基于时态GIS的古气候动力模拟动态演化的分析与实现

对古气候研究环节中的动态演化问题进行研究和分析,提出了一种时空索引模型,以解决动态演化过程中的时间和空间的对应关系问题,利用时空索引对象来解决空间对象及其属性描述信息,在时间t的信息查询、显示和叠加。为古气候研究、再现和重建古气候以及模拟古气候环境下的大气环流基本场(包括温度场、降水场、气压场和位势高度场),在两维空间格局上,进行时间维的动态演化分析,提供了一个实用工具,在全球变化和区域响应等可视化方面具有较为广泛的应用前景。     

基于3DS MAX和MultiGen Creator的虚拟地理信息系统建模的比较分析

在虚拟地理信息系统建设和应用中,构建模型是系统建立的基础,是系统运行效果和效率的关键。就两种流行的建模软件3DS MAX和MultiGen Creator在虚拟地理信息系统中的应用进行比较,以虚拟现实项目制作流程作为基础,总结了它们在实际建模过程中的优劣,便于虚拟地理信息系统建设中合理选择建模软件。     

GPS动态定位中机动随机模型分析

给出了载体状态方程的严密公式和常用近似公式,详细讨论了两者之间的区别。在高精度GPS动态定位中的应用证明,常用近似公式对载体速度和加速度有显著的影响。     

海洋三维遥感与海洋剖面激光雷达

本文从海洋与气候变化等重大前沿科学与应用对空间海洋观测系统的需求出发,基于当前国内外空间激光技术水平与前期海洋激光遥感的探索,提出了海洋遥感从二维向三维发展的紧迫性,并将海洋剖面探测激光雷达作为未来“海洋三维遥感”的主要技术手段。本文对近50年国内外激光海洋剖面探测技术的理论与应用、基础性关键探测机理问题,尤其是近10年来的试验性探索及其在多个海洋科学问题中的应用进行了综述。结合中国自主“观澜号”海洋科学卫星计划中海洋剖面探测激光雷达的系统论证与指标要求,提出了未来海洋剖面探测激光雷达发展路线图建议以及中国有望率先在空间海洋剖面激光探测领域取得突破的设想。     

海洋涡旋遥感：进展与挑战

海洋涡旋数量大、分布广、含能高、裹挟强,是研究物质循环、能量级联和圈层耦合的理想载体。对涡旋的全生命周期追踪观测成为21世纪以来海洋遥感领域最重要的进展之一,并引发了新一轮涡旋研究的热潮。本文从涡旋的温度异常、物质示踪、旋转流场和闭合拓扑等特征出发,简述了红外辐射计、可见光扫描仪、微波高度计、合成孔径雷达等遥感技术在涡旋观测中的机理和方法,重点阐述了卫星高度计涡旋识别与追踪算法及其在涡旋形态学、运动学和动力学中的应用。基于虚拟星座下的多参数遥感,介绍了涡旋在海洋、大气、生态等交叉学科领域的前沿应用和最新进展。指出当前涡旋遥感发展面临的亚中尺度、垂直结构、跨学科研究等3大挑战,展望了新一代遥感技术在未来海洋科学特别是涡旋海洋学研究中的应用前景。     

Three-frequency BDS precise point positioning ambiguity resolution based on raw observables

All BeiDou navigation satellite system (BDS) satellites are transmitting signals on three frequencies, which brings new opportunity and challenges for high-accuracy precise point positioning (PPP) with ambiguity resolution (AR). This paper proposes an effective uncalibrated phase delay (UPD) estimation and AR strategy which is based on a raw PPP model. First, triple-frequency raw PPP models are developed. The observation model and stochastic model are designed and extended to accommodate the third frequency. Then, the UPD is parameterized in raw frequency form while estimating with the high-precision and low-noise integer linear combination of float ambiguity which are derived by ambiguity decorrelation. Third, with UPD corrected, the LAMBDA method is used for resolving full or partial ambiguities which can be fixed. This method can be easily and flexibly extended for dual-, triple- or even more frequency. To verify the effectiveness and performance of triple-frequency PPP AR, tests with real BDS data from 90 stations lasting for 21 days were performed in static mode. Data were processed with three strategies: BDS triple-frequency ambiguity-float PPP, BDS triple-frequency PPP with dual-frequency (B1/B2) and three-frequency AR, respectively. Numerous experiment results showed that compared with the ambiguity-float solution, the performance in terms of convergence time and positioning biases can be significantly improved by AR. Among three groups of solutions, the triple-frequency PPP AR achieved the best performance. Compared with dual-frequency AR, additional the third frequency could apparently improve the position estimations during the initialization phase and under constraint environments when the dual-frequency PPP AR is limited by few satellite numbers.     

