bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of Erosion/Corrosion Behavior of GRP under Harsh Operating Conditions
Authors: Hassan Mohamed K. , Redhwi Ahmad Muhammad N. , Mohamed Ahmed F. , Backar Ahmed H. , Abdellah Mohammed Y.
Published: December 2022

Glass-fiber-reinforced pipe (GRP) is a strong alternative to many other materials, such as cast iron and concrete. It is characterized by high corrosion resistance, resulting in good erosion/corrosion. For the erosion/corrosion test, commercially available GRPs were used, which are frequently utilized for oil field wastewater in harsh environments. This type of GRP material was subjected to simulated conditions replicating in situ or harsh environments. An extensive experiment was conducted. Three quantities of abrasive sand (250 g, 400 g and 500 g with a size of 65 µm) were mixed with 0.015 m3 of water. The abrasive sand samples were taken at a 90 degree angle from the wall of the cylinder tubes. Three flow rate conditions were selected, 0.01 m3/min, 0.0067 m3/min and 0.01 m3/min, with 10 wt.% chlorine. Furthermore, these tests were conducted at five different times: 1 h, 2 h, 3 h, 4 h and 5 h. The results show that the erosion rate increased both with an increasing amount of abrasive sand and with increasing flow rate. The maximum value for the erosion rate was more than three for a flow rate of 0.015 m3 with chlorine for 500 g of sand. The corrosion rate also showed the same trend, with the maximum corrosion rate being reached under the same conditions. It was found that the corrosion rate largely depends on the amount of weight loss, which is an indicator of the erosion effect. Therefore, GFRP provides better erosion/corrosion resistance in a harsh environment or in situ conditions.
Tuning the Morphology of HDPE/PP/PET Ternary Blends by Nanoparticles: A Simple Way to Improve the Performance of Mixed Recycled Plastics
Authors: Marotta Angela , Causa Andrea , Salzano de Luna Martina , Ambrogi Veronica , Filippone Giovanni
Published: December 2022

Due to a very low mixing entropy, most of the polymer pairs are immiscible. As a result, mixing polymers of different natures in a typical mechanical recycling process leads to materials with multiple interfaces and scarce interfacial adhesion and, consequently, with unacceptably low mechanical properties. Adding nanoparticles to multiphase polymeric matrices represents a viable route to mitigate this drawback of recycled plastics. Here, we use low amounts of organo-modified clay (Cloisite® 15A) to improve the performance of a ternary blend made of high-density polyethylene (HDPE), polypropylene (PP), and polyethylene terephtalate (PET). Rather than looking for the inherent reinforcing action of the nanofiller, this goal is pursued by using nanoparticles as a clever means to manipulate the micro-scale arrangement of the polymer phases. Starting from theoretical calculations, we obtained a radical change in the blend microstructure upon the addition of only 2-wt.% of nanoclay, with the obtaining of a finer morphology with an intimate interpenetration of the polymeric phases. Rather than on flexural and impact properties, this microstructure, deliberately promoted by nanoparticles, led to a substantial increase (>50 °C) of a softening temperature conventionally defined from dynamic-mechanical measurements.
Preparation of a Crosslinked Poly(imide-siloxane) for Application to Transistor Insulation
Authors: Park Hyeong-Joo , Choi Ju-Young , Jin Seung-Won , Lee Seung-Hyun , Choi Yun-Je , Kim Dam-Bi , Chung Chan-Moon
Published: December 2022

Insulated gate bipolar transistor (IGBT) is an important power device for the conversion, control, and transmission of semiconductor power, and is used in various industrial fields. The IGBT module currently uses silicone gel as an insulating layer. Since higher power density and more severe temperature applications have become the trend according to the development of electronic device industry, insulating materials with improved heat resistance and insulation performances should be developed. In this study, we intended to synthesize a new insulating material with enhanced thermal stability and reduced thermal conductivity. Poly(imide-siloxane) (PIS) was prepared and crosslinked through a hydrosilylation reaction to obtain a semi-solid Crosslinked PIS. Thermal decomposition temperature, thermal conductivity, optical transparency, dielectric constant, and rheological property of the Crosslinked PIS were investigated and compared to those of a commercial silicone gel. The Crosslinked PIS showed high thermal stability and low thermal conductivity, along with other desirable properties, and so could be useful as an IGBT-insulating material.
Characterization of Sweat Drying Performance of Single Layered Thermal Protective Fabrics Used in High-Risk Sector Workers’ Clothing
Authors: Mandal Sumit , Chowdhury Ishmam Zahin , Mazumder Nur-Us-Shafa , Agnew Robert J. , Boorady Lynn M.
Published: December 2022

