bluuebunny/crossref_metadata_2025 huggingface dataset:
PLA/PA Bio-Blends: Induced Morphology by Extrusion
Authors: García-Masabet Violeta , Santana Pérez Orlando , Cailloux Jonathan , Abt Tobias , Sánchez-Soto Miguel , Carrasco Félix , Maspoch María Lluïsa
Published: December 2019

The effect of processing conditions on the final morphology of Poly(Lactic Acid) (PLA) with bio-based Polyamide 10.10 (PA) 70/30 blends is analyzed in this paper. Two types of PLA were used: Commercial (neat PLA) and a rheologically modified PLA (PLAREx), with higher melt elasticity produced by reactive extrusion. To evaluate the ability of in situ micro-fibrillation (μf) of PA phase during blend compounding by twin-screw extrusion, two processing parameters were varied: (i) Screw speed rotation (rpm); and (ii) take-up velocity, to induce a hot stretching with different Draw Ratios (DR). The potential ability of PA-μf in both bio-blends was evaluated by the viscosity (p) and elasticity (k’) ratios determined from the rheological tests of pristine polymers. When PLAREx was used, the requirements for PA-μf was fulfilled in the shear rate range observed at the extrusion die. Scanning electron microscopy (SEM) observations revealed that, unlike neat PLA, PLAREx promoted PA-μf without hot stretching and the aspect ratio increased as DR increased. For neat PLA-based blends, PA-μf was promoted during the hot stretching stage. DMTA analysis revealed that the use of PLAREx PLAREx resulted in a better mechanical performance in the rubbery region (T > Tg PLA-phase) due to the PA-μf morphology obtained.
Edible Films and Coatings Functionalization by Probiotic Incorporation: A Review
Authors: Pop Oana L. , Pop Carmen R. , Dufrechou Marie , Vodnar Dan C. , Socaci Sonia A. , Dulf Francisc V. , Minervini Fabio , Suharoschi Ramona
Published: December 2019

Edible coatings and films represent an alternative packaging system characterized by being more environment- and customer-friendly than conventional systems of food protection. Research on edible coatings requires multidisciplinary efforts by food engineers, biopolymer specialists and biotechnologists. Entrapment of probiotic cells in edible films or coatings is a favorable approach that may overcome the limitations linked with the use of bioactive compounds in or on food products. The recognition of several health advantages associated with probiotics ingestion is worldwide accepted and well documented. Nevertheless, due to the low stability of probiotics in the food processing steps, in the food matrices and in the gastrointestinal tract, this kind of encapsulation is of high relevance. The development of new and functional edible packaging may lead to new functional foods. This review will focus on edible coatings and films containing probiotic cells (obtaining techniques, materials, characteristics, and applications) and the innovative entrapment techniques use to obtained such packaging.
Development and Optimisation of Novel Polymeric Compositions for Sustained Release Theophylline Caplets (PrintCap) via FDM 3D Printing
Authors: Tan Deck Khong , Maniruzzaman Mohammed , Nokhodchi Ali
Published: December 2019

This study reports a thorough investigation combining hot-melt extrusion technology (HME) and a low-cost fused deposition modelling (FDM) 3D printer as a continuous fabrication process for a sustained release drug delivery system. The successful implementation of such an approach presented herein allows local hospitals to manufacture their own medical and pharmaceutical products on-site according to their patients’ needs. This will help save time from waiting for suitable products to be manufactured off-site or using traditional manufacturing processes. The filaments were produced by optimising various compositions of pharmaceutical-grade polymers, such as hydroxypropyl cellulose (HPC), Eudragit® (RL PO), and polyethylene glycol (PEG), whereas theophylline was used as a model thermally stable drug. For the purpose of the study, twin-screw hot-melt extrusion (HME) was implemented from the view that it would result in the formation of solid dispersion of drug in the polymeric carrier matrices by means of high shear mixing inside the heated barrel. Four filament compositions consisting of different ratios of polymers were produced and their properties were assessed. The mechanical characterisation of the filaments revealed quite robust properties of the filaments suitable for FDM 3D printing of caplets (PrintCap), whereas the solid-state analyses conducted via DSC and XRD showed amorphous nature of the crystalline drug dispersed in the polymeric matrices. Moreover, the surface analysis conducted via SEM showed a smooth surface of the produced filaments as well as caplets where no drug crystals were visible. The in vitro drug release study showed a sustained release profile over 10 h where about 80% of the drug was released from the printed dosage forms. This indicates that our optimised 3D printed caplets could be suitable for the development of sustained release on-demand drug delivery systems.
Vegetable Additives in Food Packaging Polymeric Materials
Authors: Munteanu Silvestru Bogdănel , Vasile Cornelia
Published: December 2019

