scholarly journals A Bibliometric Profile of the Remote Sensing Open Access Journal Published by MDPI between 2009 and 2018

2019 ◽  
Vol 11 (1) ◽  
pp. 91 ◽  
Author(s):  
YuYing Zhang ◽  
Prasad S. Thenkabail ◽  
Peng Wang
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Citation Impact ◽  
Open Access Journal ◽  
Intellectual Structure ◽  
H Index ◽  
Chinese Academy Of Sciences ◽  
Author Keywords ◽  
Academy Of Sciences ◽  
Journal Impact

Remote Sensing Open Access Journal (RS OAJ) is an international leading journal in the field of remote sensing science and technology. It was first published in the year 2009 and is currently celebrating tenth year of publications. In this research, a bibliometric analysis of RS OAJ was conducted based on 5588 articles published during the 10-year (2009–2018) time-period. The bibliometric analysis includes a comprehensive set of indicators such as dynamics and trends of publications, journal impact factor, total cites, eigenfactor score, normalized eigenfactor, CiteScore, h-index, h-classic publications, most productive countries (or territories) and institutions, co-authorship collaboration about countries (territories), research themes, citation impact of co-occurrences keywords, intellectual structure, and knowledge commutation. We found that publications of RS OAJ presented an exponential growth in the past ten years. From 2010 to 2017 (for which complete years data were available), the h-index of RS OAJ is 67. From 2009–2018, RS OAJ includes publications from 129 countries (or territories) and 3826 institutions. The leading nations contributing articles, based on 2009–2018 data, and listed based on ranking were: China, United States, Germany, Italy, France, Spain, Canada, England, Australia, Netherlands, Japan, Switzerland and Austria. The leading institutions, also for the same period and listed based on ranking were: Chinese Academy of Sciences, Wuhan University, University of Chinese Academy of Sciences, Beijing Normal University, The university of Maryland, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, China University of Geosciences, United States Geological Survey, German Aerospace Centre, University of Twente, and California Institute of Technology. For the year 2017, RS OAJ had an impressive journal impact factor of 3.4060, a CiteScore of 4.03, eigenfactor score of 0.0342, and normalized eigenfactor score of 3.99. In addition, based on 2009–2018, data co-word analysis determined that “remote sensing”, “MODIS”, “Landsat”, “LiDAR” and “NDVI” are the high-frequency of author keywords co-occurrence in RS OAJ. The main themes of RS OAJ are multi-spectral and hyperspectral remote sensing, LiDAR scanning and forestry remote sensing monitoring, MODIS and LAI data applications, Remote sensing applications and Synthetic Aperture Radar (SAR). Through author keywords citation impact analysis, we find the most influential keyword is Unmanned Aerial Vehicle (UAV), followed, forestry, Normalized Difference Vegetation Index (NDVI), terrestrial laser scanning, airborne laser scanning, forestry inventory, urban heat island, monitoring, agriculture, and laser scanning. By analyzing the intellectual structure of RS OAJ, we identify the main reference publications and find that the themes are about Random Forests, MODIS vegetation indices and image analysis, etc. RS OAJ ranks first in cited journals and third in citing, this indicates that RS OAJ has the internal knowledge flow. Our results will bring more benefits to scholars, researchers and graduate students, who hopes to get a quick overview of the RS OAJ. And this article will also be the starting point for communication between scholars and practitioners. Finally, this paper proposed a nuanced h-index (nh-index) to measure productivity and intellectual contribution of authors by considering h-index based on whether the one is first, second, third, or nth author. This nuanced approach to determining h-index of authors is powerful indicator of an academician’s productivity and intellectual contribution.

scholarly journals Análisis bibliométrico mundial de la categoría 'remote sensing' de la web of science (1997-2012)

2014 ◽  
Vol 20 (4) ◽  
pp. 855-878 ◽  
Author(s):  
José Ignacio Rojas-Sola ◽  
Ángel Inocencio Aguilera-García
Keyword(s):  
Remote Sensing ◽  
Web Of Science ◽  
H Index ◽  
Chinese Academy Of Sciences ◽  
Academy Of Sciences

