Reflection Data Sets Research Articles

Estimation of Water Quality Parameters in Oligotrophic Coastal Waters Using Uncrewed-Aerial-Vehicle-Obtained Hyperspectral Data

Water quality monitoring in coastal areas and estuaries poses significant challenges due to the intricate interplay of hydrodynamic, chemical, and biological processes, regardless of the chosen monitoring methods. In this study, we analyzed the applicability of different monitoring sources using in situ data, uncrewed-aerial-vehicle (UAV)-mounted hyperspectral sensing, and Sentinel-2-based multispectral imagery. In the first part of the study, we evaluated the applicability of existing empirical algorithms for water quality (WQ) parameter retrieval using hyperspectral, simulated multispectral, and satellite multispectral datasets and in situ measurements. In particular, we focused on three optically active WQ parameters: chlorophyll a (Chl,a), turbidity (TUR), and colored dissolved organic matter (CDOM) in oligotrophic coastal waters. We observed that most existing algorithms performed poorly when applied to different reflectance datasets, similar to previous findings in small and optically complex water bodies. Hence, we proposed a novel set of locally based empirical algorithms tailored for determining water quality parameters, which constituted the second part of our study. The newly developed regression-based algorithms utilized all possible combinations of spectral bands derived from UAV-generated hyperspectral data and exhibited coefficients of determination exceeding 0.9 for the three considered WQ parameters. The presented two-part approach was demonstrated in the semi-enclosed area of Kaštela Bay and the Jadro River estuary in the Central Eastern Adriatic Sea. This study introduces a promising and efficient screening method for UAV-based water quality monitoring in coastal areas worldwide. Such an approach may support decision-making processes related to coastal management and ultimately contribute to the conservation of coastal water ecosystems.

Bottom simulating reflectors in the Manila Trench forearc and its implications on the occurrence of gas hydrates in the region

Gas hydrate occurrence and stability in active plate margins have been reported in various localities, with investigations focusing on its potential as an alternative energy resource or the threat it poses due to dissociation and methane release into the atmosphere. The Manila Trench forearc, proximal to active margins and probable methane-rich sediments, can be an analog for gas hydrate formation and geologic preconditions constrained by tectonics and sedimentation processes. The possible occurrence of gas hydrates in offshore western Luzon Island is reported for the first time based on bottom simulating reflectors (BSRs) in multi-channel seismic reflection datasets. Results indicate a prevalence of BSRs on the frontal wedge seaward of the North Luzon Trough (NLT) and in the West Luzon Trough (WLT) basin fill. Continuous, discontinuous, double, and pluming BSRs in the forearc encompass a total area of approximately 15,400 km2 at depths of 223–553 mbsf in the frontal wedge and 486 to 1428 mbsf within the basins. Enhanced amplitude reflectors (EARs) above and below the BSRs indicate possible gas hydrate and free gas accumulations, respectively. Gas chimneys associated with the upward migration of methane-rich fluids appear to be controlled by deep structural features. The accretion of continent-derived sediments along the northern segment of the frontal wedge promotes the formation of fluid migration structures, enhancing fluid migration and gas hydrate formation at shallower depths. Estimated geothermal gradient values for the frontal wedge range from 28 to 92 °C/km, consistent with previously reported in-situ measurements from offshore SW Taiwan. In contrast, arc-derived sediments within the NLT and west-ward fluid migration along the landward-tilted sequences limit gas hydrate accumulation within the basin. To the south, the preferential formation of gas hydrates within the WLT basin points to deep gas sources within the forearc basin sediments, with upward movement of methane-rich fluids along normal faults. Estimated geothermal gradient values in the basin are lower, ranging from 12 to 45 °C/km, reflecting lower thermal conditions. The absence of BSRs seaward of the WLT signifies widespread gas hydrate dissociation in the frontal wedge slope.

