Surface Mapping Research Articles

Mapping classes are almost determined by their finite quotient actions

Given any connected compact orientable surface, a pair of mapping classes is said to be procongruently conjugate if it induces a conjugate pair of outer automophisms on the profinite completion of the fundamental group of the surface. For example, this occurs if they induce conjugate outer automorphisms on every characteristic finite quotient of the fundamental group. In this paper, it is shown that every procongruent conjugacy class of mapping classes, as a subset of the surface mapping class group, is the disjoint union of at most finitely many conjugacy classes of mapping classes. For any pseudo-Anosov mapping class of a connected closed orientable surface, several topological features are confirmed to depend only on the procongurent conjugacy class of the mapping class, including the stretching factor, the topological type of the prong singularities, the transverse orientability of the invariant foliations, and the isomorphism type of the symplectic Floer homology.

Increasing Fuel Loads, Fire Hazard, and Carbon Emissions from Fires in Central Siberia

The vast Angara region, with an area of 13.8 million ha, is located in the southern taiga of central Siberia, Russia. This is one of the most disturbed regions by both fire and logging in northern Asia. We have developed surface and ground fuel-load maps by integrating satellite and ground-based data with respect to the forest-growing conditions and the disturbance of the territory by anthropogenic and natural factors (fires and logging). We found that from 2001 to 2020, fuel loads increased by 8% in the study region, mainly due to a large amount of down woody debris at clearcuts and burned sites. The expansion of the disturbed areas in the Angara region resulted in an increase in natural fire hazards in spring and summer. Annual carbon emissions from fires varied from 0.06 to 6.18 Mt, with summer emissions accounting for more than 95% in extreme fire years and 31–68% in the years of low fire activity. While the trend in the increase in annual carbon emissions from fires is not statistically significant due to its high interannual variability and a large disturbance of the study area, there are significantly increasing trends in mean carbon emissions from fires per unit area (p < 0.005) and decadal means (p < 0.1). In addition, we found significant trends in the increase in emissions released by severe fires (p < 0.005) and by fires in wetter, dark, coniferous (spruce, p < 0.005 and Siberian pine, p < 0.025) forests. This indicates deeper burning and loss of legacy carbon that impacts on the carbon cycle resulting in climate feedback.

Detection and mapping of specular surfaces using multibounce LiDAR returns.

We propose methods that use specular, multibounce LiDAR returns to detect and map specular surfaces that might be invisible to conventional LiDAR systems that rely on direct, single-scatter returns. We derive expressions that relate the time- and angle-of-arrival of these multibounce returns to scattering points on the specular surface, and then use these expressions to formulate techniques for retrieving specular surface geometry when the scene is scanned by a single beam or illuminated with a multi-beam flash. We also consider the special case of transparent specular surfaces, for which surface reflections can be mixed together with light that scatters off of objects lying behind the surface.

On the birationality of the Hessian maps of quartic curves and cubic surfaces

We show that the Hessian map of quartic plane curves is a birational morphism onto its image, thus bringing new evidence for a very interesting conjecture of Ciro Ciliberto and Giorgio Ottaviani. Our new approach also yields a simpler proof of the similar property for cubic surfaces, which is already known by the work of these two authors.

In vitro and in vivo validation of a new three-dimensional fringe projection-based device (AEVA-HE) dedicated to skin surface mapping.

Aging signs are much visible on the surface of the skin that presents different changes: cheeks start to sag, more and deeper wrinkles appear, and pigmentation spotsincrease.Face diagnostic torecommend products includes assessingcutaneous micro-reliefor themicro-depressive networkon the face.Furthermore,there is anincreasing demand for clinical and instrumental methods to provetheefficacy ofanti-agingtreatments.As a result,very accurate and sensitive three-dimensional (3D) devicesare developedand validatedto measure and quantify aging skin andto catch fine anti-aging productsacting on wrinklesand fine lines. AEVA-HE,anon-invasive3Dmethodbased onfringe projectiontechnology, is used to robustly characterize theskinmicro-relieffrom afull-faceacquisitionandfrommultipleextractedzonesof interest.In vitro and in vivo studiesare conductedtoassessthe reproducibility of this systemandits precision towarda standard fringe projection system,DermaTOP. TheAEVA-HEsuccessfully measuredmicro-relief and wrinklesand demonstrated the reproducibility of measurements. AEVA-HEparameters were found highly correlated toDermaTOP. The present work illustrates theperformance of theAEVA-HEdevice and its dedicatedsoftwarekitasa precious tool for quantifying themajor characteristics ofwrinklesappearingwith ageandthus offersa high potential forassessing the effect of anti-wrinkling products.

