scholarly journals K-NEAREST NEIGHBOUR QUERY PERFORMANCE ANALYSES ON A LARGE SCALE TAXI DATASET: POSTGRESQL VS. MONGODB

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1531-1538 ◽  
Author(s):  
İ. B. Coşkun ◽  
S. Sertok ◽  
B. Anbaroğlu
Keyword(s):  
New York ◽  
Spatial Data ◽  
Large Scale ◽  
Information Science ◽  
Spatial Information ◽  
Database Management System ◽  
Nearest Neighbour ◽  
Spatial Accuracy ◽  
K Value ◽  
Spatial Information Science

<p><strong>Abstract.</strong> The increasing volume of transport network data necessitates the use of a DataBase Management System (DBMS) to store, query and analyse data. There are two main types of DBMS: relational and non-relational. Many different DBMS are available on the market but only some of them could handle spatial data. Therefore, determining which DBMS to use for operational purposes is of interest to researchers and analysts working in spatial information science. One of the commonly used spatial queries in GIS is the k-Nearest Neighbour (kNN) of a given point. This paper analyses the performance of the kNN query in PostgreSQL and MongoDB, both being a representative of relational and NoSQL DBMS respectively. Two different metrics have been investigated to determine the performance: i) spatial accuracy and ii) run time. Haversine and Vincenty formulas are used to calculate the distance between the point and the determined neighbours, which are then used to determine the spatial accuracy of the DBMS. Sensitivity analysis have been carried out by varying the k value and the execution times are recorded. The experiments are carried out on New York City’s openly available taxi dataset consisting of millions of taxi pickup and dropoff points. The results indicate that MongoDB outperforms Postgres both in terms of execution time and spatial accuracy regardless the value of k. In order to facilitate reproducibility of the results, the developed software is shared on GitHub.</p>

scholarly journals Creation of a Model for Estimating the Home-return Rate of Evacuees Using Mobile Phone Movement Histories and Its Application to the Nankai Trough Earthquake

2020 ◽  
Vol 1 ◽  
pp. 1-16
Author(s):  
Yoshiki Ogawa ◽  
Taisei Sato ◽  
Yoshihide Sekimoto
Keyword(s):  
Local Governments ◽  
Large Scale ◽  
Information Science ◽  
Spatial Information ◽  
Nankai Trough ◽  
Quantitative Relationship ◽  
Tsunami Disaster ◽  
Gis Data ◽  
Spatial Information Science ◽  
Post Disaster

Abstract. Considering the 2011 Great East Japan Earthquake, by utilizing GPS based large-scale people flow data, we developed a home-return model considering city variables that can estimate the rate of people who will have returned home on any number of days after an earthquake tsunami disaster. We obtained high accuracy with the sparse logit model in this study. The model can be applied in estimating a disaster only by using grid-based city variables of GIS data and existing damage estimation models. In addition, we used the model in the case of the Nankai Trough megathrust earthquake and simulated the transition of post-disaster home-return ratio. The estimation result can help local governments plan the management of evacuation centers in terms of the management of supplies and goods for disasters. The study could help a new understanding of the quantitative relationship between people returning home after evacuation and city variables with regard to earthquake and tsunami hazards based on spatial information science.

scholarly journals Digital archiving project of paper maps collected for the International Map Exhibition 1980 in Tokyo

2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Hideki Kaji ◽  
Ken’Ichi Tsuruoka ◽  
Ruochen Si ◽  
Min Lu ◽  
Masatoshi Arikawa ◽  
...  
Keyword(s):  
Information Science ◽  
New Technologies ◽  
Spatial Information ◽  
Fiscal Year ◽  
Digital Archive ◽  
Cooperative Research ◽  
Digital Archiving ◽  
Spatial Information Science ◽  
The University ◽  
And Storage

