bluuebunny/crossref_metadata_2025 huggingface dataset:
The Influence of Extracts from Common Houseleek (Sempervivum tectorum) on the Metabolic Activity of Human Melanoma Cells WM-266-4
Authors: Knez Marevci Maša , Bjelić Sašo , Dariš Barbara , Knez Željko , Leitgeb Maja
Published: September 2021

Human melanoma cells are known as one of the most aggressive cancer cells, and consequently, melanoma is one of the most incurable cancer diseases. There is intense activity in research and development of potential medicines for malignant diseases, including alternative forms of remedies. Therefore, the purpose of our work was testing extracts from the common houseleek (Sempervivum tectorum) grown in Slovenia to establish its impact on human melanoma cells. Namely, we wanted to verify if the extracts inhibit growth of malignant cells and their metabolic activity. Soxhlet, cold solvent, ultrasound, and supercritical extraction methods were applied to obtain S. tectorum extracts. Polyphenols and proanthocyanins content in acquired extracts was determined as well as their antioxidative potential. For a relevant comparison, Chinese (CHI) dried and Slovenian (SLO) lyophilized S. tectorum was used. Results showed that the highest contents of polyphenols and proanthocyanins were yielded from lyophilized material, which also had the highest antioxidative potential. The focus of our work was on analysis of possible inhibition effects of the extracts on human melanoma cells since no past studies were found regarding the possible effects of S. tectorum on metabolic activity of WM-266-4. We established that in a 24-h incubation period, the extracts inhibited metabolic activity of the cells at their concentrations of 20, 10, 4, 2, 1, 0.2, and 0.02 mg/mL. Extract obtained from SLO S. tectorum (ultrasound extraction with acetone as a solvent), which showed promising results of inhibitory effect on the mentioned cells, was further described since the local plant was the focus of our study. CHI S. tectorum extract (Soxhlet extraction with ehtanol:water mixture = 1:1 as a solvent) showed the highest inhibitory effect on human melanoma cells WM-266-4, although both obtained extracts are suitable for their growth inhibition of this specific cell line. Our results suggest inhibitory ability of S. tectorum extracts on the metabolic activity of WM-266-4 metastatic cell line, suggesting their potential use as an anticancer agent.
An Improved Hybrid Aquila Optimizer and Harris Hawks Algorithm for Solving Industrial Engineering Optimization Problems
Authors: Wang Shuang , Jia Heming , Abualigah Laith , Liu Qingxin , Zheng Rong
Published: September 2021

Aquila Optimizer (AO) and Harris Hawks Optimizer (HHO) are recently proposed meta-heuristic optimization algorithms. AO possesses strong global exploration capability but insufficient local exploitation ability. However, the exploitation phase of HHO is pretty good, while the exploration capability is far from satisfactory. Considering the characteristics of these two algorithms, an improved hybrid AO and HHO combined with a nonlinear escaping energy parameter and random opposition-based learning strategy is proposed, namely IHAOHHO, to improve the searching performance in this paper. Firstly, combining the salient features of AO and HHO retains valuable exploration and exploitation capabilities. In the second place, random opposition-based learning (ROBL) is added in the exploitation phase to improve local optima avoidance. Finally, the nonlinear escaping energy parameter is utilized better to balance the exploration and exploitation phases of IHAOHHO. These two strategies effectively enhance the exploration and exploitation of the proposed algorithm. To verify the optimization performance, IHAOHHO is comprehensively analyzed on 23 standard benchmark functions. Moreover, the practicability of IHAOHHO is also highlighted by four industrial engineering design problems. Compared with the original AO and HHO and five state-of-the-art algorithms, the results show that IHAOHHO has strong superior performance and promising prospects.
A Simple Nozzle-Diffuser Duct Used as a Kuroshio Energy Harvester
Authors: Yeh Po-Hung , Tsai Shang-Yu , Chen Wei-Ren , Wu Shing-Nan , Hsieh Meng-Chang , Chen Bang-Fuh
Published: September 2021

In response to the increasing energy demand in Taiwan and the global trend of renewable energy development, Kuroshio energy is a potential energy source. How to extract this invaluable natural resource has then become an intriguing and important question in engineering practices. This study reported the results of a feasibility study for a nozzle-diffuser duct (NDD) as the Kuroshio currents energy harvester. The computational fluid dynamics (CFD) software ANSYS Fluent was employed to calculate the drag and added mass coefficients of the duct anchored to the seabed. Those coefficients were further imported into Orcaflex to simulate the motion of the duct under normal and storm wave conditions. Results showed that the duct was stable 25 m below the sea surface under normal wave conditions. When the wave condition changed to storm waves, the duct needed to dive into at least 90 m below the sea surface to regain its stability and obtain high power take-off (PTO). An optimal design nozzle-diffuser-duct was reported, and a PTO peak of 15 kW was expectable in the Kuroshio currents. Once a suitable offshore platform can be developed with sixty-six NDDs, a Megawatt Kuroshio ocean current power generation system is feasible in the near future.
Modeling Freight Consolidation in a Make-to-Order Supply Chain: A Simulation Approach
Authors: Alnahhal Mohammed , Ahrens Diane , Salah Bashir
Published: September 2021