Plants are the most abundant bioresources, providing valuable materials that can be used as additives in polymeric materials, such as lignocellulosic fibers, nano-cellulose, or lignin, as well as plant extracts containing bioactive phenolic and flavonoid compounds used in the healthcare, pharmaceutical, cosmetic, and nutraceutical industries. The incorporation of additives into polymeric materials improves their properties to make them suitable for multiple applications. Efforts are made to incorporate into the raw polymers various natural biobased and biodegradable additives with a low environmental fingerprint, such as by-products, biomass, plant extracts, etc. In this review we will illustrate in the first part recent examples of lignocellulosic materials, lignin, and nano-cellulose as reinforcements or fillers in various polymer matrices and in the second part various applications of plant extracts as active ingredients in food packaging materials based on polysaccharide matrices (chitosan/starch/alginate).
Production of Butyric Anhydride Using Single Reactive Distillation Column with Internal Material Circulation
Authors: Chen Guanghui , Jin Fushuang , Guo Xiaokai , Xiang Shuguang , Tao Shaohui
Published: December 2019

The traditional two-column reactive distillation (RD) process is used for the production of butyric anhydride, which is synthesized with butyric acid and acetic anhydride via a reversible reaction. In this work, a novel process with a single RD column (SRDC) is designed for the production of butyric anhydride, where the second distillation column for separating excess reactant is removed based on the boiling point profile of the reaction system. Two applications of the proposed SRDC process, namely SRDC with excess butyric acid or acetic anhydride circulating internally, are economically optimized, and the results show that both SRDC processes have a lower total annual cost (TAC) than the traditional two-column process. Furthermore, from the perspective of TAC, the application with an excess feed of butyric acid is better than the application with excess acetic anhydride. The developed technique may also be applied to retrofit other traditional two-column RD processes, where the overhead and bottom products are the lightest and heaviest components of the reaction system, respectively, and no azeotrope is involved in the RD column.
Validation of the Burden Distribution of the 1/3-Scale of a Blast Furnace Simulated by the Discrete Element Method
Authors: Mio Hiroshi , Narita Yoichi , Nakano Kaoru , Nomura Seiji
Published: December 2019

The objective of this paper was to develop a prediction tool for the burden distribution in a charging process of a bell-less-type blast furnace using the discrete element method (DEM). The particle behavior on the rotating chute and on the burden surface was modeled, and the burden distribution was analyzed. Furthermore, the measurements of the burden distribution in a 1/3-scale experimental blast furnace were performed to validate the simulated results. Particle size segregation occurred during conveying to the experimental blast furnace. The smaller particles were initially discharged followed by the larger ones later. This result was used as an input in the simulation. The burden profile simulated using DEM was similar to the experimental one. The terrace was found at the burden surface subsequent to ore-charging, and its simulated position simulated agreed with that of the experimental result. The surface angle of the ore layer was mostly similar. The simulated ore to coke mass ratio (O/C) distribution in the radial direction and the mean particle diameter distribution correlated with the experimental results very well. It can be concluded that this method of particle simulation of the bell-less charging process is highly reliable in the prediction of the burden distribution in a blast furnace.
Ultrasound-Assisted Extraction of GAC Peel: An Optimization of Extraction Conditions for Recovering Carotenoids and Antioxidant Capacity
Authors: Chuyen Hoang V. , Roach Paul D. , Golding John B. , Parks Sophie E. , Nguyen Minh H.
Published: December 2019

The peel of Gac fruit (Momordica cochinchinensis Spreng.), which is considered as waste of Gac processing, has been found to possess high levels of carotenoids and other antioxidants. This study aimed at determining the optimal conditions of an ultrasound-assisted extraction for recovering carotenoids and antioxidant capacity from Gac peel. A response surface methodology using the Box–Behnken design was employed to investigate the impact of extraction time, temperature and ultrasonic power on the recovery of total carotenoid and antioxidant capacity. The results showed that an extraction time of 76 min, temperature of 50 °C and ultrasonic power of 250 W were the optimal conditions for the extraction. The experimental carotenoid yield and antioxidant capacity obtained under the optimal extraction conditions were validated as 269 mg/100 g DW (dry weight) and 822 µM TE (Trolox equivalent)/100 g DW, respectively. These values were not significantly different from the values predicted by the models. The HPLC analysis for carotenoid composition showed that β-carotene, lycopene and lutein were the principal carotenoids of the extract, which constitute 86% of the total carotenoid content. Based on the obtained results, the ultrasound-assisted extraction using ethyl acetate under the above optimal conditions is suggested for the simultaneous recovery of carotenoids and antioxidant capacity from Gac peel.
Investigation and Improvement of Scalable Oxygen Reducing Cathodes for Microbial Fuel Cells by Spray Coating
Authors: Muddemann Thorben , Haupt Dennis , Jiang Bolong , Sievers Michael , Kunz Ulrich
Published: December 2019

