Priestorová analýza dát z povrchového zberu na lokalite Vráble-Fidvár

The goal of this study is to introduce selected methods of spatial analysis and their contribution to evaluation of fieldwalking data. Spatial analysis encompasses various methods suitable for identification, objective evaluation and visualization of spatial patterns which are present in obtained data. This article primarily deals with sampled data, collected during a 2007 fieldwalking campaign. The dataset consisting of potsherds was spatially autocorrelated, using the global and local Moran’s I coefficient, which was used to identify clusters of finds. Spatial pattern of the settlement was visualised by geostatistical interpolation method – kriging.

Study of Spatial Distribution of Greenhouse gases (methane gas) Over Iraq using Geostatistical Analysis

Wetlands are one of the most important natural resources on Earth. Marshes are important wintering and resting area for migratory water birds and other migratory birds. Historical data on bird migration in the Marshes suggest that they were one of the largest wintering areas for migratory water birds in the Middle East. The Iraqi marshlands lies in the floodplain which is created by the Tigris-Euphrates river system in the lower part Mesopotamia basin. The existence of water vapor, carbon dioxide, methane and ozone in the troposphere makes surface of our planet habitable. The greenhouse gases absorb thermal radiation and also emit these wavelengths, making the mean surface temperature of the earth higher, and contribute to global warming. Human activities produce large amounts of greenhouse gases, like carbon dioxide, methane, ozone and others. Methane is produced by the decomposition of plants in wetlands. Geostatistical interpolation methods are adopted in this paper. We use the analyst in ArcGIS to apply cross-validation. The cross-validation calculate some criteria to insure the accuracy of predictions made using the ordinary kriging method. Maps were created for methane over Iraq. Cross validation errors were calculated using ArcGIS. The produced maps assure that lower Mesopotamian basin have high concentration of Methane gas which make it as a wintering and resting area for migratory water birds.

Terrain Proxy-Based Site Classification for Seismic Zonation in North Korea within a Geospatial Data-Driven Workflow

Numerous seismic activities occur in North Korea. However, it is difficult to perform seismic hazard assessment and obtain zonal data in the Korean Peninsula, including North Korea, when applying parametric or nonparametric methods. Remote sensing can be implemented for soil characterization or spatial zonation studies on irregular, surficial, and subsurface systems of inaccessible areas. Herein, a data-driven workflow for extracting the principal features using a digital terrain model (DTM) is proposed. In addition, geospatial grid information containing terrain features and the average shear wave velocity in the top 30 m of the subsurface (VS30) are employed using geostatistical interpolation methods; machine learning (ML)-based regression models were optimized and VS30-based seismic zonation in the test areas in North Korea were forecasted. The interrelationships between VS30 and terrain proxy (elevation, slope, and landform class) in the training area in South Korea were verified to define the input layer in regression models. The landform class represents a new proxy of VS30 and was subgrouped according to the correlation with grid-based VS30. The geospatial grid information was generated via the optimum geostatistical interpolation method (i.e., sequential Gaussian simulation (SGS)). The best-fitting model among four ML methods was determined by evaluating cost function-based prediction performance, performing uncertainty analysis for the empirical correlations of VS30, and studying spatial correspondence with the borehole-based VS30 map. Subsequently, the best-fitting regression models were designed by training the geospatial grid in South Korea. Then, DTM and its terrain features were constructed along with VS30 maps for three major cities (Pyongyang, Kaesong, and Nampo) in North Korea. A similar distribution of the VS30 grid obtained using SGS was shown in the multilayer perceptron-based VS30 map.

