Gradient Map Research Articles

Effects of the Karacadag Volcanic Complex on the thermal structure and geothermal potential of southeast Anatolia

The Karacadag Volcanic Complex (KVC) is the largest volcanic unit in SE Turkey. It is also defined as a shield volcano on the northernmost part of the Arabian Plate. The main goal of this study is to investigate the geothermal potential of this region associated with the magnetic signature of this volcanic complex and surrounding area. Besides this primary objective, the possibility of there being volcanic intrusion into the buried fault zones under the volcanic cover are also investigated to determine the interrelations between the active tectonics and heat flow in the area. A spectral analysis method is applied to the magnetic anomalies of the volcanic rocks to identify the Curie point depth (CPD) and geothermal gradient, as well as to estimate heat flow and radiogenic heat production of radioactive minerals in the complex. A tilt angle map is also presented, in correlation with instrumentally recorded earthquake magnitudes, to indicate tectonic trends that are consistent with the maps of the thermal parameters in this study. In contrast with expectations for the KVC area, the region around Akcakale and Suruc Grabens is the most prolific zone for geothermal potential, despite them not showing strong magnetic anomalies. Curie point depths are shallow, down to 18 km, around the Akcakale Graben, and deeper, down to 22 km, around the Bitlis-Zagros Suture Zone where the geothermal gradients increase from 26 to 32 °C km−1 through the graben area. Heat flows in this zone are in the range from 75 to 90 mW m−2 depending on the thermal conductivity coefficient (2.3, 2.5, 2.7, and 3.0 W m−1 K−1) used. Radiogenic heat production values also indicate slightly changing spectra in the range 0.19 to 0.25 μW m−3). None of these parameters are focused around Mt. Karacadag. However, the earthquake epicenters (generally M ≤ 4) are aligned with the boundary faults of the Akcakale Graben where the CPD, geothermal gradient, and heat flow maps indicate relatively high potential. We thus suggest that this graben area would be good for future geothermal exploration. On the contrary, considering the low geothermal gradient and heat flow values, Mt. Karacadag can be accepted as being an extinct volcano, despite its apparent, high, magnetic anomalies.

Structuration profonde dans la région de Bir M’Chergua (Nord-Est de la Tunisie). Implications hydrogéologiques

[fr] La région de Bir M’Chergua sise à cinquante kilomètres de la capitale Tunis constitue un pôle économique important en Tunisie. Cependant la pénurie en eau résultante de la succession de nombreuses périodes de sécheresse a généré une notable dégradation de diverses activités industrielles, touristiques et agricoles dans cette région. L’exploitation des eaux souterraines peut pallier à cette situation mais elle nécessite une meilleure caractérisation des aquifères. Dans ce contexte, est réalisée la présente étude qui vise à apporter des précisions au schéma hydrogéologique de la région de Bir M’Chergua en déterminant la structuration profonde à partir de l’interprétation des données gravimétriques. Des cartes d’anomalie résiduelle, de la dérivée verticale et du gradient horizontal total sont calculées à partir de l’anomalie de Bouguer pour identifier et délimiter les sources perturbatrices. La technique de déconvolution d’Euler est aussi appliquée pour estimer la profondeur de ces sources. La carte structurale issue de l’interprétation gravimétrique permet de mettre en évidence des structures enfouies et des discontinuités de différentes directions et profondeurs qui peuvent influencer énormément la géométrie et le fonctionnement du système aquifère de Bir M’Chergua. En effet, la mise en évidence des accidents tectoniques profonds de plus de 1500 m aux alentours du Dôme du Jebel Oust permet d’expliquer l’origine et la forte salinité des eaux thermales dans ce secteur; les accidents ont favorisé une pénétration profonde des eaux de recharge ainsi que leur contact avec les terrains triasiques.