Absorption and transportation of moisture from sweat are the crucial properties of the fabrics used in performance clothing. Sweat moisture is a significant factor that may cause discomfort to the wearer. The majority of the injuries and fatalities that happen to the high-risk sector workers in their line of duty may be caused by inadequate comfort provided by the protective uniform. The purpose of this study is to scientifically investigate the sweat drying performance of the different protective fabrics used in high-risk sectors’ workers’ clothing. Firstly, this study experimentally analyzed the sweat drying of protective fabrics with different attributes under various ambient environments and wearers’ internal physiology. Secondly, this study explained the phenomena of sweat drying in protective fabric through the theory of heat and mass transfer. Sweat drying performance of the fabrics used in functional clothing mainly depends on the evaporative resistance regardless of the presence of water and oil repellent coating on the fabric surface. The drying performance increases with the increased wetted area and increased air flow. The wetted area depends on the absorption and wicking properties of the fabrics. The findings of this research will advance the field by developing knowledge on sweat drying performance of fabrics used in protective clothing; in turn, this could provide better comfort and safety to high-risk sectors’ workers.
Variable Effects of the In Ovo Administration of an Escherichia coli Vaccine in the Amnion or Air Cell on Commercial Layer Embryo and Hatchling Development
Authors: Lindsey Lauren L. , Elliott Katie Elaine Collins , Fatemi Seyed Abolghasem , Evans Jeff D. , Mousstaaid Ayoub , Gerard Patrick D. , Peebles Edgar David
Published: December 2022

The effects of injecting the Poulvac E. coli vaccine (PECV) into either the air cell (AC) or amnion (AM) at different dosages at 18 days of incubation (DOI) on Hy-Line W-36-layer embryo and hatchling development were investigated. Serial dilutions of the PECV in diluent provided either 6.5 × 104, 6.5 × 103, 6.5 × 102, or 6.5 × 101 CFU dosages of E. coli. A diluent only injection treatment was included as a control. A total of 19 live embryonated eggs in each of 10 treatment groups were represented on each of 16 replicate levels (3040 total) in the hatcher unit. At 19 DOI, swabs of the AM indicated that the 6.5 × 101 and 6.5 × 102 CFU dosages provided a 50% level of PECV presence, whereas the 6.5 × 103 and 6.5 × 104 CFU dosages provided a 100% level of PECV presence. Conversely, only the 6.5 × 103 and 6.5 × 104 CFU dosages provided a 50% level of PECV presence in the AC. At all E. coli dosage levels, injection in the AM led to higher percentages of live or dead embryos that failed to pip (PEIS) (p = 0.001) or complete hatch (PEPE) (p ≤ 0.001) and a lower percentage of live fully hatched chicks (HI) (p ≤ 0.001), when compared to those injected in the AC. Like HI, significantly lower percentages of female hatchlings were also observed at 22 DOI for the AM compared to the AC injection, for all dosages except for the 6.5 × 102 CFU dosage. However, at all the dosages above the 6.5 × 101 CFU dosage, the AM injection resulted in a lower mean hatchling body weight (p = 0.010) at 22 DOI. In conclusion, E. coli populations were more prevalent in the AM than in the AC after the injection of the PECV in those sites. Furthermore, the injection of the PECV in the AM at all E. coli dosages generally increased late embryo mortality and decreased hatchability and hatchling body weight in comparison to an AC injection. It is concluded that the negative impact of the in ovo administration of the PECV in the AM at 18 DOI on the hatch process is dose dependent. However, effects of an increase in AC dosages and a decrease in AM dosages should be further investigated.
Domestic Wastewater Treatment Using Constructed Wetland with Para Grass Combined with Sludge Adsorption, Case Study in Vietnam: An Efficient and Alternative Way
Authors: Ho Van Thi Thanh , Bui Khang Quang , Le Dien Vinh , Chau Dung Hung , Hoang Bich Ngoc , Pham Huong Thi , Nguyen Anh Tuan
Published: December 2022

The environmental pollution due to wastewater, especially domestic wastewater, is becoming more serious. Thus, this study was performed to assess the removal of pollutants by the combination of wetland technology, specifically constructed wetland (CW), with Para grass (Brachiaria mutica) together with the adsorption of red sludge. With an organic loading rate (OLR) of 120 (kg COD/ha/day), the treatment efficiency for wastewater in this study is quite high and the concentrations of parameters in the effluent were lower than the limits established by the QCVN 14:2015/BTNMT for domestic wastewater, which indicated the feasibility of this combination. These results are expected to open the possibilities of using environmentally friendly processes for wastewater treatment in urban and industrial areas.
Numerical Investigation of the Use of Boron Nitride/Water and Conventional Nanofluids in a Microchannel Heat Sink
Authors: Kaya Fuat
Published: December 2022

The purpose of this paper is to study the effects of the use of boron nitride (BN) and other conventional nanoparticles (Al2O3, CuO and TiO2) on pressure drop and heat transfer in a microchannel. The governing equations for forced fluid flow and heat transfer were worked out by using fluent computational fluid dynamics (CFD) code. Computational results collected from fluent CFD code for Al2O3 as the nano-particle were compared with numerical values used in the literature for validation. The basis of a water-cooled (pure water, Al2O3/Water, CuO/Water, TiO2/Water and BN/Water) smooth microchannel was outlined, and then the corresponding laminar flow and heat transfer were evaluated numerically. The results from the numerical tests (NT) express good agreement with the values found in the literature. These results also indicate, through the comparison which was performed by taking the heat transfer and pressure loss parameters between BN and other widely used conventional nanoparticles (Al2O3, CuO and TiO2) into consideration, that BN is the more favorable nanoparticle. In comparison to other common nanoparticles (Al2O3, CuO and TiO2), BN enhances heat transfer and slightly raised pressure losses owing to its high thermal conductivity and high velocity profile because of low density. It is also chemically stable at the highest temperature relative to most solid materials. Thus, it has a structure that can be used in cooling systems for a long time without causing a problem of agglomeration.
Development for Cooling Operations through a Model of Nanofluid Flow with Variable Heat Flux and Thermal Radiation
Authors: Alrehili Mohammed
Published: December 2022

