Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records

Understanding the spatiotemporal dynamics of urban population is crucial for addressing a wide range of urban planning and management issues. Aggregated geospatial big data have been widely used to quantitatively estimate population distribution at fine spatial scales over a given time period. However, it is still a challenge to estimate population density at a fine temporal resolution over a large geographical space, mainly due to the temporal asynchrony of population movement and the challenges to acquiring a complete individual movement record. In this article, we propose a method to estimate hourly population density by examining the time‐series individual trajectories, which were reconstructed from call detail records using BP neural networks. We first used BP neural networks to predict the positions of mobile phone users at an hourly interval and then estimated the hourly population density using log‐linear regression at the cell tower level. The estimated population density is linearly correlated with population census data at the sub‐district level. Trajectory clustering results show five distinct diurnal dynamic patterns of population movement in the study area, revealing spatially explicit characteristics of the diurnal commuting flows, though the driving forces of the flows need further investigation.     

利用出租车轨迹数据估计城市道路拥堵状况

交通拥堵是当代各大城市普遍面临的问题,如何通过各种技术手段发现城市交通的易拥堵路段并予以改善是城市交通相关部门以及学者关心的一个问题。通过各种GPS设备产生的历史轨迹数据对城市的研究逐渐受到重视,且取得一定的进展。文中总结运行车辆的4种通行状态:正常行驶、停靠/停泊、信号灯等待以及拥堵,分析这4种状态下运行车辆的速度特征,定义轨迹段平均速度和轨迹段速度方差两个数字特征用来描述运行车辆轨迹段的速度特征以及描述路段拥堵程度的拥堵指数,提出一种基于轨迹分段的拥堵检测的可视化方法,通过实验验证发现其可以较好地估计城市交通拥堵状况。     

An analysis of movement patterns between zones using taxi GPS data

The discovery of zones and people's movement patterns supports a better understanding of modern cities and enables a more comprehensive strategy for urban planning. This article proposes a modified method based on previous research to simultaneously discover people's zones and movement patterns, called movement patterns between functional zones (MPFZ). The method attempts to take full advantage of taxi GPS data to identify MPFZs by merging the movement traces satisfying the merging conditions. Considering movement directions, movement numbers and the adjacent constraints that consist of spatial relationship and attribute features, the merging conditions limit the movement traces to be merged. The new MPFZs are discovered by an iteration process and are measured by the following three evaluation indices: v‐value, a‐value and c‐value, which represent coverage, accuracy and their trade‐off. Using a real‐world taxi dataset of Beijing, 24 new MPFZs are discovered, which have higher v‐, a‐ and c‐values than the unmerged MPFZs. The results of the real‐world dataset experiment show that the proposed approach is effective and efficient. The proposed method can also be applied to other types of transportation data and regions by adjusting the dataset utilized and controlling the iteration process.     

出租车轨迹数据挖掘进展

大数据、物联网与精密定位技术的发展推动了城市感知的进步。随着社会活动的与日俱增,出租车轨迹数据不仅记录了出租车的行车轨迹,还蕴藏着道路交通状态、城市居民出行规律、城市结构及其他社会问题。通过各种数据分析与挖掘手段对出租车轨迹数据进行深入探究,对于智能交通、城市规划等有着重要意义。本文综述了近十年国内外基于出租车轨迹大数据的相关研究,按照空间统计方法、时间序列方法、图论与网络方法及机器学习方法等4类,详细阐述各类方法的研究现状。随后,本文分析了现有研究的应用领域、热点主题和发展趋势。最后,本文指出了出租车轨迹数据挖掘研究领域面临的挑战和未来研究方向。     

数字城市中城市空间数据基础设施建设构想

作为数字化区域的重要形式,"数字城市"建设日益受到重视.城市空间数据基础设施是数字城市基础层的核心.在阐述数字城市与城市空间数据基础设施关系基础上,着重论述了城市空间数据基础设施的建设构想,包括其建设标准和规范、城市空间数据信息库建设和数据共享发布.     

