bluuebunny/crossref_metadata_2025 huggingface dataset:
Light Down-Converter Based on Luminescent Nanofibers from the Blending of Conjugated Rod-Coil Block Copolymers and Perovskite through Electrospinning
Authors: Jiang Dai-Hua , Kobayashi Saburo , Jao Chih-Chun , Mato Yoshinobu , Isono Takuya , Fang Yu-Han , Lin Chun-Che , Satoh Toshifumi , Tung Shih-Huang , Kuo Chi-Ching
Published: January 2020

We demonstrated a novel strategy for the preparation of light down-converter by combining rod-coil block copolymers with perovskite quantum dots (QDs) through electrospinning. Reports have shown that polymer deformability can be enhanced by incorporating a soft segment and controlled by varying the rod/coil ratio. Therefore, we first synthesized the rod-coil block copolymer through the click reaction of polyfluorene (PF) and poly(n-butyl acrylate) (PBA). Next, the CsPbBr3@PF8k-b-PBA12k composite fibers were fabricated by blending perovskite through electrospinning. Optical spectral evidence demonstrated the success of the strategy, as light down-converters were prepared through the controlled variance of QD/polymer ratios to achieve tunable color and stretchability. This result reveals the potential of using rod-coil block copolymers to fabricate color-tunable perovskite light down-converters.
Evolution of the Surface Wettability of PET Polymer upon Treatment with an Atmospheric-Pressure Plasma Jet
Authors: Vesel Alenka , Zaplotnik Rok , Primc Gregor , Mozetič Miran
Published: January 2020

A useful technique for pre-treatment of polymers for improved biocompatibility is surface activation. A method for achieving optimal wettability at a minimal thermal load and unwanted modifications of the polymer properties is elaborated in this paper. Samples of polyethylene terephthalate polymer were exposed to an atmospheric-pressure plasma jet created by a high-impedance low-frequency discharge in wet argon. Different treatment times and distances from the end of the glowing discharge enabled detailed investigation of the evolution of surface activation. A rather fast saturation of the surface wettability over the area of the order of cm2 was observed upon direct treatment with the glowing discharge. At a distance of few mm from the glowing discharge, the activation was already two orders of magnitude lower. Further increase of the distance resulted in negligible surface effects. In the cases of a rapid activation, very sharp interphase between the activated and unaffected surface was observed and explained by peculiarities of high-impedance discharges sustained in argon with the presence of impurities of water vapor. Results obtained by X-ray photoelectron spectroscopy confirmed that the activation was a consequence of functionalization with oxygen functional groups.
Cross-Linking of Wheat Bran Arabinoxylan by Fungal Laccases Yields Firm Gels
Authors: Khalighi Sanaz , Berger Ralf G. , Ersoy Franziska
Published: January 2020

The native extractable arabinoxylans (AX) from wheat bran were cross-linked by the commercial laccase C (LccC) and self-produced laccases from Funalia trogii (LccFtr) and Pleurotus pulmonarius (LccPpu) (0.04 U/µg FA, each). Dynamic oscillation measurements of the 6% AX gels demonstrated a storage modulus of 9.4 kPa for LccC, 9.8 kPa for LccFtr, and 10.0 kPa for LccPpu. A loss factor ≤ 0.6 was recorded in the range from 20 to 80 Hz for all three laccases, and remained constant for four weeks of storage, when LccFtr and LccPpu were used. Arabinoxylan gel characteristics, including high water holding capacity, swelling ratio in saliva, and heat resistance indicated a covalently cross-linked network. Neither the mediator compounds caffeic acid and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid (ABTS), nor citrus pectin, enhanced the elastic properties of the gels. Using laccases as an oxidant provided gels with a solid and stable texture, comparable in firmness to traditional gelatin gels. Thus, AX gels can be presented in the vegan, halal, and kosher food markets. They may also find use in pharmaceutical and other industrial applications.
Optimal Design of Standalone Photovoltaic System Based on Multi-Objective Particle Swarm Optimization: A Case Study of Malaysia
Authors: Mohammed Ridha Hussein , Gomes Chandima , Hizam Hashim , Ahmadipour Masoud
Published: January 2020

This paper presents a multi-objective particle swarm optimization (MOPSO) method for optimal sizing of the standalone photovoltaic (SAPV) systems. Loss of load probability (LLP) analysis is considered to determine the technical evaluation of the system. Life cycle cost (LCC) and levelized cost of energy (LCE) are treated as the economic criteria. The two variants of the proposed PSO method, referred to as adaptive weights PSO ( A W P S O c f ) and sigmoid function PSO ( S F P S O c f ) , are implemented using MATLAB software to the optimize the number of PV modules in (series and parallel) and number of the storage battery. The case study of the proposed SAPV system is executed using the hourly meteorological data and typical load demand for one year in a rural area in Malaysia. The performance outcomes of the proposed A W / S F P S O c f methods give various configurations at desired levels of LLP values and the corresponding minimum cost. The performance results showed the superiority of S F P S O c f in terms of accuracy is selecting an optimal configuration at fitness function value 0.031268, LLP value 0.002431, LCC 53167 USD, and LCE 1.6413 USD. The accuracy of A W / S F P S O c f methods is verified by using the iterative method.
Enhancing the Removal of Sb (III) from Water: A Fe3O4@HCO Composite Adsorbent Caged in Sodium Alginate Microbeads
Authors: Zhang Jun , Deng Renjian , Ren Bozhi , Yaseen Mohammed , Hursthouse Andrew
Published: January 2020

