MORPHOMETRIC ANALYSIS OF KARST DEPRESSIONS ON A MEDITERRANEAN KARST MASSIF

Dolines are the most typical landform in karst landscapes. They play an important role in karst hydrogeology; they are effective sediment traps that provide information about past climates and karst evolution, and can also be indicators of tectonic activity. The morphometic analysis of those depressions can help in their study and interpretation. However, detailed identification and delineation of dolines becomes increasingly difficult when the study area is very large, of limited access or covered by vegetation. Here, we have used a method developed by the authors for automatic identification and delineation of karst depressions based on the use of a pit removal algorithm. Next a complete morphometric analysis of the karst depressions has been carried out. The main advantage of the methodology is that by delineating and identifying the depth of each doline from its rim, many morphometric statistics can be obtained, including the relation of doline depth and area with respect to altitude, the main doline orientations, doline density, the fractal dimension of doline area and frequency, and point field analysis, among others. The results are interpreted from a geomorphological point of view and the mapped dolines can be easily integrated into geomorphological mapping. A case study is presented from the large Sierra Gorda karst massif in southern Spain, where 3100 depressions have been identified. A strong structural control of doline shape and orientation is demonstrated; the main areas of doline density are highlighted and doline size is shown to follow a fractal law.     

Opportunities accruing from the application of public private partnerships in down market urban housing in Kenya

GeoJournal - The purpose of this study was to investigate the opportunities which accrue from application of PPPs in development of down market urban housing in Kenya, hence attracting private...     

Development,urban planning and political decisions. A triad that built territories at risk

Natural Hazards - Chilean geography exposes the country to high-level risks such as earthquakes and tsunamis. The disasters of 1930, 1960, 2010, and 2014 testify to the continuous link between...     

Relationships Between Petrophysical and Mechanical Properties of Certain Calcarenites Used in Building

Mendicino calcarenite was once widely used in traditional constructions by Italy’s foremost stonemasons’ schools. This paper provides a complete physico-mechanical characterization in order to improve understanding of strength and durability properties and so apply that knowledge to conservation and new construction. Stone samples from three lithofacies are taken from the following quarries of Cosenza province: Scannelle in Malito; Cannataro in Carolei; Albanese in San Lucido. Samples are subjected to: X-ray diffraction, mercury intrusion porosimetry, ultrasonic pulse velocity, capillary water absorption, uniaxial compressive, flexural, point load tests with respect to the X, Y, Z axes. Malito samples exhibit creamy colour, better hydric behaviour, low open porosity, reduced water absorption capability, isotropic hydric behaviour, higher fossil abundance (both in number and size) than the lithofacies taken from Carolei and San Lucido, which exhibit whitish colour, greater strength and more homogeneous texture. The greater compactness of Carolei and San Lucido samples can be ascribed to homogeneity and low porosity and their better mechanical properties to textural features. Anisotropy plays an important role. Placing stone samples along the Z axis prevents water intrusion, and improves mechanical strength. Isotropy and compact and heterogeneous fabric in stones result in higher strength and lower water absorption.

     

9000 years of changes in peat organic matter composition in Store Mosse (Sweden) traced using FTIR-ATR

