The Late Cretaceous Klepa basalts in Macedonia (FYROM)—Constraints on the final stage of Tethys closure in the Balkans

The waning stage(s) of the Tethyan ocean(s) in the Balkans are not well understood. Controversy centres on the origin and life‐span of the Cretaceous Sava Zone, which is allegedly a remnant of the last oceanic domain in the Balkan Peninsula, defining the youngest suture between Eurasia‐ and Adria‐derived plates. In order to investigate to what extent Late‐Cretaceous volcanism within the Sava Zone is consistent with this model we present new age data together with trace‐element and Sr–Nd–Pb isotope data for the Klepa basaltic lavas from the central Balkan Peninsula. Our new geochemical data show marked differences between the Cretaceous Klepa basalts (Sava Zone) and the rocks of other volcanic sequences from the Jurassic ophiolites of the Balkans. The Klepa basalts mostly have Sr–Nd–Pb isotopic and trace‐element signatures that resemble enriched within‐plate basalts substantially different from Jurassic ophiolite basalts with MORB, BAB and IAV affinities. Trace‐element modelling of the Klepa rocks indicates 2%–20% polybaric melting of a relatively homogeneously metasomatised mantle source that ranges in composition from garnet lherzolite to ilmenite+apatite bearing spinel–amphibole lherzolite. Thus, the residual mineralogy is characteristic of a continental rather than oceanic lithospheric mantle source, suggesting an intracontinental within‐plate origin for the Klepa basalts. Two alternative geodynamic models are internally consistent with our new findings: (1) if the Sava Zone represents remnants of the youngest Neotethyan Ocean, magmatism along this zone would be situated within the forearc region and triggered by ridge subduction; (2) if the Sava Zone delimits a diffuse tectonic boundary between Adria and Europe which had already collided in the Late Jurassic, the Klepa basalts together with a number of other magmatic centres represent volcanism related to transtensional tectonics.     

Silver and silver microparticles of the Cretaceous-Paleogene boundary sediment of Fish Clay Højerup (Stevns Klint,Denmark)

We report the occurrence of micrometer-sized silver particles in the red (“impact” or “ejecta”) layer of the Fish Clay. These appear to be embedded into the biogenic/abiogenic calcite matrix. Energy dispersive X-ray analysis indicates that these microparticles are composed of pure silver (>99% of the total weight). Scanning electron microscopy images reveal irregular and predominantly rounded shapes with rugged surfaces. Numerous silver microparticles are spherical, and some exhibit dendritic textures. These microparticles were probably originated during the Chicxulub asteroid impact event, or immediately afterwards, and dispersed globally.     

Examination of physical processes of convective cell evolved from a MCS — Using a different model initialization

The present study is focused on examination of the physical processes of convective cell evolved from a MCS occurred on 4 November 2011 over Genoa, Italy. The Quantitative Precipitation Forecasts (QPF) have been performed using WRF v3.6 model under different configurations and cloud permitting simulations. The results indicate underestimation of the amount of precipitation and spatial displacement of the area with a peak 24-h accumulated rainfall in (mm). Our main objective in the research is to test the cloud model ability and performance in simulation of this particular case. For that purpose a set of sensitivity experiments under different model initializations and initial data have been conducted. The results also indicate that the merging process apparently alters the physical processes through low- and middle-level forcing, increasing cloud depth, and enhancing convection. The examination of the microphysical process simulated by the model indicates that dominant production terms are the accretion of rain by graupel and snow, probabilistic freezing of rain to form graupel and dry and wet growth of graupel. Experiment under WRF v3.6 model initialization has shown some advantage in simulation of the physical processes responsible for production and initiation of heavy rainfall compared to other model runs. Most of the precipitation came from ice-phase particles-via accretion processes and the graupel melting at temperature T₀ ≥ 0°C. The rainfall intensity and accumulated rainfall calculated by the model closely reflect the amount of rainfall recorded. Thus, the main benefit is to better resolve convective showers or storms which, in extreme cases, can give rise to major flooding events. In such a way, this model may become major contributor to improvements in weather analysis and small-scale atmospheric predictions and early warnings of such subscale processes.     