Stage-dependent effects of chlorpyrifos on medaka (Oryzias latipes) swimming behavior using a miniaturized swim flume

By considering chlorpyrifos (CPF), an organophosphorus pesticide with known mechanisms of action that affect neurobehavioral development, we assessed the validity and sensitivity of a miniaturized swim flume by investigating the effects of the insecticide on swimming behavior in medaka (Oryzias latipes) fish growing stages. Medaka in three developmental periods, namely 0, 20 and 40 day-old post-hatch (i.e. time points 0, 20 and 40, respectively), were exposed to CPF (12.5, 25, 50 and 100 μg/L) for 48 h under semi-static conditions. The CPF half-lives during exposures were evaluated and the swimming patterns in a flume section (arena) were presented on two-dimensional gradient maps of forced movement of fish against water current. A comparative numerical analysis of fish residence times between each time point control and the corresponding CPF groups was performed by dividing arenas into 15 proportional areas. The time point 0 control group gradient map showed a noticeably different swim pattern from those of the ≥12.5 μg CPF/L groups, which was statistically supported by the differences for residence times seen in ≥12 corresponding areas. The control group gradient maps for time points 20 and 40 differed from those of the respective ≥12.5 μg CPF/L groups. The comparative analysis of the residence times in the corresponding 15 areas revealed differences in ≥5 areas for time point 20 and in ≥3 areas for time point 40. The integrative analysis of the gradient maps and the numerical statistics revealed stage-specific effects and a concentration-response relationship between CPF and alterations on forced medaka swimming despite the dissipation of CPF from the water column. These results indicate the validity of the miniaturized swim flume toward a more environmentally realistic scenario for the evaluation of neurodevelopmental and behavioral toxicity in small fish models.

No Reference Quality Assessment for Screen Content Images With Both Local and Global Feature Representation.

In this paper, we propose a novel no reference quality assessment method by incorporating statistical luminance and texture features (NRLT) for screen content images (SCIs) with both local and global feature representation. The proposed method is designed inspired by the perceptual property of the human visual system (HVS) that the HVS is sensitive to luminance change and texture information for image perception. In the proposed method, we first calculate the luminance map through the local normalization, which is further used to extract the statistical luminance features in global scope. Second, inspired by existing studies from neuroscience that high-order derivatives can capture image texture, we adopt four filters with different directions to compute gradient maps from the luminance map. These gradient maps are then used to extract the second-order derivatives by local binary pattern. We further extract the texture feature by the histogram of high-order derivatives in global scope. Finally, support vector regression is applied to train the mapping function from quality-aware features to subjective ratings. Experimental results on the public large-scale SCI database show that the proposed NRLT can achieve better performance in predicting the visual quality of SCIs than relevant existing methods, even including some full reference visual quality assessment methods.

Self-adapting weighted operators for multiscale gradient fusion

Gradient maps are common intermediate representations in image processing, with extensive use in both classical and state-of-the-art algorithms. Most of the research on gradient map extraction has been devoted to the definition of gradient extraction operators or filters, normally by optimizing certain criteria. In this context, we find a rather limited literature in gradient map extraction using multiscale information. In this work, we develop the idea of producing a gradient map by fusing the gradient maps obtained at different scales. We first analyze the Gaussian Scale Space and the behaviour of gradients when images are projected into it; second, we propose two classes of self-adapting vector fusion operators, which are inspired by the focus-selective nature of the human visual system; third, we present a framework for multiscale boundary detection based on the use of such classes of operators for multiscale gradient fusion. We experimentally test our boundary detection framework to illustrate the validity of our vector fusion operators.

Exponentially concave functions and a new information geometry

A function is exponentially concave if its exponential is concave. We consider exponentially concave functions on the unit simplex. In a previous paper, we showed that gradient maps of exponentially concave functions provide solutions to a Monge–Kantorovich optimal transport problem and give a better gradient approximation than those of ordinary concave functions. The approximation error, called L-divergence, is different from the usual Bregman divergence. Using tools of information geometry and optimal transport, we show that L-divergence induces a new information geometry on the simplex consisting of a Riemannian metric and a pair of dually coupled affine connections which defines two kinds of geodesics. We show that the induced geometry is dually projectively flat but not flat. Nevertheless, we prove an analogue of the celebrated generalized Pythagorean theorem from classical information geometry. On the other hand, we consider displacement interpolation under a Lagrangian integral action that is consistent with the optimal transport problem and show that the action minimizing curves are dual geodesics. The Pythagorean theorem is also shown to have an interesting application of determining the optimal trading frequency in stochastic portfolio theory.

