Identification of the factors determining the concentration and spatial distribution of Zn, Pb and Cd in the soils of the non-forest Tatra Mountains (southern Poland)

We investigated trace-metal (TM)––Zn, Pb and Cd––concentrations and spatial distributions in the uppermost layers of non-forest soils from Tatra National Park (West Carpathians). We aimed to determine the main factors affecting the distribution of TMs, as well as the risk they posed to the environment. TM concentrations were compared to the target and intervention values established by the Dutch Ministry. Principle component analysis was used to identify the potential factors affecting TM accumulation, with two-factor analysis being applied to further examine the importance of any given factor. To examine the regularity of the TM distribution, semivariograms were created. The semivariograms of Cd and Pb were similar, suggesting a moderate spatial dependence for these metal concentrations, while the Zn variogram indicated a lack of spatial continuity for this metal. We established that the Zn, Pb and Cd exceeded target levels and at some sites, Cd exceeded the intervention values, posing a strong ecological risk to the environment. Our study confirmed that the parent rock was the most important factor affecting the TM accumulation. The carbonate-free soils differed from carbonate soils in the second important factor affecting TM accumulation, for carbonate-free soils it was location when for carbonate soils–TM content in the parent material. The Zn, Pb and Cd distribution patterns indicated that Cd, but also to a lesser degree Pb and Zn, accumulation mainly resulted from long-range transport from industrialised areas, while the Zn concentrations were also affected by local sources, such as the historical mining of Zn ore.

Leveraging Large Subsurface Data and Associated Uncertainties to Build High Quality 3D Structural Model

Objectives/Scope At brownfield development stage, dealing with diverse and large amount of data makes it challenging to integrate them all in a consistent manner to build a prime structural model. Like many others, the studied field consists of several-stacked reservoirs featuring many faults and close to a thousand drilled wells with vertical, slanted and horizontal trajectories. On top of that, many horizontal wells are targeting thin carbonate layers for which tightly spaced data points often result in conflicting observations. Consequently, horizontal and deviated wells are commonly discarded from structural modelling, leaving substantial and valuable information unused. Some of these wells may be indirectly accounted through the introduction of pseudo-wells, making the modelling workflow tedious, user-dependent and therefore difficult to repeat. Methods, Procedures, Process ’It's better to be approximately right than exactly wrong’ quoted by Carveth Read, 18th century. Accordingly, every physical measurement, even from the most modern and sophisticated tools, is subject to some uncertainty. Therefore, assessing the uncertainty related to each input data is paramount in this method. Integrated teamwork between geologists, geophysicists and drilling specialists lead to a thorough analysis of each data feeding the process of structural model building while providing best uncertainty estimates. The ranges were specified for ∼1000 well trajectories, ∼16000 geological markers, 3 seismic travel time maps, 3 interval velocities and 59 thickness maps. All available data are used in a consistent manner to minimize the depth uncertainty. The accuracy is further improved by linking together all surfaces in a multi-layered model. In addition, this methodology considers both large scale spatial continuity capturing structural trends and more local scale incorporating inter-well variations of thickness due to sedimentological controls. Results, Observations, Conclusions After following this approach, all subsurface data started to come in agreement and resulted in more geological architectures. As an example, Figure 1 shows a cross-section along a well that drilled in B4 target layer which average thickness of 6 ft. As illustrated in the left figure, classical workflow using vertical wells and some pseudo-wells resulted in an anomalous pull-up structure and overall wavy non-geological geometry. Moreover, the well shows that it is in non-reservoir dense layer even though the well in the reservoir based on the zone log interpretation. However, the right figure shows that considering horizontal wells and uncertainties help to integrate all subsurface data with improved consistency where the structure model is smoother & more geological, plus the well is correctly placed in the targeted reservoir. Novel/Additive Information This approach will make the studied field one of the first brownfields that incorporated all data in consistent manner without pseudo-wells to build 3D structural model. It will bring considerable value to reduce uncertainties during subsequent property and dynamic modelling stages.