To remove antimony (Sb) ions from water, a novel composite adsorbent was fabricated from ferriferous oxide and waste sludge from a chemical polishing process (Fe3O4@HCO) and encapsulated in sodium alginate (SAB). The SAB adsorbent performed well with 80%–96% removal of Sb (III) ions within a concentration range of 5–60 mg/L. The adsorption mechanism of Sb (III) was revealed to be the synergy of chemisorption (ion exchange) and physisorption (diffusion reaction). The adsorption isotherms and kinetics conformed to the Langmuir isotherm and the pesudo-second-order kinetic model. Both initial pH and temperature influenced the adsorption performance with no collapse of microbeads within solution pH range 3–7. Most importantly for practical applications, these microspheres can be separated and recovered from aqueous solution by a magnetic separation technology to facilitate large-scale treatment of antimony-containing wastewater.
Pd/Au Based Catalyst Immobilization in Polymeric Nanofibrous Membranes via Electrospinning for the Selective Oxidation of 5-Hydroxymethylfurfural
Authors: Bonincontro Danilo , Fraschetti Francesco , Squarzoni Claire , Mazzocchetti Laura , Maccaferri Emanuele , Giorgini Loris , Zucchelli Andrea , Gualandi Chiara , Focarete Maria Letizia , Albonetti Stefania
Published: January 2020

Innovative nanofibrous membranes based on Pd/Au catalysts immobilized via electrospinning onto different polymers were engineered and tested in the selective oxidation of 5-(hydroxymethyl)furfural in an aqueous phase. The type of polymer and the method used to insert the active phases in the membrane were demonstrated to have a significant effect on catalytic performance. The hydrophilicity and the glass transition temperature of the polymeric component are key factors for producing active and selective materials. Nylon-based membranes loaded with unsupported metal nanoparticles were demonstrated to be more efficient than polyacrylonitrile-based membranes, displaying good stability and leading to high yield in 2,5-furandicarboxylic acid. These results underline the promising potential of large-scale applications of electrospinning for the preparation of catalytic nanofibrous membranes to be used in processes for the conversion of renewable molecules.
Supporting Design Optimization of Tunnel Boring Machines-Excavated Coal Mine Roadways: A Case Study in Zhangji, China
Authors: Tang Bin , Cheng Hua , Tang Yongzhi , Zheng Tenglong , Yao Zhishu , Wang Chuanbing , Rong Chuanxin
Published: January 2020

Tunnel Boring Machines (TBMs) are a cutting-edge excavating equipment, but are barely applied in underground coal mines. For TBM excavation projects involving the Zhangji coal mine, the surrounding rock properties, stress field, cross section geometry, as well as the excavation-induced stress path of TBM-excavated coal mine roadways are different from those of traditional tunnels or roadways. Consequently, traditional roadway supporting technologies and experiences cannot be relied on for this project. In order to research an appropriate supporting pattern for a TBM-excavated coal mine roadway, first of all, the constitutive model of roadway surrounding rocks was derived, and a rock failure criterion was proposed based on rock mechanical tests. Secondly, a three-dimension finite element model was established and computer simulations under three different supporting patterns were conducted. Stress redistribution, roadway convergence, and excavation damage zone ranges of surrounding rocks under three different support patterns were analyzed and an optimal support design of the TBM-excavated roadway was made based on simulation results. During roadway excavation, convergence gauge and rock bolt dynamometers were installed for monitoring roadway convergence and the axial forces of rock bolts. The in-situ monitoring results verified the validity of roadway supporting designs.
A Reference-Model-Based Artificial Neural Network Approach for a Temperature Control System
Authors: Xu Song , Hashimoto Seiji , Jiang YuQi , Izaki Katsutoshi , Kihara Takeshi , Ikeda Ryota , Jiang Wei
Published: January 2020

Artificial neural networks (ANNs), which have excellent self-learning performance, have been applied to various applications, such as target detection and industrial control. In this paper, a reference-model-based ANN controller with integral-proportional-derivative (I-PD) compensation has been proposed for temperature control systems. To improve the ANN self-learning efficiency, a reference model is introduced for providing the teaching signal for the ANN. System simulations were carried out in the MATLAB/SIMULINK environment and experiments were carried out on a digital-signal-processor (DSP)-based experimental platform. The simulation and experimental results were compared with those for a conventional I-PD control system. The effectiveness of the proposed method was verified.
Investigating the Characteristics of Two-Phase Flow Using Electrical Capacitance Tomography (ECT) for Three Pipe Orientations
Authors: Almutairi Zeyad , Al-Alweet Fayez M. , Alghamdi Yusif A. , Almisned Omar A. , Alothman Othman Y.
Published: January 2020