Spatio‐Temporal Variations in Sediment Delivery as a Response to Rapid Quaternary Climate Change in the Lake Malawi Rift, East Africa

AbstractThe interplay of rapid climate change and tectonics drives landscape development, sediment routing, and deposition in early‐stage continental rift systems. The Lake Malawi Rift, in the Western Branch of the East African Rift, is an archetype of a juvenile rift and an ideal natural laboratory for evaluating lacustrine source‐to‐sink systems on orbital or shorter timescales. We examine the interplay of these processes over the past 140 kyr using observations from nested seismic reflection data sets tied to scientific drill cores, which calibrate numerical forward models of this closed sedimentary system. Fault slip rates measured from seismic data drive tectonic displacements in the model. Satellite‐derived precipitation maps constrain modern precipitation and are scaled to previous hydrologic balance studies to reconstruct past climates. Our model reproduces known sediment thicknesses across the rift and accounts for 96% of the estimated siliciclastic sediment deposited over the past 140 kyr. The results demonstrate that the onset of arid climate conditions (140–95 kyr BP) causes extreme drainage adjustments downstream and the formation of mega‐catchments that flow axially into a shallow restricted paleo‐lake. Sedimentation rates during this time are twice the present values due to increased sediment focusing via these axial systems into a much smaller, hydrologically closed lake. As the climate became wetter (95–50 kyr BP), the lake rapidly expanded, decreasing both erosion and sedimentation rates across the rift. This closed‐loop approach allows us to evaluate the role of high‐frequency climate change in modulating basin physiography as well as sediment fluxes in juvenile rift systems.

A 2D seismic reflection dataset of the Caosiyao giant porphyry Mo deposit in the shallow coverage area in Jining, Inner Mongolia, China

AbstractProspecting for and exploiting buried mineral deposits is currently challenging. Given their high precision and resolution, reflection seismic methods might be useful in such applications involving deep mineral deposits. However, there are few open seismic datasets available from mineral deposit exploration, especially in hardrock environments. The world‐class Caosiyao porphyry Molybdenum deposit (1.76 Mt) in the Jining area of Inner Mongolia, China, is largely covered by loess layers, which poses challenges to its exploration. Seismic reflection surveys were conducted to help delineate the deep granite porphyry intrusions and associated orebodies. This paper presents the raw seismic reflection dataset from three profiles on the Caosiyao deposit area, which can be used as a standard dataset for reflection seismic processing in shallow coverage and hardrock areas. Situated at the juxtaposition of the Khondalite Belt and the Trans‐North China Orogen in the northern North China Craton, the Jining region hosts considerable known porphyry Mo deposits. As such, this open dataset can assist in research on deep geological structures and hence increase prospecting efficiency in geologically similar areas.

Quantitative effect of kerogen type on the hydrocarbon generation potential of Paleogene lacustrine source rocks, Liaohe Western Depression, China

Kerogen types exert a decisive effect on the onset and capacity of hydrocarbon generation of source rocks. Lacustrine source rocks in the Liaohe Western Depression are characterized by thick deposition, high total organic carbon (TOC) content, various kerogen types, and a wide range of thermal maturity. Consequently, their hydrocarbon generation potential and resource estimation can be misinterpreted. In this study, geochemical tests, numerical analysis, hydrocarbon generation kinetics, and basin modeling were integrated to investigate the differential effects of kerogen types on the hydrocarbon generation potential of lacustrine source rocks. Optimized hydrocarbon generation and expulsion (HGE) models of different kerogen types were established quantitatively upon abundant Rock-Eval/TOC/vitrinite reflectance (Ro) datasets. Three sets of good–excellent source rocks deposited in the fourth (Es4), third (Es3), and first (Es1) members of Paleogene Shahejie Formation, are predominantly types I–II1, II1–II2, and II–III, respectively. The activation energy of types I–II2 kerogen is concentrated (180–230 kcal/mol), whereas that of type III kerogen is widely distributed (150–280 kcal/mol). The original hydrocarbon generation potentials of types I, II1, II2, and III kerogens are 790, 510, 270, and 85 mg/g TOC, respectively. The Ro values of the hydrocarbon generation threshold for type I–III source rocks gradually increase from 0.42% to 0.74%, and Ro values of the hydrocarbon expulsion threshold increase from 0.49% to 0.87%. Types I and II1 source rocks are characterized by earlier hydrocarbon generation, more rapid hydrocarbon expulsion, and narrower hydrocarbon generation windows than types II2 and III source rocks. The kerogen types also affect the HGE history and resource potential. Three types (conventional, tight, and shale oil/gas) and three levels (realistic, expected, and prospective) of hydrocarbon resources of different members in the Liaohe Western Depression are evaluated. Findings suggest that the Es3 member has considerable conventional and unconventional hydrocarbon resources. This study can quantitatively characterize the hydrocarbon generation potential of source rocks with different kerogen types, and facilitate a quick and accurate assessment of hydrocarbon resources, providing strategies for future oil and gas exploration.