<p><strong>Abstract.</strong> The Kashiwa Library (KL), The University of Tokyo, holds a collection of old paper maps over the world, about a half of which were originally collected for the International Map Exhibition 1980 in Tokyo. The collection has 3,200 maps published in the 1970s and 1980s, and 1,260 of them were displayed at the exhibition. The map collection is important because it represents the cartography at the emerging era of new technologies and techniques such as satellite remote sensing, computers and GIS for map production (Arikawa et al., 2016). These maps were donated from the Japan Cartographers Association in March 2016, after their collection and storage by the association since the exhibition. In the Japanese fiscal year 2017, the Center for Spatial Information Science (CSIS), The University of Tokyo, and KL started a cooperative research project to produce a digital archive of this map collection, with support from the University of Tokyo Academic Archives Project that facilitates digital archiving of academic materials owned by various units at the university. This presentation explains the procedure of making our digital archive “Kashiwanoha Paper Maps Digital Archive”. “Kashiwanoha” is the address of the Kashiwa Campus of The University of Tokyo where KL and CSIS are located, and it literally means “oak leaf”.</p>

scholarly journals PREFACE: TECHNICAL COMMISSION IV ON SPATIAL INFORMATION SCIENCE

2020 ◽  
Vol XLIII-B4-2020 ◽  
pp. 7-9
Author(s):  
S. Zlatanova ◽  
S. Dragicevic ◽  
G. Sithole
Keyword(s):  
Data Fusion ◽  
Peer Review ◽  
Information Science ◽  
Review Process ◽  
Spatial Information ◽  
Peer Review Process ◽  
Human Society ◽  
Wide Range ◽  
Spatial Information Science ◽  
Advance Research

Abstract. The unusual circumstances created by the coronavirus pandemic has impacted recent activities of Commission IV. The situation also provides an excellent opportunity to connect the work of the Commission to addressing an important global problem. Managing the social and economic challenges brought by increased complexity and interconnectivity of activities in human society requires new dimensions of analysing information and specifically spatial information. The increased pressure on the usage of geographic space, maintaining sustainable development and creating liveable community environments increases the requirements for spatial decision-making tools. Commission IV Spatial Information Science (2016–2020) is dedicated to advance research activities in spatial information sciences for modelling, structuring, management, analysis, visualization and simulation of (big) data with focus on the third spatial dimension and taking into consideration dynamic changes. Special attention is given to linking information about real-world physical phenomena with societal, organizational and legal information in order to address the complexity of issues in their entirety. The Commission has contributed to advancements in data modelling, data fusion and management, visualization (web-based, VR and AR), simulation and city analytics, and 3D applications. The work had largely been implemented in cooperation with international organizations such as FIG, UDMS, 3DGeoinfo, ICA, OGC, ISO and Web3D.The Commission consists of 10 scientific areas of research that is coordinated by 10 working groups (WG) as follows - WG1: Strengthen the work on multidimensional spatial model and representations towards seamless data fusion; WG2: Advance the semantic modelling, development and linking of ontologies; WG3: Intensify research into data interpretation, quality and uncertainty modelling; WG4: Strengthen research on crowdsourced data and public participation, towards community-driven and participatory applications, collaborative mapping and use/usability of maps; WG5: Strengthen research on seamless indoor/outdoor location-based services, navigation and tracking, and analysis of human movement; WG6: Advance interoperable Internet of Things, Sensor web, SDI and linked data; WG7: Advance research on spatial data types, indexing methods and analysis to further contribute to development of spatial DBMS for management and analysis of multi-dimensional data; WG8: Encourage the use of functional programming and streaming algorithms in development of demos and applications as well as parallel and distributed processing paradigms; WG9: Advance visual analytics, online multi-dimensional visualization on mobile and desktop devices, considering human-centred applications, privacy and security issues; WG10: Advance knowledge on the use of spatial information (BIM/GIS) for urban modelling; ICWG IV/III: Global Mapping: Updating, Verification and Interoperability with the mission to promote the development of advanced methodologies and applications for the update, verification and interoperability of geospatial databases.The papers received for the ISPRS congress reflect the above-mentioned scientific research areas. The reported research ranges from advancements in new and emerging theories, through experiments and analysis to demonstration of technologies in different applications. The research was captured through papers and abstracts published in the collection of ISPRS Annals and ISPRS Archives. The papers and abstracts were selected for inclusion through a rigorous peer-review process. The ISPRS Annals contain 29 papers and the ISPRS Archives contain 114 papers. The diversity of the research topics presented in the published papers clearly indicate the wide range of topics within the field of Spatial Information Science. A rigorous peer-review process by the ISPRS TC IV Scientific Committee Working Group Chairs ensured hight quality and scientific innovation.