Experiments of gas–liquid flow in a circular pipe for horizontal and inclined positions (upward/downward) are reported. The characteristics of two-phase flow in terms of liquid holdup (ε(L)) and induced flow patterns are studied using three experimental techniques; time-averaged ε(L) from permittivity profiles using electrical capacitance tomography (ECT), instantaneous ε(L) using two fast-closing valves (TFCV), and high-speed camera images (HSCI) to capture/identify the formed flow patterns. Thus, this experimental setup enables the development of more well-defined flow patterns in gas–liquid two-phase flow and allows for multi-technique verification of the results. Taken from experimental measurements, a model is proposed to predict ε(L) for high and low situations. The correlations are a function of the hydrodynamic dimensionless quantities which provide hydrodynamic similarity. Regarding different pipe orientations, ε(L) predictions are comparable to ε(L) from experimental measurements with accepted accuracy: 88% of the predictions are within ±5–15% and 98% are below ±20%. The correlations also were validated by reported results and against correlations available in the literature and show higher prediction accuracy. It is confirmed that the kinematic similarity which is achieved by the gas–liquid velocity ratios and the inertial forces influence the flow pattern and the liquid holdup.
Process of Natural Gas Explosion in Linked Vessels with Three Structures Obtained Using Numerical Simulation
Authors: Wang Qiuhong , Sun Yilin , Li Xin , Shu Chi-Min , Wang Zhirong , Jiang Juncheng , Zhang Mingguang , Cheng Fangming
Published: January 2020

Combinations of spherical vessels and pipes are frequently employed in industries. Scholars have primarily studied gas explosions in closed vessels and pipes. However, knowledge of combined spherical vessel and pipe systems is limited. Therefore, a flame acceleration simulator was implemented with computational fluid dynamics software and was employed to conduct natural gas explosions in three structures, including a single spherical vessel, a single spherical vessel with a pipe connected to it, and a big spherical vessel connected to a small spherical vessel with a pipe. These simulations reflected physical experiments conducted by at Nanjing Tech University. By changing the sizes of vessels, lengths of pipes, and ignition positions in linked vessels, we obtained relevant laws for the time, pressure, temperature, and concentrations of combustion products. Moreover, the processes of natural gas explosions in different structures were obtained from simulation results. Simulation results agreed strongly with corresponding experimental data, validating the reliability of simulation.
Synergistic Effect on the Non-Oxygenated Fraction of Bio-Oil in Thermal Co-Pyrolysis of Biomass and Polypropylene at Low Heating Rate
Authors: Supramono Dijan , Sitorus Adithya Fernando , Nasikin Mohammad
Published: January 2020

Biomass pyrolysis and polypropylene (PP) pyrolysis in a stirred tank reactor exhibited different heat transfer phenomena whereby heat transfer in biomass pyrolysis was driven predominantly by heat radiation and PP pyrolysis by heat convection. Therefore, co-pyrolysis could exhibit be expected to display various heat transfer phenomena depending on the feed composition. The objective of the present work was to determine how heat transfer, which was affected by feed composition, affected the yield and composition of the non-polar fraction. Analysis of heat transfer phenomena was based on the existence of two regimes in the previous research in which in regime 1 (the range of PP composition in the feeds is 0–40%), mass ejection from biomass particles occurred without biomass particle swelling, while in regime 2 (the range of PP composition in the feeds is 40–100%), mass ejection was preceded by biomass particle swelling. The co-pyrolysis was carried out in a stirred tank reactor with heating rate of 5 °C/min until 500 °C and using N2 gas as carrier gas. Temperature measurement was applied to pyrolysis fluid at the lower part of the reactor and small biomass spheres of 6 mm diameter to simulate heat transfer to biomass particles. The results indicate that in regime 1 convective and radiative heat transfers sparingly occurred and synergistic effect on the yield of non-oxygenated phase increased with increasing convective heat transfer at increasing %PP in feed. On the other hand, in regime 2, convective heat transfer was predominant with decreasing synergistic effect at increasing %PP in feed. The optimum PP composition in feed to reach maximum synergistic effect was 50%. Non-oxygenated phase portion in the reactor leading to the wax formation acted as donor of methyl and hydrogen radicals in the removal of oxygen to improve synergistic effect. Non-oxygenated fraction of bio-oil contained mostly methyl comprising about 53% by mole fraction, while commercial diesel contained mostly methylene comprising about 59% by mole fraction
Estimation of Actuator and System Faults Via an Unknown Input Interval Observer for Takagi–Sugeno Systems
Authors: Martínez-García Citlaly , Puig Vicenç , Astorga-Zaragoza Carlos-M. , Madrigal-Espinosa Guadalupe , Reyes-Reyes Juan
Published: January 2020

