基于多粒度时空对象数据模型的高速公路智能监控系统建模

多粒度时空对象数据模型更注重现实世界复杂、动态现象的表达,能更好地应用于智能设施管理和智能决策支持系统。该文基于多粒度时空对象数据模型及其建模理论,对高速公路智能监控系统中实体对象的特征和关系进行概念建模,设计数据存储方案,开发高速公路智能监控多粒度时空对象建模原型系统,并验证数据模型的实用性。结果表明:多粒度时空对象数据模型可以很好地支撑高速公路智能监控系统中动态智能实体及实体间复杂关系的表达、管理和分析,实现对路情的智能分析与决策。     

空间运动对象与时空数据类型研究

当前时空数据模型多以描述空间实体的离散变化为主。该文中对空间运动对象在抽象层次的无限连续空间、离散层次的有限离散空间上的数据类型进行分析和定义，将其分别划分为时间类型、空间类型和时态类型来研究，并提出支持空间运动对象的表示方法和操作方式。该方法既能表示空间实体的连续运动，也能表示其离散变化，为空间运动对象时空数据模型的建立奠定了基础。     

Discovering relative motion patterns in groups of moving point objects

Technological advances in position‐aware devices are leading to a wealth of data documenting motion. The integration of spatio‐temporal data‐mining techniques in GIScience is an important research field to overcome the limitations of static Geographic Information Systems with respect to the emerging volumes of data describing dynamics. This paper presents a generic geographic knowledge discovery approach for exploring the motion of moving point objects, the prime modelling construct to represent GPS tracked animals, people, or vehicles. The approach is based on the concept of geospatial lifelines and presents a formalism for describing different types of lifeline patterns that are generalizable for many application domains. Such lifeline patterns allow the identification and quantification of remarkable individual motion behaviour, events of distinct group motion behaviour, so as to relate the motion of individuals to groups. An application prototype featuring novel data‐mining algorithms has been implemented and tested with two case studies: tracked soccer players and data points representing political entities moving in an abstract ideological space. In both case studies, a set of non‐trivial and meaningful motion patterns could be identified, for instance highlighting the characteristic ‘offside trap’ behaviour in the first case and identifying trendsetting districts anticipating a political transformation in the latter case.     

Plain move predicate and its consistency concerning the moving agents in a network

Advances in GIS and databases for dealing with spatiotemporal frameworks are leading to efficient querying, analyzing, and reasoning about moving objects/agents. However, contemporary frameworks on spatiotemporal logics are usually limited to qualitative approaches, such as the numerous studies on spatiotemporal databases that focus on observations, ignoring the intended movements of the agents. Moving object databases, on the other hand, can handle queries about the location, velocity, and time by assuming some agents to be targets. However, reasoning about the plan of moving agents, especially on the network and the achievability of such a plan, still remains a challenge. Studies on vehicle routing are often about the centralized planning of moving agents from scratch and do not deal with intended plans. Based on a plain move predicate, this paper presents a generic framework that can be used for representing and reasoning about plans of moving agents. Concepts from motion, network structure, graph theory, predicate logic, and constraint satisfaction are used to create the framework. We have also provided efficient algorithms for checking the consistency of the movement and extracting compatible plans along with some discussions on computational analysis, logical deduction, and flexibility. Finally, we have demonstrated the application of the methodology by developing NETwork-based Move Atoms Planning System (NETMAPS). The experiments show how NETMAPS can overcome an inconsistent movement plan and deliver advantageous suggestions to an executive agent.     

人类活动研究的新支点：Wi-Fi数据的特点、研究现状与应用前景

把握人类活动的时空特征是地理学研究中探究人地关系、提升人类福祉的重要基础和核心内容,日益普及的Wi-Fi网络能够为此提供可靠的数据支持。为明确Wi-Fi数据融入地理学研究的切入点和发展方向,论文通过与GPS、手机信令、蓝牙等位置感应数据的比较,认为Wi-Fi数据具有更高的采样精度和更强的采样代表性,能够获取个体在室内外各类城市空间的连续活动轨迹,支撑精细尺度下的人类活动研究。通过系统梳理人群活动状态监测、个体间的社会关系识别、建筑物的功能识别和降低隐私泄露风险等方面的研究进展,认为Wi-Fi数据将会在基于实时动态人口数据的城市功能设施规划、融合多源数据的人地关系探究、以居民福祉为导向的宜居城市建设等方面具有应用前景,有望成为地理学研究人类活动的新支点。     