Spatial agents for geological surface modelling

Increased availability and use of 3D-rendered geological models have provided society with predictive capabilities, supporting natural resource assessments, hazard awareness, and infrastructure development. The Geological Survey of Canada, along with other such institutions, has been trying to standardize and operationalize this modelling practice. Knowing what is in the subsurface, however, is not an easy exercise, especially when it is difficult or impossible to sample at greater depths. Existing approaches for creating 3D geological models involve developing surface components that represent spatial geological features, horizons, faults, and folds, and then assembling them into a framework model as context for downstream property modelling applications (e.g. geophysical inversions, thermo-mechanical simulations, and fracture density models). The current challenge is to develop geologically reasonable starting framework models from regions with sparser data when we have more complicated geology. This study explores the problem of geological data sparsity and presents a new approach that may be useful to open up the logjam in modelling the more challenging terrains using an agent-based approach. Semi-autonomous software entities called spatial agents can be programmed to perform spatial and property interrogation functions, estimations and construction operations for simple graphical objects, that may be usable in building 3D geological surfaces. These surfaces form the building blocks from which full geological and topological models are built and may be useful in sparse-data environments, where ancillary or a priori information is available. Critical in developing natural domain models is the use of gradient information. Increasing the density of spatial gradient information (fabric dips, fold plunges, and local or regional trends) from geologic feature orientations (planar and linear) is the key to more accurate geologic modelling and is core to the functions of spatial agents presented herein. This study, for the first time, examines the potential use of spatial agents to increase gradient constraints in the context of the Loop project (https://loop3d.github.io/, last access: 1 October 2021​​​​​​​) in which new complementary methods are being developed for modelling complex geology for regional applications. The spatial agent codes presented may act to densify and supplement gradient as well as on-contact control points used in LoopStructural (https://www.github.com/Loop3d/LoopStructural, last access: 1 October 2021) and Map2Loop (https://doi.org/10.5281/zenodo.4288476, de Rose et al., 2020). Spatial agents are used to represent common geological data constraints, such as interface locations and gradient geometry, and simple but topologically consistent triangulated meshes. Spatial agents can potentially be used to develop surfaces that conform to reasonable geological patterns of interest, provided that they are embedded with behaviours that are reflective of the knowledge of their geological environment. Initially, this would involve detecting simple geological constraints: locations, trajectories, and trends of geological interfaces. Local and global eigenvectors enable spatial continuity estimates, which can reflect geological trends, with rotational bias, using a quaternion implementation. Spatial interpolation of structural geology orientation data with spatial agents employs a range of simple nearest-neighbour to inverse-distance-weighted (IDW) and quaternion-based spherical linear rotation interpolation (SLERP) schemes. This simulation environment implemented in NetLogo 3D is potentially useful for complex-geology–sparse-data environments where extension, projection, and propagation functions are needed to create more realistic geological forms.

Low-Rank and Spectral-Spatial Sparse Unmixing for Hyperspectral Remote Sensing Imagery

Sparse unmixing is an important technique for hyperspectral data analysis. Most sparse unmixing algorithms underutilize the spatial and spectral information of the hyperspectral image, which is unfavourable for the accuracy of endmember identification and abundance estimation. We propose a new spectral unmixing method based on the low-rank representation model and spatial-weighted collaborative sparsity, aiming to exploit structural information in both the spatial and spectral domains for unmixing. The spatial weights are incorporated into the collaborative sparse regularization term to enhance the spatial continuity of the image. Meanwhile, the global low-rank constraint is employed to maintain the spatial low-dimensional structure of the image. The model is solved by the well-known alternating direction method of multiplier, in which the abundance coefficients and the spatial weights are updated iteratively in the inner and outer loops, respectively. Experimental results obtained from simulation and real data reveal the superior performance of the proposed algorithm on spectral unmixing.

