---
title: "Remote sensing benchmarks datasets"
description: "Datasets in the category “Remote sensing benchmarks” were mentioned in 8 papers in the last 30 days (2026-09-27 to 2026-10-26), ranking #38 of the 58 data categories mentioned."
url: https://scholar4ai.com/datasets/remote-sensing-benchmarks
markdown_url: https://scholar4ai.com/datasets/remote-sensing-benchmarks.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "Datasets in the category “Remote sensing benchmarks” were mentioned in 8 papers in the last 30 days (2026-09-27 to 2026-10-26), ranking #38 of the 58 data categories mentioned."
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-10-26T14:52:47+09:00
window: 2026-09-27 to 2026-10-26
source: OpenAlex (CC0)
---

# Remote sensing benchmarks

Hyperspectral and aerial image collections used to compare classification and detection methods.

- 1 papers in the last 7 days
- 5 of its 6 datasets mentioned

Back to the ranking: https://scholar4ai.com/rankings/datasets.md

## Key findings

- Datasets in the category “Remote sensing benchmarks” were mentioned in 8 papers in the last 30 days (2026-09-27 to 2026-10-26), ranking #38 of the 58 data categories mentioned.
- The most-mentioned were Salinas (3), Scene classification (NWPU-RESISC45, UC Merced, AID) (2), DOTA / xView (1), Houston 2013 / 2018 (1) and Pavia University / Pavia Centre (1).
- By journal category: AI (6), Management (1) and Operations Research (1).
- Most of them appeared in Pattern Recognition (1), Neural Networks (1) and Neural Computing and Applications (1).

## Datasets

*Datasets in this category · 2026-09-27 – 2026-10-26 (30 days)*

| Dataset | Papers | Last 7 days | Names searched for |
|---|---:|---:|---|
| Salinas | 3 | 0 | Salinas scene, Salinas dataset, Salinas Valley, Salinas-A |
| Scene classification (NWPU-RESISC45, UC Merced, AID) | 2 | 0 | NWPU-RESISC45, RESISC45, UC Merced Land Use, UCMerced, Aerial Image Dataset |
| DOTA / xView | 1 | 0 | DOTA dataset, DOTA-v1, xView, DOTA |
| Houston 2013 / 2018 | 1 | 1 | Houston 2013, Houston2013, Houston 2018, Houston2018 |
| Pavia University / Pavia Centre | 1 | 0 | Pavia University, Pavia Centre, Pavia Center |
| Indian Pines | 0 | 0 | Indian Pines |

## Papers

*Papers mentioning these datasets, newest first.*

| Date | Title | Journal | Authors | Affiliations | Datasets mentioned |
|---|---|---|---|---|---|
| 2026-10-23 | [MET-FR: Mamba-enhanced Transformer with feature rectification for hyperspectral and LiDAR data fusion and classification](https://doi.org/10.1016/j.patcog.2026.115204) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Yining Feng, Wei Cheng, Zhenhua Mu et al. | Dalian University; Liaoning Normal University | Houston 2013 / 2018 |
| 2026-10-01 | [Semantic-Spatial Synergy Feature Pyramid Network for Dense Tiny Object Detection from UAV Images](https://doi.org/10.1016/j.neunet.2026.109743) | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | Zeyuan Liu, He Huang, Kaibing Zhang et al. | Chang'an University; Xi'an Polytechnic University | DOTA / xView |
| 2026-10-01 | [HydraML: a hybrid damaged roofs automated machine learning classifier for cultural heritage](https://doi.org/10.1007/s00521-026-12499-w) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Francesco Colace, Massimo De Santo, Rosario Gaeta et al. | University of Salerno; Ministero della cultura | Scene classification (NWPU-RESISC45, UC Merced, AID) |
| 2026-10-01 | [How sustainability affects financial brand value: A decision matrix for CMOs and CFOs](https://doi.org/10.1016/j.emj.2026.09.004) | [European Management Journal](https://scholar4ai.com/journals/european-management-journal.md) | Gabriela Salinas, Carmen Abril | Universidad Pontificia Comillas; Universidad Complutense de Madrid | Salinas |
| 2026-10-01 | [Dynamic clustering for channel pruning guided by deep reinforcement learning](https://doi.org/10.1016/j.knosys.2026.117158) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | Boxiao Wang, Jin Qian, Dongdong Xu et al. | Chinese Academy of Sciences; Changchun Institute of Optics, Fine Mechanics and Physics; University of Chinese Academy of Sciences | Scene classification (NWPU-RESISC45, UC Merced, AID) |
| 2026-09-30 | [ASSMamba: Prototype-conditioned spectral routing and direction-aware state-space learning for hyperspectral image classification](https://doi.org/10.1016/j.eswa.2026.134589) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Lei Zhu, Yikai Su, Liang Dong et al. |  | Pavia University / Pavia Centre |
| 2026-09-28 | [Self-Organized Context Dependent Processing in Neural Networks](https://doi.org/10.1007/s12559-026-10624-4) | [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | Hao GuangFu, Yang Chen, Sainan Qin et al. | Chinese Academy of Sciences; Institute of Automation; University of Chinese Academy of Sciences; … | Salinas |
| 2026-09-28 | [Simulation-driven multi-objective optimization for charging-aware AMR navigation in dynamic manufacturing environments](https://doi.org/10.1016/j.cie.2026.112400) | [Computers & Industrial Engineering](https://scholar4ai.com/journals/computers-industrial-engineering.md) | Kotomichi Matsuno, Haoyu Liu, Kuo‐Yi Lin | Rissho University; University of Birmingham; Waseda University | Salinas |

## Cite this page

Scholar4AI. (2026). Remote sensing benchmarks. Journal Research Rankings. Retrieved October 26, 2026, from https://scholar4ai.com/datasets/remote-sensing-benchmarks

```bibtex
@misc{scholar4ai-datasets-remote-sensing-benchmarks,
  author = {{Scholar4AI}},
  title = {Remote sensing benchmarks},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/remote-sensing-benchmarks}},
  urldate = {2026-10-26},
  note = {Journal Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).