Classifying Human Activity Patterns from Smartphone Collected GPS data: A Fuzzy Classification and Aggregation Approach

Smartphones have emerged as a promising type of equipment for monitoring human activities in environmental health studies. However, degraded location accuracy and inconsistency of smartphone‐measured GPS data have limited its effectiveness for classifying human activity patterns. This study proposes a fuzzy classification scheme for differentiating human activity patterns from smartphone‐collected GPS data. Specifically, a fuzzy logic reasoning was adopted to overcome the influence of location uncertainty by estimating the probability of different activity types for single GPS points. Based on that approach, a segment aggregation method was developed to infer activity patterns, while adjusting for uncertainties of point attributes. Validations of the proposed methods were carried out based on a convenient sample of three subjects with different types of smartphones. The results indicate desirable accuracy (e.g. up to 96% in activity identification) using of this method. Two examples are provided in the Appendix to illustrate how the proposed methods could be applied in environmental health studies. Researchers could tailor this scheme to fit a variety of research topics.     

GPS定位中对流层折射估计研究

本文首先讨论了ＧＰＳ相对定位中的对流层折射２估计的单参数方法，多参数方法，分估线性方法和随机过程方法。论证了其它方法都是随机过程方法的近似。为了用随机过程模拟对流折射，建立了一种最小二乘递推算法。在此基础上，在ＧＡＭＩＴ软件中统一实现了以各种对流层折射估计方法。最后给出并分析了不同方法所获得的结果。     

An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis: cases with different types of spatial data

ABSTRACT

Spatial heterogeneity represents a general characteristic of the inequitable distributions of spatial issues. The spatial stratified heterogeneity analysis investigates the heterogeneity among various strata of explanatory variables by comparing the spatial variance within strata and that between strata. The geographical detector model is a widely used technique for spatial stratified heterogeneity analysis. In the model, the spatial data discretization and spatial scale effects are fundamental issues, but they are generally determined by experience and lack accurate quantitative assessment in previous studies. To address this issue, an optimal parameters-based geographical detector (OPGD) model is developed for more accurate spatial analysis. The optimal parameters are explored as the best combination of spatial data discretization method, break number of spatial strata, and spatial scale parameter. In the study, the OPGD model is applied in three example cases with different types of spatial data, including spatial raster data, spatial point or areal statistical data, and spatial line segment data, and an R “GD” package is developed for computation. Results show that the parameter optimization process can further extract geographical characteristics and information contained in spatial explanatory variables in the geographical detector model. The improved model can be flexibly applied in both global and regional spatial analysis for various types of spatial data. Thus, the OPGD model can improve the overall capacity of spatial stratified heterogeneity analysis. The OPGD model and its diverse solutions can contribute to more accurate, flexible, and efficient spatial heterogeneity analysis, such as spatial patterns investigation and spatial factor explorations.     

结合深度学习和图割法的遥感影像建筑物检测

提出一种基于卷积神经网络和图割法的自动提取高分影像建筑物的方法。首先,通过卷积神经网络定位与检测建筑物的位置,逐一提取单个建筑物轮廓,利用检测结果分别建立建筑物和非建筑物的高斯混合模型（GMM）,然后结合最大流最小割的图像分割方式实现全局优化,完成建筑物初步提取,最后用形态学进行优化。通过试验证明了该方法的可行性。