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.     

Mapping the spatial disparities in urban health care services using taxi trajectories data

The understanding of spatial inequality in health care services is critical for reasonable policy‐making and management. In this study, we present a novel approach to analyze the demand–supply of health care services using taxi data. Taxi data provide observations of individual travel activities, and hence can be used to characterize the actual demand–supply of health care services. We apply the proposed approach in Guangzhou, China to carry out a case study. The results show the spatial disparities in health care service access. About 21.05% of the total population has high hospital accessibility, while the remaining 78.95% has relatively low hospital accessibility (i.e., roughly an “80/20” distribution). It is found that 6.29% of the population lives in high‐density suburban communities but has relatively low hospital accessibility. Most of the hospitals serve a population that is compatible with their capacity. One hospital is found to have a small capacity but to serve a large population, while two hospitals have relatively high capacities but serve small populations. These findings can help improve our understanding of spatial inequalities in public service provision, and may also provide useful information to address the health care problems of an aging population in contemporary, rapidly urbanizing China.     

How friends share urban space: An exploratory spatiotemporal analysis using mobile phone data

This study proposes a framework to investigate the roles of urban spaces in connecting social contacts (i.e., “friends”). The framework is applied to a Call Detail Record (CDR) dataset collected in Singapore. First, a comparative analysis is performed to understand how friends share urban space differently from random people. Then, we derive two metrics to quantify the “bonding” and “bridging” capabilities of places in the city. The two metrics reflect the potential of a place in connecting friends and random people (e.g., chance encounters), respectively. Finally, we examine the temporal signature of the places’ bonding capabilities, and associate the results with various types of Points of Interest (POIs). We find that: (1) friends are more likely to share urban space than random people, and they also share more locations; (2) a place could play different roles in connecting friends vs. random people, and the relationship (between bonding and bridging) varies depending on the time and type of a day (weekdays vs. weekends); (3) the temporal signature of bonding capability is strongly related to the semantics of a place; (4) certain POI types (e.g., shopping malls) tend to have a much higher impact on bonding capability than others (e.g., sports centers).     

Measuring the vibrancy of urban neighborhoods using mobile phone data with an improved PageRank algorithm

A neighborhood is a shared space for spatial interaction. The vibrancy of a neighborhood represents a synergy between the people, activities, and values in a place, which increases community vitality and spurs economic opportunity. It can be investigated both qualitatively and quantitatively. However, there are technical challenges involved in accurately charting vibrancy. With the recent advances in communication technology and the prevalence of location‐aware devices such as mobile phones, individual trajectories can be collected and analyzed on a large scale. In previous research, the weights of the vibrancies corresponding to different trajectories were not differentiated. In this study, an improved PageRank algorithm using a weighted bipartite graph is proposed to measure the vibrancy of an urban neighborhood from a different perspective, which highlights the differences between vibrancies arising from different types of citizens. This method connects the land much more closely with human activities and provides a new perspective on, and guidance for, urban resource allocation and urban planning.     

Visualizing population mobility from spatiotemporally aggregated mobile phone data via a 3D gradient approach

Population mobility patterns are important for understanding a city's rhythms. With the widespread use of mobile phones, population-based trajectories can be utilized to explore such mobility patterns. However, to protect personal privacy, mobile phone data must be de-identified by data aggregation within each spatiotemporal unit. In data acquired from mobile phones, population mobility features are still implicit in the spatiotemporally aggregated grid data. In this study, based on image-processing techniques, a two-step 3D gradient method is adopted to extract the movement features. The first step is to estimate the initial movement pattern in each spatiotemporal grid, and then to estimate the accumulated movement pattern within a time period around a geographical grid. This method can be applied adaptively to multi-scale spatiotemporal grid data. Using geospatial visualization methods, estimated motion characteristics such as velocity and flow direction can be made intuitive and integrated with other multiscale geospatial data. Furthermore, the correlation between the population mobility pattern and demographic characteristics, such as gender and age groups, can be analyzed with intuitive visualization. The implication of the visualization results can be used for understanding the human dynamics in a city, which can be beneficial for urban planning, transportation management, and socioeconomic development.     