This contribution describes the effect of the quality of the catalyst coating of cathodes for wastewater treatment by microbial fuel cells (MFC). The increase in coating quality led to a strong increase in MFC performance in terms of peak power density and long-term stability. This more uniform coating was realized by an airbrush coating method for applying a self-developed polymeric solution containing different catalysts (MnO2, MoS2, Co3O4). In addition to the possible automation of the presented coating, this method did not require a calcination step. A cathode coated with catalysts, for instance, MnO2/MoS2 (weight ratio 2:1), by airbrush method reached a peak and long-term power density of 320 and 200–240 mW/m2, respectively, in a two-chamber MFC. The long-term performance was approximately three times higher than a cathode with the same catalyst system but coated with the former paintbrush method on a smaller cathode surface area. This extraordinary increase in MFC performance confirmed the high impact of catalyst coating quality, which could be stronger than variations in catalyst concentration and composition, as well as in cathode surface area.
Fluorescence and Molecular Simulation Studies on the Interaction between Imidazolium-Based Ionic Liquids and Calf Thymus DNA
Authors: Jumbri Khairulazhar , Kassim Mohd Azlan , M. Yunus Normawati , Abdul Rahman Mohd Basyaruddin , Ahmad Haslina , Abdul Wahab Roswanira
Published: December 2019

This work presents a molecular level investigation on the nature and mode of binding between imidazolium-based ionic liquids (ILs) ([Cnbim]Br where n = 2, 4, 6) with calf thymus DNA. This investigation offers valuable insight into the mechanisms of interactions that can affect the structural features of DNA and possibly cause the alteration or inhibition of DNA function. To expedite analysis, the study resorted to using molecular docking and COnductor like Screening MOdel for Real Solvents (COSMO-RS) in conjunction with fluorescence spectroscopic data for confirmation and validation of computational results. Both the fluorescence and docking studies consistently revealed a weak interaction between the two molecules, which corresponded to the binding energy of a stable docking conformation in the range of −5.19 to −7.75 kcal mol−1. As predicted, the rod-like structure of imidazolium-based ILs prefers to bind to the double-helix DNA through a minor groove. Interestingly, the occurrence of T-shape π-π stacking was observed between the amine group in adenine that faces the aromatic ring of imidazole. In addition, data of COSMO-RS for the interaction of individual nucleic acid bases to imidazolium-based ILs affirmed that ILs showed a propensity to bind to different bases, the highest being guanine followed by cytosine, thymine, uracil, and adenine.
Entropy Generation and Dual Solutions in Mixed Convection Stagnation Point Flow of Micropolar Ti6Al4V Nanoparticle along a Riga Surface
Authors: Zaib A. , Khan Umair , Khan Ilyas , H. Seikh Asiful H. , M. Sherif El-Sayed M.
Published: December 2019

Entropy generation and dual solutions are rarely studied in the literature. An analysis is attempted here. More exactly, the present paper looks at the impact of radiation of a micropolar fluid on mixed convective flow containing the titanium alloy Ti6Al4V nanoparticle along with a Riga plate. The study of dual-nature solution for the entropy generation along a Riga surface was not being explored in the literature; therefore, the current model focuses on the dual solutions of this complex nature model. Riga surface is identified as an actuator of electromagnetic in which electrodes are accumulated alternatively. This array produces the behavior of electromagnetic hydrodynamic in the flow field. The transmuted leading equations were worked out through the formula of 3-stage Lobatto IIIA. Influences of exercising enormous parameters on temperature distribution, velocity, and micro rotation fields are portrayed and argued. More than one solution is achieved in opposing flow, while in the phenomenon of assisting flow result is unique. Moreover, due to the micropolar parameter, the separation of the boundary layer is decelerating. It is determined that the entire structure produces the dual-nature solution of the phenomenon of stagnation point flow, and the temperature profile behavior shows the significant enhancement in the thermal conductivity due to the addition of the nanoparticle. The results exposed that liquid velocity is enhanced, and micro rotation is decelerated, by improving the values of Hartmann numbers in both solutions, whereas the temperature field is decelerated in the first solution and accelerated in the second solution.
Cross-Linking of Fibrex Gel by Fungal Laccase: Gel Rheological and Structural Characteristics
Authors: Khalighi Sanaz , Berger Ralf G. , Ersoy Franziska
Published: December 2019

Sugar beet fibre (fibrex) is an abundant side-stream from the sugar refining industry. A self-produced laccase from Funalia trogii (LccFtr) (0.05 U/µg FA) successfully cross-linked fibrex to an edible gel. Dynamic oscillation measurements of the 10% fibrex gels showed a storage modulus of 5.52 kPa and loss factors ≤ 0.36 in the range from 20 to 80 Hz. Comparing storage stability of sweetened 10% fibrex gels with sweetened commercial 6% gelatin gels (10% and 30% d-sucrose) indicated a constant storage modulus and loss factors ≤ 0.7 during four weeks of storage in fibrex gels. Loss factors of sweetened gelatin gels were ≤0.2, and their storage modulus decreased from 9 to 7 kPa after adding d-sucrose and remained steady for four weeks of storage. Fibrex gel characteristics, including high water holding capacity, swelling ratio in saliva, and heat resistance are attributed to a covalently cross-linked network. Vanillin, as a mediator, and citrus pectin did not enhance covalent cross-links and elastic properties of the fibrex gels. Thus, laccase as an oxidative agent provided gels with a solid and stable texture. Fibrex gels may find uses in pharmaceutical and other industrial applications, which require a heat-resistant gel that forms easily at room temperature. They also represent an ethical alternative for manufacturing vegan, halal, and kosher food.
Intelligence and Religiosity among Dating Site Users
Authors: Kirkegaard Emil O. W. , Lasker Jordan
Published: December 2019