Modeling Urban Land Use Changes Using Support Vector Machines

Support Vector Machines (SVM) is a machine learning (ML) algorithm commonly applied to the classification of remotely sensing data and more recently for modeling land use changes. However, in most geospatial applications the current literature does not elaborate on specifications of the SVM method with respect to data sampling, attribute selection and optimal parameters choices. Therefore the main objective of this study is to present and investigate the SVM technique for modeling urban land use change. The SVM model building procedure is presented together with the detailed evaluation of the output results with respect to the choice of datasets, attributes and the change of SVM parameters. Geospatial datasets containing nine land use classes and spatial attributes for the Municipality of Zemun, Republic of Serbia were used for years 2001, 2003, 2007 and 2011. The Correlation‐based Feature Subset method, kappa coefficient, Area Under Receiver Operating Characteristic Curve (AUC) and kappa simulation were used to perform the model evaluation and compare the model outputs with the real land use datasets. The obtained results indicate that the SVM‐based models perform better when implementing balanced data sampling, reduced data sets to informative subsets of attributes and properly identify the optimal learning parameters.     

Stratigraphic and lithologic characteristics of Pleistocene fluvial deposits in the Danube and Sava riparian area near Belgrade (Serbia)

The Quaternary sediments in the Danube and Sava riparian area near Belgrade have a considerable thickness. Several categories of deposits (fluvial-lacustrine, fluvial and aeolian) of Pliocene and Quaternary age have been identified. Their thickness, granulometric composition and paleontological features change depending on the distance from the recent Danube and Sava riverbeds. The Pleistocene fluvial deposits are underlain by sediments of the Late Miocene (Sarmatian and Pannonian) or the Plio-Pleistocene age, and are overlain by fluvial-palustrine deposits of the Pleistocene age and recent alluvial deposits. Pleistocene fluvial deposits that form a major part of the Quaternary sediments, have a great significance, since they are proved to be excellent collectors of ground water. Although these deposits are at lower altitudes in the area of Srem, they could be correlated with the high Danube and Morava terraces in Serbia and Drava in Croatia on the basis of their lithologic and paleontological features.     

AMSR-E sea surface temperature (SST) charts enhancement

Microwave satellite images used for retrieving sea surface temperatures often have such distortions as noise and blurring of the thermal fronts. An image processing approach based on the Mumford-Shah model of optimal image approximation is considered for the solution to this problem. We divide images into flat areas and frontal zones, and then process these areas separately. Image fragmentation is based on automatic detection of the thermal front lines. SST enhancement in frontal zones is achieved by using image deconvolution methods. It has been shown that SST errors in high gradient areas reach 1–3 °C. The proposed approach can decrease this discrepancy.     

Integration of GIS and video surveillance

This paper discusses the integration of three-dimensional (3D) geographic information systems (GIS) and video surveillance systems using augmented reality (AR) techniques. The motivation for this integration is to overcome problems faced by conventional video surveillance systems. Explicit information concerning which camera currently monitors what area in such systems is missing; therefore, insight into the situation depends heavily on the operator’s training and experience. To ensure the complete coordination and monitoring of a situation in a system with multiple cameras, it is necessary to introduce a single reference system. GIS arises as a natural solution because it not only provides a solid ground truth but also provides semantic information that can be highly important in certain video surveillance applications. To integrate information into a GIS application, that information must be georeferenced. Based on our previous research regarding the addition of georeferencing information to surveillance video, this paper introduces models that can be applied to help integrate video and GIS. With an analogy to Milgram’s continuum between the real world and virtual reality, and analogous to the augmented reality and augmented virtuality in Milgram’s continuum, two models of integration are defined here: GIS-augmented video and video-augmented GIS. Then, we define the architecture of GIS-based video surveillance based on these proposed integration models, and finally, a prototype is implemented. The implemented prototype serves as a basis for analysing possible applications of real-world systems based on the integration of GIS and video.     

Erosion processes in karst landscapes of the Russian plain northern taiga,based on digital elevation modeling

This paper considers the problems of the potential development of erosion processes in the natural landscapes of northern taiga in the Russian plain. It is considered that in forest ecosystems, erosion processes are slow and are weakly reflected in the terrain. However, the situation changes radically if the vegetation cover integrity is violated, which is inevitable with the modern methods of developing northern territories. Furthermore, global changes in average annual temperatures and the occurrence of karst processes may be the reason behind the development of erosion processes. The authors suggest a method for determining territories with a varying occurrence probability of erosional processes, based on digital elevation modelling. The territory of the Pinezhsky Nature Reserve (Arkhangelsk region) was chosen as the test plot. Direct field studies were previously used to detect exogenous geological processes in this territory. The authors were the first to suggest digital elevation modelling as a method that allows determining the potential danger of erosion in karst landscapes of the northern taiga. The geomorphometric studies resulted in the determination of areas with the greatest and lowest occurrence probability of erosion processes in the Pinezhsky Nature Reserve. It was established that the most significant erosion type was linear erosion, represented by incised river valleys and karst ravines. Sheet erosion is less significant and occurs as sinkholes, local declines, and chasms over the valleys of subterranean rivers.