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Rule-based classification of multi-temporal satellite imagery for habitat and agricultural land cover mapping / Robert Lucas in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 3 (August 2007)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 62 n° 3 (August 2007) . - pp 165 - 185 Titre : Rule-based classification of multi-temporal satellite imagery for habitat and agricultural land cover mapping Type de document : Article/Communication Auteurs : Robert Lucas, Auteur ; A. Rowlands, Auteur ; A. Brown, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 165 - 185 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] agriculture [Termes IGN] carte d'occupation du sol [Termes IGN] classification floue [Termes IGN] eCognition [Termes IGN] habitat (urbanisme) [Termes IGN] image Landsat [Termes IGN] image multitemporelle [Termes IGN] indice de végétation [Termes IGN] intelligence artificielle [Termes IGN] logique floue [Termes IGN] Pays de Galles [Termes IGN] segmentation d'image [Termes IGN] série temporelle Résumé : (Auteur) The aim is to evaluate the use of time-series of Landsat sensor data acquired over an annual cycle for mapping semi-natural habitats and agricultural land cover. The location is Berwyn Mountains, North Wales, United Kingdom. The methods are Using eCognition Expert, segmentation of the Landsat sensor data was undertaken for actively managed agricultural land based on Integrated Administration and Control System (IACS) land parcel boundaries, whilst a per-pixel level segmentation was undertaken for all remaining areas. Numerical decision rules based on fuzzy logic that coupled knowledge of ecology and the information content of single and multi-date remotely sensed data and derived products (e.g., vegetation indices) were developed to discriminate vegetation types based primarily on inferred differences in phenology, structure, wetness and productivity. The results : The rule-based classification gave a good representation of the distribution of habitats and agricultural land. The more extensive, contiguous and homogeneous habitats could be mapped with accuracies exceeding 80%, although accuracies were lower for more complex environments (e.g., upland mosaics) or those with broad definition (e.g., semi-improved grasslands). The application of a rule-based classification to temporal imagery acquired over selected periods within an annual cycle provides a viable approach for mapping and monitoring of habitats and agricultural land in the United Kingdom that could be employed operationally. Copyright ISPRS Numéro de notice : A2007-367 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2007.03.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2007.03.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28730 [article]

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