浅论新农村建设中基层国土所的作用

2008年以来,临朐县加大土地储备力度,共储备土地73．33hm^2,招拍挂出让土地43．33hm^2,总成交价达2．4亿元。大量的土地储备与有序供应,有效地促进了土地资源的合理利用,实现了城市建设经济效益和社会效益的最大化。     

Mesoscale physical processes and zooplankton transport-retention in the northern Norwegian shelf region

Northern Norwegian shelf regions are highly productive, supporting fisheries rich in commercially important species such as cod, herring and capelin. It has been long recognized that the mesoscale jets, meanders and eddies associated with interactions between the North Atlantic Current, Norwegian Coastal Current and regional bottom topographic features such as troughs, banks and shelfbreaks play important roles in transporting and retaining zooplankton. To investigate zooplankton distributions and their correspondence with the physical fields, three large-scale surveys with mesoscale resolutions on physical and biological fields were conducted in northern Norwegian shelf regions between latitudes 68°15′N and 70°15′N in springs of 2000–2002. Survey results provide insights into the relationships between zooplankton distributions and the physical features such as fronts, the Norwegian Coastal Current and eddies related to topographic features. The physical and biological data are integrated and analyzed focusing on water types, estimation of geostrophic currents from direct current measurements, along-shelf transport of zooplankton, and retention of zooplankton by the mesoscale meander–eddy over a typical bank area on the shelf. The estimated mean transport in the upper 100 m on the shelf in the survey region is approximately 6.4×10³ tonnes wet weight day⁻¹ northward. High zooplankton abundances were found over both Malangsgrunnen and Sveinsgrunnen banks. The specific accumulation rate from northward–southward transport in the upper 100 m over Malangsgrunnen was approximately 0.08 day⁻¹, while variable currents with an offshore gradient of zooplankton abundance over Sveinsgrunnen implies an offshore dispersion of coastal-originated zooplankton cohort.     

Fuzzy comprehensive evaluation model for water resources carrying capacity in Tarim River Basin, Xinjiang, China

This paper explores the method of comprehensive evaluation of water resources carrying capacity and sets up an evaluation model applying the fuzzy comprehensive evaluation method. Based on the data of nature, society, economics and water resources of the Tarim River Basin in 2002, we evaluated the water resources carrying capacity of the basin by means of the model. The results show that the comprehensive grades are 0.438 and 0.454 for Aksu and Kashi prefectures respectively, where the current water resources exploitation and utilization has reached a relative high degree and there is only a very limited water carrying capacity, 0.620 for Kizilsu Kirgiz Autonomous Prefecture, where water resources carrying capacity is much higher, and in between for Hotan Prefecture and Bayingolin Mongolian Autonomous Prefecture. As a whole, the comprehensive grade of the Tarim River Basin is 0.508 and the current water resources exploitation and utilization has reached a relative high degree. Thus, we suggest that the integrated management of the water resources in the basin should be strengthened in order to utilize water resources scientifically and sustainably.     

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BIM与SuperMap GIS数据集成技术

现代社会大型复杂建设工程越来越多,室内3D GIS应用需求旺盛,但海量室内3D数据的缺乏成为室内GIS应用瓶颈。建筑信息模型(Building Information Models,BIM)提供丰富的建筑空间几何和语义信息,可为GIS所用。BIM与GIS数据集成技术成为国内外研究热点。本文从GIS应用的角度出发,通过分析BIM与GIS在数据标准和几何、语义表达方面的差异,提出BIM与SuperMap GIS 8C软件的数据集成技术,并实现了BIM在SuperMap GIS中的高性能空间分析与可视化。本文的研究有助于扩展SuperMap GIS的应用领域至室内空间,实现室外到室内、城市宏观到建筑微观的一体化应用,满足大型复杂室内场所的应急救援、导航与位置服务需求,服务于智慧城市建设。     

