中国西太平洋海域1′×1′垂线偏差模型及精度评估

联合多种测高数据和重力异常数据,设计了观测点距离和测高精度融合的定权方法,采用最小二乘方法和Vening-Meinesz公式,分别构建了西太平洋海域(0°N—40°N,105°E—145°E)1′×1′网格化垂线偏差数字模型。选取两个不同特征区域,将垂线偏差的两个数字模型和EGM2008模型三者进行相互比较分析。结果表明:卯酉分量η的均方根差大于子午分量ξ的均方根差,海底地形复杂的南海特征区域的垂线偏差均方根差大于西太平洋中部的均方根差,构建的两个垂线偏差模型总体均方根差优于1.6″。     

点状地名信息的加权泰森多边形检索法

鉴于地名库中多数地名仅以中心点坐标形式记录其空间位置信息,缺乏其空间范围的具体描述,造成地名检索中的片面性和局限性,本文在深入分析地名及其空间属性、空间关系的基础上,考虑同类型地名的不同性质在检索中的重要作用,利用泰森多边形在地名边界近似中的优势,提出了针对点状地名信息的加权泰森多边形检索法,依据同类型地名的面积属性作为权重指标构建泰森多边形,以近似表达地名的空间范围,进而描述地名间的各类空间关系;并从拓扑关系、方位关系与距离关系3个方面给出了具体公式以计算地名间的空间相似性;最后以行政区划边界近似与检索为例验证该方法。试验结果表明,该方法可较好地近似表达地名空间范围及空间关系,增强了检索词与地理信息资源在空间位置上的相似性度量,检索结果优于传统方法。     

多目标遗传算法改进的加权多点灰色模型

针对传统多点灰色预测模型MGM(1,n)白化背景值构造方法不合理性导致模型往往不符合变形体实际情况的问题,该文提出了一种基于遗传算法的加权MGM(1,n)模型。引入白化背景值最佳生成权值矩阵替换传统模型背景值构造公式中的紧邻均值生成权阵,较好地顾及变形区域内多监测点变形趋势的突变性与不规则性,弥补了线性系统MGM(1,n)模型在非线性动力学系统变形预测分析应用中的不足;建立多目标优化实数编码遗传算法,实现背景值最优构造权阵的迭代搜索。基于仿真和工程实例数据的建模结果表明:改进模型较传统MGM(1,n)模型预测精度提高,抗噪声干扰能力增强。     

河南省县域粮食生产格局演化及影响因素

优化粮食生产布局、探讨粮食发展规律是有效调整农业空间结构、最大限度地提高土地生产效率的有效途径.以县域为单元,借用OpenGeoDa中空间自相关和ArcGIS 10.2中地理加权回归探究了1995-2014年河南省县域粮食生产格局演化及影响因素.结果表明:① 河南省粮食产量在全国粮食总产量中的比重总体呈现增长趋势;② 县域粮食生产现状显示"东部多西部少"的分布格局,其粮食生产多集中分布在中东部平原区的产粮大县,县域粮食生产空间集聚性逐渐增强;③ 粮食生产的影响因素在不同的空间上具有不同的影响程度,且粮食生产朝低碳有机和规模化方向发展.     

地面摄影测量测定地质结构面产状和几何要素方法的研究

本文详细叙述了用地面摄影测量方法确定露岩地质结构面的产状和几何要素的具体方法,包括摄影、控制,象片上节理面特征点的选取和量测,节理面的拟合和产状要素的算计以及精度评定等,并提出平差计算时采用选权迭代法以剔除粗差、保证成果质量。所编制的产状要素计算软件应用于某矿区的实际计算后证明是成功的,所获结果倾向中误差:m_(α0)=±1.0°,倾角中误差 m_(β0)=±1.47°,较好地满足用户提出的小于±5°的要求。     

基于在线加权式多模型方法的磁控立方星姿态机动控制

针对一类低轨道磁控立方星,提出一种在线加权式多模型自适应跟踪控制方法,使得卫星姿态能够根据指令实现较大角度的机动,并将误差保持在容许的范围内,达到满意的动态性能.首先,在卫星的几个姿态平衡点处建立控制系统模型,通过模型匹配度指标值,在线调整加权式多模型控制算法;其次,在多模型控制回路中引入动态自适应神经网络,充分利用其结构和参数均可以在线自适应调节的特点,以消除卫星在轨运行时受到的地球磁场变化的影响,并抑制不确定的外部干扰,提高系统鲁棒性能;最后,以某立方星为对象,进行仿真验证,结果表明所提方法是有效的.     