3D Probabilistic Modelling and Uncertainty Analysis of Glacial and Post-Glacial Deposits of the City of Saguenay, Canada

Knowledge of the stratigraphic architecture and geotechnical properties of surficial soil sediments is essential for geotechnical risk assessment. In the Saguenay study area, the Quaternary deposits consist of a basal till layer and heterogeneous post-glacial deposits. Considering the stratigraphic setting and soil type heterogeneity, a multistep stochastic methodology is developed for 3D geological modelling and quantification of the associated uncertainties. This methodology is adopted for regional studies and involves geostatistical interpolation and simulation methods. Empirical Bayesian kriging (EBK) is applied to generate the bedrock topography map and determine the thickness of the till sediments and their uncertainties. The locally varying mean and variance of the EBK method enable accounting for data complexity and moderate nonstationarity. Sequential indicator simulation is then performed to determine the occurrence probability of the discontinuous post-glacial sediments (clay, sand and gravel) on top of the basal till layer. The individual thickness maps of the discontinuous soil layers and uncertainties are generated in a probabilistic manner. The proposed stochastic framework is suitable for heterogeneous soil deposits characterised with complex surface and subsurface datasets.

Rainfall estimates from opportunistic sensors in Germany across spatio-temporal scales – Geostatistical interpolation framework

<p>Precipitation - highly variable in space and time - is the most important input for many hydrological models. As these models become more and more detailed in space and time, high-resolution input data are required. Especially for modeling and prediction in fast reacting catchments, such as urban catchment areas, a higher space-time resolution is needed than the current ground measurement networks operated by national weather services usually provide. With the increasing number and availability of opportunistic sensors such as commercial microwave links (CMLs) and personal weather stations (PWS) in recent years, new opportunities for measuring meteorological data are emerging.</p><p>We developed a geostatistical interpolation framework which allows a combination of different opportunistic sensors and their specific features and geometric properties, e.g. point and line information. In this framework, a combined kriging approach is introduced, taking into account not only the point information of a reliable primary network, e.g., from national weather services, but also the higher uncertainty of the PWS- and CML-based precipitation. The path-averaged information of the CMLs is included through a block kriging-type approach.</p><p>The methodology was applied for two 7-months periods in Germany using an hourly temporal and a 1x1 km spatial resolution. By incorporating CMLs and PWS, the Pearson correlation could be increased from 0.56 to 0.73 compared to using only primary network for interpolation. The resulting precipitation maps also provided good agreement compared to gauge adjusted radar products.</p>

Tectonic insight and 3-D modelling of the Lusi (Java, Indonesia) mud edifice through gravity analyses

SUMMARY Lusi is a sediment-hosted hydrothermal system located near Sidoarjo in Central Java, Indonesia, and has erupted continuously since May 2006. This mud eruption extends over a surface of ∼7 km2, and is framed by high containment dams. The present study investigates the geometry of the subsurface structures using a detailed gravimetric model to visualize in 3-D the Lusi system and surrounding lithologies. The obtained residual Bouguer anomaly map, simulated through geostatistical interpolation methods, supports the results of previous deformation studies. The negative gravity anomaly zones identified at Lusi are interpreted as fractured areas through which fluids can ascend towards the surface. A 3-D detailed geological model of the area was constructed with Geomodeller™ to highlight the main features. This model relies on the structures’ density contrasts, the interpreted residual Bouguer anomaly map, and geological data from previous authors. 3-D algorithms were used to calculate the gravity response of the model and validate it by inverse methods. The final output is a gravity constrained 3-D geological model of the Lusi mud edifice. These results provide essential details on the Lusi subsurface and may be useful for possible future geothermal resource exploitation and for the risk mitigation plans related to the maintenance of the man-made framing embankment.

Geospatial Situation Analysis for the Prediction of Possible Cases of Suicide Using EBK

This research presents the application of Empirical Bayesian Kriging, a geostatistical interpolation method. The case study is about suicide prevention. The dataset is composed of more than one million records, obtained from the report database of the Emergency Service 911 of the Mexican State of Aguascalientes. The purpose is to get prediction surfaces, probability, and standard error prediction for completed suicide cases. Here, the variations in the environment of suicide cases are relative to and dependent on economic, social, and cultural phenomena.