非局部均值滤波在重力异常数据处理中的应用

根据小子域滤波原理,小子域滤波产生异常边界扭曲主要表现为高频干扰,提出小子域滤波与非局部均值滤波联合的方法以克服小子域滤波存在的异常边界扭曲问题。利用小子域滤波良好的边界增强能力和非局部均值滤波高频细节保护能力,在压制小子域滤波缺陷的同时尽可能保护小子域滤波的边界增强效果。通过模拟计算和莱州湾海域实测重力数据处理表明,本文方法在增强异常边界的同时压制小子域滤波产生的边界扭曲效应,获得了更好的重力异常处理效果。与单一小子域滤波相比,本文方法不需要考虑异常边界形态,具有更强的稳定性和普适性。     

An optimized baseflow separation method for assessment of seasonal and spatial variability of baseflow and the driving factors

Baseflow is an important component of river or streamflow. It plays a vital role in water utilization and management. An improved Eckhardt recursive digital filter(IERDF) is proposed in this study. The key filter parameter and maximum baseflow index(BFImax) were estimated using the minimum smoothing method to improve baseflow estimation accuracy. The generally considered BFImax of 0.80, 0.50 and 0.25 according to the drainage basin's predominant geological characteristics often leads to significant errors in the regions that have complex subsurface and hydrologic conditions. The IERDF improved baseflow estimation accuracy by avoiding arbitrary parameter values. The proposed method was applied for baseflow separation in the upstream of Yitong River, a tributary of the Second Songhua River, and its performance was evaluated by comparing the results obtained using isotope-tracer data. The performance of IERDF was also compared with nine baseflow separation techniques belonging to filter, BFI and HYSEP methods. The IERDF was also applied for baseflow separation and calculation of rainfall infiltration recharge coefficient at different locations along the Second Songhua River's mainstream for the period 2000–2016. The results showed that the minimum smoothing method significantly improved BFImax estimation accuracy. The baseflow process line obtained using IEDRF method was consistent with that obtained using isotope 18 O. The IERDF estimated baseflow also showed stability and reliability when applied in the mainstream of the Second Songhua River. The BFI alone in the river showed an increase from the upstream to the downstream. The proportion of baseflow to total flow showed a decrease with time. The intra-annual variability of BFI was different at different locations of the river due to varying climatic conditions and subsurface characteristics. The highest BFI was observed at the middle reaches of the river in summer due to a water surplus from power generation. The research provided valuable information on baseflow characteristics and runoff mode determination, which can be used for water resources assessment and optimization of economic activity distribution in the region.     

中国省际人口迁移短期预测分析

人口迁移是一个时空路径依赖过程,同时受迁移存量和周边迁移状况影响。当前人口迁移预测大多建立在时间序列模型之上,重点考虑迁移流在时间维度上的联系,忽视了其中的时空关联。该文将特征向量时空滤波方法与普通泊松模型相结合,考虑迁移流中可能存在的时空滞后和同期两种结构,对1985-2015年不同时段的中国省际人口迁移流数据进行建模和估计,并利用拟合程度较优的模型预测2015-2025年省际人口迁移的发展趋势。结果表明:1)特征向量时空滞后和同期滤波泊松模型均能较好地模拟研究时段省际人口迁移过程,自1985年以来我国省际人口迁移流不仅受迁出地和迁入地经济、社会等因素影响,也与过去迁移存量及周边迁移流密切相关;2)区域人口规模和GDP对迁移流的“推—拉”作用符合预期,地区人口规模较高和经济发展水平较低会促进人口外迁,反之则有利于吸引外来人口;3)与特征向量时空滞后滤波泊松模型相比,时空同期模型更便于捕捉省际人口迁移过程中的时空路径依赖特性,意味着当前人口迁移流的发展更易受到同时期周边迁移流的影响,表现出明显的羊群效应;4)预计2015-2025年我国省际迁移总量持续增加,呈现更集聚的空间模式,高迁入与高迁出区域在空间上相连,形成一条南北贯通的“高密度迁移地带”。将特征向量时空滤波模型拓展到人口迁移这一空间相互作用领域,可为当前构建更加完善的要素市场化配置体制机制等提供科学参考。     

建筑室内空间定位技术研究

为解决某市行政中心楼因建筑体量巨大、室内结构复杂而导致办事人员不易寻找目的地的问题,本文研究了室内空间定位搜寻方案,探讨了室内无卫星信号的定位方式。借助无线网络信号定位分析了无线网络信号传输中涉及的测距、信号滤波、空间定位等核心技术问题,并进行了试验验证,收到了良好的效果。     