We sought to assess whether previous findings regarding the relationship between cognitive ability and religiosity could be replicated in a large dataset of online daters (maximum n = 67k). We found that self-declared religious people had lower IQs than nonreligious people (atheists and agnostics). Furthermore, within most religious groups, a negative relationship between the strength of religious conviction and IQ was observed. This relationship was absent or reversed in nonreligious groups. A factor of religiousness based on five questions correlated at −0.38 with IQ after adjusting for reliability (−0.30 before). The relationship between IQ and religiousness was not strongly confounded by plausible demographic covariates (β = −0.24 in final model versus −0.30 without covariates).
The Structure of Change: A Structural Interpretation of the Biblical Story of Joseph
Authors: Cooper Samuel , Guzmen-Carmeli Shlomo
Published: December 2019

In recent years, theories of structuralism in anthropology are being re-examined. This article uses structural analysis to create an anthropological interpretation of the Joseph story in the Bible and to evaluate its modes of interpretation and how it influences the formation of Jewish religious practices. The structural interpretation shows how stories serve as models for the process of cultural creation. In the case of Joseph’s story, the narrative creates a mythology but also a recurring operational infrastructure that echoes in different contexts: in ethical actions, in halachic perception, and in the foundation of various practices in Judaism including concealment and removal, covering and disrobing, that appear repeatedly and function as structures that signify and enable change.
Fire Frequency and Related Land-Use and Land-Cover Changes in Indonesia’s Peatlands
Authors: Vetrita Yenni , Cochrane Mark A.
Published: December 2019

Indonesia’s converted peatland areas have a well-established fire problem, but limited studies have examined the frequency with which they are burning. Here, we quantify fire frequency in Indonesia’s two largest peatland regions, Sumatra and Kalimantan, during 2001–2018. We report, annual areas burned, total peatland area affected by fires, amount of recurrent burning and associations with land-use and land-cover (LULC) change. We based these analyses on Moderate Resolution Imaging Spectroradiometer (MODIS) Terra/Aqua combined burned area and three Landsat-derived LULC maps (1990, 2007, and 2015) and explored relationships between burning and land-cover types. Cumulative areas burned amounted nearly half of the surface areas of Sumatra and Kalimantan but were concentrated in only ~25% of the land areas. Although peatlands cover only 13% of Sumatra and Kalimantan, annual percentage of area burning in these areas was almost five times greater than in non-peatlands (2.8% vs. 0.6%) from 2001 to 2018. Recurrent burning was more prominent in Kalimantan than Sumatra. Average fire-return intervals (FRI) in peatlands of both regions were short, 28 and 45 years for Kalimantan and Sumatra, respectively. On average, forest FRI were less than 50 years. In non-forest areas, Kalimantan had shorter average FRI than Sumatra (13 years vs. 40 years), with ferns/low shrub areas burning most frequently. Our findings highlight the significant influence of LULC change in altering fire regimes. If prevalent rates of burning in Indonesia’s peatlands are not greatly reduced, peat swamp forest will disappear from Sumatra and Kalimantan in the coming decades.
Combination of AIRS Dual CO2 Absorption Bands to Develop an Ice Clouds Detection Algorithm in Different Atmospheric Layers
Authors: Wang Liwen , Zheng Youfei , Liu Chao , Niu Zeyi , Xu Jingxin , Chen Wenfeng , Jiang Rongsheng
Published: December 2019

The use of infrared (IR) sensors to detect clouds in different layers of the atmosphere is a big challenge, especially for ice clouds. This study aims to improve ice cloud detection using Lin’s algorithm and apply it to Atmospheric Infrared Sounder (AIRS). To achieve these objectives, the scattering and emission characteristics of clouds as perceived by AIRS longwave infrared (LWIR, ~15 μm) and shortwave infrared (SWIR, ~4.3 μm) CO2 absorption bands are applied for ice cloud detection. Hence, the weighting function peak (WFP), cut-off pressure, and correlation coefficients between the brightness temperatures (BTs) of LWIR and SWIR channels are used to pair the LWIR and SWIR channels. After that, the linear relationship between the clear-sky BTs of the paired LWIR and SWIR channels is established by the cloud scattering and emission Index (CESI). However, the linear relationship fails in the presence of ice clouds. Comparing these results with collocated Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations show that the probability of detection of ice clouds for Pair-8 (WFP~330hPa), Pair-19 (WFP~555hPa), and Pair-24 (WFP~866hPa) are 0.63, 0.71, and 0.73 in the daytime and 0.46, 0.62, and 0.7 in the nighttime at a false alarm rate of 0.1 when ice clouds top pressure above 330 hPa, 555 hPa, and 866 hPa, respectively. Furthermore, the thresholds of the three pairs are 2.4 K, 3 K, and 8.7 K in the daytime and 1.7 K, 1.7 K, and 4.4 K in the nighttime at the highest Heike Skill Score (HSS). The error of HSS values based on thresholds of ice clouds is between 0.01 and 0.02 which is comparable with the ice cloud detection results in both day and night conditions. It is shown that Pair-8 (WFP~330hPa) can detect opaque and thick ice clouds above its WFP altitude over the tropical areas but it is unable to observe ice clouds over the mid-latitude while Pair-19 and Pair-24 can identify ice clouds above their WFP altitude.
Supervised and Semi-Supervised Self-Organizing Maps for Regression and Classification Focusing on Hyperspectral Data
Authors: Riese Felix M. , Keller Sina , Hinz Stefan
Published: December 2019