人类活动轨迹的分类、模式和应用研究综述

各种传感器的应用与发展,如车载GPS、手机、公交卡、银行卡等,记录了人类的活动轨迹。这些海量的人类活动轨迹数据中蕴含着人类行为的时空分布模式。通过对这些轨迹的研究可以挖掘个体轨迹模式,理解人类动力学特征,进而为对轨迹预测、城市规划、交通监测等提供支持。因此,研究各类传感器记录的人类活动轨迹数据成为当前的研究热点。本文对人类活动轨迹的获取与表达方式进行剖析,并将人类的活动轨迹按照采样方式和驱动因素的不同分为基于时间间隔采样、基于位置采样和基于事件触发采样等3类轨迹数据。由于各类轨迹数据均由起始点、锚点和一般节点等构成,因而将轨迹模式挖掘的研究按照锚点、出行范围、形状模式、OD流模式、时间模式等进行组织,研究成果揭示人类活动轨迹在时间、空间的从聚模式、周期性等特点。在此基础上,将人类活动轨迹在城市研究中的应用,按照用户轨迹预测、城市动态景观、城市交通模拟与监控、城市功能单元识别以及城市中其他方面的研究应用进行系统综述,认为人类活动模式挖掘是城市规划、城市交通、公共安全等方面应用的基础。     

西宁市居民工作日和休息日时空活动差异研究

以手机信令数据为数据源,研究西宁市居民在工作日和休息日的时空活动差异及POI设施空间分布对居民活动差异的影响。结果表明:1)西宁市为单中心空间结构,居民在工作日集中分布在市中心区域,而在休息日的分布较分散;2)在休息日,商业和交通设施对居民活动产生积极影响,居住用地在早上对居民活动产生较强的积极影响(下午影响强度减弱),工业用地和公共用地在大部分时段对居民活动强度产生消极影响;3)在工作日,商业设施对居民活动的影响明显减弱,居住用地仅在晚上和凌晨对居民活动产生积极影响,而白天大部分时段出现消极影响,工业用地和公共用地在白天大部分时段会促进居民停留。研究结果有助于明确工作日和休息日居民在城市空间的时空活动差异及影响机制,可为城市出行空间和基础设施规划提供参考。     

Scaling of foreign attractiveness for countries and states

People’s behavior on online social networks, which store geo-tagged information showing where people were or are at the moment, can provide information about their offline life as well. In this paper we present one possible research direction that can be taken using Flickr dataset of publicly available geo-tagged media objects (e.g., photographs, videos). Namely, our focus is on investigating attractiveness of countries or smaller large-scale composite regions (e.g., US states) for foreign visitors where attractiveness is defined as the absolute number of media objects taken in a certain state or country by its foreign visitors compared to its population size. We also consider it together with attractiveness of the destination for the international migration, measured through publicly available dataset provided by United Nations. By having those two datasets, we are able to look at attractiveness from two different perspectives: short-term and long-term one. As our previous study showed that city attractiveness for Spanish cities follows a superlinear trend, here we want to see if the same law is also applicable to country/state (i.e., composite regions) attractiveness. Finally, we provide one possible explanation for the obtained results.     

滑动平均差检测法的提出及验证

时间序列突变点的检测研究是当前气候变化问题的关键环节,其方法和成果也较多,传统的检测方法因统计量结构不合理、假设条件不符合实际以及受主观因素影响等,结果常常缺乏可信度。本文提出一种新的时间序列突变点的检测方法——滑动平均差检测法,将该方法分别用理想时间序列和实际观测序列进行应用检验,并与现有常用的4种突变检验方法比较,发现滑动平均差法具有：① 结构简单、物理意义明确;② 检测突变点更精确;③ 能同时检测出所有突变点的突变位置和其突变强度3个明显的优势。综合利用滑动平均差检测法和传统的4种方法,对黄河流域几个重点水文控制站实测输沙量资料进行突变分析,结果表明：黄河上游输沙量在1986年发生突变,黄河中游输沙量在1979年和1996年发生突变,华县站和潼关站输沙量在1979年、1996年和2003年发生突变,造成输沙量突变的主要因素为水利工程建设和大规模水土保持措施等人类活动。     

