中国航磁大地构造单元划分

本文以我国截止到2011年基本覆盖陆域及部分海域的航磁数据编制的全国航磁系列图为基础,以航磁反映的区域磁场和磁性基底起伏特征为依据,汲取主流大地构造观的划分理念,以板块构造理论及大陆动力学思想为指导,以磁场反映的构造特征为切入点,结合重力、遥感、地质资料对中国陆域构造单元进行划分。大地构造单元划分4个级别:一级构造单元为陆块区和造山系,共划分出8个;二级构造单元为陆块、弧盆系和地块,共划分出32个;三级构造单元为盆地、坳陷带(区)和隆起带(区),共划分出85个;四级构造单元为隆起和坳陷,共划分出332个。本划分方案旨在为油气地质构造背景研究及油气勘探提供一份地球物理资料。文中重点讨论了一、二级构造单元界线厘定的磁场依据及与前人划分存在的不同之处,而三、四级构造单元完全依据磁场及磁性基底起伏情况进行划分,并在盆地和坳陷区给出了深度信息,这为油气勘探者提供了必要的技术支撑。同时,借助丰富的航磁信息提示出一些地质构造方面难解现象,供同行专家参考与讨论。     

检索词优化与空间自适应的深网POI获取方法研究

针对检索词库构建困难、数据请求量受限制等相关问题,该文提出一种基于独立覆盖率排序和空间自适应剖分的深网POI信息搜索方法,通过候选检索词初步构建、贪婪式探测搜索、检索词优化降维、空间自适应剖分爬行等主要流程,利用逐步逼近POI搜索的最大覆盖最优解,实现对深网POI信息的全量获取,大幅度提高深网POI数据的召回率与采集效率,该方法对于丰富地理信息资源、提升空间信息服务与内容管理能力具有重要意义。     

A hierarchical indexing strategy for optimizing Apache Spark with HDFS to efficiently query big geospatial raster data

ABSTRACT

Earth observations and model simulations are generating big multidimensional array-based raster data. However, it is difficult to efficiently query these big raster data due to the inconsistency among the geospatial raster data model, distributed physical data storage model, and the data pipeline in distributed computing frameworks. To efficiently process big geospatial data, this paper proposes a three-layer hierarchical indexing strategy to optimize Apache Spark with Hadoop Distributed File System (HDFS) from the following aspects: (1) improve I/O efficiency by adopting the chunking data structure; (2) keep the workload balance and high data locality by building the global index (k-d tree); (3) enable Spark and HDFS to natively support geospatial raster data formats (e.g., HDF4, NetCDF4, GeoTiff) by building the local index (hash table); (4) index the in-memory data to further improve geospatial data queries; (5) develop a data repartition strategy to tune the query parallelism while keeping high data locality. The above strategies are implemented by developing the customized RDDs, and evaluated by comparing the performance with that of Spark SQL and SciSpark. The proposed indexing strategy can be applied to other distributed frameworks or cloud-based computing systems to natively support big geospatial data query with high efficiency.     

中国沿海小黄鱼种群动力学及其空间异质性研究

小黄鱼是我国近海四种最重要的经济鱼类之一,在过去的几十年中小黄鱼种群及其两个地理亚种群经历了巨大的变化。小黄鱼的种群动力学研究,对于维持这一重要渔业的可持续管理是至关重要的。目前仅有的两个小黄鱼种群动力学模型只涵盖了较短的时间,且没有关注其空间差异。本文研究了1968年至2015年间黄渤海和东海小黄鱼的种群动力学模型,包含和不包含空间分层结构的两种贝叶斯模型被用于分析其种群动力学的大尺度空间异质性。本文分析了不同的假设,来研究小黄鱼种群动力学潜在的变化趋势。研究结果表明小黄鱼种群动力学特征具有明显的时间和空间变化。种群的增长速度从20世纪八十年代开始增加,而可捕系数从1981年到2015年增加了两倍多。与黄渤海亚种群相比,东海的小黄鱼亚种群生长速度更快,遭受的捕捞压力也更大。基于最大可持续产量MSY的参考点表明,无论是整个小黄鱼种群还是两个亚种群,近年来都有非常高的过度捕捞风险。因此我国小黄鱼的渔业管理急需更加保守的管理策略,同时考虑其地域差异。本文所用的方法可以应用于其他种类的资源评估和渔业管理,尤其是具有空间异质性和数据有限的种类。     

Multivariate analysis of fluorescence and source identification of dissolved organic matter in Jiaozhou Bay, China

Hierarchical clustering analysis and principal component analysis (PCA) methods were used to assess the similarities and dissimilarities of the entire Excitation-emission matrix spectroscopy (EEMs) data sets of samples collected from Jiaozhou Bay, China. The results demonstrate that multivariate analysis facilitates the complex data treatment and spectral sorting processes, and also enhances the probability to reveal otherwise hidden information concerning the chemical characteristics of the dissolved organic matter (DOM). The distribution of different water samples as revealed by multivariate results has been used to track the movement of DOM material in the study area, and the interpretation is supported by the results obtained from the numerical simulation model of substance tracing technique, which show that the substance discharged by Haibo River can be distributed in Jiaozhou Bay.     

�α�Ԥ��ģ�͵Ķ��ݽ׷���

?????????г???????????????????????????????????????????????????????????????????????????α?????????黯???α?????????????????????????????????α?????????????????????????????????????е????????????,??????????α???????????     

新旧地形图编号及范围解算方法

在深入分析新、旧地形图分幅及编号规则的基础上,建立了新地形图编号算法模型、新地形图图幅范围解算模型以及新、旧地形图编号转换算法模型。解决了地形图编号的快速检索与图幅范围解算等问题。     

山区遥感图像自动分类研究——以西南地区为例(英文)

In mountainous areas, it is the undulant terrain, various types of geomorphic and land use that make the remote sensing images great metamorphism. Moreover, due to the elevation, there are many areas covered with shadow, clouds and snow that make the images more inaccurate. As a result, it would be very difficult to carry out auto-classification of RS images in these areas. The study took Southwest China as the case study area and the TM images, SPOT images as the basic information sources assisted by the a...     

元素迁移的分维结构、级序路径及共轭地球化学异常存在的理论依据

微量元素在矿源岩（层）中迁移遵循严格的级序路径，并且存在两种迁移倾向。迁移的结果图象是一分维结构。两种共轭地球化学异常出现的有利环境是温度高度反差地区和大断裂系及其附近。