Lun Wu

Towards Estimating Urban Population Distributions from Mobile Call Data

Today, large-volume mobile phone call datasets are widely applied to investigate the spatio-temporal characteristics of human urban activity. This paper discusses several fundamental issues in estimating population distributions based on mobile call data. By adopting an individual-based call activity dataset that consists of nearly two million mobile subscribers who made over one hundred million communications over seven consecutive days, we explore the relationships among the Erlang values, the number of calls, and the number of active mobile subscribers. Then, the LandScan population density dataset is introduced to evaluate the process of estimating the population. The empirical findings indicate that: (1) Temporal variation exists in the relation between the Erlang values and the number of calls; (2) The number of calls is linearly proportional to the number of active mobile subscribers; (3) The proportion between the mobile subscribers and the actual total population varies in different areas, thus failing to represent the underlying population. Hence, the call activity reflects “activity intensity” rather than population distribution. The Erlang is a defective indicator of population distribution, whereas the number of calls serves as a better measure. This research provides an explicit clarification with respect to using call activity data for estimating population distribution.

Towards a General Field model and its order in GIS

Geospatial data modelling is dominated by the distinction between continuous‐field and discrete‐object conceptualizations. However, the boundary between them is not always clear, and the field view is more fundamental in some respects than the object view. By viewing a set of objects as an object field and unifying it with conventional field models, a new concept, the General Field (G‐Field) model, is proposed. In this paper, the properties of G‐Field models, including domain, range, and categorization, are discussed. As a summary, a descriptive framework for G‐Field models is proposed. Then, some common geospatial operations in geographic information systems are reconsidered from the G‐Field perspective. The geospatial operations are classified into order‐increasing operations and non‐order‐increasing operations, depending on changes induced in the G‐Fields order. Generally, the order can be viewed as an indicator of the level of information extraction of geospatial data. It is thus possible to integrate the concept of order with a geo‐workflow management system to support geographic semantics.

Quantifying Tourist Behavior Patterns by Travel Motifs and Geo-Tagged Photos from Flickr

With millions of people traveling to unfamiliar cities to spend holidays, travel recommendation becomes necessary to assist tourists in planning their trips more efficiently. Serving as a prerequisite to travel recommender systems, understanding tourist behavior patterns is therefore of great importance. Recently, geo-tagged photos on social media platforms like Flickr have provided a rich data source that captures location histories of tourists and reflects their preferences. This article utilizes geo-tagged photos from Flickr to extract trajectories of tourists and then extends the concept of motifs from topological spaces, to temporal spaces and to semantic spaces, for detecting tourist mobility patterns. By representing trajectories in terms of three distinct types of travel motif and further using them to measure user similarity, typical tourist travel behavior patterns associated with distinct sightseeing tastes/preferences are identified and analyzed for tourism recommendation. Our empirical results confirm that the proposed analytical framework is effective to uncover meaningful tourist behavior patterns.

Delineating intra-urban spatial connectivity patterns by travel-activities: A case study of Beijing, China

Travel activities have been widely applied to quantify spatial interactions between places, regions, and nations. In this paper, we model the spatial connectivities between 652 Traffic Analysis Zones (TAZs) in Beijing by a taxi OD dataset. First, we unveil the gravitational structure of intra-urban spatial connectivities of Beijing. Overall, the inter-TAZ interactions are well governed by the Gravity Model Gij= λpipj/dij, where pi, pj are degrees of TAZ i, j and dij the distance between them, with a goodness-of-fit around 0.8. Second, the network-based analysis well reveals the polycentric form of Beijing. Last, we detect the semantics of inter-TAZ connectivities based on their spatiotemporal patterns. We further find that inter-TAZ connections deviating from the Gravity Model can be well explained by link semantics.

Building the distributed geographic SQL workflow in the Grid environment

Over recent years, massive geospatial information has been produced at a prodigious rate, and is usually geographically distributed across the Internet. Grid computing, as a recent development in the landscape of distributed computing, is deemed as a good solution for distributed geospatial data management and manipulation. Thus, the Grid computing technology can be applied to integrate various distributed resources into a ‘super-computer’ that enables efficient distributed geospatial query processing. In order to realize this vision, an effective mechanism for building the distributed geospatial query workflow in the Grid environment needs to be elaborately designed. The workflow-building technology aims to automatically transform the global geospatial query into an equivalent distributed query process in the Grid. In response to this goal, detailed steps and algorithms for building the distributed geospatial query workflow in the Grid environment are discussed in this article. Moreover, we develop corresponding software tools that enable Grid-based geospatial queries to be run against multiple data resources. Experimental results demonstrate that the proposed methodology is feasible and correct.