Mapping urban growth of the capital city of Honduras from Landsat data using the impervious surface fraction algorithm

This study developed an impervious surface fraction algorithm (ISFA) for automatic mapping of urban areas from Landsat data. We processed the data for 2001 and 2014 to trace the urbanization of Tegucigalpa, the capital city of Honduras, using a four-step procedure: (1) data pre-processing to perform image reflectance normalization, (2) quantification of impervious surface area (ISA) using ISFA, (3) accuracy assessment of mapping results and (4) change analysis of urban growth. The mapping results compared with the ground reference data confirmed the validity of ISFA for automatic delineation of ISA in the study region. The overall accuracy and Kappa coefficient achieved for 2001 were 92.8% and 0.86, while the values for 2014 were 91.8% and 0.84, respectively. The results of change detection between the classification maps indicated that ISA increased approximately 1956.7 ha from 2001 to 2014, mainly attributing to the increase of the city’s population.     

城市规划空间数据的多尺度特征及其关键问题

分析城市规划空间数据的主要特点,指出城市规划空间数据多尺度可视化表达的关键在于建立一个多分辨率的空间以及相应的空间数据模型,其尺度效应及其尺度转换规律的研究必须考虑城市规划空间数据属性的语义层次,通过多尺度处理,新的空间数据集在一定条件下的产生应该是双向的。     

Mining spatial associations between daily activities and health using EMA–GPS data

The geographical explicit ecological momentary assessment (GEMA) data collection platform provides extremely rich geospatial datasets and is very promising to gain behavior insights linking mobility, activities, and health. However, the task of analyzing these large datasets effectively is not straightforward, because they often involve a large multivariable dimension and rich qualitative data formats. Responding to the call for innovative analytic approaches in GIScience, this article advocates the use of spatial association rule mining (SARM) to extract frequent associations among daily activities, daily mobility, and health, including both physical health (e.g. pain) and mental health (e.g. happiness). This inductive mining approach works robustly with large datasets and is suitable for both qualitative and quantitative studies. A novel visualization technique to analyze the mined rules is also developed and presented.     

Mapping GPS positional errors using spatial linear mixed models

Nowadays, GPS receivers are very reliable because of their good accuracy and precision; however, uncertainty is also inherent in geospatial data. Quality of GPS measurements can be influenced by atmospheric disturbances, multipathing, synchronization of clocks, satellite geometry, geographical features of the observed region, low broadcasting coverage, inadequate transmitting formats, or human or instrumental unknown errors. Assuming that the scenario and technical conditions that can influence the quality of GPS measurements are optimal, that functional and stochastic models that process the signals to a geodetic measurement are correct, and that all the GPS observables are taken in the same conditions, it is still possible to estimate the positional errors as the difference between the real coordinates and those measured by the GPS. In this paper, three spatial linear mixed models, one for each axis, are used for modelling real-time kinematic GPS accuracy and precision, of a multiple-reference-station network in dual-frequency with carrier phase measurements. Along the paper, the proposed models provide an estimate of the “accuracy” in terms of bias defined as the difference between real coordinates and measured coordinates after being processed and “precision” through the standard errors of the estimated differences. This is done using ten different transmitting formats. Mapping and quantifying these differences can be interesting for users and GPS professionals. The performance of these models is illustrated by mapping positional error estimates within the whole region of Navarre, Spain. Sampled data have been taken in 54 out of the 211 geodetic vertex points of this region. Maps show interesting error patterns depending on transmitting formats, the different axes, and the geographical characteristics of the region. Higher differences are found in regions with bad broadcasting coverage, due to the presence of mountains and high degree of humidity.     