Spatially filtered ridge regression (SFRR): A regression framework to understanding impacts of land cover patterns on urban climate

Understanding the impacts of land cover pattern on the heat island effect is essential for sustainable urban development. Conventional model fitting methods have restricted ability to produce accurate estimates of the land cover‐temperature association due to the lack of procedures to address two important issues: spatial dependence in proximal spatial units and high correlations among predictor variables. In this study, we seek to develop an effective framework called spatially filtered ridge regression (SFRR) to estimate the variations in the quantity and distribution of land surface temperature (LST) in response to various land cover patterns. The SFRR effectively integrates spatial autoregressive models and ridge regression, and it achieves reliable parameter estimates with substantially reduced mean square errors. We show this by comparing the performance of the SFRR to other widely adopted models using Monte Carlo simulation followed by an empirical study over central Phoenix. Results highlight the great potential of the SFRR in producing accurate statistical estimates, providing a positive step toward informed and unbiased decision‐making across a wide variety of disciplines. (Code and data to reproduce the results in the case study are available at: https://github.com/cfan13/SFRRTGIS.git .)     

半自动机载LiDAR点云建筑物三维重建方法

针对全自动建筑物3D重建存在需要后续人工检验,且发现重建错误需要花费额外时间修改的问题,提出了一种半自动的面向对象的机载LiDAR点云建筑物3D重建方法。基于建筑物类别点云的联通分析和平面生长分割结果,提出了自动的建筑物栋数检测、单栋建筑物外轮廓提取、单栋建筑物内部结构线提取方法;同时,在计算机无法完成部分工作时,人工辅助计算机完成高程阶越线提取、识别建筑物屋顶附属物点云等工作。实验证明,该方法可以适用于高密度机载LiDAR点云数据中城区大部分建筑物的3D模型重建。     

基于混合过滤的地学数据个性化推荐方法设计与实现

推荐系统是帮助互联网用户克服信息过剩的有效工具。在地学数据共享领域,较其他物品的内容属性,地学数据具有更加丰富的时空属性,这也给地学数据推荐带来挑战。针对地学数据的特点,为地学数据共享推荐服务开发了一种动态加权的混合过滤方法。该方法分别采用协同过滤和基于内容过滤算法预测用户对数据的兴趣度,再以训练模型计算最优加权权重,计算最终预测评分。在数据获取阶段,通过用户访问日志数据,采用Jenks Natural Break算法分析用户访问记录获取用户的数据兴趣度。在基于内容过滤部分,通过数据的空间、时间及内容属性计算数据相似度,并以用户历史行为为依据计算用户兴趣。在协同过滤和基于内容过滤中分别采用k-NN算法计算用户对未访问数据的预测评分,并进行加权求和。通过训练集,对理想权重值及用户的共同评价度（co-rating level）进行建模,拟合二者的关系。该模型被应用于混合过滤的权重调整,以获得最优的加权方程。测试结果显示,结合数据时空属性的混合过滤方法的准确度和召回率,较单一的协同过滤或基于内容过滤方法有显著提高。     

Vondrak滤波方法在软件接收机卫星双向时间传递中的应用

基于软件接收机的卫星双向时间传递(Two-Way Satellite Time and Frequency Transfer based on Software Defined Receiver, SDR-TWSTFT)链路每秒采集测量数据后通过数学模型将原始数据拟合为300 s一组的观测文件,因此链路的时间传递结果受短期测量噪声和非模型误差的影响,呈现出一定的随机噪声的特征.提出了一种频域幅值分析方法,针对性地确定滤波因子,构造符合需求的低通Vondrak滤波器.通过对中国科学院国家授时中心(National Time Service Center, NTSC)和德国联邦物理技术研究所(Physikalisch-Technische Bundesanstalt, PTB)之间的SDR-TWSTFT链路测量数据的分析发现,该方法对过滤链路平均时间一天内的高频噪声有效,能够提高链路时间传递结果的可信度,同时滤波后链路的短期频率、时间稳定度也有了显著提高.     

迭代扩展卡尔曼滤波用于实时GPS数据处理

标准的卡尔曼滤波可以扩展到非线性模型,即将泰勒公式应用于状态方程和观测方程,得到扩展卡尔曼滤波公式。首先推导了计算公式,研究了迭代计算方法,并将其用于ＧＰＳ数据的实时处理。