Slope unit-based landslide susceptibility zonation

Landslide susceptibility zonation is essential for disaster management and control in mountainous regions. Most landslide susceptibility zonations up to now are pixel-based and somehow are impracticable in landslide hazard management. In this paper, we propose a procedure for slope unit-based landslide susceptibility zonation with a case study of Shenzhen, China. First, the flat terrain is removed by slope classification, and then slope units are derived through watershed segmentation of mean curvature. The impact factors of a slope unit are assigned the mean or majority values of the factors of all pixels within that unit, respectively. The slope units containing the existing landslides are picked as positive training examples. Applying the one-class Support Vector Machine (SVM) under a 20% holdout cross validation strategy, we successfully predict slope units as safe or landslide-prone. Compared with a pixel-based method, the slope unit-based method significantly decreases the computing costs and predicts reasonable landslide-prone areas without obvious growth of omission error.

Inferring spatial interaction patterns from sequential snapshots of spatial distributions

ABSTRACT Spatial interactions underlying consecutive sequential snapshots of spatial distributions, such as the migration flows underlying temporal population snapshots, can reflect the details of spatial evolution processes. In the era of big data, we have access to individual-level data, but the acquisition of high-quality spatial interaction data remains a challenging problem. Most research has been focused on distributions of movable objects or the modelling of spatial interaction patterns, with few attempts to identify hidden spatial interaction patterns from temporal transitions of spatial distributions. In this article, we introduced an approach to infer spatial interaction patterns from sequential snapshots of spatial population distributions by incorporating linear programming and the spatial constraints of human movement. Experiments using synthetic data were conducted using four simple scenarios to explore the characteristics of our method. The proposed method was used to extract interurban flows of migrants during the Chinese Spring Festival in 2016. Our research demonstrated the feasibility of using discrete multi-temporal snapshots of population distributions in space to infer spatial interaction patterns and offered a general analytical framework from snapshot data to spatial interaction patterns.

A method for land surveying sampling optimization strategy

At present, how to select a limited but representative sample dataset from the existing land information database to guide the new round of land survey and assessment sampling is a critical issue for land sampling strategy study. As a case study to determine and analyze the sample capacity and sample spatial location of land survey sampling for the study area, Panyu District in Guangzhou, the paper developed the strategy based on the combination of classical sampling technique and geographical model under a certain confidence level and estimation accuracy requirement, and the performance of the sampling strategy was then evaluated by the Global Gearys C and the Quick-BP neural network model respectively. The test result showed that, compared with traditional c-means clustering sampling method, the accuracy of the sampling prediction based on local Moran index spatial clustering sampling method was increased by 13.57% which abstracted better the land information in the database.

A framework for distributed metadata management of mineral information resources with access control

Distributed metadata management is an efficient way to address the huge data of mineral information resources, which are usually distributed stored. In this paper, existing related metadata standards of mineral resource are firstly explored, based on which three typical kinds of metadata management mode, centralized metadata management mode, distributed metadata management mode and shared metadata management mode are summarized and evaluated. Considering the advantages and disadvantages of the three modes and the features of management, a framework for distributed metadata management of mineral information resources with access control is proposed to provide data management and share ability with access control. In this framework, a mineral information metadata table based on the standard published by China Geological Survey is defined to describe the metadata of distributed mineral information resources. The framework provides metadata and catalogue management abilities to fulfill data share and access control between different departments. The detailed design of the management framework is also given in this paper.

Integrated land-use and transportation models

The need to mitigate the repercussions of urban sprawl over the last decades triggered the use of systematic urban plans that encompass land use, transportation and environmental dimensions. These plans aim at forecasting housing demand and analyzing the impacts governmental policy programs may have on urban development. A considerable number of integrated urban models have been developed and used in the regional transportation planning. Within this context, the history and future of integrated transportation and land-use urban models are discussed and indicated. The review of these models embarks on the process of building the future integrated urban model.