This paper presents a simultaneous state variables and system and actuator fault estimation, based on an unknown input interval observer design for a discrete-time parametric uncertain Takagi–Sugeno system under actuator fault, with disturbances in the process and measurement noise. The observer design is synthesized by considering unknown but bounded process disturbances, output noise, as well as bounded parametric uncertainties. By taking into account these considerations, the upper and lower bounds of the considered faults are estimated. The gain of the unknown input interval observer is computed through a linear matrix inequalities (LMIs) approach using the robust H ∞ criteria in order to ensure attenuation of process disturbances and output noise. The interval observer scheme is experimentally evaluated by estimating the upper and lower bounds of a torque load perturbation, a friction parameter and a fault in the input voltage of a permanent magnet DC motor.
Numerical and Experimental Study on the Internal Flow of the Venturi Injector
Authors: Li Hao , Li Hong , Huang Xiuqiao , Han Qibiao , Yuan Ye , Qi Bin
Published: January 2020

To study the appropriate numerical simulation methods for venturi injectors, including the investigation of the hydraulic performance, mixing process, and the flowing law of the two internal fluids, simulations and experiments were conducted in this study. In the simulations part, the cavitation model based on the standard k–ε turbulence and mixture models was added, after convergence of the calculations. The results revealed that the cavitation model has good agreement with the experiment. However, huge deviations occurred between the experimental results and the ones from the calculation when not considering the cavitation model after cavitation. Thus, it is inferred that the cavitation model can exactly predict the hydraulic performance of a venturi injector. In addition, the cavitation is a crucial factor affecting the hydraulic performance of a venturi injector. The cavitation can ensure the stability of the fertilizer absorption of the venturi injector and can realize the precise control of fertilization by the venturi injector, although it affects the flow stability and causes energy loss. Moreover, this study found that the mixing chamber and throat are the main areas of energy loss. Furthermore, we observed that the internal flow of the venturi injector results in the majority of mixing taking place at the diffusion and outlet sections.
A Modular Framework for the Modelling and Optimization of Advanced Chromatographic Processes
Authors: Schmölder Johannes , Kaspereit Malte
Published: January 2020

A framework is introduced for the systematic development of preparative chromatographic processes. It is intended for the optimal design of conventional and advanced concepts that exploit strategies, such as recycling, side streams, bypasses, using single or multiple columns, and combinations thereof. The Python-based platform simplifies the implementation of new processes and design problems by decoupling design tasks into individual modules for modelling, simulation, assertion of cyclic stationarity, product fractionation, and optimization. Interfaces to external libraries provide flexibility regarding the choice of column model, solver, and optimizer. The current implementation, named CADET-Process, uses the software CADET for solving the model equations. The structure of the framework is discussed and its application for optimal design of existing and identification of new chromatographic operating concepts is demonstrated by case studies.
Modern Analogue Approach Applied to High-Resolution Varved Sediments—A Synthesis for Lake Montcortès (Central Pyrenees)
Authors: Vegas-Vilarrúbia Teresa , Rull Valentí , Trapote Maria del Carmen , Cao Min , Rosell-Melé Antoni , Buchaca Teresa , Gomà Joan , López Pilar , Sigró Javier , Safont Elisabet , Cañellas Núria , Garcés-Pastor Sandra , Giralt Santiago , Corella Juan Pablo , Pérez-Zanón Núria
Published: January 2020

In Quaternary paleosciences, the rationale behind analogical inference presupposes that former processes can be explained by causes operating now, although their intensity and rates can vary through time. In this paper we synthesised the results of different modern analogue studies performed in a varved lake. We discuss their potential value to obtain best results from high resolution past records. Different biogeochemical contemporary processes revealed seasonality and year-to-year variability, e.g., calcite precipitation, lake oxygenation, production and deposition of pollen and phytoplankton growth. Fingerprints of the first two of these processes were clearly evidenced in the varve-sublayers and allow understanding related to past events. Pollen studies suggested the possibility of identifying and characterizing seasonal layers even in the absence of varves. Marker pigments in the water column were tightly associated with phytoplankton groups living today; most of them were identified in the sediment record as well. We observed that 50% of these marker pigments were destroyed between deposition and permanent burying. In another study, seasonality in the production/distribution of branched glycerol dialkyl glycerol tetraethers (brGDGTs) and derived temperature estimates were investigated in catchment soils and particles settling in the lake. The signatures of brGDGTs in depositional environments mainly were representative of stable conditions of soils in the catchment that last over decades; no brGDGTs seemed to be produced within the lake. The main contribution of this review is to show the advantages and limitations of a multiproxy modern-analogue approach in Lake Montcortès as a case study and proposing new working hypotheses for future research.
On Socio-Economic Predictors of Religious Intolerance: Evidence from a Large-Scale Longitudinal Survey in the Largest Muslim Democracy
Authors: Yusuf Arief Anshory , Shidiq Akhmad Rizal , Hariyadi Hariyadi
Published: January 2020

