scholarly journals An End-to-End Point of Interest (POI) Conflation Framework

2021 ◽  
Vol 10 (11) ◽  
pp. 779
Author(s):  
Raymond Low ◽  
Zeynep Duygu Tekler ◽  
Lynette Cheah

Point of interest (POI) data serves as a valuable source of semantic information for places of interest and has many geospatial applications in real estate, transportation, and urban planning. With the availability of different data sources, POI conflation serves as a valuable technique for enriching data quality and coverage by merging the POI data from multiple sources. This study proposes a novel end-to-end POI conflation framework consisting of six steps, starting with data procurement, schema standardisation, taxonomy mapping, POI matching, POI unification, and data verification. The feasibility of the proposed framework was demonstrated in a case study conducted in the eastern region of Singapore, where the POI data from five data sources was conflated to form a unified POI dataset. Based on the evaluation conducted, the resulting unified dataset was found to be more comprehensive and complete than any of the five POI data sources alone. Furthermore, the proposed approach for identifying POI matches between different data sources outperformed all baseline approaches with a matching accuracy of 97.6% with an average run time below 3 min when matching over 12,000 POIs to result in 8699 unique POIs, thereby demonstrating the framework’s scalability for large scale implementation in dense urban contexts.

2020 ◽  
Vol 10 (1) ◽  
pp. 7
Author(s):  
Miguel R. Luaces ◽  
Jesús A. Fisteus ◽  
Luis Sánchez-Fernández ◽  
Mario Munoz-Organero ◽  
Jesús Balado ◽  
...  

Providing citizens with the ability to move around in an accessible way is a requirement for all cities today. However, modeling city infrastructures so that accessible routes can be computed is a challenge because it involves collecting information from multiple, large-scale and heterogeneous data sources. In this paper, we propose and validate the architecture of an information system that creates an accessibility data model for cities by ingesting data from different types of sources and provides an application that can be used by people with different abilities to compute accessible routes. The article describes the processes that allow building a network of pedestrian infrastructures from the OpenStreetMap information (i.e., sidewalks and pedestrian crossings), improving the network with information extracted obtained from mobile-sensed LiDAR data (i.e., ramps, steps, and pedestrian crossings), detecting obstacles using volunteered information collected from the hardware sensors of the mobile devices of the citizens (i.e., ramps and steps), and detecting accessibility problems with software sensors in social networks (i.e., Twitter). The information system is validated through its application in a case study in the city of Vigo (Spain).


Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1049
Author(s):  
Zhang Deng ◽  
Yixing Chen ◽  
Xiao Pan ◽  
Zhiwen Peng ◽  
Jingjing Yang

Urban building energy modeling (UBEM) is arousing interest in building energy modeling, which requires a large building dataset as an input. Building use is a critical parameter to infer archetype buildings for UBEM. This paper presented a case study to determine building use for city-scale buildings by integrating the Geographic Information System (GIS) based point-of-interest (POI) and community boundary datasets. A total of 68,966 building footprints, 281,767 POI data, and 3367 community boundaries were collected for Changsha, China. The primary building use was determined when a building was inside a community boundary (i.e., hospital or residential boundary) or the building contained POI data with main attributes (i.e., hotel or office building). Clustering analysis was used to divide buildings into sub-types for better energy performance evaluation. The method successfully identified building uses for 47,428 buildings among 68,966 building footprints, including 34,401 residential buildings, 1039 office buildings, 141 shopping malls, and 932 hotels. A validation process was carried out for 7895 buildings in the downtown area, which showed an overall accuracy rate of 86%. A UBEM case study for 243 office buildings in the downtown area was developed with the information identified from the POI and community boundary datasets. The proposed building use determination method can be easily applied to other cities. We will integrate the historical aerial imagery to determine the year of construction for a large scale of buildings in the future.


2019 ◽  
Vol 8 (8) ◽  
pp. 326
Author(s):  
Ci Song ◽  
Tao Pei

The decomposition of a point process is useful for the analysis of spatial patterns and in the discovery of potential mechanisms of geographic phenomena. However, when a local repulsive cluster is present in a complex heterogeneous point process, the traditional solution, which is based on clustering, may be invalid for decomposition because a repulsive pattern is not subject to a specific probability distribution function and the effects of aggregative and repulsive components may be counterbalanced. To solve this problem, this paper proposes a method of decomposing repulsive clusters in complex point processes with multiple heterogeneous components. A repulsive cluster is defined as a set of repulsive density-connected points that are separated by a certain distance at a small scale and aggregated at a large scale simultaneously. The H-function is used to identify repulsive clusters by determining the repulsive distance and extracting repulsive points for further clustering. Through simulation experiments based on three datasets, the proposed method has been shown to effectively perform repulsive cluster decomposition in heterogeneous point processes. A case study of the point of interest (POI) dataset in Beijing also indicates that the method can identify meaningful repulsive clusters from types of POIs that represent different service characteristics of shops in different local regions.


