空间选址关键因素及其建模研究

影响空间选址的因素错综复杂,本文在对以往一些研究成果进行综合分析的基础上,提出了空间选址的三大影响因素:容量、区位特征和作用范围,并进行了空间选址的建模研究,建立了三个基本模型(容量因素影响模型、区位特征因素影响模型、作用范围因素影响模型)和空间选址的评估模型,并结合应用实例对该模型进行了初步的验证。     

利用中心差分法进行GPS定速时最佳点数的选取

分析了利用中心差分法进行GPS定速时的主要误差来源,证明了当数据采样率一定时,增加中心差分法的点数可减少微分过程中的截断误差,但同时会放大导出相位率的观测误差,得出中心差分法的最佳点数应使这两种误差之和最小的结论。实验结果表明,当数据采样间隔为1s、载体平均速度和加速度为20m.s-1和0.2m.s-2时,9个点的中心差分法定速精度最高。     

缺少控制点的卫星遥感对地目标定位

从单线阵推扫式传感器的成像机理出发,利用6个卫星轨道开普勒参数和3个传感器姿态角建立了推扫式卫星遥感影像坐标与其地面点在地心坐标系下的坐标关系式,即构像方程。按照所建立的构像方程,对某地区一景SPOT-5影像进行对地目标定位,获得了实地上83.392m的平面精度;利用单个地面控制点对卫星轨道开普勒参数和传感器姿态实施调整后,目标定位精度提高到14.217m。试验证实,所建立的构像方程是正确的,在卫星遥感对地目标定位中有较好的应用前景。     

Toward seamless indoor-outdoor applications: Developing stakeholder-oriented location-based services

Location-Based Services (LBS), an emerging new business based on smartphone and mobile networks, are becoming more and more popular. Most of these LBSs, however, only offer non-seamless indoor/outdoor applications and simple applications without giving stakeholders the chance to play an active role. Our specific aim is to solve these issues. This paper presents concepts to solve these issues by expanding the Open Location Services Interface Standard (OpenLS) to allow seamless indoor/outdoor positioning and to extend the content of the services to include information recommended by stakeholders.     

一等水准点之记标准化与规范化研究

为保证一等水准点之记精度与质量,提高测绘人员野外工作效率,对目前的一等水准点之记进行了探讨与分析,指出了其详细位置图与点位,详细说明表达、标石断面图绘制和经纬度书写及交通路线描述中存在的缺点,并基于此提出了若干改进意见,这在一定程度上促进了一等水准点之记信息的标准化与规范化。     

基于灰色预测法的超市选址模型研究

超市的选址是企业战略决策的重要内容之一,影响超市选址的各种因子错综复杂,无法进行精确的定量分析。文中对影响超市选址的各种因子建立二级选址指标体系,进行权重分析,同时结合选址因子结构关系模糊、动态变化随机、浮动范围不确定等灰色特性,采用灰色预测法建立超市选址模型,并利用缓冲区分析、叠置分析等GIS空间分析方法,基于Supermapobjects组件进行了二次开发实验。     

Multi‐scale approach to mining significant spatial co‐location patterns

Spatial co‐location pattern mining aims to discover a collection of Boolean spatial features, which are frequently located in close geographic proximity to each other. Existing methods for identifying spatial co‐location patterns usually require users to specify two thresholds, i.e. the prevalence threshold for measuring the prevalence of candidate co‐location patterns and distance threshold to search the spatial co‐location patterns. However, these two thresholds are difficult to determine in practice, and improper thresholds may lead to the misidentification of useful patterns and the incorrect reporting of meaningless patterns. The multi‐scale approach proposed in this study overcomes this limitation. Initially, the prevalence of candidate co‐location patterns is measured statistically by using a significance test, and a non‐parametric model is developed to construct the null distribution of features with the consideration of spatial auto‐correlation. Next, the spatial co‐location patterns are explored at multi‐scales instead of single scale (or distance threshold) discovery. The validity of the co‐location patterns is evaluated based on the concept of lifetime. Experiments on both synthetic and ecological datasets show that spatial co‐location patterns are discovered correctly and completely by using the proposed method; on the other hand, the subjectivity in discovery of spatial co‐location patterns is reduced significantly.     

基于局部地球重力场模型的水下目标被动定位

提出了一种基于局部地球重力场模型的水下被动定位新模式。这种方法无需使用常用的匹配算法,因而也就摆脱了匹配算法的诸多限制。以分辨率为2′×2′的某区域重力异常数据为背景场进行仿真,仿真结果表明,局部重力场模型的平均误差小于0.133 1 mGal,潜器的平均经纬方向定位误差分别小于0.777 0nmile和1.244 4 nmile。     

Toward seamless indoor-outdoor applications: Developing stakeholder-oriented location-based services

Location-Based Services (LBS),an emerging new business based on smartphone and mobile networks,are becoming more and more popular.Most of these LBSs,however,only offer non-seamless indoor/outdoor applications and simple applications without giving stakeholders the chance to play an active role.Our specific aim is to solve these issues.This paper presents concepts to solve these issues by expanding the Open Location Services Interface Standard (OpenLS) to allow seamless indoor/outdoor positioning and to extend the content of the services to include information recommended by stakeholders.