Shipment consolidation is one of main initiatives to reduce CO2 emissions and transportation cost. It reduces the number of shipments per customer and reduces transportation costs by using larger shipments. This paper investigates the temporal consolidation process in a central consolidation center in a make-to-order supply chain. This research was motivated by a case study of a design furniture company that has many suppliers and customers in large parts of Europe. Simulation was used to check the effect of a new and a special time-based temporal consolidation on the response time in outbound logistics. A soft delivery deadline that is less than the average lead time was used because of the long lead time. Arena Software was used to model the supply chain in order to find the best circumstances to use consolidation. Results showed that temporal consolidation could be more effective when order preparation time is with larger variability. The useful waiting is more when there is at least one order every four days. A formula that approximates the percent of reduced shipments was found. Furthermore, many shipments can be reduced without severely affecting the average response time. The value of the study is that it investigates consolidation problems in a high-mix low-volume environment that was overlooked by previous research.
Polyphenolic Herbal Extract of Cistus incanus as Natural Preservatives for Sausages Enriched with Natural Colors
Authors: Sośnicka Marta , Nowak Agnieszka , Czyżowska Agata , Gałązka-Czarnecka Ilona , Czerbniak Aleksandra
Published: September 2021

This study evaluates the effects of polyphenolic extract of Cistus incanus, lycopene dye from tomatoes, and betanin dye from red beet on selected parameters of model meat products with reduced nitrate contents. The polyphenolic composition and activity of the C. incanus extract was analyzed, revealing the presence of elagotannins, flavanols, and glycosylated flavanols. We studied the effects of the extract and dyes as well as of mixtures of the extract and dyes on the growth of bacteria characteristic of the meat environment: E. coli, S. enterica, P. fragi, L. monocytogenes, B. thermosphacta, and L. sakei. We studied the effects of the extract and dyes on the lipid oxidation, color, and microbiological quality of pork sausages with reduced nitrate content over 28 days of storage. During storage, the amounts of malon dialdehyde reduced, which indicates that the extract and dyes exhibited antioxidant activity and slowed lipid oxidation in the sausages. An increase in red color was also observed in the sausages with natural additives, despite their decreased nitrate content. It was found that the C. incanus extract combined with coloring agents positively influenced the selected parameters of the analyzed pork sausages.
Effects of Spray-Drying Inlet Temperature on the Production of High-Quality Native Rice Starch
Authors: Tay Jamie Boon Jun , Chua Xinying , Ang Cailing , Subramanian Gomathy Sandhya , Tan Sze Yu , Lin Esther Marie Jierong , Wu Wen-Ya , Goh Kelvin Kim Tha , Lim Kaiyang
Published: September 2021

Rice starch is a common functional ingredient used in various food applications. The drying regime to obtain dry starch powder is an important processing step, which affects the functional properties of the starch. The application of extreme thermal treatment during the conventional drying process tends to elicit irreversible changes to the rice starch, resulting in the loss of desired functionalities. In a previous study, we reported the development of a novel low temperature spray-drying based process which efficiently dries waxy rice starch, while preserving its physicochemical properties and functionalities. This study, a follow-up to the previous report, evaluated the effect of different spray-drying inlet temperatures on the production yield, physicochemical properties, and functionalities of waxy rice starch. Increasing the inlet temperature from 40 °C to 100 °C resulted in an increase in the process yield from 74.83% to 88.66%, respectively. All spray dried waxy rice starches possessed a low moisture content of less than 15%, and a consistent particle size (median ~6.00 μm). Regardless of the inlet temperatures, the physicochemical functionalities, including the pasting characteristics and flowability, were similar to that of the native waxy rice starch. The molecular and A-type crystalline structure of the waxy rice starches were also conserved. An inlet temperature of 60 °C represented the optimum temperature for the spray-drying process, with a good yield (84.55 ± 1.77%) and a low moisture content (10.74 ± 1.08%), while retaining its native physicochemical functionalities and maximizing energy efficacy.
Improving Sports Outcome Prediction Process Using Integrating Adaptive Weighted Features and Machine Learning Techniques
Authors: Lu Chi-Jie , Lee Tian-Shyug , Wang Chien-Chih , Chen Wei-Jen
Published: September 2021

Developing an effective sports performance analysis process is an attractive issue in sports team management. This study proposed an improved sports outcome prediction process by integrating adaptive weighted features and machine learning algorithms for basketball game score prediction. The feature engineering method is used to construct designed features based on game-lag information and adaptive weighting of variables in the proposed prediction process. These designed features are then applied to the five machine learning methods, including classification and regression trees (CART), random forest (RF), stochastic gradient boosting (SGB), eXtreme gradient boosting (XGBoost), and extreme learning machine (ELM) for constructing effective prediction models. The empirical results from National Basketball Association (NBA) data revealed that the proposed sports outcome prediction process could generate a promising prediction result compared to the competing models without adaptive weighting features. Our results also showed that the machine learning models with four game-lags information and adaptive weighting of power could generate better prediction performance.
Modelling Norm Scores with the cNORM Package in R
Authors: Gary Sebastian , Lenhard Wolfgang , Lenhard Alexandra
Published: September 2021

