Análisis Bibliométrico Acerca del Uso de Drones para Análisis y Detección de Inundaciones

Este análisis bibliométrico explora la literatura científica existente sobre el uso de drones en la predicción de inundaciones. El estudio tiene como objetivo proporcionar una visión general de la cantidad de publicaciones científicas, las tendencias temporales de investigación y los actores clave e...

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Autores:: Cardenas Rodriguez, Arley Giovanni

Tipo de recurso:: Trabajo de grado de pregrado

Fecha de publicación:: 2023

Institución:: Universidad Santo Tomás

Repositorio:: Repositorio Institucional USTA

Idioma:: spa

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dc.title.spa.fl_str_mv	Análisis Bibliométrico Acerca del Uso de Drones para Análisis y Detección de Inundaciones
title	Análisis Bibliométrico Acerca del Uso de Drones para Análisis y Detección de Inundaciones
spellingShingle	Análisis Bibliométrico Acerca del Uso de Drones para Análisis y Detección de Inundaciones bibliometric analysis drones unmanned aerial vehicle (UAV) floods floods prevention floods management Ingeniería Ambiental Literatura Científica Publicaciones Científicas Drones análisis bibliométrico drones; vehículo aéreo no tripulado (UAV) inundaciones prevención de inundaciones manejo de inundaciones
title_short	Análisis Bibliométrico Acerca del Uso de Drones para Análisis y Detección de Inundaciones
title_full	Análisis Bibliométrico Acerca del Uso de Drones para Análisis y Detección de Inundaciones
title_fullStr	Análisis Bibliométrico Acerca del Uso de Drones para Análisis y Detección de Inundaciones
title_full_unstemmed	Análisis Bibliométrico Acerca del Uso de Drones para Análisis y Detección de Inundaciones
title_sort	Análisis Bibliométrico Acerca del Uso de Drones para Análisis y Detección de Inundaciones
dc.creator.fl_str_mv	Cardenas Rodriguez, Arley Giovanni
dc.contributor.advisor.none.fl_str_mv	Sierra Parada, Ronal Jackson
dc.contributor.author.none.fl_str_mv	Cardenas Rodriguez, Arley Giovanni
dc.contributor.orcid.spa.fl_str_mv	https://orcid.org/0000-0002-9206-5682
dc.contributor.googlescholar.spa.fl_str_mv	https://scholar.google.com/citations?hl=es&user=0793qhcwBoMC
dc.contributor.cvlac.spa.fl_str_mv	https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001431760
dc.subject.keyword.spa.fl_str_mv	bibliometric analysis drones unmanned aerial vehicle (UAV) floods floods prevention floods management
topic	bibliometric analysis drones unmanned aerial vehicle (UAV) floods floods prevention floods management Ingeniería Ambiental Literatura Científica Publicaciones Científicas Drones análisis bibliométrico drones; vehículo aéreo no tripulado (UAV) inundaciones prevención de inundaciones manejo de inundaciones
dc.subject.lemb.spa.fl_str_mv	Ingeniería Ambiental Literatura Científica Publicaciones Científicas Drones
dc.subject.proposal.spa.fl_str_mv	análisis bibliométrico drones; vehículo aéreo no tripulado (UAV) inundaciones prevención de inundaciones manejo de inundaciones
description	Este análisis bibliométrico explora la literatura científica existente sobre el uso de drones en la predicción de inundaciones. El estudio tiene como objetivo proporcionar una visión general de la cantidad de publicaciones científicas, las tendencias temporales de investigación y los actores clave en este campo. También examina las áreas temáticas comunes y los enfoques metodológicos utilizados en los estudios identificados. El análisis se realizó utilizando dos bases de datos académicas de renombre, ScienceDirect y Scopus. Los resultados revelan un interés creciente en el uso de drones para la prevención y gestión de inundaciones, con un aumento constante en el número de publicaciones a lo largo de los años. Se identifican autores e instituciones destacados que contribuyen a la investigación, destacando sus áreas de especialización. El análisis también revela la naturaleza multidisciplinaria de la investigación, siendo la informática, la ingeniería y las ciencias terrestres y planetarias las áreas de estudio más destacadas. Además, el estudio examina la distribución geográfica de la investigación, con China a la cabeza en cuanto al número de publicaciones. Los hallazgos subrayan la participación y colaboración global en el uso de drones para la prevención y gestión de inundaciones. El análisis de los tipos de documentos revela que los artículos y las ponencias de congresos son los principales medios para compartir conocimientos en este campo. Además, el estudio identifica a los principales patrocinadores involucrados, lo que indica un importante apoyo financiero de diversas fuentes en todo el mundo. En general, este análisis bibliométrico proporciona información valiosa sobre el estado actual de la investigación sobre el uso de drones en la predicción y manejo de inundaciones, identificando lagunas de conocimiento y áreas que requieren mayor atención. Los resultados pueden guiar a los investigadores, profesionales y tomadores de decisiones a centrar sus esfuerzos en vías de investigación prometedoras y estrategias de mitigación y predicción de inundaciones más efectivas.
