Linked Open Data for Raster and Vector Geospatial Information Processing

Authors: Jon Arocena Javier Lozano Marco Quartulli Igor García Olaizola J. Bermúdez

Date: 26.07.2015


Abstract

Most EO image analysis algorithms ignore existing maps for solving ill-posed scene understanding problems and developing inversion procedures, yet new EO data often represent aspects of known objects and events. To solve part of this problem, we introduce a prototype designed to integrate, process and distribute existing heterogeneous local public authority maps with the outputs of automatic reconstruction/interpretation engines using mathematical tools for geoprocessing and operating on satellite images

BIB_text

@Article {
title = {Linked Open Data for Raster and Vector Geospatial Information Processing},
pages = {5023-5026},
abstract = {

Most EO image analysis algorithms ignore existing maps for solving ill-posed scene understanding problems and developing inversion procedures, yet new EO data often represent aspects of known objects and events. To solve part of this problem, we introduce a prototype designed to integrate, process and distribute existing heterogeneous local public authority maps with the outputs of automatic reconstruction/interpretation engines using mathematical tools for geoprocessing and operating on satellite images


}
isbn = {978-1-4799-7929-5},
isi = {1},
date = {2015-07-26},
year = {2015},
}
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