This article discusses the flow of a non-Newtonian Carreau nanoliquid across a stretching radiative nonlinear sheet that is exposed to a variable heat flux. Analysis is done with changing thermal conductivity since it affects how heat and mass transfer occur. Nanoparticles are modelled using the Brownian motion and the thermophoresis phenomenon. The introduction of a similar solution to our challenge, as obtained by our paper, received significant attention. To create a dimensionless system, the governing partial differential equations are subjected to the mathematical model’s convenient similarity transformations after it has been developed. The numerical solution of the coupled highly nonlinear ordinary differential equations characterizing velocity, temperature and nanoparticles concentration is shown using an effective shooting approach. Additionally, all factors affecting the situation that could increase the effectiveness of cooling operations will be looked into. Results for velocity, the thermal field, the concentration of nanoparticles, the skin-friction coefficient, and the local Nusselt and Sherwood numbers are provided and explored. Tables and graphics will be used to illustrate the paper’s conclusions. Results are also given in comparison to existing literature. Excellent agreement has been reached. Furthermore, it is clear that the local Sherwood number, the local Nusselt number, and the skin friction coefficient are all observed to increase as the power law index does.
Measuring and Promoting the Success of an Open Science Discovery Platform through “Compass Indicators”: The GoTriple Case
Authors: De Paoli Stefano , Blotière Emilie , Forbes Paula , Arasteh-Roodsary Sona
Published: December 2022

Previous research on indicators for measuring the success of Open Science tends to operate at a macro/global level and very rarely addresses the need to measure success at the level of a single project. However, this previous research has the merit of arguing for the definition of indicators that offer an alternative to more traditional bibliometric measures or indicators that focus on mere performance. This paper is the outcome of work conducted for a specific project that aims to build a discovery platform for social sciences and humanities, the platform GoTriple. GoTriple is designed taking inspiration from Open Science principles and has been built through a user-centered approach. The paper details the practice-led work conducted by the GoTriple team for assessing the meaning of the term success for the project and to identify indicators. To this end, this paper proposes the concept of compass indicators and presents how the project team arrived at the definition of this concept. The paper also highlights a distinction between compass indicators, which are modest measures, and key performance indicators, which tend to be tied up with measurable objectives. Compass indicators are defined as indicators that do not aim to achieve a specified numerical target of success but rather explain the journey of a project toward achieving certain desirable outcomes and offer insights to take action. Compass indicators defined for the project embrace areas such as diversity, inclusivity, collaboration, and the general use of the platform. In the final discussion, the paper offers reflections on the potential relevance of the notion of compass indicators and closes with a discussion of the next steps for this work.
Visual Metaphor and Image Interpretation of “Guan-Yin-Ma-Lian”
Authors: Zhang Beibei , Liu Anlu , Shu Xiaping
Published: December 2022

From the perspective of production technology, the god image usually has two manifestations: paintings and sculptures, while there are two main forms of paintings: murals and prints. In this paper, the engravings of gods named “Guan-yin-ma-lian” (觀音媽聯) were taken as the research object. The origin of “Guan-yin-ma-lian” is traced back. The form of plane composition of this type of engraving is analyzed from the perspective of iconology. The image of Mazu (媽祖) and its implied meaning in “Guan-yin-ma-lian” are discussed from the perspective of folk beliefs. As one of the plane images of Mazu, “Guan-yin-ma-lian” is not only a very important religious art in folk culture, but also an important link closely connecting Mazu belief circles at home and abroad. It is also an important cultural asset of Chinese people who worship Mazu.
Christian Religioscapes in the Levant: The Question of Geo-Religious Materiality of a Minority in Decline
Authors: Trantas Georgios E.
Published: December 2022

The Levant has diachronically been a highly contested region in terms of rights and entitlement, and, ultimately, in terms of sovereignty over territory. This is not a new phenomenon, particularly in a region that is laden with history. Religion has been, and still is, central in the demarcation and distinction of territorial custodianship, administration, and ownership, as it codetermines the terms and limits of boundaries by way of materiality in the public sphere. Antitheses and frictions are frequent over disputed territories and spatialities, where religioscapes overlap or intersect in a non-harmonious fashion. Especially at times of political unrest, religion, as a value system, as cultural heritage and as a collective identifier of self-perception, has a central role in the signification of (pre)dominance over territory. This holds true particularly for the Christian minorities in the Levant, with immediate consequences on their religious sites and their overall religiocultural heritage. In this light, I argue that this issue deserves extensive further study, to better understand and explain the complex georeligious landscape in the region, and specifically the place of Christianity therein by way of its materiality, given that the latter is mutatis mutandis under threat.
High-Resolution Mapping of Seaweed Aquaculture along the Jiangsu Coast of China Using Google Earth Engine (2016–2022)
Authors: Cheng Jie , Jia Nan , Chen Ruishan , Guo Xiaona , Ge Jianzhong , Zhou Fucang
Published: December 2022

