Détail de l'auteur
Auteur A. Gimona |
Documents disponibles écrits par cet auteur (2)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externes
Spatio-temporal MODIS EVI gap filling under cloud cover: An example in Scotland / L. Poggio in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)
[article]
Titre : Spatio-temporal MODIS EVI gap filling under cloud cover: An example in Scotland Type de document : Article/Communication Auteurs : L. Poggio, Auteur ; A. Gimona, Auteur ; I. Brown, Auteur Année de publication : 2012 Article en page(s) : pp 56 - 72 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification pixellaire
[Termes IGN] Ecosse
[Termes IGN] image CMODIS
[Termes IGN] interpolation
[Termes IGN] krigeage
[Termes IGN] nuage
[Termes IGN] ombre
[Termes IGN] résiduRésumé : (Auteur) Time series of satellite data have an important role in the monitoring of regional and global ecosystem properties. Satellite images often present missing data due to atmospheric aerosol, clouds or other atmospheric conditions. Most methods proposed to minimise the effects of degradation and to restore signal values do not take into account the spatial and temporal correlation of the values in the pixels. The aim of this study was to propose and test a spatio-temporal interpolation method to reconstruct pixel values in MODIS data time series that are missing due to cloud cover or other image noise. The method presented and tested is an example of a hybrid Generalised Additive Model (GAM)-geostatistical space-time model, including the fitting of a smoother spatio-temporal trend and a spatial component to account for local details supported by information in covariates. The method is not limited by the type of noise or degradation of pixels values, latitude, vegetation dynamics and land uses. The application of cloud masks on the target image provided the data for a quantitative validation through the comparison between the modelled EVI values and those from the MODIS product. The method was able to restore data providing very good to adequate responses in series of simulations of missing data. The comparison of distributions showed good agreement and predictive capabilities. The spatio-temporal method always performed better and the use of kriged residuals was helpful for situations with high percentages of missing data. The spatial pattern and the local features were well preserved for cloud coverage Numéro de notice : A2012-494 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.06.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.06.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31940
in ISPRS Journal of photogrammetry and remote sensing > vol 72 (August 2012) . - pp 56 - 72[article]Réservation
Réserver ce documentExemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 081-2012061 SL Revue Centre de documentation Revues en salle Disponible Estimating local variations in land use statistics / A. Geddes in International journal of geographical information science IJGIS, vol 17 n° 4 (june 2003)
[article]
Titre : Estimating local variations in land use statistics Type de document : Article/Communication Auteurs : A. Geddes, Auteur ; A. Gimona, Auteur ; D.A. Elston, Auteur Année de publication : 2003 Article en page(s) : pp 299 - 319 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Information géographique
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification dirigée
[Termes IGN] distribution spatiale
[Termes IGN] Ecosse
[Termes IGN] estimation statistique
[Termes IGN] géostatistique
[Termes IGN] recensement agricole
[Termes IGN] statistique descriptive
[Termes IGN] système d'information géographique
[Termes IGN] utilisation du sol
[Termes IGN] variable régionaliséeRésumé : (Auteur) The Scottish agricultural census provides land use statistics as summaries for parish areas. We investigated the disaggregation of these parish summaries using the Land Capability for Agriculture and the 1988 Land Cover of Scotland as supporting data sets. It is unlikely that allocation rules to implement the disaggregation should be identical across all parishes. Equally, rules for individual parishes are indeterminate. The 891 parishes were classified into nine classes, then each class was regionalised, creating 91 regions overall. Allocation rules were estimated independently for each region and class. Statistical testing identified greater variations in the rules than is expected by random allocation of regions to classes. Numéro de notice : A2003-095 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/1365881021000026539 En ligne : https://doi.org/10.1080/1365881021000026539 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22391
in International journal of geographical information science IJGIS > vol 17 n° 4 (june 2003) . - pp 299 - 319[article]Réservation
Réserver ce documentExemplaires (2)
Code-barres Cote Support Localisation Section Disponibilité 079-03041 RAB Revue Centre de documentation En réserve L003 Disponible 079-03042 RAB Revue Centre de documentation En réserve L003 Disponible