publishDate	2023
dc.date.accessioned.none.fl_str_mv	2023-10-03T13:17:20Z
dc.date.available.none.fl_str_mv	2023-10-03T13:17:20Z
dc.date.issued.none.fl_str_mv	2023-09-29
dc.type.local.spa.fl_str_mv	Trabajo de Grado
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dc.identifier.citation.spa.fl_str_mv	Cárdenas Rodríguez, A, G. (2023). Análisis bibliométrico acerca del uso de drones para análisis y detección de inundaciones. [Trabajo de Grado, Universidad Santo Tomás]. Repositorio Institucional.
dc.identifier.uri.none.fl_str_mv	http://hdl.handle.net/11634/52559
dc.identifier.reponame.spa.fl_str_mv	reponame:Repositorio Institucional Universidad Santo Tomás
dc.identifier.instname.spa.fl_str_mv	instname:Universidad Santo Tomás
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identifier_str_mv	Cárdenas Rodríguez, A, G. (2023). Análisis bibliométrico acerca del uso de drones para análisis y detección de inundaciones. [Trabajo de Grado, Universidad Santo Tomás]. Repositorio Institucional. reponame:Repositorio Institucional Universidad Santo Tomás instname:Universidad Santo Tomás repourl:https://repository.usta.edu.co
url	http://hdl.handle.net/11634/52559
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dc.relation.references.spa.fl_str_mv	Albort-Morant, G., & Ribeiro-Soriano, D. (2016). A bibliometric analysis of international impact of business incubators. Journal of Business Research, 69(5), 1775–1779. https://doi.org/10.1016/j.jbusres.2015.10.054 A-m, T. (2021). INTELLIGENT MONITORING OF DISEASED PLANTS USING DRONES. En Cadastre Series) (Vol. 51). Apriliyanti, I. D., & Alon, I. (2017). Bibliometric analysis of absorptive capacity. International Business Review, 26(5), 896–907. https://doi.org/10.1016/j.ibusrev.2017.02.007 Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/J.JOI.2017.08.007 Arshad, B., Ogie, R., Barthelemy, J., Pradhan, B., Verstaevel, N., & Perez, P. (2019). Computer vision and iot-based sensors in flood monitoring and mapping: A systematic review. Sensors (Switzerland), 19(22). https://doi.org/10.3390/s19225012 Baas, J., Schotten, M., Plume, A., Côté, G., & Karimi, R. (2020). Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies. Quantitative Science Studies, 1(1), 377–386. https://doi.org/10.1162/QSS_A_00019 Batra, S., Saini, M., & Yadav, M. (2023). Mapping the intellectual structure of corporate governance and ownership structure: a bibliometric analysis. International Journal of Law and Management, 65(4), 333–353. https://doi.org/10.1108/IJLMA-01-2023-0001 Burnham, J. F. (2006). Scopus database: A review. Biomedical Digital Libraries, 3. https://doi.org/10.1186/1742-5581-3-1 Bushnaq, O. M., Mishra, D., Natalizio, E., & Akyildiz, I. F. (2022). Unmanned aerial vehicles (UAVs) for disaster management. Nanotechnology-Based Smart Remote Sensing Networks for Disaster Prevention, 159–188. https://doi.org/10.1016/B978-0-323-91166-5.00013-6 Castillo-Vergara, M., Alvarez-Marin, A., & Placencio-Hidalgo, D. (2018). A bibliometric analysis of creativity in the field of business economics. Journal of Business Research, 85, 1–9. https://doi.org/10.1016/j.jbusres.2017.12.011 Danvila Del Valle, I., & Sastre Castillo, M. A. (2009). Human capital and sustainable competitive advantage: An analysis of the relationship between training and performance. International Entrepreneurship and Management Journal, 5(2), 139–163. https://doi.org/10.1007/S11365-008-0090-3 Delery, J. E., & Doty, D. H. (1996). Modes of