丽水市城市空间基础地理数据库的建设与应用

城市基础数据库是"数字城市"建设的重要组成部分。本文介绍了丽水市城市空间基础地理数据库的建设和应用情况,论述了空间基础地理数据库中数据的更新过程和管理功能。     

Exploiting spectral and spatial information in hyperspectral urban data with high resolution

Very high resolution hyperspectral data should be very useful to provide detailed maps of urban land cover. In order to provide such maps, both accurate and precise classification tools need, however, to be developed. In this letter, new methods for classification of hyperspectral remote sensing data are investigated, with the primary focus on multiple classifications and spatial analysis to improve mapping accuracy in urban areas. In particular, we compare spatial reclassification and mathematical morphology approaches. We show results for classification of DAIS data over the town of Pavia, in northern Italy. Classification maps of two test areas are given, and the overall and individual class accuracies are analyzed with respect to the parameters of the proposed classification procedures.     

Path-finding through flexible hierarchical road networks: An experiential approach using taxi trajectory data

Optimal paths computed by conventional path-planning algorithms are usually not “optimal” since realistic traffic information and local road network characteristics are not considered. We present a new experiential approach that computes optimal paths based on the experience of taxi drivers by mining a huge number of floating car trajectories. The approach consists of three steps. First, routes are recovered from original taxi trajectories. Second, an experiential road hierarchy is constructed using travel frequency and speed information for road segments. Third, experiential optimal paths are planned based on the experiential road hierarchy. Compared with conventional path-planning methods, the proposed method provides better experiential optimal path identification. Experiments demonstrate that the travel time is less for these experiential paths than for paths planned by conventional methods. Results obtained for a case study in the city of Wuhan, China, demonstrate that experiential optimal paths can be flexibly obtained in different time intervals, particularly during peak hours.     

Mapping collective human activity in an urban environment based on mobile phone data

Identifying and characterizing variations of human activity – specifically changes in intensity and similarity – in urban environments provide insights into the social component of those eminently complex systems. Using large volumes of user-generated mobile phone data, we derive mobile communication profiles that we use as a proxy for the collective human activity. In this article, geocomputational methods and geovisual analytics such as self-organizing maps (SOM) are used to explore the variations of these profiles, and its implications for collective human activity. We evaluate the merits of SOM as a cross-dimensional clustering technique and derived temporal trajectories of variations within the mobile communication profiles. The trajectories’ characteristics such as length are discussed, suggesting spatial variations in intensity and similarity in collective human activity. Trajectories are linked back to the geographic space to map the spatial and temporal variation of trajectory characteristics. Different trajectory lengths suggest that mobile phone activity is correlated with the spatial configuration of the city, and so at different times of the day. Our approach contributes to the understanding of the space-time social dynamics within urban environments.     

利用浮动车GPS轨迹识别与提取城市道路交叉口

道路交叉口作为道路交汇的枢纽,是路网的重要组成部分,也是最重要的基础地理信息数据之一.浮动车GPS数据具有易获取、低成本和数据量大等优点,但工作同时伴随不少噪点.为了降低噪点对交叉口提取过程的影响,提高计算效率,本文运用KNN算法建立空间索引;计算向量夹角,判定道路出入口,粗筛取交叉口附近点;分别采用K-means算法...     

Mapping burns and natural reforestation using thematic Mapper data

Remote sensing techniques are specially suitable to detect and to map areas affected by forest fires. In this work, Landsat 5 Thematic Mapper (TM) data has been used to study a number of forest fires that occurred in the province of Valencia (Spain) and to monitor the vegetation regeneration over burnt areas.

A reference area (non‐burnt forest) was established to assess the change produced by fire. The radiance in the thermal band (10.4–12.5 μm) and the normalized difference in reflectance between near 1R (0.76–0.90 μm) and middle IR (2.08–2.35 μm) were the most suitable parameters to map burnt areas. This index can also be used for monitoring vegetation regeneration in burnt areas. About a month after the fire, the burns show temperatures of 5–6 °C higher than those found in the reference area, and the vegetation index shows negative values whereas the reference area values remain positive. The differences between the burns and the reference area for the vegetation index decrease with time as vegetation regenerates.     