Machine learning approaches are valuable methods in hyperspectral remote sensing, especially for the classification of land cover or for the regression of physical parameters. While the recording of hyperspectral data has become affordable with innovative technologies, the acquisition of reference data (ground truth) has remained expensive and time-consuming. There is a need for methodological approaches that can handle datasets with significantly more hyperspectral input data than reference data. We introduce the Supervised Self-organizing Maps (SuSi) framework, which can perform unsupervised, supervised and semi-supervised classification as well as regression on high-dimensional data. The methodology of the SuSi framework is presented and compared to other frameworks. Its different parts are evaluated on two hyperspectral datasets. The results of the evaluations can be summarized in four major findings: (1) The supervised and semi-Supervised Self-organizing Maps (SOM) outperform random forest in the regression of soil moisture. (2) In the classification of land cover, the supervised and semi-supervised SOM reveal great potential. (3) The unsupervised SOM is a valuable tool to understand the data. (4) The SuSi framework is versatile, flexible, and easy to use. The SuSi framework is provided as an open-source Python package on GitHub.
Identifying and Quantifying the Abundance of Economically Important Palms in Tropical Moist Forest Using UAV Imagery
Authors: Tagle Casapia Ximena , Falen Lourdes , Bartholomeus Harm , Cárdenas Rodolfo , Flores Gerardo , Herold Martin , Honorio Coronado Eurídice N. , Baker Timothy R.
Published: December 2019

Sustainable management of non-timber forest products such as palm fruits is crucial for the long-term conservation of intact forest. A major limitation to expanding sustainable management of palms has been the need for precise information about the resources at scales of tens to hundreds of hectares, while typical ground-based surveys only sample small areas. In recent years, small unmanned aerial vehicles (UAVs) have become an important tool for mapping forest areas as they are cheap and easy to transport, and they provide high spatial resolution imagery of remote areas. We developed an object-based classification workflow for RGB UAV imagery which aims to identify and delineate palm tree crowns in the tropical rainforest by combining image processing and GIS functionalities using color and textural information in an integrative way to show one of the potential uses of UAVs in tropical forests. Ten permanent forest plots with 1170 reference palm trees were assessed from October to December 2017. The results indicate that palm tree crowns could be clearly identified and, in some cases, quantified following the workflow. The best results were obtained using the random forest classifier with an 85% overall accuracy and 0.82 kappa index.
Land Use Changes in the Zoige Plateau Based on the Object-Oriented Method and Their Effects on Landscape Patterns
Authors: Shen Ge , Yang Xiuchun , Jin Yunxiang , Luo Sha , Xu Bin , Zhou Qingbo
Published: December 2019

Land use/land cover change (LUCC) is the most direct driving force of landscape pattern change. The Zoige Plateau is a natural ecosystem with the largest high-altitude swamp wetland in China and its land use pattern has undergone great changes in recent years, but how the changes of each land use type affect the landscape pattern is uncertain. Here, we used the object-oriented method to extract land use information in 2015. Then, combined with land use data, the land use change characteristics from 2000 to 2015 were analyzed. We used the correlation analysis method to analyze the effects of land use changes on landscape pattern systematically. Three key conclusions were reached. (1) Land use information for the Zoige Plateau could be extracted with high accuracy by combining the object-oriented method and support vector machine (SVM). The overall accuracy was 93.2% and the Kappa coefficient was 0.889. (2) The comprehensive dynamic degree of land use was the highest from 2010 to 2015. From 2000 to 2015, the wetland area decreased the fastest because 57.05% of the wetlands were transferred out. Construction land increased the fastest, and the transferred in area from grassland and farmland were the main reason. (3) The effects of unused land, farmland, and construction land on the overall landscape pattern were stronger than that of the other types, among which farmland had the most significant impact (with a correlation coefficient of 0.959, p < 0.001). The change of unused land was the most highly significant factor associated with the landscape area pattern, and both the water body and unused land showed strong correlations with landscape shape pattern change. This suggested that the effects of land use types occupying a relatively small area on the landscape pattern were intensified. This study will provide guidance for the environmental management of local land resources and other natural ecosystem areas.
Designing and Evaluating a User-Oriented Calibration Field for the Target-Based Self-Calibration of Panoramic Terrestrial Laser Scanners
Authors: Medić Tomislav , Kuhlmann Heiner , Holst Christoph
Published: December 2019