Seaweed aquaculture produces enormous economic and ecological service benefits, making significant contributions to achieving global Sustainable Development Goals (SDGs). However, large-scale development of seaweed aquaculture and the unreasonable use of aquaculture rafts may trigger green tide, bringing negative ecological, social, and economic impacts. Therefore, it is vital to monitor the seaweed aquaculture industry accurately. Here, we mapped 10-m-resolution seaweed aquaculture along the Jiangsu coast of China based on active and passive remote sensing (Sentinel-1/2) and Random Forest using Google Earth Engine. The results demonstrate satisfactory model performance and data accuracy. The square seaweed aquaculture in the Lianyungang Offshore (Mode-I) has gradually expanded to the deep sea since 2016, with a maximum area of 194.06 km2 in 2018. Between 2021 and 2022, the area of the strip-shaped seaweed aquaculture in Subei radiation shoals (Mode-II) was considerably reduced, with most of the reduced land lying on the east side of the Dafeng Elk National Nature Reserve. In general, the area of the seaweed aquaculture in the prohibited breeding area was reduced from 20.32 km2 to 3.13 km2, and the area of the seaweed aquaculture in the restricted breeding area was reduced from 149.71 km2 to 33.15 km2. Results show that under the policy restriction, the scale of unsustainable seaweed aquaculture along the Jiangsu coast has been greatly reduced within seven years. This study can provide an efficient approach for the medium-scale extraction of seaweed aquaculture and provide decision support for the sustainable development of marine aquaculture.
The Suitability of UAV-Derived DSMs and the Impact of DEM Resolutions on Rockfall Numerical Simulations: A Case Study of the Bouanane Active Scarp, Tétouan, Northern Morocco
Authors: Bounab Ali , El Kharim Younes , El Hamdouni Rachid
Published: December 2022

Rockfall simulations constitute the first step toward hazard assessments and can guide future rockfall prevention efforts. In this work, we assess the impact of digital elevation model (DEM) resolution on the accuracy of numerical rockfall simulation outputs. For this purpose, we compared the simulation output obtained using 1 m, 2 m and 3 m resolution UAV-derived DEMs, to two other models based on coarser topographic data (a 5 m resolution DEM obtained through interpolating elevation contours and the Shuttle Radar Topographic Mission 30m DEM). To generate the validation data, we conducted field surveys in order to map the real trajectories of three boulders that were detached during a rockfall event that occurred on 1 December 2018. Our findings suggest that the use of low to medium-resolution DEMs translated into large errors in the shape of the simulated trajectories as well as the computed runout distances, which appeared to be exaggerated by such models. The geometry of the runout area and the targets of the potential rockfall events also appeared to be different from those mapped on the field. This hindered the efficiency of any prevention or correction measures. On the other hand, the 1m UAV-derived model produced more accurate results relative to the field data. Therefore, it is accurate enough for rockfall simulations and hazard research applications. Although such remote sensing techniques may require additional expenses, our results suggest that the enhanced accuracy of the models is worth the investment.
Analysis of BDS-3 Real-Time Satellite Clock Offset Estimated in Global and Asia-Pacific and the Corresponding PPP Performances
Authors: Wang Hu , Li Pengyuan , Wang Jiexian , Ma Hongyang , Hou Yangfei , Ren Yingying
Published: December 2022

The quality of satellite clock offset affects the performances of positioning, navigation and timing services, and thus it is essential to the Global Navigation Satellite System (GNSS). This research focuses on the estimation of BeiDou Navigation Satellite System (BDS) real-time precise satellite clock offset by using GNSS stations located in the Global and Asia-Pacific region based on the mixed-difference model. The precision of the estimated BDS clock corrections is then analyzed with the classification of the orbit types, satellite generations, and atomic clock types. The results show that the precision of the BDS clock offset estimated in the Asia-Pacific for Geosynchronous Earth Orbit (GEO), Inclined Geosynchronous Satellite Orbit (IGSO) and Medium Earth Orbit (MEO) satellites are 0.204 ns, 0.077 ns and 0.085 ns, respectively, as compared to those of clock offsets estimated in globally distributed stations. The average precision of the BDS-3 satellites clock offset estimated in global region is 0.074 ns, which is much better than the 0.130 ns of BDS-2. Furthermore, analyzing the characteristics of the corresponding atomic clocks can explain the performance of the estimated satellite clock offset, and the stability and accuracy of various parameters of the Passive Hydrogen Maser (PHM) atomic clocks are better than those of Rubidium (Rb) atomic clocks. In the positioning domain, the real-time clocks estimated in the global/Asia-Pacific have been applied to BDS kinematic Precise Point Positioning (PPP) in different regions. The Root Mean Square (RMS) of positioning results in global real-time kinematic PPP is within 4 cm in the horizontal direction and about 6 cm in the vertical direction. Hence, the BDS real-time clock offset can supply the centimeter-level positioning demand around the world.
Retrieval of Aerosol Microphysical Properties from Multi-Wavelength Mie–Raman Lidar Using Maximum Likelihood Estimation: Algorithm, Performance, and Application
Authors: Chang Yuyang , Hu Qiaoyun , Goloub Philippe , Veselovskii Igor , Podvin Thierry
Published: December 2022