Multi-level method for discovery of regional co-location patterns

Regional co-location patterns represent subsets of feature types that are frequently located together in sub-regions in a study area. These sub-regions are unknown a priori, and instances of these co-location patterns are usually unevenly distributed across a study area. Regional co-location patterns remain challenging to discover. This study developed a multi-level method to identify regional co-location patterns in two steps. First, global co-location patterns were detected, and other non-prevalent co-location patterns were identified as candidates for regional co-location patterns. Second, an adaptive spatial clustering method was applied to detect the sub-regions where regional co-location patterns are prevalent. To improve computational efficiency, an overlap method was developed to deduce the sub-regions of (k + 1)-size co-location patterns from the sub-regions of k-size co-location patterns. Experiments based on both synthetic and ecological data sets showed that the proposed method is effective in the detection of regional co-location patterns.     

Integration of nighttime light remote sensing images and taxi GPS tracking data for population surface enhancement

The population distribution grid at fine scales better reflects the distribution of residents and plays an important role in investigating urban systems. The recent years have witnessed a growing trend of applying the nighttime light data to the estimation of population at micro levels. However, using the nighttime light data alone to estimate population may cause the overestimation problem due to excessively high light radiance in specific types of areas such as commercial zones and transportation hubs. In dealing with this issue, this study used taxi trajectory data that delineate people’s movements, and explored the utility of integrating the nighttime light and taxi trajectory data in the estimation of population in Shanghai at the spatial resolution of 500 m. First, the initial population distribution grid was generated based on the NPP-VIIRS nighttime light data. Then, a calibration grid was created with taxi trajectory data, whereby the initial population grid was optimized. The accuracy of the resultant population grid was assessed by comparing it with the refined survey data. The result indicates that the final population distribution grid performed better than the initial population grid, which reflects the effectiveness of the proposed calibration process.     

沙漠地质记录和人类活动遗迹数据汇交规范化

数据汇交是实现数据共享的前提,是实现科学数据的持续累积、科学整合和有效管理可持续发展的重要基础.分析了沙漠地质记录和人类活动遗迹数据汇交规范化存在的问题,强调了制定沙漠地质记录和人类活动遗迹数据汇交规范的必要性,根据沙漠地质记录和人类活动遗迹资料的数据特性,对数据分类并建立不同专题数据库,因地制宜采纳国际和国内现行的规...     

A data model for moving regions of fixed shape in databases

Moving object databases are designed to store and process spatial and temporal object data. An especially useful moving object type is a moving region, which consists of one or more moving polygons suitable for modeling the spread of forest fires, the movement of clouds, spread of diseases and many other real-world phenomena. Previous implementations usually allow a changing shape of the region during the movement; however, the necessary restrictions on this model result in an inaccurate interpolation of rotating objects. In this paper, we present an alternative approach for moving and rotating regions of fixed shape, called Fixed Moving Regions, which provide a significantly better model for a wide range of applications like modeling the movement of oil tankers, icebergs and other rigid structures. Furthermore, we describe and implement several useful operations on this new object type to enable a database system to solve many real-world problems, as for example collision tests, projections and intersections, much more accurate than with other models. Based on this research, we also implemented a library for easy integration into moving objects database systems, as for example the DBMS Secondo (1) (2) developed at the FernUniversität in Hagen.     

A regionalization method for clustering and partitioning based on trajectories from NLP perspective

ABSTRACT

Regionalization attempts to group units into a few subsets to partition the entire area. The results represent the underlying spatial structure and facilitate decision-making. Massive amounts of trajectories produced in the urban space provide a new opportunity for regionalization from human mobility. This paper proposes and applies a novel regionalization method to cluster similar areal units and visualize the spatial structure by considering all trajectories in an area into a word embedding model. In this model, nodes in a trajectory are regarded as words in a sentence, and nodes can be clustered in the feature space. The result depicts the underlying socio-economic structure at multiple spatial scales. To our knowledge, this is the first regionalization method from trajectories with natural language processing technology. A case study of mobile phone trajectory data in Beijing is used to validate our method, and then we evaluate its performance by predicting the next location of an individual’s trajectory. The case study indicates that the method is fast, flexible and scalable to large trajectory datasets, and moreover, represents the structure of trajectory more effectively.     

