González Bascoy, PedroSuárez Garea, Jorge AlbertoBlanco Heras, DoraArgüello Pedreira, FranciscoOrdóñez Iglesias, Álvaro2021-09-302021-09-302019Pedro 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: 10.1117/12.2532760978-151063001-70277-786Xhttp://hdl.handle.net/10347/26960In 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 resultsengCopyright 2019 Society of Photo-Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibitedVegetationImage segmentationImage classificationData modelingMultispectral imagingSensorsUnmanned aerial vehiclesMultispectralClassificationTexturesSuperpixelSupport vector machinejournal article10.1117/12.2532760open access