theorizing in strategic human resource management: Tests of universalistic, contingency, and configurational performance predictions. Academy of Management Journal, 39(4), 802–835. https://doi.org/10.2307/256713 Donthu, N., Kumar, S., Pandey, N., & Gupta, P. (2021). Forty years of the International Journal of Information Management: A bibliometric analysis. International Journal of Information Management, 57. https://doi.org/10.1016/j.ijinfomgt.2020.102307 Dwivedi, R., Nerur, S., & Balijepally, V. (2023). Exploring artificial intelligence and big data scholarship in information systems: A citation, bibliographic coupling, and co-word analysis. International Journal of Information Management Data Insights, 3(2). https://doi.org/10.1016/j.jjimei.2023.100185 Dzikowski, P. (2018). A bibliometric analysis of born global firms. Journal of Business Research, 85, 281–294. https://doi.org/10.1016/j.jbusres.2017.12.054 Etemad, H., & Lee, Y. (2003). The Knowledge Network of International Entrepreneurship: Theory and Evidence. Small Business Economics, 20(1), 5–23. https://doi.org/10.1023/A:1020240303332 Gagolewski, M. (2011). Bibliometric impact assessment with R and the CITAN package. Journal of Informetrics, 5(4), 678–692. https://doi.org/10.1016/j.joi.2011.06.006 Garrigos-Simon, F. J., Narangajavana-Kaosiri, Y., & Lengua-Lengua, I. (2018). Tourism and sustainability: A bibliometric and visualization analysis. Sustainability (Switzerland), 10(6). https://doi.org/10.3390/su10061976 Giannitsopoulos, M. L., Leinster, P., Butler, D., Smith, M., & Casado, M. R. (2022a). Towards the coordinated and fit-for-purpose deployment of Unmanned Aerial Systems (UASs) for flood risk management in England. Aqua Water Infrastructure, Ecosystems and Society, 71(8), 879–895. https://doi.org/10.2166/aqua.2022.101 Giannitsopoulos, M. L., Leinster, P., Butler, D., Smith, M., & Casado, M. R. (2022b). Towards the coordinated and fit-for-purpose deployment of Unmanned Aerial Systems (UASs) for flood risk management in England. Aqua Water Infrastructure, Ecosystems and Society, 71(8), 879–895. https://doi.org/10.2166/aqua.2022.101 Goerlandt, F., Li, J., & Reniers, G. (2020). The landscape of risk communication research: A scientometric analysis. International Journal of Environmental Research and Public Health, 17(9). https://doi.org/10.3390/ijerph17093255 González-Alcaide, G. (2021). Bibliometric studies outside the information science and library science field: uncontainable or uncontrollable? Scientometrics, 126(8), 6837–6870. https://doi.org/10.1007/S11192-021-04061-3 Guler, A. T., Waaijer, C. J. F., & Palmblad, M. (2016). Scientific workflows for bibliometrics. Scientometrics, 107(2), 385–398. https://doi.org/10.1007/S11192-016-1885-6 Haak, L. L., Fenner, M., Paglione, L., Pentz, E., & Ratner, H. (2012). ORCID: A system to uniquely identify researchers. Learned Publishing, 25(4), 259–264. https://doi.org/10.1087/20120404 Hooker, H., Dance, S. L., Mason, D. C., Bevington, J., & Shelton, K. (2022). Spatial scale evaluation of forecast flood inundation maps. Journal of Hydrology, 612, 128170. https://doi.org/10.1016/J.JHYDROL.2022.128170 IEEE Xplore. Version 1.3. (2002). Online Information Review, 26(4), 285. https://doi.org/10.1108/OIR.2002.26.4.285.12 Iqbal, U., Perez, P., Li, W., & Barthelemy, J. (2021). How computer vision can facilitate flood management: A systematic review. En International Journal of Disaster Risk Reduction (Vol. 53). Elsevier