In this article, we explain and demonstrate how to model norm scores with the cNORM package in R. This package is designed specifically to determine norm scores when the latent ability to be measured covaries with age or other explanatory variables such as grade level. The mathematical method used in this package draws on polynomial regression to model a three-dimensional hyperplane that smoothly and continuously captures the relation between raw scores, norm scores and the explanatory variable. By doing so, it overcomes the typical problems of classical norming methods, such as overly large age intervals, missing norm scores, large amounts of sampling error in the subsamples or huge requirements with regard to the sample size. After a brief introduction to the mathematics of the model, we describe the individual methods of the package. We close the article with a practical example using data from a real reading comprehension test.
Faculty Use of Open-Access Journals: A Case Study of Faculty Publications and Cited References at a California University
Authors: Faulkner Kendall
Published: September 2021

Many in the library world see open-access (OA) publishing as the way of the future, necessary to combat ever-rising costs, expand knowledge and information production, and level the playing field for researchers and students across the world. However, ingrained notions of the publishing process in academia, and concerns over OA journals’ quality and costs often make researchers less enthusiastic. This study takes a close look at faculty habits at the college-department level by reviewing faculty publishing habits and cited references in those publications. Results show that the faculty in the Psychology Department at California State University, Los Angeles regularly publish at all OA levels, but utilize formal self-archiving less than what is found in their cited references. Furthermore, the department faculty cite fully OA (Gold) journals less than they publish in them.
Effect of Hard Plastic Waste on the Quality of Recycled Polypropylene Blends
Authors: Tratzi Patrizio , Giuliani Chiara , Torre Marco , Tomassetti Laura , Petrucci Roberto , Iannoni Antonio , Torre Luigi , Genova Salvatore , Paolini Valerio , Petracchini Francesco , Di Carlo Gabriella
Published: September 2021

The recycling of plastic waste is undergoing fast growth due to environmental, health and economic issues, and several blends of post-consumer and post-industrial polymeric materials have been characterized in recent years. However, most of these researches have focused on plastic containers and packaging, neglecting hard plastic waste. This study provides the first experimental characterization of different blends of hard plastic waste and virgin polypropylene in terms of melt index, differential scan calorimetry (DSC), thermogravimetric analysis (TGA), mechanical properties (tensile, impact and Shore hardness) and Vicat softening test. Compared to blends based on packaging plastic waste, significant differences were observed in terms of melt flow index (about 10 points higher for hard plastic waste). Mechanical properties, in particular yield strain, were instead quite similar (between 5 and 9%), despite a higher standard deviation being observed, up to 10%, probably due to incomplete homogenization. Results demonstrate that these worse performances could be mainly attributed to the presence of different additives, as well as to the presence of impurities or traces of other polymers, other than incomplete homogenization. On the other hand, acceptable results were obtained for selected blends; the optimal blending ratio was identified as 78% post-consumer waste and 22% post-industrial waste, meeting the requirement for injection molding and thermoforming.
Modern Teachers of Ars moriendi
Authors: Janiak Agnieszka , Gierczyk Marcin
Published: September 2021

It is evident that a change is happening, a breakthrough, in perceptions of death; the next episode is being unveiled. After the stages Philippe Aries named death of the tame and then death of the wild, people today are finally experiencing the humanizing of death, which we call sharing death, whose influence is worth deep analysis. Our hypothesis is that today, Ars moriendi, meeting the needs of the dying, may be learned from the so-called death teachers, whose message is growing noticeably in society. This research shows a certain reversal of social roles that are worth noting and accepting. In the past, a priest was a guide and a teacher in the face of dying and death; today, he has the opportunity to learn Ars moriendi from contemporary teachers of dying, to imagine an empty chair standing by a dying person.
The Wind’s Prayer, the World’s Sabbath: Spirit and Place in Lance Henson and Wendell Berry
Authors: Burkemper Elizabeth , Mahan David C.
Published: September 2021

Although a vast body of poetry celebrates the natural world and addresses issues concerning the environment, it can be overlooked in the discourses of environmental activism. In this paper, we seek to demonstrate the unique contributions that poetry makes to a thoughtful, and in this case, theological, engagement with our present environmental crises. Here, we create a conversation between two poets of two different religious traditions. Cheyenne poet Lance Henson’s poem “we are a people” reimagines humanity’s self-conception in light of earthly interconnectedness from the perspective of his own Native American spiritual sensibilities. Christian poet Wendell Berry’s poem “Sabbaths IV” (1983) relocates our understanding of Sabbath beyond its liturgical designations and practices, asking us to attend to “the true world’s Sabbath”. We offer close readings of these two poems that mark the distinctions that emerge from and interact with their respective theological visions, but also where they find common ground. Through this work of reading literature theologically, we argue that these poems both refine our attentiveness to the earth as the site of religious import and consequence, and call upon readers to enact other ways of being in the world amidst the climate catastrophe that are inspired by faith and spirituality.
How Does Religious Commitment Affect Satisfaction with Life during the COVID-19 Pandemic? Examining Depression, Anxiety, and Stress as Mediators
Authors: Koçak Orhan
Published: September 2021

