Remote Sensing Submission Process

This page is about workflow after you decide to submit.

Use it when you want to understand:

• what happens after upload

• how editors judge fit, validation, and broader relevance early

• what the early statuses are usually signaling

• where papers tend to stall before or after external review

If you still need help deciding whether the package itself is ready, that belongs on the submission-guide page.

The Remote Sensing submission process usually moves through four stages:

1. upload and file-completeness review

1. editorial screening for fit, validation, and scope

1. reviewer invitation and external review

1. first decision after editor synthesis

The decisive stage is number two. If the editor sees a paper that is too local, too weakly validated, or only incidentally related to remote sensing, the manuscript can stall before reviewers are central to the outcome.

That means the process is not only about portal compliance. It is about whether the manuscript already reads like a broad remote-sensing contribution.

Of the 100 papers our team reviewed when this guide was built, the most reusable Remote Sensing pattern was not a topic category. It was whether the paper made its sensor, validation, and transferability logic easy to audit before the application details took over.

Manusights review data points to the same failure pattern: strong local case studies often look weaker in the process when the title, abstract, and first validation figure do not show what another remote-sensing reader can reuse. We find that editors consistently screen for this before the paper reaches a full methodological debate.

The key process lesson is that Remote Sensing papers stall when the editor cannot quickly identify the transferable remote-sensing contribution. A strong local application is not enough unless the method, validation logic, or interpretation framework travels.

Source limitation: Manusights review patterns are anonymized and do not expose MDPI's private editorial notes. Use them as practical pre-submission signals, not as a guaranteed prediction of an individual decision.

The process goes better when the manuscript already behaves like a Remote Sensing paper before the portal opens:

• the remote-sensing contribution is central

• the validation is easy to trust

• the broader lesson is explicit

That is why the workflow question starts before upload.

The administrative layer is straightforward:

• manuscript upload

• author information and declarations

• figure and table files

• supplementary material

• cover letter

• suggested reviewers if the system requests them

For this journal, package quality still matters. A broad-scope journal does not mean a careless package is tolerated. If the validation details are hard to find, the figures are weakly labeled, or the cover letter never explains why the paper belongs in Remote Sensing, the editorial process starts from a worse place than it should.

The early stage is not just an admin check. Editors are effectively testing whether:

• the paper really belongs in remote sensing

• the validation is strong enough to justify reviewer time

• the broader lesson travels beyond one local case

• the package looks reproducible and professionally prepared

That is why a technically complete upload can still fail quickly.

If you are unsure whether the validation story is visible enough for that first screen, use the free readiness check before the MDPI upload rather than after a rapid editorial stop.

For manuscripts targeting Remote Sensing, three patterns generate the most consistent early-process friction. These are visible before MDPI SuSy upload in the abstract, cover letter, validation figures, benchmark table, error analysis, data statement, supplementary files, and references.

Local application result where the reusable Remote Sensing contribution stays secondary

For manuscripts targeting Remote Sensing, the most common failure mode is a strong local application that uses satellite, UAV, SAR, LiDAR, hyperspectral, or multispectral data well but never makes the reusable remote-sensing contribution the protagonist.

The abstract names a crop, city, watershed, forest, glacier, coast, or disaster setting; the figures show a convincing local result; the methods describe sensors and preprocessing; but the cover letter, validation figure, and discussion do not explain what another Remote Sensing reader can reuse.

The manuscript may belong in an environmental modeling, agriculture, hydrology, urban planning, ecology, or geospatial-engineering journal if the transferable contribution is the application insight rather than the sensing workflow. The fix is to make the sensor logic, feature design, atmospheric or geometric correction, scale transfer, uncertainty handling, and validation strategy visible in the abstract, first figure, methods, data statement, and cover letter.

Redirect targets when that cannot be done include Remote Sensing of Environment, ISPRS Journal of Photogrammetry and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, Environmental Modelling and Software, Computers and Electronics in Agriculture, and Science of the Total Environment.

Validation package present but not strong enough for the claimed transferability

For manuscripts targeting Remote Sensing, the second recurring pattern is a validation package that exists but does not support the manuscript's generality claim.

The benchmark table may include accuracy, F1, RMSE, IoU, spectral angle, or correlation metrics, yet the methods do not explain ground-truth quality, sensor harmonization, train-test leakage, temporal transfer, spatial holdout design, cloud or topographic effects, field-sampling limits, or uncertainty propagation.

Editors can see the problem quickly when the abstract promises generalizable mapping or monitoring but the validation figure only proves one season, one sensor, one geographic region, or one curated dataset. The manuscript components that need alignment are the abstract, validation map, benchmark table, error-analysis subsection, supplementary field-data description, code or data statement, and cover letter.

A Remote Sensing submission should make the limits of transfer honest while still proving a reusable method or interpretation framework. If the evidence is mainly algorithmic, IEEE TGRS or ISPRS may fit better; if it is mainly local environmental inference, an application journal may be cleaner.