Ltd. https://doi.org/10.1016/j.ijdrr.2020.102030 Iqbal, U., Riaz, M. Z. Bin, Barthelemy, J., Hutchison, N., & Perez, P. (2022). Floodborne Objects Type Recognition Using Computer Vision to Mitigate Blockage Originated Floods. Water (Switzerland), 14(17). https://doi.org/10.3390/w14172605 Islam, M. A., Rashid, S. I., Hossain, N. U. I., Fleming, R., & Sokolov, A. (2023). An integrated convolutional neural network and sorting algorithm for image classification for efficient flood disaster management. Decision Analytics Journal, 7. https://doi.org/10.1016/j.dajour.2023.100225 Ivanova, S., Prosekov, A., & Kaledin, A. (2022). A Survey on Monitoring of Wild Animals during Fires Using Drones. 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AGILITY IN MARKETING: A BIBLIOMETRIC ANALYSIS. Business: Theory and Practice, 24(1), 173–182. https://doi.org/10.3846/BTP.2023.17090 Velez-Estevez, A., Perez, I. J., García-Sánchez, P., Moral-Munoz, J. A., & Cobo, M. J. (2023). Current trends in bibliometric APIs: A comparative analysis. Information Processing & Management, 60(4), 103385. https://doi.org/10.1016/J.IPM.2023.103385 Verma, K., & Malhotra, K. (2023). A bibliometric analysis of sport utility vehicle segment in the automobile industry: two decades study based on web of science database. International Journal of Business and Emerging Markets, 15(2), 135–156. https://doi.org/10.1504/IJBEM.2023.130476 Waltman, L. (2016). A review of the literature on citation impact indicators. Journal of Informetrics, 10(2), 365–391. https://doi.org/10.1016/j.joi.2016.02.007 Wei, W., & Jiang, Z. (2023). A bibliometrix-based visualization analysis of international studies on conversations of people with aphasia: Present and prospects. Heliyon, 9(6). https://doi.org/10.1016/j.heliyon.2023.e16839 White, H. D., & Griffith, B. C. (1981). Author cocitation: A literature measure of intellectual structure. Journal of the American Society for Information Science, 32(3), 163–171. https://doi.org/10.1002/ASI.4630320302 World Wildlife Fund, & Agencia de los Estados Unidos para el Desarrollo Internacional. (2018). GUÍA VERDE PARA INUNDACIONES. https://wwflac.awsassets.panda.org/downloads/flood_green_guide_espanol_revisado_armado.pdf Zupic, I., & Čater, T. (2015). Bibliometric Methods in Management and Organization. Organizational Research Methods, 18(3), 429–472. https://doi.org/10.1177/1094428114562629
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spelling	Sierra Parada, Ronal JacksonCardenas Rodriguez, Arley Giovannihttps://orcid.org/0000-0002-9206-5682https://scholar.google.com/citations?hl=es&user=0793qhcwBoMChttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=00014317602023-10-03T13:17:20Z2023-10-03T13:17:20Z2023-09-29Cárdenas Rodríguez, A, G. (2023). Análisis bibliométrico acerca del uso de drones para análisis y detección de inundaciones. [Trabajo de Grado, Universidad Santo Tomás]. Repositorio Institucional.http://hdl.handle.net/11634/52559reponame:Repositorio Institucional Universidad Santo Tomásinstname:Universidad Santo Tomásrepourl:https://repository.usta.edu.coEste análisis bibliométrico explora la literatura científica existente sobre el uso de drones en la predicción de inundaciones. El estudio tiene como objetivo proporcionar una visión general de la cantidad de publicaciones científicas, las tendencias temporales de investigación y los actores clave en este campo. También examina las áreas temáticas comunes y los enfoques metodológicos