Optimization of fishbone biochar preparation process based on adsorption performance

Food and Kitchen Waste with high organic matter poses great challenge to the living environment and ecology, which arouses great enthusiasm for suitable treatment routes. As one kind of major component of Food and Kitchen Waste, fishbone was selected as potential feedstock for high-value biochar production. The effect of major parameters controlling fishbone carbonization was investigated on biochar production performance. And with Plackett-Burman and Central Composite Design methodology, multi-factor process optimization was performed in order to achieve better biochar yield and quality. Experimental results revealed that carbonization temperature has the most significant impact on the yield and adsorption performance of biochar, especially at 2.5–5 °C·min−1 heating rate and residence time. Based on Response Surface Method, a three-dimensional surface model was constructed to evaluate the quality of biochar with varied carbonization conditions. Better biochar yield was achieved at carbonization conditions (473 °C, 6.3 °C·min−1, 1.3 h), with biochar adsorption value of methylene blue at 20.193 mg g−1 and specific surface area at 21.936 m2 g−1, which was also confirmed by biochar characterization. The established three-dimensional surface map provides theoretical basis for valued fishbone biochar conversion, and also for process optimization of Food and Kitchen waste carbonization.

Object Recognition of a GCP Design in UAS Imagery Using Deep Learning and Image Processing—Proof of Concept Study

Image-based unmanned aircraft systems (UASs) are used in a variety of geodetic applications. Precise 3D terrain surface mapping requires ground control points (GCPs) for scaling and (indirect) georeferencing. In image analysis software (e.g., Agisoft Metashape), the images can be generated to a 3D point cloud using Structure-from-Motion (SfM). In general, the conventional GCP design for UAS flights is a checkerboard pattern, which is provided in the software and used for automatic marker detection in each image. When changing the pattern, manual work would be required by picking the GCP individually by hand. To increase the level of automation in the evaluation, this article aims to present a workflow that automatically detects a new edge-based GCP design pattern in the images, calculates their center points, and provides this information to the SfM software. Using the proposed workflow based on deep learning (DL) and image processing, the quality of the resulting 3D model can be equated to the result with GCP center points picked by human evaluator. Consequently, the workload can be accelerated with this approach.

Bibliometric analysis of surface water detection and mapping using remote sensing in South America

Bibliometric analysis of surface water detection and mapping using remote sensing in South America

Analyzing physical and socio-economic factors for property crime incident in Addis Ababa, Ethiopia

Property crime has become a challenge in major cities of developing countries including Addis Ababa, Ethiopia. However, factors contributing to property crime have not been carefully examined. Therefore, this paper presents the physical and socio-economic factors that clearly have a substantial impact on property crime. In this study, both primary and secondary data were used. Recorded property crime was collected from Addis Ababa police commission. Property crime incidence locations were georefrenced using Google Earth as well as handheld Global Positioning System. Then, a property crime surface map and pattern were created using point pattern analysis and inverse distance weighted interpolation technique. The study area was then classified into low crime and hotspot areas based on the frequency of crime events as well as the created crime surface map. A total of 200 respondents (100 in high crime area and 100 in low crime area) were selected using purposive sampling techniques. Five key informants were selected purposely from senior police officers. Data were collected using questionnaires and in-depth interview. A binary logistic regression model was employed to analyze the collected data. The data analysis showed that physical features mainly commercial center, road with no street light and river courses were positively correlated at significant level with the committing of property crime. On the other hand, public participation in crime prevention, witness and crime events reporting influenced negatively the committing of property crime. In addition, unemployment, family background, education level, age, time, season and police patrolling activities determine the occurrence of property crime events. The finding depicts that the identified physical and socio-economic factors can influence the patterns and rate of crime incidents in the study area. Therefore, the law enforcement officers should consider these influential factors to deploy police officers and to reduce property crime problems.

