scholarly journals Determination of Phycocyanin from Space—A Bibliometric Analysis

2020 ◽  
Vol 12 (3) ◽  
pp. 567
Author(s):  
Igor Ogashawara
Keyword(s):  
Remote Sensing ◽  
Bibliometric Analysis ◽  
Water Quality Monitoring ◽  
Development Trend ◽  
Future Research ◽  
Observation Data ◽  
The Past ◽  
The Status ◽  
Earth Observation Data ◽  
Remote Sensing Techniques

Over the past few decades, there has been an increase in the number of studies about the estimation of phycocyanin derived from remote sensing techniques. Since phycocyanin is a unique pigment of inland water cyanobacteria, the quantification of its concentration from earth observation data is important for water quality monitoring - once some species can produce toxins. Because of the growth of this field in the past decade, several reviews and studies comparing algorithms have been published. Thus, instead of focusing on algorithms comparison or description, the goal of the present study is to systematically analyze and visualize the evolution of publications. Using the Web of Science database this study analyzed the existing publications on remote sensing of phycocyanin decade-by-decade for the period 1991–2020. The bibliometric analysis showed how research topics evolved from measuring pigments to the quantification of optical properties and from laboratory experiments to measuring entire temperate and tropical aquatic systems. This study provides the status quo and development trend of the field and points out what could be the direction for future research.

scholarly journals Bibliometric Analysis of Remote Sensing of Inland Waters Publications from 1985 to 2020

Geographies ◽  
2021 ◽  
Vol 1 (3) ◽  
pp. 346-361
Author(s):  
Igor Ogashawara
Keyword(s):  
Remote Sensing ◽  
Bibliometric Analysis ◽  
Future Research ◽  
Inland Waters ◽  
Aquatic Environments ◽  
Scientific Publications ◽  
Earth Observations ◽  
The Past ◽  
Remote Sensing Techniques ◽  
The Relationship

Over the past few decades, there has been a significant increase in the number of studies about the use of remote sensing techniques for the monitoring of inland waters. Since these aquatic environments have multiple uses for mankind, monitoring them is essential for the environment, society, and the economy. The use of Earth Observations data for the monitoring of inland waters is important for water quantity and quality management. Because of this, the goal of the present study is to systematically analyze and visualize the evolution of publications in this field. This study will not focus on algorithm comparisons or descriptions; instead, it will use a co-citation analysis to map the relationship among publications. Using the Web of Science database, publications related to the terms, “remote sensing” + “inland waters”, were analyzed using the entire database. The bibliometric analysis showed how research topics evolved from measuring optical properties and understanding their signal to the development of remote sensing algorithms and their applications to satellite imagery. This study provides the historical development of the scientific publications in this field and points out what could be the direction for future research.

scholarly journals Research on the Literature of Green Building Based on the Web of Science: A Scientometric Analysis in CiteSpace (2002–2018)

2019 ◽  
Vol 11 (13) ◽  
pp. 3716 ◽  
Author(s):  
Yingling Shi ◽  
Xinping Liu
Keyword(s):  
Web Of Science ◽  
Green Building ◽  
Development Trend ◽  
Status Quo ◽  
Future Research ◽  
Building Industry ◽  
Scientometric Analysis ◽  
The Past ◽  
Evolution Pattern ◽  
The Status

Since the 21st century, the concept of green building has been gradually popularized and implemented in more countries, which has become a popular direction in the area of sustainability in the building industry. Over the past few decades, many scholars and experts have done extensive research on green building. The purpose of this paper is to systematically analyze and visualize the status quo of green building. Therefore, based on Web of Science (WoS), this paper analyzed the existing knowledge system of green building using CiteSpace, identified keywords related to green building and their frequency of occurrence using the function of keyword co-occurrence analysis, recognized five clusters using the function of cluster analysis, and explored the knowledge evolution pattern of green building using citation bursts analysis in order to reveal how research related to green building has evolved over time. On the basis of aforementioned keywords, clusters, and citation bursts analysis, this paper has built a knowledge graph for green building. This paper can help readers to better understand the status quo and development trend of green building and to easier recognize the shortcomings in the development of green building, so as to provide a promising direction for future research.

scholarly journals Worldwide scientific productions with immunotherapy of sepsis: a bibliometric analysis

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7116 ◽  
Author(s):  
Ronghao Wan ◽  
Lei Li ◽  
Chenwei Xing ◽  
Ronggang Peng ◽  
Liang Gao
Keyword(s):  
Critical Care ◽  
Bibliometric Analysis ◽  
Development Trend ◽  
Future Research ◽  
Medical Field ◽  
The Past ◽  
The World Bank ◽  
The Us ◽  
Scopus Database ◽  
Host Inflammatory Response

