Evaluation of the Influence of Aquatic Plants and Lake Bottom on the Remote-Sensing Reflectance of Optically Shallow Waters
Bibliographic record
Abstract
Aquatic plants and lake bottoms in optically shallow waters (OSWs) wield great influence on reflectance spectra, resulting in the inapplicability of most existing bio-optical models for water colour remote sensing in lakes. Based on radiative transfer theory and measured spectra from a campaign for Lake Taihu in October 2008, absorption and backscattering coefficients were used to simulate the remote-sensing reflectance, which are considered to be reliable if matched to their measured counterparts. Several cases of measured spectra at different depths, Secchi disk depth transparency, and aquatic plant height and coverage were analyzed thoroughly for spectral properties. The contribution of aquatic plants was evaluated and compared with the measured and simulated remote-sensing reflectance values. This is helpful for removing the influence of aquatic plants and lake bottoms from the spectra and for constructing an improved chlorophyll a retrieval model for OSWs, such as that for Lake Taihu, China.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".