Modeling of the Foca-Uzunada magnetic anomaly and thermal structure in the gulf of Izmir, western Turkey

The Gulf of Izmir (GoI) is one of the largest gulfs in the Aegean Sea, Turkey. There is a large magnetic anomaly extending in the NE-SW direction between Foca and Uzunada (Uzun Island) in the gulf. Previously, Curie Point Depth (CPD), geothermal gradient, heat-flow and radiogenic heat production maps of the onshore part of the Aegean region were constructed from the aeromagnetic data. In this study, the same maps except radiogenic heat production map are presented for the offshore part and the largest magnetic anomaly in the northern part of the gulf is focused, particularly. As a result, the thermal structure of GoI is clearly defined and according to the results of this study, CPD values were found from 7 km in the NE of Foca to 10 km through the south of the gulf. The geothermal gradient values vary between 50 and 80 °C/km. Maximum heat flow values around the anomaly are calculated as 200 and 215 mW/m2 according to the thermal conductivity coefficients of 2.5 W m−1 K−1 and 2.7 W m−1 K−1, respectively. Although the anomaly is located in the Izmir Gulf; CPD, geothermic gradient, heat flow anomalies are shifted through the north of Foca and Aliaga towns in the Candarli Bay. This prominent anomaly in the Gulf of Izmir is associated with the magmatics that were encountered at 969 m in the Foca-1 well although it was drilled about 2 km away from the outermost closed contour of the magnetic anomaly. The anomaly is also modeled three dimensionally (3D) in this study. In the model map, the top of the causative body is completely located in the outer part of the gulf, and is very shallow at about 0.5 km while its bottom is inclined through the west of Cigli and Menemen. From this viewpoint, it is possible to suggest that the causative body is inclined through the Foca Peninsula. However, its closed contours are in the NE direction, through the Candarli Bay. Top depth of the causative body is also calculated from the basement horizon on the seismic sections crossing this anomaly. Depth calculations are consistent in these sections and confirm the top depths from the modeling study. The basement geometry in the seismic sections also reflects the shape of 3D model geometry, and bottom depth of the magmatics is also verified by the basement depth calculations in seismic sections.

Adaptive PCA transforms with geometric morphological grouping for image noise removal

This paper presents a novel approach of image noise removal via integrating geometric morphological patch grouping and adaptive principal component analysis (PCA) transform domain choosing. Image noise removal based on PCA has acquired much attention and success because of the essential difference: the energy of signal concentrates on the small subset of PCA transformed dataset, while the energy of noise evenly spreads over the whole data set. In this paper, the noisy image will be firstly decomposed into overlap patches that contain different content and structure information. However, some of them potentially have similar geometric morphology. So, their gradient map is utilized to compute the dominant orientation of gradient field to group these geometric morphology patches. Such a grouping procedure guarantees that only similar patches are used to perform hard thresholding on the coefficients to remove the noise. Furthermore, as the result and effect of feature extraction are different in different transform domain, a proper one could be adaptively chosen for different types. Finally, a comprehensive empirical evaluation of the proposed method is carried out in terms of accuracy and visuality, and the results reveal that our method appears to be competitive with the state-of-the-art noise removal methods.

Earth crust vertical movements according to ITRF2000, ITRF2005, ITRF2008 and ITRF2014 coordinate systems and their comparing analysis

The analysis of Earth’s crust movement vertical velocities was made both for separate regions, and averaged on regions. As input data coordinates and velocities of earth crust points, obtained in International Coordinate Systems ITRF2000, ITRF2005, ITRF2008 on the base of processing radio interferometric (VLBI), laser (SLR), Doppler (DORIS) and GPS observations was used. For the purpose of global analysis all input velocity values were averaged in the х trapezoids. For filling trapezoids the spherical function expansion to N=36 was made. Expansion harmonic coefficients allowed determine the global characteristics of earth crust movements both for all Earth, and for separate hemispheres, polar and equatorial regions, continents and oceans. It appears, that polar regions were risen, and equatorial ones were lowered, that can indicate the modern Earth oblateness reduction. The constructed maps of vertical velocities were compared with obtained by us map of earth crust strain distribution. It is appeared, that regions of modern earth surface rising (Fennoscandia, Canada, Antarctica) coincide with regions of vertical extension strain, and the lowering regions – with compression regions. Simultaneously with the determination of harmonious coefficients the mean-square error of approximation for expansion of power n=1 N and power dispersion were determined. Whereas the results converge badly and dispersion increased with the n grows, hence we can concludes, that vertical movements do not characterized global earth crust movement and denotes the unrelated character of these movement. Seemingly, the main cause of such movement origin is the local seismic events (earthquake, volcanic eruption and so on). It confirms by our conclusions about correspondence of vertical strain maximal gradient (and therefore vertical velocities) map of the earthquake distribution. In work the detailed analysis of obtained results for separate Earth’s regions was made.