Comprehensive Insights into Spatial-Temporal Evolution Patterns, Dominant Factors of NDVI from Pixel Scale, as a Case of Shaanxi Province, China

Based on long term NDVI (1982–2015), climate, topographic factors, and land use type data information in Shaanxi Province, multiple methods (linear regression, partial and multiple correlation analysis, redundancy analysis and boosted regression trees method) were conducted to evaluate the spatial-temporal change footprints and driving mechanisms in the pixel scale. The results demonstrated that (1) the overall annual average and seasonal NDVI in this region showed a fluctuating upward trend, especially in spring. The difference between the end of season (eos) and start of season (sos) gradually increased, indicating the occurrence of temporal “greening” across most Shaanxi Province. (2) The overall spatial distribution of annual mean NDVI in Shaanxi Province was prominent in the south and low in the north, and 98.83% of the areas had a stable and increasing trend. Pixel scale analysis reflected the spatial continuity and heterogeneity of NDVI evolution. (3) Trend and breakpoint evaluation results showed that evolutionary trends were not homogeneous. There were obvious breakpoints in the latitude direction of NDVI evolution in Shaanxi Province, especially between 32–33°N and in the north of 37° N. (4) Compared with precipitation, the annual average temperature was significantly correlated with the vegetation indices (annual NDVI, max NDVI, time integrated NDVI) and phenology metrics (sos, eos). (5) Considering the interaction between environmental variables, the NDVI evolution was dominated by the combined influence of climate and geographic location factors in most areas.

Composites to Produce a Material with Zero Absolute Thermopower S = 0 or a Thermopower Switch between S = 0 and S ≠ 0

From the theory of two-phase composites it is concluded that in the concentration dependence of the Seebeck coefficient S a kink can occur precisely at S=0 absolute if the two phases have different kinds of carriers, electrons and holes, and if the phase grains are spherical without preferred orientations and arranged in a symmetrical fashion. This feature, indeed found to be realized in amorphous Cr1−xSix thin films deposited by ion beam sputtering from Cr-Si alloy targets, can be applied to make reference standards for S=0 at room temperature and even at higher temperatures. Additionally, it may be used to design a thermopower switch between S=0 and S≠0. It is also concluded that the structure realized in any alloy during solidification does not only depend on the diffusion mobility of the atoms and on the existence of a (relative) minimum in the Gibbs’ free energy. It depends also on the fact whether this structure is compatible with the demand that (spatial) continuity of the entropy and energy flux densities and their gradients is saved during the solidification process.

Spatial distribution of Gasterophilus pecorum (Diptera) eggs in the desert steppe of the Kalamaili Nature Reserve (Xinjiang, China)

Background The dominant Gasterophilus species in the desert steppe (Xinjiang, China) Gasterophilus pecorum poses a serious threat to the reintroduced Przewalski’s horses. We investigated the distribution pattern of G. pecorum eggs in June 2017. Methods Two sampling methods, transect and grid, were used, and the results were analyzed via geostatistics by semivariance. The nest quadrat was used to determine the optimal quadrat size. Results Eggs were found in 99 quadrats (63.1%) and 187 clusters (1.5%) of Stipa caucasica on the steppe. The mean oviposition count of a cluster was 3.8 ± 1.6. Three-eggs is the mode of which females oviposit on each ovigerous S. caucasica (22.0%). Semivariogram analysis revealed that the distance of spatial dependence for eggs was 921 m, 1233 m and 1097 m for transect 1, transect 2 and grid methods, respectively, while spatial continuity was 62%, 77% and 57.0% for transect 1, transect 2 and grid, respectively. The eggs showed a patchy, aggregated distribution pattern. This suggested the spherical model is most applicable. The proportion of ovigerous S. caucasica was significantly correlated with the distance from water resources (r = − 0.382, p = 0). Conclusion Our findings indicated that diversification of G. pecorum oviposition was a new adaptative strategy for its survival in the desert steppe ecological niche. This made it more efficient at infecting hosts in the local environment. Areas surrounding water resources, especially around the drinking paths of equids (500 m radius surrounding the water), were concentrated epidemic areas. It is suggested that more attention to be paid to the ecological characteristics of G. pecorum in order to develop control measures that would reduce the infection risk for Przewalski’s horses.

