RT Journal Article
T1 Hyperspectral sensors as a management tool to prevent the invasion of the exotic cordgrass "Spartina densiflora" in the Doñana wetlands
A1 Bustamante, Javier
A1 Aragonés, David
A1 Afán, Isabel
A1 Luque Palomo, Carlos Javier
A1 Pérez Vázquez, Andrés
A1 Castellanos Verdugo, Eloy Manuel
A1 Díaz Delgado, Carlos
AB We test the use of hyperspectral sensors for the early detection of the invasive densefloweredcordgrass (Spartina densiflora Brongn.) in the Guadalquivir River marshes, SouthwesternSpain. We flew in tandem a CASI-1500 (368–1052 nm) and an AHS (430–13,000 nm) airbornesensors in an area with presence of S. densiflora. We simplified the processing of hyperspectraldata (no atmospheric correction and no data-reduction techniques) to test if these treatments werenecessary for accurate S. densiflora detection in the area. We tested several statistical signal detectionalgorithms implemented in ENVI software as spectral target detection techniques (matched filtering,constrained energy minimization, orthogonal subspace projection, target-constrained interferenceminimized filter, and adaptive coherence estimator) and compared them to the well-known spectralangle mapper, using spectra extracted from ground-truth locations in the images. The targetS. densiflora was easy to detect in the marshes by all algorithms in images of both sensors. The bestmethods (adaptive coherence estimator and target-constrained interference minimized filter) on thebest sensor (AHS) produced 100% discrimination (Kappa = 1, AUC = 1) at the study site and onlysome decline in performance when extrapolated to a new nearby area. AHS outperformed CASI inspite of having a coarser spatial resolution (4-m vs. 1-m) and lower spectral resolution in the visibleand near-infrared range, but had a better signal to noise ratio. The larger spectral range of AHS inthe short-wave and thermal infrared was of no particular advantage. Our conclusions are that it ispossible to use hyperspectral sensors to map the early spread S. densiflora in the Guadalquivir Rivermarshes. AHS is the most suitable airborne hyperspectral sensor for this task and the signal processingtechniques target-constrained interference minimized filter (TCIMF) and adaptive coherence estimator(ACE) are the best performing target detection techniques that can be employed operationally with asimplified processing of hyperspectral images.
PB MDPI
SN 10.3390/rs8121001
SN 2072-4292
YR 2016
FD 2016
LK http://hdl.handle.net/10272/13633
UL http://hdl.handle.net/10272/13633
LA eng
NO Bustamante, J., Aragonés, D., Afán, I., Luque Palomo, C.J., Pérez Vázquez, A., Castellanos Verdugo, E.M., Díaz Delgado, C.: "Hyperspectral sensors as a management tool to prevent the invasion of the exotic cordgrass "Spartina densiflora" in the Doñana wetlands". Remote Sensing. Vol. 8, n. 12, (2016). DOI: 10.3390/rs8121001
NO This study has been funded by the Spanish Ministry of Science and Innovation through the research projects HYDRA (No. CGL2006-02247/BOS) and HYDRA2 (CGL2009-09801/BOS), by the National Parks Authority (Organismo Autonomo de Parques Nacionales) of the Spanish Ministry of Environment to project OAPN 042/2007, and by funding from the European Union (EU) Horizon 2020 research and innovation program under grant agreement No. 641762 to ECOPOTENTIAL project. The Espacio Natural de Donana provided permits for field work in protected areas with restricted access. We are grateful to the Instituto Nacional de Tecnica Aeroespacial (INTA), Spain, for performing the airborne campaign and the geometric correction of the images. J.B. has to acknowledge a sabbatical stay at Pye Laboratory of the Commonwealth Scientific and Research Organization (CSIRO) Marine and Atmospheric Sciences, Australia, and at the Climate Change Cluster (C3) of the University of Technology Sydney, Australia, funded by the Spanish Ministry of Education, during data analysis and writing of this paper. This publication is a contribution from CEIMAR and also a contribution from CEICAMBIO.
DS Repositorio Institucional de la Universidad de Huelva
RD 31 may 2026