Heterogeneous Strain Distribution in the Malawi (Nyasa) Rift, East Africa: Implications for Rifting in Magma‐Poor, Multi‐Segment Rift Systems

AbstractHalf‐graben basins bounded by border faults typify early‐stage continental rifts. Deciphering the role that intra‐rift faults play in rift basin development is challenging as patterns of early‐stage faulting are commonly overprinted by subsequent deformation; yet the characterization of these faults is crucial to understand the fundamental controls on their evolution, their contribution to rift opening, and to assess their seismic hazard. By integrating multiple offshore seismic reflection data sets with age‐dated drill core, late‐Quaternary and cumulative faulting patterns are characterized in the Central and South Basins of the Malawi (Nyasa) Rift, an active, early‐stage rift system. Almost all intra‐rift faults offset a late‐Quaternary lake lowstand surface, suggesting they are active and should be considered in hazard assessments. Fault throw profiles reveal sawtooth patterns indicating segmented slip histories. Observed extension on intra‐rift faults is approximately twice that predicted from hanging wall flexure of the border fault, suggesting that intra‐rift faults accommodate a proportion of the regional extension. Cumulative and late‐Quaternary throws on intra‐rift faults are correlated with throw measured on the border fault in the Central Basin, whereas an anticorrelation is observed in the South Basin. Viewed in a regional context, these differences do not relate solely to the proposed southward younging of the rift. Instead, it is inferred that the distribution of extension is also influenced by variations in lithospheric structure and crustal heterogeneities that are documented along the rift axis.

A study on bubble suppression for deep marine reflection data acquired by a small airgun array

AbstractThe oscillatory bubble pulses generated by airguns in seawater are known to produce artefacts in seismic images. Although such artefacts are suppressible by employing larger airgun arrays in acquisition, small airgun arrays are used more often now to minimize the environmental impacts, thus raising the need for further suppressing bubble pulses at data processing stage. For a deep marine reflection dataset recently acquired by a small airgun array, we compare the effectiveness of three popular debubbling methods that estimate the far‐field source signature based on theoretical simulation and wavelets extracted from seafloor reflections and direct arrivals, respectively. In this case, due to the lack of near‐field measurements for calibration, the debubbling via simulation underperforms the two wavelet extraction methods. Overlapping events in the noisy response of seafloor sediments lead to the failure of the wavelet extraction from primary seafloor reflections. The estimated source signature based on direct arrivals achieves the best bubble suppression result, indicating the importance of signal‐to‐noise ratio and a low level of directionality of the small airgun array source.

BATHYMETRIC MAPPING OF CO TO ISLAND AREA, QUANG NINH PROVINCE USING SENTINEL-2 AND LANDSAT 8 IMAGES

This study developed an automated depth mapping methodology based on the surface reflection datasets of Landsat 8 and Sentinel-2 satellite imagery in Google Earth Engine. The study was conducted in the area of Co To island, Co To district, Quang Ninh province. The results of the study obtained a bathymetric map of the waters around the island, tested with 199 actual field measurement points for a coefficient of determination (R2 ) of 0.95 with Sentinel-2 images and 0.91 with Landsat 8 images. Besides, the root mean square error (RMSE) obtained with the result of the Sentinel-2 image and Landsat 8 image is 0.145 m and 0.195 m, respectively. The initial method shows automatic, fast, efficient, and reliable results in establishing depth maps in the ocean of Vietnam, especially in coastal and archipelago areas. In addition, the method also supports regular monitoring and updates.