A comparative study of the segmentation of weighted aggregation and multiresolution segmentation

Multiresolution segmentation (MRS) algorithm has been widely used to handle very-high-resolution (VHR) remote sensing images in the past decades. Unfortunately, segmentation quality is limited by the dependency of parameter selection on users’ experience and diverse images. Contrarily, the segmentation by weighted aggregation (SWA) can partly overcome the above limitations and produce an optimal segmentation for maximizing the homogeneity within segments and the heterogeneity across segments. However, SWA is solely tested and justified with digital photos in computer vision field instead of VHR images. This study aims at evaluating SWA performance on VHR imagery. First, multiscale spectral, shape, and texture features are defined to measure homogeneity of image objects for segmentation. Second, SWA is implemented to handle QuickBird, unmanned aerial vehicle (UAV), and GF-1 VHR images and further compared with MRS in eCognition software to demonstrate the applicability of SWA to diverse images in building, vegetation and water, forest stands, farmland, and mountain areas. Third, the results are fully evaluated with quantitative measurements on segmented objects and classification-based accuracy assessment on geographic information system vector data. The results indicate that SWA can produce higher quality segmentations, need fewer parameters and manual interventions, create fewer segmentation levels, incorporate more features, and obtain larger classification accuracy than MRS.     

基于重庆CORS网的电离层VTEC插值研究

通过处理重庆CORS网的5个基准站观测数据,获得5个基准站上空电离层垂直总电子含量(VTEC)。利用其中的4个测站上空的VTEC采用克里金插值和反距离加权插值内插出另外一个测站上空VTEC。将插值结果及广义三角级数函数模型计算的电离层VTEC与实测VTEC进行比较,发现克里金插值和反距离加权插值的精度比广义三角级数函数计算的精度更高,更稳定;且克里金插值精度高于反距离加权插值。     

Comparison of spatial and aspatial logistic regression models for landmine risk mapping

Landmines continue to affect the lives of millions of people living in war-torn countries. One major challenge in humanitarian mine action (HMA) is finding new and integrated approaches to land release, which remains a slow and costly process. The use of geographic information systems (GIS) in HMA can improve the land release process by efficient mapping and prioritizing of landmine risk areas. This study explores the usage of aspatial and spatial regression techniques to construct a predictive geo-statistical model for landmine risk mapping in a small 160 km² municipality in Bosnia and Herzegovina (BiH) and a large 4500 km² region in Colombia. The first application of logistic geographically weighted regression to landmine risk mapping is presented. The results show that in the BiH study area, the effect of local parameters that influence the distribution of landmine risk varies significantly across the study area. Conversely, in the Colombia case study the effect of explanatory variables remains more homogeneous over the study area. We produced two landmine risk maps for each study area, based on aspatial and spatial regression models. Risk maps are classified into five classes, i.e. very low, low, medium, high, and very high risk. The landmine risk maps created through the usage of these innovative methodologies improve the assessment of risk and prioritization of the land release process in mine-contaminated areas, compared to existing approaches.     

中国高技术产业创新效率影响因素的空间异质效应—基于地理加权回归模型的实证研究

首先借助超越对数生产函数形式的多产出随机前沿模型估算出2008年~2013年中国30个省域高技术产业创新效率,继而基于地理加权回归模型(GWR)研究了企业规模、市场结构、政府投入及研发支出结构对创新效率的影响。结果表明:中国30个省域高技术产业创新效率存在空间正自相关性;企业规模、市场结构及研发支出结构对创新效率产生正向影响,而政府投入阻碍了高技术产业创新效率;各影响因素对高技术产业创新效率的影响均具有空间异质性特征,且随着时间的推移稳定存在。最后提出相关政策建议。