The effect of religiosity on individuals is seen more in stressful situations. Religion strengthens people in coping with the issues given rise by COVID-19 due to its contributions, such as reducing death fear and giving hope. The impact of religious commitment on COVID-19 fear, psychological consequences, and satisfaction with life levels in the COVID-19 period is investigated. To measure this impact of religious commitment, a cross-sectional study was designed with 2810 adults in Turkey. For this purpose, religious commitment, COVID-19 fear, DASS-21, and satisfaction with life scales were used. Mediation and moderation analyses were conducted to test the formed hypotheses. First, the impact of religious commitment on satisfaction with life with depression, anxiety, and stress was tested. Then, the moderating impact of COVID-19 fear in terms of the effect of religious commitment on satisfaction with life was analyzed. Finally, the role of depression’s mediation and COVID-19 fear’s moderation in terms of the impact of religious commitment on satisfaction with life was found. It was found that satisfaction with life decreased more in those with high COVID-19 fear than those with low COVID-19 fear; additionally, religious commitment increased satisfaction with life by reducing depression.
“This Is My Place”. (Hi)Storytelling Churches in the Northern Netherlands
Authors: Kroesen Justin E. A.
Published: September 2021

This article proposes storytelling as a tool to return historic church buildings to the people in today’s secularized society. It starts by recognizing the unique qualities shared by most historic churches, namely that they are (1) different from most other buildings, (2) unusually old, and (3) are often characterized by beautiful exteriors and interiors. The argument builds on the storytelling strategies that were chosen in two recent book projects (co-)written by the author of this article, on historic churches in the northern Dutch provinces of Frisia (Fryslân) and Groningen. Among the many stories “told” by the Frisian and Groningen churches and their interiors, three categories are specifically highlighted. First, the religious aspect of the buildings’ history, from which most of its forms, fittings, and imagery are derived, and which increasingly needs to be explained in a largely post-Christian society. Second, churches tell us local histories, because they were the communities’ most public space for centuries, and a room for social representation. Finally, third, local history is always “glocal”, because it is interwoven with multiple connections to other places far and near. Researching, cherishing, and telling these stories are powerful means to engage communities in the future preservation of their old churches as religious and cultural heritage.
Amway as Neoliberal Religious Tradition
Authors: Laminack Michael
Published: September 2021

Why do people desire their own continued oppression under neoliberalism? This essay seeks an answer to this confounding question through analysis of the Amway organization, an American multi-level-marketing (MLM) company that rose to a multi-billion dollar value in the 1980s and 90s. My argument is that Amway serves as a prime case study for the relation between neoliberalism and religious practices––people desire their continued oppression under neoliberalism in part because neoliberalism bears meaning at the level of culture and religion. What sets Amway apart from other MLMs, and makes Amway a prime case study for neoliberalism and religious practices, is its amalgamation of neoliberal ideology with ideas and trends from American evangelicalism, to the extent that it serves as a kind of neoliberal religious tradition. As this amalgamation demonstrates, people may defend neoliberalism with a similar fervor as defending cultural or religious traditions. The conclusion explores the possibility of a decolonial American evangelicalism, which would seek options for broadening the horizons of American evangelicalism beyond the relationship to neoliberalism and the possibility of a critical theology robust enough to thoughtfully critique neoliberalism. In pursuit of this thesis, the essay utilizes a theoretical framework guided by the contributions of scholars including Wendy Brown, Walter Benjamin, Olivier Roy, Walter Mignolo, and Carl Raschke in order to analyze Amway through the lens of contemporary political theories of neoliberalism.
Goddess of the Orient: Exploring the Relationship between the Persian Goddess Anahita and the Sufi Journey to Mount Qaf
Authors: Mirjalili Faranak
Published: September 2021

This paper explores the possible connections between the Persian Goddess Aredvi Sura Anahita and Sufi cosmology. How can we trace images, symbols and functions of the goddess in the symbolic journey to Mount Qaf in Sufism? The research question was posed by the author after a collision of mystical experiences and dreams with the figure of Anahita while being on the Sufi path. The paper offers a linguistic, scriptural and hermeneutic analysis of Anahita in the Avesta and her role in Zoroastrian cosmology, while looking at the symbolic importance of Mount Qaf and the figure of Khezr in Sufism. The comparative study draws on the work of Henry Corbin and Shahab al-Din Sohrawardi to explore the threads between these two ancient Persian traditions.
Analysis of the Negative Daily Temperatures Influence on the Failure Rate of the Water Supply Network
Authors: Żywiec Jakub , Boryczko Krzysztof , Kowalski Dariusz
Published: September 2021