Object Shapes from Regular Curves through Sparse Representations

Robotics coupled with image processing algorithms have led to more advanced control systems in varied applications. Object detection systems are used in multiple places like warehouses where detecting the object faster, makes efficient warehouse management. In this work, an object detection algorithm which uses shape as an object representation is presented. The algorithm uses semi-local contour grouping which is based on gradient maps generated from G-Let filters. The algorithm offers a computationally simpler solution as the original gradient map is reduced to a sparse representation using different thresholding techniques. The sparse representation of the object is modeled as a neighbor graph and the shape is constructed using alpha-hull of the nearest neighbor graph. The construction of a gradient map and working with its local curvatures simplifies the shape detection problem, from building hierarchical structures of local-to-global contour relationships to nearest neighbor calculations on a graph and fixing their boundary.

GIS-Mapping of Soil Available Plant Nutrients (Potentiality, Gradient, Anisotropy)

The research was elaborated in Kafr El-Dawar area (Egypt northern region) to study the availability of the soil plant nutrients. The research introduced three parameters to comprehensively and carefully describe the availability of the soil plant nutrients: potentiality, gradient and anisotropy. Potentiality defines the categories of soil ability to supply plant nutrients; meanwhile gradient expresses the increasing rate of the availability of the soil plant nutrients. The gradient anisotropy refers to the directions or orientation of the increasing rate of the availability of the soil plant nutrients. The introduced parameters enabled to spatially study the availability of the soil plant nutrients. Analytical data, of soil available phosphorus (P), indicated that P ranged from 0.2 ppm to 11.4 ppm to locate all studied soil samples into the low class of the soil nutritional P ability. This was not the case of available potassium (K), where the soil samples were distributed into three available K soil categories: medium, high, and very high. GIS map of soil P nutritional potentiality for plant (potato), displayed the soil studied area in one category, as low P soil nutritional potentiality to coincide with the analytical data classification. Contrary, the K map classified the soil studied area into three categories of soil K nutritional potentiality: medium, high and excessive. This obviously referred that the individual determination of soil K nutritional potentiality is misleading for interpretation of soil tests because it does care of the spatial distribution of soil available K. Nearly, all soil samples had high available micronutrients that they were located in the high category in both classification of analytical data and GIS maps. GIS gradient maps of the soil available plant nutrients referred that the soil plant nutrients, exception of K, had two gradients: non increasing-slight increasing and build up. Gradient of soil available potassium was classified into four classes: non increasing-slight increasing, build up, moderately increasing and hike. Regardless potassium case, the non increasing-slight increasing gradient class dominated the others. GIS maps of anisotropy soil availability of macronutrients (P and K) generally showed that their gradients mainly increased in two directions: north and south. The incasing directions of soil availability of micronutrients coincided with that of the macronutrients.

The Aperture Shape Optimization Based on Fuzzy Enhancement

The aperture shape optimization (ASO) is a critical step in the direct aperture optimization (DAO) method. During ASO, the gradient of objective function is calculated with respect to the beamlet weight. These gradient components are directly utilized to generate the new aperture shape. In this way, the beamlet of the large positive gradient value may be grouped into the generated aperture shape. The treatment quality may be deteriorated by adding this aperture into the treatment plan. In order to overcome this drawback, a novel method based on the fuzzy enhancement was proposed to generate the aperture shape. We apply the fuzzy enhancement method to enhance the gradient map that is composed of the gradients of objective function in a beam. The enhanced gradient map was then employed to form a network flow, which was solved to generate the new aperture shape. The optimal aperture shape was generated by removing the beamlet of the large positive gradient value from the new generated aperture shape. To verify the effectiveness, the proposed method was compared with the conventional column generation (CG) method on a prostate cancer case and on a head-and-neck cancer case. Experimental results demonstrate that the new algorithm has a better performance than the CG algorithm. The proposed method can further reduce the dose delivered to the critical structures, when the similar dose coverage is delivered on the targets.

