Seabed mapping in coastal shallow waters using high resolution multispectral and hyperspectral imagery

Coastal ecosystems experience multiple anthropogenic and climate change pressures. To monitor the variability of the benthic habitats in shallow waters, the implementation of effective strategies is required to support coastal planning. In this context, high-resolution remote sensing data can be of fundamental importance to generate precise seabed maps in coastal shallow water areas. In this work, satellite and airborne multispectral and hyperspectral imagery were used to map benthic habitats in a complex ecosystem. In it, submerged green aquatic vegetation meadows have low density, are located at depths up to 20 m, and the sea surface is regularly affected by persistent local winds. A robust mapping methodology has been identified after a comprehensive analysis of different corrections, feature extraction, and classification approaches. In particular, atmospheric, sunglint, and water column corrections were tested. In addition, to increase the mapping accuracy, we assessed the use of derived information from rotation transforms, texture parameters, and abundance maps produced by linear unmixing algorithms. Finally, maximum likelihood (ML), spectral angle mapper (SAM), and support vector machine (SVM) classification algorithms were considered at the pixel and object levels. In summary, a complete processing methodology was implemented, and results demonstrate the better performance of SVM but the higher robustness of ML to the nature of information and the number of bands considered. Hyperspectral data increases the overall accuracy with respect to the multispectral bands (4.7% for ML and 9.5% for SVM) but the inclusion of additional features, in general, did not significantly improve the seabed map quality.Peer ReviewedPostprint (published version

Aplicación de TIG en la generación de indicadores de calidad ambiental de sistemas playa-dunas

Se presentan resultados parciales del subproyecto “Ecosistemas y Biodiversidad: vigilancia de espacios arenosos protegidos de Canarias y África”, incluido en el 'Programa para el desarrollo de redes tecnológicas y de aplicación de datos de teledetección en África Occidental', TELECAN (MAC/3/C181), financiado por el Programa de Cooperación Transnacional Madeira-Azores-Canarias (MAC) 2007/2013. El objetivo principal era definir, mediante el uso de imágenes de satélite, indicadores de calidad ambiental para sistemas playa-dunas, al ser éstos espacios fundamentales en el desarrollo socio-económico de estos territorios, dado su atractivo turístico. En este trabajo se presentan los resultados obtenidos para una de las áreas piloto, Maspalomas (Gran Canaria, islas Canarias). Los indicadores se obtuvieron mediante el procesado de imágenes del satélite WorldView-2, con validación, en 2013, mediante campañas marinas. Asimismo, se utilizaron imágenes de archivo, correspondientes a los años 2010, 2011 y 2012. Estos indicadores se basaron en variables relacionadas con las características físicas y biológicas de las aguas litorales y de las playas y dunas. Los resultados indican una calidad, por lo general, alta y muy alta, tanto para el medio terrestre como para el marino, con superficies dentro de estas categorías del 20,3% y 75,3% y del 26,1% y 70,6%, respectivamente.Esta es una contribución del 'Programa para el desarrollo de redes tecnológicas y de aplicación de datos de teledetección en África Occidental', TELECAN (MAC/3/C181), financiado por el Programa de Cooperación Transnacional Madeira-Azores-Canarias (MAC) 2007/2013

Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations

Peer reviewe

Seabed mapping in coastal shallow waters using high resolution multispectral and hyperspectral imagery

Coastal ecosystems experience multiple anthropogenic and climate change pressures. To monitor the variability of the benthic habitats in shallow waters, the implementation of effective strategies is required to support coastal planning. In this context, high-resolution remote sensing data can be of fundamental importance to generate precise seabed maps in coastal shallow water areas. In this work, satellite and airborne multispectral and hyperspectral imagery were used to map benthic habitats in a complex ecosystem. In it, submerged green aquatic vegetation meadows have low density, are located at depths up to 20 m, and the sea surface is regularly affected by persistent local winds. A robust mapping methodology has been identified after a comprehensive analysis of different corrections, feature extraction, and classification approaches. In particular, atmospheric, sunglint, and water column corrections were tested. In addition, to increase the mapping accuracy, we assessed the use of derived information from rotation transforms, texture parameters, and abundance maps produced by linear unmixing algorithms. Finally, maximum likelihood (ML), spectral angle mapper (SAM), and support vector machine (SVM) classification algorithms were considered at the pixel and object levels. In summary, a complete processing methodology was implemented, and results demonstrate the better performance of SVM but the higher robustness of ML to the nature of information and the number of bands considered. Hyperspectral data increases the overall accuracy with respect to the multispectral bands (4.7% for ML and 9.5% for SVM) but the inclusion of additional features, in general, did not significantly improve the seabed map quality.Peer Reviewe

Vegetation species mapping in a coastal-dune ecosystem using high resolution satellite imagery