基于光谱和空域信息的城区变化检测方法研究

目前的变化检测研究主要集中在利用中、小比例尺遥感图像进行自然环境等方面的变化检测,如草场的季节性变化、灾害检测、植被分布变化、土地使用规划等。然而随着城市的快速发展,为了满足城区管理规划中对道路、房屋等变化细节进行分析的需求,并由于高分辨率卫星诸如Ikonos,Quickbird等的出现,我们有必要并且有可能开发出一套实用、有效的、可靠的城区自动变化检测系统。针对城市区域的复杂性及其高分辨率卫星影像的配准误差问题,本文提出一种通过模糊逻辑结合光谱特征和空域特征的城区变化检测方法,以期望减小图像整体及局部配准误差对变化检测精度的影响。     

Mapping of hydrogeomorphological features in varaha river basin using IRS data

Hydrogeomorphological mapping in Varaha River Basin (VRB) was carried out to develop relationship between groundwater condition and geomophology of the area. The VRB is located in the north coastal region of Andhra Pradesh is characterised by variability in precipitation, temperature, vegetation, infiltration and run-off. Realising the significance of remote sensing in natural resource management and development, IRS 1A data was used in the study. It is inferred that various hydrogeomorphological units identified in the study area, are the outcome of different geomorphic processes that have been operating in the area and reveal which close relationship between groundwater condition and geology and geomorphol-ogy of the area. Areas covered by buried channels have shallow aquifers of good quality wa-ter with excellent yield. Lineaments and fractures may prove to be potential zones for ground-water development.     

Expanding the SDI environment: comparing current spatial data infrastructure with emerging indoor location-based services

The authors compare key elements of the emerging field of Indoor Location-Based Services (Indoor LBS) to those currently found in spatial data infrastructure (SDI) programs. After a brief review of SDIs and Location-Based Services, the corresponding drivers, characteristics and emerging issues within the field of Indoor LBS are introduced and discussed. A comparative framework relates the two in terms of the criteria ‘People’, ‘Data', ‘Technologies', ‘Standards' and ‘Policies/Institutional Arrangements'. After highlighting key similarities and differences, the authors suggested three areas – definition of common framework datasets in Indoor LBS, more effective use of volunteered geographic information by SDI programs and development of appropriate privacy policies by both communities – that may benefit from sharing ‘lessons learned'.     

Studies on urban heat islands using envisat AATSR data

Urbanization has significant effects on local weather and climate and among these effects one of the most familiar is the urban heat island, for which the temperatures of the central urban locations are several degrees higher than those of nearby rural areas of similar elevation. Satellite data provides important inputs for estimating regional surface albedo and evapotranspiration required in the studies related to surface energy balance. Present study describes the analysis of day and night ENVISAT-AATSR satellite data for Urban heat island and surface thermal inertia. Field campaigns have been conducted in synchronous with the satellite data over pass for validating the surface temperature estimated from AATSR data. Satellite derived surface temperature values are within ±1° C from ground measured values. Heat island formations in urban regions of Hyderabad and environs can be clearly seen in the night time data with core urban regions showing high temperatures. Apparent thermal inertia derived from AATSR day and night data sets have shown typical variations over urban regions.     

基于MODIS数据的长株潭地区城市热岛时空分析

基于MODIS影像,采用分裂窗算法反演的地表温度对长株潭地区城市热岛空间分布与季相变化特征、影响因子进行定量研究。结果表明,长株潭地区春季和夏季存在明显的城市热岛效应,而冬季和秋季城市热岛并不明显;地表覆盖类型对城市热岛的影响十分明显,长株潭地区春、夏、秋季植被绿地状况与城市热岛呈现明显负相关分布,其中以夏季最为明显,夏季地表温度与NDVI相关系数的平方R2达到0.8193,即植被覆盖对城市地表温度的影响显著。因此,城市植被的分布与季节变化影响着城市热岛的强度与时空分布,揭示出植被绿地对降低城市热岛效应具有重要的作用,大范围的绿地建设能有效降低城市热岛效应。