Store Mosse (the ‘Great Bog’ in Swedish) is one of the most extensive bog complexes in southern Sweden (~77 km²), where pioneering palaeoenvironmental research has been carried out since the early 20th century. This includes, for example, vegetation changes, carbon and nitrogen dynamics, peat decomposition, atmospheric metal pollution, mineral dust deposition, dendrochronology, and tephrochronology. Even though organic matter (OM) represents the bulk of the peat mass and its compositional change has the potential to provide crucial ecological information on bog responses to environmental factors, peat OM molecular composition has not been addressed in detail. Here, a 568-cm-deep peat sequence was studied at high resolution, by attenuated reflectance Fourier-transform infrared spectroscopy (FTIR-ATR) in the mid-infrared region (4000–400 cm^–1). Principal components analysis was performed on selected absorbances and change-point modelling was applied to the records to determine the timing of changes. Four components accounted for peat composition: (i) depletion/accumulation of labile (i.e. carbohydrates) and recalcitrant (i.e. lignin and other aromatics, aliphatics, organic acids and some N compounds) compounds, due to peat decomposition; (ii) variations in N compounds and carbohydrates; (iii) residual variation of lignin and organic acids; and (iv) residual variation of aliphatic structures. Peat decomposition showed two main patterns: a long-term trend highly correlated to peat age (r = 0.87), and a short-term trend, which showed five main phases of increased decomposition (at ~8.4–8.1, ~7.0–5.6, ~3.5–3.1, ~2.7–2.1 and ~1.6–1.3 ka) – mostly corresponding to drier climate and its effect on bog hydrology. The high peat accumulation event (~5.6–3.9 ka), described in earlier studies, is characterized by the lowest degree of peat decomposition of the whole record. Given that FTIR-ATR is a quick, non-destructive, cost-effective technique, our results indicate that it can be applied in a systematic way (including multicore studies) to peat research and provide relevant information on the evolution of peatlands.     

Resource Model Updating For Compositional Geometallurgical Variables

In the field of mineral resources extraction, one main challenge is to meet production targets in terms of geometallurgical properties. These properties influence the processing of the ore and are often represented in resource modeling by coregionalized variables with a complex relationship between them. Valuable data are available about geometalurgical properties and their interaction with the beneficiation process given sensor technologies during production monitoring. The aim of this research is to update resource models as new observations become available. A popular method for updating is the ensemble Kalman filter. This method relies on Gaussian assumptions and uses a set of realizations of the simulated models to derive sample covariances that can propagate the uncertainty between real observations and simulated ones. Hence, the relationship among variables has a compositional nature, such that updating these models while keeping the compositional constraints is a practical requirement in order to improve the accuracy of the updated models. This paper presents an updating framework for compositional data based on ensemble Kalman filter which allows us to work with compositions that are transformed into a multivariate Gaussian space by log-ratio transformation and flow anamorphosis. This flow anamorphosis, transforms the distribution of the variables to joint normality while reasonably keeping the dependencies between components. Furthermore, the positiveness of those variables, after updating the simulated models, is satisfied. The method is implemented in a bauxite deposit, demonstrating the performance of the proposed approach.

     

Coastal and estuarine habitat mapping, using LIDAR height and intensity and multi-spectral imagery

The airborne laser scanning LIDAR (LIght Detection And Ranging) provides high-resolution Digital Terrain Models (DTM) that have been applied recently to the characterization, quantification and monitoring of coastal environments. This study assesses the contribution of LIDAR altimetry and intensity data, topographically-derived features (slope and aspect), and multi-spectral imagery (three visible and a near-infrared band), to map coastal habitats in the Bidasoa estuary and its adjacent coastal area (Basque Country, northern Spain). The performance of high-resolution data sources was individually and jointly tested, with the maximum likelihood algorithm classifier in a rocky shore and a wetland zone; thus, including some of the most extended Cantabrian Sea littoral habitats, within the Bay of Biscay. The results show that reliability of coastal habitat classification was more enhanced with LIDAR-based DTM, compared with the other data sources: slope, aspect, intensity or near-infrared band. The addition of the DTM, to the three visible bands, produced gains of between 10% and 27% in the agreement measures, between the mapped and validation data (i.e. mean producer's and user's accuracy) for the two test sites. Raw LIDAR intensity images are only of limited value here, since they appeared heterogeneous and speckled. However, the enhanced Lee smoothing filter, applied to the LIDAR intensity, improved the overall accuracy measurements of the habitat classification, especially in the wetland zone; here, there were gains up to 7.9% in mean producer's and 11.6% in mean user's accuracy. This suggests that LIDAR can be useful for habitat mapping, when few data sources are available. The synergy between the LIDAR data, with multi-spectral bands, produced high accurate classifications (mean producer's accuracy: 92% for the 16 rocky habitats and 88% for the 11 wetland habitats). Fusion of the data enabled discrimination of intertidal communities, such as Corallina elongata, barnacles (Chthamalus spp.), and stands of Spartina alterniflora and Phragmites australis, which presented misclassification when conventional visible bands were used alone. All of these results were corroborated by the kappa coefficient of agreement. The high classification accuracy found here, selecting data sources, highlights the value of integrating LIDAR data with multi-spectral imagery for habitat mapping in the intertidal complex fringe.     