utilizados en los estudios identificados. El análisis se realizó utilizando dos bases de datos académicas de renombre, ScienceDirect y Scopus. Los resultados revelan un interés creciente en el uso de drones para la prevención y gestión de inundaciones, con un aumento constante en el número de publicaciones a lo largo de los años. Se identifican autores e instituciones destacados que contribuyen a la investigación, destacando sus áreas de especialización. El análisis también revela la naturaleza multidisciplinaria de la investigación, siendo la informática, la ingeniería y las ciencias terrestres y planetarias las áreas de estudio más destacadas. Además, el estudio examina la distribución geográfica de la investigación, con China a la cabeza en cuanto al número de publicaciones. Los hallazgos subrayan la participación y colaboración global en el uso de drones para la prevención y gestión de inundaciones. El análisis de los tipos de documentos revela que los artículos y las ponencias de congresos son los principales medios para compartir conocimientos en este campo. Además, el estudio identifica a los principales patrocinadores involucrados, lo que indica un importante apoyo financiero de diversas fuentes en todo el mundo. En general, este análisis bibliométrico proporciona información valiosa sobre el estado actual de la investigación sobre el uso de drones en la predicción y manejo de inundaciones, identificando lagunas de conocimiento y áreas que requieren mayor atención. Los resultados pueden guiar a los investigadores, profesionales y tomadores de decisiones a centrar sus esfuerzos en vías de investigación prometedoras y estrategias de mitigación y predicción de inundaciones más efectivas.This bibliometric analysis explores the existing scientific literature on the use of drones in flood prediction. The study aims to provide an overview of the quantity of scientific publications, temporal research trends, and key players in this field. It also examines the common thematic areas and methodological approaches used in the identified studies. The analysis was conducted using two renowned academic databases, ScienceDirect and Scopus. The results reveal a growing interest in the use of drones for flood prevention and management, with a steady increase in the number of publications over the years. Prominent authors and institutions contributing to the research are identified, highlighting their areas of expertise. The analysis also uncovers the multidisciplinary nature of the research, with computer science, engineering, and earth and planetary sciences being the most prominent areas of study. Additionally, the study examines the geographic distribution of research, with China leading in terms of the number of publications. The findings underscore the global participation and collaboration in using drones for flood prevention and management. The analysis of document types reveals that articles and conference papers are the primary means of sharing knowledge in this field. Furthermore, the study identifies the major sponsors involved, indicating substantial financial support from various sources worldwide. Overall, this bibliometric analysis provides valuable insights into the current state of research on the use of drones in flood prediction, identifying knowledge gaps and areas requiring further attention. The results can guide researchers, professionals, and decision-makers in focusing their efforts on promising research