| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Environmental Sciences | 21 | 1451 | 3575 | 82 |
| Computer Science | 37 | 631 | 1805 | 69 |
The journal generally zeroes in on subjects such as Remote sensing, Artificial intelligence, Satellite, Remote sensing (archaeology) and Meteorology. The research on Remote sensing featured in Remote Sensing combines topics in other fields like Pixel and Vegetation. Normalized Difference Vegetation Index is a major topic of Vegetation research presented in the journal.
While work presented in the journal provided substantial information on Artificial intelligence, it also covered topics in Machine learning, Computer vision and Pattern recognition.
The journal articles investigate areas of study like Remote sensing, Artificial intelligence, Vegetation, Normalized Difference Vegetation Index and Land cover. The Remote sensing research presented in the published articles focuses mostly on Satellite and, on occasion, topics in Meteorology. The published articles focus on Artificial intelligence but the discussions also offer insight into other areas such as Machine learning, Computer vision and Pattern recognition.
The main research concerns discussed in Remote Sensing are Remote sensing, Artificial intelligence, Remote sensing (archaeology), Satellite and Pattern recognition. Lidar, Hyperspectral imaging and Multispectral image are all areas of Remote sensing tackled in Remote Sensing. In the journal, Machine learning and Computer vision are investigated in conjunction with one another to address concerns in Artificial intelligence research.
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 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 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, 94.20% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 18.30% were posted by at least one author from the top 10 institutions publishing in the journal. Another 6.38% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 14.89% of all publications and 60.43% 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.
Hao Chen;Zhenwei Shi
(2020)Carlos M. Souza;Julia Z. Shimbo;Marcos R. Rosa;Leandro L. Parente
(2020)Rajendra P. Sishodia;Ram L. Ray;Sudhir K. Singh
(2020)Bing Lu;Phuong D. Dao;Jiangui Liu;Yuhong He
(2020)Marcel Buchhorn;Myroslava Lesiv;Nandin Erdene Tsendbazar;Martin Herold
(2020)Darius Phiri;Matamyo Simwanda;Serajis Salekin;Vincent R. Nyirenda
(2020)Sofia L. Ermida;Patrícia Soares;Vasco Mantas;Frank M. Göttsche
(2020)Wenzhong Shi;Min Zhang;Min Zhang;Rui Zhang;Shanxiong Chen;Shanxiong Chen
(2020)Simon Good;Emma Fiedler;Chongyuan Mao;Matthew J. Martin
(2020)Christopher D. Elvidge;Mikhail N. Zhizhin;Tilottama Ghosh;Feng-Chi Hsu
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