As a part of the critical infrastructure, water supply systems must be characterized by an appropriate level of operational reliability and safety. One of the threats to this is the failure of the water supply network, influenced by many factors, among which we can distinguish internal factors related to the process of designing, construction and system operation, and external factors related to the impact of the environment. The paper presents the influence of negative daily temperature on the failure rate of the water supply network, taking into account the material of the pipes, their diameters, and the cause of failure. The research was carried out on operational data from the period 2004–2018 from the water supply network in a city located in south-eastern Poland. The relationship between the daily temperature and the failure rate of the water supply system has been shown. As the temperature values drop, the failure rate values increase. The biggest influence of the negative daily temperature on the water supply network failure rate is observed for cast iron pipes. PE and PVC pipes are more resistant to the influence of negative temperatures. The most common cause of failure is corrosion and unsealing of the pipes. Pipes with the diameters of 100, 150, 300, 350, and 400 mm in distribution and main networks turned out to fail most often. These results can be used by water supply companies to limit the influence of factors related to negative daily temperatures on the failure rate of the water supply network.
Risk Management Committee, Auditor Choice and Audit Fees
Authors: Harymawan Iman , Prabhawa Aditya Aji , Nasih Mohammad , Putra Fajar Kristanto Gautama
Published: September 2021

We find that risk management committees and BIG4 audit firms contribute to audit fees. We use observations of 895 companies registered in Indonesia for 2014–2018, and to answer our hypothesis we used ordinary least squares analysis. The results show that BIG4 weakens the relationship between RMC and audit fees. Our study proves that higher demand for audit coverage will occur if there is a risk management committee within the company. As a result, audit fees increase. RMC may demand high-quality external guarantees, but the presence of BIG4 as a moderating variable reduces the relationship between the two variables. We assume that this can happen because auditors can work more efficiently if the company has an RMC, auditor(s) could indirectly reduce the risk because it is partially results from the performance of the RMC. In addition, we also use the robustness test to handle the endogeneity problem with consistent results as OLS. These findings provide evidence for policy makers about the relationship between audit fees and risk management committees.
Empirics of Korean Shipping Companies’ Default Predictions
Authors: Park Sunghwa , Kim Hyunsok , Kwon Janghan , Kim Taeil
Published: September 2021

In this paper, we use a logit model to predict the probability of default for Korean shipping companies. We explore numerous financial ratios to find predictors of a shipping firm’s failure and construct four default prediction models. The results suggest that a model with industry specific indicators outperforms other models in predictive ability. This finding indicates that utilizing information about unique financial characteristics of the shipping industry may enhance the performance of default prediction models. Given the importance of the shipping industry in the Korean economy, this study can benefit both policymakers and market participants.
Using Unmanned Aerial Vehicle and LiDAR-Derived DEMs to Estimate Channels of Small Tributary Streams
Authors: Grau Joan , Liang Kang , Ogilvie Jae , Arp Paul , Li Sheng , Robertson Bonnie , Meng Fan-Rui
Published: September 2021

Defining stream channels in a watershed is important for assessing freshwater habitat availability, complexity, and quality. However, mapping channels of small tributary streams becomes challenging due to frequent channel change and dense vegetation coverage. In this study, we used an Unmanned Aerial Vehicle (UAV) and photogrammetry method to obtain a 3D Digital Surface Model (DSM) to estimate the total in-stream channel and channel width within grazed riparian pastures. We used two methods to predict the stream channel boundary: the Slope Gradient (SG) and Vertical Slope Position (VSP). As a comparison, the same methods were also applied using low-resolution DEM, obtained with traditional photogrammetry (coarse resolution) and two more LiDAR-derived DEMs with different resolution. When using the SG method, the higher-resolution, UAV-derived DEM provided the best agreement with the field-validated area followed by the high-resolution LiDAR DEM, with Mean Squared Errors (MSE) of 1.81 m and 1.91 m, respectively. The LiDAR DEM collected at low resolution was able to predict the stream channel with a MSE of 3.33 m. Finally, the coarse DEM did not perform accurately and the MSE obtained was 26.76 m. On the other hand, when the VSP method was used we found that low-resolution LiDAR DEM performed the best followed by high-resolution LiDAR, with MSE values of 9.70 and 11.45 m, respectively. The MSE for the UAV-derived DEM was 15.12 m and for the coarse DEM was 20.78 m. We found that the UAV-derived DEM could be used to identify steep bank which could be used for mapping the hydrogeomorphology of lower order streams. Therefore, UAVs could be applied to efficiently map small stream channels in order to monitor the dynamic changes occurring in these ecosystems at a local scale. However, the VSP method should be used to map stream channels in small watersheds when high resolution DEM data is not available.
NaturaSat—A Software Tool for Identification, Monitoring and Evaluation of Habitats by Remote Sensing Techniques
Authors: Mikula Karol , Šibíková Mária , Ambroz Martin , Kollár Michal , Ožvat Aneta A. , Urbán Jozef , Jarolímek Ivan , Šibík Jozef
Published: September 2021