Extent and variability of Mesozoic‐Cenozoic multi‐stage salt diapirs in the Southern Permian Basin, Southern North Sea

AbstractSalt structures can be used as an archive for tectonic and depositional processes as all salt structures respond distinctively. Few salt tectonic studies have investigated the evolution of multi‐stage salt structures, nevertheless, no previous study had systematically identified, mapped, nor classified, the evolution of multi‐stage salt structures in a regional study. Decades of hydrocarbon exploration and the heavily dense 3D seismic data available, make the Southern North Sea one of the best natural laboratories to investigate the evolution of salt structures. The Southern North Sea salt basin is a Late Permian Zechstein salt mega‐basin containing a myriad of salt structures. The complex tectonic evolution of the Southern North Sea created diverse Mesozoic structural sub‐basins with different tectonostratigraphic evolutions. We defined a nomenclature, linked to the mega‐stratigraphic sequences, for the classification of salt structures. We used a Two‐Way‐Travel‐Time 3D seismic reflection dataset and time‐thickness variations around salt structures to systematically analyse the evolution of salt structures across the diverse structural sub‐basins of the Southern North Sea. Multi‐stage salt diapirs were triggered halokinetically in the Early Triassic and are linked to regional palaeo‐depocentres controlled by the sub‐Zechstein structural configuration. Multi‐stage salt diapirs in the different sub‐basins evolved through three different regional phases and up to five distinctive local stages. The most complex salt diapirs developed in the Central Graben, Sole Pit High and Silver Pit Basin, where multi‐stage salt diapirs showed 4–5 local stages of salt diapirism. The multi‐stage evolution of salt structures should be thoroughly investigated to reduce risks and uncertainties in the energy sector and net zero projects, such as in carbon capturing and storage projects, and energy storage in man‐made salt caverns.

Tectonic Evolution of a Sedimented Oceanic Transform Fault: The Owen Transform Fault, Indian Ocean

AbstractThe Owen transform fault (OTF) connecting the Sheba and the Carlsberg spreading ridges in the Indian Ocean currently forms the active plate boundary between India and Somalia plates. This 330‐km‐long transform fault is by far the longest transform fault along the India‐Somalia plate boundary and its valley is buried under the thick distal turbidites of the Indus Fan with total thickness ranging from 1,000 to >5,000 m. A new set of seismic reflection and multibeam bathymetric data reveals remarkable transpressive structures along its entire length recorded as folds in the sedimentary cover, eruption of mud ridges at the seafloor, thrusts in the young oceanic lithosphere. Based on a new regional time‐calibration of the seismic reflectors, we show that sediments in the transform valley (post 8.6 Ma) recorded a period of tectonic quiescence until the onset of a transpressive event around 1.5–2.4 Ma that we relate to a minor change in India‐Somalia kinematics not captured by magnetic anomalies. This tectonic regime is still active based on compressive earthquakes and deformation of the most recent sediments. Transpression resulted in the formation of a proto‐median ridge and the coeval propagation of the tip of the Carlsberg Ridge into the Somalian plate. These features are typically encountered at many other transform faults but rarely captured in their very early stage.

Spatial prediction of soil salinity based on the Google Earth Engine platform with multitemporal synthetic remote sensing images

Accurately analyzing the spatial distribution of salinity at the regional scale is crucial for regional sustainable development. Currently, there are no reliable approaches for mapping salinity due to the substantial spatial variability of soil salinity. However, remote sensing technology has been successfully used to monitor soil properties in various locations. This research investigates an approach to choose the most appropriate remote sensing time window using a cloud computing platform and synthesizes multitemporal remote sensing images for high spatial resolution digital mapping of salinization at the regional scale. The research site for this experiment is the Werigan-Kuqa Oasis in Xinjiang, China. In the first stage, we screen the Landsat-8 surface reflectance datasets for four-time windows: April–October, May–September, June–August multitemporal, and July single-date images using the Google Earth Engine (GEE) cloud platform. Then, we synthesize images based on minimum, maximum, mean, and median values and construct multiple spectral indices. We completed model training and digital mapping in the second stage using a geemap. For the first time, we used geemap to integrate a local scikit-learn machine learning library with GEE to train a machine learning model. Next, we performed salinity prediction and mapping based on the best data set. This study demonstrates that (1) Various environmental variables contribute differently to modeling in the same time window. Additionally, these variables exhibit variation across different time windows. However, certain indices, including clay index (CLEX), near infrared (NIR), difference vegetation index (DVI), carbonate index (CAEX), green ratio vegetation index (GRVI), canopy response salinity (CRSI), and elevation, demonstrate stable contributions across different time windows. (2) Employing GEE to choose the suitable time window for synthesizing remote sensing images has a better prediction effect compared to single-date image prediction accuracy. Through experimental comparison, the best time window is May–September. (3) The mean synthesis approach from May to September exhibits the best performance in the model, while the median synthesis approach exhibits stable performance in the other two individual time windows. (4) Combining scikit-learn with GEE using Geemap improves model optimization and enhances the mapping performance. This study broadens the application of GEE in soil mapping and improves salinity prediction using multitemporal synthetic pictures with time frames.

