Remote Sensing Acceptance Rate
Remote Sensing's acceptance rate in context, including how selective the journal really is and what the number leaves out.
Journal evaluation
Want the full picture on Remote Sensing?
See scope, selectivity, submission context, and what editors actually want before you decide whether Remote Sensing is realistic.
What Remote Sensing's acceptance rate means for your manuscript
Acceptance rate is one signal. Desk rejection rate, scope fit, and editorial speed shape the realistic path more than the headline number.
What the number tells you
- Remote Sensing accepts roughly ~50-60% of submissions, but desk rejection accounts for a disproportionate share of early returns.
- Scope misfit drives most desk rejections, not weak methodology.
- Papers that reach peer review face a higher bar: novelty and fit with editorial identity.
What the number does not tell you
- Whether your specific paper type (review, letter, brief communication) faces the same rate as full articles.
- How fast you will hear back — check time to first decision separately.
- What open access costs — ~$1,900-2,200 for gold OA.
Quick answer: Remote Sensing does not currently publish a simple live acceptance-rate figure in a form I could verify cleanly on its public stats page. What MDPI does publish is more useful for planning: 2024 impact factor 4.1, five-year JIF 4.8, CiteScore 8.6, a current rejection-rate-by-year chart, and about 24 days to first decision on current MDPI-facing material. The best official historical benchmark I could verify is MDPI's older 2013 disclosure showing 47% acceptance for that year, but that should be treated as history, not a live 2026 rate.
The Remote Sensing journal page is the best cluster reference if you want to compare the acceptance-rate question against impact factor, APC, review-time, and submission-fit context.
Remote Sensing acceptance-rate context at a glance
Metric | Current figure | Why it matters |
|---|---|---|
Current live official acceptance rate | Not cleanly published as text | No simple official 2026 percentage to quote responsibly |
Best official historical benchmark I could verify | 47% acceptance in 2013 | Directional history only, not a current live rate |
Current public stats page | Rejection-rate-by-year chart | Better current signal than recycled rumor percentages |
Impact factor (2024) | 4.1 | Real Q1 geosciences standing |
5-year impact factor | 4.8 | Longer citation durability than the short window alone |
CiteScore | 8.6 | Strong secondary visibility signal |
Time to first decision | About 24 days | Fast editorial intake for a broad-scope venue |
That is the honest answer surface. Remote Sensing is better understood as a fast, broad, high-volume remote-sensing journal with real filters, not as one fixed acceptance-rate number.
Longer-term metrics context
Year | Impact score trend |
|---|---|
2017 | 4.06 |
2018 | 4.66 |
2019 | 5.25 |
2020 | 5.32 |
2021 | 5.51 |
2022 | 5.39 |
2023 | 4.55 |
2024 | 4.67 |
The broader citation signal is up from 4.55 in 2023 to 4.67 in 2024, even though the journal is no longer in the peak-citation phase of the early 2020s. That means the venue still matters, but authors should read it as a durable broad-scope owner rather than a scarcity journal.
How Remote Sensing compares with nearby journals
Journal | Acceptance signal | IF (2024) | Best fit |
|---|---|---|---|
Remote Sensing | No clean current official text figure | 4.1 | Broad remote-sensing methods and applications |
Remote Sensing of Environment | No current official live rate | 11.1 | Stronger earth-system consequence and novelty |
ISPRS Journal of Photogrammetry and Remote Sensing | No current official live rate | 10.6 | More technical photogrammetry and methods ownership |
IEEE TGRS | No current official live rate | 7.5 | Stronger engineering and methods prestige |
GIScience & Remote Sensing | No current official live rate | 6.9 | Narrower geospatial and remote-sensing audience |
This is the main interpretation problem. Authors ask about acceptance rate when they are really deciding whether the paper belongs in a broad, fast, applied remote-sensing venue or a tighter, higher-consequence methods venue.
What the acceptance-rate question really means here
For Remote Sensing, the query usually stands in for:
Will this paper survive as a real remote-sensing contribution, or is it just a local application with weak transfer logic?
That is the question reviewers and editors actually care about.