Infrared small target detection based on local intensity and gradient properties

Infrared small target detection is a challenging task for computer vision due to the factors such as scale variations of the targets and strong clutters. Inspired by the Gaussian-like shape of the small target, we characterize two local properties of the small target from the perspective of intensity and gradient to address this problem. The two properties are that the intensity value of the target pixels is greater than the value of its locally neighboring pixels, and the gradients towards the target center often distribute regularly around the target. First, based on the two properties, the local intensity and gradient (LIG) map is calculated from the original infrared image in order to enhance the targets and suppress clutters. Next, we can obtain the targets conveniently via segmentation from the LIG map. Extensive evaluations on real data demonstrate that the proposed algorithm has satisfactory results in terms of clutter suppression and robustness.

Magnetic Structure of the Ischia volcanic island, Southern Italy

We carried out a study of the structures of the volcanic island of Ischia by the analysis and interpretation of high-resolution aeromagnetic data and by a newly compiled in-land gravity data set. The comparison between the vertical gradient of gravity data and pole-reduced magnetic data was performed through semblance analysis and highlighted a correspondence between the main magnetic and gravity highs over the lava and green tuff deposits (e.g., Punta Imperatore, Mt. Trippodi, Zaro, Mt. Rotaro, Mt. Epomeo). Our analysis also highlighted the simultaneous presence of a magnetic minimum and a gravimetric maximum in the central part of the island, mainly visible in the long-period components of the two data sets. This may be due to the existence of a partially demagnetized structure with positive density contrast, representing the island's igneous basement. The boundaries of the lava and tuffs deposits of the island were clearly pointed out by the maxima of the total horizontal gradient maps of magnetic and gravity data. Those maxima also show the position of several lineaments, in good agreement with the mapped faults of the island.

Embedding optimal transports in statistical manifolds

We consider Monge-Kantorovich optimal transport problems on ℝ d , d ≥ 1, with a convex cost function given by the cumulant generating function of a probability measure. Examples include theWasserstein-2 transport whose cost function is the square of the Euclidean distance and corresponds to the cumulant generating function of the multivariate standard normal distribution. The optimal coupling is usually described via an extended notion of convex/concave functions and their gradient maps. These extended notions are nonintuitive and do not satisfy useful inequalities such as Jensen’s inequality. Under mild regularity conditions, we show that all such extended gradient maps can be recovered as the usual supergradients of a nonnegative concave function on the space of probability distributions. This embedding provides a universal geometry for all such optimal transports and an unexpected connection with information geometry of exponential families of distributions.

Landslide hazard mapping along national highway-154A in Himachal Pradesh, India using information value and frequency ratio

For the socio-economic development of a country, the highway network plays a pivotal role. It has therefore become an imperative to have landslide hazard assessment along these roads to provide safety. The current study presents landslide hazard zonation maps, based on the information value method and frequency ratio method using GIS on 1:50,000 scale by generating the information about the landslide influencing factors. The study was carried out in the year 2017 on a part of Ravi river catchment along one of the landslide-prone Chamba to Bharmour road corridor of NH-154A in Himachal Pradesh, India. A number of landslide triggering geo-environmental factors like “slope, aspect, relative relief, soil, curvature, Land Use and Land Cover (LULC), lithology, drainage density, and lineament density” were selected for landslide hazard mapping based on landslide inventory. The landslide inventory has been developed using satellite imagery, Google earth and by doing exhaustive field surveys. A digital elevation model was used to generate slope gradient, slope aspect, curvature, and relative relief map of the study area. The other information, i.e., soil maps, geological maps, and toposheets, have been collected from various departments. The landslide hazard zonation map was categorized namely “very high hazard, high hazard, medium hazard, low hazard, and very low hazard.” The results from these two methods have been validated using area under curve (AUC) method. It has been found that hazard zonation map prepared using frequency ratio model had a prediction rate of 75.37% while map prepared using information value method had prediction rate of 78.87%. Hence, on the basis of prediction rate, the landslide hazard zonation map, obtained using information value method, was experienced to be more suitable for the study area.

