RESUMEN
Several gravity cores and vibro-cores were recovered from selected sites in the inner sector of Ría de Ferrol, NW Iberia (Muñoz Sobrino et al., 2021) [1]. These sediment cores were obtained during the surveys ECOMER-2014 and ECOMER-2015, developed from 2014 to 2015 on-board the R/V Mytilus (Consejo Superior de Investigación Científica) and the Amarradores Mil (Amarradores del Puerto y Ría de Ferrol, S.L.), respectively. Sedimentary and other multiproxy data presented here belong to four selected sediment cores located in the innermost part of the study area. Two were recovered using a gravity corer and another two using a vibro-corer. The depth of the cores and samples obtained is referred to the NMMA (the mean sea level in Alicante), which is the Spanish orthometric datum. One half of each core was subjected to non-destructive analysis using an ITRAX core scanner providing X-ray fluorescence (XRF) elemental data. Particle size distribution was characterised by laser diffraction. For radiocarbon dating, well-preserved articulated valves, small remains of wood and very organic bulk sediment from one location free of biogenic gas were selected. Palynological analyses were performed on selected sections of the sediment. All samples were spiked with Lycopodium spores for absolute palynomorph estimation and analysed using 400x and 600x magnifications. The ratio of dinoflagellate cyst concentrations to pollen, fern spore and dinoflagellate cyst concentrations (D/P ratio, ranging between 0 and 1) was calculated for each sample to show the temporal variation. Combined seismic, lithological, elemental, chronological and palynological data enable reconstructing the environmental changes that occurred during the local marine transgression. Besides, the combination of evidence identified may also be applied to other areas or periods in order to perform local reconstructions of changing coastal ecosystems. This type of high-resolution spatial-temporal reconstructions of past changes in estuarine environments may be a valuable tool for modelling, predicting and managing the changes and threats linked to the global warming and sea-level rise associated.
RESUMEN
Although remote sensing is increasingly in use for habitat mapping, traditional image classification methods tend to suffer shortcomings due to non-normality of spectral signatures, as well as overlapping and heterogeneity in radiometric responses of natural and semi natural vegetation. Methods using non-parametric classifiers and object-oriented analysis have been suggested as possible solutions for overcoming these limitations. In this paper, we aimed at evaluating the performance of some of these techniques for the European Natura 2000 network of protected areas habitats mapping. For this purpose, we tested different methods of supervised image classification in the Northern Mountains of Galicia, Spain, an area included in the Natura 2000 network, which is characterized by a highly heterogeneous landscape. Methods involved the use of maximum likelihood and nearest neighbour decision rules in per-pixel and per-object classification analyses on Landsat TM imagery. Per-object classifications were completed using the segment mean and segment means plus standard deviation feature spaces. The results showed the existence of significant differences in the accuracies for the different methodologies, their strengths and weaknesses and identified the most adequate approach for habitat mapping. Analyses pointed out that significant improvements in accuracy were achieved only under certain combinations of per-object analysis, non-parametric classifiers and high dimensionality feature space.