scholarly journals Preface: Technical Commission IV on Spatial Information Science

2020 ◽  
Vol V-4-2020 ◽  
pp. 7-9
Author(s):  
S. Zlatanova ◽  
S. Dragicevic ◽  
G. Sithole
Keyword(s):  
Data Fusion ◽  
Peer Review ◽  
Information Science ◽  
Review Process ◽  
Spatial Information ◽  
Peer Review Process ◽  
Human Society ◽  
Wide Range ◽  
Spatial Information Science ◽  
Advance Research

Abstract. The unusual circumstances created by the coronavirus pandemic has impacted recent activities of Commission IV. The situation also provides an excellent opportunity to connect the work of the Commission to addressing an important global problem. Managing the social and economic challenges brought by increased complexity and interconnectivity of activities in human society requires new dimensions of analysing information and specifically spatial information. The increased pressure on the usage of geographic space, maintaining sustainable development and creating liveable community environments increases the requirements for spatial decision-making tools. Commission IV Spatial Information Science (2016–2020) is dedicated to advance research activities in spatial information sciences for modelling, structuring, management, analysis, visualization and simulation of (big) data with focus on the third spatial dimension and taking into consideration dynamic changes. Special attention is given to linking information about real-world physical phenomena with societal, organizational and legal information in order to address the complexity of issues in their entirety. The Commission has contributed to advancements in data modelling, data fusion and management, visualization (web-based, VR and AR), simulation and city analytics, and 3D applications. The work had largely been implemented in cooperation with international organizations such as FIG, UDMS, 3DGeoinfo, ICA, OGC, ISO and Web3D.The Commission consists of 10 scientific areas of research that is coordinated by 10 working groups (WG) as follows - WG1: Strengthen the work on multidimensional spatial model and representations towards seamless data fusion; WG2: Advance the semantic modelling, development and linking of ontologies; WG3: Intensify research into data interpretation, quality and uncertainty modelling; WG4: Strengthen research on crowdsourced data and public participation, towards community-driven and participatory applications, collaborative mapping and use/usability of maps; WG5: Strengthen research on seamless indoor/outdoor location-based services, navigation and tracking, and analysis of human movement; WG6: Advance interoperable Internet of Things, Sensor web, SDI and linked data; WG7: Advance research on spatial data types, indexing methods and analysis to further contribute to development of spatial DBMS for management and analysis of multi-dimensional data; WG8: Encourage the use of functional programming and streaming algorithms in development of demos and applications as well as parallel and distributed processing paradigms; WG9: Advance visual analytics, online multi-dimensional visualization on mobile and desktop devices, considering human-centred applications, privacy and security issues; WG10: Advance knowledge on the use of spatial information (BIM/GIS) for urban modelling; ICWG IV/III: Global Mapping: Updating, Verification and Interoperability with the mission to promote the development of advanced methodologies and applications for the update, verification and interoperability of geospatial databases.The papers received for the ISPRS congress reflect the above-mentioned scientific research areas. The reported research ranges from advancements in new and emerging theories, through experiments and analysis to demonstration of technologies in different applications. The research was captured through papers and abstracts published in the collection of ISPRS Annals and ISPRS Archives. The papers and abstracts were selected for inclusion through a rigorous peer-review process. The ISPRS Annals contain 29 papers and the ISPRS Archives contain 114 papers. The diversity of the research topics presented in the published papers clearly indicate the wide range of topics within the field of Spatial Information Science. A rigorous peer-review process by the ISPRS TC IV Scientific Committee Working Group Chairs ensured hight quality and scientific innovation.