avenues and more effective flood prediction and mitigation strategies.Ingeniero AmbientalPregradoapplication/pdfspaUniversidad Santo TomásPregrado de Ingeniería AmbientalFacultad de Ingeniería AmbientalAtribución-NoComercial-SinDerivadas 2.5 Colombiahttp://creativecommons.org/licenses/by-nc-nd/2.5/co/Abierto (Texto Completo)info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Análisis Bibliométrico Acerca del Uso de Drones para Análisis y Detección de Inundacionesbibliometric analysisdronesunmanned aerial vehicle (UAV)floodsfloods preventionfloods managementIngeniería AmbientalLiteratura CientíficaPublicaciones CientíficasDronesanálisis bibliométricodrones; vehículo aéreo no tripulado (UAV)inundacionesprevención de inundacionesmanejo de inundacionesTrabajo de Gradoinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_7a1finfo:eu-repo/semantics/bachelorThesisCRAI-USTA BogotáAlbort-Morant, G., & Ribeiro-Soriano, D. 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Organizational Research Methods, 18(3), 429–472. https://doi.org/10.1177/1094428114562629ORIGINAL2023ArleyCardenas.pdf2023ArleyCardenas.pdfTrabajo de gradoapplication/pdf848622https://repository.usta.edu.co/bitstream/11634/52559/1/2023ArleyCardenas.pdfa22996ed923c573b135f8ef6f286eb5aMD51open accessCarta_aprobacion_facultad_2021 - CARDENAS RODRIGUEZ ARLEY GIOVANNI.pdfCarta_aprobacion_facultad_2021 - CARDENAS RODRIGUEZ ARLEY GIOVANNI.pdfCarta aprobación de la facultadapplication/pdf1153942https://repository.usta.edu.co/bitstream/11634/52559/2/Carta_aprobacion_facultad_2021%20-%20CARDENAS%20RODRIGUEZ%20ARLEY%20GIOVANNI.pdf5f8a04ec2e50d8927cf53c3a99b9c6e1MD52metadata only access1Carta_autorizacion_autoarchivo_autor_2021.pdf1Carta_autorizacion_autoarchivo_autor_2021.pdfCarta Derechos de autorapplication/pdf922569https://repository.usta.edu.co/bitstream/11634/52559/3/1Carta_autorizacion_autoarchivo_autor_2021.pdfa35867793ace721b01e4719aefe55b5eMD53metadata only accessCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8811https://repository.usta.edu.co/bitstream/11634/52559/4/license_rdf217700a34da79ed616c2feb68d4c5e06MD54open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-8807https://repository.usta.edu.co/bitstream/11634/52559/5/license.txtaedeaf396fcd827b537c73d23464fc27MD55open accessTHUMBNAIL2023ArleyCardenas.pdf.jpg2023ArleyCardenas.pdf.jpgIM Thumbnailimage/jpeg8576https://repository.usta.edu.co/bitstream/11634/52559/6/2023ArleyCardenas.pdf.jpg64d98d50baa4a6e0940be3b6d49399abMD56open accessCarta_aprobacion_facultad_2021 - CARDENAS RODRIGUEZ ARLEY GIOVANNI.pdf.jpgCarta_aprobacion_facultad_2021 - CARDENAS RODRIGUEZ ARLEY GIOVANNI.pdf.jpgIM Thumbnailimage/jpeg6770https://repository.usta.edu.co/bitstream/11634/52559/7/Carta_aprobacion_facultad_2021%20-%20CARDENAS%20RODRIGUEZ%20ARLEY%20GIOVANNI.pdf.jpg45bd3fe9ab7a625263e0d0d9b8cc1861MD57open access1Carta_autorizacion_autoarchivo_autor_2021.pdf.jpg1Carta_autorizacion_autoarchivo_autor_2021.pdf.jpgIM Thumbnailimage/jpeg7692https://repository.usta.edu.co/bitstream/11634/52559/8/1Carta_autorizacion_autoarchivo_autor_2021.pdf.jpg775c791ca38e92510108d4dbccad0d67MD58open access11634/52559oai:repository.usta.edu.co:11634/525592023-10-04 03:17:39.432open accessRepositorio Universidad Santo Tomásnoreply@usta.edu.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

Análisis Bibliométrico Acerca del Uso de Drones para Análisis y Detección de Inundaciones

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