Lidar plays an essential role in monitoring the vertical variation of atmospheric aerosols. However, due to the limited information that lidar measurements provide, ill-posedness still remains a big challenge in quantitative lidar remote sensing. In this study, we describe the Basic algOrithm for REtrieval of Aerosol with Lidar (BOREAL), which is based on maximum likelihood estimation (MLE), and retrieve aerosol microphysical properties from extinction and backscattering measurements of multi-wavelength Mie–Raman lidar systems. The algorithm utilizes different types of a priori constraints to better constrain the solution space and suppress the influence of the ill-posedness. Sensitivity test demonstrates that BOREAL could retrieve particle volume size distribution (VSD), total volume concentration (Vt), effective radius (Reff), and complex refractive index (CRI = n − ik) of simulated aerosol models with satisfying accuracy. The application of the algorithm to real aerosol events measured by LIlle Lidar AtmosphereS (LILAS) shows it is able to realize fast and reliable retrievals of different aerosol scenarios (dust, aged-transported smoke, and urban aerosols) with almost uniform and simple pre-settings. Furthermore, the algorithmic principle allows BOREAL to incorporate measurements with different and non-linearly related errors to the retrieved parameters, which makes it a flexible and generalized algorithm for lidar retrieval.
Using Deep Learning to Model Elevation Differences between Radar and Laser Altimetry
Authors: Horton Alex , Ewart Martin , Gourmelen Noel , Fettweis Xavier , Storkey Amos
Published: December 2022

Satellite and airborne observations of surface elevation are critical in understanding climatic and glaciological processes and quantifying their impact on changes in ice masses and sea level contribution. With the growing number of dedicated airborne campaigns and experimental and operational satellite missions, the science community has access to unprecedented and ever-increasing data. Combining elevation datasets allows potentially greater spatial-temporal coverage and improved accuracy; however, combining data from different sensor types and acquisition modes is difficult by differences in intrinsic sensor properties and processing methods. This study focuses on the combination of elevation measurements derived from ICESat-2 and Operation IceBridge LIDAR instruments and from CryoSat-2’s novel interferometric radar altimeter over Greenland. We develop a deep neural network based on sub-waveform information from CryoSat-2, elevation differences between radar and LIDAR, and additional inputs representing local geophysical information. A time series of maps are created showing observed LIDAR-radar differences and neural network model predictions. Mean LIDAR vs. interferometric radar adjustments and the broad spatial and temporal trends thereof are recreated by the neural network. The neural network also predicts radar-LIDAR differences with respect to waveform parameters better than a simple linear model; however, point level adjustments and the magnitudes of the spatial and temporal trends are underestimated.
Multispectral UAV-Based Monitoring of Leek Dry-Biomass and Nitrogen Uptake across Multiple Sites and Growing Seasons
Authors: Haumont Jérémie , Lootens Peter , Cool Simon , Van Beek Jonathan , Raymaekers Dries , Ampe Eva , De Cuypere Tim , Bes Onno , Bodyn Jonas , Saeys Wouter
Published: December 2022

Leek farmers tend to apply too much nitrogen fertilizer as its cost is relatively low compared to the gross value of leek. Recently, several studies have shown that proximal sensing technologies could accurately monitor the crop nitrogen content and biomass. However, their implementation is impeded by practical limitations and the limited area they can cover. UAV-based monitoring might alleviate these issues. Studies on UAV-based vegetable crop monitoring are still limited. Because of the economic importance and environmental impact of leeks in Flanders, this study aimed to investigate the ability of UAV-based multispectral imaging to accurately monitor leek nitrogen uptake and dry biomass across multiple fields and seasons. Different modelling approaches were tested using twelve spectral VIs and the interquartile range of each of these VIs within the experimental plots as predictors. In a leave-one-flight out cross-validation (LOF-CV), leek dry biomass (DBM) was most accurately predicted using a lasso regression model (RMSEct = 6.60 g plant−1, R2= 0.90). Leek N-uptake was predicted most accurately by a simple linear regression model based on the red wide dynamic range (RWDRVI) (RMSEct = 0.22 gN plant−1, R2 = 0.85). The results showed that randomized Kfold-CV is an undesirable approach. It resulted in more consistent and lower RMSE values during model training and selection, but worse performance on new data. This would be due to information leakage of flight-specific conditions in the validation data split. However, the model predictions were less accurate for data acquired in a different growing season (DBM: RMSEP = 8.50 g plant−1, R2 = 0.77; N-uptake: RMSEP = 0.27 gN plant−1, R2 = 0.68). Recalibration might solve this issue, but additional research is required to cope with this effect during image acquisition and processing. Further improvement of the model robustness could be obtained through the inclusion of phenological parameters such as crop height.
Effects of Viewing Geometry on Multispectral Lidar-Based Needle-Leaved Tree Species Identification
Authors: Budei Brindusa Cristina , St-Onge Benoît , Fournier Richard A. , Kneeshaw Daniel
Published: December 2022

