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http://hdl.handle.net/10553/69802
| Título: | Evaluation of hyperspectral classification maps in heterogeneous ecosystem | Autores/as: | Ibarrola-Ulzurrun, Edurne Marcello, Javier Gonzalo Martin,Consuelo Chanussot, Jocelyn |
Clasificación UNESCO: | 220990 Tratamiento digital. Imágenes | Palabras clave: | Binary Partition Tree Casi Sensor Ecosystem Management Hyperspectral Imagery Support Vector Machine |
Fecha de publicación: | 2018 | Proyectos: | Procesado Avanzado de Datos de Teledetección Para la Monitorización y Gestión Sostenible de Recursos Marinos y Terrestres en Ecosistemas Vulnerables. | Publicación seriada: | IEEE International Geoscience and Remote Sensing Symposium proceedings | Conferencia: | IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2018) | Resumen: | Ecosystem management and monitoring are essential to preserve natural resources. Hyperspectral imagery (HSI) is a useful tool to obtain accurate classification maps, providing significant level of detail. Thus, traditional and novel methodologies based on pixel and object classification approaches are compared and evaluated in a homogeneous and mixed vulnerable ecosystem. Considering the challenging ecosystem, all classifications successfully resulted in high OA (higher than 82%), showing that HSI is very useful providing accurate vegetation maps to evaluate and monitor the ecosystems in a faster and economic way. | URI: | http://hdl.handle.net/10553/69802 | ISBN: | 9781538671504 | ISSN: | 2153-6996 | DOI: | 10.1109/IGARSS.2018.8518308 | Fuente: | IEEE International Geoscience and Remote Sensing Symposium proceedings [2153-6996],v. 2018-July, p. 5764-5767 |
| Colección: | Actas de congresos |
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