Testing Sentinel-1 SAR Interferometry Data for Airport Runway Monitoring: A Geostatistical Analysis

Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques are gaining momentum in the assessment and health monitoring of infrastructure assets. Amongst others, the Persistent Scatterers Interferometry (PSI) technique has proven to be viable for the long-term evaluation of ground scatterers. However, its effectiveness as a routine tool for certain critical application areas, such as the assessment of millimetre-scale differential displacements in airport runways, is still debated. This research aims to demonstrate the viability of using medium-resolution Copernicus ESA Sentinel-1A (C-Band) SAR products and their contribution to improve current maintenance strategies in case of localised foundation settlements in airport runways. To this purpose, “Runway n.3” of the “Leonardo Da Vinci International Airport” in Fiumicino, Rome, Italy was investigated as an explanatory case study, in view of historical geotechnical settlements affecting the runway area. In this context, a geostatistical study is developed for the exploratory spatial data analysis and the interpolation of the Sentinel-1A SAR data. The geostatistical analysis provided ample information on the spatial continuity of the Sentinel 1 data in comparison with the high-resolution COSMO-SkyMed data and the ground-based topographic levelling data. Furthermore, a comparison between the PSI outcomes from the Sentinel-1A SAR data—interpolated through Ordinary Kriging—and the ground-truth topographic levelling data demonstrated the high accuracy of the Sentinel 1 data. This is proven by the high values of the correlation coefficient (r = 0.94), the multiple R-squared coefficient (R2 = 0.88) and the Slope value (0.96). The results of this study clearly support the effectiveness of using Sentinel-1A SAR data as a continuous and long-term routine monitoring tool for millimetre-scale displacements in airport runways, paving the way for the development of more efficient and sustainable maintenance strategies for inclusion in next generation Airport Pavement Management Systems (APMSs).

Pilot Study Using ArcGIS Online to Enhance Students’ Learning Experience in Fieldwork

Applying ArcGIS Online application to geological fieldwork provides an alternative way to teach students. This brief report describes an educational innovation for geological fieldwork with the ArcGIS Online application to examine students’ learning experiences. In comparison to traditional classrooms, this teaching method enables students to more easily comprehend how geological structures and features connect through the mapping area. This observation indicates that students can think about the structure and deformation events as spatial continuity during acquisition data gathering in the field. Results from independent t-tests between treated and untreated student groups show that the average post-test scores of the treated students were significantly higher than pre-test scores, at a p = 0.05 level, after using ArcGIS Online in fieldwork designed in this study. Therefore, the ArcGIS Online application plays an important role in changing and developing the geological fieldwork in Thailand at the university scale for students. This teaching method could potentially benefit any science teaching and have applications in other disciplines requiring similar skills as well.

Modeling Insolation, Multi-Spectral Imagery and LiDAR Point-Cloud Metrics to Predict Plant Diversity in a Temperate Montane Forest

Incident solar radiation (insolation) passing through the forest canopy to the ground surface is either absorbed or scattered. This phenomenon, known as radiation attenuation, is measured using the extinction coefficient (K). The amount of radiation reaching the ground surface of a given site is effectively controlled by the canopy’s surface and structure, determining its suitability for plant species. Menhinick’s and Simpson’s biodiversity indexes were selected as spatially explicit response variables for the regression equation using canopy structure metrics as predictors. Independent variables include modeled area solar radiation, LiDAR-derived canopy height, effective leaf area index data derived from multi-spectral imagery and canopy strata metrics derived from LiDAR point-cloud data. The results support the hypothesis that (1) canopy surface and strata variability may be associated with understory species diversity due to radiation attenuation and the resultant habitat partitioning and that, (2) such a model can predict both this relationship and biodiversity clustering. The study data yielded significant correlations between predictor and response variables and were used to produce a multiple–linear model comprising canopy relief, the texture of heights, and vegetation density to predict understory plant diversity. When analyzed for spatial autocorrelation, the predicted biodiversity data exhibited non-random spatial continuity.