Vegetation mapping is a priority when managing natural protected areas. In this context, very high resolution satellite remote sensing data can be fundamental in providing accurate vegetation cartography at species level. In this work, a complete processing methodology has been developed and validated in a complex vulnerable coastal-dune ecosystem. Specifically, the analysis has been carried out using WorldView-2 imagery, which offers spatial and spectral resolutions. A thorough assessment of 5 atmospheric correction models has been performed using real reflectance measures from a field radiometry campaign. To select the classification methodology, different strategies have been evaluated, including additional spectral (23 vegetation indices) and spatial (4 texture parameters) information to the multispectral bands. Likewise, the application of linear unmixing techniques has been tested and abundance maps of each plant species have been generated using the library of spectral signatures recorded during the campaign. After the analysis conducted, a new methodology has been proposed based on the use of the 6S atmospheric model and the Support Vector Machine classification algorithm applied to a combination of different spectral and spatial input data. Specifically, an overall accuracy of 88,03% was achieved combining the corrected multispectral bands plus a vegetation index (MSAVI2) and texture information (variance of the first principal component). Furthermore, the methodology has been validated by photointerpretation and 3 plant species achieve significant accuracy: Tamarix canariensis (94,9%), Juncus acutus (85,7%) and Launaea arborescens (62,4%). Finally, the classified procedure comparing maps for different seasons has also shown robustness to changes in the phenological state of the vegetation

Specific association of HLA-DRB1*03 with anti-carbamylated protein antibodies in patients with rheumatoid arthritis

[Objective]: Recognition of a new type of rheumatoid arthritis (RA)-specific autoantibody, the anti-carbamylated protein antibodies (anti-CarP), has provided an opportunity to improve the management and understanding of RA. The current study was undertaken to assess the relationship between anti-CarP antibodies and HLA-DRB1 alleles in RA. [Methods]: Serum samples were obtained from 3 different collections, comprising a total of 1,126 RA patients. Serum reactivity against in vitro carbamylated fetal calf serum proteins was determined by enzyme-linked immunosorbent assay. HLA-DRB1 alleles were determined using either hybridization techniques or imputation from HLA-dense genotypes. Results of these analyses were combined in a meta-analysis with data from 3 previously reported cohorts. The carrier frequencies of the common HLA-DRB1 alleles were compared between the antibody-positive RA subgroups and the double-negative subgroup of RA patients stratified by anti-citrullinated protein antibody (ACPA)/anti-CarP antibody status, and also between the 4 RA patient strata and healthy controls. [Results]: Meta-analysis was conducted with 3,709 RA patients and 2,305 healthy control subjects. Results revealed a significant increase in frequency of HLA-DRB1*03 carriers in the ACPA-/anti-CarP+ subgroup as compared to ACPA-/anti-CarP- RA patients and healthy controls; this was consistently found across the 6 sample collections. This association of HLA-DRB1*03 with ACPA-/anti-CarP+ RA was independent of the presence of the shared allele (SE) and any other confounders analyzed. No other allele was specifically associated with the ACPA-/anti-CarP+ RA patient subgroup. In contrast, frequency of the SE was significantly increased in the ACPA+/anti-CarP- and ACPA+/anti-CarP+ RA patient subgroups, without a significant distinction between them. Furthermore, some alleles (including HLA-DRB1*03) were associated with protection from ACPA+ RA. [Conclusion]: These findings indicate a specific association of HLA-DRB1*03 with ACPA-/anti-CarP+ RA, suggesting that preferential presentation of carbamylated peptides could be a new mechanism underlying the contribution of HLA alleles to RA susceptibility.Supported by the Instituto de Salud Carlos III and FEDER (grant RD16/0012/0012 to Dr. Balsa, grants PI14/00442 and RD16/0012/0011 to Dr. Gonzalez-Alvaro, and grants RD16/0012/0014 and PI17/01606 to Dr. Gonzalez). Ms Regueiro's work was supported by the Ministerio de Educacion Cultura y Deporte (FPU pre-doctoral fellowship FPU15/03434)Peer reviewe

Epidemiology of surgery associated acute kidney injury (EPIS-AKI): a prospective international observational multi-center clinical study

Purpose: The incidence, patient features, risk factors and outcomes of surgery-associated postoperative acute kidney injury (PO-AKI) across different countries and health care systems is unclear. Methods: We conducted an international prospective, observational, multi-center study in 30 countries in patients undergoing major surgery (> 2-h duration and postoperative intensive care unit (ICU) or high dependency unit admission). The primary endpoint was the occurrence of PO-AKI within 72 h of surgery defined by the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Secondary endpoints included PO-AKI severity and duration, use of renal replacement therapy (RRT), mortality, and ICU and hospital length of stay. Results: We studied 10,568 patients and 1945 (18.4%) developed PO-AKI (1236 (63.5%) KDIGO stage 1500 (25.7%) KDIGO stage 2209 (10.7%) KDIGO stage 3). In 33.8% PO-AKI was persistent, and 170/1945 (8.7%) of patients with PO-AKI received RRT in the ICU. Patients with PO-AKI had greater ICU (6.3% vs. 0.7%) and hospital (8.6% vs. 1.4%) mortality, and longer ICU (median 2 (Q1-Q3, 1-3) days vs. 3 (Q1-Q3, 1-6) days) and hospital length of stay (median 14 (Q1-Q3, 9-24) days vs. 10 (Q1-Q3, 7-17) days). Risk factors for PO-AKI included older age, comorbidities (hypertension, diabetes, chronic kidney disease), type, duration and urgency of surgery as well as intraoperative vasopressors, and aminoglycosides administration. Conclusion: In a comprehensive multinational study, approximately one in five patients develop PO-AKI after major surgery. Increasing severity of PO-AKI is associated with a progressive increase in adverse outcomes. Our findings indicate that PO-AKI represents a significant burden for health care worldwide