Motivated by increasing religious intolerance, we study the socio-economic covariates of individual-level religious intolerance in Indonesia, the largest Muslim democracy in the world. We use panel data from 2007 and 2014 of more than 20,000 adult individuals (representing 83% of the population) and apply fixed-effect regression analysis to identify relevant socio-economic characteristics that are highly associated with religious intolerance at the individual level. We utilize survey questions on willingness to accept someone with different faith living in the same village, living in the same neighborhood, renting a house, marrying relatives or children, and building a place of worship in the neighborhood as our measures of religious intolerance. We find that higher individual income and educational attainment are positively correlated with the tolerance level. At the same time, a higher level of self-declared religiosity is negatively correlated with a tolerant attitude. For location-specific characteristics, higher income inequality and extent of poverty in the location where an individual resides are associated with a higher level of religious intolerance. These patterns are generally robust across different measures of religious intolerance, although there is heterogeneity in the magnitudes of the correlations, where these covariates have the smallest correlations with the willingness to accept interfaith marriage in the family.
Ultrasonic Arrays for Remote Sensing of Pasture Biomass
Authors: Legg Mathew , Bradley Stuart
Published: January 2020

The profitability of agricultural industries that utilise pasture can be strongly affected by the ability to accurately measure pasture biomass. Pasture height measurement is one technique that has been used to estimate pasture biomass. However, pasture height measurement errors can occur if the sensor is mounted to a farm vehicle that experiences tilting or bouncing. This work describes the development of novel low ultrasonic frequency arrays for pasture biomass estimation. Rather than just measuring the distance to the top of the pasture, as previous ultrasonic studies have done, this hardware is designed to also allow ultrasonic measurements to be made vertically through the pasture to the ground. The hardware was mounted to a farm bike driving over pasture at speeds of up to 20 km/h. The analysed results show the ability of the hardware to measure the ground location through the grass. This allowed pasture height measurement to be independent of tilting and bouncing of the farm vehicle, leading to 20 to 25% improvement in the R 2 value obtained for biomass estimation compared with the traditional technique. This corresponded to a reduction in root mean squared error of predicted biomass from about 350 to 270 kg/ha, where the average biomass of the pasture was 1915 kg/ha.
Hyperspectral Classification of Plants: A Review of Waveband Selection Generalisability
Authors: Hennessy Andrew , Clarke Kenneth , Lewis Megan
Published: January 2020

Hyperspectral sensing, measuring reflectance over visible to shortwave infrared wavelengths, has enabled the classification and mapping of vegetation at a range of taxonomic scales, often down to the species level. Classification with hyperspectral measurements, acquired by narrow band spectroradiometers or imaging sensors, has generally required some form of spectral feature selection to reduce the dimensionality of the data to a level suitable for the construction of a classification model. Despite the large number of hyperspectral plant classification studies, an in-depth review of feature selection methods and resultant waveband selections has not yet been performed. Here, we present a review of the last 22 years of hyperspectral vegetation classification literature that evaluates the overall waveband selection frequency, waveband selection frequency variation by taxonomic, structural, or functional group, and the influence of feature selection choice by comparing such methods as stepwise discriminant analysis (SDA), support vector machines (SVM), and random forests (RF). This review determined that all characteristics of hyperspectral plant studies influence the wavebands selected for classification. This includes the taxonomic, structural, and functional groups of the target samples, the methods, and scale at which hyperspectral measurements are recorded, as well as the feature selection method used. Furthermore, these influences do not appear to be consistent. Moreover, the considerable variability in waveband selection caused by the feature selectors effectively masks the analysis of any variability between studies related to plant groupings. Additionally, questions are raised about the suitability of SDA as a feature selection method, with it producing waveband selections at odds with the other feature selectors. Caution is recommended when choosing a feature selector for hyperspectral plant classification: We recommend multiple methods being performed. The resultant sets of selected spectral features can either be evaluated individually by multiple classification models or combined as an ensemble for evaluation by a single classifier. Additionally, we suggest caution when relying upon waveband recommendations from the literature to guide waveband selections or classifications for new plant discrimination applications, as such recommendations appear to be weakly generalizable between studies.
The Socio-Economic and Environmental Variables Associated with Hotspots of Infrastructure Expansion in South America
Authors: Andrade-Núñez María José , Aide T. Mitchell
Published: January 2020

The built environment, defined as all human-made infrastructure, is increasing to fulfill the demand for human settlements, productive systems, mining, and industries. Due to the profound direct and indirect impacts that the built environment produces on natural ecosystems, it is considered a major driver of land change and biodiversity loss, and a major component of global environmental change. In South America, a global producer of minerals and agricultural commodities, and a region with many biodiversity hotspots, infrastructure expanded considerably between 2001 and 2011. This expansion occurred mainly in rural areas, towns, and sprawling suburban areas that were not previously developed. Herein, we characterized the areas of major infrastructure expansion between 2001 and 2011 in South America. We used nighttime light data, land use maps, and socio-economic and environmental variables to answer the following questions: (1) Where are the hotspots of infrastructure expansion located? and (2) What combination of socio-economic and environmental variables are associated with infrastructure expansion? Hotspots of infrastructure expansion encompass 70% (337,310 km2) of the total infrastructure expansion occurring between 2001 and 2011 across South America. Urban population and economic growth, mean elevation, and mean road density were the main variables associated with the hotspots, grouping them into eight clusters. Furthermore, within the hotspots, woody vegetation increased around various urban centers, and several areas showed a large increase in agriculture. Investments in large scale infrastructure projects, and the expansion and intensification of productive systems (e.g., agriculture and meat production) play a dominant role in the increase of infrastructure across South America. We expect that under the current trends of globalization and land changes, infrastructure will continue increasing and expanding into no-development areas and remote places. Therefore, to fully understand the direct and indirect impacts of land use change in natural ecosystems studies of infrastructure need to expand to areas beyond cities. This will provide better land management alternatives for the conservation of biodiversity as well as peri-urban areas across South America.
Change Detection of Soil Formation Rate in Space and Time Based on Multi Source Data and Geospatial Analysis Techniques
Authors: Li Qin , Wang Shijie , Bai Xiaoyong , Luo Guangjie , Song Xiaoqing , Tian Yichao , Hu Zeyin , Yang Yujie , Tian Shiqi
Published: January 2020

