| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Environmental Sciences | 207 | 176 | 211 | 23 |
| Computer Science | 302 | 107 | 155 | 19 |
The objective of the journal is to combine knowledge in the areas of Remote sensing, Remote sensing (archaeology), Satellite, Meteorology and Vegetation. International Journal of Remote Sensing facilitates discussions on Remote sensing that incorporate concepts from other fields like Cartography and Pixel. The study on Cartography presented is investigated in conjunction with research in Land cover.
The Land cover study featured falls within the larger field of Land use. International Journal of Remote Sensing features research on Pixel in an attempt to reinforce studies in the field of Artificial intelligence. Discussions in it are anchored in the subject of Satellite and the similar topic of Climatology.
Vegetation research presented is mostly focused on the subject of Normalized Difference Vegetation Index. The work on Synthetic aperture radar addressed in it expands to the thematically related Radar. The journal focuses on Radiometry as well as the interrelated topic of Advanced very-high-resolution radiometer.
The journal articles mostly deal with topics like Remote sensing, Vegetation, Thematic Mapper, Cartography and Normalized Difference Vegetation Index. The journal publications are mostly focused on Remote sensing, specifically Remote sensing (archaeology). The studies on Vegetation discussed at the published articles can also contribute to research in the domains of Hydrology, Biomass (ecology), Satellite imagery and Physical geography.
The concepts of Remote sensing, Remote sensing (archaeology), Artificial intelligence, Satellite and Hyperspectral imaging are tackled in the journal. Land cover, Image (mathematics) and Cloud computing are some topics wherein Remote sensing research discussed in it have an impact. International Journal of Remote Sensing holds forums on Artificial intelligence that merges themes from other disciplines such as Computer vision and Pattern recognition.
International Journal of Remote Sensing explores research in Pattern recognition and the adjacent study of Hyperspectral image classification.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in International Journal of Remote Sensing (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in International Journal of Remote Sensing (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 4.17% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 15.86% were posted by at least one author from the top 10 institutions publishing in the journal. Another 3.84% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 10.23% of all publications and 70.08% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Pedzisai Kowe;Onisimo Mutanga;Timothy Dube
(2021)Guoqing Zhou;Guoqing Zhou;Xiang Zhou;Xiang Zhou;Youjian Song;Donghui Xie
(2021)Srishti Gaur;Ateeksha Mittal;Arnab Bandyopadhyay;Ian Holman
(2020)Ya Zhang;Zhenfeng Shao
(2021)Sajad Jamshidi;Shahrokh Zand-Parsa;Dev Niyogi
(2021)Lisa Caturegli;Monica Gaetani;Marco Volterrani;Simone Magni
(2020)Volkan Yilmaz;Cigdem Serifoglu Yilmaz;Oguz Güngör;Jie Shan
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