The NaturaSat software integrates various image processing techniques together with vegetation data, into one multipurpose tool that is designed for performing facilities for all requirements of habitat exploration, all in one place. It provides direct access to multispectral Sentinel-2 data provided by the European Space Agency. It supports using these data with various vegetation databases, in a user-friendly environment, for, e.g., vegetation scientists, fieldwork experts, and nature conservationists. The presented study introduces the NaturaSat software, describes new powerful tools, such as the semi-automatic and automatic segmentation methods, and natural numerical networks, together with validated examples comparing field surveys and software outputs. The software is robust enough for field work researchers and stakeholders to accurately extract target units’ borders, even on the habitat level. The deep learning algorithm, developed for habitat classification within the NaturaSat software, can also be used in various research tasks or in nature conservation practices, such as identifying ecosystem services and conservation value. The exact maps of the habitats obtained within the project can improve many further vegetation and landscape ecology studies.
The Role of Earth Observation in Achieving Sustainable Agricultural Production in Arid and Semi-Arid Regions of the World
Authors: Qader Sarchil Hama , Dash Jadu , Alegana Victor A. , Khwarahm Nabaz R. , Tatem Andrew J. , Atkinson Peter M.
Published: September 2021

Crop production is a major source of food and livelihood for many people in arid and semi-arid (ASA) regions across the world. However, due to irregular climatic events, ASA regions are affected commonly by frequent droughts that can impact food production. In addition, ASA regions in the Middle East and Africa are often characterised by political instability, which can increase population vulnerability to hunger and ill health. Remote sensing (RS) provides a platform to improve the spatial prediction of crop production and food availability, with the potential to positively impact populations. This paper, firstly, describes some of the important characteristics of agriculture in ASA regions that require monitoring to improve their management. Secondly, it demonstrates how freely available RS data can support decision-making through a cost-effective monitoring system that complements traditional approaches for collecting agricultural data. Thirdly, it illustrates the challenges of employing freely available RS data for mapping and monitoring crop area, crop status and forecasting crop yield in these regions. Finally, existing approaches used in these applications are evaluated, and the challenges associated with their use and possible future improvements are discussed. We demonstrate that agricultural activities can be monitored effectively and both crop area and crop yield can be predicted in advance using RS data. We also discuss the future challenges associated with maintaining food security in ASA regions and explore some recent advances in RS that can be used to monitor cropland and forecast crop production and yield.
Characterizing Small-Town Development Using Very High Resolution Imagery within Remote Rural Settings of Mozambique
Authors: Chen Dong , Loboda Tatiana V. , Silva Julie A. , Tonellato Maria R.
Published: September 2021

While remotely sensed images of various resolutions have been widely used in identifying changes in urban and peri-urban environments, only very high resolution (VHR) imagery is capable of providing the information needed for understanding the changes taking place in remote rural environments, due to the small footprints and low density of man-made structures in these settings. However, limited by data availability, mapping man-made structures and conducting subsequent change detections in remote areas are typically challenging and thus require a certain level of flexibility in algorithm design that takes into account the specific environmental and image conditions. In this study, we mapped all buildings and corrals for two remote villages in Mozambique based on two single-date VHR images that were taken in 2004 and 2012, respectively. Our algorithm takes advantage of the presence of shadows and, through a fusion of both spectra- and object-based analysis techniques, is able to differentiate buildings with metal and thatch roofs with high accuracy (overall accuracy of 86% and 94% for 2004 and 2012, respectively). The comparison of the mapping results between 2004 and 2012 reveals multiple lines of evidence suggesting that both villages, while differing in many aspects, have experienced substantial increases in the economic status. As a case study, our project demonstrates the capability of a coupling of VHR imagery with locally adjusted classification algorithms to infer the economic development of small, remote rural settlements.
Variation Tendency of Coastline under Natural and Anthropogenic Disturbance around the Abandoned Yellow River Delta in 1984–2019
Authors: Sun Zhipeng , Niu Xiaojing
Published: September 2021

The coast around the Abandoned Yellow River Delta underwent significant changes under anthropogenic disturbance. This study aims to reveal the variation of the coastline, tidal flat area, and intertidal zone slope before, during, and after extensive reclamation during the period of 1984–2019 using satellite remote sensing images. In order to eliminate the influence of the varying water level, a new coastline correction algorithm had been proposed under the condition of insufficient accurate slope and water level data. The influence of seawalls on slope estimation were considered in it. The spatiotemporal evolution of coast had been analyzed and confirmed to be reasonable by comparing with the observed data. The results show that the coast can be roughly divided into a north erosion part and a south deposition part. Affected by reclamation, their tidal flat area in 2019 is reduced to only 43 and 27% of original area in 1984, respectively, which results in a continuous decrease in the tidal flat width. The adjustment of the tidal flat profile makes the slopes steeper in the erosion part, while the slopes in the deposition part remain stable. The reclamation has stimulated a cumulative effect as the disappearance of the intertidal zone, which may lead to the destruction of biological habitats.
Deep Siamese Networks Based Change Detection with Remote Sensing Images
Authors: Yang Le , Chen Yiming , Song Shiji , Li Fan , Huang Gao
Published: September 2021