Spatialization of soil formation rate (SFR) is always a difficult problem in soil genesis. In this study, the dissolution rate in karst areas of China during the period 1983–2015 was estimated on the basis of geospatial analysis techniques and detection of variation via the law of chemical thermodynamics in conjunction with long-term serial ecohydrology data. SFR at different lithological backgrounds was calculated on the basis of the content of acid-insoluble substances. Results showed that the spatial dissolution rate of carbonate rock ranges between 0 and 106 mm/ka, averaged at 22.51 mm/ka, and the SFR ranges between 10 and 134.93 t km−2 yr−1, averaged at 18.59 t km−2 yr−1. The dissolution rate and SFR exhibit a slight increasing trend with 0.04 mm/ka and 0.003 t km−2 yr−1, respectively. The risk for soil erosion was reevaluated on the basis of the SFR results, and the area with erosion risk and the ecologically safe area were corrected. Results indicated that the area with erosion risk is four times higher than the ecologically safe area. This study will hopefully instigate and facilitate the application and popularization of geospatial analysis technology to the research field of rock weathering and soil formation.
Along-Track Multistatic Synthetic Aperture Radar Formations of Minisatellites
Authors: Guccione Pietro , Monti Guarnieri Andrea , Rocca Fabio , Giudici Davide , Gebert Nico
Published: January 2020

The paper analyses an along-track multistatic Synthetic Aperture Radar (SAR) formation. The formation aims at achieving a high azimuth resolution maintaining at the same time a large swath width. The case with one transmitting sensor and all receiving is analyzed (Single Input Multiple Output, SIMO). An effective and novel reconstruction, in the two-dimensional frequency domain is introduced that is able to keep low the azimuth ambiguity and achieve a recombination gain close to the theoretical one. Degradation of the system performance due to the loss of the control of formation position is analyzed using probabilistic considerations. Moreover, some innovative methods to mitigate the loss of optimality are introduced and evaluated using simulations. Finally, considerations on the impact of the across-track non zero baseline are discussed.
Predicting Forage Quality of Grasslands Using UAV-Borne Imaging Spectroscopy
Authors: Wijesingha Jayan , Astor Thomas , Schulze-Brüninghoff Damian , Wengert Matthias , Wachendorf Michael
Published: January 2020

The timely knowledge of forage quality of grasslands is vital for matching the demands in animal feeding. Remote sensing (RS) is a promising tool for estimating field-scale forage quality compared with traditional methods, which usually do not provide equally detailed information. However, the applicability of RS prediction models depends on the variability of the underlying calibration data, which can be brought about by the inclusion of a multitude of grassland types and management practices in the model development. Major aims of this study were (i) to build forage quality estimation models for multiple grassland types based on an unmanned aerial vehicle (UAV)-borne imaging spectroscopy and (ii) to generate forage quality distribution maps using the best models obtained. The study examined data from eight grasslands in northern Hesse, Germany, which largely differed in terms of vegetation type and cutting regime. The UAV with a hyperspectral camera on board was utilised to acquire spectral images from the grasslands, and crude protein (CP) and acid detergent fibre (ADF) concentration of the forage was assessed at each cut. Five predictive modelling regression algorithms were applied to develop quality estimation models. Further, grassland forage quality distribution maps were created using the best models developed. The normalised spectral reflectance data showed the strongest relationship with both CP and ADF concentration. From all predictive algorithms, support vector regression provided the highest precision and accuracy for CP estimation (median normalised root mean square error prediction (nRMSEp) = 10.6%), while cubist regression model proved best for ADF estimation (median nRMSEp = 13.4%). The maps generated for both CP and ADF showed a distinct spatial variation in forage quality values for the different grasslands and cutting regimes. Overall, the results disclose that UAV-borne imaging spectroscopy, in combination with predictive modelling, provides a promising tool for accurate forage quality estimation of multiple grasslands.
Towards Benthic Habitat 3D Mapping Using Machine Learning Algorithms and Structures from Motion Photogrammetry
Authors: Mohamed Hassan , Nadaoka Kazuo , Nakamura Takashi
Published: January 2020