Broad claims that outgrow the data, code, and supplementary package

For manuscripts targeting Remote Sensing, the third pattern is an overbroad claim paired with an underpowered reproducibility package.

The title and abstract promise operational monitoring, global transfer, near-real-time deployment, policy-ready mapping, or cross-sensor generalization, while the supplementary files do not provide enough data access, code description, parameter settings, sensor metadata, preprocessing detail, or error analysis for readers to inspect the claim.

This mismatch creates avoidable editorial risk because Remote Sensing publishes quickly and broadly, but still expects authors to make the sensing workflow auditable.

The practical fix is to narrow the claim or strengthen the package before submission: put sensor metadata and preprocessing choices in the methods, document field or reference data in supplementary files, connect every headline metric to a validation figure, name the code or repository status honestly, and use the cover letter to explain why the paper is a Remote Sensing contribution rather than a local case study.

Check whether your Remote Sensing manuscript is submission-ready →

1. Does the paper belong in remote sensing?

Editors want the remote-sensing contribution to be central. They are usually asking:

• is remote sensing the scientific core of the paper

• does the journal’s audience learn something reusable

• would this manuscript still make more sense in a narrower application journal

If remote sensing is only the data source rather than the contribution, the process becomes weaker quickly.

2. Is the validation strong enough?

Validation is one of the fastest screening questions in this journal. Editors want to see:

• fair baselines

• clear metrics

• enough error analysis

• realistic comparison logic

If the paper sounds broad but the benchmark logic is thin, the process usually slows immediately.

3. Is the takeaway broad enough?

Remote Sensing is more forgiving than a narrowly elite journal, but it still wants papers that travel beyond a single site or one isolated project. If the paper is only a local demonstration, it usually starts from a weaker editorial position.

This happens when the paper sits halfway between remote sensing, environmental modeling, agriculture, ecology, or engineering and never makes its main identity obvious. Reviewer routing becomes slower and editorial confidence drops.

Many papers technically include enough benchmarking but make the editor work too hard to see it. The process slows when the strongest comparisons and limitations are buried too deep.

Editors notice quickly when the abstract promises generalizable conclusions but the paper mainly supports a narrow case study.

Remote Sensing reports fast journal-level timing, but authors still misread quiet periods.

• early quiet usually means fit, validation, and transferability are being judged

• later quiet often means reviewer recruitment or debate over whether the broader lesson is real enough

• a rapid no usually means the package failed the journal-fit screen, not that the work had no value

The useful question is not just how many days have passed. It is what the paper is plausibly being evaluated for right now.

The title, abstract, and cover letter should make clear why this is a remote-sensing paper, not only a paper that happens to use remotely sensed data.

The strongest comparisons, error logic, and benchmark fairness need to be visible early. The process is much smoother when the validation is not only present but easy to audit on a first read.

The paper should tell editors what readers outside the study area can reuse:

• a workflow

• a benchmarking lesson

• a validation standard

• a reusable interpretation framework

That is what makes a broad journal route feel justified.

That is why the process can feel inconsistent from the outside. The journal is broad, but the editorial screen is still looking for clarity and transferable value.

If the paper would still read the same way with remote sensing replaced by another data source, the fit argument is probably not strong enough yet.

Before submission, ask:

• are the baselines fair

• are the metrics appropriate

• is the comparison with prior work explicit

• would a skeptical reviewer call the validation underpowered

Those are often the exact stress points that slow the process.

The editor should not have to infer what other readers can reuse. Put the transferable lesson in the abstract, introduction framing, and conclusion.

Before upload, the Remote Sensing package should feel easy to route:

• the title makes the remote-sensing contribution obvious

• the abstract says what readers can reuse

• the first validation figures are easy to audit

• the supplement clarifies methods and limits quickly

• the cover letter explains why the paper belongs in this journal rather than a narrower application venue

When those pieces align, the process usually becomes a real fit-and-review decision instead of a packaging problem.

One useful way to predict whether the editorial process will feel smooth is to ask what the first reviewer objections are likely to be.

For Remote Sensing, they are often:

• the baselines are incomplete or unfair

• the study is too local to support a broad claim

• the remote-sensing contribution is weaker than the application framing

• the error analysis is present but not decision-useful

If those concerns are still easy to imagine before you submit, the process is not really “ready” yet. The paper may still upload cleanly, but the route to first decision is much more likely to stall.

That is the practical advantage of doing a harsh pre-submit review yourself. It lets you convert likely reviewer objections into clearer framing, better comparisons, and a cleaner editorial first read before the journal has to do that work for you.

• Start with the Remote Sensing submission guide if you want the surrounding cluster in one place.

• Compare the journal profile on the Remote Sensing journal page.

• If you want a fuller pre-submit package check, start the Remote Sensing submission readiness check.

• If your bigger concern is early editorial rejection, read Desk Rejection: What It Means, Why It Happens, and What to Do Next.