Sperm whale ship strikes in the Pelagos Sanctuary and adjacent waters: assessing and mapping collision risks in summer

Collisions with large vessels potentially present a major conservation issue for sperm whales in the Pelagos Sanctuary in the northwestern Mediterranean Sea. The exact numbers and locations of ship strikes remain largely unknown at present. In this study, sightings of sperm whales in summer (June–September) were gathered for the period between 1998 and 2008 from nine French and Italian organisations, together covering an area of more than 68,000km. Working on a regular grid of 0.1° × 0.1° latitude/longitude cells, approximate surface density of the whales was calculated using kriging methods. A database of shipping lanes of ferries and merchant vessels was assembled, and traffic density was mapped (kilometres travelled per cell). The data was overlayed and multiplied, using ArcGis, to create a relative density surface map of sperm whales correlated with the relative density of maritime traffic. Several maps of collision risk were drawn up according to the speed class of the vessels. Of living animals that had been photo-identified, 9% had scars attributed to ship strike. Results show that sperm whales are at high risk from merchant vessels along the French and Italian continental coasts and at risk from conventional ferries on the east side of the islands of Corsica and Sardinia. It was calculated that 74 animals could be in a ship strike risk situation during the summer period in the Pelagos Sanctuary. Based on these results, mitigation measures already in place were reviewed and new measures to reduce ship strike risk are suggested.

LITHOFACIES DISTRIBUTION AND DEPOSITIONAL ARCHITECTURAL STUDIES OF THE MIOCENE DEPOSITS OF THE “THOR” FIELD, COASTAL SWAMP DEPOBELT, NIGER DELTA BASIN, NIGERIA

The study accesses the petrophysical data from the Eocene deposit of the “Thor” field, Coastal swamp depobelt, Niger Delta and process it to decipher the different lithological makeup, the reservoir units, the depositional architecture and how these factors influenced reservoir distribution within the field. The study made use of well logs consisting of gamma ray, resistivity, neutron and density logs. Gamma ray log aided lithological identification, resistivity logs help to isolate reservoir rocks from non-reservoir rocks while neutron and density logs was used to differentiate oil or gas zones. Three hydrocarbon reservoirs designated as R-1, R-2 and R-3 were interpreted from the logs and the sand bodies show a lateral continuity within the field in the north-eastern direction. Log sequences analysis of the field made use of a combination of gamma ray and restively logs via electro-sequence identification and mapping of key stratigraphic surfaces and the identification of para-sequences including retrogadational, aggradational and progradational stacking pattern leading to the delineation of the environment of deposition. The three stratigraphic surfaces enable the classification of the field into two depositional sequences and further subdivision into three system tracts. The first depositional sequence is interpreted as the oldest and lies at the base which is about 1201ft thick while the second depositional sequence overlies the first sequence with about 1605ft in thickness and is interpreted to be younger. Sediments within the two sequences are thought to be deposited in deltaic environment within the marginal to shallow marine settings.

Integrating MR imaging with full-surface indentation mapping of femoral cartilage in an ex vivo porcine stifle

The potential of MRI to predict cartilage mechanical properties across an entire cartilage surface in an ex vivo model would enable novel perspectives in modeling cartilage tolerance and predicting disease progression. The purpose of this study was to integrate MR imaging with full-surface indentation mapping to determine the relationship between femoral cartilage thickness and T2 relaxation change following loading, and cartilage mechanical properties in an ex vivo porcine stifle model. Matched-pairs of stifle joints from the same pig were randomized into either 1) an imaging protocol where stifles were imaged at baseline and after 35 min of static axial loading; and 2) full surface mapping of the instantaneous modulus (IM) and an electromechanical property named quantitative parameter (QP). The femur and femoral cartilage were segmented from baseline and post-intervention scans, then meshes were generated. Coordinate locations of the indentation mapping points were rigidly registered to the femur. Multiple linear regressions were performed at each voxel testing the relationship between cartilage outcomes (thickness change, T2 change) and mechanical properties (IM, QP) after accounting for covariates. Statistical Parametric Mapping was used to determine significance of clusters. No significant clusters were identified; however, this integrative method shows promise for future work in ex vivo modeling by identifying spatial relationships among variables.

Epicardial conduction abnormalities in patients with Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) and mutation positive healthy family members - A study using electrocardiographic imaging.