El objetivo principal del trabajo ha sido analizar la evolución de la investigación en la categoría 'Remote Sensing', revisándose en la Web of Science, las revistas que se encuentran en dicha categoría, y analizándose bibliométricamente las publicaciones de dichas revistas para la serie temporal 1997-2012. Para ello, se han analizado para los diferentes países y centros de investigación, diversos indicadores bibliométricos como el número de documentos, y mostrándose por documento, la productividad, el número medio de citas, de autores, de centros de investigación, la colaboración nacional e internacional incluidas sus redes, el factor de impacto ponderado y relativo, así como el h-index. Asimismo, se ha analizado la difusión internacional de las investigaciones de los países a través de las revistas y la relación con el factor de impacto, para detectar las revistas de publicación de cada país. Por otro lado, se muestra cómo el inglés es el lenguaje de publicación por excelencia, consolidándose USA como el país más productivo aunque con un factor de impacto relativo bajo. También se muestra cómo la Chinese Academy of Sciences junto a la National Aeronautics and Space Administration (NASA) son las instituciones más productivas y el gran crecimiento de publicaciones de algunas universidades chinas.

​Bibliometric Analysis of the Research Characteristics and Trends in Legume Mycorrhiza Field

2021 ◽  
Author(s):  
S.X. Xu
Keyword(s):  
Mycorrhizal Fungi ◽  
Web Of Science ◽  
Wide Distribution ◽  
Intellectual Structure ◽  
N Fixation ◽  
Field Methods ◽  
Bibliometric Method ◽  
Chinese Academy Of Sciences ◽  
Resistance To Stress ◽  
Academy Of Sciences

Background: Legumes are notable for wide distribution and indispensable food function. Majority of legume species are known to form mycorrhizal symbioses. The visualized and quantitative analysis legume mycorrhiza research has been reported although much attention has been paid in this field. Methods: This study reviewed and analyzed systematically the research characteristics and trends in legume mycorrhiza by bibliometric method based on the citation data collected from the Web of Science Core Collection by CiteSpace software. Result: The publication concerning legume mycorrhiza research increases rapidly and is still a hotspot. The most active collaboration countries are USA, France, Germany, China and Australia, whereas the two institutions of University of Western Australia and Chinese Academy of Sciences collaborate most with others. The intellectual structure analysis showed that the main intellectual base is nitrogen-fixing of cereal. The top ranked of keyword by bursts was rhizobia with strength value of 5.2899, which began from 2016 and ended in 2018. The distinction of 24 bursting keywords is relatively small, which showed that the research hotpot and trend should be interaction between legume plants and mycorrhizal fungi for improving nutrition absorption, N-fixation, resistance to stress and their mechanisms in future.

scholarly journals Text Mining in Management Research: A Bibliometric Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Guandong Song ◽  
Jiying Wu ◽  
Sihui Wang
Keyword(s):  
Performance Analysis ◽  
Text Mining ◽  
Bibliometric Analysis ◽  
The United States ◽  
Intellectual Structure ◽  
Science Mapping ◽  
Scientific Publications ◽  
H Index ◽  
Research Themes ◽  
Author Keywords

The goal of this paper is to provide a bibliometric analysis of scientific publications that employ text mining in management. To accomplish this, the authors collected 1282 documents from the Web of Science and performed performance analysis and science mapping with the help of the Bibliometrix package in Rstudio. The performance analysis used a range of bibliometric indicators such as productivity, citations, h-index, and m-quotient, in order to identify research trends and the most influential journals, authors, countries, and literature in the study. Science mapping used author keywords co-occurrence, co-authorship, and co-citation analysis to reflect the conceptual, social, and intellectual structure of the research. Specifically, we have seen an exponential increase in the use of text mining in management in recent years. The United States is the dominant country for research, having the earliest studies and the highest number of literature and citations. Furthermore, the research themes showed that topic modeling is at the forefront of current text mining research about management. This study will help scholars and management practitioners interested in the intersection of text mining and management to quickly understand the latest advances in research.