Capabilities of the bathymetric Hawk Eye LiDAR for coastal habitat mapping: A case study within a Basque estuary

The bathymetric LiDAR system is an airborne laser that detects sea bottom at high vertical and horizontal resolutions in shallow coastal waters. This study assesses the capabilities of the airborne bathymetric LiDAR sensor (Hawk Eye system) for coastal habitat mapping in the Oka estuary (within the Biosphere Reserve of Urdaibai, SE Bay of Biscay, northern Spain), where water conditions are moderately turbid. Three specific objectives were addressed: 1) to assess the data quality of the Hawk Eye LiDAR, both for terrestrial and subtidal zones, in terms of height measurement density, coverage, and vertical accuracy; 2) to compare bathymetric LiDAR with a ship-borne multibeam echosounder (MBES) for different bottom types and depth ranges; and 3) to test the discrimination potential of LiDAR height and reflectance information, together with multi-spectral imagery (three visible and near infrared bands), for the classification of 22 salt marsh and rocky shore habitats, covering supralittoral, intertidal and subtidal zones. The bathymetric LiDAR Hawk Eye data enabled the generation of a digital elevation model (DEM) of the Oka estuary, at 2 m of horizontal spatial resolution in the terrestrial zone (with a vertical accuracy of 0.15 m) and at 4 m within the subtidal, extending a water depth of 21 m. Data gaps occurred in 14.4% of the area surveyed with the LiDAR (13.69 km²). Comparison of the LiDAR system and the MBES showed no significant mean difference in depth. However, the Root Mean Square error of the former was high (0.84 m), especially concentrated upon rocky (0.55–1.77 m) rather than in sediment bottoms (0.38–0.62 m). The potential of LiDAR topographic variables and reflectance alone for discriminating 15 intertidal and submerged habitats was low (with overall classification accuracy between 52.4 and 65.4%). In particular, reflectance retrieved for this case study has been found to be not particularly useful for classification purposes. The combination of the LiDAR-based DEM and derived topographical features with the near infrared and visible bands has permitted the mapping of 22 supralittoral, intertidal and subtidal habitats of the Oka estuary, with high overall classification accuracies of between 84.5% and 92.1%, using the maximum likelihood algorithm. The airborne bathymetric Hawk Eye LiDAR, although somewhat limited by water turbidity and wave breaking, provides unique height information obscured from topographic LiDAR and acoustic systems, together with an improvement of the habitat mapping reliability in the complex and dynamic coastal fringe.     

Uncoupled transport of chlorofluorocarbons and anthropogenic carbon in the subpolar North Atlantic

Chlorofluorocarbon (CFC) 11 and 12 transports across the transoceanic World Ocean Circulation Experiment (WOCE) A25 section in the subpolar North Atlantic are derived from an inverse model using hydrographic and ADCP data (Lherminier et al., 2007). CFC and anthropogenic carbon (C_ANT) advective transports contrary to expected are uncoupled: C_ANT is transported northeastwards (82±39 kmol s^?1) mainly within the overturning circulation, while CFC-11 and CFC-12 are transported southwestwards (?24±4 and ?11±2 mol s^?1, respectively) as part of the large-scale horizontal circulation. The main reason for this uncoupled behaviour is the complex CFC vs. C_ANT relation in the ocean, which stems from the contrasting temperature relation for both tracers: more C_ANT dissolves in warmer waters with a low Revelle factor, while CFC’s solubility is higher in cold waters. These results point to C_ANT and CFC having different routes of uptake, accumulation and transport within the ocean, and hence: C_ANT transport would be more sensitive to changes in the overturning circulation strength, while CFC to changes in the East Greenland Current and Labrador Sea Water formation in the Irminger Sea. Additionally, C_ANT and CFCs would have different sensitivities to circulation and climate changes derived from global warming as the slowdown of the overturning circulation, increase stratification due to warming and changes in wind stress.