The diagnosis of arrhythmogenic right ventricular cardiomyopathy (ARVC) in early stages is challenging. The aim of this study was therefore to investigate whether electrocardiographic imaging (ECGI) can detect epicardial conduction changes in ARVC patients and healthy mutation-carriers (M-carriers). Twelve ARVC patients, 20 M-carriers and 8 controls underwent 12-lead ECG, signal-averaged ECG, 2-dimensional echocardiography, 24-hours Holter monitoring and ECGI (body surface mapping and computer tomography with offline analysis of reconstructed epicardial signals). Total and Right Ventricular Activation Time (tVAT and RVAT respectively), area of Ventricular Activation during the terminal 20 milliseconds (aVAte20) and the activation patterns were compared between groups. In ARVC patients the locations of aVAte20 were scattered or limited to smaller parts of the right ventricle (RV) versus in controls, in whom aVAte20 was confined to right ventricular outflow tract (RVOT) and left ventricle (LV) base (+/- RV base). ARVC patients had smaller aVAte20 (35cm2 vs 87cm2, p<0.05), longer tVAT (99msec vs 58msec, p<0.05) and longer RVAT (66msec vs 43msec, p<0.05) versus controls. In 10 M-carriers (50%), the locations of aVAte20 were also eccentric. This sub-group presented smaller aVAte20 (53cm2 vs 87cm2, p = 0.009), longer RVAT (55msec vs 48msec, p = 0.043), but similar tVAT (65msec vs 60msec, p = 0.529) compared with the M-carriers with normal activation pattern. ECGI can detect epicardial conduction abnormalities in ARVC patients. Moreover, the observation of localized delayed RV epicardial conduction in M-carriers suggests an early stage of ARVC and may be a useful diagnostic marker enhancing an early detection of the disease.

The Myth of Social Mobility: Subjective Social Mobility and Mental Health

A common assumption is that upward mobility produces positive psychological outcomes. However, status-based identity framework and social class worldview model propose that perceived social mobility in either direction will lead to increased distress. Based on this claim, we examined relations among subjective social mobility, life satisfaction, and mental health using polynomial regression with response surface mapping. In Study 1, groups that experienced both subjective downward and upward mobility reported more depressive symptomatology than groups that remained in middle or upper social statuses in a sample of 567 adults. We did not find significant relations between subjective social mobility and life satisfaction. In Study 2, both groups that experienced subjective downward and upward mobility reported more depressive and academic distress symptomatology than groups that remained in middle or upper social social statuses in a sample of 7,598 clients from college counseling center data. The results provide insights relevant to multicultural counseling and training.

Three-dimensional visual mapping of underwater ship hull surface using image stitching geometry

This paper presents a method for three-dimensional (3D) visual mapping of underwater ship hulls using monocular vision. Visual inspection of underwater ship hulls using unmanned underwater vehicles needs to be conducted at very close range to the target surface because of the limited visibility in underwater environments. These environmental challenges can result in ineffective photometric and geometric information in hull surface images. Therefore, the performance of conventional 3D reconstruction techniques based on monocular vision is often unsatisfactory. To address these challenges and generate a precise 3D global map of the surveyed hull surface, the proposed visual mapping method adopts a two-step approach comprising global registration in two-dimensional space and 3D reconstruction using the information of the stitching geometry drawn by the registered images. Experimental results are shown to demonstrate the feasibility of the proposed method using image datasets obtained in field experiments with two different full-scale ships in real sea environments.

Pluto’s Surface Mapping Using Unsupervised Learning from Near-infrared Observations of LEISA/Ralph

We map the surface of Pluto using an unsupervised machine-learning technique using the near-infrared observations of the LEISA/Ralph instrument on board NASA’s New Horizons spacecraft. The principal-component-reduced Gaussian mixture model was implemented to investigate the geographic distribution of the surface units across the dwarf planet. We also present the likelihood of each surface unit at the image pixel level. Average I/F spectra of each unit were analyzed—in terms of the position and strengths of absorption bands of abundant volatiles such as N2, CH4, and CO and nonvolatile H2O—to connect the unit to surface composition, geology, and geographic location. The distribution of surface units shows a latitudinal pattern with distinct surface compositions of volatiles—consistent with the existing literature. However, previous mapping efforts were based primarily on compositional analysis using spectral indices (indicators) or implementation of complex radiative transfer models, which need (prior) expert knowledge, label data, or optical constants of representative end-members. We prove that an application of unsupervised learning in this instance renders a satisfactory result in mapping the spatial distribution of ice compositions without any prior information or label data. Thus, such an application is specifically advantageous for a planetary surface mapping when label data are poorly constrained or completely unknown, because an understanding of surface material distribution is vital for volatile transport modeling at the planetary scale. We emphasize that the unsupervised learning used in this study has wide applicability and can be expanded to other planetary bodies of the solar system for mapping surface material distribution.