scholarly journals Remote Sensing Applications in Monitoring of Protected Areas: A Bibliometric Analysis

2020 ◽  
Vol 12 (5) ◽  
pp. 772 ◽  
Author(s):  
Peili Duan ◽  
Yeqiao Wang ◽  
Peng Yin
Keyword(s):  
Remote Sensing ◽  
Protected Areas ◽  
Intellectual Structure ◽  
Future Research ◽  
Scientific Publications ◽  
Sensing Applications ◽  
Sensing Platforms ◽  
Academic Publications ◽  
Author Keywords ◽  
Area Monitoring

The development of remote sensing platforms and sensors and improvement in science and technology provide crucial support for the monitoring and management of protected areas. This paper presents an analysis of research publications, from a bibliometric perspective, on the remote sensing of protected areas. This analysis is focused on the period from 1991 to 2018. For data, a total of 4546 academic publications were retrieved from the Web of Science database. The VOSviewer software was adopted to evaluate the co-authorships among countries and institutions, as well as the co-occurrences of author keywords. The results indicate an increasing trend of annual publications in the remote sensing of protected areas. This analysis reveals the major topical subjects, leading countries, and most influential institutions around the world that have conducted relevant research in scientific publications; this study also reveals the journals that include the most publications, and the collaborative patterns related to the remote sensing of protected areas. Landsat, MODIS, and LiDAR are among the most commonly used satellites and sensors. Research topics related to protected area monitoring are mainly concentrated on change detection, biodiversity conservation, and climate change impact. This analysis can help researchers and scholars better understand the intellectual structure of the field and identify the future research directions.

The integrated interventional radiology match: a bibliometric analysis of matched first-year residents

2019 ◽  
Vol 3 ◽  
pp. 13 ◽  
Author(s):  
Vishnu Chandra ◽  
Neil Jain ◽  
Pratik Shukla ◽  
Ethan Wajswol ◽  
Sohail Contractor ◽  
...  
Keyword(s):  
Interventional Radiology ◽  
Bibliometric Analysis ◽  
Statistical Significance ◽  
Univariate Analysis ◽  
Impact Factors ◽  
Index Number ◽  
Research Information ◽  
H Index ◽  
Scopus Database ◽  
Journal Impact

Objectives: The integrated interventional radiology (IR) residency has only been established relatively recently as compared to other specialties. Although some preliminary information is available based on survey data five, no comprehensive bibliometric analysis documenting the importance of the quantity and quality of research in applying to an integrated-IR program currently exists. As the first bibliometric analysis of matched IR residents, the data obtained from this study fills a gap in the literature. Materials and Methods: A list of matched residents from the 2018 integrated-IR match were identified by contacting program directors. The Scopus database was used to search for resident research information, including total publications, first-author publications, radiology-related publications, and h-indices. Each matriculating program was categorized into one of five tiers based on the average faculty Hirsch index (h-index). Results: Sixty-three programs and 117 matched residents were identified and reviewed on the Scopus database. For the 2018 cycle, 274 total publications were produced by matched applicants, with a mean of 2.34 ± 0.41 publication per matched applicant. The average h-index for matched applicants was 0.96 ± 0.13. On univariate analysis, the number of radiology-related publications, highest journal impact factor, and h-index were all associated with an increased likelihood of matching into a higher tier program (P < 0.05). Other research variables displayed no statistical significance. All applicants with PhDs matched into tier one programs. Conclusions: Research serves as an important element in successfully matching into an integrated-IR residency. h-index, number of radiology-related manuscripts, and highest journal impact factors are all positively associated with matching into a higher tier program.

scholarly journals Archaeological Surveying of Subarctic and Arctic Landscapes: Comparing the Performance of Airborne Laser Scanning and Remote Sensing Image Data

2021 ◽  
Vol 13 (4) ◽  
pp. 1917
Author(s):  
Alma Elizabeth Thuestad ◽  
Ole Risbøl ◽  
Jan Ingolf Kleppe ◽  
Stine Barlindhaug ◽  
Elin Rose Myrvoll
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
Image Data ◽  
Remote Sensing Image ◽  
Airborne Laser Scanning ◽  
Aerial Images ◽  
Detection Rates ◽  
Airborne Laser ◽  
Pros And Cons

