hig.sePublikationer
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • harvard-cite-them-right
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • sv-SE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • de-DE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Characterizing the Heterogeneity of the OpenStreetMap Data and Community
Högskolan i Gävle, Akademin för teknik och miljö, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, Samhällsbyggnad, GIS.
Högskolan i Gävle, Akademin för teknik och miljö, Avdelningen för bygg- energi- och miljöteknik, Energisystem.
Högskolan i Gävle, Akademin för teknik och miljö, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, Samhällsbyggnad, GIS.ORCID-id: 0000-0002-2337-2486
2015 (Engelska)Ingår i: ISPRS International Journal of Geo-Information, ISSN 2220-9964, Vol. 4, nr 2, s. 535-550Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

OpenStreetMap (OSM) constitutes an unprecedented, free, geographical information source contributed by millions of individuals, resulting in a database of great volume and heterogeneity. In this study, we characterize the heterogeneity of the entire OSM database and historical archive in the context of big data. We consider all users, geographic elements and user contributions from an eight-year data archive, at a size of 692 GB. We rely on some nonlinear methods such as power law statistics and head/tail breaks to uncover and illustrate the underlying scaling properties. All three aspects (users, elements, and contributions) demonstrate striking power laws or heavy-tailed distributions. The heavy-tailed distributions imply that there are far more small elements than large ones, far more inactive users than active ones, and far more lightly edited elements than heavy-edited ones. Furthermore, about 500 users in the core group of the OSM are highly networked in terms of collaboration.

Ort, förlag, år, upplaga, sidor
2015. Vol. 4, nr 2, s. 535-550
Nyckelord [en]
OpenStreetMap, big data, power laws, head/tail breaks, ht-index
Nationell ämneskategori
Annan data- och informationsvetenskap Naturgeografi
Identifikatorer
URN: urn:nbn:se:hig:diva-20223DOI: 10.3390/ijgi4020535ISI: 000358987600006Scopus ID: 2-s2.0-84948967039OAI: oai:DiVA.org:hig-20223DiVA, id: diva2:852398
Tillgänglig från: 2015-09-09 Skapad: 2015-09-09 Senast uppdaterad: 2018-12-03Bibliografiskt granskad
Ingår i avhandling
1. Topological and Scaling Analysis of Geospatial Big Data
Öppna denna publikation i ny flik eller fönster >>Topological and Scaling Analysis of Geospatial Big Data
2018 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

Geographic information science and systems face challenges related to understanding the instinctive heterogeneity of geographic space, since conventional geospatial analysis is mainly founded on Euclidean geometry and Gaussian statistics. This thesis adopts a new paradigm, based on fractal geometry and Paretian statistics for geospatial analysis. The thesis relies on the third definition of fractal geometry: A set or pattern is fractal if the scaling of far more small things than large ones recurs multiple times. Therefore, the terms fractal and scaling are used interchangeably in this thesis. The new definition of fractal is well-described by Paretian statistics, which is mathematically defined as heavy-tailed distributions. The topology of geographic features is the key prerequisite that enables us to see the fractal or scaling structure of the geographic space. In this thesis, topology refers to the relationship among meaningful geographic features (such as natural streets and natural cities).

The thesis conducts topological and scaling analyses of geographic space and its involved human activities in the context of geospatial big data. The thesis utilizes the massive, volunteered, geographic information coming from LBSM platforms, which are the global OpenStreetMap database and countrywide, geo-referenced tweets and check-in locations. The thesis develops geospatial big-data processing and modeling techniques, and employs complexity science methods, including heavy-tailed distribution detection and head/tail breaks, along with some complex network analysis. Head/tail breaks and the induced ht-index are a powerful tool for geospatial big-data analytics and visualization. The derived scaling hierarchies, power-law metrics, and network measures provide quantitative insights into the heterogeneity of geographic space and help us understand how it shapes human activities at city, country, and world scales. 

Ort, förlag, år, upplaga, sidor
Gävle: Gävle University Press, 2018. s. 73
Serie
Studies in the Research Profile Built Environment. Doctoral thesis ; 7
Nyckelord
Third definition of fractal, scaling, topology, power law, head/tail breaks, ht-index, complex network, geospatial big data, natural cities, natural streets
Nationell ämneskategori
Data- och informationsvetenskap Geovetenskap och miljövetenskap
Identifikatorer
urn:nbn:se:hig:diva-26197 (URN)978-91-88145-24-6 (ISBN)978-91-88145-25-3 (ISBN)
Disputation
2018-05-16, Lilla Jadwiga-salen, Kungsbäcksvägen 47, Gävle, 10:00 (Engelska)
Opponent
Handledare
Tillgänglig från: 2018-04-24 Skapad: 2018-03-04 Senast uppdaterad: 2018-04-25

Open Access i DiVA

Fulltext saknas i DiVA

Övriga länkar

Förlagets fulltextScopus

Personposter BETA

Ma, DingSandberg, MatsJiang, Bin

Sök vidare i DiVA

Av författaren/redaktören
Ma, DingSandberg, MatsJiang, Bin
Av organisationen
Samhällsbyggnad, GISEnergisystem
I samma tidskrift
ISPRS International Journal of Geo-Information
Annan data- och informationsvetenskapNaturgeografi

Sök vidare utanför DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetricpoäng

doi
urn-nbn
Totalt: 550 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • harvard-cite-them-right
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • sv-SE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • de-DE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf