Publications des scientifiques de l'IRD

Pierkot Christelle, Andrés S., Faure Jean-François, Seyler Frédérique. (2013). Formalizing spatiotemporal knowledge in remote sensing applications to improve image interpretation. Journal of Spatial Information Science, (7), p. 77-98. ISSN 1948-660X.

Titre du document
Formalizing spatiotemporal knowledge in remote sensing applications to improve image interpretation
Année de publication
2013
Type de document
Article
Auteurs
Pierkot Christelle, Andrés S., Faure Jean-François, Seyler Frédérique
Source
Journal of Spatial Information Science, 2013, (7), p. 77-98 ISSN 1948-660X
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.
Plan de classement
Analyse d'image [126TELTRN03]
Descripteurs
TELEDETECTION SPATIALE ; IMAGE SATELLITE ; INTERPRETATION D'IMAGE ; MODELISATION ; METHODOLOGIE ; SEMANTIQUE ; ETUDE DE CAS ; COUVERT VEGETAL ; VARIATION SPATIALE ; VARIATION TEMPORELLE ; ONTOLOGIE ; REPRESENTATION DES CONNAISSANCES ; STANDARDISATION
Description Géographique
AMAZONIE ; BRESIL ; PARA BRESIL
Localisation
Fonds IRD [F B010062904]
Identifiant IRD
fdi:010062904
Contact