Detailed Land Cover Mapping from Multitemporal Landsat-8 Data of Different Cloud Cover

Abstract : Detailed, accurate and frequent land cover mapping is a prerequisite for several important geospatial applications and the fulfilment of current sustainable development goals. This paper introduces a methodology for the classification of annual high-resolution satellite data into several detailed land cover classes. In particular, a nomenclature with 27 different classes was introduced based on CORINE Land Cover (CLC) Level-3 categories and further analysing various crop types. Without employing cloud masks and/or interpolation procedures, we formed experimental datasets of Landsat-8 (L8) images with gradually increased cloud cover in order to assess the influence of cloud presence on the reference data and the resulting classification accuracy. The performance of shallow kernel-based and deep patch-based machine learning classification frameworks was evaluated. Quantitatively, the resulting overall accuracy rates differed within a range of less than 3%; however, maps produced based on Support Vector Machines (SVM) were more accurate across class boundaries and the respective framework was less computationally expensive compared to the applied patch-based deep Convolutional Neural Network (CNN). Further experimental results and analysis indicated that employing all multitemporal images with up to 30% cloud cover delivered relatively higher overall accuracy rates as well as the highest per-class accuracy rates. Moreover, by selecting 70% of the top-ranked features after applying a feature selection strategy, slightly higher accuracy rates were achieved. A detailed discussion of the quantitative and qualitative evaluation outcomes further elaborates on the performance of all considered classes and highlights different aspects of their spectral behaviour and separability.
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Article dans une revue
Remote Sensing, MDPI, 2018, 10 (8), 〈10.3390/rs10081214〉
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https://hal.inria.fr/hal-01959065
Contributeur : Maria Vakalopoulou <>
Soumis le : mardi 18 décembre 2018 - 14:18:56
Dernière modification le : jeudi 7 février 2019 - 16:34:33

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Christina Karakizi, Konstantinos Karantzalos, Maria Vakalopoulou, Georgia Antoniou. Detailed Land Cover Mapping from Multitemporal Landsat-8 Data of Different Cloud Cover. Remote Sensing, MDPI, 2018, 10 (8), 〈10.3390/rs10081214〉. 〈hal-01959065〉

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