Precise classification of coastal benthic habitats using high resolution Worldview-2 imagery

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 2015-November, Issue , 2015, Pages 2307-2310

  Marcello, J ^a   Eugenio, F ^a   Marques, F ^b   Martin, J ^a  

^a UNIVERSITY OF LAS PALMAS DE GRAN CANARIA   (Spain)

^b UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

Author keywords

benthic classification; seagrass; SVM; Worldview 2

Indexed keywords

EID: 84962504506     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2015.7326269     Document Type: Conference Paper

References (10)

1. M. Lyons, S. Phinn and C. Roelfsema, "Integrating Quickbird multi-spectral satellite and field data: Mapping bathymetry, seagrass cover, seagrass species and change in Moreton bay, Australia in 2004 and 2007, " Remote Sensing, vol. 3, pp. 42-64, 2011.
2. Gobierno de Canarias. Plan Regional de Ordenación de la Acuicultura de Canarias. Tomo I: Memoria de Información del Medio Natural Terrestre y Marino, December 2013.
3. Martinez, J., Análisis espacio-temporal de las praderas de Cymodocea nodosa (Ucria) Ascherson en la isla de Gran Canaria, Master Thesis, Universidad de Las Palmas de Gran Canarias, Dec. 2011.
4. F. Eugenio, J. Martin, J. Marcello, and E. Fraile-Nuez, "Environmental monitoring of El Hierro Island submarine volcano, by combining low and high resolution satellite imagery, " International Journal of Applied Earth Observation and Geoinformation, vol. 29, pp. 53-66, 2014.
5. Martin, J., F. Eugenio, and J. Marcello Estudio, Implementación y validación de algoritmos para la cartografía de vegetación béntica (sebadales) a partir de las imágenes corregidas del satélite Worldview 2, Informe Final de la Fase 5 del convenio de colaboración Observatorio Ambiental de Granadilla y Universidad de Las Palmas de Gran Canaria, Febrero 2013.
6. G. Vivone, L. Alparone, J. Chanussot, M. Dalla Mura, A. Garzelli, G. Licciardi, Restaino and L. Wald, "A Critical Comparison Among Pansharpening Algorithms, " IEEE Transactions on Geosciences and Remote Sensing, v. 53, n. 5, 2015.
7. Tso, B. and P. M. Mather, Classification Methods for Remotely Sensed Data, Taylor and Francis Inc., New York, 2009.
8. G. Mountrakis, J. Im and C. Ogole, "Support vector machines in remote sensing: A review, " ISPRS Journal of Photogrammetry and Remote Sensing, vol. 66, pp. 247-259, 2011.
9. T. Kavzoglu and I. Colkesen, "A Kernel Functions Analysis for Support Vector Machines for Land Cover Classification, " International Journal of Applied Earth Observation and Geoinformation, vol. 11-5, pp. 352-359, 2009.
10. X. Yang, "Parameterizing Support Vector Machines for Land Cover Classification, " Photogrammetric Engineering and Remote Sensing, vol. 77-1, pp. 27-37, 2011.