Identifying tree species with remote sensing techniques, such as lidar, can improve forest management decision-making, but differences in scan angle may influence classification accuracy. The multispectral Titan lidar (Teledyne Optech Inc., Vaughan, ON, Canada) has three integrated lasers with different wavelengths (1550, 1064 and 532 nm), and with different scan angle planes (respectively tilted at 3.5°, 0° and 7° relative to a vertical plane). The use of multispectral lidar improved tree species separation, compared to mono-spectral lidar, by providing classification features that were computed from intensities in each channel, or from pairs of channels as ratios and normalized indices (NDVIs). The objective of the present study was to evaluate whether scan angle (up to 20°) influences 3D and intensity feature values and if this influence affected species classification accuracy. In Ontario (Canada), six needle-leaf species were sampled to train classifiers with different feature selection. We found the correlation between feature values and scan angle to be poor (mainly below |±0.2|), which led to changes in tree species classification accuracy of 1% (all features) and 8% (3D features only). Intensity normalization for range improved accuracies by 8% for classifications using only single-channel intensities, and 2–4% when features that were unaffected by normalization were added, such as 3D features or NDVIs.
Bi-Kernel Graph Neural Network with Adaptive Propagation Mechanism for Hyperspectral Image Classification
Authors: Hu Haojie , Ding Yao , He Fang , Zhang Fenggan , Zhao Jianwei , Yao Minli
Published: December 2022

Graph neural networks (GNNs) have been widely applied for hyperspectral image (HSI) classification, due to their impressive representation ability. It is well-known that typical GNNs and their variants work under the assumption of homophily, while most existing GNN-based HSI classification methods neglect the heterophily that is widely present in the constructed graph structure. To deal with this problem, a homophily-guided Bi-Kernel Graph Neural Network (BKGNN) is developed for HSI classification. In the proposed BKGNN, we estimate the homophily between node pairs according to a learnable homophily degree matrix, which is then applied to change the propagation mechanism by adaptively selecting two different kernels to capture homophily and heterophily information. Meanwhile, the learning process of the homophily degree matrix and the bi-kernel feature propagation process are trained jointly to enhance each other in an end-to-end fashion. Extensive experiments on three public data sets demonstrate the effectiveness of the proposed method.
Upper Mantle beneath the Myanmar and Surrounding Tomography: New Insight into Plate Subduction and Volcanism
Authors: Meng Xiangyu , Li Tonglin , Zhang Rongzhe , Shi Huiyan , Han Ying
Published: December 2022

Myanmar and its surrounding areas have complex topography and strong tectonic movement, which has always been a challenge to most geoscientists. We used teleseismic tomography to study the subsurface velocity structure in this area. We present a new P-wave tomographic model beneath Myanmar and the surrounding areas by inverting 129,788 arrival-time data recorded by 372 stations. We found an inclined high-velocity subducting plate beneath central Myanmar, where the dip angle becomes smaller near 25°~26°N, and the seismic depth is limited below 200 km. The Indian oceanic lithosphere is being detached from the Indian continental lithosphere, which limits the depth of the earthquake. The active Tengchong volcano is underlain by a prominent low-velocity (low-V) anomaly in the shallow mantle, which may be caused by the subduction and dehydration of the Burma microplate (or Indian plate). The formation of the Singu volcano is related to the mantle flow of the Qinghai–Tibet plateau and the tearing of the Indian plate. The Yangtze craton (beneath the Sichuan Basin) shows a high-velocity anomaly, and both the shallow and deep parts have been destroyed, which may be related to the upwelling of deep heat flow.
Evaluation and Improvement of No-Ground-Truth Dual Band Algorithm for Shallow Water Depth Retrieval: A Case Study of a Coastal Island
Authors: Yang Qingjie , Chen Jianyu , Chen Benqing , Tao Bangyi
Published: December 2022

Conventional bathymetric inversion approaches require bathymetric data as ground truth to obtain shallow water depth from high spatial resolution remote sensing imagery. Thus, bathymetric mapping methods that do not require inputs from in situ measurements are highly desirable. In this paper, we propose a dual-band model improvement method and evaluate the performance of this novel dual-band model approach to obtain the underwater terrain around a coastal island by using four WorldView-2/3 imageries. Then, we validate the results through changing water column properties with the Kd multiple linear regression model simulated by Hydrolight. We multiply the best coefficient and blue–green band value with different substrates on the pixels, which sample along the coastal line and isobath. The results show that the mean bias of inversed depth ranges from 1.73 to 2.96 m in the four imageries. The overall accuracy of root mean square errors (RMSEs) is better for depths shallower than 10 m, and the average relative error is 11.89%. The inversion accuracy of this new model is higher than Lee’s classical Kd model and has a wider range of applications than Chen’s dual-band model. The no-ground-truth dual-band algorithm has higher accuracy than the other log-ratio methods mentioned in this paper.
Ultra-High-Resolution UAV-Based Detection of Alternaria solani Infections in Potato Fields
Authors: Van De Vijver Ruben , Mertens Koen , Heungens Kurt , Nuyttens David , Wieme Jana , Maes Wouter H. , Van Beek Jonathan , Somers Ben , Saeys Wouter
Published: December 2022