What the current non-text acceptance-rate situation tells you indirectly:
- the journal is broad enough that many near-fit papers get submitted
- fast handling does not mean weak review
- broad-scope venues still punish thin benchmarking and local-only claims
What it does not tell you:
- whether the method beats current baselines fairly
- whether the result travels beyond one study area
- whether remote sensing is the actual contribution rather than the data source
What Remote Sensing editors and reviewers are actually screening for
The recurring screen at Remote Sensing is straightforward:
- is the contribution genuinely about remote sensing
- are the benchmarks and validation defensible
- would a broad remote-sensing reader learn something transferable from this paper
- are the claims honest about limitations and generalization
That is why certain papers fail consistently:
- local case studies with no broader transfer logic
- deep-learning or classification papers with thin benchmark comparisons
- application papers where remote sensing is only the data source, not the intellectual advance
Readiness check
See how your manuscript scores against Remote Sensing before you submit.
Run the scan with Remote Sensing as your target journal. Get a fit signal alongside the IF context.
What we see in pre-submission review work
In our pre-submission review work, the same problems keep surfacing.
The study is local but written as if it is general. A single region or dataset can still publish, but the paper has to explain the transfer boundary honestly.
The benchmarking is too thin. Papers often under-compare against current baselines, or compare under non-equivalent settings.
The contribution is not really remote sensing. If the manuscript would read almost the same with a different data source, the fit argument weakens quickly.
That is why the acceptance-rate discussion is secondary. The paper usually fails on transferability or validation, not on one hidden percentage.
The better submission question
For Remote Sensing, the better decision question is:
If a skeptical remote-sensing reviewer looked at the benchmarks, transfer claims, and reproducibility, would the paper still feel broad enough for this venue?
If yes, the journal is plausible. If no, a recycled acceptance-rate estimate will not fix the real issue.
Submit if / Think twice if
Submit if:
- the paper makes remote sensing central to the contribution
- the benchmarking is current, fair, and easy to audit
- the result has believable transfer value beyond one dataset or site
- the methods and reporting are reproducible enough for a broad reader
Think twice if:
- the manuscript is mainly a local case study
- the strongest claim depends on weak or incomplete validation
- remote sensing is only the data source rather than the actual advance
- the better home is a narrower methods journal or a stronger top-end venue
Practical verdict
The defensible answer is:
- Remote Sensing does not currently expose a simple live acceptance-rate figure I could verify cleanly
- MDPI does expose enough current journal statistics to show that the venue moves quickly and filters actively
- the real submission decision is about transfer value, benchmarking, and remote-sensing centrality, not a single percentage
If you want a reviewer-style read on whether the manuscript actually behaves like a solid Remote Sensing submission before upload, a Remote Sensing submission readiness check is the best next step.
Frequently asked questions
Not as a simple clean text figure I could verify on the current public stats page. MDPI currently exposes journal statistics, publication-time data, and a rejection-rate-by-year chart for Remote Sensing. The best official historical benchmark I could confirm is MDPI's 2013 disclosure showing about 47% acceptance that year, which should not be treated as a live 2026 rate.
Whether the paper has real transfer value, benchmark quality, and a contribution that is genuinely about remote sensing rather than just using remote-sensing data.
Remote Sensing currently reports a 2024 impact factor of 4.1, a five-year impact factor of 4.8, a 2024 CiteScore of 8.6, and about 24 days to first decision on current official MDPI-facing material.
Remote Sensing is a broad, fast, high-volume remote-sensing venue. Remote Sensing of Environment is a much tighter prestige and novelty screen. The latter expects stronger general consequence and stronger methodological or earth-system significance.
Submitting a local case study or a thinly benchmarked methods paper as if broad scope means lower standards. Reviewers still expect transferable conclusions and defensible validation.
Sources
Before you upload
Want the full picture on Remote Sensing?
Scope, selectivity, what editors want, common rejection reasons, and submission context, all in one place.
These pages attract evaluation intent more than upload-ready intent.
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Where to go next
Start here
Same journal, next question
- Is Remote Sensing a Good Journal? JIF, Scope & Fit Guide
- IEEE Transactions on Geoscience and Remote Sensing Submission Guide
- Remote Sensing Review Time: What Authors Can Actually Expect
- How to Avoid Desk Rejection at Remote Sensing in 2026
- Remote Sensing Impact Factor 2026: 4.1, Q1, Rank 47/258
- Is Your Paper Ready for Remote Sensing (MDPI)? An Honest Pre-Submission Checklist
Supporting reads
Want the full picture on Remote Sensing?
These pages attract evaluation intent more than upload-ready intent.