Although considerable success has been achieved in change detection on optical remote sensing images, accurate detection of specific changes is still challenging. Due to the diversity and complexity of the ground surface changes and the increasing demand for detecting changes that require high-level semantics, we have to resort to deep learning techniques to extract the intrinsic representations of changed areas. However, one key problem for developing deep learning metho for detecting specific change areas is the limitation of annotated data. In this paper, we collect a change detection dataset with 862 labeled image pairs, where the urban construction-related changes are labeled. Further, we propose a supervised change detection method based on a deep siamese semantic segmentation network to handle the proposed data effectively. The novelty of the method is that the proposed siamese network treats the change detection problem as a binary semantic segmentation task and learns to extract features from the image pairs directly. The siamese architecture as well as the elaborately designed semantic segmentation networks significantly improve the performance on change detection tasks. Experimental results demonstrate the promising performance of the proposed network compared to existing approaches.
Densely Connected Pyramidal Dilated Convolutional Network for Hyperspectral Image Classification
Authors: Zhao Feng , Zhang Junjie , Meng Zhe , Liu Hanqiang
Published: September 2021

Recently, with the extensive application of deep learning techniques in the hyperspectral image (HSI) field, particularly convolutional neural network (CNN), the research of HSI classification has stepped into a new stage. To avoid the problem that the receptive field of naive convolution is small, the dilated convolution is introduced into the field of HSI classification. However, the dilated convolution usually generates blind spots in the receptive field, resulting in discontinuous spatial information obtained. In order to solve the above problem, a densely connected pyramidal dilated convolutional network (PDCNet) is proposed in this paper. Firstly, a pyramidal dilated convolutional (PDC) layer integrates different numbers of sub-dilated convolutional layers is proposed, where the dilated factor of the sub-dilated convolution increases exponentially, achieving multi-sacle receptive fields. Secondly, the number of sub-dilated convolutional layers increases in a pyramidal pattern with the depth of the network, thereby capturing more comprehensive hyperspectral information in the receptive field. Furthermore, a feature fusion mechanism combining pixel-by-pixel addition and channel stacking is adopted to extract more abstract spectral–spatial features. Finally, in order to reuse the features of the previous layers more effectively, dense connections are applied in densely pyramidal dilated convolutional (DPDC) blocks. Experiments on three well-known HSI datasets indicate that PDCNet proposed in this paper has good classification performance compared with other popular models.
Seasonal Surface Change of Urumqi Glacier No. 1, Eastern Tien Shan, China, Revealed by Repeated High-Resolution UAV Photogrammetry
Authors: Wang Puyu , Li Hongliang , Li Zhongqin , Liu Yushuo , Xu Chunhai , Mu Jianxin , Zhang Hui
Published: September 2021

The seasonal surface changes of glaciers in Tien Shan have seen little prior investigation despite the increase in geodetic studies of multi-year changes. In this study, we analyzed the potential of an Unmanned Aerial Vehicle (UAV) to analyze seasonal surface change processes of the Urumqi Glacier No. 1 in eastern Tien Shan. We carried out UAV surveys at the beginning and the end of the ablation period in 2018. The high-precision evolution of surface elevation, geodetic mass changes, surface velocity, and terminus change in the surveyed ablation area were correspondingly derived in combination with ground measurements, including stake/snow-pit observation and GPS measurement. The derived mean elevation change in the surveyed ablation area was −1.64 m, corresponding to the geodetic mass balance of approximately −1.39 m w.e. during the ablation period in 2018. The mean surface velocity was 3.3 m/yr and characterized by the spatial change of the velocity, which was less in the East Branch than in the West Branch. The UAV survey results were a little less than those from the ground measurements, and the correlation coefficient was 0.88 for the surface elevation change and 0.87 for surface displacement. The relative error of the glacier terminus change was 4.5% for the East Branch and 6.2% for the West Branch. These results show that UAV photogrammetry is ideal for assessing seasonal glacier surface changes and has a potential application in the monitoring of detailed glacier changes.
Interactive Contribution of Indian Summer Monsoon and Western North Pacific Monsoon to Water Level and Terrestrial Water Storage in the Mekong Basin
Authors: Shi Taoran , Fok Hok Sum , Ma Zhongtian
Published: September 2021

