Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
Fusion of High Resolution Multispectral Imagery in Vulnerable Coastal and Land Ecosystems
Year:2017
Research Areas
  • Remote sensing
Information
Abstract
Ecosystems provide a wide variety of useful resources that enhance human welfare, but these resources are declining due to climate change and anthropogenic pressure. In this work, three vulnerable ecosystems, including shrublands, coastal areas with dunes systems and areas of shallow water, are studied. As far as these resources? reduction is concerned, remote sensing and image processing techniques could contribute to the management of these natural resources in a practical and cost-effective way, although some improvements are needed for obtaining a higher quality of the information available. An important quality improvement is the fusion at the pixel level. Hence, the objective of this work is to assess which pansharpening technique provides the best fused image for the different types of ecosystems. After a preliminary evaluation of twelve classic and novel fusion algorithms, a total of four pansharpening algorithms was analyzed using six quality indices. The quality assessment was implemented not only for the whole set of multispectral bands, but also for the subset of spectral bands covered by the wavelength range of the panchromatic image and outside of it. A better quality result is observed in the fused image using only the bands covered by the panchromatic band range. It is important to highlight the use of these techniques not only in land and urban areas, but a novel analysis in areas of shallow water ecosystems. Although the algorithms do not show a high difference in land and coastal areas, coastal ecosystems require simpler algorithms, such as fast intensity hue saturation, whereas more heterogeneous ecosystems need advanced algorithms, as weighted wavelet ?à trous? through fractal dimension maps for shrublands and mixed ecosystems. Moreover, quality map analysis was carried out in order to study the fusion result in each band at the local level. Finally, to demonstrate the performance of these pansharpening techniques, advanced Object-Based (OBIA) support vector machine classification was applied, and a thematic map for the shrubland ecosystem was obtained, which corroborates wavelet ?à trous? through fractal dimension maps as the best fusion algorithm for this ecosystem.
International
Si
JCR
Si
Title
Sensors
ISBN
1424-8220
Impact factor JCR
2,033
Impact info
Datos JCR del año 2015
Volume
17
10.3390/s17020228
Journal number
2
From page
228
To page
238
Month
SIN MES
Ranking
36/75
Participants
  • Autor: Eduren Ibarrola (Universidad de las Palmas de gran Canarias)
  • Autor: Consuelo Gonzalo Martin (UPM)
  • Autor: Javier Marcello (Universidad de las Palmas de gran Canarias)
  • Autor: Angel Mario García Pedrero (UPM)
  • Autor: Dionisio Rodriguez (Universidad de las Palmas de gran Canarias)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Minería de Datos y Simulación (MIDAS)
  • Centro o Instituto I+D+i: Centro de tecnología Biomédica CTB
  • Departamento: Arquitectura y Tecnología de Sistemas Informáticos
S2i 2020 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)