Background Sepsis represents a significant healthcare problem worldwide and causes a high number of deaths every year but remains to be fully understood. During and after sepsis, the host immune response is complex and involves an initial excessive host inflammatory response to infection that is closely related to tissue damage and leads to organ failure. Over the past three decades, immunotherapy for sepsis has vastly improved, but in this area, the most influential articles, journals, authors, and countries have not yet been completely summarized and analyzed. Objective Performed a bibliometric analysis on all the articles concerning immunotherapy for sepsis from 1962 to 2019 was our objective, and we also explored the potential correlations between publications of different countries and their gross domestic product (GDP). Methods All articles about immunotherapy for sepsis were extracted from the Scopus database and analyzed. We also retrieved GDP data from all the countries that have published information from the World Bank. Results In summary, we have retrieved 1,483 related articles from the Scopus database starting from the first publication on immunotherapy for sepsis in 1962 through March 16, 2019. Over the past decade, the number of the articles published has increased year by year to reach 866 in total, which accounts for about 58% of all publications, with 2017 being the most prolific year when 179 articles were published. The US published 604 articles (41%), followed by China (n = 163, 11%), and Germany (n = 158, 11%). In terms of publishing media, the journal that published the highest number of the articles was Journal of Critical Care Medicine with 65 articles (4%), followed by Shock with 55 articles (4%), and Critical Care with 35 articles (2%). There was a strong correlation between the GDP of the different countries and their publication numbers (r = 0.811, P < 0.001). Conclusions Our present study analyzed all types of articles concerning immunotherapy for sepsis over the past 57 years and countries with high GDP tends to make more contributions to the medical field of this field. In the meantime, these studies highlight the importance of immunotherapy in the treatment of sepsis patients. The recognition of the historical status and development trend of this field can promote inter-agency cooperation, guide future research, and ultimately provide the basis for clinical practice guidelines.

scholarly journals Semantics-Driven Remote Sensing Scene Understanding Framework for Grounded Spatio-Contextual Scene Descriptions

2021 ◽  
Vol 10 (1) ◽  
pp. 32
Author(s):  
Abhishek V. Potnis ◽  
Surya S. Durbha ◽  
Rajat C. Shinde
Keyword(s):  
Remote Sensing ◽  
Domain Knowledge ◽  
Situational Awareness ◽  
Scene Understanding ◽  
Graph Representation ◽  
Observation Data ◽  
Test Scenario ◽  
Semantic Web Technologies ◽  
Earth Observation Data ◽  
Contextual Domain

Earth Observation data possess tremendous potential in understanding the dynamics of our planet. We propose the Semantics-driven Remote Sensing Scene Understanding (Sem-RSSU) framework for rendering comprehensive grounded spatio-contextual scene descriptions for enhanced situational awareness. To minimize the semantic gap for remote-sensing-scene understanding, the framework puts forward the transformation of scenes by using semantic-web technologies to Remote Sensing Scene Knowledge Graphs (RSS-KGs). The knowledge-graph representation of scenes has been formalized through the development of a Remote Sensing Scene Ontology (RSSO)—a core ontology for an inclusive remote-sensing-scene data product. The RSS-KGs are enriched both spatially and contextually, using a deductive reasoner, by mining for implicit spatio-contextual relationships between land-cover classes in the scenes. The Sem-RSSU, at its core, constitutes novel Ontology-driven Spatio-Contextual Triple Aggregation and realization algorithms to transform KGs to render grounded natural language scene descriptions. Considering the significance of scene understanding for informed decision-making from remote sensing scenes during a flood, we selected it as a test scenario, to demonstrate the utility of this framework. In that regard, a contextual domain knowledge encompassing Flood Scene Ontology (FSO) has been developed. Extensive experimental evaluations show promising results, further validating the efficacy of this framework.

scholarly journals Research Trends of Acupuncture Therapy on Cancer Over the Past Two Decades: A Bibliometric Analysis

2020 ◽  
Vol 19 ◽  
pp. 153473542095944
Author(s):  
Jing Guo ◽  
Lixia Pei ◽  
Lu Chen ◽  
Hao Chen ◽  
Dongmei Gu ◽  
...  
Keyword(s):  
Neuropathic Pain ◽  
Acupuncture Therapy ◽  
Supportive Care ◽  
Bibliometric Analysis ◽  
Integrative Medicine ◽  
Clinical Studies ◽  
Current Status ◽  
Cancer Center ◽  
Future Research ◽  
The Past

