Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/47789
Title: Advanced classification of remote sensing high resolution imagery. An application for the management of natural resources
Authors: Ibarrola-Ulzurrun, Edurne 
Marcello, Javier 
Gonzalo Martin,Consuelo 
UNESCO Clasification: 220990 Tratamiento digital. Imágenes
Keywords: Remote sensing
High resolution image
Pansharpening
Orthorectification
OBIA
Issue Date: 2018
Publisher: 1860-949X
Journal: Studies in Computational Intelligence 
Abstract: In the last decades, there has been a decline in ecosystems natural resources. The objective of the study is to develop advanced image processing techniques applied to high resolution remote sensing imagery for the ecosystem conservation. The study area is focused in three ecosystems from The Canary Islands, Teide National Park, Maspalomas Natural Reserve and Corralejo and Islote de Lobos Natural Park. Different pre-processing steps have been applied in order to acquire high quality imagery. After an extensive analysis and evaluation of pansharpening techniques, Weighted Wavelet 'à trous’ through Fractal Dimension Maps, in Teide and Maspalomas scenes, and Fast Intensity Hue Saturation, in Corralejo scene, are used, then, a RPC (Rational Polymodal Coefficients) model performs the orthorectification and finally, the atmospheric correction is carried out by the 6S algorithm. The final step is to generate marine and terrestrial thematic products using advanced classification techniques for the management of natural resources. Accurate thematic maps have already been obtained in Teide National Park. A comparative study of both pixel-based and object-based (OBIA) approaches was carried out, obtaining the most accurate thematic maps in both of them using Support Vector Machine classifier.
URI: http://hdl.handle.net/10553/47789
ISSN: 1860-949X
DOI: 10.1007/978-3-319-58965-7_1
Source: Studies in Computational Intelligence[ISSN 1860-949X],v. 718, p. 1-13
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