Water level (WL) and terrestrial water storage (TWS) are two important indicators for early alerts of hydrological extremes. Their variation is governed by precipitation under monsoon variability, in particular in the Mekong river basin, where it is affected by the interaction between the Indian summer monsoon (ISM) and western North Pacific monsoon (WNPM). This study aimed to quantify the contributions of two monsoons to the water levels of four hydrological stations (i.e., My Thuan, Can Tho, Chau Doc and Tan Chau) on the Mekong Delta and the terrestrial water storage of the entire Mekong River basin through relative importance analysis. Three methods—multivariate linear regression; Lindeman, Merenda and Gold (LMG); and the proportional marginal variance decomposition (PMVD) methods—were selected to quantitatively obtain the relative influence of two monsoons on water level and TWS. The results showed that, from 2010 to 2014, the proportions of the ISM impacts on the water level obtained with the three methods ranged from 55.48 to 81.35%, 50.69 to 57.55% and 55.41 to 93.64% via multivariate linear regression, LMG and PMVD, respectively. Further analysis showed that different choices of time spans could lead to different results, indicated that the corresponding proportion would be influenced by other factors, such as El Niño–Southern Oscillation (ENSO). The removal of ENSO further enlarged the relative importance of the ISM, and the mean values of the four stations were increased by 8.78%, 2.04% and 14.92%, respectively, via multivariate linear regression, LMG and PMVD. Meanwhile, based on the analysis of terrestrial water storage, it was found that the impact of the ISM on the whole Mekong River basin was dominant: the proportions of the impact of the ISM on terrestrial water storage increased to 68.79%, 54.60% and 79.43%, which rose by 11.24%, 2.96% and 19.77%, respectively, via linear regression, LMG and PMVD. The increases almost equaled the quantified proportion for the ENSO component. Overall, the novel technique of quantifying the contributions of monsoons to WL and TWS can be applied to the influence of other atmospheric factors or events on hydrological variables in different regions.
Using Historical Archives and Landsat Imagery to Explore Changes in the Mangrove Cover of Peninsular Malaysia between 1853 and 2018
Authors: Gopalakrishnan Lavaniadevi , Satyanarayana Behara , Chen Danyang , Wolswijk Giovanna , Amir A. Aldrie , Vandegehuchte Michiel , Muslim Aidy , Koedam Nico , Dahdouh-Guebas Farid
Published: September 2021

Archive records such as maps, journals, books, sketches, cadastre and notarial documents have been underutilised in describing past and present changes in ecological systems, such as mangrove forests. Historical records can be invaluable information sources for baseline establishment, to undertake long-term study on mangrove dynamics and enhance the historical land cover and land-use dynamics of a country. In this study, we explore these untapped information reservoirs, used complementarily with remote sensing techniques, to explain the dynamics of the mangrove systems in Peninsular Malaysia. The archives in the United Kingdom, the Netherlands, Malaysia and Singapore were explored and mined for related information on the mangrove systems in Peninsular Malaysia from past centuries. Most historical records found in this study were used to validate the mangrove presence in Peninsular Malaysia since 1853 while two records from 1944 and 1954 were used to quantify the mangrove cover extent. A significant finding of this study was the oldest record found in 1853 that attested to the presence of a mangrove system on the mainland Penang of Peninsular Malaysia which was not identified again as such in records post-1853. Remote sensing data, specifically Landsat images, were used to determine the mangrove extent in Peninsular Malaysia for the years 1988, 1992, 2002, 2012 and 2018. By complementing the historical records with remote sensing information, we were able to validate the mangrove presence in Peninsular Malaysia since 1853 and determine the gain/loss of mangrove systems over the last 74 years. Peninsular Malaysia has lost over 400 km2 of mangrove forests, equivalent to 31% of its original extent between 1944 and 2018. This is a significant loss for Peninsular Malaysia which has less than 1% mangrove cover of its total land area presently.
RGB Indices and Canopy Height Modelling for Mapping Tidal Marsh Biomass from a Small Unmanned Aerial System
Authors: Morgan Grayson R. , Wang Cuizhen , Morris James T.
Published: September 2021

Coastal tidal marshes are essential ecosystems for both economic and ecological reasons. They necessitate regular monitoring as the effects of climate change begin to be manifested in changes to marsh vegetation healthiness. Small unmanned aerial systems (sUAS) build upon previously established remote sensing techniques to monitor a variety of vegetation health metrics, including biomass, with improved flexibility and affordability of data acquisition. The goal of this study was to establish the use of RGB-based vegetation indices for mapping and monitoring tidal marsh vegetation (i.e., Spartina alterniflora) biomass. Flights over tidal marsh study sites were conducted using a multi-spectral camera on a quadcopter sUAS near vegetation peak growth. A number of RGB indices were extracted to build a non-linear biomass model. A canopy height model was developed using sUAS-derived digital surface models and LiDAR-derived digital terrain models to assess its contribution to the biomass model. Results found that the distance-based RGB indices outperformed the regular radio-based indices in coastal marshes. The best-performing biomass models used the triangular greenness index (TGI; R2 = 0.39) and excess green index (ExG; R2 = 0.376). The estimated biomass revealed high biomass predictions at the fertilized marsh plots in the Long-Term Research in Environmental Biology (LTREB) project at the study site. The sUAS-extracted canopy height was not statistically significant in biomass estimation but showed similar explanatory power to other studies. Due to the lack of biomass samples in the inner estuary, the proposed biomass model in low marsh does not perform as well as the high marsh that is close to shore and accessible for biomass sampling. Further research of low marsh is required to better understand the best conditions for S. alterniflora biomass estimation using sUAS as an on-demand, personal remote sensing tool.