Landscape units estimation in WorldView-2 images by using segmented urban areas, green areas and water bodies for monitoring variation/evolution of cities

Alejandro Ramirez, Erwin Dianderas, Guillermo Kemper

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

This work proposes a method to estimate landscape units contained in a region (using satellite WorldView-2 imagery as input) for urban planning. Number of landscape units contained in a region and their extension are estimated by a graph-based segmentation algorithm while the composition of each landscape unit is estimated by a modular neural network. The proposed method, despite of the subjectivity of what represents a landscape unit, achieves the following results: vegetation estimation accuracy: 99.58%, water estimation accuracy: 98.08%, urban area estimation accuracy: 90.38% and soil estimation accuracy: 90.25%, over 2400 testing pixels (600 pixels/image-4 satellite images).

Idioma originalInglés
Título de la publicación alojada2015 20th Symposium on Signal Processing, Images and Computer Vision, STSIVA 2015 - Conference Proceedings
EditoresPedro Vizcaya Guarin, Lorena Garcia Posada
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781467394611
DOI
EstadoPublicada - 16 nov. 2015
Publicado de forma externa
Evento20th Symposium on Signal Processing, Images and Computer Vision, STSIVA 2015 - Bogota, Colombia
Duración: 2 set. 20154 set. 2015

Serie de la publicación

Nombre2015 20th Symposium on Signal Processing, Images and Computer Vision, STSIVA 2015 - Conference Proceedings

Conferencia

Conferencia20th Symposium on Signal Processing, Images and Computer Vision, STSIVA 2015
País/TerritorioColombia
CiudadBogota
Período2/09/154/09/15

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