# Dataset audit: Mavic 3M optical rice disease screening

**Audit date:** 2026-08-04  
**Research status:** prospective engineering and validation study  
**Intended use:** bacterial-leaf-blight-suspect area screening through cross-sensor transfer to DJI Mavic 3M imagery  
**Excluded claim:** pathogen confirmation, food-safety determination, pesticide prescription, or autonomous treatment

This audit covers only primary dataset records, original research articles and official equipment documentation. Search summaries, reposts and vendor marketing interpretations are not evidence.

## Decision summary

| Source | Rights decision | Scientific decision | Public-release decision |
|---|---|---|---|
| BLB UAV Dataset v3, Figshare | CC BY 4.0 verified | Core disease-specific training/reproduction source | May redistribute an attributed subset or derived material within license conditions; prefer DOI-linked retrieval plus manifest |
| GD-RGBMS-DB, Zenodo | **License field blank** as checked | Mavic 3M pipeline-compatibility candidate only | Do not redistribute, train release-bound weights, or incorporate into a public bundle until written rights are clarified |
| NCHU rice nematode UAV dataset | Record-specific page provides no usable license; platform terms are restrictive | Optional Taiwan/Mavic 3M comparison only after approval | Do not download into a public workspace, redistribute, modify, use commercially, or expose through model weights without written permission |
| Mendeley proximal brown-spot dataset | CC BY 4.0 verified | Optional spectral/lesion pretraining; not aerial validation | May be used with attribution, but scale and geometry must remain disclosed |
| PLOS sheath-blight supporting package | CC BY 4.0 verified | Literature/reanalysis support, not a complete segmentation corpus | May be used with attribution; preserve individual file provenance |

## Core dataset audit: BLB UAV Dataset v3

- Primary record: <https://doi.org/10.6084/m9.figshare.26955862>
- License shown by the repository: Creative Commons Attribution 4.0 International.
- Sensor: DJI Phantom 4 Multispectral, not DJI Mavic 3M.
- Semantic classes: healthy rice, low BLB severity, high BLB severity and other/background.
- Total record count: **11,144 files**.
  - D1, D2 and D3 each contain 1,299 training images and matching masks, 277 validation images and matching masks, and 281 test images and matching masks.
  - This is 3,714 image/mask files per dataset variant, or 11,142 paired image/mask files across D1/D2/D3, plus two supporting files.
- D1 uses the five available P4M bands; D2 adds NDVI; D3 adds NDRE. The deployment-aligned experiment must exclude P4M Blue and use only the common G/R/RE/NIR bands plus indices recomputed from calibrated common bands.

### Split-integrity finding

The authors describe creating 256 × 256 patches with 128-pixel overlap and subsequently assigning patches to 70% training, 15% validation and 15% testing. The released record does not provide field/date grouping metadata adequate for an independent grouped split.

Because neighboring overlapping patches can contain repeated or highly autocorrelated ground content, a random post-patching split **may** place near-duplicate spatial content in more than one subset. This is a methodological concern inferred from the documented workflow, not an accusation of misconduct and not proof that a particular test pair is duplicated. Consequently:

1. Published split results are treated as within-record reproduction only.
2. They are not described as cross-field, cross-year, Taiwan or Mavic 3M generalization.
3. If source coordinates cannot be recovered, the project will report this unresolved limitation rather than invent group labels.
4. New local data must be split by complete field/date/orthomosaic before patch extraction.

## Mavic 3M compatibility candidate: GD-RGBMS-DB

- Primary record: <https://doi.org/10.5281/zenodo.17008818>
- The record describes co-aligned Mavic 3M RGB and multispectral imagery with segmentation masks.
- The record's **License field was blank on 2026-08-04**. Public accessibility and DOI assignment do not independently grant copying, model-training, redistribution or derivative-weight rights.
- Until the depositor or repository record supplies an explicit license:
  - retain only bibliographic metadata and a file-manifest/checksum reference;
  - do not add the archive to Git, website static files or a public reproducibility package;
  - do not use it to train any weights intended for publication or commercial deployment;
  - do not describe it as CC BY 4.0.
- Even if rights are later clarified, grain discoloration is a visible symptom complex rather than pathogen-specific BLB ground truth. It can validate Mavic 3M input handling and co-registration, not BLB diagnostic validity.

## Taiwan candidate: NCHU rice nematode imagery

The NCHU record is useful because it concerns a Taiwan rice field and Mavic 3M acquisition. It concerns white-tip/nematode symptoms, not BLB. Its resource page states that no usable license is available, while platform conditions restrict purposes and redistribution. The strict, record-specific interpretation is applied. Written approval must specify download, transformation, model training, weight publication, commercial use and redistribution separately.

## Sensor and task compatibility

| Difference | Consequence | Control |
|---|---|---|
| P4M NIR center differs from M3M NIR center (840 versus 860 nm); common bands also remain separate camera domains | Spectral distributions and index thresholds can shift | Train on common band names, calibrate reflectance, measure target-field distributions, and fine-tune on consented M3M labels |
| Thailand artificial/inoculated or study-managed disease versus Taiwan natural field conditions | Background, cultivar, severity and confounders differ | Independent Taiwan field/date holdout with expert confirmation |
| Orthomosaic patching and overlap | Inflated effective sample size and possible spatial leakage | Group before patching; confidence intervals by field/plot rather than pixel |
| Healthy versus low/high BLB labels | Severity boundaries may not transfer | Document annotation rubric and report ordinal as well as pixel metrics |
| Optical stress symptoms are nonspecific | Nutrient, water, weeds, shadow and senescence can resemble disease | Output “BLB-suspect / needs inspection”; include abstention and ground verification |

## Acquisition and release checks

Before any dataset is used, record:

- exact DOI/version and retrieval date;
- repository-displayed license plus a saved text or metadata snapshot of its wording;
- filename, size and SHA-256 checksum;
- sensor, bands, units, calibration state, site, date, altitude, ground sampling distance and annotation provenance where supplied;
- whether field/date/orthomosaic group identifiers exist;
- whether the license permits download, transformation, redistribution, commercial use and weight publication;
- whether files contain people, vehicle plates, precise private-field coordinates or other identifying information.

No source archive, copied website HTML, screenshot, personal information or unlicensed third-party material is to be placed under the website static directory. Public releases contain only authorized source subsets, original code, original figures, citations and non-identifying derived metrics.

## Unresolved items

1. Obtain explicit rights clarification from the GD-RGBMS-DB depositor before training or redistributing any content or weights derived from it.
2. Obtain separate written NCHU permission if that Taiwan dataset is pursued; a generic registration or click-through is not sufficient for public/commercial reuse.
3. Determine whether original BLB orthomosaic identifiers or coordinates can be obtained from the authors for a genuine grouped re-split.
4. A Taiwan Mavic 3M BLB dataset with a clear redistributable license was not identified; prospective collection remains necessary for deployment claims.