Thermal structure of Sikhote Alin and adjacent areas based on spectral analysis of the anomalous magnetic field

The depth of the base of the magnetoactive layer and the geothermal gradient in the Sikhote Alin crust are estimated based on a method determining the Curie depth point of magnetoactive masses by using spectral analysis of the anomalous magnetic field. A detailed map of the geothermal gradient is constructed for the first time for the Sikhote Alin and adjacent areas of the Central Asian belt. Analysis of this map shows that the zones with a higher geothermal gradient geographically fit the areas with a higher level of seismicity.

Radial gradient and radial deviation radiomic features from pre-surgical CT scans are associated with survival among lung adenocarcinoma patients.

The goal of this study was to extract features from radial deviation and radial gradient maps which were derived from thoracic CT scans of patients diagnosed with lung adenocarcinoma and assess whether these features are associated with overall survival. We used two independent cohorts from different institutions for training (n= 61) and test (n= 47) and focused our analyses on features that were non-redundant and highly reproducible. To reduce the number of features and covariates into a single parsimonious model, a backward elimination approach was applied. Out of 48 features that were extracted, 31 were eliminated because they were not reproducible or were redundant. We considered 17 features for statistical analysis and identified a final model containing the two most highly informative features that were associated with lung cancer survival. One of the two features, radial deviation outside-border separation standard deviation, was replicated in a test cohort exhibiting a statistically significant association with lung cancer survival (multivariable hazard ratio = 0.40; 95% confidence interval 0.17-0.97). Additionally, we explored the biological underpinnings of these features and found radial gradient and radial deviation image features were significantly associated with semantic radiological features.

The role of E–W basement faults in the Mesozoic geodynamic evolution of the Gafsa and Chotts basins, south-central Tunisia

The Gafsa and Chotts intracratonic basins in south-central Tunisia are transitional zones between the Atlasic domain to the north and the Saharan platform to the south. The principal aim of this paper is to unravel the geodynamic evolution of these basins following an integrated approach including seismic, well log and gravity data. These data are used to highlight the tectonic control on the deposition of Jurassic and Lower Cretaceous series and to discuss the role of the main faults that controlled the basin architecture and Cretaceous–Tertiary inversion. The horizontal gravity gradient map of the study area highlights the pattern of discontinuities within the two basins and reveals the presence of deep E–W basement faults. Primary attention is given to the role played by the E–W faults system and that of the NW–SE Gafsa fault which was previously considered active since the Jurassic. Facies and thickness analyses based on new seismic interpretation and well data suggest that the E–W-oriented faults controlled the subsidence distribution especially during the Jurassic. The NW–SE faults seem to be key structures that controlled the basins paleogeography during Late Cretaceous–Cenozoic time. The upper Triassic evaporite bodies, which locally outline the main NW–SE Gafsa fault, are regarded as intrusive salt bodies rather than early diapiric extrusions as previously interpreted since they are rare and occurred only along main strike-slip faults. In addition, seismic lines show that Triassic rocks are deep and do not exhibit true diapiric features.

Edge‐guided with gradient‐assisted depth up‐sampling

Most of depth up-sampling algorithms are based on the consistent hypothesis, i.e. the object boundaries in the colour image are consistent with depth discontinuity regions in the depth map. However, the hypothesis is not always correct. Under the combined guidance of high-resolution (HR) depth edge map and HR colour image gradient map, a simple and efficient depth up-sampler is presented. Firstly, the consistent regions are distinguished from the other regions and more accurate depth edge points are found. Then, the initial up-sampled depth map from traditional bilinear interpolation is refined by an effective depth-assignment scheme. Extensive experiments demonstrate that the proposed method outperforms conventional interpolation algorithms and some other edge-based depth up-sampling methods.