Purpose: Acupuncture has been used for managing cancer-related symptoms. However, there are still few studies concerning the overall trends in acupuncture therapy on cancer based on bibliometric analysis. This study aims to demonstrate the current status and trends in this field over the past 2 decades. Methods: Articles were retrieved from the Web of Science from 2000 to 2019. CiteSpace was used for co-authorship network of countries/institutions, dual-map analysis, and detecting the keywords with citation bursts. VOSviewer was used to construct networks based on co-authorship and co-citation analysis of authors, and co-occurrence of keywords. Results: A total of 927 articles and reviews were included in the final analysis. The number of publications has steadily increased with some fluctuations among years. The country and institution contributing most to this field are the USA and Memorial Sloan Kettering Cancer Center. Mao JJ was the most productive author and Molassiotis A ranked first in the cited authors. The co-occurrence analysis revealed 5 clusters (including “clinical trials,” “clinical studies on chemotherapy/radiation-induced symptoms,” “CAM therapy for cancer,” “clinical studies on vasomotor symptoms,” and “systematic reviews”). Most recent keyword bursts were “neuropathic pain,” “arthralgia,” “prevention,” “supportive care,” and “integrative medicine”. Conclusions: The annual publication output would increase rapidly in the next decade, which shows a promising future in this research field. Future research hotspots would focus on the role of acupuncture in neuropathic pain, arthralgia, prevention, supportive care, and integrative medicine.

scholarly journals A Review on Remote Sensing Data Fusion with Generative Adversarial Networks (GAN)

2021 ◽  
Author(s):  
Peng Liu
Keyword(s):  
Remote Sensing ◽  
Data Fusion ◽  
Remote Sensing Data ◽  
Generative Adversarial Networks ◽  
Future Research ◽  
Observation Data ◽  
Sensing Data ◽  
Advantages And Disadvantages ◽  
Adversarial Networks ◽  
Active Research

In the past decades, remote sensing (RS) data fusion has always been an active research community. A large number of algorithms and models have been developed. Generative Adversarial Networks (GAN), as an important branch of deep learning, show promising performances in variety of RS image fusions. This review provides an introduction to GAN for remote sensing data fusion. We briefly review the frequently-used architecture and characteristics of GAN in data fusion and comprehensively discuss how to use GAN to realize fusion for homogeneous RS data, heterogeneous RS data, and RS and ground observation data. We also analyzed some typical applications with GAN-based RS image fusion. This review takes insight into how to make GAN adapt to different types of fusion tasks and summarizes the advantages and disadvantages of GAN-based RS data fusion. Finally, we discuss the promising future research directions and make a prediction on its trends.

A comprehensive analysis of the 21st century's research trends in English Mobile Learning: a bibliographic review of the literature

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rouhollah Khodabandelou ◽  
Masood Fathi ◽  
Mohammad Amerian ◽  
Mohammad Reza Fakhraie
Keyword(s):  
Bibliometric Analysis ◽  
Mobile Learning ◽  
Research Trends ◽  
Current Status ◽  
Future Research ◽  
Review Of Literature ◽  
Content Type ◽  
The Past ◽  
Learning Research ◽  
Points Of View

PurposeThis study examines the importance of English Mobile Learning research as a foundation for lifelong and sustainable education from different points of view, including those of technology innovation experts, psychologists and educators. It aims to explore the current status and relevant research trends through the application of bibliometric mapping and bibliometric analysis.Design/methodology/approachFor this study, all Web of Science records (in total 5,343) from 2000 to 2020 in the field of English Mobile Learning were analyzed using the VOSviewer and CiteSpace software tools. The WoS built-in functions, including “Refine” and “Analyze,” were employed to perform the bibliometric analysis. The study further analyzed a sample of the five most-cited articles to identify the previous studies with the highest quality or impact.FindingsThe results showed that research in English Mobile Learning is growing quickly and steadily with a noticeable emphasis on various device-based technologies and applications. The study also discusses the key implications for research institutions, education policymakers and academicians, and identifies the most prominent avenues for future research on English Mobile Learning. Moreover, the results shared in this review highlight the most important and emerging areas of research in the field.Originality/valueThis article is the most recent bibliographic review of literature that particularly addresses the English Mobile Learning research during the past two decades.

scholarly journals Production Trends, Collaboration, and Main Topics of the Integrative and Complementary Oncology Research Area: A Bibliometric Analysis

2019 ◽  
Vol 18 ◽  
pp. 153473541984640 ◽  
Author(s):  
Jose A. Moral-Munoz ◽  
Lidia Carballo-Costa ◽  
Enrique Herrera-Viedma ◽  
Manuel J. Cobo
Keyword(s):  
Bibliometric Analysis ◽  
The United States ◽  
Research Area ◽  
Current Status ◽  
Future Research ◽  
Nf Kappa B ◽  
Republic Of China ◽  
The Past ◽  
Oncology Research ◽  
Complementary Oncology

