Text mining in remotely sensed phenology studies. A review on research development, main topics, and emerging issues
As an interdisciplinary field of research, phenology is developing rapidly, and the contents of phenological research have become increasingly abundant. In addition, the potentiality of remote sensing technologies has largely contributed to the growth and complexity of this discipline, in terms of t...
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Online Access: | http://hdl.handle.net/11573/1362974 https://doi.org/10.3390/rs11232751 |
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ftunivromairis:oai:iris.uniroma1.it:11573/1362974 2024-02-11T10:01:43+01:00 Text mining in remotely sensed phenology studies. A review on research development, main topics, and emerging issues Bajocco, Sofia Raparelli, Elisabetta Teofili, Tommaso Bascietto, Marco Ricotta, Carlo Bajocco, Sofia Raparelli, Elisabetta Teofili, Tommaso Bascietto, Marco Ricotta, Carlo 2019 http://hdl.handle.net/11573/1362974 https://doi.org/10.3390/rs11232751 eng eng MDPI place:Basel info:eu-repo/semantics/altIdentifier/wos/WOS:000508382100032 volume:11 numberofpages:23 journal:REMOTE SENSING http://hdl.handle.net/11573/1362974 doi:10.3390/rs11232751 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85076558347 info:eu-repo/semantics/openAccess bibliometric analysi land surface phenology network analysi research topic scientific mapping info:eu-repo/semantics/article 2019 ftunivromairis https://doi.org/10.3390/rs11232751 2024-01-17T18:05:14Z As an interdisciplinary field of research, phenology is developing rapidly, and the contents of phenological research have become increasingly abundant. In addition, the potentiality of remote sensing technologies has largely contributed to the growth and complexity of this discipline, in terms of the scale of analysis, techniques of data processing, and a variety of topics. As a consequence, it is increasingly di°cult for scientists to get a clear picture of remotely sensed phenology (rs+pheno) research. Bibliometric analysis is increasingly used for the study of a discipline and its conceptual dynamics. This review analyzed the last 40 years (1979-2018) of publications in the rs+pheno field retrieved from the Scopus database; such publications were investigated by means of a text mining approach, both in terms of bibliographic and text data. Results demonstrated that rs+pheno research is exponentially growing through time; however, it is primarily considered a subset of remote sensing science rather than a branch of phenology. In this framework, in the last decade, agriculture is becoming more and more a standalone science in rs+pheno research, independently from other related topics, e.g., classification. On the contrary, forestry struggles to gain its thematic role in rs+pheno studies and remains strictly connected with climate change issues. Classification and mapping represent the major rs+pheno topic, together with the extraction and the analysis of phenological metrics, like the start of the growing season. To the contrary, forest ecophysiology, in terms of ecosystem respiration and net ecosystem exchange, results as the most relevant new topic, together with the use of the red edge band and SAR (Synthetic Aperture Radar) data in rs+pheno agricultural studies. Some niche emerging rs+pheno topics may be recognized in the ocean and arctic investigations linked to phytoplankton blooming and ice cover dynamics. The findings of this study might be applicable for planning and managing remotely sensed phenology ... Article in Journal/Newspaper Arctic Climate change Phytoplankton Sapienza Università di Roma: CINECA IRIS Arctic Remote Sensing 11 23 2751 |
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Open Polar |
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Sapienza Università di Roma: CINECA IRIS |
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ftunivromairis |
language |
English |
topic |
bibliometric analysi land surface phenology network analysi research topic scientific mapping |
spellingShingle |
bibliometric analysi land surface phenology network analysi research topic scientific mapping Bajocco, Sofia Raparelli, Elisabetta Teofili, Tommaso Bascietto, Marco Ricotta, Carlo Text mining in remotely sensed phenology studies. A review on research development, main topics, and emerging issues |
topic_facet |
bibliometric analysi land surface phenology network analysi research topic scientific mapping |
description |
As an interdisciplinary field of research, phenology is developing rapidly, and the contents of phenological research have become increasingly abundant. In addition, the potentiality of remote sensing technologies has largely contributed to the growth and complexity of this discipline, in terms of the scale of analysis, techniques of data processing, and a variety of topics. As a consequence, it is increasingly di°cult for scientists to get a clear picture of remotely sensed phenology (rs+pheno) research. Bibliometric analysis is increasingly used for the study of a discipline and its conceptual dynamics. This review analyzed the last 40 years (1979-2018) of publications in the rs+pheno field retrieved from the Scopus database; such publications were investigated by means of a text mining approach, both in terms of bibliographic and text data. Results demonstrated that rs+pheno research is exponentially growing through time; however, it is primarily considered a subset of remote sensing science rather than a branch of phenology. In this framework, in the last decade, agriculture is becoming more and more a standalone science in rs+pheno research, independently from other related topics, e.g., classification. On the contrary, forestry struggles to gain its thematic role in rs+pheno studies and remains strictly connected with climate change issues. Classification and mapping represent the major rs+pheno topic, together with the extraction and the analysis of phenological metrics, like the start of the growing season. To the contrary, forest ecophysiology, in terms of ecosystem respiration and net ecosystem exchange, results as the most relevant new topic, together with the use of the red edge band and SAR (Synthetic Aperture Radar) data in rs+pheno agricultural studies. Some niche emerging rs+pheno topics may be recognized in the ocean and arctic investigations linked to phytoplankton blooming and ice cover dynamics. The findings of this study might be applicable for planning and managing remotely sensed phenology ... |
author2 |
Bajocco, Sofia Raparelli, Elisabetta Teofili, Tommaso Bascietto, Marco Ricotta, Carlo |
format |
Article in Journal/Newspaper |
author |
Bajocco, Sofia Raparelli, Elisabetta Teofili, Tommaso Bascietto, Marco Ricotta, Carlo |
author_facet |
Bajocco, Sofia Raparelli, Elisabetta Teofili, Tommaso Bascietto, Marco Ricotta, Carlo |
author_sort |
Bajocco, Sofia |
title |
Text mining in remotely sensed phenology studies. A review on research development, main topics, and emerging issues |
title_short |
Text mining in remotely sensed phenology studies. A review on research development, main topics, and emerging issues |
title_full |
Text mining in remotely sensed phenology studies. A review on research development, main topics, and emerging issues |
title_fullStr |
Text mining in remotely sensed phenology studies. A review on research development, main topics, and emerging issues |
title_full_unstemmed |
Text mining in remotely sensed phenology studies. A review on research development, main topics, and emerging issues |
title_sort |
text mining in remotely sensed phenology studies. a review on research development, main topics, and emerging issues |
publisher |
MDPI |
publishDate |
2019 |
url |
http://hdl.handle.net/11573/1362974 https://doi.org/10.3390/rs11232751 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change Phytoplankton |
genre_facet |
Arctic Climate change Phytoplankton |
op_relation |
info:eu-repo/semantics/altIdentifier/wos/WOS:000508382100032 volume:11 numberofpages:23 journal:REMOTE SENSING http://hdl.handle.net/11573/1362974 doi:10.3390/rs11232751 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85076558347 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.3390/rs11232751 |
container_title |
Remote Sensing |
container_volume |
11 |
container_issue |
23 |
container_start_page |
2751 |
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1790597516477071360 |