Modes of gas migration and seepage on the salt-rooted Palmahim Disturbance, southeastern Mediterranean

Mass transport complexes often form key elements of petroleum systems, affecting sedimentary structures, seepage pathways and biodiversity hotspots on the seafloor. Yet, the feedback and interaction between these elements is not well constrained. This study investigates the modes of gas accumulation, migration, and seepage at the toe of Palmahim Disturbance (PD), a major salt-rooted mass transport complex across the southeastern Mediterranean margin, and adjacent edge of the eastern deep-sea fan of the Nile. Interpretation of a 3D time migrated seismic reflection dataset was calibrated with visual seafloor observations of active seepage. The toe of PD, in the eastern part of the study area, comprises four km-scale NE-SW oriented bathymetric ridges. At the crests of the eastern three of these ridges are six, hundreds-of-meters wide pockmark systems, four of which host verified seeps. Multiple sub-circular tens-of-meters wide pockmarks are mapped in the Nile fan west of PD. Active seepage was also identified within two elongate pockmarks along the flanks of the bordering Levant Channel. The seismic data reveal that the PD toe pockmarks and ridges overlie anomalous high amplitude seismic reflections (HASRs) from just beneath the surface to hundreds-of-meters deep intervals - below, at the base of and within a buried paleo mass transport deposit (MTD). These HASRs are interpreted to represent multiple gas-bearing intervals within thrust-faulted and folded blocks and their intermittent sealing, primarily at the base of the MTD. The Nile fan pockmarks overlie pervasive sub-seafloor HASRs that are overlain by low amplitude reflections, interpreted as gas-bearing channel-lobe sediments. Gas migration occurs via lateral to updip flow within depositional features and deeper folded sediments, and via sub-vertical flow, associated with the formation and leakage of transient reservoirs. Extension of fan sediments towards the PD pockmarks suggests additional updip focusing of gas, complementing sub-vertical gas flow to the PD pockmarks.

A Data-Driven Approach to the Unified Evaluation of Conventional and Unconventional Hydrocarbon Resources: Application to Low-Mature to Mature Source Rocks in the Liaohe Western Depression

Hydrocarbon potential evaluation is a high priority in oil/gas exploration which is significantly influenced by evaluation methods and subjective cognition. With the aim of quantitatively establishing a hydrocarbon generation and expulsion (HGE) model of source rocks, a data-driven approach is proposed based on abundant and readily available Rock-Eval/total organic carbon content (TOC)/vitrinite reflectance (VRo) datasets. This approach takes into account the original hydrocarbon generation potential (GPIo) and the loss of TOC. Hydrocarbon generation simulation was also adopted in this study. This data-driven method was applied to the Lower Paleogene Shahejie Formation (Es4), which has three sets of superior source rocks (average thickness > 250 m, TOC > 3%). The GPIo of the Es4 low-maturity source rock was 600 mg HC/g TOC. The initial maturity values of hydrocarbon generation and expulsion were 0.36% and 0.46%, respectively. The Gaosheng sub-member of the Es4 source rock had the largest amount of hydrocarbon generation but a limited amount of hydrocarbon expulsion, implying a favorable exploration of shale oil resources. By contrast, the values of the conventional, unconventional tight, and shale oil resource potentials of the Niuxintuo sub-member were 3.20 × 107, 7.70 × 107, and 5.93 × 108 t, respectively, indicating good prospects for tight oil and shale oil exploration. A comparison between the previous method and the data-driven method showed considerable differences in the restoration of GPIo and TOC, and both had their own limitations. This data-driven approach provides a quick and valid source rock evaluation method and can greatly enhance the accuracy of resource assessment.