scholarly journals A REVIEW OF RECENT RESEARCH IN INDOOR MODELLING & MAPPING

2016 ◽  
Vol XLI-B4 ◽  
pp. 289-294 ◽  
Author(s):  
M. Gunduz ◽  
U. Isikdag ◽  
M. Basaraner
Keyword(s):  
Information Acquisition ◽  
Information Science ◽  
Spatial Information ◽  
Ethical Issues ◽  
Urban Spaces ◽  
Future Research ◽  
Scientific Publications ◽  
Research Directions ◽  
Spatial Information Science ◽  
Future Research Directions

Indoor modeling and mapping has been an active area of research in last 20 years in order to tackle the problems related to positioning and tracking of people and objects indoors, and provides many opportunities for several domains ranging from emergency response to logistics in micro urban spaces. The outputs of recent research in the field have been presented in several scientific publications and events primarily related to spatial information science and technology. This paper summarizes the outputs of last 10 years of research on indoor modeling and mapping within a proper classification which covers 7 areas, i.e. Information Acquisition by Sensors, Model Definition, Model Integration, Indoor Positioning and LBS, Routing & Navigation Methods, Augmented and Virtual Reality Applications, and Ethical Issues. Finally, the paper outlines the current and future research directions and concluding remarks.

Implementation and QoS for High-performance GIServices in Special Information Grid

2011 ◽  
pp. 181-203 ◽  
Author(s):  
Fang Huang
Keyword(s):  
Spatial Data ◽  
High Performance ◽  
Information Science ◽  
Spatial Information ◽  
Grass Gis ◽  
Information Grid ◽  
Special Information ◽  
Services Implementation ◽  
Spatial Information Grid

With the development of grid technology, the spatial information grid researches are also in progress. In China, the spatial information grid platform (abbreviation to SIG) not only can provide geo-spatial data services (GDS) for handling terabytes of geospatial data, but also can present processing functionality services (PFS) encapsulated from several Remote Sensing (RS) software to solve RS computing problems remotely. In particular, the spatial user can utilize some provided high-performance PFS to achieve those computing intensive tasks that lacking of the high-performance computing facility such as cluster or Condor platform. Unfortunately, the existing SIG paid litter attention to Geographic Information Science (GIS) field, as a result, the constitution of PFS related to GIS, especially the high-performance GIServices (HP-GIServices), are becoming the main issues for SIG’s next research. Lacking of GIServices mainly resulted from the limitations of SIG architecture, difficulty of extracting parallel GIS functionalities modules, as well as the complexity for services implementation and encapsulation. Based on existing SIG platform, this chapter proposes the improved architecture for SIG, upon which the constituted GIS nodes can provide GIServices. Within the new architecture, some parallel GRASS GIS (Geographic Resources Analysis Support System) 1 algorithms programs, which are built by different parallelization patterns and can run in cluster with better efficiency, are encapsulated to high-performance GIServices guiding by certain generic mode. Lastly, the QoS (quality of services) indexes are proposed to evaluate the quality of the constituted HP-GIServices in SIG. From the tentative experiments and analyses, the facts demonstrate that this approach can reach our aims. In all, the chapter firstly gives an overview of existing SIG platform. Facing to the problem of lacking of HP-GIServices, the improved architecture, various parallelization patterns to extract parallel GIS algorithms based on GRASS GIS are proposed. Furthermore, the encapsulation guidance and QoS for evaluating HP-GIServices are also discussed.

Sign in / Sign up

Export Citation Format

Share Document