Formalizing spatiotemporal knowledge in remote sensing applications to improve image interpretation

Technological tools allow the generation of large volumes of data. For example satellite images aid in the study of spatiotemporal phenomena in a range of disciplines, such as urban planning, environmental sciences, and health care. Thus, remote-sensing experts must handle various and complex image...

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Bibliographic Details
Published in:Journal of Spatial Information Science
Main Authors: Christelle Pierkot, Samuel Andrés, Jean François Faure, Frédérique Seyler
Format: Article
Language:English
Published: University of Maine 2013-12-01
Subjects:
Online Access:http://josis.org/index.php/josis/article/view/142
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author Christelle Pierkot
Samuel Andrés
Jean François Faure
Frédérique Seyler
author_facet Christelle Pierkot
Samuel Andrés
Jean François Faure
Frédérique Seyler
author_sort Christelle Pierkot
collection DOAJ
container_title Journal of Spatial Information Science
description Technological tools allow the generation of large volumes of data. For example satellite images aid in the study of spatiotemporal phenomena in a range of disciplines, such as urban planning, environmental sciences, and health care. Thus, remote-sensing experts must handle various and complex image sets for their interpretations. The GIS community has undertaken significant work in describing spatiotemporal features, and standard specifications nowadays provide design foundations for GIS software and spatial databases. We argue that this spatiotemporal knowledge and expertise would provide invaluable support for the field of image interpretation. As a result, we propose a high level conceptual framework, based on existing and standardized approaches, offering enough modularity and adaptability to represent the various dimensions of spatiotemporal knowledge.
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spelling doaj-art-796913a9fdcc4ebc86c19e37ecaf3e102025-08-19T19:40:25ZengUniversity of MaineJournal of Spatial Information Science1948-660X2013-12-0120137779810.5311/JOSIS.2013.7.14291Formalizing spatiotemporal knowledge in remote sensing applications to improve image interpretationChristelle Pierkot0Samuel Andrés1Jean François Faure2Frédérique Seyler3IRD UMR Espace-DevIRD UMR Espace-DevIRD UMR Espace-DevIRD UMR Espace-DevTechnological tools allow the generation of large volumes of data. For example satellite images aid in the study of spatiotemporal phenomena in a range of disciplines, such as urban planning, environmental sciences, and health care. Thus, remote-sensing experts must handle various and complex image sets for their interpretations. The GIS community has undertaken significant work in describing spatiotemporal features, and standard specifications nowadays provide design foundations for GIS software and spatial databases. We argue that this spatiotemporal knowledge and expertise would provide invaluable support for the field of image interpretation. As a result, we propose a high level conceptual framework, based on existing and standardized approaches, offering enough modularity and adaptability to represent the various dimensions of spatiotemporal knowledge.http://josis.org/index.php/josis/article/view/142Spatio-temporalitygeographic standardsremote-sensing interpretation
spellingShingle Christelle Pierkot
Samuel Andrés
Jean François Faure
Frédérique Seyler
Formalizing spatiotemporal knowledge in remote sensing applications to improve image interpretation
Spatio-temporality
geographic standards
remote-sensing interpretation
title Formalizing spatiotemporal knowledge in remote sensing applications to improve image interpretation
title_full Formalizing spatiotemporal knowledge in remote sensing applications to improve image interpretation
title_fullStr Formalizing spatiotemporal knowledge in remote sensing applications to improve image interpretation
title_full_unstemmed Formalizing spatiotemporal knowledge in remote sensing applications to improve image interpretation
title_short Formalizing spatiotemporal knowledge in remote sensing applications to improve image interpretation
title_sort formalizing spatiotemporal knowledge in remote sensing applications to improve image interpretation
topic Spatio-temporality
geographic standards
remote-sensing interpretation
url http://josis.org/index.php/josis/article/view/142
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AT frederiqueseyler formalizingspatiotemporalknowledgeinremotesensingapplicationstoimproveimageinterpretation