基于腾讯位置数据的南昌市活动空间凝聚结构与区划研究

近年来地理信息大数据运用在人文地理学领域成为了新热潮。本文借助腾讯位置数据,得到了工作日、休息日、节假日三种类型的数据,以南昌市为例,从居民实际活动的视角出发,首先对研究区域的活动空间时序变化特征进行研究,在此基础上,通过核密度分析法总结了研究区域的活动空间凝聚结构,最后利用热度山顶点提取和泰森多边形等方法对具体的城市活动空间功能区进行划分与分析。研究发现：①工作日的高频活动区域面积明显高于休息日和节假日,分类区间的热力值越大像元数量越小。②研究区域城市活动空间的凝聚结构有四种,分别为“单核结构”、“双核结构”、“三核结构”、“集聚结构”,每种结构都有独特的形态特征以及代表性的典型区域。③研究区域可划分为六种活动空间功能区划：综合活动区、居住活动区、学习活动区、休闲娱乐区、交通枢纽区、就业活动区,不同的活动模式对应着各自的活动频度变化规律,且运用叠加分析法识别出六种功能模式的核心区和边缘区。④研究区域的活动功能区分布不均,大部分的活动类型为居住活动区和学习活动区,但主城区的居民活动类型更加丰富,主城区的集聚程度高于远城区,且活动功能区与空间凝聚结构具有一定联系。⑤根据大数据挖掘发现的南昌市活动空间凝聚结构分布特征、活动功能区的分布特征,结合南昌市城市发展规划,对南昌市目前的活动空间结构进行评价,从而对昌南、昌北、城东的发展提出相应建议。     

Deferred decentralized movement pattern mining for geosensor networks

This article presents an algorithm for decentralized (in-network) data mining of the movement pattern flock among mobile geosensor nodes. The algorithm DDIG (Deferred Decentralized Information Grazing) allows roaming sensor nodes to ‘graze’ over time more information than they could access through their spatially limited perception range alone. The algorithm requires an intrinsic temporal deferral for pattern mining, as sensor nodes must be enabled to collect, memorize, exchange, and integrate their own and their neighbors' most current movement history before reasoning about patterns. A first set of experiments with trajectories of simulated agents showed that the algorithm accuracy increases with growing deferral. A second set of experiments with trajectories of actual tracked livestock reveals some of the shortcomings of the conceptual flocking model underlying DDIG in the context of a smart farming application. Finally, the experiments underline the general conclusion that decentralization in spatial computing can result in imperfect, yet useful knowledge.     

风沙活动强度3种估算指标对比及适用性分析

风沙活动强度是风沙地区交通、能源基地等基础设施建设和运营中科学开展风沙工程防护设计须考虑的重要内容。但在实际工作中尚缺乏操作性强、适用性广的风沙活动强度估算指标。本研究选取风蚀气候侵蚀力、沙丘活化指数和输沙势3种常用指标,基于中国北方风沙区多个具体工程案例,对比分析了3种指标的适宜性及存在问题。结果表明：（1）由于没有考虑工程周边沙源丰富程度的相关影响因素（如植被、戈壁砾石的覆盖度）,3种指标的估算结果均难以准确客观地反映具体工程的实际风沙问题。（2）采用高精度风速风向数据计算的输沙势更能表达干旱地区的风沙活动特征,但在降水较多的区域偏差较大。（3）铁路等线性工程两侧风沙活动强度可能存在差异,相同防沙措施的防护效益存在明显差别,具体工程风沙活动强度的估算应明确其方向性差异。在指导防护体系建设时,需尽可能考虑降水、气温、风速、风向等多种因子,同时结合沙源、地表覆盖度、工程走向等实际情况来分析风沙活动强度差异。研究结果有助于提出一种准确度高、适用性广、可操作性强的风沙活动强度估算指标,为有效开展防沙工程设计提供指导。