Background: The prevalence of cancer has increased over time worldwide. Nevertheless, the number of deaths has been reduced during the past 2 decades. Thus, one-third of the cancer patients are users of complementary and alternative therapies, looking for other types of interventions. The main aim of the present study is to understand the current status of the research in integrative and complementary oncology. Three different aspects were analyzed: production trends, country collaboration, and leading research topics. Methods: The dataset was obtained from the documents indexed under the Integrative and Complementary Medicine category of the Web of Science database from 1976 to 2017. VOSviewer and SciMAT software were employed to perform the bibliometric analysis. Results: The Journal of Ethnopharmacology, China Medical University and the People’s Republic of China are the leading producers in the field. Regarding the collaboration, the United States and China present a close connection. The scientific community is focused on the following topics: apoptosis, breast cancer, oxidative stress, chemotherapy, and nuclear factor-Kappa-B (NF-Kappa-B). Conclusions: The present article shows potentially important information that allows understanding of the past, present, and future of research in integrative and complementary oncology. It is a useful evidence-based framework on which to base future research actions and academic directions.

scholarly journals A Review of the Sustainability Concept and the State of SDG Monitoring Using Remote Sensing

2020 ◽  
Vol 12 (11) ◽  
pp. 1770 ◽  
Author(s):  
Ronald Estoque
Keyword(s):  
Remote Sensing ◽  
Sustainable Development ◽  
Sustainable Development Goals ◽  
Global Scale ◽  
Full Potential ◽  
Observation Data ◽  
The Sustainable Development ◽  
Sustainability Concept ◽  
Development Goals ◽  
Earth Observation Data

The formulation of the 17 sustainable development goals (SDGs) was a major leap forward in humankind’s quest for a sustainable future, which likely began in the 17th century, when declining forest resources in Europe led to proposals for the re-establishment and conservation of forests, a strategy that embodies the great idea that the current generation bears responsibility for future generations. Global progress toward SDG fulfillment is monitored by 231 unique social-ecological indicators spread across 169 targets, and remote sensing (RS) provides Earth observation data, directly or indirectly, for 30 (18%) of these indicators. Unfortunately, the UN Global Sustainable Development Report 2019—The Future is Now: Science for Achieving Sustainable Development concluded that, despite initial efforts, the world is not yet on track for achieving most of the SDG targets. Meanwhile, through the EO4SDG initiative by the Group on Earth Observations, the full potential of RS for SDG monitoring is now being explored at a global scale. As of April 2020, preliminary statistical data were available for 21 (70%) of the 30 RS-based SDG indicators, according to the Global SDG Indicators Database. Ten (33%) of the RS-based SDG indicators have also been included in the SDG Index and Dashboards found in the Sustainable Development Report 2019—Transformations to Achieve the Sustainable Development Goals. These statistics, however, do not necessarily reflect the actual status and availability of raw and processed geospatial data for the RS-based indicators, which remains an important issue. Nevertheless, various initiatives have been started to address the need for open access data. RS data can also help in the development of other potentially relevant complementary indicators or sub-indicators. By doing so, they can help meet one of the current challenges of SDG monitoring, which is how best to operationalize the SDG indicators.

scholarly journals Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces

2020 ◽  
Vol 12 (22) ◽  
pp. 3690 ◽  
Author(s):  
Angela Lausch ◽  
Michael E. Schaepman ◽  
Andrew K. Skidmore ◽  
Sina C. Truckenbrodt ◽  
Jörg M. Hacker ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Science ◽  
Cost Effective ◽  
Trait Variation ◽  
The Past ◽  
Objective Monitoring ◽  
The Status ◽  
Close Range ◽  
Hyperspectral Sensor

The status, changes, and disturbances in geomorphological regimes can be regarded as controlling and regulating factors for biodiversity. Therefore, monitoring geomorphology at local, regional, and global scales is not only necessary to conserve geodiversity, but also to preserve biodiversity, as well as to improve biodiversity conservation and ecosystem management. Numerous remote sensing (RS) approaches and platforms have been used in the past to enable a cost-effective, increasingly freely available, comprehensive, repetitive, standardized, and objective monitoring of geomorphological characteristics and their traits. This contribution provides a state-of-the-art review for the RS-based monitoring of these characteristics and traits, by presenting examples of aeolian, fluvial, and coastal landforms. Different examples for monitoring geomorphology as a crucial discipline of geodiversity using RS are provided, discussing the implementation of RS technologies such as LiDAR, RADAR, as well as multi-spectral and hyperspectral sensor technologies. Furthermore, data products and RS technologies that could be used in the future for monitoring geomorphology are introduced. The use of spectral traits (ST) and spectral trait variation (STV) approaches with RS enable the status, changes, and disturbances of geomorphic diversity to be monitored. We focus on the requirements for future geomorphology monitoring specifically aimed at overcoming some key limitations of ecological modeling, namely: the implementation and linking of in-situ, close-range, air- and spaceborne RS technologies, geomorphic traits, and data science approaches as crucial components for a better understanding of the geomorphic impacts on complex ecosystems. This paper aims to impart multidimensional geomorphic information obtained by RS for improved utilization in biodiversity monitoring.

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