2021 ◽  
Author(s):  
Mihal Miu ◽  
Xiaokun Zhang ◽  
M. Ali Akber Dewan ◽  
Junye Wang

Geospatial information plays an important role in environmental modelling, resource management, business operations, and government policy. However, very little or no commonality between formats of various geospatial data has led to difficulties in utilizing the available geospatial information. These disparate data sources must be aggregated before further extraction and analysis may be performed. The objective of this paper is to develop a framework called PlaniSphere, which aggregates various geospatial datasets, synthesizes raw data, and allows for third party customizations of the software. PlaniSphere uses NASA World Wind to access remote data and map servers using Web Map Service (WMS) as the underlying protocol that supports service-oriented architecture (SOA). The results show that PlaniSphere can aggregate and parses files that reside in local storage and conforms to the following formats: GeoTIFF, ESRI shape files, and KML. Spatial data retrieved using WMS from the Internet can create geospatial data sets (map data) from multiple sources, regardless of who the data providers are. The plug-in function of this framework can be expanded for wider uses, such as aggregating and fusing geospatial data from different data sources, by providing customizations to serve future uses, which the capacity of the commercial ESRI ArcGIS software is limited to add libraries and tools due to its closed-source architectures and proprietary data structures. Analysis and increasing availability of geo-referenced data may provide an effective way to manage spatial information by using large-scale storage, multidimensional data management, and Online Analytical Processing (OLAP) capabilities in one system.


2021 ◽  
Author(s):  
Shaun A Truelove ◽  
Sonia A Hegde ◽  
Lori Niehaus ◽  
Natalya Kostandova ◽  
Chiara Altare ◽  
...  

Background Since the emergence of the COVID-19 pandemic, substantial concern has surrounded its impact among the Rohingya refugees living in the Kutupalong-Balukhali refugee camps in Bangladesh. Early modeling work projected a massive outbreak was likely after an introduction of the SARS-CoV-2 virus into the camps. Despite this, only 317 laboratory-confirmed cases and 10 deaths were reported through October 2020. While these official numbers portray a situation where the virus has been largely controlled, other sources contradict this, suggesting the low reported numbers to be a result of limited care seeking and testing, highlighting a population not willing to seek care or be tested. SARS-CoV-2 seroprevalence estimates from similar a timeframe in India (57%) and Bangladesh (74%) further sow doubt that transmission had been controlled. Here we explore multiple data sources to understand the plausibility of a much larger SARS-CoV-2 outbreak among the Rohingya refugees. Methods We used a mixed approach to analyze SARS-CoV-2 transmission using multiple available datasets. Using data from reported testing, cases, and deaths from the World Health Organization (WHO) and from WHO's Emergency Warning, Alert, and Response System, we characterized the probabilities of care seeking, testing, and being positive if tested. Unofficial death data, including reported pre-death symptoms, come from a community-based mortality survey conducted by the International Organization for Migration (IOM),) in addition to community health worker reported deaths. We developed a probabilistic inference framework, drawing on these data sources, to explore three scenarios of what might have happened among the Rohingya refugees. Results Among the 144 survey-identified deaths, 48 were consistent with suspected COVID-19. These deaths were consistent with viral exposures during Ramadan, a period of increased social contacts, and coincided with a spike in reported cases and testing positivity in June 2020. The age profile of suspected COVID-19 deaths mirrored that expected. Through the probability framework, we find that under each scenario, a substantial outbreak likely occurred, though the cumulative size and timing vary considerably. In conjunction with the reported and suspected deaths, the data suggest a large outbreak could have occurred early during spring 2020. Furthermore, while many mild and asymptomatic infections likely occurred, death data analyzed suggest there may have been significant unreported mortality. Conclusions With the high population density, inability to home isolate adequately, and limited personal protective equipment, infection prevention and control in the Rohingya population is extremely challenging. Despite the low reported numbers of cases and deaths, our results suggest an early large-scale outbreak is consistent with multiple sources of data, particularly when accounting for limited care seeking behavior and low infection severity among this young population. While the currently available data do not allow us to estimate the precise incidence, these results indicate substantial unrecognized SARS-CoV-2 transmission may have occurred in these camps. However, until serological testing provides more conclusive evidence, we are only able to speculate about the extent of transmission among the Rohingya.