Automatic detection of foliar diseases in potato fields, such as early blight caused by Alternaria solani, could allow farmers to reduce the application of plant protection products while minimizing production losses. UAV-based, high resolution, NIR-sensitive cameras offer the advantage of a detailed top-down perspective, with high-contrast images ideally suited for detecting Alternaria solani lesions. A field experiment was conducted with 8 plots housing 256 infected plants which were monitored 6 times over a 16-day period with a UAV. A modified RGB camera, sensitive to NIR, was combined with a superzoom lens to obtain ultra-high-resolution images with a spatial resolution of 0.3 mm/px. More than 15,000 lesions were annotated with points in two full size images corresponding to 1250 cropped tiles of 256 by 256 pixels. A deep learning U-Net model was trained to predict the density of Alternaria solani lesions for every pixel. In this way, density maps were calculated to indicate disease hotspots as a guide for the farmer.
Assessment of Carbon Productivity Trends and Their Resilience to Drought Disturbances in the Middle East Based on Multi-Decadal Space-Based Datasets
Authors: Alsafadi Karam , Bi Shuoben , Bashir Bashar , Mohammed Safwan , Sammen Saad Sh. , Alsalman Abdullah , Srivastava Amit Kumar , El Kenawy Ahmed
Published: December 2022

Gross primary production (GPP) is a key component in assessing the global change in carbon uptake and in evaluating the impacts of climate change on terrestrial ecosystems. A decrease in the photosynthetic rate due to stomata closing by vegetation could have an impact on GPP. Nonetheless, the uncertainty in long-term GPP patterns and their resilience to drought disturbances has not yet been examined thoroughly. In this study, four state-of-the-art GPP datasets, including the revised EC-LUE algorithm-driven GPP (GLASS-GPP), the EC flux tower upscaling-based GPP (FluxCom-GPP), the MODIS algorithm-driven GPP model (GIMMS-GPP), and the vegetation photosynthesis model-GPP (VPM-GPP), were used to assess GPP characteristics in the Middle East region for 36 years spanning the period of 1982 to 2016. All investigated datasets revealed an increasing trend over the study period, albeit with a more pronounced upward trend for the VPM-GPP dataset in the most recent decades (2000–2016). On the other hand, FluxCom-GPP exhibited less variability than the other datasets. In addition, while GLASS-GPP presented a significant increasing trend in some parts of the region, significant negative trends dominated the other parts. This study defined six significant drought episodes that occurred in the Middle East region between 1982 and 2017. The most severe drought events were recorded in 1985, 1989–1990, 1994, 1999–2001, 2008, and 2015, spreading over more than 15% of the total area of the region. The extreme droughts accounted for a high decline in GPP in the north of Iraq, the northeast of Syria, and the southwest of Iran, where 20.2 and 40.8% of the ecosystem’s GPP were severely non-resilient to drought according to the GLASS and VPM-based GPP responses, respectively. The spatial distribution patterns of the correlations between the SEDI and GPP products were somewhat similar and coherent. The highest positive correlations were detected in the central and western parts of Turkey, the western and northeastern parts of Iran, and north Iraq, which showed anomalous r values (r = 0.7), especially for the SEDI-VPM and SEDI-FluxCom GPP associations. The findings of this study can provide a solid base for identifying at-risk regions in the Middle East in terms of climate change impacts, which will allow for better management of ecosystems and proper implementation of climate policies.
War Related Building Damage Assessment in Kyiv, Ukraine, Using Sentinel-1 Radar and Sentinel-2 Optical Images
Authors: Aimaiti Yusupujiang , Sanon Christina , Koch Magaly , Baise Laurie G. , Moaveni Babak
Published: December 2022