Evaluation of Color Difference Prediction with CIECAM16 using CIE 2- and 10-degree Observers

CIE has recently recommended a new color appearance model CIECAM16 to replace CIECAM02. It was also intended to recommend a uniform color space (UCS) based on CIECAM16, CIECAM16-UCS, for predicting color difference. However, there was a debate as to whether CIECAM16 can be used to predict color difference, since it takes tristimulus values calculated using the CIE 2∘ observer as input, while tristimulus values for color difference are usually calculated using the CIE 10∘ observer, as in the CIEDE2000 formula. Thus, further evidence is needed before CAM16-UCS can be recommended by the CIE as uniform color space. In this paper, we investigate the likely difference in color difference prediction when using CAM16-UCS, and its potential statistical significance. Firstly, the reflectance of each pair of color samples in the visual color difference datasets: BFD-P, Leeds, RIT-DuPont and Witt was generated based on the given tristimulus values. Then, color difference ΔE2, F and ΔE10, F, with F being the CAM16-UCS, can be computed under any illuminant using the 2∘ and 10∘ observers respectively. Comparison results showed that the difference between ΔE2, F and ΔE10, F was not statistically significant. Finally, both ΔE2, F and ΔE10, F were used to predict the visual color difference DV and the STRESS values between ΔE2, F and DV , and between ΔE10, F and DV respectively. Statistical tests showed that the differences between ΔE2, F and DV , and between ΔE10, F and DV were not significant. Hence this study shows that CAM16-UCS can be reliably used for predicting color difference. The findings are valuable for CIE to recommend CAM16-UCS as a uniform color space. Currently CIE TC1-98 is investigating the establishment of a new colorimetric system based on cone response tristimulus values LMS. It is expected that the reflectance datasets generated from the color difference datasets will be useful for the evaluation of any new colorimetric system.

Seismic characterization of a fluid escape structure in the North Sea: the Scanner Pockmark complex area

SUMMARYSubsurface fluid escape structures are geological features which are commonly observed in sedimentary basins worldwide. Their identification and description have implications for various subsurface fluid flow applications, such as assuring integrity of overburden rocks to geological CO2 storage sites. In this study, we applied 3-D first-arrival traveltime tomography to a densely sampled wide-azimuth and wide-angle ocean bottom seismometer (OBS) data set collected over the Scanner Pockmark complex, a site of active gas venting in the North Sea. Seismic reflection data show a chimney structure underlying the Scanner Pockmark. The objective of this study was to characterize this chimney as a representative fluid escape structure in the North Sea. An area of 6$\times $6 km2 down to a depth of 2 km below sea level was investigated using a regularized tomography algorithm. In total, 182 069 manually picked traveltimes from 24 OBS were used. Our final velocity model contains compressional wave velocity perturbations ranging from −125 to +110 ms−1 relative to its average 1-D model and compares favourably with a coincident seismic reflection data set. The tomographic velocity model reveals that the chimney as observed in seismic reflection data is part of a larger complex fluid escape structure, and discriminates the genuine chimney from seismic artefacts. We find that part of the seeping gas migrates from a deep source, accumulates beneath the Crenulate Reflector unconformity at ∼250 m below seafloor (mbsf) before reaching the porous sediments of the Ling Bank and Coal Pit formation at <100 mbsf. In addition, the model shows that the venting gas at Scanner Pockmark is also being fed laterally through a narrow NW–SE shallow channel. Quantitative velocity analysis suggests a patchy gas saturation within the gas-charged sediments of the Ling Bank and the Coal Pit formations. Confined to the well-resolved regions, we estimate a base case average gas saturation of ∼9 per cent and in-situ gas volume of ∼1.64 $\times {10^6}\ {{\rm{m}}^3}$ across the Ling Bank and Coal Pit Fm. that can sustain the observed methane flux rate at the Scanner Pockmark for about 10 to 17 yr.

Depth migration of crustal-scale seismic reflection profiles: A case study in the Bohai Bay basin

The application of the pre-stack depth migration (PSDM) method using deep seismic reflection data is still a challenge. In this paper, a deep seismic reflection dataset collected from the Bohai Bay Basin is used to test the applicability of the pre-stack depth migration method. After improving the signal-to-noise ratio of the prestack gathers and building an accurate velocity model capturing lateral and vertical variations, a high-quality pre-stack depth migration profile is obtained. This profile shows detailed crustal structures and an undulating Moho. The depth difference between the east and west sides of the Moho imaged in the profile is about 6 km. The Moho is disrupted by several discontinuities. Compared with conventionally stacked time-migration profiles, the pre-stack depth migration profile provides a higher-resolution subsurface image with accurate depth information. Combining geological and geophysical data, the pre-stack depth migration profile reveals geologic structures responsible for crust thinning during the destruction of the North China Craton. The profile also provides more accurate depth domain information for further study of crust-mantle interaction in this area.