Analysis of a Pull-Apart Basin and Its Associated Fractures in the Woodford Shale, Central Oklahoma

Pull-apart basins are faulting and folding zones with high intensity of fractures that strongly affect the production in unconventional shale gas. While most observations of pull-apart basins were from surface mapping or laboratory experiments, we investigated a nascent pull-apart basin in the subsurface. We characterized a nascent pull-apart basin along the strike-slip fault within the Woodford Shale by using seismic attributes analyses, including coherence, dip-azimuth, and curvature. The results indicate a 32 km long, N-S striking strike-slip fault that displays a distinct but young pull-apart basin, which is ~1.6 km by 3.2 km in size and is bounded by two quasi-circular faults. The curvature attribute map reveals two quasi-circular folds, which depart from the main strike-slip fault at ~25°, resulting in an elliptical basin. Inside the basin, a series of echelon quasi-circular normal faults step into the bottom of the basin with ~80 m of total subsidence. We propose that the controls of the shape of pull-apart basin are the brittleness of the shale, and we suggest proper seismic attributes as a useful tool for investigating high fracture intensity in the subsurface for hydrofracturing and horizontal drilling within the shale.

A Statistical Rule of the Stokes Parameters of Pol-SAR for Identifying Flat Surface in PSR

Finding a flat area is critical for choosing the landing site, especially in the permanently shadowed region (PSR) without reference of optical images. The digital elevation model (DEM) data are not enough to describe the complex lunar topography in the landing mission. High-resolution polarimetric synthetic aperture radar (pol-SAR) can acquire the polarized scattering map of lunar surface. In this paper, Chandrayaan-2 pol-SAR images of flat and rocky regions at non-PSR are selected with assistance of optical image. The statistics of the Stokes parameters can tell the difference between flat and rocky surfaces. Enhanced backscattering with a large variance from rough surfaces with rocks can be distinguished from the smooth and flat areas. Large value of the first Stokes parameter I1 with extendedly distributed probability distribution function is related with the scatterings from rough surface and rocks. A statistics rule of the Stokes parameters is established, and is applied to identifying the flat regions in the PSR of the crater Shoemaker.

Soft body reconstruction of a reptile fossil by the nondestructive elemental mapping with a newly designed XRF

AbstractVertebrate fossils usually consist only of mineralized skeletons and rarely preserve soft body parts. However, the buried soft body releases the degraded material into the surrounding sediments. The degraded material can be preserved as invisible signals of some chemicals or authigenic minerals, which can be revealed by the elemental distribution of the fossils' surface and their surrounding rock. As a method for surface elemental mapping, X‐ray fluorescence (XRF) measurement requires the samples to be ground and polished as a mirror‐like plane that keeps a stable distance of X‐ray source‐sample‐detector. This destructive pretreatment is undesirable for precious fossils. To rectify this problem, a nondestructive XRF for element mapping of the fossils' 3D surface is newly invented. The new equipment can follow the 3D shape model to keep the distance for every XRF scanned point. We performed the element mapping of Ca and Fe on the surface of a marine sauropterygian fossil (Keichousaurus hui) and its surrounding sediments, and found that the soft tissue around the thoracic cage is thicker than the abdomen. The abnormal elemental distribution on the area of the angular and surangular of the skull can be explained as unprofessionally prepared. In addition, this research found that elemental mapping revealed the invisible signals of the paleoenvironment around fossils and information for the reconstruction of soft‐tissue anatomy. We also give an example that based on the wide application of the “Internet of Things” and “Industrial Network,” the design and development of specialized equipment for paleontologists' requirements are going simple.

Unraveling process-microstructure-property correlations in powder-bed fusion additive manufacturing through information-rich surface features with deep learning

A machine learning (ML)–based framework has been developed to optimize the process parameters and unravel the paramount process–microstructure–property (PMP) relationships rapidly and precisely, which is demonstrated using electron beam melting (EBM®)-processed Ti–6Al–4V alloy. The process maps are constructed using ML to discover the optimal process window based on the three criteria: fully dense (≥ 99.5% in relative build density), flat fusion surface and highest possible strength, without which the optimization outcome will be deficient. By using the ML-optimized process parameters, Ti–6Al–4V parts were fabricated with ultimate tensile strength ∼5% higher and ∼80% faster than the classical parameter setting developed by the original machine manufacturer. The α/β dual-phase microstructure and tensile deformation mechanism are further studied to understand the superior mechanical properties obtained in the ML-optimized sample. In addition, the information-rich top fusion surface is found to be an alternative route to implicitly materialize the microstructure-to-property relationships with a prediction accuracy of ∼98%. The full-scope surface and microstructure maps are then generated from the process parameters. Surface features that reflect superior and poor mechanical properties are particularly identified. Finally, the implications of the ML-based PMP framework with surface feature correlation are discussed in the context of improving resources utilization efficiency.