Calibration of terrestrial laser scanners (TLSs) is one of the fundamental tasks for assuring the high measurement accuracy required by an increasing number of end-users. Nevertheless, the development of user-oriented calibration approaches is still an active topic of research. The calibration fields for the target-based self-calibration of TLSs described in the literature are based on the quasi-random distribution of a high number of targets, and they rely on heavy redundancy. This redundancy assures highly accurate calibration results, however, with the price of reduced efficiency. In contrast, this work follows the design, implementation, and validation of a user-oriented, cost-efficient calibration field intended for TLS calibration prior to measurement campaigns. Multiple goals and constraints are placed upon the design of the calibration field, such as comprehensive calibration for high-end panoramic TLSs considering all relevant mechanical misalignments, delivering stable and reusable calibration parameters, increasing calibration efficiency by minimizing calibration-field assembly, measurement acquisition and processing time through reducing the number of targets and scanner stations, as well as estimating calibration parameters with predefined quality criteria. The calibration field design was derived through a series of simulation experiments and it was compared with the current state of the art. The simulations indicate comparable calibration results, with eight times smaller number of targets (14 instead of 120). The implemented calibration field was tested on a range of instruments, successfully improving the measurement quality, both in situ and in the subsequent applications.
Biomass and Crop Height Estimation of Different Crops Using UAV-Based Lidar
Authors: ten Harkel Jelle , Bartholomeus Harm , Kooistra Lammert
Published: December 2019

Phenotyping of crops is important due to increasing pressure on food production. Therefore, an accurate estimation of biomass during the growing season can be important to optimize the yield. The potential of data acquisition by UAV-LiDAR to estimate fresh biomass and crop height was investigated for three different crops (potato, sugar beet, and winter wheat) grown in Wageningen (The Netherlands) from June to August 2018. Biomass was estimated using the 3DPI algorithm, while crop height was estimated using the mean height of a variable number of highest points for each m2. The 3DPI algorithm proved to estimate biomass well for sugar beet (R2 = 0.68, RMSE = 17.47 g/m2) and winter wheat (R2 = 0.82, RMSE = 13.94 g/m2). Also, the height estimates worked well for sugar beet (R2 = 0.70, RMSE = 7.4 cm) and wheat (R2 = 0.78, RMSE = 3.4 cm). However, for potato both plant height (R2 = 0.50, RMSE = 12 cm) and biomass estimation (R2 = 0.24, RMSE = 22.09 g/m2), it proved to be less reliable due to the complex canopy structure and the ridges on which potatoes are grown. In general, for accurate biomass and crop height estimates using those algorithms, the flight conditions (altitude, speed, location of flight lines) should be comparable to the settings for which the models are calibrated since changing conditions do influence the estimated biomass and crop height strongly.
Correction: Liu, L., et al. Spatiotemporal Variation of Drought and Associated Multi-Scale Response to Climate Change over the Yarlung Zangbo River Basin of Qinghai–Tibet Plateau, China. Remote Sensing 2019, 11, 1596
Authors: Li Hao , Liu Liu , Shan Baoying , Xu Zhicheng , Niu Qiankun , Cheng Lei , Liu Xingcai , Xu Zongxue
Published: December 2019

The authors wish to make the following corrections to this paper [1]: [...]
Matching Confidence Constrained Bundle Adjustment for Multi-View High-Resolution Satellite Images
Authors: Ling Xiao , Huang Xu , Zhang Yongjun , Zhou Gang
Published: December 2019

Bundle adjustment of multi-view satellite images is a powerful tool to align the orientations of all the images in a unified framework. However, the traditional bundle adjustment process faces a problem in detecting mismatches and evaluating low/medium/high-accuracy matches, which limits the final bundle adjustment accuracy, especially when the mismatches are several times more than the correct matches. To achieve more accurate bundle adjustment results, this paper formulates the prior knowledge of matching accuracy as matching confidences and proposes a matching confidence based bundle adjustment method. The core algorithm firstly selects several highest-confidence matches to initially correct orientations of all images, then detects and eliminates the mismatches under the initial orientation guesses and finally formulates both the matching confidences and the forward-backward projection errors as weights in an iterative bundle adjustment process for more accurate orientation results. We compared our proposed method with the famous RANSAC strategy as well as a state-of-the-art bundle adjustment method on the high-resolution multi-view satellite images. The experimental comparisons are evaluated by image checking points and ground control points, which shows that our proposed method is able to obtain more robust and more accurate mismatch detection results than the RANSAC strategy, even though the mismatches are four times more than the correct matches and it can also achieve more accurate orientation results than the state-of-the-art bundle adjustment method.
Feasibility of Burned Area Mapping Based on ICESAT−2 Photon Counting Data
Authors: Liu Meng , Popescu Sorin , Malambo Lonesome
Published: December 2019

