的影响。时间变化上,各取样站位表现出沉积物粒径粗、细不同程度的多种变化趋势,以秋季为参考,整体上表现为由南到北粒级的变小、增大和稳定,这与东北、南南西季风影响下的浪、潮作用以及沿岸流系格局变化下的水动力环境有关。     

Dasymetric Spatiotemporal Interpolation

This research applies the principles of dasymetric mapping to spatiotemporal interpolation by extending the spatial concepts of zone and area to their temporal analogs of interval and duration, respectively. An example application of dasymetric spatiotemporal interpolation using crime event data is presented. Results indicate that dasymetric spatiotemporal interpolation significantly improves the accuracy of estimates over areal or duration weighting. In addition, even when dasymetric interpolation in either the spatial or temporal dimension is relatively weak, combining dasymetric estimation in both space and time dimensions simultaneously has the potential to amplify the accuracy of the overall dasymetric estimation.