Mapping 3D visibility in an urban street environment from mobile LiDAR point clouds

ABSTRACT

Visibility determination is a key requirement in a wide range of national and urban applications, such as national security, landscape management, and urban design. Mobile LiDAR point clouds can depict the urban built environment with a high level of details and accuracy. However, few three-dimensional visibility approaches have been developed for the street-level point-cloud data. Accordingly, an approach based on mobile LiDAR point clouds has been developed to map the three-dimensional visibility at the street level. The method consists of five steps: voxelization of point-cloud data, construction of lines-of-sight, construction of sectors of sight, construction of three-dimensional visible space, and calculation of volume index. The proposed approach is able to automatically measure the volume of visible space and openness at any viewpoint along a street. This approach has been applied to three study areas. The results indicated that the proposed approach enables accurate simulation of visible space as well as high-resolution (1 m × 1 m) mapping of the visible volume index. The proposed approach can make a contribution to the improvement of urban planning and design processes that aim at developing more sustainable built environments.     

Identifying stops from mobile phone location data by introducing uncertain segments

Identifying stops is a primary step in acquiring activity‐related information from mobile phone location data to understand the activity patterns of individuals. However, signal jumps in mobile phone location data may create “fake moves,” which will generate fake activity patterns of “stops‐and‐moves.” These “fake moves” share similar spatiotemporal features with real short‐distance moves, and the stops and moves of trajectories (SMoT), which is the most extensively used stop identification model, often fails to distinguish them when the dataset has coarse temporal resolution. This study proposes the stops, moves, and uncertainties of trajectories (SMUoT) model to address this issue by introducing uncertain segment analysis to distinguish “fake moves” and real short‐distance moves. A real mobile phone location dataset collected in Shenzhen, China is used to evaluate the performance of SMUoT. We find that SMUoT improves the performance (i.e., 15 and 19% increase in accuracy and recall rate for a one‐hour temporal resolution dataset, respectively) of stop identification and exhibits high robustness to parameter settings. With a better reliability of “stops‐and‐moves” pattern identification, the proposed SMUoT can benefit various individual activity‐related research based on mobile phone location data for many fields, such as urban planning, traffic analysis, and emergency management.     

Geographical impacts on social networks from perspectives of space and place: an empirical study using mobile phone data

Space and place are two fundamental concepts in geography. Geographical factors have long been known as drivers of many aspects of people’s social networks. But whether and how space and place affect social networks differently are still unclear. The widespread use of location-aware devices provides a novel source for distinguishing the mechanisms of their impacts on social networks. Using mobile phone data, this paper explores the effects of space and place on social networks. From the perspective of space, we confirm the distance decay effect in social networks, based on a comparison between synthetic social ties generated by a null model and actual social ties derived from real-world data. From the perspective of place, we introduce several measures to evaluate interactions between individuals and inspect the trio relationship including distance, spatio-temporal co-occurrence, and social ties. We found that people’s interaction is a more important factor than spatial proximity, indicating that the spatial factor has a stronger impact on social networks in place compared to that in space. Furthermore, we verify the hypothesis that interactions play an important role in strengthening friendships.     

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...     

Estimation of hourly and daily evapotranspiration and soil moisture using downscaled LST over various urban surfaces

Surface moisture is important to link land surface temperature (LST) to people’s thermal comfort. In urban areas, the surface roughness from buildings and urban trees impacts wind speed, and consequently surface moisture. To find the role of surface roughness in surface moisture estimation, we developed methods to estimate daily and hourly evapotranspiration (ET) and soil moisture, based on a case study of Indianapolis, Indiana, USA. In order to capture the spatial and temporal variations of LST, hourly and daily LST was produced by downscaling techniques. Given the heterogeneity in urban areas, fractions of vegetation, soil, and impervious surfaces were calculated. To describe the urban morphology, surface roughness parameters were calculated from digital elevation model (DEM), digital surface model (DSM), and Terrestrial Light Detection and Ranging (LiDAR). Two source energy balance (TSEB) model was employed to generate ET, and the temperature vegetation index (TVX) method was used to calculate soil moisture. Stable hourly soil moisture fluctuated from 15% to 20%, and daily soil moisture increased due to precipitation and decreased due to seasonal temperature change. ET over soil, vegetation, and impervious surface in the urban areas yielded different patterns in response to precipitation. The surface roughness from high-rise has bigger influence on ET in central urban areas.     

