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Darius Phiri, Matamyo Simwanda, Vincent Nyirenda, Yuji Murayama and Manjula Ranagalage
Decision tree (DT) algorithms are important non-parametric tools used for land cover classification. While different DTs have been applied to Landsat land cover classification, their individual classification accuracies and performance have not been comp...
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Sante Francesco Rende, Alessandro Bosman, Rossella Di Mento, Fabio Bruno, Antonio Lagudi, Andrew D. Irving, Luigi Dattola, Luca Di Giambattista, Pasquale Lanera, Raffaele Proietti, Luca Parlagreco, Mascha Stroobant and Emilio Cellini
In this study, we present a framework for seagrass habitat mapping in shallow (5?50 m) and very shallow water (0?5 m) by combining acoustic, optical data and Object-based Image classification. The combination of satellite multispectral images-acquired fr...
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Ugur Alganci
Uncontrolled and continuous urbanization is an important problem in the metropolitan cities of developing countries. Urbanization progress that occurs due to population expansion and migration results in important changes in the land cover characteristic...
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Isabel Luisa Castillejo-González, Cristina Angueira, Alfonso García-Ferrer and Manuel Sánchez de la Orden
This paper presents an object-based approach to mapping a set of landforms located in the fluvio-eolian plain of Rio Dulce and alluvial plain of Rio Salado (Dry Chaco, Argentina), with two Landsat 8 images collected in summer and winter combined with top...
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Isabel Luisa Castillejo-González
This study sought to verify whether remote sensing offers the ability to efficiently delineate olive tree canopies using QuickBird (QB) satellite imagery. This paper compares four classification algorithms performed in pixel- and object-based analyses. T...
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