Accurately mapping burned areas is crucial for the analysis of carbon emissions and wildfire risk as well as understanding the effects of climate change on forest structure. Burned areas have predominantly been mapped using optical remote sensing images. However, the structural changes due to fire also offer opportunities for mapping burned areas using three-dimensional (3D) datasets such as Light detection and ranging (LiDAR). This study focuses on the feasibility of using photon counting LiDAR data from National Aeronautics and Space Administration’s (NASA) Ice, Cloud, and land Elevation Satellite-2 (ICESat−2) mission to differentiate vegetation structure in burned and unburned areas and ultimately classify burned areas along mapped ground tracks. The ICESat−2 mission (launched in September 2018) provides datasets such as geolocated photon data (ATL03), which comprises precise latitude, longitude and elevation of each point where a photon interacts with land surface, and derivative products such as the Land Water Vegetation Elevation product (ATL08), which comprises estimated terrain and canopy height information. For analysis, 24 metrics such as the average, median and standard deviation of canopy height were derived from ATL08 data over forests burned by recent fires in 2018 in northern California and western New Mexico. A reference burn map was derived from Sentinel−2 images based on the differenced Normalized Burn Ratio (dNBR) index. A landcover map based on Sentinel−2 images was employed to remove non-forest classes. Landsat 8 based dNBR image and landcover map were also used for comparison. Next, ICESat−2 data of forest samples were classified into burned and unburned ATL08 100-m segments by both Random Forest classification and logistic regression. Both Sentinel−2 derived and Landsat 8 derived ATL08 samples got high classification accuracy, 83% versus 76%. Moreover, the resulting classification accuracy by Random Forest and logistic regression reached 83% and 74%, respectively. Among the 24 ICESat−2 metrics, apparent surface reflectance and the number of canopy photons were the most important. Furthermore, burn severity of each ATL08 segment was also estimated with Random Forest regression. R2 of predicted burn severity to observed dNBR is 0.61 with significant linear relationship and moderate correlation (r = 0.78). Overall, the reasonably high accuracies achieved in this study demonstrate the feasibility of employing ICESat−2 data in burned forest classification, opening avenues for improved estimation of burned biomass and carbon emissions from a 3D perspective.
Exploring Spatial and Temporal Connection Patterns among the Districts in Chongqing Based on Highway Passenger Flow
Authors: Huang Yang , Shi Kaifang , Zong Huiming , Zhou Tinggang , Shen Jingwei
Published: December 2019

Investigating regional connections and their influencing factors from the perspective of “flow” space is one of the foundations of promoting regional development. In this article, the data we used includes actual highway passenger flow data, National Polar-orbiting Partnership/Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) nighttime light remote sensing data, and socioeconomic data. We analyzed the spatial distribution pattern, connection intensity and spatial autocorrelation of highway passenger flow in Chongqing during the working day, weekend and May Day and revealed the influencing factors by means of a geographic detector. Three key conclusions resulted from this research. First, highway passenger flow in Chongqing districts exhibits spatial agglomeration that is clearly higher in western Chongqing than in eastern Chongqing and forms an obviously dual-core “star” structure, with the main urban area and Wanzhou serving as the core. Second, a factor detector notes that the nighttime light area index (0.9251, 0.9512, 0.9541) has the strongest explanatory power for the spatial differentiation of passenger traffic in Chongqing districts, which is the key factor. Third, interaction detection shows that the interaction between the two factors displays an enhancement effect at different times. The nighttime light area index shows the strongest explanatory power under the synergy of tourist attractions, which are 0.9850, 0.9903 and 0.9908. But the per capita GDP and highway mileage have the most obvious enhancement effect after interaction (0.9544, 0.9661, 0.9652). Therefore, in future planning and development, we should pay attention to cooperation and exchanges between districts and use the nighttime light area index as an important reference factor to provide a scientific basis for the construction of public transport and economic construction in Chongqing.
Cross-Comparison and Methodological Improvement in GPS Tomography
Authors: Brenot Hugues , Rohm Witold , Kačmařík Michal , Möller Gregor , Sá André , Tondaś Damian , Rapant Lukas , Biondi Riccardo , Manning Toby , Champollion Cédric
Published: December 2019

GPS tomography has been investigated since 2000 as an attractive tool for retrieving the 3D field of water vapour and wet refractivity. However, this observational technique still remains a challenging task that requires improvement of its methodology. This was the purpose of this study, and for this, GPS data from the Australian Continuously Operating Research Station (CORS) network during a severe weather event were used. Sensitivity tests and statistical cross-comparisons of tomography retrievals with independent observations from radiosonde and radio-occultation profiles showed improved results using the presented methodology. The initial conditions, which were associated with different time-convergence of tomography inversion, play a critical role in GPS tomography. The best strategy can reduce the normalised root mean square (RMS) of the tomography solution by more than 3 with respect to radiosonde estimates. Data stacking and pseudo-slant observations can also significantly improve tomography retrievals with respect to non-stacked solutions. A normalised RMS improvement up to 17% in the 0–8 km layer was found by using 30 min data stacking, and RMS values were divided by 5 for all the layers by using pseudo-observations. This result was due to a better geometrical distribution of mid- and low-tropospheric parts (a 30% coverage improvement). Our study of the impact of the uncertainty of GPS observations shows that there is an interest in evaluating tomography retrievals in comparison to independent external measurements and in estimating simultaneously the quality of weather forecasts. Finally, a comparison of multi-model tomography with numerical weather prediction shows the relevant use of tomography retrievals to improving the understanding of such severe weather conditions.
Potential of Night-Time Lights to Measure Regional Inequality
Authors: Ivan Kinga , Holobâcă Iulian-Horia , Benedek József , Török Ibolya
Published: December 2019