利用手机信令数据刻画不同人物画像

本文基于微软亚洲研究院Geolife项目北京志愿者2007—2012年长时间尺度的手机信令数据,以个体为单元开展了出行类型和人物画像研究,提出了一种基于高簇聚类对用户轨迹类型进行划分,然后结合出行规律,综合考虑职业类型、年龄、爱好属性特征的人物画像刻画的方法.研究主要结论为:①本文划分了包括两点一线固定型、两点一线变化...     

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.     

一种基于地理信息的手机用户定位方法北大核心CSCD

基于手机信令数据的用户轨迹行为分析已广泛应用于交通监测、城市管理、人口分析等多个业务领域。针对手机基站定位与用户实际位置存在偏差且驻留轨迹缺失语义信息的问题,本文提出了一种基于地理信息的手机信令数据用户定位方法。该方法首先构建面向轨迹分析的地理实体数据采集规范;然后对手机信令数据进行聚类,建立地理实体与基站的权重映射关系;最后使用时空推理及对轨迹的深度学习技术,将用户有效驻留轨迹点拟合至实际的地理实体,实现用户定位。验证结果表明,该方法提升了用户定位的准确度,为后续业务场景的应用提供了可靠的数据支撑。     

Comparative geometric and radiometric evaluation of mobile phone and still video cameras

This paper examines the potential of mobile phones to be used as front-end sensors for photogrammetric procedures and applications. For this purpose, two mobile phone cameras (Sony Ericsson K750i and Nokia N93) were calibrated over an indoor 3D testfield, using a self-calibrating bundle adjustment. Geometric accuracy tests were carried out in order to evaluate their metric performances and to compare the results with respect to two off-the-shelf digital still video cameras (Sony DSC W100 and Sony DSC F828). The geometric accuracy evaluation comprised an absolute accuracy test, JPEG test and temporal stability test. The radiometric capabilities of all cameras (except that the DSC W100 was replaced with a DSC T100 camera) were also evaluated and compared by carrying out modulation transfer function (MTF) analysis, image noise analysis and an operating range test. Substantial systematic errors were diagnosed in some systems. However, with proper calibration it is believed that these devices can be used for many photogrammetric tasks.     

Mapping and monitoring of urban landuse of Hisar Town,Haryana using remote sensing techniques

Aerial photographs for the year 1965 and 1975 and Landsat TM (FCC) 1986 data on 1:50,000 scale were used to map and monitor the pattern of growth and development of Hisar Town during the last 20 years. The different landuse categories identified are residential, commercial, industrial, recreational, vacant lands etc. The original shape of the town was nucleated one, but presently it is star-shaped, which is due to extension of the urban centre along the radiating roads. It has mainly elongated itself along the Delhi and Rajgarh roads. The presence of Government Livestock Farm (GLF), Equine Breeding Farm and HAU Farm towards North-west of the town has completely checked its growth on these sides. The total residential-cum-commercial area has nearly doubled during 1965–1975 and trebled by 1986. The change in net area under different types of urban land-use categories, described above has also been calculated. Degraded scrub lands and sandy wasteland on the fringes of the town have been identified where further development can be planned to avoid encroachment on good agricultural lands. Recommendations have been given for future urban planning of the town.     

Analysis of population dynamics using satellite remote sensing and US census data