基于概率积分法的采动坡体稳定性预测与分析

地下采煤会引起地表沉降、变形,甚至引发山体、河堤滑坡等地质灾害。采动坡体的稳定性研究一直是采矿工程中实际关心的问题。该文首先介绍分析了概率积分法移动变形稳态、动态预测模型以及基于极限平衡理论的单滑面采动坡体稳定性预测模型,提出了使用概率积分法结合Knothe时间函数对采动坡体稳定性进行预测分析的方法,并使用C#及XML Schema语言编制了相关的计算程序。最后,结合一个工程实例对采动坡体稳定性和动态变化过程进行了预测与分析,通过实测数据验证了提出方法的可行性,得出了采动引起的坡体下沉是影响坡体稳定性的主要因素,并提出了在坡体拉伸阶段进行注浆加固的方法。     

Large area forest inventory using Landsat ETM+: A geostatistical approach

Large area forest inventory is important for understanding and managing forest resources and ecosystems. Remote sensing, the Global Positioning System (GPS), and geographic information systems (GIS) provide new opportunities for forest inventory. This paper develops a new systematic geostatistical approach for predicting forest parameters, using integrated Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images, GPS, and GIS. Forest parameters, such as basal area, height, health conditions, biomass, or carbon, can be incorporated as a response variable, and the geostatistical approach can be used to predict parameter values for uninventoried points. Using basal area as the response and Landsat ETM+ images of pine stands in Georgia as auxiliary data, this approach includes univariate kriging (ordinary kriging and universal kriging) and multivariable kriging (co-kriging and regression kriging). The combination of bands 4, 3, and 2, as well as the combination of bands 5, 4, and 3, normalized difference vegetation index (NDVI), and principal components (PCs) were used in this study with co-kriging and regression kriging. Validation based on 200 randomly sampling points withheld field inventory was computed to evaluate the kriging performance and demonstrated that band combination 543 performed better than band combination 432, NDVI, and PCs. Regression kriging resulted in the smallest errors and the highest R-squared indicating the best geostatistical method for spatial predictions of pine basal area.     

利用TGO软件的点校正功能实现物探测量GPS控制网待定点的解算

基于泌阳凹陷高精度三维地震采集测量GPS控制测量项目,作者论述了在TGO软件中利用点校正功能求解控制网中待定点坐标方法。通过与约束平差结果的比较,证明了此方法的可行性。     

广西扶绥地区那江盆地陆相层序地层初析

那江盆地是十万大山盆地北侧的一个中小型断陷盆地之一。本文根据陆相盆地层序地层的构造背景、控制因素及层序边界和内部结构特征等方面对那江断陷地层进行层序地层初析,确定出４个层序边界,划分出２个超层序（二级旋回）和３５个层序（三级旋回）;识别出冲积体系域（ＡＳＴ）、湖泊扩展体系域（ＥＳＴ）和湖泊萎缩体系域（ＲＳＴ）,初步探讨了断陷盆地层序地层的特征及其控制因素。     

基于改进EWT和LogitBoost集成分类器的地震事件分类识别算法

快速、准确地识别天然地震和人工爆破事件是地震台网监测的重要工作之一,也是提高地震观测记录质量、开展地震研究工作的重要基础。针对反向传播神经网络、支持向量机等主流分类识别方法在地震事件分类识别应用上的不足,提出一种基于改进EWT和LogitBoost集成分类器的地震事件分类识别算法。首先,基于S谱能量曲线对传统经验小波变换进行改进,将信号自适应分解为按频率和能量分布的本征模函数;其次,提取P波与S波最大振幅比,前4个本征模函数的香农熵、对数能量熵,以及去噪后重构信号主频等特征;最后,采用基于集成学习LogitBoost的决策树集成分类器进行分类。实验结果表明,所提算法具有较高的鲁棒性,能有效解决样本不足的问题,识别准确率达93.1%以上,比集成学习AdaBoost、反向传播神经网络和支持向量机等方法提高了1%以上,且分类识别效果好。