Night-time lights satellite images provide a new opportunity to measure regional inequality in real-time by developing the Night Light Development Index (NLDI). The NLDI was extracted using the Gini coefficient approach based on population and night light spatial distribution in Romania. Night-time light data were calculated using a grid with a 0.15 km2 area, based on Defense Meteorological Satellite Program (DMSP) /Operational Linescan System (OLS satellite imagery for the 1992–2013 period and based on the National Polar-orbiting Partnership–Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) satellite imagery for the 2014–2018 period. Two population density grids were created at the level of equal cells (0.15 km2) using ArcGIS and PostgreSQL software, and census data from 1992 and 2011. Subsequently, based on this data and using the Gini index approach, the Night Light Development Index (NLDI) was calculated within the MATLAB software. The NLDI was obtained for 42 administrative counties (nomenclature of territorial units for statistics level 3 (NUTS-3 units)) for the 1992–2018 period. The statistical relationship between the NLDI and the socio-economic, demographic, and geographic variables highlighted a strong indirect relationship with local tax income and gross domestic product (GDP) per capita. The polynomial model proved to be better in estimating income based on the NLDI and R2 coefficients showed a significant improvement in total variation explained compared to the linear regression model. The NLDI calculated on the basis of night-time lights satellite images proved to be a good proxy for measuring regional inequalities. Therefore, it can play a crucial role in monitoring the progress made in the implementation of Sustainable Development Goal 10 (reduced inequalities).
Automated Georectification and Mosaicking of UAV-Based Hyperspectral Imagery from Push-Broom Sensors
Authors: Angel Yoseline , Turner Darren , Parkes Stephen , Malbeteau Yoann , Lucieer Arko , McCabe Matthew F.
Published: December 2019

Hyperspectral systems integrated on unmanned aerial vehicles (UAV) provide unique opportunities to conduct high-resolution multitemporal spectral analysis for diverse applications. However, additional time-consuming rectification efforts in postprocessing are routinely required, since geometric distortions can be introduced due to UAV movements during flight, even if navigation/motion sensors are used to track the position of each scan. Part of the challenge in obtaining high-quality imagery relates to the lack of a fast processing workflow that can retrieve geometrically accurate mosaics while optimizing the ground data collection efforts. To address this problem, we explored a computationally robust automated georectification and mosaicking methodology. It operates effectively in a parallel computing environment and evaluates results against a number of high-spatial-resolution datasets (mm to cm resolution) collected using a push-broom sensor and an associated RGB frame-based camera. The methodology estimates the luminance of the hyperspectral swaths and coregisters these against a luminance RGB-based orthophoto. The procedure includes an improved coregistration strategy by integrating the Speeded-Up Robust Features (SURF) algorithm, with the Maximum Likelihood Estimator Sample Consensus (MLESAC) approach. SURF identifies common features between each swath and the RGB-orthomosaic, while MLESAC fits the best geometric transformation model to the retrieved matches. Individual scanlines are then geometrically transformed and merged into a single spatially continuous mosaic reaching high positional accuracies only with a few number of ground control points (GCPs). The capacity of the workflow to achieve high spatial accuracy was demonstrated by examining statistical metrics such as RMSE, MAE, and the relative positional accuracy at 95% confidence level. Comparison against a user-generated georectification demonstrates that the automated approach speeds up the coregistration process by 85%.
The Influence of Different Modelling Factors on Global Temperature and Pressure Models and Their Performance in Different Zenith Hydrostatic Delay (ZHD) Models
Authors: Yang Fei , Meng Xiaolin , Guo Jiming , Shi Junbo , An Xiangdong , He Qiyi , Zhou Lv
Published: December 2019

Surface temperature and pressure are indispensable variables in Global Navigation Satellite System (GNSS) meteorology. The lack of meteorological observations located at or near the GNSS sites is a big challenge for the calculation of accurate zenith hydrostatic delay (ZHD). Therefore, various empirical models with different model forms were established to provide temperature and pressure values. In this study, the influence of different modelling factors, including model forms, temporal resolution of the data sources, and the spatial resolution of the data sources, is evaluated and the temperature and pressure model with the best performance is developed. On the basis of the meteorological parameters estimated by the above model, we analyzed the global performance of the three most commonly used ZHD models, that is, the Saastamoinen, Hopfield, and Black models. The numerical results show that the model with the idea of time-segmented modelling performs best, of which the global mean root mean square (RMS), mean absolute error (MAE), and standard deviation (SD) are 7.87/6.33/7.17 hPa and 2.95/2.31/2.79 K for pressure and temperature, respectively, using the data sources with temporal resolution of 2 h and spatial resolution of 2.5° × 2° in the reanalysis data comparison. In comparison with the radiosonde data, the mean RMS/MAE/SD are 7.02/5.24/6.46 hPa and 4.05/3.17/3.86 K for pressure and temperature, respectively. The Saastamoinen model with a global mean bias/RMS of 1.01/16.9 mm achieved the best ZHD estimated values compared with the other two ZHD models.