Internet-Based Spectral Database for Different Land Covers in Egypt
Bibliographic record
Abstract
The spectral signatures of natural objects in the visible and near-infrared spectral range are influenced by the object’s physical and biochemical properties. These signatures can be compiled in a database and used to retrieve information of land cover types and their physical composition from actual hyperspectral observations. This paper describes development process of hyperstectral database of reflectance from different land cover types in Egypt. It has been compiled from data obtained using a ground-based spectroradiometer system that covers the spectral range from 350 to 2500 nm at 1 nm resolution. The database is accessible through a website http://www.spectraldb.narss.sci.eg/spectral, where the system includes also metadata that describes the site environment and measurement processes. The system provides flexible mechanisms and friendly interfaces to allow accessing the database by the non-specialized people, whereas spectral data can be sorted by sites, species or selected environmental parameters. The system presents sample results from different vegetation and soil covers. Development of such a database is essential for different remote sensing applications, satellite’s calibrations, data dissemination and linkage with other databases for scientific researches purposes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".