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.     

The Air-Coastal Sea Chemical Exchange: A Case Study on the New Jersey Coast

The coastal marine atmosphere adjacent to large urban and industrial centers is in general strongly impacted by pollution emissions, resulting in high loading of pollutants in the ambient air. Among the airborne substances are certain trace elements from a variety of emission sources that can serve as micronutrients to marine organisms in coastal waters. High concentrations of such elements in coastal air can result in enhanced air-to-sea deposition fluxes to coastal waters. They could also be transported over the open ocean, affecting the composition of the remote marine atmosphere and then ocean ecosystems. To provide better understanding of the extent of air-to-sea deposition processes on the New Jersey coast, a heavily polluted coastal region on the US East Coast, a synthesis of observation data was carried out for selected trace elements, including Fe, Cd, Cr and Cu, derived from measurements of both size-segregated and bulk aerosol particles, as well as precipitation around the New Jersey coast. The atmospheric input of Hg was also estimated based on measurement data. Results indicated that the total deposition fluxes of most trace elements were higher in Northern coastal NJ compared to Southern coastal NJ, reflecting the differences in the source strengths of these element emissions between the two coastal regions. Dry deposition processes were more significant for common dust-derived elements, particularly Fe and Al, compared with their wet deposition fluxes. However, the processes of precipitation scavenging appeared to be more important for the elements that were often enriched in fine particles including Zn, Cu, Pb and Ni. The removal of Hg from the ambient air was overwhelmingly dominated by atmospheric wet deposition. In the future, atmospheric measurements at more sites on the NJ coast should be performed simultaneously to reduce the spatial and temporal uncertainties associated with atmospheric deposition fluxes estimated in this study.     

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.     

3rd Regional Symposium on Landslides in the Adriatic-Balkan Region (3rd ReSyLAB)—a final report

The 3rd Regional Symposium on Landslides in the Adriatic-Balkan Region (3rd ReSyLAB) was held in Ljubljana, Slovenia, from June 11 to 13, 2017, with 70 participants from nine countries (Austria, Bosnia and Hercegovina, Croatia, Czech Republic, Italy, Republic of Macedonia, Serbia, Slovenia, Spain)—scientists, engineers, researchers, students, experts, politicians, and other decision-makers working in the area of landslide risk reduction in the region. The ReSyLAB is a biannual event organized by the Adriatic-Balkan Network of the International Consortium on Landslides (ICL ABN). Being an important form of activities of this ICL regional network comprising of six ICL members from four countries, it was also a contribution of the International Consortium on Landslides (ICL) to the implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030. This article reports on the main outcomes of the 3rd ReSyLAB Symposium. Altogether, 41 abstracts were published in the symposium book of abstracts, and the symposium proceedings with over 20 reviewed full papers are under preparation to be printed early in 2018. During the 3rd ReSyLAB, a five invited keynote lectures have been presented, and 28 oral presentations are given to the audience. An important part of the symposium was a Round Table entitled “Enhancing cooperation between landslide research community and end users.” On the last day of the symposium, over 30 experts participated in two post-symposium study tours in Slovenia.     

Implementing landslide path dependency in landslide susceptibility modelling

Landslide susceptibility modelling—a crucial step towards the assessment of landslide hazard and risk—has hitherto not included the local, transient effects of previous landslides on susceptibility. In this contribution, we implement such transient effects, which we term “landslide path dependency”, for the first time. Two landslide path dependency variables are used to characterise transient effects: a variable reflecting how likely it is that an earlier landslide will have a follow-up landslide and a variable reflecting the decay of transient effects over time. These two landslide path dependency variables are considered in addition to a large set of conditioning attributes conventionally used in landslide susceptibility. Three logistic regression models were trained and tested fitted to landslide occurrence data from a multi-temporal landslide inventory: (1) a model with only conventional variables, (2) a model with conventional plus landslide path dependency variables, and (3) a model with only landslide path dependency variables. We compare the model performances, differences in the number, coefficient and significance of the selected variables, and the differences in the resulting susceptibility maps. Although the landslide path dependency variables are highly significant and have impacts on the importance of other variables, the performance of the models and the susceptibility maps do not substantially differ between conventional and conventional plus path dependent models. The path dependent landslide susceptibility model, with only two explanatory variables, has lower model performance, and differently patterned susceptibility map than the two other models. A simple landslide susceptibility model using only DEM-derived variables and landslide path dependency variables performs better than the path dependent landslide susceptibility model, and almost as well as the model with conventional plus landslide path dependency variables—while avoiding the need for hard-to-measure variables such as land use or lithology. Although the predictive power of landslide path dependency variables is lower than those of the most important conventional variables, our findings provide a clear incentive to further explore landslide path dependency effects and their potential role in landslide susceptibility modelling.     

Comparison of different models of water quality index in the assessment of surface water quality

The method of water quality index is widely used in evaluation of the surface water quality because of its capability to summarize a number of water quality parameters into one numeric value, along with defined scale of water quality range. The current investigation includes application of modified model for calculating water quality index values, generated using experimental data and literary models. Software was created using modular design. Fourteen physical, chemical and biological parameters representing water quality state along with the assigned weights were elected. Comparison between models generated based on Serbian and American models of water quality index was done. Selected parameters differ mutually in number of parameters used in calculation of index, as well as in values of the weighting factors. In order to enable an efficient water quality analysis and to reconcile the requirements of both Serbian and American model, two software solutions were generated and processed on the example of the water quality of the Danube River in Serbia. Danube water quality was assessed at seventeen measuring locations along the river flow. Index values obtained from the two generated software applications were compared with the results of the official Serbian online calculator. Water quality determined using new generated models shows stricter approach and one class lower water quality compared to the existing Serbian model. Therefore, modular and open-generated simulation software is of great significance for the comparison and testing of different water quality models, not just those two shown in this study.