Author(s):  
Kai Xia ◽  
Liang Gao ◽  
Lihui Wang ◽  
Weidong Li ◽  
Kuo-Ming Chao

Sustainable management of waste electrical and electronic equipment (WEEE) has attracted escalating concerns of researchers and industries. Closer information linking among the participants in the products's lifecycle should take place. How to interoperate among the distributed and heterogeneous information systems of various participants is a challenge faced. Targeting the cloud-based remanufacturing, this article aims to develop a semantic information services framework for sustainable WEEE management. In the proposed framework, an ontology based approach is developed to integrate and represent the lifecycle information from multiple local data sources within an information services provider. Meanwhile, a semantic information services management platform is introduced for the advertisement, matchmaking and retrieval of semantic information services. Some relevant techniques used to build the framework are introduced extensively. A demonstration case study on waste LCD TV is used to illustrate the effectiveness and significance of the proposed framework.


Author(s):  
Azadeh Arjomand Kermani

PurposeLarge-scale interventions are still the dominant approach in dealing with historic cities in Iran; however, during the last decade there has been a shift towards integrated and decentralised policies and a series of locally based projects were initiated across the country. Political and ideological forces, population growth as well as cultural and heritage consensus are influencing approaches towards urban conservation and heritage management constantly. This paper opens up the urban intervention approaches in the historic core of Shiraz and provides a deeper insight and better understanding of heritage management and regeneration plans in Shiraz as a representative of historic Iranian cities.Design/methodology/approachThe study explains and analyses major urban transformations in Shiraz. The main approaches towards historical city core are identified and the mechanism that shaped these approaches in national and local scale is discussed. This investigation primarily uses qualitative data sources. The study relies on multiple sources of evidence which result in the reliability and validity of the investigation. Therefore, primary sources include original documents, maps and photographs published in documentation for the projects, published and unpublished materials and archives about case study city and secondary sources such as interviews with consultants and authorities as well as residents have been used.FindingsThis paper provides a more detailed explanation about several interrelated factors that affected the process of decision and policy making, planning and implementation of city centre interventions during the last two decades.Originality/valueThis paper anticipates consequent trends in heritage management in Shiraz and recommends further research areas. The paper can be used to develop a more practical set of recommendations for urban heritage management in Iran.


Author(s):  
Philipp Singer ◽  
Thomas Niebler ◽  
Markus Strohmaier ◽  
Andreas Hotho

In this article, the authors present a novel approach for computing semantic relatedness and conduct a large-scale study of it on Wikipedia. Unlike existing semantic analysis methods that utilize Wikipedia’s content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment – a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors’ results are intriguing: They suggest that (i) semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia’s plain link structure alone and (ii) that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors’ work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.


2013 ◽  
Vol 455 ◽  
pp. 434-437
Author(s):  
Jing Tao Zhou

Master-slave P2P mapping principle proposed in our previous work [ is a semantic P2P mapping paradigm with modularity and loosely coupled characteristics. The intent of this paper is to define a common case study of this paradigm for the semantic information integration. The domain of the case study is a semantic P2P information integration system called SGII[, i.e., system that help in information coordinating and interoperating by orchestrating the content and formalization expression of master-slave P2P mapping between elements from different peer node models which represent the data exposed (shared) by data sources. Furthermore, an illustrative example of master-slave P2P mapping paradigm is given to explain how the mappings are implemented and to demonstrate the paradigm can hence be applied in semantic information integration scenarios.


2021 ◽  
Author(s):  
Mihal Miu ◽  
Xiaokun Zhang ◽  
M. Ali Akber Dewan ◽  
Junye Wang

Geospatial information plays an important role in environmental modelling, resource management, business operations, and government policy. However, very little or no commonality between formats of various geospatial data has led to difficulties in utilizing the available geospatial information. These disparate data sources must be aggregated before further extraction and analysis may be performed. The objective of this paper is to develop a framework called PlaniSphere, which aggregates various geospatial datasets, synthesizes raw data, and allows for third party customizations of the software. PlaniSphere uses NASA World Wind to access remote data and map servers using Web Map Service (WMS) as the underlying protocol that supports service-oriented architecture (SOA). The results show that PlaniSphere can aggregate and parses files that reside in local storage and conforms to the following formats: GeoTIFF, ESRI shape files, and KML. Spatial data retrieved using WMS from the Internet can create geospatial data sets (map data) from multiple sources, regardless of who the data providers are. The plug-in function of this framework can be expanded for wider uses, such as aggregating and fusing geospatial data from different data sources, by providing customizations to serve future uses, which the capacity of the commercial ESRI ArcGIS software is limited to add libraries and tools due to its closed-source architectures and proprietary data structures. Analysis and increasing availability of geo-referenced data may provide an effective way to manage spatial information by using large-scale storage, multidimensional data management, and Online Analytical Processing (OLAP) capabilities in one system.


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