Spectral Reflectance Estimation from Camera Responses Using Local Optimal Dataset

A novel method is proposed to estimate surface-spectral reflectance from camera responses using a local optimal reflectance dataset. We adopt a multispectral imaging system that involves an RGB camera capturing multiple images under multiple light sources. A spectral reflectance database is utilized to locally determine the candidates to optimally estimate the spectral reflectance. The proposed estimation method comprises two stages: (1) selecting the local optimal reflectance dataset and (2) determining the best estimate using only the local optimal dataset. In (1), the camera responses are predicted for the respective reflectances in the database, and then the prediction errors are calculated to select the local optimal dataset. In (2), multiple methods are used; in particular, the Wiener and linear minimum mean square error estimators are used to calculate all statistics, based only on the local optimal dataset, and linear and quadratic programming methods are used to solve optimization problems with constraints. Experimental results using different mobile phone cameras show that the estimation accuracy has improved drastically. A much smaller local optimal dataset among spectral reflectance databases is enough to obtain the optimal estimates. The method has potential applications including fields of color science, image science and technology, computer vision, and graphics.

Hyperspectral reflectance dataset of pristine, weathered, and biofouled plastics

Abstract. This work presents a hyperspectral reflectance dataset of macroplastic samples acquired using Analytical Spectral Devices (ASD) FieldSpec 4. Samples analyzed consisted of pristine, artificially weathered, and biofouled plastic items and plastic debris samples collected in the docks of the Port of Antwerp and in the river Scheldt near Temse Bridge (Belgium). The hyperspectral signal of each sample was measured in controlled dry conditions in an optical calibration facility at the Vlaamse Instelling voor Technologisch Onderzoek (VITO; Flemish Institute for Technological Research) and, for a subset of plastics, under wet and submerged conditions in a silo tank at Flanders Hydraulics. The wet and submerged hyperspectral signals were measured in a mesocosm setting that mimicked environmentally relevant concentrations of freshwater microalgae and suspended sediment. The ASD was equipped with an 8∘ field of view at the calibration facility, and a 1∘ field of view was used in the mesocosm setting. The dataset obtained complies with the FAIR (Findable, Accessible, Interoperable, Reusable) principles and is available in the open-access repository Marine Data Archive (https://doi.org/10.14284/530, Leone et al., 2021).

MART-soil: A modified analytical radiative transfer mode for simulating multi-angular reflection of soils with different particle size

Understanding the angular reflection properties of soils and quantifying their particle size distribution through physical models is valuable for ecological and agricultural applications in arid and semi-arid regions. An analytical radiative transfer (ART) model has considered the absorptivity, k, as a constant to simulate the angular reflection of soil at two measurement directions and invert the soil particle size. However, the limited viewing directions cannot reflect the key role of ART in characterizing the effects of particle size on angular reflection. In this study, an ART model was first assessed based on a multi-angular soil reflection dataset from six types of dry soil samples with different particle size. The absorptivity, k, an inverted model parameter, was found to be strongly dependent on the angular distribution of soil reflection for different soil types. Subsequently, we coupled the ART model with a semiempirical function that can characterize the angular distribution of k, to improve the model’s ability in simulating the multi-angular reflection of soil. The modified ART model (defined as MART-Soil) made it possible to generate satisfying simulated multi-angular soil reflections with different particle sizes from all six soil types. Moreover, the model parameters of MART-Soil have the potential for representing different soil types in the simulation. These results indicate that MART-Soil model can quantify angular reflection properties of soils with different particle size and may also be useful for characterizing the radiative transfer process in land surfaces.

Machine learning for scattering data: strategies, perspectives and applications to surface scattering.

Machine learning (ML) has received enormous attention in science and beyond. Discussed here are the status, opportunities, challenges and limitations of ML as applied to X-ray and neutron scattering techniques, with an emphasis on surface scattering. Typical strategies are outlined, as well as possible pitfalls. Applications to reflectometry and grazing-incidence scattering are critically discussed. Comment is also given on the availability of training and test data for ML applications, such as neural networks, and a large reflectivity data set is provided as reference data for the community.