The accurate classification and 3D mapping of benthic habitats in coastal ecosystems are vital for developing management strategies for these valuable shallow water environments. However, both automatic and semiautomatic approaches for deriving ecologically significant information from a towed video camera system are quite limited. In the current study, we demonstrate a semiautomated framework for high-resolution benthic habitat classification and 3D mapping using Structure from Motion and Multi View Stereo (SfM-MVS) algorithms and automated machine learning classifiers. The semiautomatic classification of benthic habitats was performed using several attributes extracted automatically from labeled examples by a human annotator using raw towed video camera image data. The Bagging of Features (BOF), Hue Saturation Value (HSV), and Gray Level Co-occurrence Matrix (GLCM) methods were used to extract these attributes from 3000 images. Three machine learning classifiers (k-nearest neighbor (k-NN), support vector machine (SVM), and bagging (BAG)) were trained by using these attributes, and their outputs were assembled by the fuzzy majority voting (FMV) algorithm. The correctly classified benthic habitat images were then geo-referenced using a differential global positioning system (DGPS). Finally, SfM-MVS techniques used the resulting classified geo-referenced images to produce high spatial resolution digital terrain models and orthophoto mosaics for each category. The framework was tested for the identification and 3D mapping of seven habitats in a portion of the Shiraho area in Japan. These seven habitats were corals (Acropora and Porites), blue corals (H. coerulea), brown algae, blue algae, soft sand, hard sediments (pebble, cobble, and boulders), and seagrass. Using the FMV algorithm, we achieved an overall accuracy of 93.5% in the semiautomatic classification of the seven habitats.
SAR Target Classification Based on Deep Forest Model
Authors: Zhang Jiahuan , Song Hongjun , Zhou Binbin
Published: January 2020

Synthetic aperture radar (SAR) has become one of the most important means of information acquisition in today’s society and shows great potential in many fields. Target identification and classification of SAR images are also the focus of research. With the vigorous development of deep learning, many researchers apply this method to SAR target classification to obtain a more automatic process and more accurate results. In this paper, a novel deep forest model constructed by multi-grained cascade forest (gcForest), which is different from the traditional neural network (NN) model, is employed to classify ten types of SAR targets in the moving and stationary target acquisition and recognition (MSTAR) dataset. Considering that the targets of input images may be off-center and of different sizes in practical applications, two improved models based on varying weights by image features have been put forward, and both obtain better results. A series of experiments have been conducted to optimize model parameters, and final results with the MSTAR dataset illustrate that the two improved models are both superior to the original gcForest model. This is the first attempt to classify SAR targets using the non-NN model.
The Performance of Different Mapping Functions and Gradient Models in the Determination of Slant Tropospheric Delay
Authors: Qiu Cong , Wang Xiaoming , Li Zishen , Zhang Shaotian , Li Haobo , Zhang Jinglei , Yuan Hong
Published: January 2020

Global navigation satellite systems (GNSSs) have become an important tool for remotely sensing water vapor in the atmosphere. In GNSS data processing, mapping functions and gradient models are needed to map the zenith tropospheric delay (ZTD) to the slant total tropospheric delay (STD) along a signal path. Therefore, it is essential to investigate the spatial–temporal performance of various mapping functions and gradient models in the determination of STD. In this study, the STDs at nine elevations were first calculated by applying the ray-tracing method to the atmospheric European Reanalysis-Interim (ERA—Interim) dataset. These STDs were then used as the reference to study the accuracy of the STDs that determined the ZTD together with mapping functions and gradient models. The performance of three mapping functions (i.e., Niell mapping function (NMF), global mapping function (GMF), and Vienna mapping function (VMF1)) and three gradient models (i.e., Chen, MacMillan, and Meindl) in six regions (the temperate zone, Qinghai–Tibet Plateau, Equator, Sahara Desert, Amazon Rainforest, and North Pole) in determining slant tropospheric delay was investigated in this study. The results indicate that the three mapping functions have relatively similar performance above a 15° elevation, but below a 15° elevation, VMF1 clearly performed better than the GMF and NMF. The results also show that, if no gradient model is included, the root-mean-square (RMS) of the STD is smaller than 2 mm above the 30° elevation and smaller than 9 mm above the 15° elevation but shows a significant increase below the 15° elevation. For example, in the temperate zone, the RMS increases from approximately 35 mm at the 10° elevation to approximately 160 mm at the 3° elevation. The inclusion of gradient models can significantly improve the accuracy of STDs by 50%. All three gradient models performed similarly at all elevations and in all regions. The bending effect was also investigated, and the results indicate that the tropospheric delay caused by the bending effect is normally below 13 mm above a 15° elevation, but this delay increases dramatically from approximately 40 mm at a 10° elevation to approximately 200 mm at a 5° elevation, and even reaches 500–700 mm at a 3° elevation in most studied regions.
Assessing the Changes in the Moisture/Dryness of Water Cavity Surfaces in Imlili Sebkha in Southwestern Morocco by Using Machine Learning Classification in Google Earth Engine
Authors: Hakdaoui Sofia , Emran Anas , Pradhan Biswajeet , Qninba Abdeljebbar , Balla Taoufik El , Mfondoum Alfred Homère Ngandam , Lee Chang-Wook , Alamri Abdullah M.
Published: January 2020

