RT Journal Article
T1 Texture-based analysis of hydrographical basins with multispectral imagery
A1 González Bascoy, Pedro
A1 Suárez Garea, Jorge Alberto
A1 Blanco Heras, Dora
A1 Argüello Pedreira, Francisco
A1 Ordóñez Iglesias, Álvaro
K1 Vegetation
K1 Image segmentation
K1 Image classification
K1 Data modeling
K1 Multispectral imaging
K1 Sensors
K1 Unmanned aerial vehicles
K1 Multispectral
K1 Classification
K1 Textures
K1 Superpixel
K1 Support vector machine
AB In this paper the problem of studying the presence of different vegetation species and artificial structures in the riversides by using multispectral remote sensing information is studied. The information provided contributes to control the water resources in a region in northern Spain called Galicia. The problem is solved as a supervised classification computed over five-band multispectral images obtained by an Unmanned Aerial Vehicle (UAV). A classification scheme based on the extraction of spatial, spectral and textural features previous to a hierarchical classification by Support Vector Machine (SVM) is proposed. The scheme extracts the spatial-spectral information by means of a segmentation algorithm based on superpixels and by computing morphological operations over the bands of the image in order to generate an Extended Morphological Profile (EMP). The texture features extracted help in the classification of vegetation classes as the spatial-spectral features for these classes are not discriminant enough. The classification is computed over segments instead of pixels, thus reducing the computational cost. The experimental results over four real multispectral datasets from Galician riversides show that the proposed scheme improves over a standard classification method achieving very high accuracy results
PB SPIE
SN 978-151063001-7
SN 0277-786X
YR 2019
FD 2019
LK http://hdl.handle.net/10347/26960
UL http://hdl.handle.net/10347/26960
LA eng
NO Pedro G. Bascoy, Alberto S. Garea, Dora B. Heras, Francisco Argüello, Alvaro Ordóñez, "Texture-based analysis of hydrographical basins with multispectral imagery," Proc. SPIE 11149, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI, 111490Q (21 October 2019). DOI: 10.1117/12.2532760
NO This work was supported in part by the Civil Program UAVs Initiative, promoted by the Xunta de Galicia and developed in partnership with the Babcock company to promote the use of unmanned technologies in civil services.We also have to acknowledge the support by the Consellería de Educación, Universidade e Formación Profesional [grant numbers GRC2014/008, ED431C 2018/19, and ED431G/08], Ministerio de Economía y Empresa, Government of Spain [grant number TIN2016-76373-P] and by Junta de Castilla y León - ERDF (PROPHET Project) [grant number VA082P17]. All are co–funded by the European Regional Development Fund (ERDF)
DS Minerva
RD 23 abr 2026