A feature-based approach to conflation of geospatial sources

Ashok K Samal, Sharad Seth, Kevin Cueto

Research output: Contribution to journalArticle

100 Citations (Scopus)

Abstract

A Geographic Information System (GIS) populated with disparate data sources has multiple and different representations of the same real-world object. Often, the type of information in these sources is different, and combining them to generate one composite representation has many benefits. The first step in this conflation process is to identify the features in different sources that represent the same real-world entity. The matching process is not simple, since the identified features from different sources do not always match in their location, extent, and description. We present a new approach to matching GIS features from disparate sources. A graph theoretic approach is used to model the geographic context and to determine the matching features from multiple sources. Experiments on implementation of this approach demonstrate its viability.

Original languageEnglish (US)
Pages (from-to)459-489
Number of pages31
JournalInternational Journal of Geographical Information Science
Volume18
Issue number5
DOIs
StatePublished - Jul 1 2004

Fingerprint

Geographic information systems
information system
Composite materials
viability
Experiments
experiment
geographic information system

ASJC Scopus subject areas

  • Information Systems
  • Geography, Planning and Development
  • Library and Information Sciences

Cite this

A feature-based approach to conflation of geospatial sources. / Samal, Ashok K; Seth, Sharad; Cueto, Kevin.

In: International Journal of Geographical Information Science, Vol. 18, No. 5, 01.07.2004, p. 459-489.

Research output: Contribution to journalArticle

@article{02f867b4da1f46219129e0f536b8960f,
title = "A feature-based approach to conflation of geospatial sources",
abstract = "A Geographic Information System (GIS) populated with disparate data sources has multiple and different representations of the same real-world object. Often, the type of information in these sources is different, and combining them to generate one composite representation has many benefits. The first step in this conflation process is to identify the features in different sources that represent the same real-world entity. The matching process is not simple, since the identified features from different sources do not always match in their location, extent, and description. We present a new approach to matching GIS features from disparate sources. A graph theoretic approach is used to model the geographic context and to determine the matching features from multiple sources. Experiments on implementation of this approach demonstrate its viability.",
author = "Samal, {Ashok K} and Sharad Seth and Kevin Cueto",
year = "2004",
month = "7",
day = "1",
doi = "10.1080/13658810410001658076",
language = "English (US)",
volume = "18",
pages = "459--489",
journal = "International Journal of Geographical Information Science",
issn = "1365-8816",
publisher = "Taylor and Francis Ltd.",
number = "5",

}

TY - JOUR

T1 - A feature-based approach to conflation of geospatial sources

AU - Samal, Ashok K

AU - Seth, Sharad

AU - Cueto, Kevin

PY - 2004/7/1

Y1 - 2004/7/1

N2 - A Geographic Information System (GIS) populated with disparate data sources has multiple and different representations of the same real-world object. Often, the type of information in these sources is different, and combining them to generate one composite representation has many benefits. The first step in this conflation process is to identify the features in different sources that represent the same real-world entity. The matching process is not simple, since the identified features from different sources do not always match in their location, extent, and description. We present a new approach to matching GIS features from disparate sources. A graph theoretic approach is used to model the geographic context and to determine the matching features from multiple sources. Experiments on implementation of this approach demonstrate its viability.

AB - A Geographic Information System (GIS) populated with disparate data sources has multiple and different representations of the same real-world object. Often, the type of information in these sources is different, and combining them to generate one composite representation has many benefits. The first step in this conflation process is to identify the features in different sources that represent the same real-world entity. The matching process is not simple, since the identified features from different sources do not always match in their location, extent, and description. We present a new approach to matching GIS features from disparate sources. A graph theoretic approach is used to model the geographic context and to determine the matching features from multiple sources. Experiments on implementation of this approach demonstrate its viability.

UR - http://www.scopus.com/inward/record.url?scp=3242699504&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=3242699504&partnerID=8YFLogxK

U2 - 10.1080/13658810410001658076

DO - 10.1080/13658810410001658076

M3 - Article

AN - SCOPUS:3242699504

VL - 18

SP - 459

EP - 489

JO - International Journal of Geographical Information Science

JF - International Journal of Geographical Information Science

SN - 1365-8816

IS - 5

ER -