The population dynamics from 1991 to 2006 for the seven-county Twin Cities Metropolitan Area (TCMA), Minnesota, USA, was analysed in this study. Per cent impervious surface areas (%ISA) for 1991, 1999 and 2006 were derived from Landsat Thematic Mapper (TM) images and were modified using two different masking methods. The modified %ISA images of 1991 and 1999 were correlated with 1990 and 2000 census block group data of the ‘two highly developed counties’, ‘five suburban counties’ and ‘all seven counties.’ Populations of both years were then modelled, assessed and compared. Next, the statistical models based on the 1999 %ISA and 2000 census data were applied to the 2006 residential %ISA image to estimate the 2006 population. These 2006 estimates were compared with census county-level population projections for 2006. In comparison to Method A, which uses ‘adjusted %ISA images’ by masking out highway centrelines and areas that have greater than 75% imperviousness, Method B based on ‘pure residential %ISA image’ has higher coefficient of determination (R ²) and much lower, consistent mean absolute relative errors (MARE). For both methods, the strongest R ² and lowest MARE values between modelled population density and true density were found in the five-county model, followed by the seven-county model. The two-county model ranks last in terms of model performance for both years. In general, populations for the two highly developed counties were underestimated whereas the opposite was true for the five suburban counties. Population was most accurately estimated based on data from counties with the same or similar characteristics. By comparing the 1990/1991 and 1999/2000 models, we also found that the rate of population density per unit of impervious surface declined from 1991 to 1999. High accuracy was achieved when applying the 1999/2000 model to predict the 2006 population, suggesting that the relationship between per cent imperviousness and population density were relatively stable between 1999 and 2006.     

Characterizing European urban settlements from population data: a cartographic approach

ABSTRACT

The cartographic identification and characterization of urban settlements is problematic, particularly in varied areas or in large geographical extensions. This is due to the divergence between morphological area structures and data attribution, which is generally available at the level of administrative units. Most existing experiences focus on small regions or use indirect data, from which only indirect information can be derived. This paper proposes an identification of urban settlements in the European Union space, which combines urban population and shape through geographic information system (GIS) techniques. For that purpose, 1 km² cells with associated population data are used. A procedure is developed establishing three different types of urban settlements, according to population and population density values: high-density urban clusters, small and medium-sized towns, and very small towns. A validation of this procedure is performed using direct survey from local experts in 10 selected study areas. The final results show that 78,307 urban settlements can be identified: 88.17% of them are classified as “very small towns,” 10.75% as “small and medium-sized towns,” and 1.08% as high-density urban clusters. This exercise generates new information for the European Union and surrounding countries, and yields the basis for further research. All GIS operations are performed using vector layers, which is not usual in large-area regional studies.     

扩展卡尔曼滤波的安卓手机定位算法研究

随着手机定位的应用越来越多,目前市场中许多APP(Application)都会用到定位功能.但多数APP使用传统的定位算法,不能满足人们实时获取高精度地理位置信息的需求.现阶段对于手机的全球定位系统(GPS)芯片原始数据定位方法的研究较少,因此本文主要对利用手机GPS原始数据定位的可行性及定位算法进行了研究.利用Android 7.0系统提供的应用程序接口获取GPS芯片的原始数据参数,根据手机实用场景的速度特征,分别设计并实现了针对于静态场景的静态卡尔曼滤波和针对低速场景的动态卡尔曼滤波定位算法.通过静态实验以及电动车实验和步行实验的结果表明:与传统的定位算法相比,本文设计的静态卡尔曼滤波和动态卡尔曼滤波定位算法拥有更好的定位结果,更加接近实际行走路线,证明了利用手机GPS原始数据定位的可行性,同时也证明了设计的卡尔曼滤波算法可以提高定位精度,论文的研究结果为实现静态与动态的高精度手机定位算法提供了理论依据.     

Design and implementation of framework of mobile GIS based on phone terminal for environmental monitoring

This paper proposes a method for constructing an extensive wireless GIS network by utilizing Java cellular phone as GIS terminal for environmental monitoring through dynamic location disaster-emergency notification management of spatial databases. An experimental case study is demonstrated to show its potential in the application field.     

Mapping needs of urban and regional planners some solutions

To tackle problems arising due to rapid urbanisation, the physical planners need up-to-date large scale maps. Since preparation of such maps by conventional methods is time consuming and therefore, not suited to the present situation, introduction of new technology is imperative. Application of Remote Sensing Data Products, mainly Aerial Remote Sensing, is an alternative. Aerial photographs in the form of PHOTO MAPS can be used as map substitutes, as well as basis for extraction of lot of physical data by interpretation to study various physical aspects of urbanisation and expansion. As a step further, computer-aided techniques with appropriate HARDWARE/SOFTWARE Systems like MASMAP, can further simplify and expedite the procedure, especially in the case of spontaneous settlements. The present paper discusses, these problems and in the light of the experience gained at IIRS, suggests some solutions.