| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Environmental Sciences | 444 | 46 | 50 | 11 |
| Computer Science | 521 | 37 | 41 | 11 |
The journal primarily focuses on research topics in Remote sensing, Artificial intelligence, Pattern recognition, Computer vision and Synthetic aperture radar. The journal explores issues in Remote sensing which can be linked to other research areas like Meteorology, Satellite, Moderate-resolution imaging spectroradiometer and Vegetation. The study on Satellite presented in the journal intersects with the topics under Climatology.
Presentations on Artificial intelligence include those discussing Hyperspectral imaging, Image (mathematics), Pixel, Convolutional neural network and Feature (computer vision). The journal investigates Hyperspectral imaging research which frequently intersects with Hyperspectral image classification. Remote Sensing Letters connects research in Pattern recognition with the related topic of Deep learning.
The most cited publications explore disciplines such as Remote sensing, Artificial intelligence, Pattern recognition, Satellite and Land cover. The published papers are focused mainly on Remote sensing, particularly Remote sensing (archaeology). In addition to Artificial intelligence research, the journal articles aim to explore topics under Data mining and Computer vision.
The main research concerns discussed in the journal are Remote sensing, Detector, Surface (mathematics), Meteorology and Tropical cyclone. Some problems in Remote sensing that were presented in it overlapped with concepts under Amazon basin and Gravity (chemistry).
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 Letters (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 Letters (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 2022 edition, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 16.67% were posted by at least one author from the top 10 institutions publishing in the journal. Another 16.67% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 16.67% of all publications and 50.00% 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.
Rui Cao;Qian Zhang;Jiasong Zhu;Qing Li
(2020)Preet Lal;Aniket Prakash;Amit Kumar;Prashant K. Srivastava
(2020)Peifeng Ma;Fan Zhang;Hui Lin
(2020)Costas A. Varotsos;Arthur P. Cracknell
(2020)Fan Zhang;Yingbing Liu;Yongsheng Zhou;Qiang Yin
(2020)Rui Qiao;Ali Ghodsi;Honggan Wu;Yuanfei Chang
(2020)Clemens Jänicke;Akpona Okujeni;Sam Cooper;Matthew Clark
(2020)Linbin Zhang;Chuyin Li;Lingjun Zhao;Boli Xiong
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