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A data mining approach for evaluation of optimal time-series of MODIS data for land cover mapping at a regional level / Fuqun Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 84 (October 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 84 (October 2013) . - pp 114 - 129 Titre : A data mining approach for evaluation of optimal time-series of MODIS data for land cover mapping at a regional level Type de document : Article/Communication Auteurs : Fuqun Zhou, Auteur ; Aining Zhang, Auteur ; Lawrence Townley-Smith, Auteur Année de publication : 2013 Article en page(s) : pp 114 - 129 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] carte d'occupation du sol [Termes IGN] exploration de données géographiques [Termes IGN] image Terra-MODIS [Termes IGN] indice de végétation [Termes IGN] occupation du sol [Termes IGN] série temporelle Résumé : (Auteur) Optical Earth Observation data with moderate spatial resolutions, typically MODIS (Moderate Resolution Imaging Spectroradiometer), are of particular value to environmental applications due to their high temporal and spectral resolutions. Time-series of MODIS data capture dynamic phenomena of vegetation and its environment, and are considered as one of the most effective data sources for land cover mapping at a regional and national level. However, the time-series, multiple bands and their derivations such as NDVI constitute a large volume of data that poses a significant challenge for automated mapping of land cover while optimally utilizing the information it contains. In this study, time-series of 10-day cloud-free MODIS composites and its derivatives – NDVI and vegetation phenology information, are fully assessed to determine the optimal data sets for deriving land cover. Three groups of variable combinations of MODIS spectral information and its derived metrics are thoroughly explored to identify the optimal combinations for land cover identification using a data mining tool. The results, based on the assessment using time-series of MODIS data, show that in general using a longer time period of the time-series data and more spectral bands could lead to more accurate land cover identification than that of a shorter period of the time-series and fewer bands. However, we reveal that, with some optimal variable combinations of few bands and a shorter period of time-series data, the highest possible accuracy of land cover classification can be achieved. Numéro de notice : A2013-520 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.07.008 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.07.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32657 [article]

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