Natural and anthropogenic disasters can cause significant damage to urban infrastructure, landscape, and loss of human life. Satellite based remote sensing plays a key role in rapid damage assessment, post-disaster reconnaissance and recovery. In this study, we aim to assess the performance of Sentinel-1 and Sentinel-2 data for building damage assessment in Kyiv, the capital city of Ukraine, due to the ongoing war with Russia. For damage assessment, we employ a simple and robust SAR log ratio of intensity for the Sentinel-1, and a texture analysis for the Sentinel-2. To suppress changes from other features and landcover types not related to urban areas, we construct a mask of the built-up area using the OpenStreetMap building footprints and World Settlement Footprint (WSF), respectively. As it is difficult to get ground truth data in the ongoing war zone, a qualitative accuracy assessment with the very high-resolution optical images and a quantitative assessment with the United Nations Satellite Center (UNOSAT) damage assessment map was conducted. The results indicated that the damaged buildings are mainly concentrated in the northwestern part of the study area, wherein Irpin, and the neighboring towns of Bucha and Hostomel are located. The detected building damages show a good match with the reference WorldView images. Compared with the damage assessment map by UNOSAT, 58% of the damaged buildings were correctly classified. The results of this study highlight the potential offered by publicly available medium resolution satellite imagery for rapid mapping damage to provide initial reference data immediately after a disaster.
Modelling the Dynamics of Carbon Storages for Pinus densata Using Landsat Images in Shangri-La Considering Topographic Factors
Authors: Liao Yi , Zhang Jialong , Bao Rui , Xu Dongfan , Han Dongyang
Published: December 2022

Accurate estimation of forest carbon storage is essential for understanding the dynamics of forest resources and optimizing decisions for forest resource management. In order to explore the changes in the carbon storage of Pinus densata in Shangri-La and the influence of topography on carbon storage, two dynamic models were developed based on the National Forest Inventory (NFI) and Landsat TM/OLI images with a 5-year interval change and annual average change. The three modelling methods used were partial least squares (PLSR), random forest (RF) and gradient boosting regression tree (GBRT). Various spectral and texture features of the images were calculated and filtered before modelling. The terrain niche index (TNI), which is able to reflect the combined effect of elevation and slope, was added to the dynamic model, the optimal model was selected to estimate the carbon storage, and the topographic conditions in areas of change in carbon storage were analyzed. The results showed that: (1) The dynamic model based on 5-year interval change data performs better than the dynamic model with annual average change data, and the RF model has a higher accuracy compared to the PLSR and GBRT models. (2) The addition of TNI improved the accuracy, in which R2 is improved by up to 10.48% at most, RMSE is reduced by up to 7.32% at most, and MAE is reduced by up to 8.89% at most, and the RF model based on the 5-year interval change data has the highest accuracy after adding TNI, with an R2 of 0.87, an RMSE of 3.82 t-C·ha−1, and a MAE of 1.78 t-C·ha−1. (3) The direct estimation results of the dynamic model showed that the carbon storage of Pinus densata in Shangri-La decreased in 1987–1992 and 1997–2002, and increased in 1992–1997, 2002–2007, 2007–2012, and 2012–2017. (4) The trend of increasing or decreasing carbon storage in each period is not exactly the same on the TNI gradient, according to the dominant distribution, as topographic conditions with lower elevations or gentler slopes are favorable for the accumulation of carbon storage, while the decreasing area of carbon storage is more randomly distributed topographically. This study develops a dynamic estimation model of carbon storage considering topographic factors, which provides a solution for the accurate estimation of forest carbon storage in regions with a complex topography.
Applications of Chromatographic Techniques in Food and Environmental Analysis
Authors: Socas-Rodríguez Bárbara
Published: December 2022

Throughout history, analytical chemistry has been a key area for many other scientific fields [...]
Assessment of Future Land Use/Land Cover Scenarios on the Hydrology of a Coastal Basin in South-Central Chile
Authors: Pereira Camila Orellana , Escanilla-Minchel Rossana , González Alejandra Cortés , Alcayaga Hernán , Aguayo Mauricio , Arias Miguel Aguayo , Flores Alejandro N.
Published: December 2022

Land use and land cover (LULC) change is one of the clearest representations of the global environmental change phenomenon at various spatial and temporal scales. Chile is worldwide recognized to have areas dedicated to non-native forest plantations that specifically in coastal range show high environmental and economic deterioration, questioning the sustainability of the forestry industry. Currently, there are no studies in Chile that reveal the real effects of the LULC change on the water balance at basin or sub-basin scales associated with future scenarios, which might contribute to territorial decision-making and reveal the real magnitude of the effects of these dynamics. In this study, in order to study LULC dynamics in a coastal basin in South-Central Chile, we assessed and analyzed the effects of future LULC change scenarios on the hydrological processes by generating future synthetic land cover maps from Landsat (Landsat 5 TM and Landsat 8 OLI) image datasets. The hydrological model Soil Water Assessment Tool (SWAT) was calibrated and validated, using hydroclimatic time series, to simulate discharges and other hydrological components over those future LULC scenarios. The LULC future scenarios were projected using combined Markov chain analysis (CA–Markov) and cellular automata algorithms for the near (2025), middle (2035) and far (2045) future. The results revealed that the effects on the different components of the water balance of the basin are not as significant except in the soil water transfer in percolation (increase 72.4%) and groundwater flow (increase 72.5%). This trend was especially observed in sub-basins with non-native forest plantations that dominated land cover in the year 2035, in which an increase of 43.6% in percolation and groundwater flows resulted in increased aquifer recharge and water storage, mainly offset by a decrease of 27% in the evapotranspiration. This work demonstrates the importance of evaluating the impacts of the dynamics of LULC on the hydrological response of a coastal basin, and also on how the land use governance and policy are closely linked to that of water resources.