Distributed Vector based Spatial Data Conflation Services

Sérgio Freitas, Ana Paula Afonso: Distributed Vector based Spatial Data Conflation Services. In: Namikawa, Laercio; Bogorny, Vania (Ed.): pp. 23-29, 2012, ISSN: 2179-4847.

Abstract

Spatial data conflation is a key task for consolidating geographic knowledge from different data sources covering overlapping regions that were gathered using different methodologies and objectives. Nowadays this research area is becoming more challenging because of the increasing size and number of overlapping spatial data sets being produced. This paper presents an approach towards distributed vector to vector conflation, which can be applied to overlapping heterogeneous spatial data sets through the implementation of Web Processing Services
(WPS). Initial results show that distributed spatial conflation can be effortlessly achieved if during the pre-processing phase disjoint clusters are created. However, if this is not possible further horizontal conflation algorithms are applied to neighbor clusters before obtaining the final data set.

BibTeX (Download)

@inproceedings{freitas2012distributed,
title = {Distributed Vector based Spatial Data Conflation Services},
author = { Sérgio Freitas and Ana Paula Afonso},
editor = {Laercio M. Namikawa and Vania Bogorny},
url = {http://www.geoinfo.info/geoinfo2012/papers/freitas.pdf},
issn = {2179-4847},
year  = {2012},
date = {2012-01-01},
pages = {23-29},
abstract = {Spatial  data  conflation  is  a  key  task for  consolidating  geographic knowledge from different data sources covering overlapping regions that were gathered   using   different   methodologies   and   objectives.   Nowadays   this research  area  is  becoming  more  challenging  because  of  the  increasing  size and  number  of  overlapping  spatial  data  sets  being  produced.  This  paper presents  an  approach  towards  distributed  vector  to  vector  conflation,  which can  be  applied  to  overlapping  heterogeneous  spatial  data  sets  through  the implementation  of  Web  Processing  Services 
(WPS).  Initial  results  show  that distributed  spatial  conflation  can  be  effortlessly  achieved  if  during  the  pre-processing phase disjoint clusters are created. However, if this is not possible further  horizontal  conflation algorithms  are  applied  to neighbor clusters before obtaining the final data set.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}