惊岚 2021-03-17

The previous one was written incorrectly, this system does not allow modifications, rewrite a new one.
First submission on June 5, 2020, rejected within three hours due to language issues.
After revising and polishing it on June 29, 2020, it was not rejected.
Received the first trial results on November 18, 2020, with a total of several major issues and a few minor ones.
Submitted the revised draft and response to comments for the first trial on February 3, 2021.
Received the acceptance notice on March 13, 2021, and the APC has been paid. Currently waiting for the final proofreading.

惊岚 2021-03-17

June 5, 2020, the first submission was rejected within three hours due to language issues.
After self-revision and polishing on June 29, 2020, it was not rejected.
On November 18, 2020, the first trial results came out, with several major workload issues and a few minor problems.
On February 13, 2021, the revised manuscript for the first trial was submitted along with response comments.
On March 13, 2021, the acceptance notice was received. Currently, the APC has been paid and awaiting the final version from the university.

Shank 2021-03-17

Submission 2021.01
First round of revisions 2021.02: Three reviewers, two accepted directly, one major revision (supplementing explanations of model parameters, adding a future outlook section to the paper, discussing a technical issue, recommending citation of another paper).
Accepted 2020.03
This work is more of an applied study and the submission process went relatively smoothly. It may be easier to review compared to model algorithms. It is evident that everyone's efficiency has increased from Christmas to the Lunar New Year, as the deadlines for several review invitations have become closer.

Shank 2021-03-14

The assessment still depends on the division. We all need to make a living, so we must first possess the "Four Uniques" before breaking them. Furthermore, to be honest, the average quality of TGRS is getting worse year by year.

兄弟萌，冲啊！ 2021-03-14

Posted in early December 2020
First round of minor revisions in mid-January 2021
Second round of minor revisions in mid-February 2021
Accepted in mid-March 2021
This article can be considered very lucky. Thank you to the editor and reviewers.
The expertise of the three reviewers is very high, and they are peers in the same field. Their comments were very insightful and greatly contributed to improving the quality of the article.
I hope to be able to publish future successful results in TGRS.

Feedbacks 2021-03-12

Journal classification is a problem of the Chinese Academy of Sciences based on impact factors and has nothing to do with TGRS. The classification itself has many problems. Peers who truly engage in academic research do not rely on journal classifications, and foreigners are also unaware of Chinese classifications. Those in the same field will know which is the best journal in their hearts, as well as where the best articles are published. However, students may find it difficult to strictly adhere to administrative classifications. On a side note, TGRS was far ahead in the remote sensing field 20 years ago because the older scientists at that time preferred to focus on formulas and theory.

Shank 2021-03-12

Submission in September 2020: I hesitated for a long time between submitting to ISPRS or TGRS (TGRS is really disappointing in terms of impact factor, Weng Qihao is awesome).

First major revision in December 2020: Three reviewers, all junior colleagues. Two reviewers suggested major revisions (5 comments each, similar suggestions to simplify formula derivation and increase textual explanations (there were too many complex formulas in the original manuscript), provide additional explanations and discussions on parameters, modify image fonts, and two positive evaluations). One reviewer suggested minor revisions (modify chart fonts and correct some symbol errors). The associate editor gave a major revision without any additional comments.

Second minor revision in January 2021: Two reviewers accepted the manuscript with minor revisions (recommended citing papers, modifying color scheme in Figure 1).

Acceptance in February 2021: I can't help but complain about IEEE's final formatting, it's really ugly. I spent a long time aligning the long formulas in LaTeX, only to have the IEEE typesetting editor revert them back to the original.

The review process for this paper was relatively slow, taking almost 6 months from start to finish. It may be due to the lengthy nature of the manuscript (exceeding 6 pages) and the large number of formulas. The reviewers took a long time to review, but their comments were quite professional. The second revision caught me off guard and delayed the process for over a month.

After the acceptance of the paper, I received phone calls from the reviewers one after another, and surprisingly, they were all familiar junior colleagues... After all the trouble, do we really have to harm each other?

QLZ 2021-02-13

It's really interesting. Every once in a while, that person who criticizes deep learning and machine learning under a pseudonym comes here to read the comments. Then they crazily dislike comments that disagree with them and crazily like their own negative comments. They are like a piece of dog skin plaster. TGRS is really unlucky to encounter such a sour person. I guess they either had their manuscript rejected or their competitors published something there. With such a mindset, how can they possibly do good research? They should go see a psychologist. Also, even though you vent your dissatisfaction by crazily disliking this comment I received, it might be helpful for your mental state.

Elric 2021-01-12

2020.08 Submission;
2020.10 Major revision: One reviewer provided 4 comments, the other reviewer provided 8 comments, and they both reviewed the article meticulously;
2020.10 Response;
2020.12 Minor revision: One reviewer had no comments, the other reviewer provided 2 comments;
2020.01 Response;
2020.01 Acceptance.
It took a total of 5 months from submission to acceptance. The first major revision was the most challenging, with a total of 12 comments from both reviewers. It was necessary to address each comment and make changes to the methodology, experiments, and the article itself. However, the results were satisfactory. After the response, one reviewer unintentionally only made one small suggestion, as well as pointed out terminological issues. It is awkward that I forgot to thank these two anonymous reviewers in the acknowledgments, as they indeed provided many thoughtful questions. I wonder if it is possible to add acknowledgments after publication. = =!
In the end, I wish everyone's articles to be accepted!

Feedbacks 2021-01-09

I personally think that a certain individual who constantly changes accounts is too extreme. They always focus on papers related to deep learning and machine learning. To be honest, 99% of people in the remote sensing field use ready-made methods for machine learning and deep learning. There are just too many. If you say that deep learning and machine learning are not important in the field of remote sensing, there are plenty of papers in journals such as RSE (Remote Sensing of Environment), AFM (Agricultural and Forest Meteorology), JGR (Journal of Geophysical Research), and ESSD (Earth System Science Data) that utilize deep learning and machine learning for remote sensing products and algorithms. Just search and you will find out. In other words, this is how the remote sensing community operates. TGRS (IEEE Transactions on Geoscience and Remote Sensing) is relatively strict in this regard. For example, I know a prominent figure who is a deputy editor of TGRS, and he said that they usually reject papers related to machine learning without even sending them for review. This is related to the attitude of the editors towards the manuscripts. TGRS has a high reputation in the industry, especially in the hearts of smaller peers, because of the publication of milestone papers on electromagnetic scattering and emission models, remote sensing mechanisms, SAR imaging algorithms, and commercialized physical algorithms for products. The quality of a journal should be judged based on how many milestone papers it has, not by focusing on marginal topics and the lower limits of papers. Also, one should not easily draw extreme conclusions, as this is unfair to those who are genuinely working on remote sensing mechanisms. There are plenty of journals for applications, but for remote sensing models, one can rely on IEEE TGRS and its letters.

brickerrrr 2021-01-08

TGRS is becoming increasingly mediocre now, even for deep learning stuff. The articles from the previous years can at most be considered as borrowing ideas from the computer vision field. They would at least make some changes and provide suggestions for improvement, adding their own elements. But now, many articles are simply copied without any modifications. I don't have the audacity to do that. Although I have two articles on hand, I won't submit them to TGRS in the future. Moreover, I have observed that many experts in the field no longer submit to TGRS either; they have switched to TIP or TNNLS. TGRS is now almost on the same level as ISPRS, which it used to look down upon. If TGRS still can't surpass ISPRS, its only advantage will be its CCF-B certification.