What can remote sensing contribute to archaeological surveying in subarctic and arctic landscapes? The pros and cons of remote sensing data vary as do areas of utilization and methodological approaches. We assessed the applicability of remote sensing for archaeological surveying of northern landscapes using airborne laser scanning (LiDAR) and satellite and aerial images to map archaeological features as a basis for (a) assessing the pros and cons of the different approaches and (b) assessing the potential detection rate of remote sensing. Interpretation of images and a LiDAR-based bare-earth digital terrain model (DTM) was based on visual analyses aided by processing and visualizing techniques. 368 features were identified in the aerial images, 437 in the satellite images and 1186 in the DTM. LiDAR yielded the better result, especially for hunting pits. Image data proved suitable for dwellings and settlement sites. Feature characteristics proved a key factor for detectability, both in LiDAR and image data. This study has shown that LiDAR and remote sensing image data are highly applicable for archaeological surveying in northern landscapes. It showed that a multi-sensor approach contributes to high detection rates. Our results have improved the inventory of archaeological sites in a non-destructive and minimally invasive manner.

scholarly journals Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas

2021 ◽  
Vol 13 (3) ◽  
pp. 507
Author(s):  
Tasiyiwa Priscilla Muumbe ◽  
Jussi Baade ◽  
Jenia Singh ◽  
Christiane Schmullius ◽  
Christian Thau
Keyword(s):  
Remote Sensing ◽  
Vegetation Structure ◽  
Laser Scanning ◽  
Spatial Scales ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Parameter Extraction ◽  
Airborne Lidar ◽  
Special Focus ◽  
Vegetation Parameter

Savannas are heterogeneous ecosystems, composed of varied spatial combinations and proportions of woody and herbaceous vegetation. Most field-based inventory and remote sensing methods fail to account for the lower stratum vegetation (i.e., shrubs and grasses), and are thus underrepresenting the carbon storage potential of savanna ecosystems. For detailed analyses at the local scale, Terrestrial Laser Scanning (TLS) has proven to be a promising remote sensing technology over the past decade. Accordingly, several review articles already exist on the use of TLS for characterizing 3D vegetation structure. However, a gap exists on the spatial concentrations of TLS studies according to biome for accurate vegetation structure estimation. A comprehensive review was conducted through a meta-analysis of 113 relevant research articles using 18 attributes. The review covered a range of aspects, including the global distribution of TLS studies, parameters retrieved from TLS point clouds and retrieval methods. The review also examined the relationship between the TLS retrieval method and the overall accuracy in parameter extraction. To date, TLS has mainly been used to characterize vegetation in temperate, boreal/taiga and tropical forests, with only little emphasis on savannas. TLS studies in the savanna focused on the extraction of very few vegetation parameters (e.g., DBH and height) and did not consider the shrub contribution to the overall Above Ground Biomass (AGB). Future work should therefore focus on developing new and adjusting existing algorithms for vegetation parameter extraction in the savanna biome, improving predictive AGB models through 3D reconstructions of savanna trees and shrubs as well as quantifying AGB change through the application of multi-temporal TLS. The integration of data from various sources and platforms e.g., TLS with airborne LiDAR is recommended for improved vegetation parameter extraction (including AGB) at larger spatial scales. The review highlights the huge potential of TLS for accurate savanna vegetation extraction by discussing TLS opportunities, challenges and potential future research in the savanna biome.

scholarly journals Preface to the Interfacial Science Developments at the Chinese Academy of Sciences Virtual Special Issue

Langmuir ◽  
2020 ◽  
Vol 36 (41) ◽  
pp. 12087-12087 ◽  
Author(s):  
Yilin Wang ◽  
Shaoyi Jiang ◽  
Zhan Chen ◽  
Shu-Hong Yu ◽  
Gilbert Walker
Keyword(s):  
Special Issue ◽  
Interfacial Science ◽  
Chinese Academy Of Sciences ◽  
Academy Of Sciences
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