Imlili Sebkha is a stable and flat depression in southern Morocco that is more than 10 km long and almost 3 km wide. This region is mainly sandy, but its northern part holds permanent water pockets that contain fauna and flora despite their hypersaline water. Google Earth Engine (GEE) has revolutionized land monitoring analysis by allowing the use of satellite imagery and other datasets via cloud computing technology and server-side JavaScript programming. This work highlights the potential application of GEE in processing large amounts of satellite Earth Observation (EO) Big Data for the free, long-term, and wide spatio-temporal wet/dry permanent salt water cavities and moisture monitoring of Imlili Sebkha. Optical and radar images were used to understand the functions of Imlili Sebkha in discovering underground hydrological networks. The main objective of this work was to investigate and evaluate the complementarity of optical Landsat, Sentinel-2 data, and Sentinel-1 radar data in such a desert environment. Results show that radar images are not only well suited in studying desertic areas but also in mapping the water cavities in desert wetland zones. The sensitivity of these images to the variations in the slope of the topographic surface facilitated the geological and geomorphological analyses of desert zones and helped reveal the hydrological functions of Imlili Sebkha in discovering buried underground networks.
New Evidence of Mediterranean Climate Change and Variability from Sea Surface Temperature Observations
Authors: Pisano Andrea , Marullo Salvatore , Artale Vincenzo , Falcini Federico , Yang Chunxue , Leonelli Francesca Elisa , Santoleri Rosalia , Buongiorno Nardelli Bruno
Published: January 2020

Estimating long-term modifications of the sea surface temperature (SST) is crucial for evaluating the current state of the oceans and to correctly assess the impact of climate change at regional scales. In this work, we analyze SST variations within the Mediterranean Sea and the adjacent Northeastern Atlantic box (west of the Strait of Gibraltar) over the last 37 years, by using a satellite-based dataset from the Copernicus Marine Environment Monitoring Service (CMEMS). We found a mean warming trend of 0.041 ± 0.006 ∘ C/year over the whole Mediterranean Sea from 1982 to 2018. The trend has an uneven spatial pattern, with values increasing from 0.036 ± 0.006 ∘ C/year in the western basin to 0.048 ± 0.006 ∘ C/year in the Levantine–Aegean basin. The Northeastern Atlantic box and the Mediterranean show a similar trend until the late 1990s. Afterwards, the Mediterranean SST continues to increase, whereas the Northeastern Atlantic box shows no significant trend, until ~2015. The observed change in the Mediterranean Sea affects not only the mean trend but also the amplitude of the Mediterranean seasonal signal, with consistent relative increase and decrease of summer and winter mean values, respectively, over the period considered. The analysis of SST changes occurred during the “satellite era” is further complemented by reconstructions also based on direct in situ SST measurements, i.e., the Extended Reconstructed SST (ERSST) and the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST), which go back to the 19th century. The analysis of these longer time series, covering the last 165 years, indicates that the increasing Mediterranean trend, observed during the CMEMS operational period, is consistent with the Atlantic Multidecadal Oscillation (AMO), as it closely follows the last increasing period of AMO. This coincidence occurs at least until 2007, when the apparent onset of the decreasing phase of AMO is not seen in the Mediterranean SST evolution.
Antarctic Supraglacial Lake Detection Using Landsat 8 and Sentinel-2 Imagery: Towards Continental Generation of Lake Volumes
Authors: Moussavi Mahsa , Pope Allen , Halberstadt Anna , Trusel Luke , Cioffi Leanne , Abdalati Waleed
Published: January 2020

Melt and supraglacial lakes are precursors to ice shelf collapse and subsequent accelerated ice sheet mass loss. We used data from the Landsat 8 and Sentinel-2 satellites to develop a threshold-based method for detection of lakes found on the Antarctic ice shelves, calculate their depths and thus their volumes. To achieve this, we focus on four key areas: the Amery, Roi Baudouin, Nivlisen, and Riiser-Larsen ice shelves, which are all characterized by extensive surface meltwater features. To validate our products, we compare our results against those obtained by an independent method based on a supervised classification scheme (e.g., Random Forest algorithm). Additional verification is provided by manual inspection of results for nearly 1000 Landsat 8 and Sentinel-2 images. Our dual-sensor approach will enable constructing high-resolution time series of lake volumes. Therefore, to ensure interoperability between the two datasets, we evaluate depths from contemporaneous Landsat 8 and Sentinel-2 image pairs. Our assessments point to a high degree of correspondence, producing an average R2 value of 0.85, no bias, and an average RMSE of 0.2 m. We demonstrate our method’s ability to characterize lake evolution by presenting first evidence of drainage events outside of the Antarctic Peninsula on the Amery Ice shelf. The methods presented here pave the way to upscaling throughout the Landsat 8 and Sentinel-2 observational record across Antarctica to produce a first-ever continental dataset of supraglacial lake volumes. Such a dataset will improve our understanding of the influence of surface hydrology on ice shelf stability, and thus, future projections of Antarctica’s contribution to sea level rise.